The Skeletal Biology of Hibernating Woodchucks (Marmota Monax)

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THE SKELETAL BIOLOGY OF HIBERNATING WOODCHUCKS (MARMOTA MONAX)

A dissertation submitted to Kent State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy

Alison H. Doherty

May, 2013

Dissertation written by Alison H. Doherty B.A., University of Wyoming, 2003 M.A., Kent State University, 2007 Ph.D., Kent State University, 2013

Approved by

______, Chair, Doctoral Dissertation Committee Christopher J. Vinyard ______, Members, Doctoral Dissertation Committee William J. Landis ______, Walter E. Horton, Jr. ______, J.G.M Thewissen ______, Werner J. Geldenhuys

Accepted by

______, Chair, Department of Cell and Molecular Biology Robert V. Dorman ______, Dean, College of Arts and Sciences Raymond A. Craig

TABLE OF CONTENTS

LIST OF FIGURES ...... v

LIST OF TABLES ...... ix

ACKNOWLEDGEMENTS ...... xii

CHAPTER Page

1 INTRODUCTION ...... 1 Hibernation ...... 2 An Introduction to Skeletal Physiology ...... 17

2 BEHAVIORAL CHANGES IN THE LOCOMOTION OF WOODCHUCKS BEFORE AND AFTER HIBERNATION ...... 27 Introduction ...... 27 Materials and Methods...... 38 Results ...... 56 Discussion ...... 70

3 HIBERNATION DOES NOT REDUCE CORTICAL BONE DENSITY, AREA OR SECOND MOMENTS OF INTERIA IN WOODCHUCKS ...... 79 Introduction ...... 79 Materials and Methods...... 83 Results ...... 90 Discussion ...... 105

4 BONE DENSITY AND CROSS-SECTIONAL PROPERTIES IN ACTIVE AND HIBERNATING ADULT WOODCHUCKS ...... 114 Introduction ...... 114 Materials and Methods...... 118 Results ...... 132 Discussion ...... 139

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TABLE OF CONTENTS (Continued)

CHAPTER Page

5 THREE-POINT BENDING TESTS COMPARING BONE STRENGTH BEFORE AND AFTER HIBERNATION IN ADULT WOODCHUCKS ...... 146 Introduction ...... 146 Materials and Methods ...... 149 Results ...... 156 Discussion ...... 163

6 ANALYSES OF SEASONAL CHANGES IN BLOOD SERUM TO ASSESS BONE MAINTENANCE IN HIBERNATING AND ACTIVE WOODCHUCKS ...... 170 Introduction ...... 170 Materials and Methods...... 183 Results ...... 192 Discussion ...... 200

7 SUMMARY AND CONCLUSIONS ...... 212 Summary of the Skeletal Biology of Hibernating Woodchucks ...... 212 Bone Preservation of Hibernators and the Implications of this Work ..... 217 Future Clinical and Evolutionary Research ...... 220

REFERENCES ...... 224

LIST OF FIGURES

Figure Page

1.1 The woodchuck (Marmota monax) in its active state and hibernating...... 4

1.2 Intraperitoneal temperature of a woodchuck (M8) during the hibernation season 2009-2010 ...... 4

1.3 A sagittal view of a woodchuck in September of the prehibernation season in 2009 and again in April of the posthibernation season in 2010 ...... 8

1.4 Wild woodchuck (CR8) implanted with an intraperitoneal body temperature logger and maximum daily ambient temperature in 2009-2010 ...... 11

1.5 A woodchuck burrow temperature compared to outside air temperature during the hibernation season of 2011-2012 ...... 13

1.6 Pattern of bone loss/maintenance in non-hibernating and hibernating animals during extensive inactivity ...... 15

2.1 Gait diagram of a woodchuck trotting...... 29

2.2 The symmetrical and asymmetrical gaits used by woodchucks with corresponding gait diagrams ...... 31

2.3 A locomotion trial and the resulting data ...... 42

2.4 Computed tomography scans were taken of the diaphyses of the tibia, radius, and ulna approximating 50% of the length of the bone ...... 48

2.5 Lateral radiograph of a woodchuck’s forelimb demonstrating measurements collected for estimating stresses of the ulna at maximum vertical force ...... 50

LIST OF FIGURES (Continued)

Figure Page

2.6 Observed frequencies of symmetrical and asymmetrical gait types used by five individual woodchucks before and after hibernation ...... 58

2.7 The range of symmetrical and asymmetrical gaits of five woodchucks ...... 61

2.8 Speed did not differ significantly between seasons, but was significantly different between individual woodchucks by season ...... 63

2.9 Individual woodchuck fore and hindlimb duty factors were significantly different between seasons ...... 63

2.10 Maximum vertical force (FV) was significantly greater only in the forelimbs in the posthibernation season...... 66

2.11 Average compressive stress in the radius, ulna, and tibia of woodchucks was not dependent on season ...... 68

2.12 Both caudal and cranial bending strains in the tibia were significantly reduced in woodchucks following hibernation ...... 68

2.13 Seasonal average bending strains in the forearm of woodchucks ...... 69

3.1 QµCT scan locations for the long bones and mandibles of woodchucks ...... 85

3.2 Annual variation in cortical density and mandibular resistance to bending in woodchucks...... 92

3.3 Annual variation in metaphyseal trabecular densities and bone area fraction (B.Ar/T.Ar) in woodchucks...... 93

3.4 Relative diaphyseal cortical area and metaphyseal cortical density tended to be larger in each bone following hibernation ...... 96

LIST OF FIGURES (Continued)

Figure Page

3.5 Seasonal differences in diaphyseal cortical density between adult and subadult woodchucks ...... 98

4.1 Longitudinal computed tomography scoutview of the femur, tibia, and humerus ...... 125

4.2 Cortical density of tibial diaphyses significantly increased between all three seasons in a longitudinal study of captive, adult woodchucks ...... 134

4.3 There were no significant seasonal differences in cortical area or moments of inertia in the tibial diaphyses of captive, adult woodchucks ...... 135

4.4 Only whole bone density (BMD) of the femur was statistically greater between the posthibernation and summer season ...... 138

4.5 Trabecular BV/TV, thickness (Tb, Th) and number (Tb.N) of the femoral, tibial, and humeral metaphyses did not change significantly throughout the year in a cross-sectional study of adult woodchucks ...... 140

5.1 The universal testing machine (Instron ElectroPuls, E3000) used to break woodchuck bones in three-point bending ...... 152

5.2 The load-extension curve produced by a woodchuck femur in three- point bending ...... 154

5.3 The elastic modulus of the woodchuck femur was decreased significantly in the summer compared to prehibernation and posthibernation ...... 160

5.4 There were no other significant differences in the bending properties of the femur, humerus, or tibia ...... 162

6.1 Several of the mechanisms regulating bone formation and resorption processes...... 175

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LIST OF FIGURES (Continued)

Figure Page

6.2 Standardized serum analyte concentrations across three seasons in captive woodchucks ...... 195

6.3 Leptin peaked in the prehibernation season when body weight and food intake were at their highest ...... 196

6.4 Cross-correlations of serum analytes in captive woodchucks ...... 197

6.5 Females had higher density following hibernation than males in the tibial cortical density in wild woodchucks ...... 199

6.6 Calcium, ICTP, osteocalcin, and OPN increased significantly in the posthibernation season from prehibernation levels in wild woodchucks ...... 201

6.7 Alkaline phosphatase, OC, and OPN, increased in concentration significantly from the prehibernation to summer seasons in wild woodchucks ...... 203

7.1 Pattern of bone loss/maintenance in non-hibernating and hibernating animals during extensive inactivity ...... 216

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LIST OF TABLES

Table Page

1.1 Comparison of Captive and Wild Woodchuck Hibernation ...... 5

1.2 Ambient Temperatures (ºC) Experienced by Wild Woodchucks ...... 13

2.1 Gait Classification Definitions ...... 45

2.2 Summary Table of Woodchuck Kinetic Data and Variables ...... 49

2.3 Woodchuck Sample and Digitized Trials...... 55

2.4 Frequency of Symmetrical and Asymmetrical Woodchuck Gaits before and after Hibernation ...... 57

2.5 Frequency of Woodchuck Gait Type before and after Hibernation ...... 59

2.6 ANCOVA of Woodchuck Gait Components of Locomotion before and after Hibernation ...... 64

2.7 ANCOVA of Woodchuck Kinetic Components of Locomotion before and after Hibernation ...... 65

3.1 Woodchucks Skeletal Samples for Each Bone and Season ...... 84

3.2 Cross-sectional, Density and Mechanical Measurements...... 87

3.3 Two-way ANOVA Comparing Total Bone length Pre- and Posthibernation in Subadult and Adult Woodchucks ...... 89

3.4 Seasonal Measurements of Bone and ANOVA Comparisons across Hibernation Groupings for Diaphyseal and Mandibular Cortical Bone (Prehibernation and Posthibernation) ...... 91

3.5 Seasonal Measurements of Bone and ANOVA Comparisons across Hibernation Groupings for Metaphyseal cortical and Trabecular bone (Prehibernation and Posthibernation) ...... 94

LIST OF TABLES (Continued)

Table Page

3.6 Seasonal Measurements of Mechanical Properties of Bone and ANOVA Comparisons across Hibernation Groupings for Long Bone Diaphyses and Mandible (Prehibernation and Posthibernation) ...... 95

3.7 Seasonal Measurements of Mechanical Properties of Bone and ANOVA Comparisons across Hibernation Groupings for Long Bone Metaphyses (Prehibernation and Posthibernation) ...... 99

3.8 Significant Differences between Adults and Subadults Pre- and Posthibernation ...... 100

3.9 Seasonal Measurements of Adult Bone and ANOVA Comparisons across Hibernation Groupings for Diaphyseal and Mandibular Cortical Bone (Prehibernation and Posthibernation) ...... 101

3.10 Seasonal Measurements of Adult Bone and ANOVA Comparisons across Hibernation Groupings for Metaphyseal Cortical and Trabecular Bone (Prehibernation and Posthibernation) ...... 102

3.11 Seasonal Measurements of Mechanical Properties of Adult Bone and ANOVA Comparisons across Hibernation Groupings for Long Bone Diaphyses and Mandibles (Prehibernation and Posthibernation) ...... 108

3.12 Seasonal Measurements of Mechanical Properties of Adult Bone and ANOVA Comparisons across Hibernation Groupings for Long Bone Metaphyses ...... 109

3.13 Summary of the Influence of Hibernation on Bone in Various Mammals ...... 106

4.1 Cross-sectional Adult Woodchuck Sample ...... 120

4.2 Bone Cross-Sectional, Density and Mechanical Measurements ...... 127

4.3 Repeated Measures ANOVA of Tibial Cortical Properties in a Longitudinal Sample of Captive, Adult Woodchucks ...... 136

LIST OF TABLES (Continued)

Table Page

4.4 Whole Bone Density and Diaphyseal Properties of a Cross-Sectional Sample of Adult Woodchucks ...... 137

4.5 Metaphyseal Properties of a Cross-Sectional Sample of Adult Woodchucks ...... 141

5.1 Definitions and Calculations for Bone Mechanical Properties ...... 154

5.2 Adult Woodchuck Sample ...... 157

5.3 Sex Differences in Mechanical Properties of Woodchuck Bones ...... 158

5.4 Three-Point Bending Properties of Adult Woodchuck Bones ...... 161

6.1 Bone Serum Formation and Resorption Markers ...... 176

6.2 Adult Woodchuck Samples ...... 184

6.3 In-House ELISA Validation Tests ...... 189

6.4 Repeated Measures ANOVA of Average Serum Concentrations of Adult, Captive Woodchucks ...... 194

6.5 Time Series Analysis of Monthly Analyte Levels of Captive Woodchucks ...... 195

6.6 Univariate ANOVAs of Serum Concentrations from Adult, Wild Woodchucks ...... 201

ACKNOWLEDGMENTS

This project would not have been possible without the help and support of numerous people, both on and off the Northeast Ohio Medical University campus. My advisor, Chris Vinyard, deserves particular recognition in his contribution to my dissertation project. I am grateful to Chris for his willingness to take me on as a Ph.D graduate student and offer me this extraordinary opportunity. Not only did he encourage me to delve, head-first, into a project outside of his realm of research, but he continued to offer me the chance to participate in his own projects (both in the lab and in the field). For this I am especially grateful to have had the opportunity to experience and learn valuable techniques outside my particular project, and of significant interest to my overall goals as a student. Chris’ dedication to contributing to the greater good through education, honesty in scientific research, and commitment to pursue new avenues when others fail have left an indelible mark on my own teaching and research philosophy. In addition, I am grateful for his constant patience and infallible ability to repeatedly explain complex math formulae that I had the opportunity to explore with this project. I thoroughly enjoyed being a part of the

Vinyard lab.

I want to thank Dr. William Landis for his continued support throughout my graduate career, lab training, participation in various grants I applied for during this project, and serving on my dissertation committee. Dr. Landis taught me the

xii value of asking those tough questions to enhance the scientific validity of a project. His ability to identify the weak spots in a project encourages critical thinking, attention to detail, and reformulation of the research design to ultimately make the project stronger.

Dr. Walter Horton is thanked for contributing valuable insight and consultation on the project, introducing me to the research team at SUMMA and

NASA Glenn, and for participating in numerous grant applications. Dr. Horton also is thanked for serving on my dissertation committee. Dr. Hans Thewissen is acknowledged for providing sound scientific advice, voluntarily instructing me in comparative mammalian morphology, and serving on my dissertation committee.

I also thank Dr. Donald White for serving as my Graduate Representative on my committee and for editing the mathematical formulae presented in my dissertation.

Dr. Werner Geldenhuys and Dr. Richard Carroll, of Pharmaceutical

Sciences, are thanked for training me in protein analysis, specifically relating to

ELISA assays and Western blotting. In addition, I am grateful to Dr. Geldenhuys for helping with the collection of woodchucks and serving on my dissertation committee. Dr. Cornelis van der Schyf is thanked for allowing me to house my woodchucks in his Pharmaceutical Sciences Department’s walk in refrigerator each hibernation season. The project would not have been possible without the modification and use of that refrigeration unit and required the additional

xiii cooperation and sharing of the limited space in the Integrative Medical Sciences

Department, authorized by Dr. William Chilian, to accommodate the refrigeration needs of Pharmaceutical Sciences for the duration of the hibernation season every year. Furthermore, I would like to thank Dr. van der Schyf for acting as

Moderator on my committee.

I am particularly grateful to all of the people that helped me acquire the woodchucks from local properties for this study including Joe Pollock, Cindy

Fobes, Dallas Fobes, Tim Farwell, Diane Kehner, John Hughes, Mike Fobes, Mr. and Mrs. Lemon, Ruby Pahls, Joe Bocchicchio, John Ryznar, Mr. and Mrs.

Rhodes, Mr. and Mrs. Nash, Marie Docherty, Dr. Werner Geldenhuys, Dr. Jeff

Wenstrup, Dr. Colleen Novak, Dr. Brent Bruot, and Dr. Phil Westerman. Joe

Pollock deserves much of the trapping credit, as he single-handedly provided nearly half of the animals used in this study.

I am especially grateful to the technicians of the NEOMED Comparative

Medical Unit who were critical to the success of my research. Cindy Fobes, in particular, went above and beyond to help me acclimate the animals to a lab environment while ensuring their health and well-being, recognizing behavioral modifications that could be implicated, and communicating with me on a daily basis about the general maintenance of these animals. Cindy was an asset to the project and I value her opinion, assistance, and most of all, her friendship. I also thank John Ryznar for his assistance with animal care, surgical procedures,

xiv and contributing to my comparative skeletal collection. In addition, I am thankful for the help of Teresa Cooper, Greg Ferrar, John Gape, Ashley Justice, and

Linda McCort in working with these animals on a daily basis. Lora Nicholson and

Debbie Dutton are thanked for their assistance with all animal logistics and protocol questions—they were an absolute joy to work with. I am also grateful to

Dr. Walter Horne for establishing and training me in woodchuck surgical, radiography, intubation, and blood collection techniques that were integral to data collection and overall success of this research project.

The hibernation chamber was customized with the authorization of

Pharmaceutical Sciences and made possible by the help of numerous technicians in the NEOMED Physical Plant. Blaine Wyckoff, John Thomas, and

Jim Rankin are credited with helping to organize and plan modifications to the refrigeration unit in collaboration with Dr. Walter Horne. Special thanks to Ron

Pahls, Ron Wire, Skip Barnes, Nick Farkash, Everett Bender, Tim Patterson, Eric

McGaffick, Corey Robinson, George Mackey, Mechelle Gehle-Wann, and Ray

Wittensoldner for their mechanical and technical contributions to the project.

The broad scope of this research afforded me the opportunity to learn many techniques from and work with a variety of scientists. For this I am very grateful for the training and support I received from Sharon Usip, Robin Jacquet,

Denise McBurney, Beth Lowder, Jeanette Killius, Fouad Moussa, Dr. Samir

Abdelmagid, Dr. Fayez Safadi, Dr. Lisa Cooper, Dr. Jesse Young, Dr. Tobin

Hieronymus, and Dr. Brad Chadwell. I also thank those members of SUMMA and Robinson Memorial Hospital that contributed valuable input as well as provided services not available on NEOMED campus. In particular, I want to thank Karen Witter (RMH) and her team for processing woodchuck serum samples, as well as Michelle Evancho-Chapman and Donna Ferrante (SUMMA) for addressing all of our Sterrad requirements. I’m also grateful to Dr. William

Fallon, Cathy Tomala (RMH), and Larry Walker (RMH).

In addition, excellent administrative support, essential to the success of this project, and encouragement was provided by Debbie Heeter, Margaret

Weakland, Diane Kehner, Debbie Severt, Diana Dillon, Sheila Formick, Mary

Paisley, and Marie Docherty. The outstanding NEOMED library staff also deserves recognition, including Denise Cardon, Laura Colwell, Lisa Barker and

Heather McEwan, for assisting with my never-ending stream of ILL material.

My fellow graduate students, Jennifer Sensor, Summer Drake, Marie

Gadziola, Dr. Meghan Moran, Dr. Amy Mork, Dr. Brooke Armfield, Dr. Lisa

Cooper, Dr. Ashley Nugent, and Dr. Prahba Awale, are thanked for their collaboration and cooperation in KSU administration navigation, laboratory tips and tricks, and overall encouragement and backing.

Funding for this project was provided by a NEOMED Research Initiative

Grant, the Skeletal Biology Research Focus Area, the Department of Anatomy and Neurobiology, and the Society of Integrative and Comparative Biology.

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Special thanks to Dr. Walter Horton, Dr. Hans Thewissen, and Dr. Jeff Wenstrup for their continual support for this project. I am also grateful for the grant writing assistance I received from Dr. Christopher Vinyard, Dr. William Landis, Dr.

Walter Horton, Dr. Jeff Wenstrup, Dr. Brett Schofield, Dr. Kyle Nakamoto, and Dr.

Jeff Mellott. Furthermore, Charles Dardia, of the Cornell University Museum of

Vertebrates, is acknowledged for lending a substantial portion of the W. J.

Hamilton woodchuck collection to us to obtain the preliminary data that kick- started this project.

Finally, I would like to thank my wonderful family for supporting me in this amazing and difficult opportunity to further my education and follow my career goals. Words cannot express my gratitude for my husband, Adam Doherty, throughout this process. My parents, Bonnie and Phil Hofbauer, are also thanked and I continue to be inspired and driven by their overall life philosophy. I am grateful to Noreen Bowen, Skip and Konny Rosette, Linda and Steve Garcia,

Rob and Mary Weller, Lois and Dale Hoaks, and Gina Evans for their love, friendship, and support. I also thank Charles Doherty, Elizabeth Snyder, and

Jason Hoaks as truly inspirational and selfless individuals who contributed more than they know to the success of my graduate career.

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CHAPTER 1

INTRODUCTION

Long periods of inactivity in most mammals lead to significant bone loss that may not be completely recovered during an individual’s lifetime regardless of future activity (Aguirre et al., 2006; Bloomfield et al., 2002; Lang et al., 2004;

Sugiyama et al., 2002; Weiler et al., 2006; Zerwekh et al., 1998). Extended bouts of inactivity are the norm for hibernating mammals (Geiser, 1995; Grizzell,

1955; Johnson, 1931; Lyman et al., 1982; Rasmussen, 1916). It remains largely unknown, however, how these animals avoid adversely affecting bone, their quality, and ultimately survival given the challenges posed to their skeletons by inactivity and nutritional deprivation during hibernation. Hibernation likely represents a derived adaptation among mammals for surviving stressful environments (Kortner and Geiser, 2000; Liow et al., 2008; Lyman et al., 1982).

As such, hibernation provides a compelling natural experiment (Lemelin and

Schmitt, 2004; Nurnberger et al., 1994; Pearse and Welsch, 1968) for studying skeletal physiology at this extreme as it may represent a limit for inactivity, restricted food intake and reduced metabolism in mammals.

Hibernation

“Hibernation is best viewed as an adaptation to anticipated famine” (pg.

713, Boyer and Barnes, 1999). The major benefit of hibernation is conserving energy by lowering metabolic rate and body temperature (Tb), and thereby reducing heat loss when environments are stressful (Boyer and Barnes, 1999;

Geiser, 1995; 1998; Hock, 1960; Kortner and Geiser, 2000; Nedergaard and

Cannon, 1990; Twente and Twente, 1965). Hibernation is advantageous in seasonal periods of food and water shortages, extreme ambient temperatures

(Ta, both hot and cold), and is an effective predator avoidance strategy (Geiser and Turbill, 2009). Physiologically, it is a very successful trait and occurs in over

50% of mammalian orders including species of monotremes, marsupials, rodents, bats, shrews, insectivores, primates, and carnivores (Geiser, 2004a;

Geiser and Turbill, 2009). It varies, however, among species in terms of its utilization, duration, and extent of metabolic depression.

Characteristics of Hibernation

All hibernators exhibit a controlled reduction in metabolic rate, heart rate, and a decrease in body temperature (Geiser, 2004a; Hock, 1960). Some animals experience daily torpor (torpor being defined as a pronounced reduction in body metabolism and temperature; Boyer and Barnes, 1999; Geiser, 1995) as a strategy to conserve energy during the most environmentally challenging part of the day, whether it is during the cold of the night or dehydrating heat of the day. These animals are classified as daily heterotherms (Geiser, 2004a) or

facultative hibernators (Drew et al., 2007). The amount of time spent in daily torpor may fluctuate seasonally and/or with the reproductive cycle. During daily torpor, in comparison to seasonal hibernation, body temperature rarely drops below 10°C, arousal is immediate, and metabolic rate is relatively high (Geiser,

2004a). Daily heterotherms are capable of short torpor periods during certain times of the day or year and usually will not enter torpor when food is available.

An animal that experiences a long, annual hibernation season marked by profound episodes, or bouts, of torpor are considered to be prolonged (Geiser,

1995) or deep (Lyman et al., 1982) hibernators. Prolonged hibernators are entrained to the twelve-month cycle of the daily photoperiod, and thus they experience strong circadian and circannual rhythms. These animals will spontaneously hibernate in the presence of food and altered light cycles making them obligate hibernators (Drew et al., 2007; Morrison, 1960). Prolonged hibernators include several species of ground squirrels, marmots, hedgehogs, bats, and bears (Geiser, 1995). These hibernators were of particular interest to this study because of the length of time they remain inactive during hibernation.

Woodchucks, members of the genus Marmota, were used in this research as an example of an obligate hibernator (Fig. 1.1).

To understand the extent that hibernation affects the daily activity of an obligate hibernator, it is necessary to discuss the specific characteristics of this type of hibernation using the woodchuck hibernation cycle examined here as an example (Fig. 1.2). The hibernation season lasts for months at a time,

Fig. 1.1: The woodchuck (Marmota monax) in its active state (A) and hibernating (B). All animals adopt a sitting hibernation position with the nose placed at the base of the tail. Photographs: A) Used with permission from photographer Victor Lowen, B) New York State Archives, Hibernating woodchuck, December 1, 1897, Otsego County, New York. http://iarchives.nysed.gov/Gallery/galleryDetail.jsp?id=1092&ss=EDU.

Fig. 1.2: Intraperitoneal temperature of a woodchuck (M8) during the hibernation season 2009-2010. The animal hibernated for four months (mid-November through the end of March). Torpor bouts (up to 14 days) were interrupted by arousal bouts (lasting as little as 18 hours), as typically seen in obligate hibernators. The minimum body temperature of this animal was maintained at 7.5˚C. Ambient temperature of the hibernation chamber was held at 7˚ C.

depending on the species and latitude it inhabits (Zervanos et al., 2010).

Environments tending to have long, cold winters usually equate to a longer hibernation season to ensure the animal does not come above ground when conditions are still below optimal. The hibernation season is broken into alternating periods of torpor and arousal bouts (Fig. 1.2). In obligate hibernators, torpor bouts generally last between 96 and 1080 hours (Geiser, 1995).

Hibernating woodchucks in this study averaged about 186 hours per torpor bout with the maximum time spent in one torpor bout being 324 hours (or 13.5 days,

Table 1.1). During a torpor bout, heart rate reduces to 1/30 or less of an active animal (Wang, 1987). Woodchuck heart rates of this study were not only reduced, but they were also fainter and more irregularly timed with long periods between beats (personal observation). Long periods of apnea lasting over an hour have been reported in some animals, and basal metabolic rates in general

Table 1.1: Comparison of Captive and Wild Woodchuck Hibernation

Hibernation Average Maximum Average Minimum Season torpor torpor arousal arousal Average Minimum Average Sample (months) bout bout bout bout Tb (˚C) Tb (˚C) Ta (˚C) (hours) (hours) (hours) (hours)

Captive ~4 185.5 324.0 31.0 13.5 8.9 6.6 7.0 (N = 12) Wild ~4 197.3 294.0 50.5 46.0 7.4 5.0 5.2 (N = 1)

are reduced to 1-2% compared to active animals (Boyer and Barnes, 1999;

Geiser, 2004a; Wang, 1987). Body temperatures drop to nearly ambient temperatures, and as such, arctic ground squirrels have been recorded to obtain

core body temperatures as low as -2.9˚C without freezing (Boyer and Barnes,

1999; Lee and Costanzo, 1998). Contrary to what would be expected when handling live animals, hibernating individuals are cold to the touch and capable of only slow, feeble movements (Grizzell, 1955).

In nearly all hibernators, periods of torpor are interrupted by shorter episodes (usually less than 24 hours) called interbout intervals, or arousal bouts

(Fig. 1.2) (Geiser, 1995; Pengelley and Fisher, 1961). During arousal an animal comes out of a deep hibernation state within a couple of hours to return to normal active body temperature and metabolic rate (Wang, 1987). An animal may get up to drink water or urinate, but usually it will remain curled with its nose to its tail in the typical hibernation position (Fig. 1.1B). The periodic re-warming phase experienced by animals is very energetically costly, for instance requiring 40 to

76% of a ground squirrel’s winter energy store while environmental conditions remain unfavorable (Wang, 1979). Several hypotheses exist as to why arousals are so important, ranging from amelioration of sleep deprivation (Heller et al.,

1993) to maintenance of the immune system (Prendergast et al., 2002).

Particularly since arousal is so energetically expensive, and seemingly critical to nearly all obligate hibernators as a non-varying characteristic of hibernation, it remains a controversial subject sparking numerous hypotheses and research projects (Storey, 2010). Despite the reason, the alternating cycle of torpor and arousal bouts continues throughout the entire hibernation season until an animal arouses for the final time and remains euthermic (the

maintenance of normal mammalian body temperature; Buck and Barnes, 2000;

French, 1985; Geiser, 2007; Geiser et al., 1990).

Body Size and Hibernation

Successful hibernation tends to rely largely on body weight and the ability to conserve energy by reducing metabolic rate while controlling and maintaining a reduced body temperature as external temperatures fluctuate (Nedergaard and

Cannon, 1990). Animals become hyperphagic (a seasonal increase in food consumption) in late summer-early fall to gain sufficient fat mass to provide sufficient energy throughout hibernation. Woodchucks typically double their body weight in late August or early September and emerge from hibernation quite lean in comparison (Fig. 1.3; Davis, 1967a). Many obligate hibernators, like woodchucks, rely on this fat storage alone to survive the winter without feeding from food caches. Thus it is apparent that the reduction in basal metabolic rate during hibernation functions in part to diminish the energy requirements of an animal for an extended period of time. For example, it is estimated that ground squirrels experience an average energy savings of 96% over the course of the hibernation season compared to active animals (Wang, 1979). In addition, animals that have longer bouts of torpor with fewer arousal cycles conserve more energy (Nedergaard and Cannon, 1990).

The benefits of hibernation become less advantageous for larger animals

(e.g., bears). These animals are capable of remaining in a torpid state at higher body temperatures utilizing body fat reserves (Folk et al., 1972; Nedergaard and

Fig. 1.3: A sagittal view of a woodchuck in September of the prehibernation season in 2009 and again in April of the posthibernation season in 2010. The animal lost 46% of its body weight over the course of the hibernation period between the time of the two photographs. This body mass fluctuation is typical of hibernating animals. Limbs were shaved for viewing the joints.

Cannon, 1990). Interestingly, bears are the only animals considered to be prolonged hibernators that do not experience typical torpor and arousal bouts, but rather cyclic non-diurnal changes in their body temperature (which rarely goes below 30˚C) while capable of immediate arousal at low metabolic rates

(Tøien et al., 2011). Thus, larger animals (e.g., >10 kg) generally will not hibernate deeply because it is not metabolically advantageous to do so for extended periods (Geiser, 2004a; Geiser, 2004b; Geiser et al., 2008; Morrison,

1960; Nedergaard and Cannon, 1990).

Background on Woodchucks

Woodchucks (rodents of the order Sciuridae) tend to be the least social member of the genus Marmota and typically defend their home range from other woodchucks, although variability in their social organization has been described

(Hamilton, 1934; Maher, 2004). Their solitary behavior has been implicated in their courageous nature and tendency to turn and face adversaries (personal experience). They are disliked among property owners because of their adeptness at building expansive burrow networks close to buildings and are considered agricultural pests because of their voracious appetite for crops and garden produce alike. Furthermore, woodchucks tend to favor the border of forests with maintained fields, from which they introduce into inhabited areas a host of parasites and potential for disease, such as Lyme disease and rabies.

Violent interactions between conspecifics (of the same species) and heterospecifics (belonging to a different species), including repercussions to their

close proximity to humans, make them prone to injuries and infections. Nearly all animals obtained for this research were ridden with fleas, ticks, and had at least one abscess that required treatment. Age expectancy of wild woodchucks, therefore, ranges from 2 to 5 years, although animals in captivity have been reported to live over 14 years (personal communication with the Tennant

Laboratory at Cornell University).

Despite their repellent nature, woodchucks are good hibernators and of a manageable size for the laboratory (Young and Sims, 1979). Ranging from

Alaska to Alabama, animals at higher latitudes typically hibernate longer, with woodchucks in Maine averaging nearly 6 months hibernation annually compared to 2.5 months in South Carolina (Zervanos et al., 2010). They are also among the largest mammalian obligate hibernators capable of torpor bouts exceeding 96 hours in duration (Geiser, 1995; Lyman et al., 1982). In September of 2009 in this study, a young male woodchuck that had a particular fondness for the bait used in the traps was trapped and implanted with an intraperitoneal temperature logger (iButton, DS1921G, MAXIM). He was tagged and released in order to compare wild woodchuck body temperature during hibernation (Fig. 1.4) to that of the captive animals of this study (e.g. Fig.1.2, Table 1.1). Upon recapture of the wild woodchuck in April of 2010, it was determined that both wild and captive animals hibernated an average of about 4 months for the 2009-2010 hibernation season in Northeast Ohio, USA, entering hibernation in mid November or early

December. Entrance into hibernation was more abrupt in the wild animal (Fig.

1.4), whereas those held in the laboratory experienced a greater number of “test drops” at the beginning of the hibernation season as evident by the fluctuating body temperatures in November (Fig. 1.2). Average body temperature during torpor bouts was lower in the wild woodchuck (7.4˚C) compared to those held in captivity (8.9˚C, Table 1.1).

Fig. 1.4: Wild woodchuck (CR8) implanted with an intraperitoneal body temperature logger and maximum daily ambient temperature in 2009-2010. 1Temperature obtained from Rootstown, OH daily temperature history: http://www.wunderground.com/history/airport/KPOV/2012/1/25/DailyHistory.html.

Body temperature disparity between the wild and captive woodchucks is a result of the lower ambient temperatures experienced by the animal in the field.

Average ambient burrow temperature was 5.2˚C, or 1.8 degrees less than the captive animals held in a refrigerated room at 7.0˚C (Table 1.1). For comparison

to the controlled environment of the refrigerated room, burrow temperatures were examined in relation to outside air temperature over the course of one hibernation season in 2011-2012 (Fig. 1.5, Table 1.2). The burrow maintained a more stable ambient temperature and remained on average 1.5˚C warmer than outside (Table 1.2). Furthermore, the lowest outside air temperature reached -

15°C on January 20, 2012 whereas the burrow only declined to a minimum of

0.5˚C that same day. Clearly, the burrow affords quite a bit of thermal protection to the hibernating animal against the lowest ambient air temperatures, although wild animals do experience more fluctuation in the burrow than those in captivity, as would be expected.

Average torpor bout duration and length of maximum torpor bout were comparable in captive and wild woodchucks, with maximum time in torpor being greater in captive animals (324 hours) and average torpor bout duration being longer in the wild woodchuck (197.3 hours, Table 1.1). Arousal bout length was greater in the wild woodchuck (50.5 hours) compared to the captive animals

(31.0 hours). Termination of hibernation was similar in both groups when final arousal occurred in mid- to end of March. These data for both the wild and captive woodchucks are comparable to free ranging woodchucks investigated over eight hibernation seasons in Pennsylvania (Zervanos et al., 2009).

Fig. 1.5: A woodchuck burrow temperature compared to outside air temperature during the hibernation season of 2011-2012. Burrow temperature was obtained from a data logger placed 8 feet inside a woodchuck burrow on NEOMED campus. Outside air temperature was obtained from a data logger attached to a fence 5 feet off of the ground just outside the burrow.

Table 1.2: Ambient Temperatures (˚C) Experienced by Wild Woodchucks

Source Average Minimum Maximum Outside Air 3.7 -15.0 33.0 Burrow 5.2 0.5 26.0

Hibernation and the Skeleton

Previous work on skeletal physiology during hibernation has focused primarily on torpid bears demonstrating they maintain a balance between bone resorption and formation processes that prevents annual losses in bone (Fig. 1.6;

Donahue et al., 2006a; Donahue et al., 2006b; Donahue et al., 2003b; Floyd et al., 1990; Lennox and Goodship, 2008; McGee-Lawrence et al., 2008).

Unfortunately, bears present significant research challenges in terms of size, availability, and handling risks that limit procedures. Woodchucks are manageable, readily available, and hibernate with relative ease in captivity

(Young and Sims, 1979). Historical studies of small hibernators, such as hamsters (Steinberg et al., 1981), bats (Doty and Nunez, 1985), and some ground squirrels (Haller and Zimny, 1977), have reported bone loss in these animals during and immediately after hibernation based on histological studies

(Fig. 1.6). Recent research has found that at least some small rodent hibernators, particularly members of Marmota and Spermophilus (ground squirrels), are actually capable of maintaining net annual bone mass despite physical disuse associated with hibernation (Fig. 1.6; Doherty et al., 2012;

McGee-Lawrence et al., 2011; Utz et al., 2009; Wojda et al., 2012). The intention of this study was to investigate systematically the effects of inactivity on bone physiology across multiple levels of organization and organismal function to determine how bone remodeling processes are coordinated during hibernation in woodchucks.

Fig. 1.6: Pattern of bone loss/maintenance in non-hibernating and hibernating animals during extensive inactivity. Woodchucks are being investigated in this study to determine if they are able to maintain bone properties similar to other hibernators that do not lose significant bone throughout the year. “=” No net bone loss or gain; “▲” Bone increase; “▼” Bone decrease. ┼Frogs aestivate for up to nine months out of the year. *Bears are torpid for 4-5 months out of the year, but are comparatively more active than small hibernators during hibernation. 1Hudson et al., 2004. 2Donahue et al., 2006; Floyd et al., 1990; Harvey and Donahue, 2004; Harvey et al.; 2005; McGee et al., 2008; McGee et al., 2007; McGee-Lawrence et al., 2009; Donahue et al., 2006; Lennox and Goodship, 2008; McGee-Lawrence et al., 2008. 3Wojda et al., 2012. 4Utz et al., 2009; Haller and Zimny, 1977; McGee-Lawrence et al., 2011; Zimny et al., 1973; Zimmerman et al., 1976. 5Steinberg et al., 1981. 6Doty and Nunez, 1985; Nunez et al., 1969; Nunez et al., 1972; Kwiecinski et al., 1987.

Woodchucks are intermediate in body size (~3 - 7.5 kg) between bears

(92 – 780 kg) and several smaller hibernators (< 1 kg) including multiple rodent species (Buck and Barnes, 2000; Nowak, 1999; Tøien et al., 2011). Given this intermediate size as a relatively large rodent hibernator, woodchucks can help us understand potential size-related variation in bone physiology across hibernators.

Previous comparisons demonstrate that larger mammals maintain relatively greater skeletal mass (Christiansen, 2002; Prange et al., 1979; Schmidt-Nielsen,

1984) yet have reduced osteocyte density (Bromage et al., 2009; Mullender et al., 1996) and are capable of maintaining lower levels of circulating calcium per unit of body weight (Kjeld and Olafsson, 2008). It is possible that woodchucks are large enough to experience some size-related benefit in maintaining lower levels of circulating calcium per unit body weight while still being small enough to benefit from the metabolic advantages of prolonged hibernation.

Relative to prior work on bears, assessing how bone responds to hibernation in an obligate hibernator will result in one of two significant outcomes.

First, if woodchucks resemble bears in their mechanistic response to hibernation, this will point to a specific target that may be repeatedly manipulated in hibernating animals during evolution. Alternatively, if woodchucks deviate from bears in their mechanism(s) for maintaining bone, then the different process(es) point to plasticity in the physiological response of bone to hibernation. Either outcome of these comparisons will provide novel data adding significantly to our understanding of the physiological processes regulating bone density, area, and

performance in hibernating mammals (Donahue et al., 2006b; Lennox and

Goodship, 2008; McGee-Lawrence et al., 2008).

An Introduction to Skeletal Physiology

Bone is maintained in healthy adults by a balance between bone formation and resorption (Caetano-Lopes et al., 2007; Ducy et al., 2000b; Harada and

Rodan, 2003; Robling et al., 2006; Seeman, 2009; Teitelbaum, 2000). This remodeling process is a key mechanism for maintaining calcium (specifically

2+ Ca , abbreviated to Ca for simplicity throughout), inorganic phosphate (PI), and magnesium homeostasis in the skeleton (Berne et al., 2004; Seibel et al., 2006).

Remodeling is regulated by diet, exercise, as well as a host of hormones, cytokines, and growth factors (Borer, 2005; Guadalupe-Grau et al., 2009; Rizzoli,

2008; Rosen and Klibanski, 2009; Seeman, 2003; Seibel et al., 2006; Stransky and Rysava, 2009; Tucker, 2009; Winsloe et al., 2009).

Osteoclasts carry out the process of bone resorption. These cells destroy their surrounding bone matrix, and in the process extract and release essential minerals, such as Ca, into circulation. Bone formation, on the other hand, involves osteoblasts initiating the formation of new bone and sequestering Ca, PI, and other circulating ions during mineralization. Inactivity in most mammals uncouples these competing processes so that resorption is upregulated in comparison to bone formation (Seibel et al., 2006). A net loss of bone mass results from extended periods of immobilization, such as bed rest, weightlessness, or paralysis in humans and many other mammals (Aguirre et al.,

2006; Bloomfield et al., 2002; Lang et al., 2004; Sugiyama et al., 2002; Weiler et al., 2006; Zerwekh et al., 1998).

Inactivity and Osteoporosis

Osteoporosis, the result of increased bone remodeling favoring that of resorption, is a disease that has impacted our skeletal health dating back to our ancestors and has been documented microscopically in fossilized hominid remains (Schultz, 1999). Prehistoric cases were largely results of trauma- induced injuries and the subsequent disuse of a limb, but occasionally older individuals have been reported to have also decreased bone mass (Agarwal and

Grynpas, 1996; Schultz, 1999). Considering the increasing trend in sedentary habits, a significant contributing factor to overall bone health at any age, the etiology of osteoporosis has changed in modern society (Agarwal and Grynpas,

1996). Officially coined in the 1820’s to mean porous bone, it has been the focus of countless descriptions, investigations, and clinical trials (Schapira and

Schapira, 1992). Indeed, osteoporosis warrants the attention because today over 10 million people nationwide have osteoporosis and 34 million are at risk of developing the disease (National Osteoporosis Foundation, www.nof.org).

Women over 50 years of age have an increased chance of developing osteoporosis, but 25% of aging men will also be diagnosed (www.nof.org).

People who suffer osteoporosis-related fractures are more likely to die within one year of experiencing a broken bone, and the cost of osteoporosis-related injuries is projected to be in the tens of billions of dollars each year by 2025

(www.nof.org). Despite rigorous biomedical research, there is still no cure for osteoporosis.

Once bone is lost in individuals with active osteoporosis, it is quite difficult to maintain bone mass and prevent future fractures (Stevenson et al., 2005).

Genetics play a large role in the predisposition of developing osteoporosis; this includes stature and ethnic background (Ralston and Uitterlinden, 2010;

Sigurdsson et al., 2008). Women are also more prone to getting the disease than men, particularly following menopause when estrogen levels decrease

(Weitzmann and Pacifici, 2006). Numerous controllable factors, such as diet and exercise, greatly impact overall bone health as well (Borer, 2005; Eastell and

Lambert, 2002; Guadalupe-Grau et al., 2009; LeBlanc et al., 1990; Rizzoli, 2008;

Stransky and Rysava, 2009; Tucker, 2009). Despite numerous pharmacological agents on the market, all have rather disappointing success rate and significant long-term side effects (Stevenson et al., 2005). Increased weight-bearing activities and calcium supplementation remain the principal two recommended preventative and therapeutic steps to slow the progress of osteoporosis and prevent future fractures (National Osteoporosis Foundation, www.nof.org; Gold and Silverman, 2004).

Considering the serious consequences of having low bone mass as a result of uncoupling the bone remodeling processes in disuse osteoporosis, it is important to be able to assess bone loss accurately. Osteoporosis and other bone loss diseases are often diagnosed on the basis of bone mineral density

measurements obtained from imaging equipment such as dual energy x-ray absorptiometry (DEXA) and computed tomography (CT). Serum collected from blood samples also provides critical information about the overall skeletal processes occurring at the time of sampling and lends great insight into the balance of bone formation and resorption.

The physiological processes influencing the skeleton ultimately impact a bone’s ability to withstand the external forces it experiences during normal activities in humans and other animals. Under normal circumstances, bone structural properties represent a trade-off between the ability to absorb energy and transmit force (Biewener, 1990; 2003b; Currey, 2002b). In a compromised skeleton, bone strength and stiffness decrease resulting in a skeleton more prone to fatigue and fracture (Biewener, 1990; Seeman, 2008; Turner and Burr,

1993). Thus, measures of the geometrical properties of bone and its mechanical strength are important factors when considering the biological relevance of bone loss to individuals after physical inactivity. Along the same lines, bone integrity ultimately results in behavioral changes during locomotion. As such, assessing the gaits utilized by individuals as well as the estimated stresses bones experience during those gaits are additional means to determine the integrity of the skeleton following disuse.

Determining the Skeletal Biology of Hibernating Woodchucks

The primary goal of this project was to identify the physiological mechanisms regulating bone density, area and strength during extended periods

of annual inactivity in hibernating woodchucks (Marmota monax) to understand how the skeleton copes with the challenges posed by hibernation. To meet this goal, the principal hypothesis that bone integrity is unaffected by several months of inactivity during hibernation in woodchucks was tested. This was accomplished by investigating several aspects of the woodchuck skeletal system during hibernation, ranging from behavioral observations of locomotion to protein assays of serum, with broad implications toward defining the evolution of the skeletal response to extreme mechanical unloading and biomedical research of osteoporosis.

Four topics of interest were investigated to collect a holistic assessment of annual woodchuck bone integrity. First, it was determined whether there were seasonal behavioral changes associated with locomotion before and after hibernation. It was assumed that woodchucks, as hibernators, sustain the capacity of their bones to withstand functional stresses (i.e., maintain bone safety factors (Biewener, 1990; Currey, 2002b)) to avoid bone failure when initiating normal activity in the spring. In addition, the gait pattern utilized before and after hibernation was compared, as well as how differences in body weight influenced the locomotion of these animals. Any differences noticed in the behavior of these animals provided evidence of how woodchucks cope with the environmental demands following physical inactivity and are a first indicator of functional deficits. It was hypothesized that there would not be significant changes in the gait pattern or stresses experienced by bone during locomotion of woodchucks.

These animals have a great, physical reproductive demand immediately following hibernation in the spring, and thus any loss of locomotor function would directly reduce their selective fitness by interfering in mate acquisition and propagation.

Second, it was determined whether bone mineral density, structural geometry, and trabecular indices change with hibernation using the bone imaging techniques of peripheral and microquantitative computed tomography (pQCT and

μQCT, respectively). Bone imaging is a primary tool used clinically to determine bone mass and diagnose osteoporosis (Garnero, 2008), thus it provided invaluable information for this study. Various groups of woodchucks were utilized to determine seasonal changes in bone mass and structure. A museum collection of animals obtained before and after hibernation were investigated for changes in bone density and geometrical properties. Live woodchucks, caught in the wild, were also examined in a cross-sectional study of these variables to understand how animal skeletons are influenced by natural hibernation. Finally, a group of captive animals that were encouraged to hibernate under simulated conditions were examined as a longitudinal sample to further investigate diaphyseal density and distribution before, during, and after hibernation. No significant changes in bone integrity as determined from QCT are predicted to result from hibernation based on previous work in other hibernators.

In association with bone stresses experienced during locomotion and estimates of geometrical properties obtained from computed tomography, direct measurements of bone strength, yield, elastic modulus, and toughness were

determined using three-point bending tests. It was assumed that when woodchucks emerge from hibernation and resume all normal acitivities, the mechanical properties of their bone would not be significantly different between the hibernating and active seasons. The consequences of reduced bone strength would affect the loads bones were capable of withstanding and leave them prone to injury and potential animal death. Osteoporotic bones are characteristically weaker, lending to higher frequencey of fractures under small loads (e.g., during sneezing or standing up; Galsworthy and Wilson, 1996).

Therefore, if bone was lost during hibernation, it would be expected that they would become stiffer and more brittle in the posthibernation season.

Finally, bone serum markers were investigated as a tool for assessing the physiological processes reflecting overall skeletal health in hibernating woodchucks. Both captive and free-ranging individuals were examined, with wild animals serving to increase sample size and provide a positive control, to determine significant differences in serum properties between seasons. Serum analysis is used clinically in association with bone imaging techniques, such as pQCT, as a diagnostic tool in identifying osteoporosis status and to obtain information about the bone formation and resorption processes regulating bone mass and structural properties (Garnero, 2008). Specifically, markers of osteoblast and osteoclast activity will be examined. Those in the bone formation pathway include osteoprotegerin (OPG), alkaline phosphatase (ALP), and osteocalcin (OC). Bone resorption markers including ICTP (a telopeptide

cleaved from Type I collagen) and osteopontin (OPN) were considered. Serum leptin was also investigated as a preliminary examination into the contribution of fat in influencing bone metabolism in hibernators. Finally, serum calcium (Ca) and inorganic phosphate (PI) levels were assessed as indicators of minerals important to the skeleton and yet requisite and available in circulation for cellular processes.

It was hypothesized that osteoblastic and osteoclastic markers would be balanced throughout the year, indicating that bone formation and resorption processes remain coupled, to prevent detrimental bone loss during annual hibernation seasons. Analyte coupling was assessed using a cross-correlation function to determine annual relationships of the markers of interest in the captive animal sample. Support for this hypothesis would indicate that the molecular signaling pathways regulating skeletal quality remain temporally correlated to maintain bone quality despite mechanical disuse. Using serum markers previously studied in bears and the bone morphometrics of this study as a starting point, the mechanisms involved in maintaining skeletal quality during hibernation will be further elucidated.

Implications and Significance of this Research

This work may have several broader implications for mammalian biology.

First, size-related changes in both metabolism and the skeleton may interact with bone-related physiological processes to impact how bone responds to hibernation across mammals (Bromage et al., 2009; Christiansen, 2002; Kjeld

and Olafsson, 2008; Mullender et al., 1996; Prange et al., 1979; Schmidt-Nielsen,

1984). Secondly, this work will further document the range of mechanisms used by hibernating mammals through comparisons with previous data collected from other hibernators (Donahue et al., 2006a; Donahue et al., 2006b; Donahue et al.,

2003a; 2003b; Doty and Nunez, 1985; Floyd and Nelson, 1990; Floyd et al.,

1990; Haller and Zimny, 1977; Harvey and Donahue, 2004; Harvey et al., 2005;

Kwiecinski et al., 1987; Lennox and Goodship, 2008; McGee-Lawrence et al.,

2008; McGee-Lawrence et al., 2011; McGee-Lawrence et al., 2009a; McGee-

Lawrence et al., 2009b; McGee et al., 2008; McGee et al., 2007; Steinberg et al.,

1981; Zimmerman et al., 1976). By adding to our understanding of the range of mechanisms available to skeletal maintenance, this work will shed new light on the current debate over the phylogenetic polarity of hibernation in mammals

(Carey et al., 2003; Geiser, 1998; 2008; Grigg et al., 2004; Kortner and Geiser,

2000; Liow et al., 2008; Lyman et al., 1982). Comparisons with other hibernating mammals will help delineate novel versus conserved physiological mechanisms used by hibernating woodchucks. The identification of differing physiological mechanisms across mammals would suggest convergence in bone physiological processes across hibernators. Finally, this work will further explore the possibility that the skeletal system is compromised during hibernation in certain mammals populating these cold, stressful environments (Doty and Nunez, 1985; Haller and

Zimny, 1977; Kwiecinski et al., 1987; Steinberg et al., 1981). Because these datasets presented in this research encompass multiple levels of biological

function from morphology and performance to protein expression, this study will provide an integrated perspective, spanning multiple levels of organization, into how bone remodeling processes are coordinated in hibernating woodchucks.

Collectively, the work will foster an increased understanding of the evolution of skeletal plasticity and its mechanistic basis in mammals with direct applications to osteoporosis research.

CHAPTER 2

BEHAVIORAL CHANGES IN THE LOCOMOTION OF WOODCHUCKS BEFORE AND AFTER HIBERNATION

Introduction

Most terrestrial animals use their limbs to maneuver through their environment. Limbs play important roles in numerous behaviors including supporting the body, obtaining food, avoiding predators, finding a mate, and migration. The locomotor abilities of numerous animals have long held the interest of functional morphologists and physicists alike to understand the function of these structures. By understanding locomotor performance, we gain valuable information about the complexity of animal form and potential insights into the selective pressures an animal may face in its natural environment.

Furthermore, with knowledge of the mechanics underlying locomotor behaviors, we can better understand the factors that can negatively impact normal locomotor function. For instance, after prolonged inactivity and/or weightlessness, both physical states known to cause increased bone resorption relative to bone formation, skeletal elements can lose bone mineral density and structural integrity (Aguirre et al., 2006; Bloomfield et al., 2002; Lang et al., 2004;

Weiler et al., 2006; Zerwekh et al., 1998). It is logical to hypothesize that

following remobilization, an animal will have to adjust its behavior to protect compromised skeletal elements during this reambulatory period. For example, dogs that lost significant bone mass in limb immobilization studies were qualitatively lame and had reduced range of motion for up to four weeks following remobilization (Kaneps et al., 1997). The goal of this study was to determine whether locomotor behavior changed following the extended inactivity during hibernation in a group of woodchucks. Observed differences in performance between seasons may relate to underlying changes in bone integrity.

Kinematics

Kinematics is the study of animal movements. Traditionally, kinematics involves classifying various gaits available to an animal by characterizing the timing, sequence, and displacement of footfalls in relation to some fixed reference point (Reilly and Biknevicius, 2003; Winter, 2005). To determine these footfall patterns, video recordings are used to document the first contact of each foot with the ground and its subsequent liftoff during locomotion. From these data, gait diagrams can be constructed representing the proportion of time of each foot’s interaction with the substrate in relation to the other limbs (Fig. 2.1A).

Specific types of locomotor gaits can be classified by the percentage of time the limbs are in contact with the ground (i.e., the duty factor) and by the action of limbs in relation to each other (i.e., limb phase; Hildebrand, 1985). Specifically, duty factor (β) is the ratio of the stance duration, or the interval the limb is contacting the ground, to the stride duration (Fig. 2.1B). A stride is the time it

Fig. 2.1: Gait diagram of a woodchuck trotting. The contralateral foot (left hind = LH) strikes the ground at nearly the same time as the reference limb (right fore = RF) demonstrating how the pair move in phase together (A). Stride duration is defined by the duration between consecutive touchdowns of the reference limb (B). The stance phase is the time the limb is supported by the ground and is often measured as the proportion of limb contact over stride duration. Swing phase is when the limb is suspended and is also considered as a proportion of stride duration.

takes to complete the sequence of all four limb movements from the touchdown of a reference foot to the subsequent touchdown of the same foot (for quadrupeds, Fig. 2.1B; Biewener, 2003a; Hildebrand, 1976). Duty factor provides information about the speed of a gait an animal chooses to use and it is negatively correlated to speed and ground force reaction. Thus, as an animal increases speed, duty factor decreases (the limbs are in contact with the ground for less time) and the ground reaction force, or the amount of force the animal exerts on the ground, increases. Regardless of footfall sequence, duty factors less than 50% are classified as running gaits and those greater than 50% are typical of walking gaits (Hildebrand, 1965).

Limb phase is calculated as the proportion of the touchdown of the ipsilateral (same side) foot after the touchdown of the reference limb in relation to stride duration (Hildebrand, 1976). This action, or phasing, of paired feet (for example, left hind and left forelimbs) is used to characterize symmetry of a gait and to classify specific gait types (Reilly and Biknevicius, 2003). Symmetry of a gait is calculated as the percentage of the interval between the touchdown of the reference limb and its contralateral (opposite) pair relative to stride duration

(Hildebrand, 1966; 1976; 1977). Symmetrical gaits have equal timing of fore and hind footfall intervals (i.e., their fore and hindlimbs move in phase in relation to each other; Hildebrand, 1966; 1976). Walks, trots, lateral sequence, and diagonal sequence gaits are examples of symmetrical gaits (Hildebrand, 1966).

Asymmetrical gaits are characteristically defined as having footfalls of pairs of feet asynchronously distributed throughout the stride. These include gallops and bounds (Hildebrand, 1977).

Besides determining symmetry of a gait, limb phase is also utilized to determine specific types of symmetrical gaits. A classical example of a symmetrical gait is the trot in which the diagonally associated front and hindlimbs contact the ground at the same time (or nearly so) and constitutes a

“two-beat” gait (Fig. 2.2A; Hildebrand, 1965). Each foot pair in a trot makes up nearly 50% of the stance duration of the stride (Hildebrand, 1966). In other symmetrical gaits, stance duration of each limb constitutes less than half of the stride duration. Symmetrical gaits in this study are further classified as lateral

Fig. 2.2: The symmetrical and asymmetrical gaits used by woodchucks with corresponding gait diagrams. Shaded limbs are of the right (far) side of the animal.

sequence (LS) and diagonal sequence (DS). Lateral sequence gaits are characterized by the footfall of a hindlimb followed by the ipsilateral forelimb (Fig.

2.2B; Hildebrand, 1965; 1966). DS gaits are defined by the touchdown of the hindlimb followed by the contralateral forelimb (Fig. 2.2C; Hildebrand, 1965;

1966). On the far end of the gait spectrum, are the paces (Hildebrand, 1966).

This gait type is characterized by the ipsilateral fore and hindlimbs moving in unison and is utilized primarily by camels, some horses and large dogs

(Hildebrand, 1985). Considering that limb phase is not indicative of speed, walks fall into the above categories of symmetrical gaits and are one of the most stable gaits available to animals because three or more limbs are in contact with the ground at all times (Biewener, 2003a). An example of a walking gait is the lateral

sequence single-foot (LSSF) which constitutes a four-beat gait with individual footfalls at equal time intervals (Fig. 2.2D; Hildebrand, 1966).

Animals move faster through their environment by increasing stride frequency. Increases in stride length, or the distance traveled, also functions to increase animal speed and is characteristic of galloping gaits (Alexander, 2003;

Biewener, 2003a). Asymmetrical gaits are typically faster and as such, duty factors tend to be low (Biewener, 2003a). Unlike the independent action of forelimbs or hindlimbs in symmetrical gaits, the forelimbs and hindlimbs function together in asymmetrical gaits (Hildebrand, 1977). Because of the uneven spacing of footfalls for forelimb pairs to hindlimb pairs within the stride, the relationship between limb contacts can be described as leading and trailing. A leading limb lags temporally but leads by virtue of foot touchdown position

(Hildebrand, 1977; Hildebrand, 1985). Bounds involve neither pairs of feet having a significant lead over the other and both forelimbs contact the ground synchronously, as do the hindlimbs (Fig. 2.2E). Half-bounds are defined when the hindlimbs move simultaneously, but one forelimb leads the other in footfall

(Fig. 2.2F). Gallops, on the other hand, involve a leading contact in both the fore and hindlimbs. Two types of gallops are recognized here based on the pattern of the leading limb. When fore and hind leading limbs occur on the same side of the body it is termed a transverse gallop (Fig. 2.2G; Hildebrand, 1985).

Alternatively, when the leading fore and hindlimb footfalls are on contralateral

sides of the body, the gallop is classified as a rotary gallop (Fig. 2.2H;

Hildebrand, 1985).

Kinetics

As an animal navigates its landscape utilizing various gaits, the bones are stressed by the impact of the animal with the ground (i.e., external forces generated outside the body) and by the muscles moving the limb (i.e., internal loads generated from within the body). Kinetics is the study of the forces that cause movement, and for accurate measurements of the forces acting on the limbs it is necessary to have a full kinematic description of the recorded locomotion (Winter, 2005). In addition to digitized videos to determine gait patterns, forceplates are commonly used to non-invasively record the vertical

(Fv), fore/aft (Ffa), and mediolateral (Fml) ground reaction forces acting in a three- dimensional landscape. These forces effectively quantify the force required to support the body mass during each step (Fv), the deceleration/acceleration of the animal as it moves horizontally (Ffa), and the mediolateral stability required to maintain an upright posture during locomotion (Fml; Reilly and Biknevicius, 2003).

From the video recordings of an animal during locomotion and the resultant ground forces obtained as it moves across a forceplate, it is possible to indirectly estimate the muscle actions required to counteract the ground reaction forces

(Biewener, 1983b). Although not as accurate as in vivo strain gauges (Biewener et al., 1983), the axial compressive and transverse bending stresses acting on each bone element of the limb during locomotion can then be estimated from the

ground reaction forces, the angle of the bones moving in relation to the ground reaction forces, and the muscle moment arms (Biewener, 1983b; Winter, 2005).

During steady-state locomotion, bones are subjected primarily to two types of strain (Rubin and Lanyon, 1982). Axial compression (σc) is produced by the force of the body elements contacting the ground and muscle force being transmitted along the longitudinal axis of the bone. Transverse bending (σb) is created by the angle of the bone in relation to the ground reaction force (GRF) and the action of muscles about the joints (Biewener, 1983b). Torsional loading is also a force component impacting bone, but it is considered to be low during forward, steady-state locomotion (Rubin and Lanyon, 1982) and is not considered in this study. Bone elements aligned to the GRF and line of muscle action tend to be influenced less by bending forces than those oriented at a greater angle to these forces. However, bone curvature, regardless of bone orientation, can subject a bone to additional amounts of transverse bending.

Bending occurs principally around the bone mid-shaft and tends to be greater on the caudal cortex of the diaphysis (or posterior cortex in bipedal animals) and is compressive (Biewener, 1983b). Concurrently, the cranial (anterior) cortex experiences tensile strains during locomotion.

Bone length, diaphyseal shape, and curvature predispose bending stresses to be greater than axial compressive stresses (Biewener et al., 1983).

Furthermore, the distal limb elements experience greater bending loads as a result of the axial compressive stresses themselves because of the bone's

curvature. The forelimb bones are curved more than the hindlimb elements, particularly those of small animals, and the radius more so than the ulna. Given this curvature, the radius has been reported to experience greater bending strains than the ulna based on its curved shape as it is assumed that both the radius and ulna equally distribute forelimb forces during locomotion (Biewener,

1983b). As an animal increases speed, a concomitant increase in peak Fv occurs, which subjects bones to greater bending strain. Furthermore, the forelimbs typically experience relatively greater Fv than the hindlimbs, and therefore more transverse bending, as they act to decelerate the animal and absorb the impact shock at contact following the areal phase of a stride

(Biewener, 1983b; Biewener et al., 1983; Hildebrand, 1976; Jayes and

Alexander, 1978).

Hibernation and Locomotion

Information gained from both kinematic and kinetic studies of animal locomotion is quite valuable to characterize not only the pattern of gait but also to understand the specific loading regimes that bones experience. It is with this background that gait preference and estimated bone stresses will be investigated in hibernating woodchucks. Although most mammals do not normally experience mechanical unloading or disuse osteoporosis in the wild, hibernating animals are inactive for several months every year (up to 9 months in some Arctic animals).

The consequences of bone loss during hibernation may compromise the skeleton and would potentially be extremely detrimental to woodchucks considering that

immediately after hibernation these animals must find a mate and reproduce, as well as effectively avoid predators and forage for food. Despite this inactive period, many hibernators live for numerous years with little evidence that their skeletal elements are weakened by annual periods of mechanical unloading

(Donahue et al., 2006b; McGee-Lawrence et al., 2008; Utz et al., 2009; Wojda et al., 2012).

It has not been directly investigated whether there are significant kinematic or kinetic differences during locomotion as a result of inactivity following hibernation in any hibernating species. Although the ground squirrel species (Ictidomys tridecemlineatus) used in Biewener (1983b) is a hibernator, this aspect of its biology was not considered in this research. A study of the closely-related golden-mantled ground squirrel (Callospermophilus lateralis) reports that fatter animals were less active on exercise wheels preceding hibernation, but does not mention speed or any other aspect of their locomotion

(Pengelley and Fisher, 1966). Body weight is certainly an important consideration in animal locomotion as body size and weight distribution potentially impact not only the forces acting on the limbs, but also the gait an animal uses. The size-related change in posture of the limbs during locomotion assists animals to achieve similar peak stresses in bones that scale geometrically across a range of body sizes (Biewener, 1983a). For example, larger animals move with straighter limbs than the crouched posture adopted by small animals. Furthermore, most animals tend to choose gaits that maximize

the time they are supported by more than one limb to increase stability during locomotion (Cartmill et al., 2002). This effectively ensures that they maintain their center of mass at a point between their diagonally associated pairs of feet

(the support polygon) during a gait (Cartmill et al., 2002).

Significant change in body mass is a hallmark characteristic of hibernating animals. Artificially manipulating the weight distribution of an animal during locomotion has been investigated to elicit changes in gait patterns (Farley and

Taylor, 1991; Lee et al., 2004; Young et al., 2007). Seasonal animals that prepare for food shortages (such as hibernators and overwintering birds) are an excellent natural model to investigate the effects of changes in body mass and distribution on locomotion. A few such studies exist, although they do not directly investigate the consequences of inactivity during hibernation on the mechanical aspects of locomotion (Lees et al., 2010; Lemelin and Schmitt, 2004; Young et al., 2007).

In this study, the kinematic and kinetic aspects of locomotion in active woodchucks were examined before and directly after hibernation. It was determined whether these animals modulated their locomotor behavior to reduce bone loading to compensate for potential deficits in bone mechanical properties following hibernation. Three hypotheses were examined. The first hypothesis was that woodchucks use similar gait symmetry and select similar gaits between seasons. Second, it was hypothesized that woodchucks do not change the magnitude of peak vertical force (after adjusting for changes in body mass)

produced during locomotion before or after hibernation. The third hypothesis stated that estimated axial compressive and transverse bending stresses remain similar between seasons. If supported, these hypotheses will reflect the ability of woodchucks to resume normal locomotor function following hibernation and will provide indirect evidence for the maintenance of bone mechanical properties throughout the year in a seasonally inactive animal.

Materials and Methods

Animals

Healthy woodchucks (Marmota monax) were trapped live according to

Northeast Ohio Medical University (NEOMED) Institutional Animal Care and Use

Committee approved protocols (#08-0027, #08-0029, #11-019) and annual Ohio

Division of Wildlife permits (#11-257, #14-68). Woodchucks were collected from

Portage County, OH in the surrounding Rootstown area with permission from property owners. Upon capture, all woodchucks were transported to the

NEOMED Comparative Medicine Unit (CMU) for initial processing. Animals were anesthetized by intramuscular injection of ketamine (50 mg/kg) and xylazine (5 mg/kg) through the wire of the box trap. Once an animal was under anesthesia, it was removed from the trap. A face mask was used to deliver 1 to 3% isoflurane gas as needed to complete all processing and data collection procedures. A general assessment of health was made, including weight, rectal temperature, tooth wear, sex, and age. Any serious health problems observed,

such as unhealed broken bones experienced prior to capture, resulted in removal of the animal from the study. Selected woodchucks were incorporated into a captive animal sample and these animals were given a rabies vaccination and a series of de-worming injections to ensure animal health throughout the study.

Blood samples, radiographs, quantitative computed tomography scans, and physical measurements were collected at the time of animal acquisition.

Animals acquired for captive studies were allowed to recover from anesthesia individually in 4’x2’ cages and acclimate to their new surroundings within the CMU. A subset of adult woodchucks (more than one-year old), were selected from the captive woodchuck sample for locomotion experiments.

Adulthood was determined based on dental characteristics, radiographic attributes of epiphyseal plate closure, pelage at time of capture, and post-mortem skeletal assessments following cold water maceration of the woodchuck at the end of the study (Davis, 1964; Hamilton, 1934). The locomotion sample included three adult males and two adult females (N = 5). These five woodchucks were maintained for nine months (August through April) spanning the hibernation season. One annual cycle, or year, was categorized into four seasons for statistical investigation: Prehibernation (August - October), Hibernation

(November – mid-March), Posthibernation (end of March - May), Summer (June-

July). This locomotion study includes three of these seasons; prehibernation, hibernation, and posthibernation.

During the active pre- and posthibernation seasons, woodchucks were given periodic access to a 15’x1.5’ runway. Diet during these active periods consisted of high fiber rabbit chow supplemented with fresh apples, carrots, and kale. Water was provided ad libitum. During the hibernation season (October 15

– March 25), woodchucks were allowed to hibernate in a walk-in refrigeration unit. Ambient temperature of the refrigerator was held at 7˚C (± 1-2 ˚C) and, to avoid interruption to hibernation during daily welfare assessments and data collection, a red-light lamp was left on for the duration of the winter. Food was restricted and withheld to initiate hibernation. Most animals did not consume food after entering hibernation.

Locomotion Experiments

During the prehibernation and posthibernation seasons, woodchucks were trained to freely move along a 15’x1.5’ raised wooden runway with an integrated forceplate (Kistler, Type 9253B, Winterthur, Switzerland). The runway was enclosed on all sides by 2’x4’ sealed wood panels except the top to provide access to the animal. The front middle panel of the runway was a 2’x4’ Plexiglas sheet to allow video recording of locomotion across the forceplate. Up to four free-standing light sources were used to illuminate the animal and video recording area along the runway.

A dark cloth was draped over each end of the runway to provide an enticing space for the animal to move toward and rest away from the lights in between recording trials. Animals were encouraged to move back and forth

along the length of the runway by removing the dark cloth where the woodchuck was resting (Fig. 2.3A). Trials in which the animals stopped on the plate or changed direction were not analyzed. Trials having single-foot contact on the force plate (i.e., at the beginning with a forefoot or at the very end with a hind) were selected for digitization and calculation of bone stresses during locomotion

(Fig. 2.3B). Force data were collected at 1000 Hz with 2000 pC amplification as the animal moved across the forceplate (Fig. 2.3C). The force output was clipped to include only the single-step traces for further calculations (Fig. 2.3D).

Three resultant force tracings were recorded, however only the vertical (Fv) and fore/aft (Ffa) directions for each trial are reported. The magnitude of the mediolateral force (Fml) component was considered to be small (Biewener,

1983b; Biewener et al., 1983). Forceplate tracings were assessed in IGOR Pro

5.0 (Wavemetrics, Inc., Portland, OR) and analyzed with a custom MATLAB program (R2010b, Mathworks, Natick, MA) in conjunction with digitized, synchronized video files in Proanalyst (3-D Professional Edition, v. 1.5.3.6,

Xcitex, Cambridge, MA). Vertical impulse was determined for each individual fore and hind foot as a measure of body weight distribution and was calculated as the area under the force trace curve (Lee et al., 1999; Young et al., 2007).

Each locomotion trial was filmed at 250 frames per second using a high speed digital Motion Scope (Redlake MASD, Inc., Model PCI 1000s,

Tallahassee, FL), with 1/2500 shutter speed and a 25 mm lens. The camera was placed 8’ directly in front of the force platform. High speed video recordings were

Fig. 2.3: A locomotion trial and the resulting data. A woodchuck (shaved for better viewing of the joints) trots across the integrated forceplate (A). The center of pressure (COP), proximal (knee), and distal (ankle) joints are digitized for each fore and hindlimb having single-foot contact with the forceplate (B). The resultant ground reaction force traces (vertical (Fv, blue), fore-aft (Ffa, black), and mediolateral (Fml, red)) recorded by the forceplate during locomotion (C). The data are cropped to the single-foot hind step to estimate maximum vertical force (MaxFv) produced by the woodchuck (D).

synchronized with a 90% TTL trigger to a custom LabView 7.0 program (National

Instruments, Austin, TX) designed to collect force output from the forceplate. An additional digital video recorder (Sony, DCR-TRV840, Tokyo, Japan) with a wider digital zoom was used to record footfalls for gait analysis. These gait videos were converted to digital AVI files using iMovie HD (v. 5.0.2, Apple, Cupertino,

CA) and digitally de-interlaced to 60 fields per second using JES Deinterlacer

(v.3.2.4).

Video Digitization and Analysis

Analysis of woodchuck kinematic videos: All gait kinematic data were digitized using ProAnalyst software (3-D Professional Edition, v. 1.5.3.6, Xcitex,

Cambridge, MA). The distance between two vertical bolts fastening the forceplate (498.48 mm) was used to calibrate each video and calculate speed of the animal by recording the number of frames between the animal’s nose passing each bolt (Young et al., 2007). Acceleration of the woodchuck was measured by tracking the eye of the animal for the duration it was visible during the video (Lee et al., 1999). Gait pattern was obtained by digitizing the touchdown (first frame of foot contact on the runway surface in view of the camera) and liftoff (last frame of foot contact) of each foot for the duration of a complete stride. Symmetrical and asymmetrical gaits were analyzed in this study. Following Young (2009), symmetrical gaits were classified as phases

between 43.75% and 56.25%. Likewise, asymmetrical gaits were identified if phases fell outside this range (Hildebrand, 1977; Young, 2009).

Limb phase and duty factor were used to define the type of gait used by the animal in each trial. Gaits of interest include the trot, lateral sequence (LS), lateral sequence single-foot (LSSF), diagonal sequence (DS), bound, half-bound, transverse gallop, and rotary gallop (Fig. 2.2, Table 2.1). Limb phase values of symmetrical gaits include the following: 44-56 represent trots, 6 to 44 represent

LS gaits, 18.75-31.25 the LSSF, and 56 to 94 indicate DS gaits (Hildebrand,

1966). Types of asymmetrical gaits were identified based on the lead intervals of forelimb and hindlimb pairs (Hildebrand, 1977). Bounds were classified by simultaneous touchdown of the fore and hindlimbs (with leads not more than

10% of the contact interval of each pair; Table 2.1). Half-bounds were distinguished if there was a forefoot lead but hindlimbs were concurrent (hind leads 10% of contact interval, fore lead >10%). Lead intervals in both the fore and hindlimbs were indicative of gallops (lead intervals greater than 10% of contact intervals). Transverse gallops constituted leads in ipsilateral fore and hind contacts whereas rotary gallops were identified by contralateral leading limbs (Hildebrand, 1977).

Analysis of woodchuck kinetic videos: The high speed videos were used to digitize the joints representing the bones of interest (i.e., tibia, radius, and ulna) during single-foot-contact with the forceplate. Only peak forces were analyzed. The femur and humerus were not included in this analysis because of

the potentially high incorporation of error in 1) projecting the moment of proximal limb elements from the ground reaction force (Winter, 2005), and 2) estimating

Table 2.1: Gait Classification Definitions

Symmetry Gait type Definition Limb phase % Diagonal front and hind

Trot limbs move in phase: 2- 44-56 %

beat gait Ipsilateral sequence of 6-44 % Lateral sequence footfalls (LS) Lateral sequence single- 18.75-31.25 %

foot (LSSF): 4-beat gait Symmetrical Diagonal sequence Contralateral sequence 56-94 % (DS) of footfalls Lead type Hindlimbs and forelimbs Lead of fore and Bound move in phase with each hindlimbs ≤10%

other contact interval

Both hindlimbs move in Hindlimb lead ≤10% Half-bound phase, forelimbs are out contact, forelimb of phase lead >10% Transverse gallop:

Asymmetrical Ipsilateral leading limbs Fore and hindlimb Gallop Rotary gallop: leads >10% contact Contralateral leading interval limbs

the complex orientation of the muscle forces acting on them (Biewener, 1983b).

The fibula is not a weight-bearing bone, and as such, was not measured in this study. Joints of interest, therefore, were the knee (proximal joint) and ankle

(distal joint) of the hindlimb; elbow (proximal) and wrist (distal) of the forelimb

(Fig.2.3B). The center of pressure (COP, or the assumed point of action of the ground reaction force in the paw) of each limb was calculated by taking the

average distance between the distal- and proximal-most contact points of the paw on the ground (Fig. 2.3B; Biewener, 1983b).

Bone Imaging Techniques and Analysis

Computed tomography: At time of capture prior to hibernation and again in the posthibernation season, peripheral quantitative computed tomography (pQCT) scans and radiographs were taken of the limbs to collect geometrical information for estimating bone stresses. Scans were limited by the

50 mm gantry of the scanner (XCT Research M 921010, Norland/Stratec) and by the amount of time required to scan the areas of interest in an anesthetized animal. For these reasons, pQCT scans were taken only of the tibial diaphysis

(approximating 50% of bone length). To obtain the scan, the left leg of the anesthetized woodchuck was positioned and securely taped, anterior side down, on a custom platform made to hold woodchucks for the pQCT scan procedure

(Bone Diagnostics, Inc.). The leg was then inserted into the gantry of the scanner and oriented as perpendicular to the radiation beam as possible. Slice thickness was 0.25 mm with a voxel size of 0.1 mm, giving a final resolution of

100 μm for each scan. All scans were acquired against a standard cone phantom with known densities (XCT Research M).

Following euthanasia (intravenous FatalPlus) and after all locomotion trials were completed, final cross-sectional data were collected on the radius and ulna using a Scanco Medical VivaCT 75 microQCT (μQCT) scanner (Brüttisellen,

Switzerland). A 7.7 mm thick section of the bones were scanned at the diaphyses (around 50% total bone length, Fig. 2.4A). Scans were acquired by beam intensity of 70 kVp, 114 μA, and voxel size of 20.5 μm.

Each scan of the tibial, radial, and ulnar diaphyses was imported as a raw stack into Image J (v. 1.45 s) for analysis (Fig. 2.4B). The scans were then thresholded and analyzed with Slice Geometry, a Bone J plugin used to estimate cross-sectional area (Ct.Ar), second moment of area (I), and distance from the centroid to the surface of cortical bone (c; Fig.2.4C and D; Doube et al., 2010).

Radiography: Radiographs were also taken of the anesthetized animals either in a prone or sagittal position on a flattop Fluoricon Compact OM unit (GE,

C7108EA/EE) using the small focal spot and KodakMin 24x30 film. Animals were x-rayed at a distance of 40 inches and exposure factors ranged between

50-70 kilovolatge peak (kVp) depending on the width of the limbs (in cm) being radiographed at 6.7 milliamperage (mA) for a duration of 1/15 seconds. Fore and hindlimbs were flexed so joint angles approximated 90 degrees mimicking a stance phase for optimal mechanical measurements.

Exposed film was developed using a Konica medical film processor

(Konica Medical Corporation, Model SRX-101A, Wayne, NJ). Radiographs were then digitally scanned using an Epson Expression scanner 1600 (Model EU-35,

Epson, Inc, Long Beach, CA) with a backlit scan adaptor to digitize image files in

Image J (v. 1.45s). Measurements were then collected from each scan for estimating bone stress during peak locomotor force (Table 2.2, Fig. 2.5).

Fig. 2.4: Computed tomography scans were taken of the diaphyses of the tibia, radius, and ulna (tibia shown) approximating 50% of the length of the bone (A). The cross-section is obtained and analyzed in Image J for geometrical analysis (B). The image is thresholded (C) and the moments of inertia (I) are calculated along with cortical area (Ct.Ar) and distance to the centroid (c; D).

Table 2.2: Summary Table of Woodchuck Kinetic Data and Variables

Measurement Type Media Term Units Definition /Equation# Angle of the muscle to the long α deg Direct

axis of the bone

Midpoint of the length of the shaft L mm Direct of the bone Moment arm of the long axis of r mm Direct bone to the middle of medullary

cavity Radiographs Moment arm of the muscles to the x mm Direct center of rotation about the joint Ct.Ar mm2 Direct Cortical area I mm4 Direct Second moment of area Distance from the neutral axis to

Constants(by individual) c mm Direct

CTScans the surface of the bone cortex Digitized distance between two scale Pixels/mm Digitized fixed points on the forceplate ProxJoint Pixels/mm Digitized Proximal joint of the limb of interest DistJoint Pixels/mm Digitized Distal joint of the limb of interest

Video Midpoint between the anterior and COP Pixels/mm Digitized posterior contact points of the paw

on the ground

Fv N Force output Vertical force component

Ffa N Force output Fore-aft force component Force Axial compressive stress of bone ϭ MPa Eq. # 1 c during contact Combined axial compressive load

C N Eq. # 2 of the ground and muscles acting on the bone Flexor muscle force on bone of P N Eq. # 3 interest

Determinant of the ground reaction

Continuous Ma unitless Eq. # 4 and 5 force and joint vectors

Ra N Eq. # 6 Bone reaction force in axial plane GRF N Eq. # 7 Ground reaction force

Calculated Angle of the bone in relation to the BF deg Eq. # 8 ang angle of the GRF

GRFang deg Eq. # 9 Angle of the GRF

Boneang Pixels/mm Eq. # 10 Angle of bone relative to ground Tensile and compressive bending Ϭ MPa Eq. # 11 b forces acting along bone mid-shaft Bone reaction force in transverse R N Eq. # 12 t plane

Fig.2.5: Lateral radiograph of a woodchuck’s forelimb demonstrating measurements collected for estimating stresses of the ulna at maximum vertical force. Measurements (blue lines) include: The moment arm from the tip of the accessory carpal (ac) to the center of rotation at the wrist (x), and the distance to the mid-shaft of the bone (L). The long axis of the bone (white line) was used to measure the angle of muscle alignment (carpal flexors) to the bone (α) and the moment arm to the middle of the medullary cavity (r). Scapula (Sc), humerus (H), ulna (U), radius (R). Based on Biewener’s Fig. 1 (1983b).

Distance to the mid-point (L) along the shaft of the tibia, ulna, and radius from the distal metaphysis was measured as well as mid-shaft width of each bone. In addition, the muscle moment arm was measured from the tip of the calcaneus or accessory carpal bone (depending on limb) to the center of rotation about the ankle or wrist (x), respectively. The angle of muscle alignment to the long axis of the bone (α) was also determined, along with the moment arm of the long axis of the bone to the middle of the medullary cavity (r). In the forearm, x and r were small measures that were not expected to vary considerably between individuals, so they were calculated from one representative sagittal x-ray of an average-sized woodchuck and used as constants for each animal. For the ulna, x was found to be 7.26 mm and r was 1.62 mm. The radius measurements documented x as 7.94 mm and r as 2.96 mm.

Calculations of Stress Estimates

Following Biewener (1983b), bone strains were calculated by integrating data obtained from digitized videos of single-contact steps at maximum vertical force with force trace data, QCT scans, and radiographs (Table 2.2).

Compressive stress, or axial loading of bone during contact, was calculated as:

Where Ct.Ar is diaphyseal cortical area (Fig. 2.4) and C is the combined axial compressive load acting on the bone:

(2) where P is the flexor muscle force and α is the angle of the muscle relative to the long axis of the bone. Flexor muscle force is estimated by measuring the moment of the ground reaction force at the ankle or wrist (Ma) divided by the moment arm of the muscles to the center of rotation about the joint (x):

(3)

Ma is determined by the Fv and Ffa forces, as well as the joint vectors:

Ma (4) which equates to:

- , (5) where DistJointx and DistJointy are the coordinates of the digitized ankle or wrist relative to the center of pressure (COP, Fig. 2.3B). COP and DistJoint are obtained from the digitized frames of locomotor events scaled to the known distance between the right and left edge of the forceplate in the video file (498.48 mm). The flexor moment force at the joint (x) is directly measured from the radiographs as the distance from the tip of the calcaneus or accessory carpal bone to the center of rotation about the ankle or wrist (Fig. 2.5).

Ra is the bone reaction force in the axial plane:

, (6) where GRF (ground reaction force) is calculated as:

GRF = (7)

and BFang is the angle of the bone subtracted from the angle of the GRF:

Where GRFang is calculated as:

and Boneang is the angle of the bone calculated from the digitized proximal and distal joints:

Bending stress, or the tensile and compressive forces acting along the mid-shaft of the bone, is calculated as:

where Rt is the bone reaction force in the transverse plane and is expressed as:

(12) and L is the mid-point of the length of the shaft of the bone, r is the moment arm of the long axis of the bone to the middle of the medullary cavity, c is the maximum distance from the neutral axis of the bone to the surface of the bone cortex, and I is the second moment of area for resisting vertical bending.

Statistics

Kinematic analysis: Analysis of gait preference was performed using a

Pearson chi-square (Χ2) on categorically defined gait types used by each individual in the pre- and posthibernation season using SPSS (v. 19, Table 2.1).

Gait symmetry was examined as a binary category in association with season to determine differences in seasonal changes in gait symmetry. Symmetrical and asymmetrical gaits were examined further using Pearson chi-square to determine selection of specific types of gaits regardless of symmetry before and after hibernation (Table 2.1). A Bonferroni post-hoc test was utilized to determine significant differences between gait types in each season. Exact tests were used

(α < 0.05) in this small sample of woodchucks. Percentages of gait selection and standardized residuals by season are reported.

Proportional changes of the durations of stance and swing phases of each digitized gait file were analyzed using univariate analysis of covariance

(ANCOVA) to determine changes in stride attributes before and after hibernation.

Speed was found to be significantly correlated with all kinematic and kinetic variables except for percent of body weight supported. As such, speed was treated as a cofactor with season in all univariate tests analyzing the gait components. Individual animals were treated as random factors in these analyses given their opportunistic trapping from a large population of wild woodchucks. In this way, they were considered to contribute to the seasonal variation being tested in woodchuck locomotor behavior. Interaction effects of

season and animals are reported. A total of 118 prehibernation and 139 posthibernation gait trials from a total of 5 woodchucks were analyzed (Table

2.3).

Table 2.3: Woodchuck Sample and Digitized Trials

Prehibernation Posthibernation Animal Sex Avg. Digitized Kinetic trials Avg. Digitized Kinetic trials mass kinematic mass kinematic (kg) trials Fore Hind (kg) trials Fore Hind M12 M 4.438 40 5 4 4.040 15 5 2 F15 F 3.313 18 4 3 2.865 45 6 6 M16 M 4.703 24 7 1 3.815 30 5 6 F17 F 4.053 25 6 6 3.253 28 8 4 4.263 11 5 4 3.325 21 7 5 CR12 M Total: 118 27 18 Total: 139 31 23

Kinetic analysis: The kinetic forces and stresses produced and experienced by woodchucks were examined before and after hibernation using univariate ANCOVA designs. The digitized single-foot contacts were analyzed separately for the fore and hindlimb. Speed was highly correlated with each variable and was used as a cofactor with season in all analyses. The exception to this was the percentage of body weight supported, in which speed was not significantly correlated, and as such speed was not used as a cofactor for this variable. Similarly, each woodchuck was treated as a random factor in the analysis to determine individual contributions to any seasonal variation in locomotor kinetics. Force production, percent body weight support, and stresses experienced by each limb were determined by adjusting for body weight (dividing

by body mass) and gravitational acceleration. A total of 45 (27 fore and 18 hind) single-foot contacts were analyzed during the prehibernation season and 54 (31 fore and 23 hind) steps were investigated in the posthibernation season (Table

2.3).

Considering that it is hypothesized there will be no significant change in locomotor behavior following hibernation, statistical power was calculated for each ANCOVA design to report the likelihood of committing Type II errors. This effectively reduces the chance of failing to reject a hypothesis when significant differences in fact exist between seasons. A power of ≥ 0.8 (1-β) was considered to be appropriate (Cohen, 1977). Large effect sizes were estimated to be 25% change and small effect size to be 10% change in locomotion variables for calculating statistical power.

Results

Kinematics of Woodchuck Locomotion

There were no significant differences between symmetrical and asymmetrical gait preference before and after hibernation (Table 2.4). One individual (M16) had a nearly significant switch in symmetrical vs. asymmetrical gait selection following hibernation (p = 0.054, Table 2.4, Fig. 2.6). However, when types of symmetrical and asymmetrical gaits were analyzed, there were no significant seasonal differences in the type of gait this individual used (p = 0.158,

Table 2.5, Fig. 2.6). Another individual (F17) appeared to favor certain gaits by

Table 2.4: Frequency of Symmetrical and Asymmetrical Woodchuck Gaits before and after Hibernation

Pearson Χ2 Season Test Animal Symmetry Pre- Post- p- Χ2 hibernation1 hibernation1 value 35% 33.3% Symmetrical (.0) (-.1) M12 0.013 1.00 65% 66.7% Asymmetrical (.0) (.1) 55.6% 77.8% Symmetrical (-.8) (.5) F15 3.111 0.121 44.4% 22.2% Asymmetrical (1.3) (-.8) 37.5% 66.7% Symmetrical (-1.1) (1.0) M16 4.562 0.054 62.5% 33.3% Asymmetrical (1.2) (-1.0) 72% 75% Symmetrical (-.1) (.1) F17 0.061 1.00 28% 25% Asymmetrical (.2) (-.1) 90.9% 76.2% Symmetrical (.4) (-.3) CR12 1.027 0.395 9.1% 23.8% Asymmetrical (-.7) (.5) 1Values represent percentage of gait utilization (standardized residual).

Fig. 2.6: Observed frequencies of symmetrical and asymmetrical (shaded) gait types used by five individual

8 58

woodchucks before and after hibernation. LSSF = Lateral sequence single-foot gait.

Table 2.5: Frequency of Woodchuck Gait Type before and after Hibernation

Gait Type Pearson Χ2 Symmetrical Gaits1 Asymmetrical Gaits1 Test Animal Season Trans- Half- Rotary 2 p- Trot LS LSSF DS Bound verse Χ bound Gallop value Gallop

Pre- 30% 2.5% 2.5% 15% 25% 15% 10% - hibernation (0.4) (-0.5) (0.3) (0.2) (0.5) (0.9) (-1.8) M12 26.6 3.752 0.754 Post- 7% 6.67% 0% 13.33% 20% 6.67% 26.67% - hibernation (- (0.5) (-0.3) (-0.2) (-0.5) (-0.9) (1.8) 0.4) 38.8 Pre- 9% 16.67% 5.56% 27.78% 11.11% - - - hibernation (- (0.1) (-0.1) (1.5) (0.5) F15 0.9) 4.826 0.327 62.2 Post- 15.6% 6.67% 8.9% 6.67% % - - - hibernation (-0.1) (0.1) (-1.0) (-0.3) (0.6) 33.3 Pre- % 4.2% 25% 8.3% 25% 4.2% - - hibernation (- (-0.3) (1.3) (-0.4) (0.7) (0.8) M16 1.0) 7.674 0.158 Post- 60% 6.67% 6.67% 13.33% 13.33% 0% - - hibernation (0.9) (0.3) (-1.2) (0.4) (-0.7) (-0.7)

40% Pre- a 32% a 4%a 24% a - - - - hibernation (- (1.5) (0.8) (-0.1) F17 1.0) 7.324 0.046 67.9 a a a Post- a 7.1% 0% 25% % - - - - hibernation (-1.4) (-0.7) (0.1) (0.9)

Pre- 54.5% 36.4% 0% 9.09% - - - - hibernation (1.4) (-0.6) (-1.0) (0) CR12 5.107 0.135 Post- 19% 57.1% 14.29% 9.52% - - - - hibernation (-1.0) (0.5) (0.7) (0)

1Values represent percentages of gait utilization (standardized residual).

Bold values are significant at the α = 0.05 level.

a,b Denotes a subset of gait categories that differ significantly from each other using Bonferroni post-hoc analysis.

LS = Lateral sequence; LSSF = Lateral sequence single-foot; DS = Diagonal sequence.

season (p = 0.046), however, the Bonferroni post-hoc failed to detect a significant difference between each gait type (Table 2.5). This woodchuck trotted 67.9% compared to other gaits during posthibernation whereas it trotted only 40% of the time during prehibernation (Table 2.5). Gait selection was independent of season in all other individuals (Table 2.5).

Interestingly, individual woodchucks used different gaits. For example,

CR12 utilized the lateral sequence single-foot (LSSF) gait both in the prehibernation and posthibernation seasons which was not observed in any other individual (Fig. 2.6). This was the only individual that did not trot in either season. Another woodchuck, M12, was the only individual to use a diagonal sequence gait, albeit only once in the prehibernation season. All individuals utilized the lateral sequence (LS) gait throughout the year, but there was individual variation in selection of all other gait types (Fig. 2.6). Despite these individual differences, all symmetrical gaits of the woodchucks followed Cartmill’s

“horse rule,” Rule 2, in that lateral sequence diagonal couplet gaits (with opposite legs touching down close in time to the contralateral reference limb) were utilized in favor of other gait types (similar to the majority of mammals) and these in turn gave way to the trot at faster speeds (slope of the linear relation between limb phase and duty factor was -0.906, and intercept = 89.5; Fig. 2.7A; Cartmill et al.,

2002). Furthermore, asymmetrical woodchuck gaits, except well defined gathered or extended rotary gallops, typically fell into the combined gathered and extended suspension models of the traditional asymmetrical gait graph (note that

the axes have been transposed so that both suspensions fall to the left on this chart, Fig. 2.7B; Hildebrand, 1977).

Fig. 2.7: The range of symmetrical (A) and asymmetrical (B) gaits of five woodchucks. LSSF = Lateral sequence single-foot.

The small sample size of woodchucks prevented examination of sex differences across seasons in the ANCOVA with individual animal as a random factor and speed as a cofactor. When analyzed independently of other variables, speed was not statistically significant between seasons or between animals

(observed power at the 10% effect level β = 0.952), however individual woodchucks did use a significantly different speed in the posthibernation period

compared to prehibernation (season by woodchuck interaction, p < 0.01, Fig.

2.8A, Table 2.6). Specifically, two animals (M12 and M16) decreased their average speed following hibernation, whereas the other three animals appeared to increase their speed posthibernation (Fig. 2.8A). Although limb phase values did not differ seasonally, average duty factor was reduced significantly between prehibernation and posthibernation (p = 0.002, Fig. 2.8B, Table 2.6). Average duty factors were also significantly different between seasons when investigating the fore (p = 0.028) and hindlimbs separately (p = 0.029, Table 2.6). As determined with speed, duty factor was particularly susceptible to animal variation and characterized the inverse pattern of that observed between individual changes in speed following hibernation (Fig. 2.9A).

A significant increase was apparent in the amount of time spent in the swing phase of the stride between animals in both the fore (p = 0.016) and hindlimbs (p = 0.044). Although there were no overall seasonal differences, individual differences of swing duration were significantly dependent on season

(p < 0.01, Fig. 2.9B, Table 2.6). All other changes observed in the gait components appeared to be individual differences related to season (Table 2.6).

These interaction effects illustrate the independent choice of gait type and symmetry available to woodchucks throughout the year. High statistical power at the 25% effect level for all variables except forelimb stance duration and limb phase made it less likely that Type II errors were committed. We confidently fail

Fig. 2.8: Speed did not differ significantly between seasons, but was significantly different between individual woodchucks by season (A). In contrast, duty factor was significantly lower in the posthibernation season despite no change in limb phase (B).

Fig. 2.9: Individual woodchuck fore (dashed) and hindlimb (solid) duty factors were significantly different between seasons (A). Swing duration increased in the fore (dashed) and hindlimbs (solid) throughout the stride between individuals in posthibernation (B).

to reject the hypothesis that individual woodchucks use similar gaits between seasons (Table 2.6).

Table 2.6: ANCOVA of Woodchuck Gait Components of Locomotion before and after Hibernation

Gait 1 Post- Season Woodchuck Interaction Limb Prehibernation 1 Power component hibernation F- p- F- p- F- p-value statistic value statistic value statistic Stride 0.3136 0.3305 0.763 0.432 5.302 0.062 2.423 0.049 0.961 Duration (0.0889) (0.0574) Stance 0.1572 0.1544 7.052 0.057 0.674 0.643 3.652 0.007 0.827 Duration (0.0666) (0.0403) Hind Swing 0.1565 0.1761 4.627 0.098 6.676 0.044 5.279 p < 0.01 0.995 Duration (0.0299) (0.0285) 0.4880 0.4639 Duty Factor 11.172 0.029 2.634 0.182 4.920 0.001 - (0.0637) (0.0597) Stride 0.3231 0.3369 0.772 0.429 6.082 0.051 4.371 0.002 0.954 Duration (0.0990) (0.0669) Stance 0.1613 0.1641 4.081 0.114 5.865 0.053 2.465 0.046 0.742 Duration (0.0781) (0.0513) Fore Swing 0.1582 0.1712 1.475 0.292 11.775 0.016 3.580 0.007 0.999 Duration (0.0279) (0.0306) 0.4901 0.4835 Duty Factor 11.410 0.028 21.179 0.004 1.174 0.323 - (0.0769) (0.0745) 1.3620 1.3402 Speed 0.021 0.891 4.097 0.100 12.286 p < 0.01 0.952 (0.0519) (0.1026) 0.4492 0.4492 0.120 0.746 16.651 0.009 3.139 0.016 0.530 Limb Phase (0.0763) (0.0770) Average Duty 0.5148 0.4777 42.725 0.002 16.621 0.007 0.848 0.497 - Factor (0.0671) (0.0592)

1Values represent gait component averages (standard deviation). Bold values are significant at the α = 0.05 level. Observed Power: Normal font indicates that sample size provides power ≥ 0.8 to differentiate a large effect change (25%) in gait components between groups. Bold power values represent effect changes of 10%.

Kinetics of Woodchuck Locomotion

Woodchucks created a greater vertical ground reaction force (Fv) in their forelimbs following hibernation (p = 0.043) after adjusting for body mass between the two seasons (Table 2.7, Fig. 2.10A). This relationship was not observed in the hindlimbs and there were no significant differences in Fv between individuals or the interaction of individuals by season in either limb. Statistical power was

Table 2.7: ANCOVA of Woodchuck Kinetic Components of Locomotion before and after Hibernation

Pre- Post- Season Woodchuck Interaction Limb Kinetic component 1 1 Power hibernation hibernation F- p- F- p- F- p- statistic value statistic value statistic value 0.651 0.651 0.230 0.655 2.992 0.155 1.694 0.177 Maximum Fv (0.075) (0.096) 0.927 0.558 0.591 1.042 0.359 1.360 0.383 0.891 0.481 Impulse (0.095) (0.104) 0.716 -4.105 -4.069 0.146 0.720 3.561 0.120 1.178 0.340 Hind Compressive

(0.992) (1.090) 0.428

-74.9676 -62.937 8.524 0.039 4.818 0.076 1.284 0.298 Bend: Caud -

(12.860) (10.539) Tibia 66.999 55.076 10.816 0.027 4.900 0.074 1.374 0.267 Bend: Cran - (11.159) (8.645) 0.899 0.956 10.817 0.043 2.623 0.162 0.657 0.625 Maximum Fv - (0.201) (0.188) 0.382 0.400 1.344 0.327 1.712 0.286 0.666 0.619 Impulse (0.054) (0.110) 0.422 -12.007 -11.004 1.432 0.303 3.842 0.101 1.680 0.170 Compressive (3.639) (2.653) 0.356 -154.410 -128.62 5.689 0.078 3.003 0.152 4.203 0.005 Bend: Caud (36.593) (36.366) 0.481

Fore Radius 133.032 109.603 6.937 0.060 3.700 0.113 4.174 0.006 Bend: Cran (30.047) (31.357) 0.499 -8.995 -8.457 1.248 0.332 0.359 0.828 1.743 0.156 Compressive

(2.123) (1.506) 0.609

-84.108 -70.848 6.988 0.059 4.985 0.071 4.731 0.003 Bend: Caud

Ulna (13.953) (18.211) 0.655 68.767 57.440 8.709 0.044 7.245 0.038 4.331 0.005 Bend: Cran - (11.253) (15.359)

Fig. 2.10: Maximum vertical force (Fv) was significantly greater only in the forelimbs in the posthibernation season (A). There was no difference in fore or hindlimb impulse between seasons (B).

high (β = 0.927) for detecting major effects (25%) in Fv following hibernation in the hindlimbs of woodchucks (Table 2.7). The hypothesis that woodchucks will not change peak Fv is rejected on the basis of the significant findings in the forelimbs in the posthibernation season.

Unfortunately, observed power was low for the remaining non-significant kinetic variables of interest in this study. Considering body weight distribution, each fore and hindlimb analyzed did not change significantly with any factor in this analysis (Table 2.7, Fig. 2.10B). Thus, despite losing considerable mass throughout the course of hibernation (over 20% in some individuals), this change in physical composition did not appear to shift the center of mass during locomotion (Table 2.3).

Peak compressive stresses on the tibia, radius, and ulna during locomotion did not change between seasons (Table 2.7, Fig. 2.11). This is consistent with the third hypothesis that axial compressive stress would not change seasonally. Bending stresses, both compressive (acting in the caudal cortex) and tensile (cranial cortex), however were significantly decreased in the tibia during the posthibernation season compared to prehibernation, favoring the rejection of the second part of the stress hypothesis regarding bending stresses

(Table 2.7). Compressive bending stresses decreased in this bone on average by 16% (p = 0.039) while tensile magnitudes were 18% lower in the posthibernation period (p = 0.027, Table 2.7, Fig. 2.12). No significant individual or interaction effects was observed in the tibia. The ulna also experienced a significant decrease in tensile stresses (p = 0.044) and a nearly significant lower magnitude of compressive bending (p = 0.059, Table 2.7, Fig. 2.13A and B).

This pattern was repeated in the radius as well, although it was not significant in either bending direction (Table 2.7, Fig. 2.13C and D). Both the ulna and radius, however, were observed to have significant differences between each individual animal dependent on season. These changes indicate that woodchucks may be reorienting their bone angle to the ground reaction force and lowering the transverse bending stresses acting on their bones in posthibernation.

Fig. 2.11: Average compressive stress in the radius, ulna, and tibia of woodchucks was not dependent on season.

Fig. 2.12: Both caudal and cranial bending strains in the tibia were significantly reduced in woodchucks following hibernation. Note: Caudal stresses are compressive and are negative.

Fig. 2.13: Seasonal average bending strains in the forearm of woodchucks. Ulnar cranial stresses were significantly lower after hibernation (A). No significant change was observed in the ulnar caudal (B), radial cranial (C), or radial caudal (D) cortices, although they tended to be decreased in posthibernation.

Discussion

Kinematics of Woodchuck Locomotion

This is the first study to investigate directly the effects of hibernation on locomotion. Considering this, there were few studies to draw comparisons to the locomotion pattern observed in woodchucks in relation to seasonal inactivity.

However, research conducted on activity levels and body mass distribution in animals that gain large fat deposits in preparation for food shortages in conjunction with traditional locomotion studies provided suitable information for contrasting data. Considering that the trials in this study were highly controlled and could not account for the transition of these wild animals to that of the locomotion experiment setting, there is no measure of natural activity levels before and after hibernation nor is the emotional state driving the locomotor patterns in the prehibernation season known.

The activity patterns of some animals are documented before they enter into hibernation. For example, woodchucks go underground in October but do not begin to hibernate until early to late November (Davis, 1967b; Zervanos and

Salsbury, 2003; personal data, see Chapter 1). Early entrance into their burrows suggests that woodchucks do become less active during this prehibernation period. Similarly, wild fat-tailed dwarf lemurs (Cheirogaleus medius) significantly decrease nightly travel distance during seasonal fattening (Fietz and Ganzhorn,

1999). These primates, one of the few to hibernate, significantly increase the size of their tail and utilize it as a fat depot in preparation for hibernation. These

findings correlate with the decreased activity observed in fat ground-squirrels before hibernation (Pengelley and Fisher, 1966). The kinematics and kinetics, however, have not been described in any animal in relation to the effects of disuse during hibernation on locomotion.

Woodchucks were found to use the same frequency of symmetrical and asymmetrical gaits between seasons, and did not consistently change their preference for certain gait types following hibernation (with the exception of one individual selecting to trot more during posthibernation). Duty factor, however, was significantly lower in posthibernation despite no change in speed or limb phase. This corroborates, in part, the findings that fat, prehibernation dwarf lemurs travel slower with increased duty factors, and as such chose to trot more than an animal with a slim tail (Young et al., 2007). The "normal" gait preference of these primates is a DS gait, thus the selection of trotting in the individual with a fatter tail mimics the significant seasonal differences for Woodchuck F17 using the slower LS gait less often in the posthibernation season after shedding her prehibernation body mass. It should be noted, however, that the natural continuum of gaits is artificially divided into specific classifications for the purpose of analysis. It is possible that the difference between the LS and trot in F17 were not as defined as these classifications would suggest. In a separate study of fat- tailed dwarf lemurs, speed differences were not observed in fatter animals which is consistent with the overall similar speeds observed in woodchucks across

seasons (Lemelin and Schmitt, 2004). However, duty factor was not reported in these lemurs and could not be compared to woodchuck duty factors.

Overwintering Svalbard rock ptarmigans (Lagopus muta) appear to use a different strategy considering they increase speed and stride frequency while concurrently reducing duty factor and stride length at peak body mass (Lees et al., 2010). Several considerations are given as to why this pattern is observed.

The most probable explanation is the extreme body mass increase (47%) in these bipedal birds instigates the adoption of a more upright posture and pendular form of locomotion (i.e., shifting their COM laterally) at the expense of an aerial phase during running.

Kinetics of Woodchuck Locomotion

With regard to woodchuck body mass distribution, body weight support of the fore and hindlimbs was not dependent on season despite large fluctuations in fat stores (average 17% loss over the course of hibernation). Captive dwarf lemurs were estimated to shift their center of mass (COM) caudally by 12.5% trunk length during periods with enlarged tails (Young et al., 2007). Indeed, lemurs were shown to experience greater hindlimb loading (peak Fv) than the forelimbs when tail mass was increased (Lemelin and Schmitt, 2004). In contrast to the unusual deposition of fat primarily in the tails of dwarf lemurs, woodchucks tend to deposit their fat equally throughout their body, both centrally and peripherally (generally not in their tail, however). Thus, it is not entirely surprising

that there was no observed shift in fore or hind body weight support for woodchucks.

Increased maximum Fv production in the forelimbs of woodchucks following hibernation differs from the pattern found in dwarf lemurs (Lemelin and

Schmitt, 2004). These primates experienced reduced peak Fv in both fore and hindlimbs in the absence of a fatty tail. Raw vertical forces, without being normalized for body weight, are significantly higher in the prehibernation season in both the fore and hindlimbs of woodchucks (not reported). Thus, it is likely that, if adjusted for mass, the difference in Fv would not be significant in fatter- tailed dwarf lemurs.

Woodchucks are similar to other animals in that they experience greater bending strains than axial compressive stresses in their tibia, radius, and ulna

(Biewener, 1983b; Demes and Carlson, 2009; Rubin and Lanyon, 1982). The magnitudes of both compressive and bending strains of the forelimbs were greater than those observed in the hind, as reported for numerous other animals

(Biewener, 1983b; Biewener et al., 1983; Hildebrand, 1976; Jayes and

Alexander, 1978). Unfortunately, there are no records of bone stress during locomotion following prolonged inactivity in other animals. There is a qualitative report of dogs being lame and having limited range of motion up to four weeks after being immobilized for 16 weeks (Kaneps et al., 1997). Similarly, human studies noted that reambulation is limited for several days because of sore soles of the feet following three months bed rest (Spector et al., 2009). These studies

indicate that locomotion was greatly altered after inactivity, and it is reasonable to hypothesize that the bone stresses would also be different following inactivity.

Bending stresses were significantly reduced in the tibia and cranial cortex of the ulna of woodchucks following hibernation. It is assumed that this was a result of a reorientation of the angle of the limbs in relation to the ground reaction force rather than because of lameness. Dwarf lemurs with fat tails greatly increased fore and hindlimb excursion and retraction angles during locomotion compared to their thin-tailed counterparts (Young et al., 2007). This was hypothesized to essentially provide greater stability to the fatter animal while navigating its environment. Visually, woodchucks did not appear to be lame following hibernation. One individual (CR12), however, did develop an abscess over a previously healed metatarsal injury. Exclusion of this animal did not result in vastly different seasonal results of any variable, kinematic or kinetic, so it was retained in the analysis. Despite having preference for slower gaits (LS and

LSSF), CR12 did not significantly change gait types depending on season, and as such it could not be ruled out that this individual fell within the normal range of gait selection in woodchucks.

There was quite a bit of variation between individuals for several variables of interest. For instance, the nearly significant preference of asymmetrical gaits of M16 in the prehibernation period limited the seasonal analysis of symmetrical gaits in this individual. On closer inspection, no significant difference was identified within the other variables on the basis of gait symmetry in this

individual. Considering this and the potentially reduced woodchuck sample with the exclusion of this animal, it was determined that the analysis of symmetrical and asymmetrical gaits together was appropriate. It cannot be ruled out that with a larger sample there would be significant kinetic differences between symmetrical and asymmetrical gaits (e.g. greater vertical force production with increasing speed) as has been previously described (Demes et al., 1994).

On the other hand, lack of apparent significance between gait symmetries could also be a mechanism utilized to compensate for additional weight in the prehibernation season. Weighted horses transitioned from a trot to a gallop at slower speeds, but at similar ground reaction forces produced by unweighted horses (Farley and Taylor, 1991). This indicates that horses transitioned to gallops earlier in the gait transition period to avoid larger stresses experienced at fast trots. Similar patterns of force avoidance in slower gallops may have been employed by larger woodchucks in the prehibernation season and could account for the lack of statistical findings between symmetrical and asymmetrical gaits of

M16.

With regard to the experimental design of this study, several assumptions were made to estimate bone stresses in single-step analyses (Biewener, 1983b).

First, it was expected that the digitized center of pressure (COP) of the mid-paw accurately reflected the point at which the ground reaction force (GRF) acted during the step. Second, it was assumed that the joint was accurately located when digitizing videos. This task was quite difficult in the prehibernation animals

considering their additional fat mass and loose skin, both of which tended to obscure joint landmarks. Furthermore, muscle moments were measured from the radiographs as accurate reflections of the true moment at peak vertical force production. Following on that, it was assumed that peak Fv correlated to peak axial compressive and bending strains. Fifth, bone angle was expected to be accurately calculated in relation to the actual GRF. And finally, loads were expected to be equally distributed between the radius and ulna. In contrast, the fibula was removed from all analyses because it is not considered to be a weight- bearing bone.

It is apparent, in light of these assumptions, that there are significant sources of potential error in estimating bone stress in locomotion studies.

Despite all of this, in comparison to in vivo strain gauges, kinematic representation of locomotion (e.g., radiographs, photographs, cine, videos) in conjunction with ground reaction forces obtained from a forceplate are considered to effectively estimate bone stresses (Biewener et al., 1983).

Considering the low power achieved even at large effect changes (25%), the conclusions of this kinetic analysis are tentative and we cannot definitively comment on the biological importance of these findings.

Finally, this report addresses only those forces experienced in forward locomotion and does not consider forces associated with non-steady state locomotion. Scaled acceleration, taking into account the body mass of the individual and gravitational acceleration, of the single-step trials of this study fell

within the range of -0.22 to 0.197 meters/second. This range is in accordance with the accelerations of dogs (-0.2 to 0.2) examined during trotting (Lee et al.,

1999). However, breaking and accelerating impulses of varying magnitudes were recorded during woodchuck locomotion trials. Such impulses cause higher strains in certain distal bone elements of the limbs (Biewener et al., 1983).

Analysis of these specific strains were not addressed in this study, but it should be noted that the horse radius was not impacted by changes in acceleration

(Biewener et al., 1983). Furthermore, the forces produced during non-steady locomotion are likely to be biologically important for withstanding greater magnitudes of stresses, including torsional stresses on bone, experienced during abrupt changes in directions, accelerations, etc. as predator avoidance strategies. Indeed, the caudal cortex of the radius of goats experienced significantly greater compressive bending stresses during acceleration and deceleration (i.e., non-steady locomotor activities) when jumping, turning, and galloping (Moreno et al., 2008).

Decreased bending strains during locomotion following physical inactivity associated with hibernation may be a product of the reorientation of the limbs liberated from the excess baggage of prehibernation body fat. In light of the intense breeding season woodchucks experience during posthibernation, it is tentatively concluded that the differences in bending strains reported here do not negatively affect the skeleton as a whole nor reflect on weakened limb elements.

The biological significance, however, of this difference in bending stresses

cannot be definitively determined at this time. Further investigations of bone properties and metabolism between seasons are necessary in order to identify in a better manner the effects of hibernation on bone and the projected consequences to woodchuck locomotor behaviors.

CHAPTER 3

HIBERNATION DOES NOT REDUCE CORTICAL BONE DENSITY, AREA OR SECOND MOMENTS OF INERTIA IN WOODCHUCKS

Introduction

It is well known that bone is lost in humans and many other mammals during extensive periods of disuse (i.e., mechanical unloading; Aguirre et al.,

2006; Bloomfield et al., 2002; Lang et al., 2004; Sugiyama et al., 2002; Weiler et al., 2006; Zerwekh et al., 1998). During inactivity, bone resorption occurs at a higher rate than bone formation, and the uncoupling of these processes ultimately leads to degradation of bone matrix (Seibel et al., 2006). As the skeleton is depleted of its mineral supplies, bone density and area decrease and the ability to absorb energy (i.e., strength) and transmit force (i.e., stiffness) are reduced (Biewener, 1990; 2003b; Currey, 2002b; Seeman, 2008). The result is a compromised skeleton more prone to injury (Biewener, 1990; Seeman, 2008;

Turner and Burr, 1993). Because animals rely on their skeletons to resist fracture, the attenuation of bone performance resulting from extensive resorption could decrease survivability (Biewener, 1990; Currey, 2002b).

Hibernating mammals experience extended periods of inactivity annually, but the extent to which their skeletons are compromised, if at all, during hibernation remains unclear. A hibernator’s survival would likely be adversely

impacted if skeletal integrity was compromised by extended periods of inactivity and reduced nutrient intake. It would be beneficial for hibernating animals to physiologically sustain the capacity of their bones to withstand functional stresses and avoid failure once activity resumes after hibernation.

Several studies have found that bears maintain a balance between bone resorption and formation processes that prevent annual losses in bone at a time when other body functions (i.e., metabolism) are decreased (Donahue et al.,

2006a; Donahue et al., 2003a; Floyd et al., 1990; McGee-Lawrence et al., 2009b;

McGee et al., 2008; Overstreet et al., 2003). Frogs preserve their skeletal integrity during nine months of aestivation (Hudson et al., 2004) and some ground squirrels (Ictidomys tridecemlineatus and Callospermophilus lateralis) maintain bone properties after hibernation (McGee-Lawrence, 2009; Utz et al.,

2009). Interestingly, closely-related and the same species of ground squirrels were found to experience seasonal disuse osteoporosis (Haller and Zimny, 1977;

Mayer and Bernick, 1958; 1963; Richardson et al., 1961; Zimmerman et al.,

1976; Zimny et al., 1973). Likewise, other small hibernating animals, such as hamsters and bats, are thought to lose bone during hibernation (Doty and Nunez,

1985; Haller and Zimny, 1977; Kayser and Frank, 1963; Krook et al., 1977;

Kwiecinski et al., 1987; Nunez et al., 1969; Steinberg et al., 1979; 1980; 1981;

1986; Whalen et al., 1972). These differing results suggest that the relationship between bone loss and formation varies across hibernators and cannot be generalized from a few studies of hibernating species.

Several hibernation studies have used bone serum markers, histology, three-point bending, and/or ash fraction techniques to define bone maintenance patterns in hibernating animals. We use peripheral quantitative computed tomography (pQCT) to quantify changes in the mechanical properties of bone between seasons in woodchucks (Marmota monax). Specifically, pQCT can determine cortical and trabecular bone density, size, and shape (Dougherty,

1996; Griffith et al., 2010; Ito, 2005; Keaveny, 2010; Lang et al., 1997; Wachter et al., 2001; Wakabayashi et al., 2003). These morphological data can be applied to estimate bone strength, based on geometry, in various loading regimes. Although pQCT has broad applications, few studies have utilized this or other imaging technologies to assess regional changes in bone cross-sections for hibernating animals. In the best developed study, microcomputed tomography was used with histology to investigate grizzly bear bone density from cores taken at the ilium, distal femur, and calcaneus before and after hibernation

(McGee-Lawrence et al., 2009b). They found no significant indications of bone loss after hibernation. Alternatively, radiographic imaging in hamsters, ground- squirrels, and bats suggest bone is lost following hibernation (Kayser and Frank,

1963; Whalen et al., 1972; Zimny et al., 1973).

We examine woodchuck (Marmota monax) long bone and mandibular cross-sections using pQCT to determine the effects of hibernation on bone density, area, bone area fraction (B.AR/T.AR), and estimated bending resistance ability. Members of the genus Marmota (including woodchucks and marmots)

are the largest mammalian hibernators to significantly decrease their body temperature (to 1-2˚C above ambient temperatures), remain non-responsive to touch (Hamilton, 1934), and immobile in torpor bouts for weeks at a time

(Armitage, 2003; Benedict and Lee, 1938; Lyman et al., 1982; Wang, 1987).

This pattern is similar to ground squirrels, bats, and other small hibernators (Buck and Barnes, 2000; Geiser, 1995; Hock, 1951; Kortner and Geiser, 2000).

Compared to marmots and woodchucks, bears are much larger in body size, maintain a relatively high body temperature, can be quickly aroused, and change position on a regular basis during torpor bouts (Craighead and Craighead, 1972;

Folk, 1974; Lyman et al., 1982; Morgan, 1939; Nelson et al., 1983; Wang, 1987;

Zhao et al., 2010). Thus, it remains to be tested whether the periodic activity between torpor bouts, the relatively larger size, or the metabolic state seen in bears helps to prevent bone loss during hibernation.

Woodchucks are an interesting species to explore further the role of disuse and nutrient deprivation on their skeleton because of their large size relative to other rodent hibernators and propensity to deeply hibernate. Given the contradictory results of how hibernation affects closely-related ground squirrels, woodchucks may experience no change in bone similar to bears or they may lose bone as suggested for other small hibernators. We test the null hypothesis that no change will occur in relative bone area, density, or load resistance ability following hibernation. The alternative hypothesis suggests that bone will decrease significantly during hibernation resulting in disuse

osteoporosis. Such a loss of bone density and area would reduce the skeleton’s load resistance ability and may affect survival.

Materials and Methods

Sample

We analyzed 100 woodchuck (Marmota monax) skeletons collected in upstate New York from 1931 to 1956 by W. J. Hamilton and housed at the

Cornell University Museum of Vertebrates. We grouped specimens based on the original museum collection date, known to approximate time of death of each individual, by sex and age (Table 3.1). Skeletal age of each specimen was taken from museum records identified and assigned by Hamilton as subadult (one year or younger) or adult based on his previously-documented morphological criteria

(Hamilton, 1934). Complete skeletons were preferred; however, some skeletons only had one or two representative bones, leaving variable sample sizes for each bone (Table 3.1). Males and females, as well as subadults and adults, were initially examined together.

Mandibles were divided into prehibernation (September – October), posthibernation (March – April) and summer active (May – August) groups.

While this temporally-restricted grouping represents a preferred separation by months, the small sample of long bones forced us to include August specimens in prehibernation and May specimens in posthibernation groups for the femur, tibia and humerus (Table 3.1). By including bones for extended periods

posthibernation, particularly for the long bones, we potentially sample bones that changed during normal activity after hibernation. We examined differences in bone measures by months within pre- and posthibernation groups, respectively, and found no changes in long bone (or mandibular) measurements across months for either group (ANOVA, α=0.05).

Table 3.1: Woodchuck Skeletal Samples for Each Bone and Season

Prehibernation (N) Posthibernation (N) Summer (N) Bone Sex Age Sex Age Sex Age

F1 M2 S3 A4 Total F M S A Total F M S A Total Humerus 11 7 9 9 18 4 8 4 8 12 - - - - - Femur 10 10 10 10 20 3 8 3 8 11 - - - - - Tibia 10 8 11 7 18 3 8 3 8 11 - - - - - Mandible 11 7 13 5 18 23 16 20 19 39 13 19 11 21 32

1Female, 2Male, 3Subadult, 4Adult.

Measurements

We scanned femora, tibiae, humeri and mandibles using a peripheral quantitative microcomputed tomography XCT Research M921010 scanner

(Norland/Stratec) at a slice thickness of 0.25 mm and voxel size of 0.07 mm

(giving a final resolution of 70 μm). All scans were acquired against a standard cone phantom (XCT Research M) with known densities. Long bones were scanned at the diaphyseal midline (defined as 50% of the total bone length) (Fig.

3.1A, B). We scanned femoral and tibial metaphyses 1 mm proximal to the distal epiphyseal line (Fig. 3.1A, C). Humeral metaphyses were scanned 1 mm distal

Fig. 3.1: QµCT scan locations for the long bones (A-C) and mandibles (D-F) of woodchucks. Diaphyses were scanned at 50% of the long bone lengths (red lines indicated by D) (A) providing a mid-shaft cross-sectional slice for analysis (B). Distal metaphyses were scanned one millimeter proximal to the epiphyseal line on the tibia and femur, and one millimeter distal to the epiphyseal line of the proximal humerus (red lines indicated by M) (A). Trabeculae filled the majority of each metaphyseal slice (C). The mandibles were scanned perpendicular to P4 (D) providing a cross-sectional scan including P4 and incisor roots as well as variable amounts of trabeculae (E). We digitally removed the teeth, roots, and trabeculae within the mandible and added a 1-pixel-wide line to close the mandible for cortical bone analysis prior to thresholding (the perpendicular lines depict principal axes generated by analytical software; F). Scale bars = 1cm.

to the proximal epiphyseal line (Fig. 3.1A). We scanned mandibles perpendicular to the corpus through the midline of the fourth premolar (P4) (Fig. 3.1D, E).

We analyzed long bone cross-sectional scans using XCT540

(Norland/Stratec) software to calculate cortical areas (CA) and apparent mineral densities for cortical (CDen) and trabecular (TDen) bone. Moments of inertia, or the ability of an object to resist deformation in specific directions, were estimated for the long bones using XCT540 software and for the mandible using

MomementMacroJ v1.3 (Warfel, 1997) in ImageJ v. 1.44. We estimated resistance to mediolateral bending in the long bones and mandible (Ixx), anteroposterior in the long bones and superoinferior resistance to bending in the mandible (Iyy), and the polar area moment of inertia (J) based on a neutral axis passing through the centroid of the section (Table 3.2).

We calculated bone area fraction (B.Ar/T.Ar) in the long bone metaphyses to estimate the percentage of trabecular bone volume within the medullary cavity

(Table 3.2; Johnson et al., 2000; Oka et al., 2002). Regions of interest (ROI) within the metaphyses were created by drawing the largest circle inside the medullary cavity of the metaphyseal scan (i.e., inside the cortical and subcortical margins; Damilakis et al., 2001; Fleming et al., 2004; Taguchi et al., 1997).

Using the Bone J Volume Fraction plugin for ImageJ (Doube et al., 2010), we calculated B.AR/T.AR by dividing the number of thresholded trabecular bone voxels by total voxels in the ROI.

Table 3.2: Cross-sectional, Density and Mechanical Measurements

Size adjusted Bone property Units Mechanical significance estimate1 2 0.5 Cortical area (CA) mm Area of cortical bone in section (CA )/L

3 Volume of cortical bone in Cortical density (C ) mg/cm N/A Den section 3 Volume of trabecular bone in Trabecular density (T ) mg/cm N/A Den section Percentage of trabecular bone Bone area fraction (B.Ar/T.Ar) % N/A area

Area moment of inertia about 4 Resistance to mediolateral 0.25 mm (Ixx )/L horizontal (x) axis (Ixx) bending (long bones and jaw)

Resistance to anteroposterior Area moment of inertia about 4 0.25 mm (long bones)/ superoinferior (I )/L vertical (y) axis (I ) yy yy (mandible) bending

Polar area moment of inertia (J) mm4 Resistance to torsion (J0.25)/L

1L = Total length of respective bone.

The variable presence of trabeculae and portions of the teeth across mandibular scans questioned their consistent contribution to area and moment of inertia measures. We digitally removed the tooth crown, roots (including those of the incisors along the ventral surface of the interior of the mandible), and trabeculae from mandibular cross-sections at P4 (Fig. 3.1E, F) using Adobe

Photoshop CS3 to analyze the remaining cortical bone (Daegling and Grine,

1991; Dumont and Nicolay, 2006; Organ et al., 2006; Vinyard and Ryan, 2006).

A 1-pixel-wide line was drawn to connect the lingual and buccal margins of the remaining mandibular cortical bone to facilitate measurement (Daegling, 1993;

Daegling and Grine, 1991); Fig. 3.1F). Final images were analyzed using

MomementMacroJ v1.3 (Warfel, 1997) in Image J to calculate cortical area and

bending moments of inertia (Ixx, Iyy; Table 3.2). It should be noted, that while the teeth contribute to the structural load resistance of the mandible the exact nature of this contribution remains elusive (Daegling, 1989; Daegling and Hylander,

2000; Daegling et al., 1992; Plavcan and Daegling, 2006).

Statistical Analysis

We used multivariate ANOVAs (SPSS 13.0) to test the null hypothesis that woodchucks do not experience a change in relative bone area, density,

B.AR/T.AR, or relative moments of inertia during hibernation. Prior to analysis,

0.5 0.25 0.25 we size adjusted area and moments of inertia by dividing CA , Ixx , Iyy , and

J0.25 by the relevant bone length (Daegling, 2001; Table 3.2). Given that bone lengths increased significantly after hibernation in both subadults and adults

(Table 3.3), analysis of size-adjusted data minimizes the effect of increased age and size in posthibernation animals and effectively makes our statistical tests more conservative. Bone density (mg/cm3) and B.AR/T.AR (% total area) are already dimensionless and were not size adjusted. Only size-adjusted or dimensionless data were analyzed. We initially included age and sex as cofactors with hibernation in the multi-way ANOVA, but co-factors were removed from the final analysis of a given bone section when not initially significant (Berry and Feldman, 1985).

Table 3.3: Two-way ANOVA Comparing Total Bone Length Pre- and Posthibernation in Subadult and adult Woodchucks

Subadult Avg. Total Length 1 Adult Avg. Total Length1 F-statistic (p-value) Bone Pre- Post- Pre- Post- hibernation hibernation Summer hibernation hibernation Summer Hibernation Age 62.74 65.00 66.96 71.15 13.008 33.647 - - Humerus (3.757) (1.955) (3.745) (2.506) (0.001) (0.0003) 71.40 74.69 74.7 81.14 23.327 23.382 - - Femur (3.497) (3.477) (4.45) (1.875) (0.0001) (0.0009) 69.43 71.44 71.98 76.41 11.413 15.564 - - Tibia (3.316) (2.549) (4.063) (2.401) (0.001) (0.0002) 60.33 60.7 57.99 61.18 64.7 63.03 5.699 21.63 (3.528) (2.064) (2.729) (2.841) (2.996) (2.746) (0.005) (0.0001) Mandible 1Data represent mean total bone length (mm) and (standard deviation).

Statistical significance was determined using a Bonferroni adjustment based on examining four bones and final α = 0.0125 (0.05/4) was considered significant (Quinn and Keough, 2002). An additional Tukey post-hoc test (α =

0.05) was applied to the mandibular analysis to determine significant differences among the three seasonal groups of this specific bone (a benefit of the greater sample size).

Because our initial hypothesis predicts no change in relative bone measures, we calculated statistical power in appropriate ANOVA designs to minimize the likelihood of Type II statistical errors. Following Cohen (1977), a power of ≥ 0.8 (1-β) is considered appropriate. We estimated large effect sizes as 10% change and medium effect sizes as 5% change based on percentage bone density reduction in human bed rest studies (LeBlanc et al., 1990;

Shackelford et al., 2004).

Finally, to evaluate trends in average differences between pre- versus posthibernation groups, we performed a Sign test (α=0.05) to determine whether bone parameters were on average significantly larger or smaller after hibernation. Initially, we considered all bone measures followed by specific groupings including all cortical variables (diaphyseal and metaphyseal measurements) and trabecular metaphyseal variables.

Results

On average, woodchucks do not experience significant bone loss throughout hibernation. Contrary to our alternative hypothesis, bone typically is either not significantly changed or it is relatively larger and/or denser after hibernation. Diaphyseal cortical density (CDen) was significantly greater in the humerus, femur and tibia following hibernation (Table 3.4, Fig. 3.2A). Relative mandibular cortical area differed significantly and based on Tukey post-hoc

0.5 comparisons, mandibular CA /L was significantly greater posthibernation compared to both summer and prehibernation periods (Table 3.4).

The single exception that potentially supports the alternative hypothesis of bone loss following hibernation is a tendency toward decreased trabecular bone in the metaphyses of the long bones. Trabecular density (TDen) in the humerus was noticeably decreased posthibernation, and B.AR/T.AR in the humerus was significantly reduced after Bonferroni adjustment (Table 3.5, Fig. 3.3A, B).

Woodchuck long bones do not differ significantly in size-adjusted bending and torsional resistance ability before and after hibernation (Table 3.6 and 3.7).

Table 3.4: Seasonal Measurements of Bone and ANOVA Comparisons across Hibernation Groupings for Diaphyseal and Mandibular Cortical Bone (Prehibernation and Posthibernation)

ANOVA ANOVA Bone Property Pre- Post- F- p- hibernation1 hibernation1 Summer1 statistic2 value3 Power4 Absolute

16.11 (3.69) 20.14 (4.20) -

5 Cortical Area Adjusted 0.0614 0.0646 0.918 (mm2) (0.0036) (0.0054) - 2.788 0.107 1352.49 1392.33 - Humerus Cortical Density (mg/cm3) (45.22) (33.59) - 8.323 0.008 Absolute Cortical 15.64 (3.85) 20.30 (6.48) -

Area Adjusted 0.0536 0.0561 0.684 5 (mm2) (0.0045) (0.0069) - 0.395 0.535 1355.56 1395.83 - Femur Cortical Density (mg/cm3) (32.52) (21.99) - 12.969 0.001 Absolute Cortical 14.77 (2.84) 17.23 (3.07) - Area Adjusted 0.0536 0.0551 0.995

2 5 (mm ) (0.0028) (0.0036) - 0.444 0.512 1338.28 1385.36 - Tibia Cortical Density (mg/cm3) (37.36) (22.54) - 17.599 0.0003

5 Absolute 24.49 30.13 25.57 (6.44) (7.73) (7.22) Cortical - Area Adjusted 0.0794 0.0868 0.0804 Mandible (mm2) (0.0113)* (0.0083)*┼ (0.0096) ┼ 7.471 0.001

1Absolute and size-adjusted values for means (standard deviations) across sexes and ages per seasonal grouping. 2The F-statistic is calculated from an ANOVA comparing size-adjusted variables.

3Bold values are significant at the α = 0.0125 level after Bonferroni adjustment.

4Power: Italicized values indicate that sample sizes provide power ≥ 0.8 to differentiate a large effect change in bone measures between groups. Large effects were estimated as a 10% change in value based on percentage bone density changes in human bed rest studies (LeBlanc et al., 1990; Shackelford et al., 2004). 5Two-way ANOVA including age as a factor. *Significant difference among prehibernation vs. posthibernation (p = 0.045) after Tukey post-hoc test. ┼ Significant difference among posthibernation vs. summer (p = 0.009) after Tukey post-hoc test.

Fig. 3.2: Annual variation in cortical density and mandibular resistance to bending in woodchucks. Long bones were classified into two groups: Prehibernation (August – October) and posthibernation (March – May). Mandibles, because of a larger sample size, afforded the possibility to classify three seasons: Summer (May – August), prehibernation (September – October), and posthibernation (March – April). Diaphyseal cortical density of all long bones (A) and observed pattern of relative mandibular resistance to mediolateral (Ixx) and superoinferior (Iyy) bending (B) were significantly greater after hibernation. There was a slight, but significant, increase in the ability of the mandible to resist loads following hibernation indicating that bone morphology was not negatively influenced by seasonal inactivity.

Fig. 3.3: Annual variation in metaphyseal trabecular densities and bone area fraction (B.Ar/T.Ar) in woodchucks. Metaphyseal trabecular density did not differ significantly between seasons (A). B.Ar/T.Ar decreased significantly in the metaphysis of the humerus following hibernation (B).

Table 3.5: Seasonal Measurements of Bone and ANOVA Comparisons across Hibernation Groupings for Metaphyseal Cortical and Trabecular Bone (Prehibernation and Posthibernation)

Pre- Post- ANOVA ANOVA 4 Bone Property 1 1 Power hibernation hibernation 2 3 F-statistic p-value Absolute 18.86 22.34 (5.19) (5.46)

Cortical Area Adjusted 0.0661 0.0679 0.853

5 (mm2) (0.0053) (0.0072) 0.382 0.542 822.88 878.43 0.684 Cortical Density (mg/cm3) (94.54) (89.80) 2.065 0.163

Humerus 42.07 37.28 - B.Ar/T.Ar (%) (3.52) (5.61) 8.33 0.007 166.57 110.00 0.106 Trabecular Density (mg/cm3) (67.45) (64.67) 4.759 0.038 Absolute 18.86 22.31 (4.98) (6.18) Cortical Area Adjusted 0.0583 0.0589 0.889

6 (mm ) (0.0044) (0.0064) 0.004 0.952 714.54 773.35 0.46 Cortical Density (mg/cm3) (107.10) (103.88) 6.72 0.016 Femur 40.72 39.47 0.587 B.Ar/T.Ar (%) (5.38) (4.89) 0.416 0.524 125.40 111.02 0.089 Trabecular Density (mg/cm3) (58.12) (61.25) 0.046 0.832 Absolute 13.96 17.44 (4.14) (4.23) Cortical Area Adjusted 0.0515 0.0552 0.803 2

(mm ) (0.0047) (0.0061) 3.121 0.089 7 820.00 884.19 0.554

Cortical Density (mg/cm3) (110.82) (102.81) 4.211 0.05 Tibia 49.39 48.39 0.999 B.Ar/T.Ar (%) (2.09) (3.01) 1.161 0.291 297.19 296.32 0.511 Trabecular Density (mg/cm3) (38.90) (42.80) 0.002 0.996 1Absolute and size-adjusted values for means (standard deviations) across sexes and ages per seasonal grouping. 2The F-statistic is calculated from an ANOVA comparing size-adjusted variables. 3Bold values are significant at the α = 0.0125 level after Bonferroni adjustment.

5Two-way ANOVA including age as a factor.

6Multiway ANOVA including age and sex as factors.

7 One-way ANOVA for season as age and sex were not initially significant.

Table 3.6: Seasonal Measurements of Mechanical Properties of Bone and ANOVA Comparisons across Hibernation Groupings for Long Bone Diaphyses and Mandible (Prehibernation and Posthibernation)

Pre- Post- 1 4 Bone Property 1 1 Summer ANOVA ANOVA Power hibernation hibernation F-statistic2 p-value3 79.46 128.73 Absolute (27.75) (53.34) - 0.0455 0.0480 0.985 4

Ixx (mm ) Adjusted (0.0022) (0.0035) - 4.048 0.055

5 42.11 64.93 Absolute (15.60) (28.21) - 0.0388 0.0404 0.942 4

Humerus Iyy (mm ) Adjusted (0.0020) (0.0032) - 0.165 0.688 121.57 193.66 Absolute (43.00) (80.58) - 0.0506 0.0531 0.996 J (mm4) Adjusted (0.0025) (0.0039) - 0.105 0.749 51.82 78.96 Absolute (20.00) (46.87) - 0.0362 0.0367 0.909 4

Ixx (mm ) Adjusted (0.0022) (0.0037) - 0.028 0.868

5 63.97 102.45 Absolute (27.16) (66.63) - 0.0380 0.0390 0.933

Femur 4 Iyy (mm ) Adjusted (0.0026) (0.0042) - 0.001 0.975 115.79 181.42 Absolute (46.71) (113.14) - 0.0442 0.0450 0.854 J (mm4) Adjusted (0.0028) (0.0046) - 0.003 0.958 48.78 68.40 Absolute (15.31) (23.41) - 0.0369 0.0551 0.997 4 Ixx (mm ) Adjusted (0.0028) (0.0036) - 0.394 0.536

29.59 36.04 5 Absolute (8.55) (10.55) - 0.0325 0.0324 1.000** Tibia 4 Iyy (mm ) Adjusted (0.0013) (0.0016) - 0.308 0.584 78.36 104.45 Absolute (23.36) (33.36) - 0.0415 0.0422 1 J (mm4) Adjusted (0.0016) (0.0022) - 0.063 0.804 378.80 535.72 431.20

Absolute (184.96) (231.95) (186.44)

5 0.0713 0.0754 0.0727 - 4 Ixx (mm ) Adjusted (0.0064)* (0.0052)* (0.0050) 5.055 0.009 143.25 194.44 141.04

Absolute (57.91) (83.12) (51.79) Mandible 0.0562 0.0587 0.0554 - 4 ┼ ┼ Iyy (mm ) Adjusted (0.0036) (0.0042) (0.0033) 7.655 0.001 1Absolute and size-adjusted values for means (standard deviations) across sexes and ages per seasonal grouping. 2The F-statistic is calculated from an ANOVA comparing size-adjusted variables. 3Bold values are significant at the α = 0.0125 level after Bonferroni adjustment. 4Power: Italicized values indicate that sample sizes provide power ≥ 0.8 to differentiate a large effect change in bone measures between groups. Large effects were estimated as a 10% change in value based on percentage bone density changes in human bed rest studies (LeBlanc et al., 1990; Shackelford et al., 2004). 5Two-way ANOVA including age as a factor. *Significant difference among prehibernation vs. posthibernation (p = 0.019) after Tukey post-hoc test. ┼ Significant difference among posthibernation vs. summer (p = 0.002) after Tukey post-hoc test. ** Power reported as ≥ 0.8 at medium effect change (5%).

Fig. 3.4: Relative diaphyseal cortical area (A) and metaphyseal cortical density (B) tended to be larger in each bone following hibernation.

0.25 Relative mandibular resistance to horizontal bending (Ixx /L) was significantly larger posthibernation compared to prehibernation (Table 3.6, Fig. 3.2B).

Across all area and density measures (N = 19), we did not see a significant shift in average values as 13 measures increased posthibernation, while 6 decreased (Sign test, p = 0.17). In specific bone measures, Sign tests revealed significant differences in averages across diaphyseal and metaphyseal cortical variables combined (13 of 13 increased posthibernation; p = 0.0002), across diaphyseal measures (7 of 7 increased posthibernation; p = 0.016; Fig.

3.2A; Fig. 3.4A), and metaphyseal cortical measures (6 of 6 increased posthibernation; p = 0.031; Fig. 3.4B). Metaphyseal trabecular averages

exhibited the opposite trend with averages of all 6 measures decreasing posthibernation (p = 0.031; Fig. 3.3A, B). Mechanical indices followed the results for area and density measures with average diaphyseal indices tending to be larger posthibernation (10 of 11; p = 0.012) and metaphyseal averages (that include trabeculae) decreasing posthibernation (8 of 9; p = 0.039). Collectively, these tests support the ANOVA results suggesting that cortical bone is maintained or potentially increased on average posthibernation while trabecular bone may be slightly reduced over this time.

Age

Adult woodchucks are larger on average than subadults in all comparisons across the skeletal sample (Fig. 3.5; see also Table 3.3). Relatively few of these comparisons, however, reached statistical significance after Bonferroni adjustment (Table 3.8). Subadults did have significantly smaller humeral diaphyseal cortical densities, femoral metaphyseal cortical areas, mandibular cortical areas, and mandibular resistance to bending (Ixx). In all bones except the tibial metaphysis, age presented at least one significant effect or interaction effect (interaction data not shown). While subadults tended to have reduced bone properties compared to adults, they also tended to increase more rapidly during hibernation and often reached adult values posthibernation (Fig. 3.5).

Fig. 3.5: Seasonal differences in diaphyseal cortical density between adult and subadult woodchucks. Before hibernation, adults had greater bone than subadults on average; however, subadults continued to grow despite inactivity during hibernation to reach near- adult levels of cortical bone density by the end of the season.

Table 3.7: Seasonal Measurements of Mechanical Properties of Bone and ANOVA Comparisons across Hibernation Groupings for Long Bone Metaphyses (Prehibernation and Posthibernation)

Pre- Post- 4 Bone Property Power hibernation1 hibernation1 ANOVA ANOVA F-statistic2 p-value3 432.73 501.84 Absolute (167.38) (174.56) 0.0695 0.0677 0.967 4

Ixx (mm ) Adjusted (0.0045) (0.0050) 0.766 0.39

5 366.58 505.98 Absolute (163.34) (193.85) 0.0665 0.0676 0.952 4

Humerus Iyy (mm ) Adjusted (0.0052) (0.0049) 0.247 0.623 799.30 1007.82 Absolute (324.23) (358.33) 0.0810 0.0805 0.958 J (mm4) Adjusted (0.0055) (0.0057) 0.043 0.838 479.23 601.47 Absolute (127.32) (274.75) 0.0636 0.0614 0.991 4

Ixx (mm ) Adjusted (0.0036) (0.0053) 2.81 0.107

6 777.64 1012.82 Absolute (208.02) (595.43) 0.0719 0.0694 0.905

Femur 4 Iyy (mm ) Adjusted (0.0043) (0.0068) 5.071 0.034 1256.87 1614.28 Absolute (322.25) (863.79) 0.0811 0.0783 0.958 J (mm4) Adjusted (0.0046) (0.0072) 4.348 0.048

Absolute 160.89 (52.18) 179.54 (64.47) 0.0503 0.0482 0.996 4 Ixx (mm ) Adjusted (0.0031) (0.0034) 2.28 0.105

7 Absolute 206.43 (65.81) 228.26 (63.36) 0.0535 0.0515 0.998

Tibia 4 Iyy (mm ) Adjusted (0.0037) (0.0031) 2.378 0.135 367.32 407.80 Absolute (114.84) (126.79) 0.0618 0.0594 0.988 J (mm4) Adjusted (0.0040) (0.0038) 2.769 0.108

1Absolute and size-adjusted values for means (standard deviations) across sexes and ages per seasonal grouping. 2The F-statistic is calculated from an ANOVA comparing size-adjusted variables. 3Bold values are significant at the α = 0.0125 level after Bonferroni adjustment.

4Power: Italicized values indicate that sample sizes provide power ≥ 0.8 to differentiate a large effect change in bone measures between groups. Large effects were estimated as a 10% change in value based on percentage bone density changes in human bed rest studies (LeBlanc et al., 1990; Shackelford et al., 2004). 5Two-way ANOVA including age as a factor. 6Multiway ANOVA including age and sex as factors. 7One-way ANOVA for season as age and sex were not initially significant.

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Table 3.8: Significant Differences between Adults and Subadults Pre- and Posthibernation

F- p- Bone Property statistic value1 Humeral Diaphyseal Cortical Density (mg/cm3) 8.599 0.007 Femoral Metaphyseal Cortical Area (mm2) 7.661 0.011 Mandibular Cortical Area (mm2) 15.885 0.0002 4 Mandibular Ixx (mm ) 17.883 0.0006 1Bold values are significant at the α = 0.0125 level after Bonferroni adjustment.

When subadults are excluded from the analysis rather than including age as a factor in the ANOVA, adult comparisons follow the previous pattern showing no significant difference in relative bone measures pre- versus posthibernation

(see Tables 3.9-3.12). Although we have reduced power when looking at only adults, relative Iyy in the mandible was significantly greater post hibernation and a

Sign test indicates that adults tend to increase average cortical areas and densities in both diaphyses and metaphyses of the long bones post hibernation

(11 of 13 increased posthibernation; p = 0.023). When subadults are removed, we no longer observe a significant decrease in B.AR/T.AR for the humeral metaphysis after Bonferroni adjustment. Humeral trabecular density significantly decreases following hibernation and adults tend to decrease average trabecular measures in the metaphyses (6 of 6 reduced posthibernation; p = 0.031).

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Table 3.9: Seasonal Measurements of Adult Bone and ANOVA Comparisons across Hibernation Groupings for Diaphyseal and Mandibular Cortical Bone (Prehibernation and Posthibernation)

ANOVA ANOVA Pre- Post- 1 4 Bone Property 1 1 Summer F- p- Power hibernation hibernation statistic2 value3

Absolute 17.80 21.63 (3.86) (3.03) - Cortical Area Adjusted 0.063 0.065 0.828 (mm2) (0.004) (0.004) - 1.87 0.192

Humerus 1383.47 1397.08 15 Cortical Density (mg/cm3) (44.63) (31.39) - 0.515 0.484 Absolute 16.94 22.16

(4.40) (6.68) - Cortical Area Adjusted .055 .058 0.379 (mm2) (.006) (.008) - 0.87 0.365

Femur 5 1374.74 1400.11 1 Cortical Density (mg/cm3) (34.47) (22.10) - 3.244 0.91 Absolute 15.09 18.21

(2.94) (2.70) -

Cortical Area Adjusted 0.054 0.056 0.867

(mm2) (0.003) (.004) - 1.306 0.274 Tibia 5 1351.94 1389.25 1 Cortical Density (mg/cm3) (39.77) (25.03) - 4.869 0.046

Absolute 27.67 33.88 28.93 (4.32) (6.79) (6.17) Cortical Area 0.087 0.090 0.085 0.976 Mandible (mm2) Adjusted (0.005) (0.007) (0.007) 2.275 0.116 1Mean absolute and size-adjusted values (standard deviations) across adults per seasonal grouping. 2The F-statistic is calculated from an ANOVA comparing size-adjusted variables. 3Bold values are significant at the α = 0.0125 level after Bonferroni adjustment.

4Power: Italicized values indicate that samples sizes provide power ≥ 0.8 to differentiate a large effect change in bone measures between groups. Large effects were estimated as a 10% change in value based on percentage of bone density changes in human bed rest studies (LeBlanc et al., 1990; Shackelford et al., 2004). 5Power reported as ≥ 0.8 at medium effect change (5%).

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Table 3.10: Seasonal Measurements of Adult Bone and ANOVA Comparisons across Hibernation Groupings for Metaphyseal Cortical and Trabecular Bone (Prehibernation and Posthibernation)

Pre- Post- ANOVA ANOVA 4 Bone Property 1 1 2 3 Power hibernation hibernation F-statistic p-value Absolute 21.95 23.91 (5.83) (4.18) Cortical Area Adjusted 0.069 0.069 0.666 (mm2) (0.006) (0.006) 0.058 0.812 877.38 897.51 0.431 Cortical Density (mg/cm3) (102.89) (93.93) 0.176 0.681

Humerus 0.430 0.366 0.404 B.Ar/T.Ar (%) (0.035) (0.065) 6.588 0.021 206.40 96.19 - Trabecular Density (mg/cm3) (52.58) (69.17) 13.877 0.002 Absolute 20.80 24.48 (5.14) (5.78) Cortical Area Adjusted 0.061 0.061 0.569 2

(mm ) (0.005) (0.007) 0 0.985 753.57 787.91 0.245 Cortical Density (mg/cm3) (126.41) (108.42) 0.371 0.551 Femur 0.397 0.384 0.323 B.Ar/T.Ar (%) (0.059) (0.054) 0.207 0.655 129.17 97.51 0.07 Trabecular Density (mg/cm3) (67.98) (64.21) 1.012 0.329 Absolute 15.28 18.63 (4.49) (3.83) Cortical Area Adjusted 0.054 0.056 0.384

(mm2) (0.006) (0.006) 0.71 0.415

849.56 898.93 0.284

Cortical Density (mg/cm3) (130.07) (99.48) 0.693 0.42 Tibia 0.497 0.486 0.972 B.Ar/T.Ar (%) (0.013) (0.032) 0.768 0.397 298.10 284.84 0.391 Trabecular Density (mg/cm3) (28.64) (37.38) 0.581 0.46

1Mean absolute and size-adjusted values (standard deviations) across adults per seasonal grouping.

2The F-statistic is calculated from an ANOVA comparing size-adjusted variables.

3Bold values are significant at the α = 0.0125 level after Bonferroni adjustment. 4Power: Italicized values indicate that samples sizes provide power ≥ 0.8 to differentiate a large effect change in bone measures between groups. Large effects were estimated as a 10% change in value based on percentage of bone density changes in human bed rest studies (LeBlanc et al., 1990; Shackelford et al., 2004).

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Table 3.11: Seasonal Measurements of Mechanical Properties of Adult Bone and ANOVA Comparisons across Hibernation Groupings for Long Bone Diaphyses and Mandibles (Prehibernation and Posthibernation)

Pre- Post- 1 4 Bone Property Summer Power hibernation1 hibernation1 ANOVA ANOVA F-statistic2 p-value3 86.21 146.61 - Absolute (28.08) (49.51) 0.045 0.048 0.849 4 - Ixx (mm ) Adjusted (0.003) (49.51) 6.635 0.021 46.87 73.35 - Absolute (16.09) (25.88) 0.039 0.041 0.729 4 -

Humerus Iyy (mm ) Adjusted (0.002) (0.003) 2.846 0.112 133.07 219.96 - Absolute (43.73) (73.94) 0.050 0.054 0.875 4 - J (mm ) Adjusted (0.003) (0.003) 5.431 0.034 57.93 91.48 - Absolute (23.47) (49.29) 0.036 0.037 0.73 4 - Ixx (mm ) Adjusted (0.003) (0.004) 0.365 0.554

72.75 121.17 - Absolute (30.98) (69.63) 0.038 0.040 0.531

Femur 4 - Iyy (mm ) Adjusted (0.003) (0.004) 0.818 0.379 130.68 212.65 - Absolute (53.80) (118.53) 0.045 0.046 0.655 4 - J (mm ) Adjusted (0.004) (0.005) 0.623 0.442 52.16 76.90 - Absolute (16.41) (20.98) 0.037 0.039 0.888 4 - Ixx (mm ) Adjusted (0.002) (0.002) 2.04 0.177 39.17 - Absolute 31.60 (8.30) (10.16)

Tibia 0.033 0.033 0.888 4 - Iyy (mm ) Adjusted (0.002) (0.002) 0.056 0.817 83.76 116.07 - Absolute (24.35) (30.49) 0.042 0.043 0.947 4 - J (mm ) Adjusted (0.002) (0.002) 0.78 0.393 477.85 660.41 516.17 Absolute (131.93) (207.16) (167.67) 0.076 0.078 0.075 0.999 4 Mandi Ixx (mm ) Adjusted (0.004) (0.004) (0.005) 2.21 0.123 ble 145.86 232.16 161.39 Absolute (23.34) (72.17) (47.04) 0.057 0.060 0.056 - 4 Iyy (mm ) Adjusted (0.001) (0.004) (0.003) 5.291 0.009

1Mean absolute and size-adjusted values (standard deviations) across adults per seasonal grouping. 2The F-statistic is calculated from an ANOVA comparing size-adjusted variables. 3Bold values are significant at the α = 0.0125 level after Bonferroni adjustment. 4Power: Italicized values indicate that sample sizes provide power ≥ 0.8 to differentiate a large effect change in bone measures between groups. Large effects were estimated as a 10% change in value based on percentage of bone density changes in human bed rest studies (LeBlanc et al., 1990; Shackelford et al., 2004).

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Table 3.12: Seasonal Measurements of Mechanical Properties of Adult Bone and ANOVA Comparisons across Hibernation Groupings for Long Bone Metaphyses

Pre- Post- ANOVA ANOVA p- 4 Bone Property Power hibernation1 hibernation1 F-statistic2 value3

470.27 541.62 Absolute (202.17) (134.18) 0.069 0.067 0.78 4 Ixx (mm ) Adjusted (0.006) (0.004) 0.227 0.64 408.42 562.71 Absolute (202.94) (166.64) 0.066 0.068 0.526 4

Humerus Iyy (mm ) Adjusted (0.006) (0.003) 0.663 0.428 878.69 1104.33 Absolute (401.95) (284.23) 0.080 0.081 0.845 J (mm4) Adjusted (0.007) (.004) 0.038 0.849 507.10 673.67 Absolute (125.98) (289.74) 0.063 0.062 0.765 4 Ixx (mm ) Adjusted (0.005) (0.006) 0.309 0.586

821.63 1178.49 Absolute (218.30) (620.57) 0.071 0.071 0.711

Femur 4 Iyy (mm ) Adjusted (0.006) (0.007) 0.017 0.897 1328.73 1852.16 Absolute (328.21) (901.87) 0.081 0.080 0.812 J (mm4) Adjusted (0.006) (0.008) 0.089 0.77 161.85 196.33 Absolute (43.35) (63.20) 0.049 0.049 0.633 4 Ixx (mm ) Adjusted (0.004) (0.004) 0.209 0.655

197.25 242.47

Absolute (38.29) (63.86)

Tibia 0.052 0.051 0.677 4 Iyy (mm ) Adjusted (0.004) (0.003) 0.152 0.703 359.10 438.79 Absolute (75.55) (125.97) 0.060 0.059 0.802 J (mm4) Adjusted (0.004) (0.004) 0.193 0.667 1Mean absolute and size-adjusted values (standard deviations) across adults per seasonal grouping. 2The F-statistic is calculated from an ANOVA comparing size-adjusted variables. 3Bold values are significant at the α = 0.0125 level after Bonferroni adjustment. 4Power: Italicized values indicate that sample sizes provide power ≥ 0.8 to differentiate a large effect change in bone measures between groups. Large effects were estimated as a 10% change in value based on percentage of bone density changes in human bed rest studies (LeBlanc et al., 1990; Shackelford et al., 2004).

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Sex

In the initial multiway-ANOVA, males and females differed significantly only in the femoral metaphysis. Females had significantly greater CDen (p =

0.011) compared to males. Thus, females followed the combined sex pattern as their cortices potentially gained bone after hibernation. Sex was removed as a factor for hypothesis testing in all other bones.

Discussion

Hibernation and Bone

Our results suggest that woodchucks do not experience a significant compromise in bone area or density following the extended mechanical disuse characteristic of long periods of hibernation. Based on our results, woodchucks appear more similar to bears (Donahue et al., 2006a; Donahue et al., 2003a;

Floyd et al., 1990; McGee-Lawrence et al., 2009b; McGee et al., 2008;

Overstreet et al., 2003), frogs (Hudson et al., 2004) and certain ground squirrels

(Ictidomys tridecemlineatus and Callospermophilus lateralis; McGee-Lawrence,

2009; Utz et al., 2009) in maintaining their skeletal integrity throughout hibernation (Table 3.13). Furthermore, we found similar patterns of potential loss of trabecular fraction as observed in adult ground squirrels (McGee-Lawrence et al., 2011). In these ground squirrels, however, loss of trabecular bone does not appear to affect bone strength and therefore may have limited impact on skeletal

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Table 3.13: Summary of the Influence of Hibernation on Bone in Various Mammals.

Bone Animal Bone Bone Net Species Resorption/ Size2 Morphology Strength Change Formation1

Bats3 5 - 40 g ▼/▲ ▼ NR ▼ Hamsters4 137 - 258 g NR ▼ NR ▼

Ground Squirrels5 85 - 1500 g =/NR ▼/= = ▼/=

Woodchucks 3 - 7.5 kg NR = NR = Bears6 92 - 780 kg ▼/▲ ▲/= ▲/= = 1 “NR” - Not Reported; “=” - No net bone loss or gain; “▲” - Bone increase; “▼” - Bone decrease. 2 Nowak, 1999; Buck and Barnes, 2000; Tøien et al., 2011. 3 Doty and Nunez, 1985; Kwiecinski et al., 1987; Nunez et al., 1972. 4 Steinberg et al., 1979, 1980, 1981, 1986; Kayser and Frank, 1963. 5 Haller and Zimny, 1977; Mayer and Bernick, 1958, 1963; McGee-Lawrence et al., 2011; Utz et al., 2009; Zimmerman et al., 1976; Zimny, 1973. 6 Donahue et al., 2006a, 2006b; Floyd and Nelson, 1990; Floyd et al., 1990; Harvey and Donahue, 2004; Harvey et al., 2005; Lennox and Goodship, 2008; McGee-Lawrence et al., 2008, 2009; McGee et al., 2007, 2008.

performance. We hypothesize that bone formation and resorption processes remain coupled throughout hibernation in woodchucks.

Sample Composition and Age Effects

Several important questions can be asked about our sample. First, we examined a cross-sectional sample of woodchucks raising the possibility of sampling biases in pre- versus posthibernation animals. Specifically, our inclusion of individuals across several months in the pre- and posthibernation

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groups may introduce variation in bone measures as we likely sample a larger range of bone remodeling processes than those occuring directly before or after hibernation. The posthibernation group deserves careful consideration as we might expect animals to regain normal bone physiological activity in the time period we sampled. Previous work points to the possibility of sex, age, and behavioral factors that could affect bone measures (Davis, 1967b; Snyder and

Christian, 1960; Snyder et al., 1961). Observations in non-hibernating mammals, however, suggest that bone recovers over a significant amount of time (i.e., at least 6 to 9 months) following mechanical unloading (Jaworski and Uhthoff, 1986;

Sibonga et al., 2007). Even though we did not see a statistical change in bone measures by month in pre- or posthibernation groups, these potential factors should be considered when interpreting our results.

While we expect that all woodchucks in the collection hibernated as part of their normal life history, we do not know the extent to which each animal was inactive (or the variation in inactivity among animals). Previous studies of woodchuck hibernation, however, indicate that these animals typically experience a week or more of inactivity during each torpor bout throughout hibernation

(Concannon et al., 2001; Zervanos and Salsbury, 2003; Zervanos et al., 2009;

AHD personal observation). By comparison, these smaller mammalian hibernators are significantly less active during this time than are larger hibernators, such as bears (Tøien et al., 2011). We have found a similar maintenance of bone geometry in an on-going analysis of a longitudinal sample

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of captive and catch-and-release woodchucks (Doherty et al., 2010), suggesting that our cross-sectional museum sample is reasonably representing key aspects of bone biology in this species.

The bone sample sizes provide sufficient statistical power to differentiate a

10% change in most bone measures and relative mechanical indices between hibernation groups (Tables 3.4-3.7). We consider a 10% change a large effect based on studies of bone loss in humans as a model non-hibernating mammal

(LeBlanc et al., 1990; Shackelford et al., 2004). In some comparisons, our sample sizes provide power to differentiate smaller effect sizes. Alternatively, we see little power for differentiating even large effects in metaphyseal density measures. The measures showing the lowest power tend to be trabecular density measures that suggest a potential reduction in trabeculae during hibernation (Table 3.5). Thus, we are conservative in suggesting the possibility of this reduction in trabecular bone geometry during hiberation as larger sample sizes are needed to strongly support this outcome. As expected, power is reduced when analyzing only adults, however, there is still sufficient power to detect large effects in many diaphyseal variables, tibial metaphyseal B.Ar/T.Ar, and the polar moment of inertia in the metaphyses (Tables 3.9, 3.10, and 3.12).

At present, we consider it safest to conclude there are no large-scale reductions in bone geometry or density following hibernation. We cannot rule out moderate to small losses, particularly in trabecular bone, that would require a larger sample size to address. The Sign tests provide an additional assessment

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suggesting that the average increase in cortical bone measures posthibernation is highly unlikely to occur if pre- and posthibernation groups were treated as random samples from the same population (i.e., no change in bone during hibernation). This observation supports our conservative conclusion that bone is maintained in woodchucks during hibernation.

Finally, the grouping of subadults with adults may contribute to the observed increase in relative bone dimensions following hibernation because it appears likely that subadults grew during hibernation (Fig. 3.5). Even without subadults, however, we still observed a tendency for bone measures to be similar to or relatively larger after hibernation in diaphyseal and metaphyseal cortical bone measures.

Little is known about how bone responds to hibernation during growth. An ontogenetic analysis of skull growth in Marmota illustrated a typical mammalian pattern of rapid growth early in ontogeny with reduced growth rates as individuals approached adulthood (Cardini and O'Higgins, 2005; Cardini and Thorington,

2006). Unfortunately, this analysis did not indicate specific growth rates during hibernation versus active periods. Histological analyses of the growth plate in

Rana caralintana similarly indicate relatively rapid bone growth through the third or fourth aestivation season (Erismis and Chinsamy, 2010), but without documenting growth rates during hibernation. Our results suggest that growth proceeds during hibernation, despite inactivity and nutritional deprivation.

Previous work in bears has also shown that bone strength is maintained

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throughout growth by annual increases in cross-sectional area without significant net change in cortical porosity (Harvey and Donahue, 2004; Harvey et al., 2005;

McGee-Lawrence et al., 2009a; McGee-Lawrence et al., 2009b; McGee et al.,

2008; McGee et al., 2007). Similarly, juvenile ground squirrels maintain bone strength throughout hibernation (McGee-Lawrence et al., 2011). These studies were designed to compare annual variation in bone and do not provide growth rates during hibernation. While bone continues to grow during disuse in non- hibernators, lack of loading usually results in reduced bone properties compared to active animals (Abram et al., 1988; Biewener and Bertram, 1994; Globus et al.,

1986). Given the well-documented observation that bone tends to be more responsive to environmental stimuli during ontogeny compared to adulthood

(Bertram and Swartz, 1991; Forwood and Burr, 1993; Ruff et al., 2006), the potential maintenance of bone growth during hibernation-induced inactivity highlights the possibility of a derived physiological mechanism(s) that may effectively “tune-out” the environmental-load stimuli (McGee-Lawrence et al.,

2008).

The Influence of Size on Bone Maintenance in Hibernating Mammals

While relatively small mammals may lose bone during hibernation, larger animals do not appear to experience decreases in macrostructural bone density or mechanical properties during hibernation (Table 3.13). It remains to be seen whether these two outcomes represent 1) varying physiological mechanisms for dealing with hibernation across species, 2) methodological differences in

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quantifying bone parameters among studies and/or 3) size-related changes in the skeletal response to hibernation.

Histological analysis indicates that bears do not lose bone microstructural integrity and maintain bone porosity following hibernation (Harvey et al., 2005;

Hudson et al., 2004; McGee et al., 2008). Parathyroid hormone (PTH) is hypothesized to act anabolically in denning bears to promote calcium recycling and prevent bone loss, compared to its normal catabolic action in non- hibernators (Donahue et al., 2006a). While the reduced activity of osteoblasts and osteoclasts during hibernation suggests that hibernators may utilize novel mechanisms for regulating bone turnover, the potentially disparate actions of

PTH highlight the possibility of differing physiological responses across hibernating mammals.

One of the challenges to concluding that different mechanisms act to regulate bone across mammalian hibernators is the disparate methods used in studying bone among these species. Much of the early work on small hibernating mammals focused on histologic analysis providing the hypothesis that osteocytic osteolysis was driving bone loss (Doty and Nunez, 1985;

Kwiecinski et al., 1987; Whalen et al., 1972). Unfortunately, these early studies do quantify bone strength to clarify how osteocytic osteolysis impacts bone performance. Recently, McGee-Lawrence et al. (2011) found that bone strength was maintained throughout hibernation in juvenile thirteen-lined ground squirrels

(I. tridecemlineatus) despite experiencing osteocytic osteolysis (Haller and

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Zimny, 1977). Utz et al. (2009) similarly found maintenance of bone strength during hibernation in the closely-related, golden-mantled ground squirrel (C. lateralis). The maintenance of bone strength in these ground squirrels suggests that osteocytic osteolysis may not compromise bone performance while regulating circulating calcium levels (Teti and Zallone, 2009).

Finally, size-related changes in metabolism and the skeleton may interact with these physiological processes and impact how bone responds to hibernation across mammals. The negative allometry, or relative decrease with body size

(Kjeld and Olafsson, 2008), of metabolic rate suggests (all else equal) that larger mammalian hibernators are able to overwinter at higher metabolic rates (Geiser,

1988; 1998; Nedergaard and Cannon, 1990). This negatively allometric relationship helps to explain how relatively large bears (92-780 kg) achieve hibernation with a relatively smaller reduction in metabolic rate (i.e., 53% of basal metabolic rate) compared to other hibernators such as the arctic ground squirrel

(<1.5 kg) that reduce metabolic rate to 2-5% of basal levels during hibernation

(Buck and Barnes, 2000; Tøien et al., 2011). Moreover, bears do not decrease body temperatures below 30˚C throughout hibernation (Tøien et al., 2011).

Initial interspecific comparisons also suggest a slight, but significant, size- related decrease in circulating serum calcium levels across all mammals (Kjeld and Olafsson, 2008). Thus, an animal the size of a black bear may exhibit up to a 10% size-related decrease in serum calcium compared to microchiropteran bats (all else equal). The negatively allometric relationship suggests that larger

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hibernators may benefit from being able to maintain lower levels of circulating calcium per unit of body weight during hibernation. Skeletal mass also increases with positive allometry across mammals (Christiansen, 2002; Prange et al., 1979;

Schmidt-Nielsen, 1984), theoretically providing a relatively larger source of stored calcium for release during hibernation. Moreover, osteocyte density decreases with body size (Bromage et al., 2009; Mullender et al., 1996) which may reduce the potential of osteocytic activity for maintaining calcium levels in larger animals.

These size-related changes in bone and metabolism may help explain the observed pattern of osteocytic osteolysis in small, but not large hibernators to date.

We do not know whether woodchucks experience osteocytic osteolysis or how PTH expression impacts their bone during hibernation. Given that woodchucks are intermediate in size between bears, that appear to maintain bone, and smaller hibernators, that may lose bone during hibernation, further examination of bone physiology and histology in woodchucks will be beneficial in helping to understand size-related changes in the mammalian skeleton during hibernation (Table 3.13). Additionally, improved documentation of how various hibernating species differ in their skeletal physiology and ability to maintain bone integrity will benefit our understanding of both how mammals respond to harsh temperature environments and the evolution of hibernation as a mammalian behavior (Geiser, 1998).

CHAPTER 4

BONE DENSITY AND CROSS-SECTIONAL PROPERTIES IN ACTIVE AND HIBERNATING ADULT WOODCHUCKS

Introduction

Bone loss is a hallmark consequence of the aging process. Although the emphasis of osteoporosis awareness and prevention in postmenopausal women is at the forefront of the National Osteoporosis Foundation message, the fact is that all people lose bone as they age regardless of sex and genetic determinants

(Newton-John and Morgan, 1968; Tung and Iqbal, 2007). Peak bone mass in humans is achieved usually before the second decade shortly after long bone epiphyseal closure, and closure of all epiphyses of the skeleton is usually achieved around the age of 25 (Heaney et al., 2000; Heikel, 1960). Starting in the 3rd and 4th decade of life, the decline of bone mass is linked to decreased levels of gonadal hormones and increased inflammatory cytokines associated with aging (Tung and Iqbal, 2007). The risk of developing osteoporosis follows as the combined effect of peak bone mass attained at maturity and the amount of bone the individual can thus “afford” to lose before compromising skeletal integrity (Bonjour et al., 1994; Heaney et al., 2000). Postmenopausal women, particularly those of European and Asian descent, combine comparatively

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smaller bone mass with a significant reduction in estrogen to experience a higher rate of bone loss and an increased risk of fragility fractures as they age.

Contributing factors, such as lack of physical activity, accelerate the natural decrease of bone mass associated with age (Gold and Silverman, 2004;

Kasturi et al., 2009; Winsloe et al., 2009). Likewise, physical activity has been shown to be important in preserving bone mass in the postmenopausal skeleton

(Forwood and Burr, 1993). In a study of long-distance runners aged 50 to 72, bone density was reported to be 40% higher in both male and female runners than a control group (Lane et al., 1986). In a separate study, elderly runners who stopped running for various reasons significantly lost bone density (13.8% in females and 8.4% in males) over the course of two years to become similar to the bone mass observed in non-runners (Lane et al., 1990). We can conclude from this work that while skeletal integrity is a culmination of genetics, age at peak bone mass, and sex, the cost of being physically inactive has a substantial negative impact on bone quality.

Skeletal Integrity in Hibernating Mammals

While inactivity contributes to significant disorders in humans and likely many other mammals, hibernating animals can routinely spend half of the year or more inactive (Lyman et al., 1982). Such a long duration of unloading of the skeleton implies that their bones would be subject to disuse induced bone loss.

Furthermore, juvenile mammalian hibernators are often required to hibernate their first year to survive the winter (Geiser, 2008). In most mammals, a lack of

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loading in maturing skeletons usually results in reduced bone properties, reduced peak bone mass at maturity, and skeletal structural abnormalities compared to active animals (Abram et al., 1988; Biewener and Bertram, 1994; Globus et al.,

1986). Previously, it was found that subadult woodchucks (Marmota monax) tend to continue growing their skeletons during the first year of hibernation

(Doherty et al., 2012). Similarly, juvenile ground squirrels (Ictidomys tridecemlineatus) maintained bone properties throughout the hibernation season

(McGee-Lawrence et al., 2011). Thus, it does not appear that peak bone mass is compromised in maturing, seasonally-inacitve hibernators.

Subadult response to hibernation and the ability to continue growing a healthy skeleton during prolonged mechanical unloading and nutrient deprivation is rather remarkable. Considering that adult humans begin to lose bone early in adulthood and that physical inactivity accelerates this bone loss (Borer, 2005;

Newton-John and Morgan, 1968), it is important to ask whether adult hibernators may be protected from disuse osteoporosis. Studies in adult rats (non- hibernating animals) have reported that inactivity is more detrimental to cortical properties of the femur and tibia than estrogen deficiency resulting from ovariectomy (Miyagawa et al., 2011). This would suggest, similar to inactivity related bone loss in humans, that hibernating adult animals would be at an increased risk of bone loss and fragility fractures following repeated annual cycles of 4 to 6 months of physical inactivity.

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Adult woodchucks have been examined with subadults in a peripheral quantitative computed tomography (pQCT) investigation of bone properties and dimensions before and after hibernation (Doherty et al., 2012). When adults were considered separately, they maintained diaphyseal cortical properties. Not surprisingly, on the other hand, there were indications that some bone was being lost in the trabecular metaphyses during the inactive period of hibernation. It was concluded that no annual net bone loss occurred in these mature animals, however the generally low power in the metaphyses combined with the pattern of decreasing trabecular properties made this conclusion tentative. To better characterize the bone properties throughout the year, it was necessary to conduct additional investigations of the cortical and trabecular bone of hibernating adult woodchucks.

In this study, adult woodchucks are examined to determine whether they lose bone as a result of inactivity and nutrient deprivation to better understand the effects of hibernation on the mature skeleton. A longitudinal sample of captive animals were hibernated under simulated laboratory conditions using pQCT to investigate diaphyseal cortical density and bone distribution before, during, and after hibernation. In addition, a cross-sectional study of adult, wild- caught woodchucks and terminal captive animals were examined using microcomputed tomography (μQCT). Cross-sectional analyses were used to supplement the findings observed previously in adult woodchucks (Doherty et al.,

2012). Diaphyseal cortical thickness and porosity were investigated as well as

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trabecular properties (including measures of trabecular number, structure, and orientation) for comparison between seasons. Decreased trabecular structures relate to increased risk of fragility fractures at the metaphyses. Building on the initial conclusions from (Doherty et al., 2012) based on a cross-sectional museum sample, it is hypothesized that there will be no change in bone properties before, during, or after hibernation in either the longitudinal or cross- sectional samples of adult woodchucks.

Materials and Methods

Animals

All procedures were conducted with prior approval from the NEOMED

Institutional Animal Care and Use Committee (Protocols #08-0027, #08-0029,

#11-019). Live animal trapping permits were acquired annually from the Ohio

Division of Wildlife (Permit #11-257). Healthy, adult woodchucks (Marmota monax) were trapped in live-capture box traps from the NEOMED campus and surrounding areas in Portage County, OH. Adulthood (one year and older) was determined based on dental characteristics, radiographic attributes of epiphyseal plate closure, pelage at time of capture, and post-mortem skeletal assessments following cold water maceration of the woodchuck (Davis, 1964; Hamilton, 1934).

Animals were included in one of two study samples: 1) A captive longitudinal sample or 2) a wild cross-sectional sample. Both males and females were

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included based on availability during trapping and significant sex differences are reported when observed.

Twelve woodchucks (6 males and 6 females) were trapped and incorporated into the captive longitudinal sample. These woodchucks were maintained at the NEOMED Comparative Medicine Unit (CMU) throughout at least one annual cycle of hibernation and active periods. Each annual cycle (i.e., year) was categorized into four seasons for statistical investigation:

Prehibernation (August - October), hibernation (November – mid-March), posthibernation (end of March - May), and summer (June-July). These animals were housed in 4’ x 2’ enclosures during the study period and were given periodic access to a 15’ x 1.5’ runway during the active seasons for exercise.

The woodchuck diet during active portions of the year consisted of high fiber rabbit chow, apples, kale, and carrots. Water was provided ad libitum throughout the year.

Additional wild woodchucks were caught and sampled along with the terminal captive animals as a comparative cross-sectional sample. This wild caught sample provided an essential positive control demonstrating that the captive hibernation setting elicits similar physiological responses to the woodchuck’s natural environment. As such, captivity status was used as a factor to distinguish between the effects of captivity compared to wild caught animals.

The cross-sectional study, including the terminal captive animals, included 34 individuals (17 captive and 17 wild, Table 4.1).

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Table 4.1: Cross-sectional Adult Woodchuck Sample

Sex Captivity Status Season Total Male Female Captive Wild Prehibernation 5 2 5 2 7 Hibernation 2 2 4 0 4 Posthibernation 4 4 6 2 8 Summer 6 9 2 13 15 Total 17 17 17 17 34

Animal Assessment and Preparation for Data Collection

Upon capture, all woodchucks were transported to the NEOMED

Comparative Medicine Unit (CMU) for initial processing. Animals were anesthetized by intramuscular injection of ketamine (50 mg/kg) and xylazine (5 mg/kg) while in the box trap. Once an animal was under anesthesia, it was removed from the trap for sampling. A face mask was used to deliver 1-3% isoflurane gas as needed to complete all data collection procedures. A general assessment of health was made, including weight, rectal temperature, tooth wear, sex, and age. Any serious health problems observed, such as unhealed broken bones experienced prior to capture, resulted in removal of the animal from the study. Captive animals were given a rabies vaccination and a series of de-worming injections to ensure animal health throughout the study. Blood samples, radiographs, peripheral quantitative computed tomography scans

(pQCT, described in more detail below), and physical measurements were collected at the time of animal acquisition. Immediately following data collection, wild woodchucks were euthanized using an intravenously administered

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pentobarbital-containing solution (1 cc / 10 lbs) and their bodies frozen (-20°C) for storage until further data analysis. Captive animals were allowed to recover from the anesthesia in their enclosures and acclimate to their new surroundings.

A month before the beginning of the hibernation season (October 1), all captive animals had a temperature data logger (iButtons – DS1921G and/or

DS1922T, MAXIM, San Jose, CA) implanted in their intraperitoneal cavity to record daily core body temperatures throughout the hibernation and active seasons. Data loggers were coated in Elvax (Minimitter, Bend, OR) and then gas-sterilized (Sterrad) in preparation for aseptic implantation. Animals were anesthetized, as described above, using ketamine and xylazine. Isoflurane gas, mixed with 1% oxygen, was administered either by face mask or endotracheal tube to maintain a level plane of anesthesia for the duration of the surgical procedure. Ketofen (3 mg/kg) was given intramuscularly before surgery as analgesia. The area overlying the linea alba of the abdomen was shaved and aseptically prepared for surgery. A 1.0 to 1.5 cm median incision was made through the skin and then carried through to divide the aponeurosis defining the linea alba to enter the intraperitoneal cavity. One or two iButtons were inserted into the incision, taking care not to touch the margins of the skin to avoid introducing any cutaneous contaminants into the abdominal cavity. The incision through the linea alba was then sutured in an interrupted continuous pattern using 4.0 Vicryl. The skin was closed with the same suture using a subcutaneous continuous pattern and 0.5 cc of 2% lidocaine was administered

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subcutaneously near the incision site. Woodchucks were then placed in their cages to recover from the anesthesia and monitored for three days for wound healing. The data loggers were explanted and replaced once a year during the summer active season following the same procedures. Hibernation status and time periods of deep hibernation based on core body temperatures were verified upon recovery of each iButton following previous research (Dallmann et al.,

2006; Davidson et al., 2003; Geiser, 1995; Long et al., 2007; Lovegrove, 2009;

Taylor et al., 2004).

Captive woodchucks were moved and maintained in a walk-in refrigeration unit for the duration of the hibernating season (October 1 – March 25). Ambient temperature of the refrigerator was held at 7˚C (± 1-2 ˚C) throughout the hibernation period. Water was continuously available, but food was initially restricted and then withheld to initiate hibernation and animals did not consume food after entering hibernation. The hibernation chamber was maintained with red light throughout the hibernation season to avoid disturbance to the animals during daily animal welfare assessments and data collection. Woodchucks were only removed from the refrigeration unit under anesthesia once during the hibernation period (late January) to take radiographs and computed tomography scans. These procedures took on average an hour and a half to complete and animals were maintained on an ice bath in a dark box for this duration to avoid animal reheating and light disturbance.

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Quantitative Computed Tomography (QCT)

Longitudinal captive woodchuck study: All captive animals were scanned using a peripheral QCT machine (pQCT) at the time of capture and quarterly (i.e., once each season) for the duration of their captivity. Computed tomography scans were taken at the tibial diaphysis using a XCT Research

M921010 scanner (Norland/Stratec, Pforzheim, Germany) at a slice thickness of

0.25 mm and voxel size of 0.1 mm (giving a final resolution of 100 μm). All scans were acquired against a standard cone phantom (XCT Research M) with known densities. The left hind limb of each anesthetized woodchuck was positioned and securely taped, ventral side down, on a platform specifically made to hold woodchucks for the CT scan procedure (Daniel Schiferl, Fort Atkinson, WI). The leg was then inserted into the 50 mm gantry of the XCT scanner and oriented as perpendicular to the radiation beam as possible. The tibiae were scanned at the diaphyseal midline (approximately 50% of the total bone length). It proved challenging to obtain an anatomically consistent slice of the distal tibial metaphysis (1 mm proximal to the distal epiphyseal line) between scans of each captive woodchuck and between animals. It was determined that the slice location at the distal tibial metaphysis was too variable for accurate evaluation across scans and no live pQCT scans were analyzed of this region. Diaphyseal scans were much more consistent. Therefore, only the scans of this region were analyzed in woodchucks using the XCT scanner.

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Calculation of volumetric bone density and microcomputed tomography (μCT) of a cross-sectional sample of woodchucks: After the terminal data collection session (i.e., day of capture for wild animals and study completion for captive animals), all woodchucks were euthanized (as described above) and frozen in storage (-20˚C). Ultimately, specimens were thawed and the humerus, femur, and tibia dissected and cleaned of all soft tissue. Wet mass of the bone was recorded using an electronic scale (to the nearest microgram) and total bone volume was determined by water displacement in a graduated cylinder to the nearest milliliter (Schneider et al., 2004). Archimedes’ principle

(density = mass/volume) was then applied to calculate whole bone volumetric density (Utz et al., 2009). The three bones were then placed in 10% phosphate buffered saline for 15 to 20 minutes before μQCT scanning to rehydrate the bones after freezing.

Two 7.7 mm thick sections of the humerus, tibia, and femur were μQCT scanned (Scanco Medical VivaCT 75, Brüttisellen, Switzerland) at the diaphyses

(approximating 50% total bone length) and metaphyses (1 mm proximal to the epiphyseal line in the tibia and femur, 1 mm distal to the epiphyseal line in the proximal humerus, Fig. 4.1). Thickness of the scans was increased if the bones did not exactly match up with each other to ensure the scan contained the region of interest for each bone. Scans were acquired by beam intensity of 70 kVp, 114

μA, and a voxel size of 20.5 μm.

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Fig. 4.1: Longitudinal computed tomography scoutview of the femur, tibia, and humerus. Shaded regions indicate areas of interest within each scan. A 1.0 mm section was investigated in the distal femoral (DF), distal tibial (DT), and proximal humeral (PH) metaphyses (asterisks). The diaphyses, approximating half the length of the bones, were also examined in a 5.0 mm slice stack (diamonds).

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Analysis of QCT Scans

Longitudinal captive woodchuck analysis: XCT diaphyseal scans of captive woodchucks were analyzed using the XCT540 (Norland/Stratec) software. Each scan was thresholded to 710 mg/cm3 as a midpoint density value. XCT software provides various algorithms for defining the contour of the bone. For this study, contour mode 1 was utilized to avoid aberrant points within the medullary cavity set at a threshold of 710 mg/cm3. The surface of the bone was further defined by using a threshold driven peel (peel mode 2) set at a threshold of 650 mg/cm3 and contour mode of 4 with a threshold of 710 mg/cm3.

All threshold values were established from a pre-analysis of a sample of the scans. Data output included cortical area (Ct.Ar) and apparent mineral densities for cortical bone (Ct.D). In addition, moments of inertia, or the ability of an object to resist deformation in specific directions, were estimated using this software, including resistance to mediolateral bending (Iml), anteroposterior resistance to bending (Iap), and the polar moment of inertia (J) based on a neutral axis passing through the centroid of the section (Table 4.2).

Although all attempts were made to obtain a consistent scan, variations in the live animals made consistent placement of the limb difficult and resulted in a slight shift in angle of the long axis of the bone away from 90 degrees relative to the radiation beam. Thus, some tibiae were inadvertently scanned at larger or smaller angles than others. To correct this deviation, the angle of the scanned bone was measured from the saved XCT scoutview image in Image J (v. 1.44).

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Table 4.2: Bone Cross-Sectional, Density and Mechanical Measurements.

Size Adjusted Bone Property* Symbol* Units Definition 1 Estimate Whole Bone Density: Apparent mineral density of Whole Bone Density BMD μg/mL3 N/A whole bone Diaphyseal Cortical Measures: Area of cortical bone in Cortical area Ct.Ar mm2 (Ct.Ar0.5)/L section Volume of cortical bone in Cortical density Ct.D mg/cm3 N/A section Area moment of inertia Resistance to mediolateral about horizontal (x) I mm4 (I 0.25)/L ml bending ml axis

Area moment of inertia 4 Resistance to 0.25 I mm (I )/L about vertical (y) axis ap anteroposterior bending ap

Polar moment of J mm4 Resistance to torsion (J0.25)/L inertia Volume of pores in cortical Cortical porosity Ct.Po % bone as a percent of the N/A total volume of interest Thickness of the diaphyseal Cortical thickness Ct.Th mm Ct.Th/L cortical wall

Metaphyseal Trabecular Measures:

Ratio of bone volume to total Bone volume fraction BV/TV % N/A volume Average thickness (i.e., Trabecular thickness Tb.Th mm Tb.Th/L structure) of the trabeculae Number of trabeculae within Trabecular number Tb.N 1/mm N/A the ROI Average of the space (i.e., Trabecular separation Tb.Sp mm background) between Tb.Sp/L trabeculae Plate vs. rod structure of Structural model index SMI N/A N/A trabeculae Trabecular orientation: Degree of anisotropy DA N/A N/A 0=isotropic, 1=anisotropic Number of trabecular Connectivity density Conn.D 1/mm3 connections within ROI N/A volume *Based on the ASBMR nomenclature (Bouxsein et al., 2010). 1L = Total length of respective bone.

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It was then possible to correct for shifts in bone from perpendicular by multiplying

Ct.Ar by the sine of the bone angle deviation. Corrected values were verified by scanning a cylinder with known dimensions at 5° increments from 55 to 125° and comparing the corrected values to those obtained at 90°.

In a similar fashion, the second and polar moments of inertia were corrected by fitting a 2nd degree polynomial function to the original scanned value of the cylinder at 90˚ for each variable (Iml, Iap, J). The equation was applied to one degree increments spanning 60° to 121° to obtain a correction factor. The actual scanned value (at an angle deviating from perpendicular) was then corrected by multiplying by the resultant correction factor corresponding to the scanned angle rounding to the nearest degree. Following verification of this correction procedure on the cylinder with known dimensions, it was applied to each bone scan. Cortical density was not corrected for scan angle.

Cross-sectional analysis of μQCT: Cross-sectional scans of the diaphyses and metaphyses of the three bones were cropped and visually assessed in Adobe Photoshop (CS3, San Jose, CA). The 7.7 mm slice stack of the each bone was trimmed and analyzed for the region of interest. Diaphyses were trimmed to a 5.0 mm length that included 50% of the total bone length.

Similarly, identifiable landmarks of the epiphyseal line within the metaphyseal scans were located and a 1.0 mm (~50 slices) thick stack was isolated for trabecular analysis. Following the standards outlined in the American Society for

Bone and Mineral Research (ASBMR) guidelines (Bouxsein et al., 2010), all

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stacks were globally thresholded, despeckled, and filtered using the Gaussian blur technique in CTAn (SkyScan v.1.12, Kontich, Belgium).

For the diaphyses, regions of interest (ROI) were drawn to encompass only the cortical bone ring and this ROI was shrunk to the periosteal and endosteal margins of the cortical bone. Cortical porosity (Ct.Po) was obtained from the CTAn analysis of the tibial diaphyses (Table 4.2). The ROI of the metaphyses was drawn within the endosteal margin of the medullary cavity and interpolated across the entire stack of slices to include only trabecular structures.

This ensured that as the metaphysis changed in shape, the ROI retained the shape of the endocortical margin to exclude cortical bone but include as much trabecular information as possible.

Metaphyseal variables of interest from this cross-sectional study included:

1) bone volume fraction (BV/TV, comparable to the single-slice measurement

B.Ar/T.Ar described in Chapter 3), 2) trabecular number within the scanned metaphyseal region (Tb.N), 3) trabecular thickness (Tb.Th), and 4) trabecular separation, or space between the trabecular lattice comprising the metaphyses

(Tb.Sp; Hildebrand and Ruegsegger, 1997a). Also of interest was the shape of trabeculae classified as plates (i.e., the ideal model of trabecular structure and indicated by values closer to 0) or rods which are characteristically formed during the process of bone degradation (and indicated by values of 3 and higher). This plate-like versus rod-like structural parameter is called the structural model index

(SMI, Table 4.2; Hildebrand and Ruegsegger, 1997b). The degree of anisotropy

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(DA) was also investigated, along with connectivity density (Conn.D) as measures of the orientation and structural relationships of the trabeculae within the metaphyses, respectively (Table 4.2; Chappard et al., 2005). The degree of anisotropy is indicative of the mechanical response of bone to loading. Thus, more isotropic orientations would be suggestive of a loss of mechanically oriented trabeculae with values nearing 0 where highly anisotropic structures are reported with values closer to 1. The mean intercept length (MIL) method established by Harrigan and Mann (1984) was used to calculate DA in the CTAn analysis.

Statistical Analysis

Prior to analysis, area and moments of inertia were size adjusted by

0.5 0.25 0.25 0.25 dividing CA , Ixx , Iyy , and J by the relevant bone length (as previously described in Doherty, 2012; see also Daegling, 2001; Table 4.2). It has been noted that trabecular structures scale allometrically with different species of animals (Doube et al., 2011). Considering that it is more difficult to determine an appropriate size dimension to scale trabecular structures than it is for the cortices, the geometric mean was obtained from the cube root of the product of the lengths of the three bones to serve as an overall size adjustment variable for all of the dimensioned trabecular variables (i.e., Tb.Th and Tb.Sp; Table 4.2;

Jungers et al., 1995). Analysis of size-adjusted data minimized the effect of increased size related to sex in all animals and effectively makes the statistical tests more conservative. Bone density (mg/cm3), DA (unitless), SMI (unitless),

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Ct.Po (%), Conn.D (1/mm3), and BV/TV (% bone volume) are already dimensionless and were not size adjusted. Sex was initially included as a cofactor with hibernation in all analyses, but this was removed from the final analysis of a given bone section when not initially significant (Berry and Feldman,

1985). All analyses were conducted in SPSS (v.19.0, IBM, Armonk, New York).

Longitudinal captive woodchuck XCT statistical analysis: Bone imaging data were averaged by season per animal (N = 12, 6 males and 6 females). Normality was assessed using a Shapiro-Wilk's test. Significance was determined using a Sequential Bonferroni (α = 0.025) based on 12 independent tests (4 bone property measures x 3 seasonal levels). Data that violated the normality assumption were examined for outliers, natural log transformed (ln), and investigated in comparison with non-ln transformed data. When results using the transformed data did not differ from the original analysis, only non- transformed analyses are reported. Following normality assessment, data were analyzed using a repeat measures general linear model with hibernation season as the independent variable. Violations of sphericity (α ≤ 0.05) were corrected using the Greenhouse-Geisser method. In addition, Bonferroni post-hoc tests were conducted to determine pair-wise directional differences between hibernation seasons.

Cross-sectional analysis of μQCT: Terminal captive and wild woodchucks were analyzed together (N = 34, 17 captive and 17 wild animals,

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Table 4.1). Data were first assessed for normality as described above using a

Sequential Bonferroni adjustment (α = 0.025) based on 28 independent tests (7 bone property measures x 3 seasonal levels). Univariate ANOVAs were utilized to test the hypothesis that woodchucks would not experience a change in relative bone properties before, during, or after hibernation. Captivity status (i.e., captive vs. wild) was initially used as a cofactor along with sex (Table 4.1). Cofactors were removed from the final analysis of a given bone property when they and their interaction effects were not initially significant (Berry and Feldman, 1985).

Statistical significance was determined using a Bonferroni adjustment based on examining three bones and final α = 0.0167 (0.05/3) was considered significant

(Quinn and Keough, 2002). Bonferroni post-hoc tests were also used to determine pair-wise comparisons between seasons. Because our initial hypothesis predicts no change in relative bone measures, we calculated statistical power in appropriate ANOVA designs to minimize the likelihood of

Type II statistical errors. Following Cohen (1977), a power of ≥ 0.8 (1-β) is considered appropriate.

Results

Longitudinal Captive Woodchuck Study

All variables were found to be normally distributed in the tibial diaphysis for the longitudinal captive woodchuck group. Sex was excluded from the final analysis as there were no significant sex differences or interaction effects (i.e.,

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season ∙ sex). There was a highly significant increase in cortical density of the tibial diaphyses during and after hibernation in the captive sample of woodchucks compared to the prehibernation period (p = 0.002, Fig. 4.2, Table 4.3). Cortical area (Fig. 4.3A) and the second moments of inertia (Iap, Iml, and J, Fig. 4.3B) did not have significant differences between seasons (Table 4.3). All four of these variables exhibited high statistical power, and the conclusion of no annual change is likely an accurate depiction of the true pattern of bone cortical properties in the tibial diaphysis (Table 4.3).

Cross-Sectional Woodchuck Study

Both diaphyseal and metaphyseal properties were normally distributed in the cross-sectional study of the femur, humerus, and tibia. No significant sex difference or interaction effect was observed in this study. Captive and wild woodchucks also did not differ significantly in their diaphyses or metaphyses between seasons despite experiencing different environmental conditions. This suggests that the captive animals are an accurate representation of the positive controls (i.e., wild woodchucks). As such, sex and captivity status were removed from the final data analysis.

Whole bone density of the femur was found to be 10% greater in the posthibernation season than during the summer (p = 0.015, Fig. 4.4A, Table 4.4).

On average, whole bone density was also greater in the humerus and tibia in the posthibernation period compared to all other seasons. No other significant differences were observed in this cross-sectional investigation of cortical

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Fig. 4.2: Cortical density of tibial diaphyses significantly increased between all three seasons in a longitudinal study of captive adult woodchucks.

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Fig. 4.3: There were no significant seasonal differences in cortical area (A) or moments of inertia (B) in the tibial diaphyses of captive, adult woodchucks.

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Table 4.3: Repeated Measures ANOVA of Tibial Cortical Properties in A Longitudinal Sample of Adult, Captive Woodchucks

Mauchly's ANOVA Bone Pre- 1 Post- ANOVA Sphericity 1 Hibernation 1 F- Power Property hibernation hibernation p-value (p-value) statistic

1245.718 1262.100 1274.705 Ct.Den 0.287 a b c 9.029 0.002 - (33.251) (21.969) (34.254) 19.117 19.042 19.379 Ct.Ar 0.897 (3.087) (2.761) (2.671) 0.053 0.052 0.053 0.5 0.837 1.987 0.163 0.796 (Ct.Ar )/L (0.003) (0.002) (0.003) 52.067 48.470 49.826 I 0.213 ml (13.879) (13.559) (13.560) 0.032 0.031 0.031 0.25 0.153 1.493 0.249 0.963 (Iml )/L (0.001) (0.001) (0.001) 47.814 45.213 45.393 I 0.793 ap (11.595) (10.961) (11.430) 0.032 0.032 0.032 0.25 0.396 2.401 0.116 0.890 (Iap )/L (0.001) (0.001) (0.001) 99.808 93.623 95.035 J 0.162 (24.852) (23.654) (23.936) 0.039 0.038 0.038 0.071 2.476 0.109 0.853 (J0.25)/L (0.001) (0.001) (0.001) 1Values reported as average bone properties (standard deviation).

Bold p-values are significant at the α = 0.5 level. a,b,c Indicate significant differences between the three seasons.

Rows without letters indicate no significant pair-wise difference between any season. Observed Power: Bold values indicate that sample sizes provide power ≥ 0.8 to differentiate a small effect change (2.5%) in bone measures between groups, medium effects (5%) are reported in italics. Values of effects based on percentage bone density changes in human bed rest studies (LeBlanc et al., 1990; Shackelford et al., 2004).

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Table 4.4: Whole Bone Density and Diaphyseal Properties of A Cross-Sectional Sample of Adult Woodchucks

Pre- 1 Post- 1 ANOVA ANOVA Bone Property Hibernation Summer Power hibernation1 hibernation1 F-statistic p-value

1.458 1.353 1.499 1.344 BMD (0.113) (0.063) (0.107)a (0.119)b 4.126 0.015 -

0.912 0.720 0.886 0.916 Ct.Th (0.132) (0.112) (0.123) (0.206) 0.011 0.008 0.010 0.011 Femur CT.Th/L (0.002) (0.002) (0.001) (0.002) 1.718 0.184 0.622 0.355 1.008 0.406 0.574 Ct.Po (0.369) (0.305) (0.281) (0.779) 1.012 0.402 0.060 1.406 1.441 1.508 1.459 BMD (0.167) (0.241) (0.123) (0.143) 0.469 0.706 0.950 0.827 0.712 0.881 0.868 Ct.Th (0.098) (0.050) (0.084) (0.156) 0.011 0.009 0.012 0.012

Humerus Ct.Th/L (0.001) (0.001) (0.001) (0.002) 2.307 0.097 0.993 1.064 1.426 0.425 1.469 Ct.Po (0.477) (0.691) (0.175) (1.312) 2.268 0.102 0.090 1.455 1.423 1.677 1.440 BMD (0.161) (0.172) (0.237) (0.149) 2.907 0.054 0.937

1.222 1.123 1.223 1.187

Ct.Th (0.168) (0.257) (0.172) (0.216)

Tibia 0.015 0.014 0.015 0.015 Ct.Th/L (0.009) (0.003) (0.002) (0.002) 0.413 0.745 0.355 1.277 1.896 1.527 0.875 Ct.Po (1.207) (1.405) (1.321) (0.751) 1.264 0.305 0.068 1Values reported as average bone property (standard deviation).

Bold p-values are significant at the α = 0.0167 level.

a,b Indicate significant differences between the three seasons.

Rows without letters indicate no significant pair-wise difference between any season.

Observed Power: Italicized values indicate that sample sizes provide power ≥ 0.8 to differentiate a medium effect change (5%) in bone measures between groups. Normal font is representative of large effect changes (10%). Values of effects based on percentage bone density changes in human bed rest studies (LeBlanc et al., 1990; Shackelford et al., 2004).

properties. Cortical thickness did tend to decrease (Fig. 4.4B) and cortical porosity to increase in the hibernation season (Fig. 4.4C), but this appeared to be recovered in posthibernation and could have been a result of the small sample of the hibernation group (N = 4 captive animals). Low statistical power of cortical porosity in all three bones makes the conclusion of no change in this cortical property throughout the year tentative (Table 4.4).

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Fig. 4.4: Only whole bone density (BMD) of the femur was statistically greater between the posthibernation and summer season (A). Other cortical properties, such as cortical thickness (Ct.Th, B) and total cortical porosity (Ct.Po, C), did not differ in any of the three bones investigated in a cross-sectional study of adult woodchucks.

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Trabecular properties of the metaphyses did not appear to change significantly between seasons (Table 4.5). Unlike that seen in humeral B.Ar/T.Ar in the museum sample of adult woodchucks (Doherty et al., 2012), there was no significant decrease in BV/TV in the cross-sectional sample observed in any of the three bones (average β = 0.828 for all three bones, Fig. 4.5A). Furthermore, although most indices did tend to decrease during the hibernation period, there were no significant differences between seasons and any bone loss in Tb.Th appeared to be recovered during the active periods (Fig. 4.5B), Tb.N (Fig. 4.5C), and Tb.Sp (Table 4.5). Similarly, there was no indication that trabeculae became more rod-like (SMI) or more isotropic (DA) during or after hibernation (Table 4.5).

Trabecular connectivity (Conn.D) also did not degrade following hibernation as might occur in disuse osteoporosis (Table 4.5). Besides BV/TV, Tb.N (average β

= 0.867) and DA (average β = 0.973) had high statistical power (Table 4.5). The lack of statistical significance in the other variables, however, may have been related to the moderate to low observed power. Thus, we cannot confidently conclude that no mass trabecular loss was occurring in Tb.Th, Tb.Sp, Conn.D, and SMI during or following hibernation in these woodchucks (Table 4.5).

Discussion

In this study, adult woodchucks did not experience significant differences in most cortical or trabecular properties during or after hibernation (i.e., no significant bone loss occurred during hibernation). However, tibial cortical density increased significantly between all three seasons in the longitudinal study

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Fig. 4.5: Trabecular BV/TV (A), thickness (Tb.Th, B), and number (Tb.N, C) of the femoral, tibial, and humeral metaphyses did not change significantly throughout the year in a cross-sectional study of adult woodchucks.

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Table 4.5: Metaphyseal Properties of a Cross-Sectional Sample of Adult Woodchucks

Pre- 1 Post- 1 ANOVA ANOVA Bone Property Hibernation Summer Power hibernation1 hibernation1 F-statistic p-value

BV/TV 28.518 23.073 25.489 24.683 1.706 0.187 (4.087) (6.044) (3.841) (4.288) 0.745 SMI 1.069 1.272 1.132 1.346 2.534 0.076 (0.207) (0.280) (0.257) (0.251) 0.405 Tb.Th 0.144 0.139 0.140 0.150 (0.007) (0.008) (0.009) (0.014) Tb.Th/L 0.002 0.002 0.002 0.002 0.140

(0.0001) (0.0001) (0.0001) (0.0002) 1.966 0.903 Tb.N 1.982 1.654 1.826 1.655 2.369 0.090 (0.273) (0.391) (0.286) (0.268) 0.784 Femur Tb.Sp 0.358 0.417 0.387 0.416 (0.057) (0.074) (0.047) (0.082) 0.004 0.005 0.005 0.005 1.296 0.294 Tb.Sp/L (0.001) (0.001) (0.0006) (0.001) 0.524 DA 0.416 0.420 0.479 0.438 1.316 0.287 (0.052) (0.033) (0.076) (0.073) 0.942 Conn.D 26.300 20.782 22.838 21.455 0.792 0.508 (8.467) (5.879) (5.043) (8.082) 0.328 BV/TV 25.704 26.074 24.724 26.223 0.280 0.839 (3.632) (3.884) (3.786) (3.878) 0.818 SMI 1.160 1.031 1.115 1.190 0.595 0.623 (0.176) (0.209) (0.294) (0.205) 0.575 Tb.Th 0.146 0.144 0.145 0.156 (0.009) (0.011) (0.005) (0.013) Tb.Th/L 0.002 0.002 0.002 0.002 0.062 (0.0001) (0.0002) (0.0001) (0.0002) 2.725 0.136 Tb.N 1.754 1.820 1.703 1.683 0.386 0.764 (0.196) (0.312) (0.268) (0.242) 0.830

Humerus Tb.Sp 0.395 0.402 0.432 0.433 (0.040) (0.066) (0.059) (0.074) 0.005 0.005 0.005 0.005 0.507 Tb.Sp/L (0.001) (0.001) (0.001) (0.001) 0.794 0.720 DA 0.486 0.451 0.452 0.430 1.293 0.295 (0.049) (0.028) (0.070) (0.068) 0.977 Conn.D 22.974 23.377 19.379 18.901 1.104 0.363 (5.578) (9.383) (5.069) (5.924) 0.283 BV/TV 39.314 35.467 38.153 37.005 0.715 0.551 (4.312) (6.428) (5.620) (3.716) 0.921 SMI 0.443 0.633 0.543 0.652 0.700 0.560 (0.311) (0.390) (0.438) (0.256) 0.074 Tb.Th 0.158 0.148 0.159 0.159 (0.011) (0.005) (0.010) (0.010) Tb.Th/L 0.002 0.002 0.002 0.002 0.218

(0.0002) (0.0001) (0.0001) (0.0001) 1.566 1.000

Tb.N 2.490 2.389 2.400 2.333 0.687 0.567

Tibia (0.170) (0.394) (0.303) (0.182) 0.986 Tb.Sp 0.288 0.298 0.297 0.299 (0.022) (0.050) (0.040) (0.032) 0.004 0.004 0.004 0.004 0.892 Tb.Sp/L (0.0003) (0.001) (0.001) (0.0004) 0.205 0.682 DA 0.473 0.456 0.425 0.472 2.615 0.069 (0.041) (0.039) (0.034) (0.044) 1.000 Conn.D 24.767 27.052 24.763 25.986 0.199 0.896 (4.142) (8.225) (5.693) (6.130) 0.371 1Values reported as average bone property (standard deviation). Observed power: Italicized values indicate that sample sizes provide power ≥ 0.8 to differentiate a medium effect change (5%) in bone measures between groups. Normal font is representative of large effect changes (10%). Values of effects based on percentage bone density changes in human bed rest studies (LeBlanc et al., 1990; Shackelford et al., 2004).

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and whole femoral density also was significantly greater compared to prehibernation values in the cross-sectional investigation. Greater cortical density supports the findings of a previous study that adult woodchucks increased diaphyseal bone quality during the hibernation season (Doherty et al.,

2012). On the other hand, the museum animals in that study appeared to experience decreased humeral trabecular density and B.Ar/T.Ar following hibernation. It was concluded that the small sample size was likely masking trabecular bone loss in adult woodchucks (Doherty et al., 2012). A more in-depth investigation of the trabecular network in the metaphyses conducted here suggests that trabecular bone does not change significantly across seasons in adult woodchucks.

Implications of Inactivity and Hibernation on the Adult Skeleton

Aging of the human skeleton is an unavoidable consequence of the loss of gonadal hormone function, increased inflammatory cytokines, and genetic predisposition (including ethnicity and peak bone mass at maturity) contributing to, decreased bone mass (Tung and Iqbal, 2007). Furthermore, environmental factors such as physical activity levels have been shown to have profound effects on skeletal integrity in adults (Miyagawa et al., 2011). Particularly, active lifestyles afford greater preservation of the skeleton during the physically demanding reproductive life stage as well as setting a solid structural foundation leading into advanced adulthood (Bonjour et al., 1994; Borer, 2005; Heaney et al., 2000).

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The maintenance of bone properties in seasonally inactive adult hibernators is particularly signficant in comparison to non-hibernating animals that do not maintain bone. Inactivity typically results in a significant loss of trabecular bone properties compared to cortical bone in non-hibernating mammals (Kaneps et al., 1997; Tervo et al., 2009). Cortical bone is not protected from disuse atrophy either, and has been found to experience greater degredation than trabeculae in humans (Bell et al., 1999). Moreover, although mechanical unloading has regional effects on different bones, the tibial diaphyses have been shown to significantly lose bone mineral content following 35 days of bed rest (Rittweger et al., 2009). Adult woodchucks, in contrast, can gain significant amounts of cortical bone density in the tibial diaphyses and do not experience significant trabecular bone loss in the metaphyses during extensive periods of inactivity characteristic of hibernation. Similarly, bears have been observed to maintain Ct.Ar, Iap, Iml, J, and Ct.Po (Harvey and Donahue, 2004;

Harvey et al., 2005; McGee-Lawrence et al., 2009a; McGee et al., 2008; McGee et al., 2007; Pardy et al., 2004). Adult bears do not experience significant loss in trabecular properties either, including Tb.Th, Tb.N, Tb.Sp, BV/TV, SMI, or DA

(McGee-Lawrence et al., 2009b; Pardy et al., 2004).

Smaller hibernators are observed to maintain bone following hibernation similar to bears. Marmots (Marmota flaviventris) preserved both cortical and trabecular properties, however, no age correlations were made in this study and samples could have been skewed by juvenile growth during the hibernation

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period (Wojda et al., 2012). Furthermore, adult golden mantled ground squirrels

(Callospermophilus lateralis) did not experience significant changes in whole bone density between active and hibernating seasons (Utz et al., 2009). Another species of ground squirrel (Ictidomys tridecemlineatus) maintained cortical properties, however, there were indications that trabecular bone was lost in these adult animals during hibernation (McGee-Lawrence et al., 2011). The information gained from this adult woodchuck analysis contributes to the growing body of evidence that a host of adult hibernating species are capable of preventing large scale bone loss that would normally accompany mechanical unloading during hibernation.

The ability of an adult hibernator to prevent significant bone loss during repeated seasonal periods of physical inactivy has potentially important evolutionary and clinical implications. Bone maintenance in adult woodchucks and other hibernators during annual cycles of hibernation appears to be a derived property of their skeletons that implies a convergence in protective bone physiological processes across these unusual animals. In non-hibernators, once bone is lost in individuals with active osteoporosis, it is difficult to maintain bone mass and prevent future fractures (Stevenson et al., 2005). Although numerous pharmacological agents are on the market to prevent bone loss (Stevenson et al., 2005), increased weight-bearing activities and calcium supplementation are the most recommended preventative and therapeutic steps against osteoporosis

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and skeletal fragility (National Osteoporosis Foundation, www.nof.org; Gold and

Silverman, 2004).

Defining the mechanisms by which hibernating animals can prevent bone loss may translate into effective and affordable disease prevention strategies

(Donahue et al., 2006b). Collectively, the finding that woodchucks preserve bone properties provides the basis for understanding the evolution of skeletal plasticity and its mechanistic basis in mammals. It is hoped that someday these data will significantly contribute to the advancement of our understanding of the physiological processes regulating bone density, area, and performance with future biomedical translational efforts aimed at treating human disuse osteoporosis.

CHAPTER 5

THREE-POINT BENDING TESTS COMPARING BONE STRENGTH BEFORE AND AFTER HIBERNATION IN ADULT WOODCHUCKS

Introduction

A primary function of limb bones is to withstand and transmit the forces produced by muscles during locomotion. The ability of bone to resist loads without breaking represents the strength of a bone. Strength relies on the components of the bone matrix and the geometrical structure of the bone, particularly the amount of bone material and its distribution in space (Currey,

2002a). In a healthy adult animal, regardless of size, the skeleton can typically withstand loads two to four times that required for normal functional stresses experienced during daily activities (Biewener, 1982; 1993). This safety factor of bone ensures that it can endure sudden elevated, often accidental, stresses without permanent harm to the animal (Biewener, 1982). Bone strength and other biomechanical measures contributing to the integrity of bone therefore become critical factors when considering certain physiological and environmental challenges an animal may experience in the wild that may put the skeleton at risk, such as extreme inactivity associated with hibernation and seasonal nutritional abstinence.

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Three-Point Bending and the Mechanical Properties of Bone

Bone strength is often investigated as a measure of nutritional status

(Crenshaw et al., 1981a; Tsanzi et al., 2008), mineral content (Donnelly et al.,

2010), drug and hormone therapy (Uyar et al., 2009; Zhao et al., 2011), age effects on the skeleton (Crenshaw et al., 1981a; Pezowicz and Glowacki, 2012) among a host of other determinants of skeletal health. In vitro three-point bending is a common, simple technique capable of producing close approximations of actual bone material and geometric properties with roughly symmetrical cross-sections of the bone of interest (Crenshaw et al., 1981b;

Turner and Burr, 1993). Information gained from three-point bending tests provides not only information on the strength of the bone, but also its rigidity, stiffness, yield strength (or amount of stress it can withstand before becoming permanently deformed), and the amount of energy required to break the bone.

These are all variables that are quite important to an animal’s postcranial skeleton when considering its ability to effectively avoid predators, reproduce, obtain food, and generally support its body during locomotion. Normally, bone strength exceeds the load-related requirements for an animal to function in its environment, however in situations of disease such as osteoporosis, compromised bone strength may predispose skeletal elements to catastrophic failure.

The integrity of the skeleton becomes compromised during physical inactivity (i.e., mechanical unloading) lasting for as little as two weeks (Li et al.,

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1990). Prolonged periods of mechanical loading can result in the inability of bone formation processes to restore the pre-inactive state of the bone (Lindgren and Mattsson, 1977). With this situation an animal often experiences disuse osteoporosis resulting from the greater rate of bone resorption compared to formation, so that bone formation processes never fully catch up to those of resorption even after remobilization (Parfitt, 1979). Permanent bone loss impedes the capacity of various components of the skeleton to resist deformation under loads and withstand functional stresses. Such a compromised skeleton makes the individual prone to fragility fractures.

Although most animals do not naturally experience mechanical unloading or disuse osteoporosis in the wild, hibernating animals are inactive for several months every year (up to 9 months in some Arctic animals). Despite this dormant period, many hibernators live for numerous years with little evidence that their skeletons are compromised by disuse osteoporosis. In fact, it has been found in bears (Harvey and Donahue, 2004; Harvey et al., 2005; McGee-

Lawrence et al., 2009a), marmots (Wojda et al., 2012), and ground squirrels

(McGee-Lawrence et al., 2011; Utz et al., 2009) that despite inactivity during hibernation, bone strength is not reduced. Furthermore, the results presented in previous chapters indicate that bone is not being lost in woodchucks (Marmota monax). In this study we measure woodchuck humeral, tibial, and femoral bending strength, energy at failure, elastic modulus, and other mechanical properties. We hypothesize that bone strength and mechanical properties will

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not change throughout the year despite an extended period of physical inactivity and nutritional deprivation associated with hibernation.

Materials and Methods

Animals

Animals were live trapped according to NEOMED Institutional Animal Care and Use Committee approved protocols (#08-0027, #08-0029, #11-019) and annual Ohio Division of Wildlife permits (#11-257). Eighteen adult wild woodchucks (Marmota monax) were collected for bone bending studies.

Incoming animals were euthanized by intravenously administered Fatal Plus (1 cc/10 lbs), and subsequently frozen with limbs intact for storage (Nazarian et al.,

2009; Turner and Burr, 1993; van Haaren et al., 2008) until three-point bending and computed tomography scanning (QCT) was performed. Additional trapped adult woodchucks (N = 15) were held captive for time periods up to two years and allowed to hibernate during the winter. These animals were selected for euthanasia at predetermined time points to add to the wild animal sample for three-point bending.

Age of each animal was determined following Davis (1964) and Hamilton

(1934). Age criteria included dental characteristics, radiographic indications of epiphyseal plate closures in the fore and hind limbs, pelage at time of capture, and post-mortem skeletal assessments following cold water maceration of the skeleton. Adults (one year and older) of both sexes were selected for this study.

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Any observed health problems at the time of death, such as abscesses, were assessed for severity and impact on the skeleton. Serious health concerns, such as unhealed broken bones (experienced prior to capture), disqualified the animal for inclusion in the study.

Animals were grouped based on the date of euthanasia for statistical analysis of seasonal differences. Seasonal groupings were defined as prehibernation (August - October), hibernation (November – mid-March), posthibernation (end of March - May), and summer (June – July). Total animal sample size included 17 male and 17 female woodchucks, for a total of 34 animals (Table 5.1). More animals were trapped in the summer months simply as a consequence of the voracious appetites of these animals during that season. Animals were more difficult to trap in the prehibernation season when they decrease food consumption in August in preparation for hibernation. Wild animals were not trapped during the hibernation period because they were underground; however, three captive animals (one female and two males) were euthanized for three-point bending during this time. Posthibernation animals were also difficult to acquire.

Specimen Preparation

Specimens were thawed the day of the experiment. The humerus, femur, and tibia were dissected and cleaned of all soft tissue. Total bone length, maximum diaphyseal width approximating 50% of bone length, and maximum diaphyseal height were measured using a sliding caliper. As described in

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Chapter 4, a 7.7 mm thick section of the bones was microQCT (μQCT) scanned

(Scanco Medical VivaCT 75, Switzerland) at the diaphyses approximating 50% total bone length where bending stresses would be applied. Bones were positioned horizontal to the scanner inside a radiolucent plastic cup filled with packing foam. Bone placement was approximately similar for all bones to minimize error in calculating geometrical properties. Scans were acquired using a beam intensity of 70 kVp, 114 μA, and voxel size of 20.5 μm. Bones were placed in phosphate buffered saline (pH 7.4) immediately after scanning for 15 to 20 minutes before subjecting them to three-point bending to fully rehydrate the bones after any drying that may have occurred during scanning.

Scans of each bone were converted to a .tif format and analyzed in Image

J using the Bone J Slice Geometry plugin (Doube et al., 2010). Each scan was calibrated and manually thresholded. Output of interest for three-point bending tests included second moment of area (I) and distance (mm) from the cortical surface in the vertical plane (y-axis) to the center of the bone, or centroid (c).

These values were input directly into the Instron Bluehill software (2.0) for further calculations as discussed below.

Three-Point Bending

To estimate bone strength and mechanical properties in bending, the tibia, femur and humerus were loaded to failure using a universal testing machine

(Instron ElectroPuls, E3000, Norwood, MA) with a 5 kN load cell (Fig. 5.1).

Rounded supports were positioned at the distal- and proximal-most surface of

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Fig. 5.1: The universal testing machine (Instron ElectroPuls, E3000) used to break woodchuck bones in three-point bending. Each bone (femur depicted) rested on the rounded supports and was held in place by finger-tightened clamps. Average span was 53.0 mm for all bones.

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each metaphysis where the bone rested on the supports without slipping (giving the greatest span distance along the length of the bone). Average span between the supports for all bones was 53.0 mm and the average span length to width ratio was 8.03 for each bone (Turner and Burr, 1993). The bones were held in place by finger-tightened clamps to avoid slippage while applying the crosshead.

Bones were positioned so the anterior surface of the diaphysis (approximating

50% of the bone) was subjected to anterior compression with a crosshead rate of

4 mm min-1 (Utz et al., 2009). This corresponds to a strain rate of 0.06/s, which is well within the physiologically relevant strain rate range of 0.01/s to 0.08/s

(Rubin and Lanyon, 1982).

Data were collected and analyzed using Instron Bluehill 2 Material Testing software (v. 2.25, Norwood, MA). Application of the crosshead onto the diaphysis of each bone resulted in a load-extension curve (Fig. 5.2A). This curve was automatically converted by the software into a stress-strain curve using the bone’s cross-sectional dimensions for all calculations (Fig. 5.2B). An automatic slack correction was applied to each dataset as it was produced, and standard calculations were completed for each bone by software using μQCT measurements (Table 5.1).

Briefly, the elastic modulus (E) was determined by calculating the slope of the linear portion of the stress-strain curve (Fig. 5.2B). This excluded the non- linear portions from the beginning and end of this curve. Yield strength was calculated as a line parallel to the modulus and the stress-strain curve with 0.2%

Fig. 5.2: The load-extension curve produced by a woodchuck femur in three-point bending (A). This curve was converted into a stress-strain curve using the bone’s cross-sectional dimensions (B). From this curve, elastic modulus, yield strength, breaking strength, modulus of toughness, elasticity, and ductility were determined.

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Table 5.1: Definitions and Calculations for Bone Mechanical Properties

Parameter Units Symbol Equation/Explanation Distance to Centroid mm c Distance from neutral axis to bone surface (vertical plane) 1 Second Moment of Inertia 4 mm I (vertical plane) Span mm L Direct measurement between bone supports Elastic modulus2 MPa E

Applied load at yield N PY Force applied to reach yield Applied load at failure N PF Force applied to break the bone Applied maximum load N PU Maximum force the bone can withstand

2 Yield strength MPa Ϭ Y

2 Breaking strength MPa Ϭ F

2 Ultimate strength MPa Ϭ U

Modulus of toughness J UF

Elastic energy J UY

Plastic energy J UP UF - UY Additional variables obtained from μQCT and three-point bending tests: y = perpendicular distance in the vertical plane from the neutral axis to point of bending, A = area, d = distance from the center of the bone to the vertical axis, P = force, s = displacement, u = work to failure. 1Swartz, 1993. 2Turner and Burr, 1993.

offset. Applied loads were converted into units of stress to remove the influence of the size and shape on the intrinsic properties of each bone (Turner and Burr,

1993; Turner and Burr, 2001). Yield strength was determined by dividing the product of the applied force value at yield (PY), distance between the supports holding the bone (L), and centroid (c) by four times the second moment of inertia

(Table 5.1; Turner and Burr, 1993). Breaking strength, or the stress experienced at failure, was similarly calculated using the applied load at fracture (Table 5.1).

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The modulus of toughness was determined as the amount of energy required to fracture the bone and is equivalent to the area under the stress-strain curve up to the point of failure (Fig. 5.2B). The area under the curve was further divided into the elastic region and the plastic region (Fig. 5.2B). The elastic region represents the energy expended before yield and the ability of bone to resist permanent deformation. The plastic region (that region under the stress- strain curve between yield and failure) corresponds to the ductility of the bone before it fails (Turner and Burr, 2001). Some bones were ductile and experienced ultimate strength values, or maximum stresses, that exceeded those at fracture (Turner and Burr, 1993). In these cases, ultimate strength was derived by using the applied maximum load (PU, Table 5.1).

Statistical Analysis

Data were analyzed using univariate ANOVAs (SPSS 19.0) to test the hypothesis that woodchucks do not experience a change in bone mechanical properties throughout the year. Sex was initially included as a cofactor along with season in the univariate ANOVA, but this cofactor was removed from the final analysis of a given bone section when not initially significant (Berry and

Feldman, 1985). Statistical significance was determined using a Bonferroni adjustment based on examining three bones to indicate that the final α = 0.017

(0.05/3) was significant (Quinn and Keough, 2002). Furthermore, main effects between seasons were investigated using Bonferroni post-hoc analyses to compare bone mechanical properties between seasons.

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It is hypothesized there will be no significant change in bone strength and other mechanical properties following hibernation. As such, statistical power was calculated for each ANOVA analysis to report the likelihood of committing Type II errors. This effectively reduces the chance of failing to reject a hypothesis when significant differences exist between seasons, but are masked by the effects of a small sample size or high statistical variation. A power ≥ 0.8 (1-β) was considered to be appropriate (Cohen, 1977). Large effect sizes were estimated to be 25% change and small effect size to be 10% change in bone mechanical properties for calculating statistical power.

Results

Males had more ductile femora than females (p = 0.017) and nearly required significantly more work to failure (p = 0.018) than females across the four seasons (Table 5.3). Although not significant in the humerus or tibia, females tended to have more brittle bones that required less energy to break than males (Table 5.3). No other significant sex differences were found and

Table 5.2: Adult Woodchuck Sample

Sex Season Total Male Female Prehibernation 5 3 8 Hibernation 2 1 3 Posthibernation 4 4 8 Summer 6 8 14 Total 17 16 33

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Table 5.3: Sex Differences in Mechanical Properties of Woodchuck Bones

Sex1 ANOVA ANOVA Bone Parameter Power Male Female F-statistic p-value Modulus of 0.632 0.495 6.423 0.018 - toughness (MPa) (0.23) (0.22) Femur Plastic Energy (J) 0.498 0.364 6.548 0.017 - (0.22) (0.23) Modulus of 0.882 0.726 5.410 0.029 0.938 toughness (MPa) (0.29) (0.21) Humerus Plastic Energy (J) 0.526 0.417 4.663 0.041 0.477 (0.31) (0.26) Modulus of 0.515 0.433 0.510 0.482 0.900 toughness (MPa) (0.17) (0.16) Tibia Plastic Energy (J) 0.285 0.220 0.341 0.564 0.479 (0.17) (0.15) 1Values reported as averages (standard deviation). Bold values significant at the α = 0.0167 level after Bonferroni adjustment (0.05/3 bones). Observed power: Normal font indicates that sample size provides power ≥ 0.8 to differentiate a large effect change (25%) in mechanical properties between groups.

there were no significant season interaction effects with sex. Sex was therefore removed as a cofactor in all other analyses and season was examined as a single factor in assessing changes in bone biomechanical properties.

The elastic modulus of the femur was decreased significantly in the summer compared to prehibernation and posthibernation seasons (p = 0.003,

Fig. 5.3, Table 5.4). Femoral stiffness (elastic modulus) was also decreased during hibernation compared to pre- and posthibernation but this was not significantly different likely because of the small sample size of the hibernation group (i.e., the three captive animals terminated during torpor, Table 5.4).

Decreased stiffness (although not significant) was also observed in the humerus.

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The tibia did not show any indication of decreased stiffness in the hibernation period (Fig. 5.3, Table 5.4).

No other statistically significant differences were found in the biomechanical properties of the femur, humerus, or tibia (Table 5.4). There were, however, trends of decreased bone strength in all three bones during hibernation. Breaking strength was reduced at this time in the femur and tibia compared to summer values with an apparent recovery of that strength again in the posthibernation season (Fig. 5.4A). Yield strength seemed to decrease during hibernation in the humerus and tibia (Fig. 5.4B) and this pattern was similar to that observed in ultimate strength for these two bones (Table 5.4).

Interestingly, the modulus of toughness increased in all three bones during hibernation (Fig. 5.4C), so the amount of work required to break a bone was

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Fig. 5.3: The elastic modulus of the woodchuck femur was decreased significantly in the summer compared to prehibernation and posthibernation. There was no significant difference in the stiffness of the humerus and tibia between seasons.

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Table 5.4: Three-Point Bending Properties of Adult Woodchuck Bones

Pre- 1 Post- 1 ANOVA ANOVA Bone Parameter 1 Hibernation 1 Summer Power hibernation hibernation F-statistic p-value Elastic modulus 13214.94 9619.96 13559.80 9901.11 6.008 0.003 - (J) (2400.1)a (2390.9) (2384.9)a (2406.7)b Yield Strength 122.97 115.73 125.35 147.63 2.946 0.049 1.000 (MPa) (27.901) (28.230) (25.646) (20.149) Breaking 129.65 120.65 130.91 148.03 1.439 0.252 0.998

strength (MPa) (32.818) (34.074) (24.729) (24.150) Ultimate 134.12 135.20 141.17 162.66 2.205 0.109 0.994 strength (MPa) (33.513) (46.690) (32.330) (17.986) Femur Modulus of 0.458 0.662 0.534 0.624 1.556 0.225 0.408 toughness (J) (.193) (0.411) (0.217) (0.223) Elastic region 0.201 0.162 0.187 0.190 0.486 0.695 0.995 (J) (0.051) (0.043) (0.049) (0.048) Plastic region 0.325 0.552 0.401 0.488 1.494 0.240 0.226 (J) (0.181) (0.405) (0.223) (0.220) Elastic modulus 2784.90 1888.24 2548.34 2593.89 0.574 0.637 0.867 (J) (798.2) (779.6) (1285.3) (938.7) Yield Strength 189.55 162.57 177.11 174.42 0.896 0.456 0.832 (MPa) (22.415) (33.107) (27.173) (25.659) Breaking 191.90 180.74 179.16 178.24

0.213 0.887 0.998 strength (MPa) (32.814) (69.986) (36.007) (35.488) Ultimate 203.37 190.59 188.66 194.06 0.297 0.827 1.000 strength (MPa) (25.775) (62.778) (23.685) (29.918)

Humerus Modulus of 0.806 0.843 0.680 0.877 1.206 0.329 0.889 toughness (J) (0.211) (0.363) (0.205) (0.289) Elastic region 0.425 0.350 0.372 0.324 1.310 0.291 1.000 (J) (0.095) (0.030) (0.089) (0.135) Plastic region 0.414 0.520 0.329 0.580 1.705 0.193 0.281 (J) (0.200) (0.399) (0.224) (0.323) Elastic modulus 7023.59 7268.86 7225.97 6980.43 0.038 0.990 0.991 (J) (1906.4) (1233.7) (1668.8) (2219.9) Yield Strength 272.47 213.83 242.95 221.70 2.923 0.051 0.843 (MPa) (38.239) (33.334) (34.417) (47.576) Breaking 222.12 166.15 216.97 182.31 2.985 0.047 1.000

strength (MPa) (31.831) (37.415) (45.858) (39.907)

Ultimate 276.83 216.97 252.85 228.84 2.906 0.051 0.873

Tibia strength (MPa) (36.684) (32.186) (33.782) (47.312) Modulus of 0.466 0.512 0.467 0.478 0.141 0.934 0.924 toughness (J) (0.135) (0.056) (0.193) (0.197) Elastic region 0.318 0.259 0.273 0.256 2.642 0.068 0.800 (J) (0.055) (0.028) (0.065) (0.042) Plastic region 0.209 0.309 0.246 0.271 0.565 0.643 0.305 (J) (0.111) (0.067) (0.192) (0.184) 1Values reported as average mechanical properties (standard deviation). Bold values significant at the α = .0167 level after Bonferroni adjustment (0.05/3 bones). a,b Denotes significant differences between seasons using Bonferroni post-hoc analysis (α=.05). Observed power: Normal font indicates that sample size provides power ≥ 0.8 to differentiate a large effect change (25%) in mechanical properties between groups. Bold power values represent effect changes of 10%.

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Fig. 5.4: There were no other significant differences in the bending properties of the femur, humerus, or tibia. Trends in the data indicated that breaking strength may be reduced in the femur and tibia compared to summer with an apparent recovery in the posthibernation season (A). Yield strength seemed to decrease during hibernation in the humerus and tibia (B). In contrast, bone toughness appeared to increase in all three bones during hibernation (C).

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increased in this season. Most of these properties were elevated again to near prehibernation values by the posthibernation season.

Discussion

The results of this study largely support the hypothesis that there is no significant difference in bone strength and other mechanical properties throughout the year in hibernating woodchucks. However, the intrinsic stiffness of the femur, which likely affects the overall strength of bone, did appear to decrease during the summer and hibernation periods. Furthermore although not significant, there was indication that breaking strength, yield strength, and the ultimate strength was seasonally reduced during hibernation. These biomechanical properties were restored during the posthibernation and/or summer seasons. Considering that all bones tended to require more energy to fracture and that they were apparently more plastic during hibernation, long bones at this time may be tougher than that of an active animal. This would equate to an inherently weaker bone, but one that experienced more post-yield deformation before breaking. A complicating factor of these results is the small sample size of the hibernation group, however there was high statistical power for many of the mechanical properties to report large effect changes of 25%.

Despite any decreasing trend during hibernation, woodchucks appear to rebound, if not exceed prehibernation values, in strength and other

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biomechanical properties in the posthibernation and summer seasons indicating that no net loss of bone occurs over the course of the year.

The results found here corroborates those found in hibernating ground squirrels, especially considering that the mean extrinsic stiffness and ultimate stress were lower and failure energy higher, although not significantly, in hibernating ground squirrels (McGee-Lawrence et al., 2011). This suggests that some mineral loss may occur despite the lack of significant results. Furthermore, indications of microstructural bone loss were histologically documented in these ground squirrels (McGee-Lawrence et al., 2011). Aestivating frogs experienced no significant change in femur or tibia strength, but several bone properties tended to be reduced during 3 and 9 months of aestivation compared to control animals (Hudson et al., 2004).

The possibility that mechanical properties may be changed during hibernation, resulting in a bone that is less stiff but requires more energy to failure, raises important questions regarding the biological implications of any imbalance in the bone remodeling system. Certainly, lack of decreased morphological changes in woodchucks indicates that the structural framework of the bones remains largely intact between seasons, and in some cases (i.e., cortical density) actually increases following hibernation (Chapter 3 and 4). The changes in woodchuck mechanical properties somewhat resembles that of mineral loss associated with osteomalacia in humans (Maricic, 2008).

Osteomalacia is commonly associated with hypovitaminosis D, whether from

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inadequate intake through the diet, limited sun exposure, or the inability to metabolize vitamin D effectively (Maricic, 2008). Classically, osteomalacia is described in cases of Rickets (Chesney, 2001), but it is also prevalent in societies with limited sun exposure and can be a secondary cause of osteoporosis (Holick et al., 2005). Osteomalacia results in bones that are under- mineralized with an increased modulus of toughness, unlike the brittle bones characteristic of osteoporosis (Turner, 2002).

In hibernating woodchucks, loss of bone minerals, such as calcium and inorganic phosphate, may contribute to a potential decrease in stiffness and strength of bone (see Chapter 6). Woodchucks primarily obtain vitamin D through their diet (25-OH D2) and grooming/UV exposure (25-OH D3), thus during hibernation when woodchucks neither eat nor groom, it is possible that the decreasing trend in bone mechanical properties could be a result of mineral loss because of low vitamin D concentrations. The organic matrix of the skeleton, primarily consisting of collagen, would then be responsible to a greater extent for contributing to the ductility of bone before fracture, as is suggested by the data presented above. In hibernating bears, animals that do not experience disuse osteoporosis with hibernation, no change was found in seasonal serum levels of total 25-OH D (Donahue et al., 2006a; Vestergaard et al., 2011). However, total

25-OH D in a different bear study masked significant differences in seasonal levels of the derivatives of 25-OH D, specifically an increase in 25-OH D2 and decrease in 25-OH D3 (Vestergaard et al., 2011). The rise in vitamin D2 during

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hibernation was hypothesized to result from metabolizing prehibernation stores of fat from food rich in 25-OH D2 (Vestergaard et al., 2011). Thus there is a highly orchestrated balance in seasonal bioactivity of vitamin D forms, and their relative contributions to the biomechanical properties of the skeleton during hibernation remains to be elucidated.

A factor to consider in this woodchuck study is the contribution of multiple hibernation seasons on the aging skeleton of the woodchucks under study. In humans, bone mineral density begins to decline around 40 years of age and progresses as individuals get older (Lips et al., 1978). Eventually, annual decline in bone mass can lead to osteoporosis, particularly in postmenopausal women, and have profound impact on the projected treatment and lifespan of the patient

(Newton-John and Morgan, 1968; Riggs and Melton, 1983). Loss of bone mineral density and mass results in bones that are stiff and brittle, requiring little energy for failure (Turner, 2002). In contrast, hibernating bears have been shown to experience similar breaking strength, elastic modulus, and have a higher ash fraction as they increase in age (Harvey and Donahue, 2004; McGee-

Lawrence et al., 2009a). Furthermore, cortical tensile strength was not compromised and cortical porosity decreased in older individuals (Harvey et al.,

2005).

Woodchucks cannot be aged accurately beyond two years of age, but considering that the captive woodchucks were housed for up to two years in this study, it can be determined that certain captive animals were three years or

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older. This is particularly relevant when considering the hibernation sample, which included one female and male greater than 3 years and one male that was

2 years of age (determined by age status when captured and duration of captivity). Was advanced age a factor in the reduction in bone strength in this hibernation group? It is known that juvenile hibernators maintain, and often exceed, prehibernation levels of bone mechanical, geometrical, and histological properties (Doherty et al., 2012; McGee-Lawrence et al., 2011; Wojda et al.,

2012). Thus there is an age effect on bone at least until an animal reaches skeletal maturity. However, wild animals included in this study were only excluded if they were less than one year of age and older animals were only removed from investigation if they showed signs of disease or had experienced previous fractures (ascertained by radiographic images). Considering that the captive animals (N = 15) could, on average, be older than the wild caught animals (N = 18), a multivariate ANOVA was conducted using captivity as a cofactor with hibernation and their interaction effect examined (data not shown).

There was no significant difference between captive and wild woodchucks in any of the parameters under investigation, nor was there any significant interaction between hibernation and captivity. It is assumed therefore, that this woodchuck sample did not experience aging related bone loss.

It is actually quite remarkable, in comparison to non-hibernating animals, that there is no pronounced loss of overall bone mechanical properties. With just two weeks of immobilization, it was found that young adult rats experienced a

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significant decline in extrinsic stiffness, yield, and ultimate strength of the femur following 4 weeks of remobilization (Trebacz, 2001). Two weeks immobilization is nearly equivalent to the maximum length of one woodchuck torpor bout that was 324 hours long, or 13.5 days (Chapter 1, Fig. 1.2). In comparison to rats, this suggests that woodchucks are capable of preventing large scale reductions in the mechanical properties of their bones during physical inactivity associated with the duration of the hibernation season. Furthermore, to recover the mechanical bone parameters following induced inactivity, it requires at least twice the length of time the animal was immobilized (Kaneps et al., 1997). Young adult dogs (Canus lupus familiaris) exhibited signs of weaker bones despite 16 weeks of exercise and weight-bearing activity following 16 weeks of immobilization

(Kaneps et al., 1997). It was not until 32 weeks, or 8 months, of physical activity that there was a recovery of bone properties to control levels. One exception to a long recovery period of bone following inactivity has been observed in Alaskan red-backed voles (Myodes rutilus). These animals are capable of restoring bone mineral density quickly after extremely reduced activity, but not hibernation, in the winter (Stevenson et al., 2009). The fact that many hibernators, including the woodchucks of this study, marmots (Wojda et al., 2012), ground squirrels

(McGee-Lawrence et al., 2011; Utz et al., 2009), and bears (McGee-Lawrence et al., 2009a), have no significant difference in bending properties between prehibernation and posthibernation seasons indicates that they not only are protected from inactivity induced net bone loss, but also have the ability to

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recover any bone structural components that may have been lost during hibernation within a very short time period after remobilization. This pattern is unlike that seen in most non-hibernating animals.

The ability of woodchucks to avoid a net loss of bone strength and mechanical properties after an extended period of hibernation is further indication that hibernators are adapted to seasonal physical inactivity. Despite reduced stiffness during the summer and hibernation season, bone integrity remains relatively intact throughout the year with no annual loss of bone that would impact the animal in its ability to survive. Woodchucks appear to have the ability to recover any loss of bone mechanical properties experienced over the course of hibernation quickly in order to enter the next hibernation season at or above the previous year’s prehibernation levels. This conclusion is further supported by the lack of change in the morphological properties of woodchuck bone (Chapter 3 and 4) and the immediate ability of these animals to resume normal locomotion following hibernation (Chapter 2). Determining the regulation of the balanced resorption and formation processes characteristic of bone remodeling in a seasonally inactive animal is the next step in uncovering the unique skeletal advantage hibernators posses that may unlock future biomedical applications for improved bone health and disease prevention.

CHAPTER 6

ANALYSES OF SEASONAL CHANGES IN BLOOD SERUM TO ASSESS BONE MAINTENANCE IN HIBERNATING AND ACTIVE WOODCHUCKS

Introduction

Strong bones are essential to human health and quality of life. According to the National Osteoporosis Foundation, bone diseases, such as osteoporosis, afflict millions of Americans and place more than half of the U.S. population over

50 years of age at risk of bone fragility fractures (www.nof.org). It is clear that bone quality is impacted by numerous, interacting factors throughout an individual’s lifetime (Gold and Silverman, 2004; Kasturi et al., 2009; Seeman,

2003; Winsloe et al., 2009). Physical activity levels (Borer, 2005; Guadalupe-

Grau et al., 2009; LeBlanc et al., 1990; Zerwekh et al., 1998) and nutrient intake

(Eastell and Lambert, 2002; Rizzoli, 2008; Stransky and Rysava, 2009; Tucker,

2009) play major roles in thwarting or advancing the progression of chronic bone diseases such as osteoporosis. The complex etiology of many bone diseases, however, remains to be fully elucidated despite significant advances in our understanding of bone disorders (Frost, 2003; Kasturi et al., 2009; Rosen and

Klibanski, 2009; Winsloe et al., 2009).

Throughout an individual's lifetime, the tissues comprising the skeleton are continually being maintained by cellular regulation. Bone modeling

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encompasses the processes of bone development and growth. Bone remodeling, in contrast, is the continual cellular regulation of bone throughout adulthood. Osteoblasts regulate the differentiation and activity of osteoclasts to degrade the surface of bone followed by the deposition of new bone by osteoblasts. Bone formation processes are 3 to 4 months slower than those of resorption (Parfitt, 1979), however in healthy individuals, remodeling results in a net maintenance of bone. With advancing age, bone loss begins to weaken the skeleton and makes it more prone to fracture (Lips et al., 1978; Newton-John and

Morgan, 1968; Riggs and Melton, 1983; Tung and Iqbal, 2007). Decreasing activity level, poor nutritional standards, hormonal changes with aging, and pharmaceutical agents can further increase disease risk (Gold and Silverman,

2004; Kasturi et al., 2009; Seeman, 2003; Winsloe et al., 2009).

Unlike humans, extended periods of inactivity and nutritional deprivation lasting several months are the norm for hibernating mammals (Geiser, 1995;

Grizzell, 1955; Johnson, 1931; Lyman et al., 1982; Rasmussen, 1916). Several studies show that torpid bears maintain a balance between bone resorption and formation that prevents annual losses of bone (Donahue et al., 2006a; Donahue et al., 2006b; Donahue et al., 2003b; Floyd et al., 1990; Harvey and Donahue,

2004; Lennox and Goodship, 2008; McGee et al., 2008; McGee et al., 2007).

Other hibernators, such as some ground squirrels (Haller and Zimny, 1977), bats

(Doty and Nunez, 1985), and hamsters (Steinberg et al., 1981), are thought to lose bone during and immediately after hibernation based on histology. In

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contrast, more recent studies of rodent hibernators, such as woodchucks

(Doherty et al., 2012), ground squirrels (Utz et al., 2009), and marmots (Wojda et al., 2012), have demonstrated that small hibernators may also be able to avoid bone loss throughout hibernation. Despite conflicting information regarding the effects of hibernation on mammalian bone, it is clear that physiological mechanisms exist in hibernators that allow them to avoid extreme bone loss that would impact their activity following hibernation. This is evident in that non- hibernating animals experience significant loss of bone following extensive physical inactivity and nutritional deprivation (Borer, 2005; Eastell and Lambert,

2002; Guadalupe-Grau et al., 2009; LeBlanc et al., 1990; Rizzoli, 2008; Stransky and Rysava, 2009; Tucker, 2009; Zerwekh et al., 1998).

Blood Serum Analysis of Bone

Direct determination of bone mineral density is assessed using dual energy x-ray absorptiometry (DXA) and other bone imaging techniques. In the case of osteoporosis, however, further diagnostic tools are required to identify overall skeletal status because nearly half of all women at risk for this disease do not fall below the diagnostic threshold established using DXA (Lenora et al.,

2010). Biochemical analysis of blood serum and urine is used in conjunction with

DXA to obtain additional information about the skeleton and the bone formation and resorption processes that are active at the time of testing. In particular, serum analysis is used to identify individuals at risk for fragility fractures, predict

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bone loss and the development of osteoporosis, and to assess treatment therapy

(Lenora et al., 2010).

The advantage of biochemical serum analysis is significant in that it provides a mechanism to assess the cellular activity and processes relating to bone quality and health in an affordable and reliable manner for health professionals and research laboratories alike. Enzyme-linked immunosorbent assays (ELISAs) are commercially available and can be accurately performed with access to the most basic laboratory supplies. Furthermore, the coupled nature of bone formation with resorption processes provides a good system to identify how one becomes out of sync with the other. Changes in any of the markers (i.e., formation or resorption) are indicative of bone metabolic disturbances (Eastell and Hannon, 2008).

In this study, we used serum collected from hibernating woodchucks in comparison to computed tomography scans of bones (see Chapters 3 and 4), similar to the DXA and biochemical routines used in clinical settings to determine skeletal health in ageing individuals. Serum analysis affords certain benefits in hibernation studies, considering that blood is easy to obtain, the procedure disturbs a hibernating animal minimally, and the analysis can be informative of numerous osteoblastic/osteoclastic processes indicative of bone formation and/or resorption.

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Bone Biology

Osteoprotegerin/RANKL: Bone remodeling, specifically bone resorption, is primarily modulated by osteoblastic production and control of the extracellular ratio of osteoprotegerin (OPG) and RANKL (receptor activator of NFкB ligand,

Fig. 6.1). RANKL interacts with its RANK receptor located on the membrane surface of osteoclasts to initiate osteoclastogenesis, osteoclast differentiation, and bone resorption (Boyce and Xing, 2008; Kobayashi et al., 2009; Seibel et al.,

2006). OPG is produced by osteoblasts and acts as a decoy receptor to RANKL

(Fig. 6.1). OPG binding to RANKL prevents the binding of RANKL to RANK and therefore blocks osteoclast activity (Boyce and Xing, 2008; Kobayashi et al.,

2009; Robling et al., 2006; Seibel et al., 2006). New serum assays have been developed to directly measure the quantity of OPG and RANKL. In this study, we will report OPG concentration in a hibernating animal for the first time (Table 6.1).

Parathyroid hormone, calcium, and inorganic phosphate: Traditionally, serum analyses have not focused specifically on OPG and RANKL, but rather on endocrine hormone concentrations regulating osteoblastic bone formation and resorption. The skeleton, under the control of PTH, acts as the primary store of essential ions (such as calcium (Ca) and inorganic phosphate (PI)) required for normal cellular functions (Berne et al., 2004; Blair et al., 2007). PTH secretion is increased to mobilize Ca (and concomitantly PI) into circulation from the skeleton by stimulating bone resorption (Berne et al., 2004; Kousteni and Bilezikian,

2008). Specifically, PTH binds its G protein-coupled receptor (PTHR1) on

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Fig. 6.1: Several of the mechanisms regulating bone formation and resorption processes.

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Table 6.1: Bone Serum Formation and Resorption Markers

Bone Acronym Origin Classification Function in bone Formation Mineralization mediator; hydrolyze inhibitors of Alkaline Bone, liver, kidney, Hydrolase ALP mineralization (Seibel et al., Phosphatase bile duct, placenta enzyme 2006)

Unknown, may signal to Noncollagenous pancreatic beta cells Osteocalcin OC Osteoblasts protein, (Ferron et al., 2008; Seibel hormone et al., 2006)

Decoy receptor to RANK, Osteoblasts, heart, inhibit bone resorption kidney, liver, spleen, Cytokine (Boyce and Xing, 2008; Osteoprotegerin OPG marrow, adipocytes, receptor Seibel et al., 2006; Simonet others et al., 1997)

Bone Acronym Origin Classification Function in bone Resorption Mineral structure of bone Skeletal reserves, Calcium Ca Mineral ion (Seibel et al., 2006) diet

Mineral structure of bone Inorganic Skeletal reserves, P Mineral ion (Seibel et al., 2006) Phosphate I diet

Bone scaffolding; Osteoblasts, C-telopeptide Type I collagen mineralization mediator ICTP fibroblasts, Type I collagen fragment (Seibel et al., 2006) odontoblasts, others

Inhibit bone formation, Adipocytes, promote resorption, placenta, ovaries, Polypeptide carboxylate OC (Karsenty, Leptin Leptin skeletal muscle, hormone 2006; Seibel, 2006; Ferron others et al., 2010)

Osteoclast adhesion, differentiation, and function; Bone, kidney, brain, Matricellular inhibit mineral formation Osteopontin OPN gut, others protein (Alford and Hankenson, 2006; Sodek et al., 2000)

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osteoblasts to increase RANKL production, exceeding the available OPG to bind to its RANK receptor on the surface of osteoclasts, and subsequently stimulate bone resorption (Murrills, 2006). The circulation of Ca and PI is tightly regulated; however an increase in these ions in the serum of a fasted and otherwise healthy animal can thus be an indication of active bone resorption (Table 6.1).

Leptin: Leptin, an adipocyte-derived hormone, also acts to modulate

OPG and RANKL production by osteoblasts. This hormone regulates bone mass, body fat mass and reproductive capabilities. In the mature skeleton, leptin acts primarily on bone through the sympathetic nervous system involving two distinct mechanisms (Fig. 6.1, Table 6.1). One pathway activates β2-andrenergic receptors on the membrane of osteoblasts to decrease cell activity, decrease osteoblast differentiation, and increase RANKL expression (Karsenty, 2006;

Kawai et al., 2009; Lee and Karsenty, 2008; Thomas, 2004). A second pathway upregulates expression of the cocaine amphetamine regulated transcript (CART, a neurotransmitter) in the hypothalamus which inhibits expression of RANKL in osteoblasts by an unknown mechanism (Karsenty, 2006; Kawai et al., 2009; Lee and Karsenty, 2008; Thomas, 2004). These two pathways collectively act to balance formation and resorption by affecting the RANKL/OPG pathway (Seibel et al., 2006), however, in general leptin has been shown to inhibit bone formation activity and favor bone resorption (Ducy et al., 2000a).

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Osteocalcin: Leptin also modifies glucose metabolism through the down regulation of the osteoblastic product osteocalcin (OC). Osteocalcin is a noncollagenous protein exclusively produced by active osteoblasts that has a high affinity for hydroxyapatite and comprises about 20% of the organic matrix in bone

(Seibel et al., 2006; Wolf, 1996; 2008). Because it is only produced by osteoblasts, OC is a clinically-established marker of osteoblastic activity, bone formation rate, and calcium accretion (Fig. 6.1, Table 6.1) (Brown et al., 1984;

Seibel et al., 2006). However OC is not mechanistically involved in the bone formation process (Ducy et al., 1996). Until recently, the function of OC was largely unknown.

Energy metabolism studies have found correlations among fat mass, leptin, and the skeleton (Iwaniec et al., 2007; Kawai et al., 2009; Lee and

Karsenty, 2008; Lee et al., 2007; Wolf, 2008). It is currently thought that central leptin indirectly inhibits insulin production by stimulating OST-PTP (an osteoblastic regulator of energy metabolism) carboxylation of OC and also potentially blocking the osteoblast insulin receptor (Confavreux et al., 2009;

Karsenty and Ferron, 2012). As such, leptin not only inhibits bone formation but also effectively decreases circulating OC. Carboxylated OC has high affinity for hydroxyapatite and is usually associated with the bony matrix (90% affinity), but uncarboxylated OC has reduced bioactivity and is found dissociated from bone in blood circulation (Ferron et al., 2008). Uncarboxylated OC is believed to regulate glucose metabolism by acting on pancreatic β-cells to increase production of

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insulin and adiponectin, thereby decreasing blood glucose levels (Ferron et al.,

2008; Ferron et al., 2010). Both leptin and insulin have been implicated in altering the carboxylation of OC as well as influencing osteoblastic regulation of bone resorption (Ferron et al., 2010; Hinoi et al., 2008).

However, osteocalcin fragments released during bone matrix resorption have been investigated in urine as a marker of bone turnover, including resorption (Ivaska et al., 2005). There are many fragments of osteocalcin found in serum, of which are speculated to be produced during osteoblastic protein synthesis, proteolysis in blood, and catabolism of the protein during bone resorption (Seibel et al., 2006). Specific fragments of OC were identified in urine as a predictor of future fractures in elderly women, however serum OC did not indicate the same predictive pattern (Garnero, 2008; Gerdhem et al., 2004).

Serum OC is still currently used as an estimate of bone formation rates and osteoblast activity (Eastell et al., 1988). In the study presented here, we assess total serum osteocalcin as an estimate of osteoblast activity in woodchucks.

Furthermore, the regulation of OC and energy storage by the skeleton could be an exciting new avenue to explore bone metabolism in hibernators considering the drastic change in fat mass experienced by these animals on a seasonal basis.

Alkaline Phosphatase: Like OC, alkaline phosphatase (ALP) is also produced by osteoblasts, although not exclusively as bone and liver ALP enzymes make up the majority of the total ALP concentration in blood serum

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(Bronner and Farach-Carson, 2004; Christenson, 1997; Seibel et al., 2006).

Bone ALP is embedded in the membrane of osteoblasts and although its exact function remains unknown, ALP is found in high concentrations during bone formation (Fig. 6.1, Table 6.1; Bronner and Farach-Carson, 2004; Christenson,

1997; Seibel et al., 2006). Given its abundance during mineralization, bone ALP is hypothesized to assist in apatite formation by concentrating mineral ions and assisting in the attachment of osteoblasts to mineralizing substrates

(Christenson, 1997; Moss, 1992). In addition, its ability to hydrolyze pyrophosphates suggests that ALP supports mineralization by removing crystallization inhibitors from the matrix (Moss, 1992). Clinically, total serum ALP is used to measure overall bone turnover and osteoblast activity (Christenson,

1997).

Osteopontin: Osteopontin (OPN) is also a non-collagenous protein that is abundant in the organic matrix of bone (Franzen and Heinegard, 1985), however it is classified as a matricellular protein that directly regulates cell function (Bornstein and Sage, 2002). Matricellular proteins have roles in cell and matrix interactions and do not typically contribute to the structural organization of the tissue they comprise, although they are not excluded from performing structural functions as well (Bornstein and Sage, 2002). Osteopontin attracts osteoclasts to the site of bone resorption and assists with cell adhesion by anchoring osteoclasts to the bone surface (Fig. 6.1, Table 6.1; Reinholt et al.,

1990). OPN knockout mice are incapable of resorbing ectopically implanted

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bone discs unless stimulated with exogenous OPN (Asou et al., 2001).

Furthermore, OPN has been shown to inhibit hydroxyapatite mineral formation

(Hunter et al., 1994). Although OPN is produced by osteoblasts, osteoclasts, and a host of non-bone related cells, its expression is associated primarily with mineral resorption processes and is considered a useful marker of bone loss

(Mosig and Martignetti, 2012).

ICTP: In addition to bone cell products, the degradation of the bony matrix during resorption produces analytes available for bone remodeling analysis. Type I collagen is a triple helical protein cross-linked by hydroxylysine and lysine (or their derivatives; Seibel et al., 2006). It comprises 90% of the organic matrix in bone (Bronner et al., 2005). During bone degradation, a carboxy-terminal cross-linked telopeptide of type I collagen (ICTP) is cleaved from the mature collagen fiber by matrix metalloproteinases (Fig. 6.1, Table 6.1;

Seibel et al., 2006). This peptide is released into the blood and has been used to quantify bone resorption rates and mineral density (Ehlers and Leary, 2008;

Seibel et al., 2006).

In this study we examined bone serum markers in hibernating woodchucks. Following previous bone marker studies in bears (Donahue et al.,

2006a) and incorporating a number of new markers routinely used in clinical settings, we investigated serum protein levels indicative of bone resorption (PTH,

RANKL, ICTP, OPN), inhibition of bone formation/promotion of resorption (leptin), and factors associated with bone formation (OPG, ALP, OC). Furthermore, we

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tracked changes in serum levels of calcium (Ca) and inorganic phosphatase (PI) ions before and after hibernation to compare serum ionic concentrations with markers indicative of bone remodeling processes. The goals of this project were to 1) characterize concentrations of serum bone markers indicative of bone formation and resorption processes in captive and wild woodchucks, and 2) determine if extended physical inactivity and nutrient deprivation associated with hibernation predisposes a rodent hibernator to experience elevated bone resorption above that of formation as would be expected of a non-hibernating animal. Woodchucks emerge from hibernation annually without visible signs of musculoskeletal distress and we have found that cortical densities of the long bones do not change significantly following hibernation (Doherty et al., 2012; see also Chapter 4). Based on these observations, we hypothesized that markers of bone formation and resorption were in net stasis (or coupled) throughout the year reflecting a balance in annual bone metabolism in woodchucks. To assess the coupling of markers we used a cross-correlation function on a sample of captive woodchucks measured throughout the year to determine the relationships between the various analytes of interest over time. In so doing, we expected that analytes of both formation and resorption processes would be temporally correlated throughout the year.

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Materials and Methods

Animals

Woodchucks (Marmota monax) were trapped live from Portage County,

OH according to Northeast Ohio Medical University (NEOMED) Institutional

Animal Care and Use Committee approved protocols (#08-0027, #08-0029, #11-

019) and annual Ohio Division of Wildlife permits (#11-257). Animals were trapped using box traps with permission on private land and on the NEOMED campus.

Immediately following capture, animals were transported to the NEOMED

Comparative Medicine Unit (CMU) for initial processing. All animals were anesthetized in the box trap with an intramuscular injection of ketamine (50 mg/kg) and xylazine (5mg/kg). Isoflurane gas was administered by face mask as needed for all data collection procedures. Select animals were incorporated into a longitudinal captive animal study, tagged and released, or euthanized on capture. Animals included in the captive animal study were examined separately from wild animals except for the initial serum collection session. The longitudinal captive study consisted of 12 animals (6 males and 6 females, Table 6.2). The wild animal study, including the first serum draw from the captive animals, included 43 individuals (20 male and 23 female, Table 6.2).

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Table 6.2: Adult Woodchuck Samples

Cortical Ca P ICTP OC Leptin OPG OPN I ALP Density Study Sex (mg/ (mg/ (ng/ (ng/ (ng/ (ng/ (ng/ (U/L) (mg/ dL) dL) mL) mL) mL) mL) mL) 3 cm )

Female 6 6 6 6 6 6 6 4 6

Captive Male 6 6 6 6 6 6 6 5 6

Total 12 12 12 12 12 12 12 9 12

Female 23 23 22 23 22 20 22 13 17 Wild Male 20 20 20 19 19 18 20 15 17 Total 43 43 42 42 41 38 42 28 34

Animal Assessment and Data Collection

Once a woodchuck was fully anesthetized, the animal was removed from the box trap. A general assessment of health was made, including weight, rectal temperature, tooth wear, sex, and age. Age of each animal was determined following Davis (1964) and Hamilton (1934). Age criteria included dental characteristics, radiographic indications of epiphyseal plate closures in the fore and hind limbs, pelage at time of capture, and post-mortem skeletal assessments following cold water maceration of the skeleton. Adults (one year and older) of both sexes were selected for this study. Any observed health problems, such as abscesses, were assessed and treated topically. Serious health concerns, such as unhealed broken bones (experienced prior to capture), disqualified the animal from inclusion in the study. Additional physical measurements included limb length and circumference, body length, chest and neck circumference.

Computed tomography scans were taken of the tibial diaphysis using a XCT

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Research M921010 scanner (Norland/Stratec, Pforzheim, Germany) at a slice thickness of 0.25 mm and voxel size of 0.1 mm. All scans were acquired against a standard cone phantom (XCT Research M) with known densities and were analyzed using XCT540 (Norland/Stratec) software to calculate apparent mineral densities for diaphyseal cortical bone (CDen) to compare to serum results.

Captive animals were scanned once per season (i.e., four times per year) and wild woodchucks were scanned at the time of capture.

Blood samples were collected from each animal once a month for the duration of captivity as described above. Hibernating animals did not receive injectable anesthesia, but rather were only masked with Isoflurane gas to avoid arousing the animal from torpor. Every attempt was made to collect blood from captive animals in the morning to avoid circadian fluctuations in analytes of interest. Blood was collected from the brachiocephalic vein. To prepare the animal, it was placed in a supine position and the skin shaved and cleaned just superior to the clavicle. Using a 5 mL syringe and 23 Ga needle, three to six milliliters of blood were collected. This was immediately dispensed into red/grey topped vacutainers (BD Diagnostics) containing sodium citrate as a coagulant.

Blood was allowed to coagulate for 15 to 30 minutes before centrifuging at room temperature for 20 minutes at 1000 rpm. Serum was then collected from the top of the vacutainer and aliquoted into labeled 1.5 mL microcentrifuge tubes for cold storage (-80˚C) until subsequent analysis.

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Animals were assigned to the wild animal group (tagged and released or euthanized immediately) or to the captive animal study. Tagged animals were allowed to recover from anesthesia (approximately 6 hours) and then released at the hole where they were box trapped. Unfortunately, only four animals were re- trapped, three of those being juveniles, so a longitudinal examination of wild catch and release animals was not possible. The majority of the wild woodchucks were euthanized immediately following blood collection with an intravenous injection of generic Fatal Plus (1 cc/10 lbs) into the brachiocephalic vein.

Additional Captive Animal Procedures

Those animals included in the captive study were given a 1 cc intramuscular rabies vaccination and de-wormed. These woodchucks were then allowed to recover from anesthesia on clean straw in 4’x2’ cages within the

NEOMED CMU. Animals were housed individually. Water was provided ad libitum as well as food, which consisted of a high fiber rabbit chow supplemented with fresh apples, carrots, and kale. Once an animal acclimated to the laboratory environment, it was periodically given access to a 15’ x 3’ runway for exercise during the active seasons.

All captive animals and one catch and release animal had temperature data loggers (iButton DS1921G, MAXIM) aseptically implanted into the intraperitoneal cavity late in the summer to record core body temperature.

Briefly, the area overlying the linea alba was shaved and aseptically prepared for

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surgery under anesthesia as described above. A 1 cm midline incision was made to enter the intraperitoneal cavity. One or two gas-sterilized data loggers

(Sterrad) coated in Elvax (Minimitter, Bend, OR) were inserted through the incision. The linea alba was sutured with a continuous pattern using 4.0 Vicryl.

The skin was closed with a subcutaneous continuous stitch with the same suture.

Animals were given 3 mg/kg ketofen intramuscularly and 0.5 cc lidocaine subcutaneously as post-operative analgesics. Following previous research, data loggers were utilized to record daily core body temperatures and to verify hibernation (Dallmann et al., 2006; Davidson et al., 2003; Geiser, 1995; Long et al., 2007; Lovegrove, 2009; Taylor et al., 2004). All data loggers were recovered following hibernation to collect temperature information. During the hibernation period (October 1 – March 25), the woodchucks were moved to a walk-in refrigerator maintained at 7 ˚C (± 1-2 ˚C). Water was continuously available, but food was restricted or, if necessary, withheld to initiate hibernation. Most animals voluntarily elected to stop eating. Animals in full hibernation did not consume food for the duration of the hibernation season. The hibernation chamber was lit by one red light bulb to avoid disturbance to the animals during daily animal welfare assessments and monthly data collection sessions. No other light was provided during this time. Animals were allowed to freely hibernate. Two animals did not hibernate by the end of December and they were removed. One of these animals was kept an additional year and did hibernate that following year, the data of which are reported only for the year the animal hibernated. If an

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animal aroused from hibernation before March 25th, the animal was fed ad libitum and removed from the hibernation chamber.

Serum Analysis

Serum calcium, ALP, and PI were outsourced to a local hospital for analysis on a UniCel DxC600 Synchron Clinical System chemical analyzer

(Beckman Coulter). Commercially available ELISA kits were used to determine serum levels of OPG (mouse MOP00, R&D Systems), OPN (mouse MOST00,

R&D Systems), leptin (rat 90040, Crystal Chem), OC (rat AC-12F1, IDSPLC), and ICTP (06099, IDSPLC). All kits and lots were validated using spike recovery tests and serial dilution curves (Table 6.3). Neither PTH nor RANKL kits recognized woodchuck serum despite trying various kits for different species.

PTH was also not identified in Western blots analyses at attempts to identify the woodchuck protein and design custom ELISAs. Effort was made to use the same lot number when available at the time of purchase and kits were used according to manufacturer instructions. Plates were read using a Shimadzu

Spectrophotometer (UV-2101PC, IetLtd.) between 450 nm and 650 nm. Data were recorded from the spectrophotometer using SoftmaxPro software (v 1.0.1).

All serum results were compiled in Excel in association with individual animal identification, age, weight, core body temperature, and time of blood collection.

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Table 6.3: In-House ELISA Validation Tests

Linearity Dilution curve Elisa Assay % Recovery Correlation Coefficient p-value ICTP 0.999 0.019 120 OC 0.967 0.038 82 LEP 0.999 0.001 61 OPG 0.999 <0.001 105 OPN 0.972 0.024 61

Statistical Analysis

Captive woodchuck study: Monthly data collected throughout the year from captive animals were categorized into one of three seasons for statistical investigation: Prehibernation (August - October), Hibernation (November – mid-

March), Posthibernation (end of March - May). Summer data were excluded in the captive animal analysis as a result of uneven, small sample sizes for this group. Serum data were averaged by season per animal (N = 12, 6 males and 6 females), with the exception of osteopontin (N = 9) because of unavoidable sample shortages (Table 6.2). First, normality was assessed using a Shapiro-

Wilk's test. Significance was determined using a Sequential Bonferroni (α =

0.025) based on 24 independent tests (8 analytes x 3 seasonal levels). Data that violated the normality assumption were examined closely for outliers, natural log transformed (ln), and investigated in comparison with non-ln data. Cases where the transformed data results did not differ from the original analysis were reported using the non-transformed analysis. Following normality assessment,

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data were analyzed using a repeat measures general linear model with hibernation season as the independent variable. Sex was examined as a cofactor and excluded in the final analysis if not initially significant (Berry and

Feldman, 1985). Violations of sphericity (α ≤ 0.05) were corrected using the

Greenhouse-Geisser method. In addition, Bonferroni post-hoc tests were conducted to determine pair-wise directional differences between hibernation seasons.

Diaphyseal cortical density measurements of the tibia were obtained from computed tomography scans of all animals except one (N = 11) during each season (i.e., quarterly). Density was used as a direct measure of bone tissue for comparison to serum results. Data were examined as described above by first examining hypothesis tests assumptions and using the repeated measures general linear model.

Time series analyses were conducted using a cross-correlation function

(CCF) on averaged captive animal data for each month (N = 12) throughout the year to determine temporal correlations between serum analytes. The significance threshold of the CCF was determined to be ±0.56 (1.96/ , where

12 is the number of months examined; Chatfield, 2004). Lags are reported in months and represent the time delay between the concentrations of any two analytes throughout the year. Therefore, a lag of zero indicates that the levels of both analytes follow a temporally similar pattern. Considering that it normally takes bone to be deposited 3 to 4 months after the degradation process of

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resorption (Parfitt, 1979), certain analytes should be correlated within a four month time span reflecting a potential relationship. Correlations found to have a delay surpassing four months are not considered to be coupled.

Wild woodchuck study: All wild and captive adult animals at the date of capture were compared across prehibernation, posthibernation, and summer seasons. The hibernation season was excluded in this study because no wild animal was sampled during the months of November through February when the woodchucks were below ground in their burrows. Data were first assessed for normality using a Shapiro-Wilk's test. As described above, significance was determined using a Sequential Bonferroni adjustment (α = 0.025) based on 24 independent tests (8 analytes x 3 seasonal levels). Data were re-examined for outliers if the normality assumption failed. Sex was initially included as a cofactor, and removed from the final analysis if it was not significant. Each analyte was investigated using a univariate general linear model and Bonferroni post-hoc tests were used to determine pair-wise comparisons between seasons.

We initially included sex as a cofactor with hibernation in the univariate ANOVA, but this was removed from the final analysis of a given analyte when not initially significant (Berry and Feldman, 1985). This sample consisted of 23 female and

20 male woodchucks (Table 6.2).

It was hypothesized that markers of bone formation and resorption would remain coupled throughout the year reflecting a balance in annual bone metabolism in woodchucks. Considering this, statistical power was calculated for

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each ANCOVA design to report the likelihood of committing Type II errors. This effectively reduces the chance of failing to reject a hypothesis when significant differences in fact exist between seasons. A power of ≥ 0.8 (1-β) was considered to be appropriate (Cohen, 1977). Large effect sizes were estimated to be 25% change and small effect size to be 10% change in locomotion variables for calculating statistical power.

Results

Captive Woodchuck Study

Only ALP in the hibernation season (p = 0.019) and osteocalcin in the posthibernation season (p = 0.013) seasons failed to meet the Shapiro-Wilk's normality test assumption. Since significance was determined to be α = 0.025 using a Sequential Bonferroni post-hoc test, we re-examined the data for outliers, transformed ALP and OC by naturally logging the data, and reran the analysis.

Logging ALP and osteocalcin did fix normality (ALP hibernation (p = 0.427) and osteocalcin posthibernation (p = 0.067)). However, both the original and logged repeated measures analyses were similar in that ALP remained statistically significant across seasons (see below) and osteocalcin was not significant. In this case, we report the original analyses for ALP and osteocalcin as the seasonal pattern does not change after transforming the data violating the assumption of normality. No significant sex differences were found with any analyte.

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All analytes were significantly different in the repeated measures general linear model between seasons except for osteocalcin (p = 0.102, Table 6.4). The pair-wise Bonferroni post-hoc test revealed that Ca (p = 0.002), PI (p < 0.01), and osteoprotegerin (p = 0.014) were significantly highest during hibernation (Fig.

6.2A). Alternatively, alkaline phosphatase (p = 0.001), ICTP (p = 0.034), and leptin (p = .004) were lowest during hibernation (Fig. 6.2B). As expected, leptin peaked in the prehibernation season when body weight and food intake were at their highest (Fig. 6.3). Furthermore, leptin was significantly negatively correlated with OC throughout the year (CCF = -0.642, Fig. 6.3, Table 6.5,).

Osteopontin remained low throughout the prehibernation and hibernation season, and then increased significantly after Bonferroni between hibernation and posthibernation (p = 0.026). There was a significant decrease between the posthibernation and prehibernation periods in calcium (p = 0.002) and osteopontin (p = 0.046). Tibial diaphyseal cortical density was significantly higher (p = 0.002) in the hibernation and posthibernation seasons compared to prehibernation (Table 6.4).

Time series analyses of averaged monthly analyte concentrations of the

12 captive animals revealed that several relationships are maintained between the markers of interest throughout the year (Table 6.5). Specifically, calcium and inorganic phosphate shared a high, positive cross-correlation (CCF = 0.811) with no lag time. Osteoprotegerin and inorganic phosphate (CCF = 0.776) also remained positively correlated throughout the year with no temporal offset. From

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Table 6.4: Repeated Measures ANOVA of Average Serum Concentrations of Adult, Captive Woodchucks

Mauchly's Sphericity Pre- 1 Post- ANOVA ANOVA Markers Sphericity 1 Hibernation 1 Power Correction hibernation hibernation F-statistic p-value (p-value)

Greenhouse- 9.37 10.3 9.72 Ca 0.006 a b c 15.373 0.001 - Geisser (0.293) (0.655) (0.217) Sphericity 13.67 6.83 11.08 ALP 0.445 a b a 9.732 0.001 - Assumed (6.75) (3.76) (5.60) Sphericity 3.81 5.85 4.00 P 0.912 a b a 16.168 < 0.01 - I Assumed (0.684) (1.34) (0.954) Sphericity 10.08 8.62 12.88 ICTP 0.161 3.951 0.034 - Assumed (3.65) (4.27) (6.01) Greenhouse- 93.10 139.72 192.13 OC 0.001 3.034 0.102 0.386 Geisser (31.15) (57.55) (161.12) Sphericity 0.985 0.672 0.843 Leptin 0.311 a b 7.386 0.004 - Assumed (0.328) (0.257) (0.301) Greenhouse- 73.32 109.38 62.46 OPG 0.006 a b 7.246 0.014 - Geisser (28.59) (50.34) (18.62) Greenhouse- 436.85 426.17 673.74 OPN 0.013 a a b 10.036 0.009 - Geisser (133.24) (108.00) (137.29) Cortical Sphericity 1245.72 1262.1 1274.75 0.287 a b c 9.029 0.002 - Density Assumed (33.25) (21.97) (34.25) 1Values reported as average serum concentrations (standard deviation).

Bold values significant at the α = 0.5 level. a,b,c Indicate significant differences between the three seasons.

Rows without letters indicate no significant pair-wise difference between any season.

Observed Power: Normal font represents effect size of 25%, bold values represent 10% effect change with β ≥ 0.8.

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Fig. 6.2: Standardized serum analyte concentrations across three seasons in captive woodchucks. Calcium (Ca), inorganic phosphate (PI), and osteoprotegerin (OPG) were significantly highest during hibernation (A). Comparatively, alkaline phosphatase (ALP), ICTP, osteopontin (OPN), and leptin were lowest during hibernation (B).

Table 6.5: Time Series Analysis of Monthly Analyte Levels of Captive Woodchucks

Markers Ca ALP PI ICTP OC LEP OPG OPN

Ca 1 -0.549 (0) 0.811 (0) 0.506 (2) 0.709 (3) -0.702 (0) 0.527 (0) 0.622 (3)

ALP 1 0.589 (-5) 0.359 (-4) -0.767 (3) 0.617 (4) 0.492 (-5) 0.838 (-1) 1 0.531 (2) 0.614 (3) -0.583 (0) 0.776 (0) 0.711 (4) PI ICTP 1 0.453 (2) -0.546 (3) 0.656 (-1) 0.428 (2)

OC 1 -0.642 (0) 0.529 (-4) 0.827 (0)

Leptin 1 -0.510 (0) 0.659 (-4)

OPG 1 0.554 (4)

OPN 1

Lag times (months) are reported in parentheses. Negative lag values represent row lag behind column heading.

Bold values are significant at the CCF = 0.566 (α=.05).

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Fig. 6.3: Leptin peaked in the prehibernation season when body weight and food intake were at their highest. Leptin was also negatively correlated with osteocalcin (OC) throughout the year.

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Fig. 6.4: Cross-correlations of serum analytes in captive woodchucks. The strong relationship between Ca, PI, and OPG persists throughout the year (A). Additionally, besides its negative association with leptin, OC was highly correlated with osteopontin (B). Alkaline phosphatase and ICTP were highly correlated to osteopontin (C) and osteoprotegerin (D), respectively.

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this it is apparent that the strong relationship between Ca, PI, and OPG persists throughout the year in woodchucks (Fig. 6.4A). Leptin had negative associations with calcium (CCF = -0.702) and inorganic phosphate (CCF = -0.583, Table 6.5).

Additionally, besides its negative association with leptin, it is notable that OC was highly correlated with osteopontin (CCF = 0.827) with no time delay (Fig. 6.4B).

The remaining markers alkaline phosphatase and ICTP were highly correlated to osteopontin (CCF = 0.838) and osteoprotegerin (CCF = 0.656), respectively.

Each lagged osteopontin (ALP, Fig. 6.4C) or osteoprotegerin (ICTP, Fig. 6.4D) by one month.

Other correlations exist when additional lag times are investigated up to four months. Osteocalcin is positively correlated with calcium (CCF = 0.709) and phosphate (CCF = 0.614), but negatively related to alkaline phosphate (CCF = -

0.767) with a lead time of three months in all three cases (Table 6.5). Calcium also peaks three months prior to osteopontin (CCF = 0.622). Alkaline phosphate concentration increases four months before leptin (CCF = 0.617), however leptin lags osteopontin by the same amount of time (CCF = 0.659). Moreover, osteopontin peaks four months after phosphate (CCF = 0.711, Table 6.5).

Collectively, these results suggest that many bone remodeling processes remain closely coupled throughout the year.

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Fig. 6.5: Females had higher density following hibernation than males in the tibial cortical density in wild woodchuck s (A). In the captive study, there was no significant interaction effect. Both males and females experienced a similar increase in cortical density in the hibernation and posthibernation periods compared to prehibernation (B).

Wild Woodchuck Study

All wild animal data met the normality assumption except for osteocalcin during the posthibernation season (p = 0.001). However, naturally logged osteocalcin revealed no change in the pattern observed between seasons compared to untransformed data, thus all results are based on the original analysis. No significant sex difference was found in any analyte; therefore the co-factor sex was removed from the analyses. However, there was a significant interaction effect (p = 0.015) in tibial cortical density between sexes across seasons indicating that females had higher density following hibernation than males (Fig. 6.5A). In the captive study, both males and females were found to experience a similar, significant increase in cortical density in the hibernation and posthibernation periods compared to prehibernation (Fig. 6.5B).

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Univariate ANOVAs of each analyte indicate that there were significant differences in calcium (p < 0.01), alkaline phosphatase (p = 0.019), ICTP (p <

0.01), osteocalcin (p = 0.003), and osteopontin (p = 0.008) across seasons

(Table 6.6). Calcium, ICTP, osteocalcin, and OPN increased significantly in the posthibernation season from prehibernation levels (Fig. 6.6). This finding was similar to that found in calcium and osteopontin levels between pre- and posthibernation in the captive woodchuck study. Both calcium and ICTP also decreased significantly between the posthibernation and summer periods (Fig.

6.6). Furthermore, alkaline phosphatase, osteocalcin, and osteopontin increased significantly from the prehibernation to summer seasons (Fig. 6.7). No significant difference was observed in inorganic phosphate, leptin, or osteoprotegerin with high statistical power for both phosphate and osteoprotegerin (Table 6.6).

Although not significant, leptin followed the same trend as that reported in the captive animal study with highest levels occurring in the prehibernation season and the lowest during hibernation.

Discussion

Despite the reported metabolic depression of nearly all visceral organs during hibernation, it is clear from the results of this study that bone formation and resorption markers remained coupled throughout the extensive physical inactivity characteristic of hibernation. Therefore, we concluded that these

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Fig. 6.6: Calcium, ICTP, osteocalcin, and OPN increased significantly in the posthibernation season from prehibernation levels in wild woodchucks. Both calcium and ICTP also decreased significantly between the posthibernation and summer periods.

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Table 6.6: Univariate ANOVAs of Serum Concentration from Adult, Wild Woodchucks

Post- Pre- 1 ANOVA ANOVA Markers 1 hibernation Summer Power hibernation 1 F-statistic p-value

Ca 8.859 9.750 8.157 a b a 11.674 < 0.01 - (0.591) (.734) (1.130) ALP 19.470 24.080 33.000 a b 4.406 0.019 - (14.235) (9.577) (12.166) P 4.447 4.001 5.407 I 2.500 0.095 0.896 (1.403) (2.14) (1.450) ICTP 12.346 32.484 13.248 a b a 17.599 < 0.01 - (6.010) (14.951) (7.328) OC 129.892 382.764 341.722 a b b 6.975 0.003 - (74.556) (256.336) (216.426) Leptin 1.232 0.932 1.029 0.684 0.511 0.556 (0.801) (0.447) (0.685) OPG 119.241 117.418 145.069 1.332 0.276 0.807 (46.195) (47.713) (55.455) OPN 729.407 1332.796 1148.313 a b b 5.831 0.008 - (206.088) (405.849) (525.418) Cortical 1253.879 1254.233 1255.308 0.006 0.994 1.000 Density (30.624) (38.186) (33.240) 1Values reported as average serum concentrations (standard deviation).

Bold values significant at the α = 0.5 level. a,b,c Indicate significant differences between the three seasons. Rows without letters indicate no significant pair-wise difference between any season. Observed Power: Normal font represents effect size of 25%, bold values represent 10% effect change with β ≥ 0.8.

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Fig. 6.7: Alkaline phosphatase, OC, and OPN increased in concentration significantly from the prehibernation to summer seasons in wild woodchucks.

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processes remain coupled to maintain bone annually. The longitudinal captive study in particular demonstrated that several analytes of interest shared a strong relationship with at least one other marker in the corresponding bone resorption/formation pathway within one month’s time delay. Additional associations were supportive of this hypothesis with up to four months lag, suggesting that the serum marker correlations were complex but not necessarily uncoupled. Most importantly was the association between Ca, PI, and OPG.

Increased Ca and PI concentrations suggest that bone resorption processes may be occurring during the hibernation season. However, the strong association of

OPG with PI and Ca suggested that bone formation processes may also occur throughout this period. In this situation, no net loss of bone would be expected since the processes appear to remain coupled. Furthermore, all other resorption analytes were found to be lowest, indicating resorption processes while active are not significantly elevated during hibernation. Future investigations of RANKL and the OPG/RANKL ratio would help to elucidate whether formation and resorption processes remain coupled throughout the year in these animals.

Interestingly the cross-sectional wild woodchuck study largely supported the findings reported for the captive animal group. Significant differences were found both in serum markers of bone formation (OC, ALP) and resorption (ICTP,

OPN, Ca) between seasons, with the lowest levels occurring during the hibernation period suggesting that the same pattern observed in the captive animals is also experienced by free-living woodchucks. Moreover, increased

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cortical density of their tibial diaphysis supports the argument that bone loss does not weaken the skeleton during hibernation.

These results have broad implications for studies on other hibernating species and clinical research. A number of the analytes of interest are known to be influenced by metabolic processes, such as ICTP, OC, OPN, and ALP, and also originate from organs besides the skeleton. It is their close associations throughout the year (even though they have different origins and are cleared by different organs) that indicate bone remodeling processes are not significantly out of balance resulting in disuse osteoporosis.

Bone Serum Studies of Hibernators

Data presented here are largely comparable to the conclusions of serum studies in other hibernators. Serological bone marker studies in torpid bears have found that these animals do not lose bone annually. The most compelling results from skeletal research on hibernating bears focuses on PTH effects on the skeleton (Donahue et al., 2006a). In denning bears, Ca levels are stable throughout hibernation (Donahue et al., 2006a; Donahue et al., 2006b; Donahue et al., 2003b; Floyd et al., 1990). Interestingly, PTH appears to be elevated during this time (Donahue et al., 2006b; McGee-Lawrence et al., 2008). One hypothesis of PTH function in bears suggests that PTH may upregulate bone formation to keep pace with bone resorption (Donahue et al., 2006a), however the precise role of PTH and its interaction with other cytokines in these animals are still unknown. In other hibernating animals, data on bone serum markers for

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Ca, PTH, and calcitonin are incomplete. Hibernating bats, like bears, increase

PTH seasonally and maintain Ca and PI homeostasis (Nunez et al., 1972). This result suggests that bone is not lost during hibernation in these animals, but histological evidence indicates that bats lose bone during this period (Doty and

Nunez, 1985).

Interestingly, woodchucks increased Ca and PI concentrations, but also increases osteopontin suggesting that bone remodeling remains balanced.

Other studies on woodchucks have found that Ca and PI are maintained but calcitonin increases in immunolocalization studies (Gatti et al., 1986; Sartorelli et al., 2004). Calcium homeostasis with respect to bone remodeling was not the primary focus of these investigations (Sartorelli et al., 2004), but they contradict that reported in this study where Ca and PI peaked in the hibernation season in these woodchucks. In addition, we were unable to analyze PTH levels in woodchuck serum and there are no studies that we know of investigating PTH in hibernating woodchucks. Thus, it remains to be seen whether PTH functions similarly to maintain bone in hibernating woodchucks as in bears, or if PTH will contribute to bone loss as seen in other animals.

Two bone formation markers, procollagen I carboxyterminal propeptide

(PICP) and N-terminal propeptide of type I collagen (PINP), have also been reported to be elevated immediately after hibernation in bears (Donahue et al.,

2003b; 2003a). The temporal offset between upregulation of ICTP versus PICP and PINP in bears suggests that bone formation and resorption processes are

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seasonally uncoupled and that these animals might exhibit a net loss of bone during hibernation only to recover it immediately after inactivity (Donahue et al.,

2003b; 2003a). ICTP was also elevated significantly in denning black bears suggesting that bone resorption occurs at this time (Donahue et al., 2003b;

2003a), however it is now thought that increased ICTP during hibernation is a result of significantly decreased glomerular filtration rates of the kidney.

Interestingly, bears are not thought to lose bone annually and even exhibit increased bone density with age (Harvey and Donahue, 2004). Thus, it is hypothesized that bears recover bone (as evidenced by the levels of PICP and

PINP), during their six months of activity (Donahue et al., 2003a; McGee-

Lawrence et al., 2008). This pattern of bone recovery differs from non- hibernating animals in that after extensive periods of disuse, bone is much slower to recover and usually is not completely replaced throughout the lifetime of the individual (Bronner and Farach-Carson, 2004).

Unfortunately, few investigations have studied the association between

OC or leptin levels and their impact on the skeleton during hibernation. However, in denning bears, OC serum levels appear elevated during hibernation (Donahue et al., 2006a; Donahue et al., 2006b; McGee-Lawrence et al., 2008), but are not statistically correlated with low post-hibernation leptin levels (Donahue et al.,

2006a). Leptin levels in hibernating black bears were significantly lower posthibernation, suggesting bone formation may experience reduced inhibition during this season (Donahue et al., 2006a). In hibernating woodchucks, research has

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focused on the increased levels of leptin in association with seasonal changes in fat mass, fat-cell size, and metabolism (Concannon et al., 2001; Florant et al.,

2004). Thus the finding that OC and leptin remain inversely coupled throughout the year supports the idea that low levels of leptin remove the inhibition on bone formation and osteoblast activity as can be seen through increasing levels of OC during hibernation.

Despite its importance as a bone formation marker, there are few investigations of ALP levels in hibernators. Previous work in hibernating bats found that ALP did not differ between hibernation and pre-hibernation levels

(Doty and Nunez, 1985), suggesting that bone formation rate may remain constant during this inactive period. However, denning bears experience an increase in ALP from the hibernation to posthibernation periods (Bradford, 2010).

Considerations of Blood Serum Analysis

Renal function during hibernation is diminished significantly and considering that serum analytes can be affected by their filtration through the kidneys, it is important to consider the effects of decreased renal metabolism on bone serum properties. Normal human glomerular filtration rate is considered to be above 90 mL/min/1.73 m2 (Levey et al., 2003). Filtration rates below 60 mL/min/1.73 m2 are considered to be indicative of moderate kidney disease and anything below 15 represents kidney failure.

Hibernating animals, especially rodent hibernators, experience 2 to 10% kidney function and in a normal clinical setting would be considered to be in

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kidney failure by these definitions. Glomerular filtration rates of black bears are reported to drop 68% relative to active animals (Brown et al., 1971) and marmots, close relatives of woodchucks, reduce this to 10% during hibernation

(Zatzman and South, 1972). Despite decreased renal function, urine is produced in measurable quantities in the bear (0.07 mL/min or 100.8 mL/day; Nelson et al.,

1975), marmot (0.05-0.1 mL/day; Zatzman and South, 1975), and bat (0.00144 mL/day; Kallen and Kanthor, 1967). However, marmots experience hypertonic urine compared to plasma levels and water resorption occurs throughout the hibernation period (Zatzman and South, 1975). Furthermore, the decrease in glomerular filtration rate is attributed to a 55% decrease in blood pressure during hibernation in hamsters and thus loss of hydrostatic pressure to drive fluid from the glomerular capillaries to Bowman’s space in hamster kidneys (Tempel et al.,

1977). Cardiac output to the kidney also decreases significantly in these animals during hibernation as blood flow is directed from peripheral visceral organs to the heart, lungs, and diaphragm (Tempel et al., 1977).

With respect to the analytes investigated in this study, ICTP and osteocalcin are known to increase in serum concentration with impaired renal function in humans (Risteli et al., 1993). The increase observed in this study in

ICTP and osteocalcin early in the hibernation season could be a result of the build-up of these proteins in the urine during decreased renal filtration. However, considering the overall metabolic shutdown of nearly every organ during hibernation, we do not anticipate that the small amount of urine produced would

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contain high levels of bone resorption or formation products. In fact, plasma constituents sampled from hibernating marmots remained relatively similar to active levels with an increase only in sodium and decrease in glucose (Zatzman and South, 1972). Considering urine concentrations were not investigated in the study presented here, further research is required to determine whether these two analytes were elevated in the urine of hibernating woodchucks.

Like the kidneys, the liver is largely metabolically inactive, but still functioning during hibernation (Baker and van Breukelen, 2009; Green et al.,

1984). Indeed, ground squirrels experience no significant changes in bile constituents throughout the hibernation period (Baker and van Breukelen, 2009), indicating that the liver remains viable. Considering this and that ALP can be produced and is also cleared by the liver, we would expect that there would be no significant fluctuation of liver alkaline phosphatase. Furthermore, we did not specifically target bone-specific alkaline phosphatase and so our analysis includes ALP of different origin, such as from the liver (the second biggest contributor of ALP in circulation, Seibel et al., 2006). Previous reports indicate that concentrations of total ALP do not change significantly compared to bone- specific alkaline phosphatase in patients with increased bone turnover

(Dominguez Cabrera et al., 1998). However, the significant increase in ALP in both the wild and captive animals is consistent with the other elevated bone markers in the posthibernation season. Likewise, total ALP reported here demonstrated the same seasonal pattern of bone-specific ALP in denning bears

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(Bradford, 2010). This indicates that there is likely a significant contribution of bone-specific alkaline phosphatase to total ALP levels at this time of increased bone turnover. Furthermore, in patients experiencing rapid bone turnover, such as in the case of Paget’s disease, total alkaline phosphate is as good a diagnostic tool as bone-specific ALP (Reid et al., 2004).

In conclusion, serum analysis of bone in hibernating woodchucks supported the hypothesis that bone remodeling processes remained coupled to maintain bone throughout the year. Increasing evidence ranging from locomotion studies to biochemical analyses indicates that hibernating animals do not experience bone loss during seasonal periods of physical inactivity. This suggests that hibernators have evolved a mechanism to preserve the integrity of their bones despite the loss of a mechanical signal. Such a mechanism would have profound implications on biomedical research and clinical therapies investigating osteoporosis and other bone loss diseases. Additionally, from this study it was apparent that the use of non-traditional animals, such as hibernators, may provide novel model systems to address persistent medical and scientific problems that continue to elude us today.

CHAPTER 7

SUMMARY AND CONCLUSIONS

Summary of the Skeletal Biology of Hibernating Woodchucks

In humans and other non-hibernating animals, lack of physical exercise reduces bone mass, decreases mechanical properties of bone, and increases the chances of fracture (Smith and Gilligan, 1991). Hibernating animals are unusual in their extreme seasonal inactivity, and the consequences of this mechanical unloading pose several pertinent questions regarding the preservation and maintenance of the skeleton of hibernators. The primary goal of this research was to identify the physiological mechanisms attributed to regulating bone density, area and strength during extended periods of annual inactivity in hibernating woodchucks (Marmota monax). The rationale of this project was to gain a better understanding of the ability of these animals to either

1) cope with a weakened skeleton each year following the hibernation season as would be expected from extreme inactivity in a non-hibernating species, or 2) preserve bone structure and integrity through derived physiological processes despite mechanical unloading and nutrient deprivation.

Considering that other hibernating animals maintain bone integrity following hibernation (Harvey and Donahue, 2004; McGee-Lawrence et al., 2011;

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McGee et al., 2007; Utz et al., 2009; Wojda et al., 2012), the principal hypothesis of this work was that bone integrity would be unaffected by several months of inactivity during hibernation. To test this hypothesis it was necessary to investigate multiple levels of biological function ranging from behavioral performance to bone-related protein expression. By spanning multiple levels of organization, it was possible to develop an integrated perspective of the mechanisms coordinating bone physiology in hibernating woodchucks.

Compared to non-hibernating animals, woodchucks were shown to avoid significant loss of bone integrity with at most minor changes in locomotor behavior. Specifically, these animals consistently used similar gaits between seasons despite significantly reducing bending loads in the tibia and ulna after hibernation (Chapter 2). It does not appear that reduced bending loads are the result of compromised bone. This conclusion follows from two observations.

First, there is a persistent lack of significant changes in bone mass, mechanical properties, and serum analytes in hibernating woodchucks. Second, a compromised skeleton would be predicted to show higher bending loads and a change in gait after hibernation, such as using slower-speed walks with less impact at substrate contact. Changes in loading observed in this study may be attributed to the position of the limbs relative to the ground reaction force in the absence of excess body weight or some other consequence of a musculoskeletal functional adaptation present during the posthibernation season.

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In addition, two computed tomography studies of the bones of woodchucks demonstrated that both subadult and adult woodchucks maintained their bone mass, distribution, and trabecular structure throughout the year

(Chapter 3 and 4). Cortical density also increased in the active seasons after hibernation, suggesting that the structural properties of bone would be greater in the diaphyses of these animals following hibernation. When directly tested in three-point bending tests, however, woodchuck bones were found to be slightly less stiff but tougher (i.e., requiring more work to fracture) during the hibernation season (Chapter 5). This reduced stiffness, although only significant in the elastic modulus of the femur, is different from the brittle bones associated with osteoporosis. Alternatively, this pattern is similar to the inherently weak, but tough bones characteristic of osteomalacia (Turner, 2002).

Considering that calcium and inorganic phosphate are elevated during hibernation in woodchucks, it is possible that the extreme inactivity and nutritional deprivation throughout this season promotes mineral loss from the organic matrix of bone. This mineral loss may occur despite a concomitant rise in osteoprotegerin, a bone formation marker (Chapter 6). This mineral loss would decrease bone stiffness, but potentially leave behind the organic scaffold that provides the toughness to skeletal elements. Bone remodeling is normally tightly regulated by the balanced processes of bone resorption and formation acting to degrade and rebuild bone, respectively. Inactivity in most mammals uncouples these two processes so that resorption is upregulated in comparison to bone

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formation (Seibel et al., 2006). Interestingly, it appears that woodchucks are capable of increased bone formation processes while experiencing increased serum levels of calcium and phosphate, and reduced bone stiffness during inactivity associated with hibernation. Furthermore, bones can withstand more post-yield deformation before breaking during the hibernation season. Such a set of outcomes would suggest a net maintenance of bone throughout the year.

Despite any trend in decreased elastic modulus during hibernation, stiffness was recovered to prehibernation values in the posthibernation season

(Chapter 5). This indicates that any mineralization lost from the organic matrix of bone contributing to reduced stiffness was quickly ameliorated with the subsequent uptake in food and return to normal physical activities following hibernation. Indeed, the biological significance of the small reduction in bone stiffness but increased toughness during the hibernation season remains to be determined. Taken together, these findings strongly suggest that woodchucks do not lose bone to the extent that would be expected from a non-hibernating animal during four months of inactivity. It is concluded that bone integrity is not adversely affected by hibernation in woodchucks and they share an advantage with other hibernating animals in protecting their skeleton during mechanical unloading (Fig. 7.1). The results of this work describe the skeletal phenotype of hibernating woodchucks and have several broader implications toward skeletal biology research, the evolution of skeletal plasticity, and biomedical applications to osteoporosis prevention and treatment.

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Fig. 7.1: Pattern of bone loss/maintenance in non-hibernating and hibernating animals during extensive inactivity. Woodchucks are able to maintain bone properties similar to other hibernators that do not lose significant bone throughout the year. “=” No net bone loss or gain; “▲” Bone increase; “▼” Bone decrease. ┼Frogs aestivate for up to nine months out of the year. *Bears are torpid for 4-5 months out of the year, but are comparatively more active than small hibernators during hibernation.

1Hudson et al., 2004. 2Donahue et al., 2006; Floyd et al., 1990; Harvey and Donahue, 2004; Harvey et al.; 2005; McGee et al., 2008; McGee et al., 2007; McGee-Lawrence et al., 2009; Donahue et al., 2006; Lennox and Goodship, 2008; McGee-Lawrence et al., 2008. 3Wojda et al., 2012. 4Utz et al., 2009; Haller and Zimny, 1977; McGee-Lawrence et al., 2011; Zimny et al., 1973; Zimmerman et al., 1976. 5Steinberg et al., 1981. 6Doty and Nunez, 1985; Nunez et al., 1969; Nunez et al., 1972; Kwiecinski et al., 1987.

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Bone Preservation of Hibernators and the Implications of this Work

Hibernation evolved independently at least three times in birds, marsupials, and mammals (Geiser, 2008). Although currently debated (Carey et al., 2003; Geiser, 1998; Grigg, 2004; Grigg et al., 2004; Lovegrove, 2012;

Lovegrove et al., 1999), it is likely that certain mammalian hibernators, such as obligate hibernators, have derived specializations for extreme forms of energy management and avoidance of harsh environmental conditions (Grigg, 2004).

Not only do these adaptations shield the animal from cold temperatures, food and water shortages, as well as non-hibernating predators, it also affords them a relatively slow rate of senescence (Turbill et al., 2011). A slow life history would have multiple benefits when considering the inactive state of hibernation and the annual preservation of the skeleton. Specifically, it would reduce the rate of age- associated loss of bone experienced by all adult animals (Syed et al., 2010) and delay the onset of gonadal loss of function which is known to contribute to dramatic loss of bone, particularly in females (Seeman, 2003). Thus, animals with slow life histories such as hibernators may have a slight advantage in protecting their skeletons despite the annual effects of hibernation.

The plasticity of the skeleton as a whole is of particular importance when regarding any adaptation to maintain bone during hibernation. The structure of various skeletal elements is quite diverse in form and function across mammals as well as other vertebrates. The modular nature of bone development allows for a greater amount of plasticity in the evolution of these forms (e.g., the mandibles

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of mammals) than may be expected (Hall, 2010). It follows then, that the processes that regulate bone integrity, such as bone formation and resorption, could also be adapted to certain evolutionary strategies to protect the skeleton from disuse-associated bone loss during the extreme inactivity characteristic of hibernation. It is clear that hibernators are atypical and potentially unique in their ability to preserve bone despite seasonal unloading of their skeleton. Moreover, juveniles still grow in an unloading environment. The process by which hibernators are capable of turning off the typical mechanobiological response of bone to inactivity merits further investigation.

One potential adaptation could relate to a novel role of parathyroid hormone (PTH) in hibernators. PTH in black bears differs by nine amino acid residues in comparison to the human sequence (1-84; Gray et al., 2012).

Furthermore, PTH concentration is significantly elevated in these animals in the posthibernation season and is thought to have an anabolic action on the hibernating skeleton considering its significant correlation with osteocalcin

(Donahue et al., 2006a). When administered to mdx mice (mice having reduced trabecular area, volume fraction, and thickness as a result of x chromosome- linked muscular dystrophy), bear PTH increased trabecular bone volume. Based on these results, it was concluded to have potential anabolic applications to treat and prevent human osteoporosis (Gray et al., 2012).

It has also been suggested that calcium recycling during hibernation contributes to the preservation of bone properties (McGee-Lawrence et al.,

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2008). Bears have elevated ionized calcium levels during hibernation and posthibernation seasons (Donahue et al., 2006a), similar to high Ca concentrations found in hibernating woodchucks. Despite decreased renal function, urine is produced in measurable quantities in the bladder of the bear

(0.07 mL/min or 100.8 mL/day; Nelson et al., 1975; Nelson et al., 1973), marmot

(0.05-0.1 mL/day; Zatzman and South, 1975), and bat (0.00144 mL/day; Kallen and Kanthor, 1967). However, it has not been directly tested whether these reduced amounts of urine produced by these hibernating animals are hypercalciuric to demonstrate calcium recycling definitively. Regardless of the outcome of these tests, it is clear from the reduction of urination in hibernating animals that some form of water and mineral resorption is occurring throughout this season (Nelson et al., 1975; Nelson et al., 1973; Zatzman and South, 1975).

Recycling minerals, rather than excreting them like most mammals, allows hibernators to maintain cellular functions during nutritional deprivation and also to recover essential materials critical for the structural integrity of bone.

The ability of hibernating animals, including woodchucks, to avoid or recover bone loss over the course of hibernation appears to be substantial in the posthibernation season and bone remodeling processes appear largely balanced to preserve the skeleton (Donahue et al., 2006b). Whether hibernating animals maintain bone through specific protein regulation, calcium and mineral recycling, or other unidentified processes (including combinations of several mechanisms) remains to be determined. Reflecting on what little we know about the processes

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regulating bone in the hibernating skeleton, there are multiple avenues of research with potential biomedical and clinical relevance.

Future Clinical and Evolutionary Research

Once bone is lost from the adult skeleton, it is quite difficult or even impossible to restore and maintain bone mass to prevent future fractures

(Stevenson et al., 2005). Osteoporosis poses a challenge to our nation as a whole, both in terms of the health and well-being of our citizens to the financial costs associated with treating this often devastating disease (www.nof.org).

Despite rigorous biomedical research, there is still no cure for osteoporosis. To treat a complex disease such as osteoporosis, it is necessary to understand the evolutionary history of the skeletal system holistically, the evolution of skeletal plasticity facilitating adaptability to environmental challenges, and the variety of mechanisms by which the skeleton is regulated. Hibernating animals provide unique animal models that are unusual in their ability to preserve skeletal structures despite extensive mechanical unloading patterns. In this way, this research has broad evolutionary and medical applications with the ultimate goal of understanding and preventing human osteoporosis.

The research presented in this dissertation described the morphological, mechanical and physiological phenotypes of bone in hibernating woodchucks.

Future research will focus on identifying the specific processes and genetic mechanisms that function to preserve the skeletal integrity of hibernators. There are several obvious questions that have been raised by the work presented here:

221

What proteins are important to preserving bone mass and integrity during hibernation? How can the system be modified by targeting specific genetic components to result in the "normal" non-hibernator associated bone loss with inactivity? How important is the significant drop in metabolism to the regulation of the skeleton and can bone maintenance during extreme inactivity be separated from a hibernating state? Clearly, the current research has only begun to describe these functional, morphological, and physiological aspects of the skeleton during hibernation.

As one example for future research, determining the interaction of OPG and RANKL in the hibernating skeleton will provide valuable insight into the remodeling processes for comparison to those of non-hibernating mammals during skeletal unloading. RANKL has a prominent role in osteoclastogenesis and osteoclast activity (Boyce and Xing, 2008). Determining its production and relative relationship (i.e., ratio) to OPG will contribute to our knowledge of the resorption processes occurring during hibernation. The role of PTH in regulating

OPG and RANKL in a hibernator is also of interest considering its anabolic action in bears (Donahue et al., 2006a) and should be investigated in association with other proteins involved in bone remodeling. Understanding the specific mechanisms regulating bone remodeling, particularly bone resorption, will help us to delineate specific processes which hibernating animals use (or avoid) to maintain skeletal integrity during disuse compared to other mammals.

222

Another area of interest that has broad clinical applications is the relationship between bone and fat. Recently the skeleton has been recognized as playing an important role in energy metabolism through endocrine regulation of insulin and adiponectin by osteocalcin (Lee et al., 2007). Similarly, adipose has been associated with influencing bone metabolism through the actions of leptin (Ducy et al., 2000a). Hibernators are adept in experiencing vast fluctuations of body fat between seasons, and as such they may provide a unique opportunity to identify the complex interplay between bone and adipose tissue in animals that are naturally inactive and seasonally fat.

Finally, the ontogeny of hibernating animals has not been investigated in the context of skeletal growth and maturation. By investigating juvenile histomorphology of bone during hibernation it would be possible to determine how these animals are capable of developing a normal skeleton despite extreme physical unloading during a developmental period when bones are highly susceptible to epigenetic factors such as diet and loading pattern (Winsloe et al.,

2009). The ability of hibernators to grow normal bones despite not eating or moving for months suggests there is a strong genetic factor governing the adult phenotype of the skeleton that overrides physical forces that may alter the shape, structure, and mechanical properties of bone.

Like other hibernating animals, woodchucks maintain a net balance of bone annually by largely coupling formation and resorption processes throughout the inactive hibernation period and by recovering any loss of bone quickly in the

223

active seasons. Although the mechanisms to preserve bone in hibernators look similar initially, it has not been determined whether these are conserved or derived traits within hibernators. It is clear that certain animals are capable of various degrees of hibernation. The arctic ground squirrel (Spermophilus parryii) for example, can maintain a body temperature of -2.9˚C (2.38 degrees below the freezing point of blood) and reduce basal metabolic rate to 1% of euthermic levels (Boyer and Barnes, 1999). This profound state of hibernation differs in the degree from other obligate hibernators adept at reducing core body temperatures and metabolic rate. Moreover, this rodent pattern is vastly different from the hibernation pattern observed in bears. It would not be surprising, therefore, if the bone regulatory processes in these animals were also derived compared to animals that are capable of less extreme forms of hibernation. Identifying the physiological differences and similarities between bone maintenance patterns across hibernators has great potential for advancing our understanding of the evolution of mammalian hibernation, the skeletal plasticity among these extreme behaviors of mammals, and bone maintenance strategies during inactivity.

Essentially, knowledge of the evolution of these complex processes would support and promote disease prevention and treatment possibilities investigated in osteoporosis research.

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