A Histomorphometric Analysis of Muscular Insertion Regions: Understanding Enthesis Etiology

A HISTOMORPHOMETRIC ANALYSIS OF MUSCULAR INSERTION REGIONS: UNDERSTANDING ENTHESIS ETIOLOGY

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in the Graduate School of The Ohio State University

Stephen Harold Schlecht, M.Sc.

Graduate Program in Anthropology

****************

The Ohio State University

2012

Dissertation Committee: Sam D. Stout, Advisor Clark Spencer Larsen Paul W. Sciulli

Stephen Harold Schlecht

2012

ABSTRACT

The purpose of this study is to explore the relationship between tendon insertions, or entheses, and mechanically induced bone remodeling. Previous research suggests size and complexity of entheses are indicative of strain magnitude resulting from habitual physical activity. However, degree differences in the morphological expression of entheses has never been explicitly linked to activity intensity. Additional factors such as age, sex, and genetics potentially influence insertion morphology. This study investigates the relationship between enthesis location and mechanical loading, quantifying histomorphometric evidence for targeted remodeling related to applied strains in the non-weight bearing human radius.

Thin sections from three diaphyseal regions of the radius associated with four muscle bodies responsible for forearm rotation were harvested from 14 human cadavers and prepared for histologic analysis. Specifically, cross-sections were removed from the right and left proximal, midshaft, and distal diaphysis where the biceps brachii, supinator, pronator teres, and pronator quadratus muscles respectively insert. Osteon population densities (OPD), or number of intact and fragmentary osteons per unit area, and osteon area (On.Ar) were quantified from eight cross-sectional zones defined by the principal anterioposterior and mediolateral axes, and their intersecting planes;

ii encompassing all potential regions of tendon insertion. OPD reflects the visible remodeling history of compacta along each ray, and On.Ar reflects strain level.

Interval mean plots confirm associations between OPD and On.Ar, demonstrating elevated bone turnover along rays aligned with three of the four considered entheses. The biceps brachii enthesis was not associated with increased remodeling, reflecting reduced cortical volume and calcified fibrocartilage present within the radial tuberosity, demonstrating composite and etiological differences between fibrous and fibrocartilaginous entheses. Findings from this investigation confirm a potential relationship between entheses and mechanical strain. However, other contributing factors remain elusive. Biological profiles that attribute enthesial morphology to general activity levels should be employed cautiously. Before the validity of their use can be confirmed, further investigation into additional mechanical and systemic influences is recommended.

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DEDICATION

Dedicated to my father Glenn A. Schlecht, and brother Peter N. Schlecht, who were not here to witness the conclusion of my formal education. You were always supportive of my dreams and I hope I have made you proud. You are loved and missed dearly.

ACKNOWLEDGEMENTS

I would first and foremost like to thank my advisor, Dr. Sam Stout, for introducing me to a histologic method of exploration that I had previously never considered. Most of all he provided me with the independence to pursue my ideas, while nurturing an appreciation for theoretical and critical analysis. My dissertation committee, Dr. Sam Stout, Dr. Clark Larsen, and Dr. Paul Sciulli were instrumental in the ultimate development and completion of this project with their constructive comments and assistance. Additionally, I would like to thank Dr. Kenneth Jones and Dr. Robert

DePhilip for expanding my knowledge and passion for human anatomical form and function.

The National Science Foundation via a doctoral dissertation improvement grant provided financial support for this project. The Ohio State University Bioarchaeological

Laboratory provided the facilities and equipment for specimen preparation and analysis.

Specimen procurement would not have been possible without the assistance of Mark

Whitmer, Michelle Whitmer, and Dr. Amanda Agnew.

I would also like to thank colleagues Corey Maggiano, Giuseppe Vercellotti,

Britney Kyle McIlvaine, and Dr. Deborrah Pinto for their assistance in conceptualizing and developing this project. I also owe a debt of gratitude to my undergraduate advisor,

Dr. James Theler, for he instilled in me a passion for anthropological inquiry that has remained with me through the years. It is he who I strive to emulate in the classroom, and I only hope I can become half the educator and mentor that he was throughout my undergraduate career.

Finally I would like to thank my family for their undying love and support through all the trials and tribulations experienced over the last few years. Without them I would never have had the drive to continue pursuing my goals, and I only hope that through the years I may repay the devotion and support laid upon me.

VITA

2002 B.Sc., University of Wisconsin-La Crosse

2004 M.Sc. with Distinction, University of Sheffield

2005-2006 Adjunct Instructor, Department of Behavioral and Social Sciences, Chaffey College, Rancho Cucamonga, CA

2006-2012 Graduate Teaching Associate, Department of Anthropology, The Ohio State University, Columbus, OH

2010 Adjunct Instructor, Department of Anthropology, Ohio University, Athens, OH

2010-2012 Adjunct Instructor, Department of Social Sciences and Anthropology, Columbus State Community College, Columbus, OH

2011-2012 Adjunct Instructor, Department of Biological Sciences, Columbus State Community College, Columbus, OH

FIELDS OF STUDY

Major Field: Anthropology

Area of Emphasis: Biological Anthropology

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TABLE OF CONTENTS

ABSTRACT ……………………………………………………………………………………………………………………ii

DEDICATION...... iv

ACKNOWLEDGEMENTS …………………...………………………………………………………………….…...v

VITA …………………………………………………………...……………………………………………………………...... vii

LIST OF TABLES ……………………………………………………...…………………………………………….….....xi

LIST OF FIGURES ……………………………………………………………………………………………………….xiii

CHAPTERS

1. Introduction……………………………………………………………………………………………………….1 1.1 Rationale for study……………………………………………………………………………………..6 1.2 Overview of sample and methods..……...…….……………………………………………….7 1.3 Specific hypotheses…………………………………………………………….....……………………9 1.4 Use of the human radius………………………………………………..……………….…………..10 1.5 Use of human cadavers…………………………………………………………………………….11

2. Bone Biology and Physiology…………………………………………………………………………..12 2.1 The osteoclast………………………………..……………….…………………………...………….13 2.2 The osteoblast and its lineage………..………………………………………….………...….15 2.3 Regulators of bone cell activation and function………………….…………...... …….....17 2.4 Bone modeling…………………………………………………..………..…………...……...…...22 2.5 Bone remodeling…………………….……………………….....……………………….…………..24 2.5.1 Primary purpose of remodeling…………………………...………………………27 2.6 The mechanostat………………………………………………...………………………………….31 2.7 Role of the lacunocanalicular network……………………..…....……...………………..34 2.8 BMU response to microdamage………………………………...... …...…………………37 2.9 Detecting mechanical strain levels in bone……………………..………...……………39

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2.9.1 Macrostructure………………………….………………………..……………………….39 2.9.2 Microstructure……………………………………………………………………………..41

3. Tendon and Biology and Physiology…………………...……………………….…………………45 3.1 Tendon development…………………………………………….……..……....………………..46 3.2 Structural properties………………………….……..………………………...…...…..…….………..…..47 3.3 Mechanical properties……………………………………...………..……....…………………49

4. Entheses…………………...…………………………………………………………………………………..53 4.1 Fibrous attachments……………………………………………..…...…………………………55 4.2 Fibrocartilaginous attachments……………………..………..…...………………………..57 4.3 Osteologic enthesial remnants……………………………………...... ………………….60 4.4 Entheses and activity-related studies……………………….…...…………...... ……...65

5. Materials and Methods………………………………………………...………………………………72 5.1 Materials…………………………..………………..………………...……………………………….….72 5.1.1 Human radius………..………………………………………………...…….…………….72 5.1.2 Population selection….…...………………………………....………………………..73 5.1.3 Population sample demographics………………....…………………..…...... 73 5.1.4 Specimen selection...... 74 5.1.5 Muscle actions...... 75 5.2 Methods...... 78 5.2.1 Specimen preparation...... 78 5.2.2 Histomorphometric field sampling...... 79 5.2.2.1 Observed and derived variables for microstructural . analysis...... 82 5.2.3 Data analysis...... 83

6. Results...... 86 6.1 Proximal cross-sections...... 86 6.2 Midshaft cross-sections...... 91 6.3 Distal cross-sections...... 94 6.4 Additional comparisons...... 98 6.4.1 Cross comparisons of three cross-sectional regions...... 98 6.4.2 Age comparisons...... 101 6.4.3 Sex comparisons...... 105

7. Discussion...... 108 7.1 Relationships between OPD and On.Ar...... 108 7.1.1 Mechanical loading...... 108 7.1.2 Age influences...... 110 7.2 Entheses and associated histomorphometry...... 111 7.2.1 Biceps brachii m...... 112 7.2.2 Pronator teres and supinator mm...... 114

7.2.3 Pronator quadratus m...... 115 7.2.4 Additional considerations...... 116 7.3 Diaphyseal asymmetry...... 117 7.4 Gross diaphyseal observations...... 117 7.5 Hypotheses revisited...... 119 7.6 Research limitations...... 121 7.7 Future directions...... 123

8. Conclusions...... 127

9. References...... 130

10. Appendix A: Total Data………………………………………………………………………………157

LIST OF TABLES

Table 5.1 Sample data for 14 individuals included in study...... 74

6.1 ANOVA of proximal cross-sections...... 90

6.2 Angular-linear correlation coefficients for proximal cross-sections………………………90

6.3 ANOVA of midshaft cross-sections...... 94

6.4 Angular-linear correlation coefficients for midshaft cross-sections………………………94

6.5 ANOVA of distal cross-sections...... 98

6.6 Angular-linear correlation coefficients for distal cross-sections……………………………98

6.7 ANOVA of all three radial cross-sections by rays...... 100

6.8 ANOVA of all three radial cross-sections by age...... 102

6.9 ANOVA of all three radial cross-sections by sex...... 106

7.1 Summary of acceptance or rejection of null and alternate hypotheses……..…….…....119

A.1 Mean OPD scores for the right radii of all 14 individuals by cross-section and quantified zone………………………………………………………………………………………………...... 156

A.2 Mean OPD scores for left radii of all 14 individuals by cross-section and quantified zone…………………………………………………………………………………………………………………..157

A.3 Mean On.Ar scores for right radii of all 14 individuals by cross-section and quantified zone………………………………………………………………………………………………….158

A.4 Mean On.Ar scores for left radii of all 14 individuals by cross-section and quantified zone…………………………………………………………………………………………………………………...159

A.5 Mean OPD scores for combined individuals by cross-section and quantified zone for both the left and right radii…………………………………………………………………………..160

A.6 Mean On.Ar scores for combined individuals by cross-section and quantified zone for both the left and right radii…………………………………………………………………………..160

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LIST OF FIGURES

Figure 2.1 Osteoclastogenesis and bone resorption in response to osteoblastic secreted regulating factors...... 21

2.2 Schematic diagram demonstrating cross-sectional modeling drift...... 22

2.3 Cutting cone demonstrating the synchronization of osteoclast and osteoblast activity along the same surface in a tunnel-like fashion...... 27

2.4 Schematic diagram demonstrating Leonardo da Vinci’s wire experiment...... 29

2.5 Simplified schematic diagram illustrating the negative feedback loop of Frost’s mechanostat...... 33

2.6 Evolution of the lacunocanalicular network...... 36

3.1 Schematic diagram of tendon microstructure...... 49

3.2 Stress/strain curve for tendon tested to failure...... 50

4.1 Fibrous bony insertion of temporal muscle along inferior temporal line...... 56

4.2 Fibrous periosteal insertion of hamstring muscle to the proximal tibia of a rat leg...... 57

4.3 Tracing of entire fibrocartilaginous insertion of biceps brachii m. onto the radial tuberosity...... 59

4.4 Pronator teres m. insertion along the lateral diaphysis of the radius...... 61

4.5 Radial tuberosity...... 62

4.6 Serial ranking of robusticity scores of radial tuberosity where biceps brachii m. inserts...... 64

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5.1 Illustration identifying the four muscle bodies predominately responsible for pronation and supination of the forearm, and thus rotation of the radius upon the ulna...... 77

5.2 Microscopic image of radial midshaft cross-section overlaid with the 8 specified zones (rays) analyzed...... 80

5.3 Merz grid as seen through a microscope eyepiece...... 81

6.1 95% confidence interval plot illustrating logged OPD means for the proximal cross- sections of the right radii...... 88

6.2 95% confidence interval plot illustrating logged OPD means for the proximal cross- sections of the left radii...... 89

6.3 95% confidence interval plot illustrating logged On.Ar means for the proximal cross-sections of the right radii...... 89

6.4 95% confidence interval plot illustrating logged On.Ar means for the proximal cross-sections of the left radii...... 90

6.5 95% confidence interval plot illustrating logged OPD means for the midshaft cross- sections of the right radii...... 92

6.6 95% confidence interval plot illustrating logged OPD means for the midshaft cross- sections of the left radii...... 92

6.7 95% confidence interval plot illustrating logged On.Ar means for the midshaft cross-sections of the right radii...... 93

6.8 95% confidence interval plot illustrating logged On.Ar means for the midshaft cross-sections of the left radii...... 93

6.9 95% confidence interval plot illustrating logged OPD means for the distal cross- sections of the right radii...... 96

6.10 95% confidence interval plot illustrating logged OPD means for the distal cross- sections of the left radii...... 96

6.11 95% confidence interval plot illustrating logged On.Ar means for the distal cross- sections of the right radii...... 97

6.12 95% confidence interval plot illustrating logged On.Ar means for the distal cross- sections of the left radii...... 97

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6.13 Line plot of mean OPD for each side-averaged radial cross-section by ray...... 100

6.14 Line plot of mean On.Ar for each side-averaged radial cross-section by ray...... 101

6.15 95% confidence interval plot illustrating logged OPD means for the proximal radial cross-sections by age range...... 102

6.16 95% confidence interval plot illustrating logged On.Ar means for the proximal radial cross-sections by age range...... 103

6.17 95% confidence interval plot illustrating logged OPD means for the midshaft radial cross-sections by age range...... 103

6.18 95% confidence interval plot illustrating logged On.Ar means for the midshaft radial cross-sections by age range...... 104

6.19 95% confidence interval plot illustrating logged OPD means for the distal radial cross-sections by age range...... 104

6.20 95% confidence interval plot illustrating logged On.Ar means for the distal radial cross-sections by age range...... 105

6.21 Bar chart illustrating mean OPD for all three radial cross-sections by males and females...... 106

6.22 Bar chart illustrating mean On.Ar for all three radial cross-sections by males and females...... 107

7.1 Microscopic image of proximal radial cross-section...... 113

rd 7.2 Schematic diagram illustrating how the forearm serves as a 3 class lever...... 118

Chapter 1: Introduction

Anthropologists regularly implement bone remodeling principles in response to mechanical loading to infer a causal relationship between muscle tendon insertions and activity levels. Previous research using both qualitative and quantitative data suggests size and complexity of osseous tendon insertions are indicative of strain magnitude resulting from habitual physical activity (al-Oumaoui et al. 2004; Capasso et al. 1999;

Cardoso and Henderson 2010; Churchill and Morris 1998; Havelkova et al. 2011; Hawkey

1998; Hawkey and Merbs 1995; Kennedy 1989; Lane 1887; Molnar 2006; Steen and Lane

1998; Stirland 1998; Thara et al. 2010; Weiss 2003; Weiss 2004; Weiss 2007; Wilczak and Kennedy 1998). This relationship has been employed to suggest general and specific activities past humans participated in throughout their lives. However, the presence and development of muscle tendon insertion sites preserved on skeletonized tissue, prematurely termed ‘musculoskeletal stress markers (MSM)’, has never explicitly been linked to activity intensity. This study investigates the relationship between these osseous attachment sites, preferentially referred to as entheses, and mechanically driven bone remodeling as reflected in bone microstructure (histomorphology).

That contractile forces generated through muscle activity are responsible for enthesis development is a logical conclusion. However, few investigators attempting behavior reconstructions question the lack of direct evidence for such a relationship. 1

Several researchers note that most activity-related studies fail to consider other mechanical and systemic influences on osteotendinous responsiveness to load, such as body mass or genetics or both (Robb 1998; Schlecht 2004; Schlecht 2008; Weiss 2003;

Wilczak 1998; Zumwalt 2006). Additionally, previous studies rarely account for muscle activity intensity, an individual’s skeletal maturity, or the time frame in which a proposed activity may have taken place during one’s lifetime.

Investigators often justify their use of MSM data by citing research conducted by

Chamay and Tschantz (1972) and Woo et al. (1981) as confirmation that activity increases periosteal apposition in regions associated with muscle tendon insertions.

Anthropologists commonly adopt the findings from these early experiments to argue that an increase in muscle contraction frequency increases periosteal capillary volume, causing the periosteum directly associated with the muscle to hypertrophy thus strengthening the tendon-anchoring mechanism (Hawkey and Merbs 1995; Torg et al.

1972; Zumwalt 2006). Both of these early exploratory studies in bone remodeling specifically concentrated on long bone diaphyses, referencing its ‘hypertrophic’ state at the periosteum following loading regimes. The respective authors were not concerned with local enthesial sites but the diaphysis as a whole. Our understanding of both mechanical and systemic influences in regional and global skeletal remodeling is much better understood since the pioneering days of these early implementers of ‘Wolff’s law,’ as discussed in chapter 2 (see Bergmann et al. 2011; Frost 2003). There is also a large body of research examining the functional roles of entheses and how they adapt

2 to a changing mechanical environment (Frost 2003; Thomopoulos et al. 2011;

Thomopoulos et al. 2010).

In 1997, a symposium entitled ‘Activity Patterns and Musculoskeletal Stress

Markers: An Integrative Approach to Bioarchaeological Questions’ was held at the sixty- sixth annual American Association of Physical Anthropologists meeting. The primary focus of this symposium was to develop a standardized method for the collection and analysis of osteological indicators presumed to have a direct correlation with physical activity. Selected papers given at this meeting, along with later contributions to the topic, were assembled into a volume of the International Journal of Osteoarchaeology

(1998) devoted entirely to MSM. Contributors assessed the role of entheses in reconstructing behavior as well as their methodological and statistical limitations.

The organizers of the symposium and the publication to follow recognized a lack of understanding in how hormones, bone remodeling rates, and various biomechanical agents affect enthesial development. However, they continued to advocate the value of muscle tendon insertions in interpreting gender-specific activities at both the individual and population-level, as long as contextual support from archaeological and ethnographic sources is available. The need for an established biological and social context when conducting behavioral interpretations is nothing new, especially since the last decade of bioarchaeology centered on how to account for this osteological paradox, or inherent mortality bias present when assessing past populations (Larsen 1997; Wood et al. 1992). Still, one cannot help but question what the predictive value of MSM

3 oriented research is when conclusions can only safely be drawn if additional contextual support is present; which is a variable factor when assessing archaeological populations.

These concerns notwithstanding, the decade to follow would include dozens of publications incorporating ‘musculoskeletal stress markers’ into their research model, and many graduate students eager to apply the evolving methodology in both archaeological and forensic settings. As momentum continued to progress forward, many of those applying the methods increasingly made concessions to the unknown parameters hypothesized to impact enthesial morphology alongside presumed mechanical forces.

To resolve some of these concerns and continue to diminish methodological subjectivity, a practicum entitled ‘Workshop in Musculoskeletal Stress Markers (MSM):

Limitations and Achievements in the Reconstruction of Past Activity Patterns’, was held in 2009 at the University of Coimbra, Portugal. Including some of the most published practitioners of MSM assessment, the workshop succeeded in generating a standardized terminology, as well as highlighting some of the methodological and interpretative contributions and restrictions associated with the use of tendon insertion morphology in behavioral reconstructions. The most important contribution to come from this seminar was the progress made in qualitatively assessing enthesial markers via 3D scanning, limiting the subjective nature of ranked morphological indicators. This technological progression in the assessment of entheses may allow for statistical correlations between skeletal morphology and activity, potentially allowing for the delineation of more meaningful macroscopic methodology in accounting for morphological development.

There continues to be a lack of sound research exploring the etiology of tendon insertion scarification, and whether it is truly indicative, or at least primarily representative, of habitually applied mechanical loads (Jurmain 1999; Pearson and

Buikstra 2006; Robb 1998; Schlecht 2004; Schlecht 2008; Weiss et al. 2012; Wilczak

1998; Zumwalt 2006).

Weiss (2003; 2004; 2007) has found statistically-significant correlations between the robusticity, geometrical properties, and MSMs of long bones, suggesting that tendon insertion development is at least partially dependent on mechanical influences, since it is well established that cross-sectional structure is indicative of such a relationship (Larsen and Ruff 1990; Ruff et al. 2006). Nevertheless, these analyses fail to identify a definitive affiliation between mechanical strain and insertion morphology since the qualitatively ranked MSM variables are statistically incompatible with the quantitatively calculated geometrical measurements. Additionally, non-demographic systemic influences and potentially impactful characteristics, such as tendon fiber volume independent of contractile strain, remain unaccounted for in these studies.

In attempting to understand this unique tissue interface and what truly drives its development, there are cost factors and technological limitations that must be considered, notwithstanding the constraints inherent in longitudinal development studies on living subadult populations. However, before anthropologists can continue to incorporate MSMs in their biological profiles, researchers must have a better grasp on how entheses respond to both internal and external environmental factors. Though anthropologists have made strides in attempting to methodologically and statistically

5 control variables such as age, sex and body mass (Villotte et al. 2010a; Villotte et al.

2010b; Weiss et al. 2012), there are still many other unexplored factors that may alter our perspective on enthesial response to load. If enthesial development is reflective of skeletal loading regimes, then methodology that is macroscopically reproducible can be devised.

If nothing else, previous research described above underscores the potential value in quantifying enthesis morphology. However, the degree to which insertion sites respond to load is still inadequately understood. More than a decade since the AAPA symposium, little has been done to address the initial concerns raised by Peterson and

Hawkey (1998). Pearson and Buikstra (2006) attribute this to a lack of interest among clinicians since osteophyte formation rarely has a detrimental effect in living humans.

To date, Ann Zumwalt (2006) has conducted the most thorough study assessing longitudinal development of entheses in exercised sheep. However, there remains a need for additional well designed experiments assessing enthesial development and what, if any, contribution these markers have in activity-based research.

1.1 Rationale for study

The following dissertation expands investigations into enthesial etiology by exploring relationships between remodeled intracortical matrix and the localized point of tendon insertion at the periosteum. This research comprises a histomorphological analysis of the non-weight-bearing radius at three distinct regions along the diaphysis where the primary performers of pronation and supination attach; including biceps

6 brachii and supinator (proximal), pronator teres (midshaft) and pronator quadratus

(distal). Quantification of the remodeling history within these three radial regions should provide a better understanding of how strains generated via muscle contraction are transferred, and ultimately dissipated, into the diaphysis. Specifically, this study tests the hypothesis that enthesial development is primarily mechanically driven, and that this is microscopically detectable within the associated compacta.

Regardless of the outcome, the following research strengthens behavioral interpretations in both anthropological and forensic contexts, with greater understanding of the unique intricacies and variances of human radial bone remodeling in response to strain. Results generated from this study may help clarify skeletal responses to habitual activity in the locomotive-free human upper limb, and expand the theoretical core of mechanically-induced bone remodeling in the human, non-weight bearing radius.

1.2 Overview of sample and methods

There are two components to this investigation. First, histomorphological evidence of lifetime remodeling activity representative of mechanical loading is calculated from left and right radii of 14 individuals. This evidence is in the form of secondary osteon creations per unit area (OPD), which reflect the history of intracortical remodeling activity. Remodeling activity (OPD) calculated for eight radial zones, defined by the anterioposterior and mediolateral axes along with their diagonal intersects, are compared to determine if remodeling is most frequent along rays directly associated

7 with enthesial insertion, as well as the diaphyseal principle strains (maximum and minimum bending strength). Second, osteon size is quantified from each radial zone, to assess the relative strain levels experienced along each ray. The calculations from all eight zones regarding these variables are compared to assess whether targeted remodeling and smaller osteons associated with higher strains are most prevalent in regions associated with enthesial insertions.

Data collecting procedures:

1. Quantify osteon population density (OPD), the number of complete and

fragmentary osteons per unit area, within the sampled zones of all radial cross-

sections.

2. Quantify the size (area) of all complete osteons within the sampled zones of all

radial cross-sections.

3. Compare the remodeling and osteonal variables to the gross morphology of the

radii to assess the relationship of these mechanically driven properties with the

insertion of particular muscle tendons.

This study furthers our understanding of enthesial development. Presence of considerable remodeling histories along rays associated with entheses suggests stress intracortically concentrated in these regions potentially result from direct tendon pull, bolstering assertions that mechanical strain significantly influences enthesial development. Relatively greater densities of smaller osteons support this, with higher

8 strains stimulating targeted remodeling (Burr 2002; Martin 2002), consisting of smaller osteons for increased intracortical fatigue resistance (Skedros et al. 2001; van Oers et al.

2008). This study is a preliminary investigation into the utility of enthesial development measures in behavioral reconstructions.

1.3 Specific hypotheses

1st Analysis

Ho: OPD scores in each radial cross-section are not significantly (p < 0.05) higher

along rays related to muscle insertions, relative to those not directly associated

with entheses.

HA: OPD scores in each radial cross-section are significantly (p < 0.05) higher

along rays related to muscle insertions, relative to those not directly associated

with entheses.

2nd Analysis

Ho: Mean osteon size in each radial cross-section is not significantly (p < 0.05)

smaller along rays related to muscles insertions, relative to those not directly

associated with entheses.

HA: Mean osteon size in each radial cross-section is significantly (p < 0.05) smaller

along rays related to muscles insertions, relative to those not directly associated

with entheses.

3rd Analysis

Ho: Significantly (p < 0.05) higher OPD scores and smaller osteon diameters are

not consistently found within similarly positioned rays.

HA: Significantly (p < 0.05) higher OPD scores and smaller osteon diameters are

consistently found within similarly positioned rays.

1.4 Use of the human radius

The human radius is chosen to serve as a simple model for examining remodeling activity in relation to muscle tendon insertions. The reasons for this are three-fold.

First, use of the radius allows for the isolation of muscular effects on bone since the influences of body weight and locomotive behavior are minimized. Second, it has easily defined enthesial placements along the diaphysis in comparison to the heavily loaded, more complex humerus, and is more active during forearm rotation than the relatively static ulna. Third, the human radius and its role in forearm dexterity is fundamental towards understanding hominin evolution in terms of specialized hand use and the increasing emphasis placed on bipedalism.

1.4 Use of human cadavers

Donated cadavers provide an ideal sample for investigating the histologic relationship between bone loading and entheses for several reasons: 1) cause of death is known, minimizing pathological conditions affecting bone turnover; 2) age and sex is known, enabling these variables to be controlled; 3) muscle tissue is present at the time of specimen collection, assuring that removed sections encompass the muscle insertions in question; 4) tissue preservation is not a concern; and 5) the sample is readily available for study and able to be investigated invasively.

Chapter 2: Bone Biology and Physiology

The vertebrate skeleton is an adaptive tissue serving several fundamental mechanical and metabolic functions throughout life. The primary role of the skeleton is to provide a scaffold for soft tissue while protecting vital areas of the body that are necessary for one’s survival. Additionally it has long been recognized that the marrow cavity, surrounded by hard tissue, is the body’s primary epicenter for hematopoiesis, or blood cell production. Metabolically, bone serves as a storehouse for soluble calcium, a crucial element in the regulation of plasma calcium homeostasis. All of these responsibilities are essential to one’s survival. However none more so than the functional adaptation of the skeleton in response to mechanical loads, maintaining the tissue’s integrity and thus its capability in providing the above-mentioned functions for the duration of an individual’s life is especially important. To accomplish this function, skeletal tissue is anisotropic, changing its macro- and micro-structural properties in relation to the direction and concentration of various mechanical stimuli.

In humans, and most other mammals, life-long bone metabolism and adaptation occurs within 4 distinct skeletal envelopes: the periosteal (outer cortical), intracortical, endosteal (inner cortical), and trabecular (marrow). Each of these surfaces vary in their response to local and systemic influences, as well as their tissue volume to surface area ratio (Parfitt 1983). However, all four envelopes consist of the same effector cells, and 12 thus bone formation and resorption along these surfaces is subject to similar physiological mechanisms.

There are two categories of effector cells found in skeletal tissue, both critical in maintaining the functional integrity of bone. Those that digest bone’s collagenous matrix are termed osteoclasts, and are aligned with the macrophages1 present in all tissues. Cells that form new bone by synthesizing and secreting unmineralized bone matrix are termed osteoblasts, which are essentially specialized fibroblasts2 and are related by lineage to osteocytes and bone lining cells (BLCs). Both of these cell types are responsible for physiological modeling and remodeling responses wherein skeletal tissue is spatially distributed and renewed to adapt to its altering systemic and local mechanical environment.

2.1 The osteoclast

Osteoclasts are multinucleated cells that originate from the union of mononuclear phagocytes in the hematopoietic red marrow found within the trabecular envelope (Li and Jee 2005). These cells are unlike the other macrophages in their lineage in that they lack many of the receptors present along their surface, aside from those for calcitonin and vitronectin (Jee 2001). The manner in which osteoclast precursor cells are signaled and thus recruited for bone resorption remains unclear, but

1 Macrophages are found throughout the body and both engulf and digest cellular and foreign materials. They are a type of phagocyte, or white blood cell, that protects the immune system. 2Fibroblasts are derived from the precursor mesenchymal cells and are responsible for synthesizing collagen and the surrounding extracellular matrix.

13 studies have found osteoblasts to play an integral part (discussed below) (Li and Jee

2005).

Following activation, osteoclast precursor cells fuse at the site of resorption to form a mature osteoclast; their primary responsibility is to digest the mineral and organic components of the bone matrix (Fig. 2.1). To initiate this process there is some evidence that BLCs, stimulated by parathyroid hormone (PTH), dissolve the outer osteoid, or unmineralized layer, providing osteoclast access to the bone matrix (Everts et al. 2002). Following this, osteoclasts attach themselves to the surface via cell membrane integrin receptors (21 and v3), which when bound to arginine-glycine- aspartic (RGD) protein sequences3 within the matrix; inform the cells of various molecules within their environment. These receptors provide the attachment for osteoclasts by forming an ectoplasmic seal around the membranous surface in contact with the bone matrix (Rodan and Rodan 1995).

Once the osteoclast attaches to the bone surface, the ruffled border of the phagocyte forms an acidic environment close to a pH level of 3.5. Herein H+ ions are secreted for the dissolution of the bone minerals, in conjunction with proteolytic enzymes4 that digest the solubulized matrix (Jee 2001). The resulting cavity, commonly referred to as a Howship’s lacuna, is then flooded with extracellular matrix once the osteoclasts detach, effectively raising the pH level to more basic levels. Osteoclasts can

3 Though not clearly known, it is thought that these protein sequences are comprised of vitronectin, osteopontin, and bone sialoprotein (Rodan and Rodan 1995). 4 Proteolytic enzymes (e.g. cathepsin K) are responsible for protein catabolism, which breaks down the peptide bonds in preparation for matrix digestion (Barrett et al. 2003). 14 live up to 7 weeks, however following cessation of bone resorption they return to the marrow and subsequently undergo apoptosis, or programmed cell death (Jee 2001).

2.2 The osteoblast and its lineage

Osteoblasts are mononuclear and originate from mesenchymal precursor cells located along the periosteal and endosteal envelopes, as well the marrow stroma5 (Jee

2001). These are cuboidal cells with a large nucleus, gap junctions, and hormonal receptors, that produce all the components found within the bone matrix (Martin et al.

1998) The process by which these stromal cells differentiate into preosteoblasts

(mesenchymal osteoprogenitor cells) and subsequently mature osteoblasts is not fully understood. However, there is some evidence for the demarcation of these cells, which is discussed below.

Once osteoblasts have reached maturity they become responsible for both matrix formation and mineralization. Though our understanding of what the exact activators of osteoblast differentiation and the processes directing their movement is unclear, there is considerable knowledge as to what occurs once they arrive to a designated locale. Osteoblasts secrete an organic matrix consisting of 90% type I collagen, and 10% noncollagenous matrix proteins (e.g., osteopontin, osteonectin, osteocalcin, sialoprotein, thrombospondin, fibronectin, proteoglycans, bone morphogenic proteins) and growth factors. Though investigations are ongoing, it

5 Marrow stroma predominately consists of adipocyte-rich yellow marrow that is not directly involved in hematopoiesis, and contains mesenchymal stem cells that differentiate into specialized cells, giving rise to various connective tissues. It acts to provide a framework for marrow tissue and provides the foundation that bone forms upon. (Bianco and Robey 2000). 15 appears the presence of these various proteins within the bone matrix may be responsible for initiating bone mineralization and calcium phosphate crystallization

(Roach 1994). Collectively, the secreted product consisting of collagen and the associated proteins comprise the osteoid. Once deposited, there is approximately a 10 day lag time before mineralization is complete in adult bone, with woven6 and diseased bone demonstrating a much shorter period for mineralization (Frost 1966; Jee 2001).

During secretion and mineralization of bone matrix some of the osteoblasts become entrapped, resulting in a transformation that alters these cells into osteocytes.

Osteocytes are situated in small bony chambers referred to as lacunae, and are the most abundant cells found within the bone matrix. In order to remain linked with cells differentiated from the same lineage (e.g., osteoblasts and BLCs), they extend cytoplasmic processes throughout the mineralized matrix that allow them to transport nutrients, signaling molecules, and waste, while remaining in contact with their lineage brethren via gap junctions. Therefore, one of their primary functions is to regulate mineral homeostasis in conjunction with BLCs. Research has shed light on the role of osteocytes and the importance of their lacunocanalicular network in detecting strain levels outside bone’s normal environment; discussed in detail below.

Like osteocytes, BLCs are also from the osteoblast lineage and remain after the bone formation process. Following the cessation of matrix deposition, BLCs remain along quiescent bone surfaces as elongated, flattened cells. These dormant osteoblasts

6 Woven bone has a highly irregular arrangement of collagen and osteocyte lacunae. This type of bone is considered immature as it is the initial deposition of bone on the cartilaginous anlage during development and forms the callus following bone fracture (Marotti 1996).

16 are capable of forming bone prior to resorption given anabolic stimulation since they maintain their hormonal receptors, unlike osteocytes (Martin et al. 1998). Additionally,

BLCs most likely play a role in calcium homeostasis by providing a barrier between bone matrix and interstitial fluids to regulate the exchange of calcium and phosphate ions

(Jee 2001).

2.3 Regulators of bone cell activation and function

The processes by which osteoclasts and osteoblasts are impacted by various hormones, proteins, cytokines and growth factors remain ambiguous, however some general observations can be made. It is well established that osteoblasts are intricately involved in the differentiation and development of osteoclasts through the production and emission of several factors that bind to osteoclast precursor cell receptors (see Fig.

2.1) (Rodan and Martin 1981).

Two effectors from the tumor necrosis superfamily (TNF), predominately synthesized by the osteoblast lineage, regulate the transcription of osteoclast precursors. Osteoprotegrin ligand (OPG-L) is a stimulatory factor that initiates cell precursor differentiation, and their subsequent fusion to form a mature osteoclast, as well as inhibiting apoptosis. Its counter effector, osteoprotegrin (OPG), inhibits cell precursor differentiation and fusion, while inducing cellular apoptosis (Xu et al. 2005).

The receptors for these effectors are members of the TNF and are referred to as RANK

(or OPG) and RANK-L (or OPG-L). RANK is found along the surfaces of osteoclast precursors and RANK-L lines the surfaces of osteoblasts and bone lining cells (BLCs).

When the effectors of RANK and RANK-L bind together they activate osteoclastogenesis.

However OPG can run interference in this process by binding to RANK-L instead of its

RANK receptor, inhibiting osteoclastogenesis (Jee 2001; Xu et al. 2005). Therefore the ratio of OPG-L and OPG in the marrow may be responsible for the number of osteoclasts present along the bone matrix, driving bone loss in osteopenia and subsequently osteoporosis (Jee 2001; Li and Jee 2005).

Signaling proteins, or cytokines, are also members of the TNF superfamily, and are expressed by osteoblasts. For example interleukin-1 (Il-1) is secreted by osteoblasts and acts to induce osteoclast differentiation. Experimental mouse models have shown that the osteoblastic release of Il-1 occurs in tandem with estrogen levels, with estrogen deficiency followed by an increase in the release of Il-1 (Troen 2003). Additionally, macrophage colony-stimulatory factor (M-CSF) binding to the surfaces of hematopoietic stem cells such as osteoclasts, are known to initiate the differentiation of uncommitted osteoclast precursor cells (Wiktor-Jedrzejczak et al. 1990). Various other forms of CSF

(i.e. granulocyte-macrophage CSF) have also been linked to osteoblast proliferation, and paradoxically inhibit their differentiation (Yoneda 1993).

The sex hormones estrogen and testosterone appear to directly influence the regulation of osteoblasts. A normal level of estrogen found in pre-menopausal women is associated with the upregulation of osteoblasts, generating an increase in bone formation along the endosteum (Frost 1992; Martin 2003c; Pearson and Lieberman

2004). In contrast, older women that are in a menopausal state, and thus their estrogen is progressively depleted, demonstrate a downregulation of osteoblasts with fewer

18 bone forming teams, halting endosteal bone formation (Weaver 1998). The effect of estrogen on osteoclasts is exactly the opposite with the hormone acting as an inhibitor to osteoclast precursor cell differentiation. Individuals with remodeling signatures associated with osteopenia and osteoporosis demonstrate a decrease in estrogen, confirming its inhibitory power in slowing the resorption process (Frost 1992; Li and Jee

2005). Similar effects have been demonstrated using testosterone with normal levels allowing for bone formation, and subnormal levels resulting in decreased bone mass

(Martin 2003c).

In addition to estrogen and androgens, thyroid hormones are also known to play an important role in regulating bone cell activity. The effect of PTH, though unclear, has been observed initiating bone resorption. As mentioned previously, PTH stimulates

BLCs which initiate the digestion of the outer osteoid layer and subsequently their retraction from the localized surface, providing osteoclasts access to the bone matrix

(Everts et al. 2002; Miller et al. 1989). Calcium deficiency elevates PTH levels, increasing vitamin D production to improve intestinal and renal mineral absorption.

Thus coupled PTH and vitamin D initiate resorption to increase calcium concentrations in blood (Harada and Rodan 2003). However bone formation following intermittent injections of PTH in pharmacological animal trials has also been observed (Dobnig and

Turner 1995).

Less is known about the effects of proteins on bone cell function, however a few studies have yielded interesting results worth mentioning. Calcitonin, a protein produced by the thyroid gland, has an opposite effect to that of PTH in that it decreases

19 calcium concentrations, and thus inhibits renal and intestinal mineral absorption, and subsequently bone resorption (Lauber et al. 1995). Leptin, a hormonal protein produced by adipocytes, has recently been linked to bone mass regulation. Research has shown that leptin has receptors on both osteoblasts and osteoclasts, and thus has a role in the regulation of bone metabolism. The expression of leptin both reduces cancellous bone volume, while increasing that of cortical bone, which may beneficial to individuals in an obese state for the enlargement of overall bone size to combat abnormal increases in body weight (Hamrick and Ferrari 2008). Holloway et al. (2002) suggest that leptin increases OPG levels while decreasing that of RANK-L, thus inhibiting osteoclast differentiation. Additionally increased leptin may also play a role in the differentiation of mesenchymal cells into osteoblasts by inhibiting that of adipocytes

(Harada and Rodan 2003; Thomas et al. 1999). However increased levels of leptin have demonstrated a reverse effect with increased bone resorption and decreased bone formation, which may be related to elevated adipogenesis in the bone marrow (Martin et al. 2007).

Osteoblast differentiation is primarily regulated by core-binding factor-1

(Cbfa1), which also regulates the rate of osteoblastic bone secretion once these cells have matured (Ducy et al. 1999). Cbfa1 is regulated by several growth factors related to osteoblastic mesenchymal origin and are grouped into five distinct families: bone morphogenetic proteins (BMPs), fibroblast growth factors (FGFs), insulin growth factors

(IGFs), platelet-derived growth factor (PDGFs), and transforming growth factor- (TGF-)

(Jee 2001). Most importantly for osteoblast differentiation are BMPs which bind to mesenchymal cells in the marrow and initiate Cbfa1 production (Li and Jee 2005).

The mounting evidence summarized above suggests that osteoblasts are at the center of modulating bone resorption. Osteoblasts produce various molecules that bind to receptors found along the osteoclast surface that both promote and inhibit their genesis (Fig 2.1). Thus, when osteoblasts are present there is almost certainly an upsurge in bone resorption.

Figure 2.1 Osteoclastogenesis and bone resorption in response to osteoblastic secreted regulating factors. Following stimulation of PTH, osteoblasts secrete RANK-L and M-CSF. PTH also inhibits OPG expression. RANK-L and M-CSF interact with their receptors along the surface of macrophage cells, activating osteoclast precursor cell differentiation, which is inhibited with the presence of OPG. Following

differentiation of mature osteoclasts, v3 integrin is released to bind the multinucleated cell to the - - exposed bone surface. Once the ruffled border forms, HCO3 /Cl exchange lowers the pH of the extracellular matrix to 3.5. H+ ions are secreted to dissolve the mineralized tissue, and cathepsin K digests the solubulized matrix. Adapted from Teitelbaum (2000).

2.4 Bone modeling

Bone modeling is a biological mechanism that allows for bone sculpting to alter their shape and increase in size. This is primarily performed during skeletal growth and development, but may continue at a lesser degree throughout one’s lifetime to meet varying biomechanical demands. The juvenile modeling process is characterized by the addition of new bone via osteoblasts and resorption of old bone via osteoclasts along independent surfaces. This creates a ‘drift’ effect, wherein bone is selectively added or removed from both the periosteal and endosteal envelopes (Fig. 2.2).

Figure 2.2 Schematic diagram demonstrating cross-sectional modeling drift. Bone is drifting from left to right. (-) signs indicate surfaces undergoing bone resorption and (+) signs reflect surfaces where bone formation is occurring.

Additionally, modeling is responsible for reduction of the periosteum of metaphyses in preparation for fusion to the diaphysis, and in expanding the marrow cavity to counter weight gains during growth (Enlow 1962; Frost 1973). Therefore, though they work on different surfaces, osteoclasts and osteoblasts are synchronized to either enlarge or shape bone in an adaptive manner. Because of drift, often there is no original tissue remaining in mature bones. This means that bone present in adults is younger than the chronological age of the individual. For example Wu et al. (1970) estimate the ‘effective’ age, or the age when all former bone is removed, is approximately 12.5 years in the human rib. Though the effective age has only been estimated in the human rib, Frost and Wu (1967) suggest this should only vary 3 years for the long bones.

Along the radial diaphysis, it is modeling in response to biomechanical forces and muscle volume that creates lateral curvature of the long bone. However, bone formation via modeling appears to be gender-specific during growth, with women substantially increasing their endosteal surface during the final years of puberty as estrogen levels rise (Martin 2003c). This is an adaptive mechanism designed to counteract the detrimental effects of increased remodeling activation following menopause as estrogen levels decrease. Following skeletal growth, drift via resorption appears to cease while formation drift, though minimized and virtually nonexistent following complete skeletal maturity in an individual’s 30s, continues on the periosteal surface (Li and Jee 2005). Modeling may occur after this point, but only in response to particular metabolic disorders and when the mechanical environment has been radically

23 altered (e.g., arthroplasty, (Peck and Stout 2007) . However, modeling in response to such factors generally involves the deposition of woven bone, not lamellar bone7 (Rubin and Lanyon 1987).

2.5 Bone remodeling

Remodeling is more complex than modeling and is the primary biological mechanism that allows bone to maintain its mechanical integrity. The primary function of remodeling is to replace fatigue damaged bone (Frost 2000). However, it is also responsible for replacing woven bone with lamellar bone during development, and to increase soluble calcium levels for homeostasis regulation. This process contrasts with modeling in that the osteoclasts and osteoblasts are coupled to achieve a common purpose along the same bone surface. Frost (1987) has termed these groups of cooperating cells basic multicellular units (BMUs). Thus, remodeling can occur in two specific manners; targeted remodeling which is a response to fatigue damage, and stochastic remodeling, a response to non-mechanical factors such as genetics, hormones, and calcium homeostatic requirements.

BMUs work on all four bone envelopes and replace tissue in discrete packets termed secondary osteons in intracortical bone and ‘hemiosteons’ within the other three envelopes. Secondary osteons, or Haversian systems, are characterized by a

7 There are two types of lamellar bone: primary bone is deposited de novo on an existing surface of immature bone, and consist of circumferentially arranged sheets (lamellae) of parallel collagen fibers; secondary bone (Haversian system or secondary osteon) results from remodeling and consists of parallel collagen fibers arranged much like twisting plywood, with the collagen orientation continuously rotating upon an axis usually in a helicoidal fashion but sometimes in 90 degree orientations. (Giraud-Guille 1998). 24 central canal allowing for fluid and nutrient movement, surrounded by centripetal lamellae containing osteocyte-filled lacunae between each lamellar sheet. As mentioned above, osteocytes maintain communication with one another and BLCs via a lacunocanalicular network. Enclosing each osteon is a demineralized zone called the cement line.

BMUs follow a sequence of events, including activation, resorption, reversal, and formation. Activation is characterized by the recruitment of differentiated cells from the precursor cell populations (Martin et al. 1998). As mentioned earlier, the initiation of this stage via chemical signaling remains unclear; however mechanical signaling may play a crucial role in activating the remodeling process (discussed below).

Following activation is resorption, characterized by the demineralizing of bone via osteoclast secretion of proteases and acids (Martin et al. 1998). Resorption occurs in a tunnel-like fashion forming what is commonly referred to as the cutting cone or resorptive bay (Fig. 2.3). It is the osteoclasts that determine the diameter of this cone, and subsequently the resulting size of the completed basic structural unit (BSU) of remodeling, or osteon. However, several factors such as age and strain magnitudes may influence this process and are discussed below. In cortical bone osteoclasts within the cutting cone move relatively parallel to the bone’s longitudinal axis in an ellipsoidal manner and form scalloped edges termed Howship’s lacunae, or resorptive bays.

Once osteoclastic activity ceases there is a lag before the formation process begins. This allows for preosteoblasts to differentiate into fully mature osteoblasts to

25 initiate the formation phase (Li and Jee 2005). The reversal cement line is indicative of this reversal phase as it signifies the maximum of osteoclastic resorption.

Formation consists of mature osteoblasts working in teams to deposit unmineralized lamellar sheets consisting of parallel collagen fibers. In cortical bone a central channel, or Haversian canal, is left open to allow passage for vascular structures that supply the surrounding tissue and associated cell bodies. Within other envelopes,

(e.g. endosteal and trabecular) these vascular structures and associated cell bodies exist within defined ‘remodeling compartments’ (Hauge et al. 2001). During the formation process some osteoblasts lag behind and are enclosed in lacunae where they differentiate into osteocytes. Other osteoblasts that remain following this development differentiate into BLCs and linger on the surface. Once deposition of the osteoid is complete, hydroxyapatite brought from the local extracellular fluid via osteocytes and their lacunocanalicular network, is deposited within and between the collagen fibers, effectively mineralizing the matrix (Li and Jee 2005).

Figure 2.3 Cutting cone demonstrating the synchronization of osteoclast and osteoblast activity along the same surface in a tunnel-like fashion. The upper portion of the figure is an active cutting cone moving longitudinally through the cortical matrix, and the lower portion is a schematic diagram demonstrating the position of osteoclast and osteoblast cells. Osteoclasts begin tunneling through the calcified matrix and osteoblasts lag behind depositing osteoid. The expanding capillary in the center of the cone provides nourishment to the advancing osteoclasts. Adapted from Robling et al. (2006).

The entire remodeling sequence for a single BMU takes approximately 90-120 days in human skeletal tissue (Martin et al. 1998). Since vascularity is essential for tissue survival, the process results in a net bone loss since bone removed for canal construction is never replaced. This is the primary issue surrounding metabolic disorders like osteoporosis, since increased remodeling activity replaces old bone, but results in greater intracortical porosity.

2.5.1 Primary purpose of remodeling

The fossil record demonstrates that skeletal remodeling has existed as long as large vertebrates became weight-bearing, terrestrial organisms (Enlow and Brown 1956;

1957; 1958). This suggests that continuous remodeling of bone was selectively advantageous for survival. One hypothesis related to fatigue damage, has its roots in a mechanical principle exemplified by Leonardo da Vinci (Fig. 2.4). Leonardo conducted a strength test on iron wires that varied in length, but consisted of equal diameters

(Martin 2003b; 2003c). This test demonstrated that longer wires were weaker than shorter ones given the same load, since the larger the volume of a structure, the greater probability of it containing significant flaws. Relating this to bone, it is well known that various species load bone to approximately the same peak strain levels regardless of their size, providing a similar situation in vertebrates as to that observed in da Vinci’s wires (Rubin and Lanyon 1984). Thus, if a large and small animal were equally loaded in a repetitive manner, and lacked a remodeling mechanism, the fatigue life of the larger animal would be much shorter than that of the smaller one (Martin 2003c). In this scenario, the logical solution would be to reduce strain by increasing bone deposition, theoretically extending the skeletal fatigue life indefinitely. However, this approach has several disadvantages. First, it creates a very large skeleton more likely to contain flaws.

Second, it requires larger muscles to allow efficient movement of the heavier limbs, increasing the original applied loads. Lastly, and most importantly, this approach reduces the fitness of an organism to survive in a particular environment, as it requires greater metabolic energy for mobility (Alexander 1992). In light of these disadvantages, it appears that maintenance of a light skeleton via bone remodeling is advantageous, as it allows for continuous removal of fatigue damage to increase a bone’s fatigue life to match that of the organism’s lifetime (Martin 2003a). With this mechanism, a more

28 gracile bone is capable of rivaling the fatigue life of a more robust bone experiencing minimal, if no remodeling.

Figure 2.4 Schematic diagram demonstrating Leonardo da Vinci’s wire experiment. All three wires consist of the same diameter but are of different lengths. Each wire was loaded with increasing loads until they broke. The load required to fracture the wire corresponded to the length of the wire, with the shortest wire having the greatest resistance to fracture. Fracture resistance is attributed to the length of the wire, with the shorter wire having less volume and thus fewer potential flaws within the material, in comparison to the more voluminous longer wires.

Microfractures provide evidence that bone is routinely subjected to fatigue damage accumulations. It is commonly accepted that this occurs as a result of bones being too light (Martin 2003a; Martin 2003b). Thus fatigue damage accumulates during normal activity levels as strain magnitude increases (Agnew 2011). It is the role of the remodeling mechanism to repair this damage to maintain a light skeleton throughout the organism’s lifetime. A light skeleton is beneficial in that it permits more efficient locomotor movements. Reductions in bone mass results in reductions in muscle mass,

29 allowing for greater efficiency in speed, endurance, and metabolic activity (Martin

2003c). A second advantage to remodeling is that it allows for more elastic bones that are tougher, enabling sufficient absorption of energy without fracture. This requires a balancing act between strength and stiffness, with bone turnover maintaining a “happy medium.”

This balancing act between strength and stiffness may also be important in fluid and solute transport between osteocytes and bone lining cells via a hydraulic, lacunocanalicular network. The major challenge for a hydraulic network in bone is the movement of nutrients across large spans of calcified matrix. Experiments have demonstrated that skeletal deformation resulting from strain, may be necessary for convective fluid movement (Knothe-Tate 2001; Knothe-Tate et al. 2000). Therefore it appears that strain magnitudes necessary for interstitial fluid flow through the lacunocanalicular network, are also sufficient to generate fatigue damage (Martin

2003b). This presents another enticing balance between bone stiffness and flexibility, and calcium homeostasis and fatigue damage. In other words, bone must be light for efficiency, yet maintain some degree of stiffness, while allowing flexibility for strain- induced interstitial fluid flow, which inadvertently results in fatigue damage. If this is in fact the process occurring in large vertebrate skeletons, then a remodeling mechanism is definitely advantageous for the preservation and maintenance of bone, which in turn extends the life of large, active vertebrates without risk of potentially fatal fracturing.

2.6 The mechanostat

So what activates BMUs in the first place? Prior to 1960, most skeletal biologists emphasized that bone physiology was predominately influenced by nonmechanical factors. Thus, within this paradigm, skeletal architecture, bone health, and overall bone strength were deemed to reflect one’s genetic and hormonal environment, which directed BMU activation. However, by the early 1960s a new understanding of skeletal biology based on increasingly new evidence came to light that both supplemented and refuted earlier claims (Frost 1995). This new evidence is collectively termed the Utah paradigm, reflecting a series of Hard Tissue Workshops held at the University of Utah

School of Medicine. Within these workshops, contributors agreed that bone adaptation in response to mechanical stimuli does not act independently of nonmechanical agents.

However, they recognized that during development it is primarily mechanical factors that guide bone growth through time and space, with the biologic response to applied stress directed by genetic baselines formed in utero. Consequently, there is now a greater emphasis placed on biomechanics when interpreting bone physiology.

Despite most skeletal biologists agreeing that mechanical stimuli play a primary role in the development and maintenance of bone, it is not clear what the mechanisms are that drive bone adaptation via mechanical loads and other nonmechanical factors.

One plausible hypothesis was developed by Harold Frost (1987; 2003) and is termed the mechanostat. Frost envisioned a system that maintains bone’s mechanical competence by synchronizing a variety of biologic machinery that alter bone mass and architecture in relation to normal activity levels. This model is a negative feedback loop mechanism

31 wherein error signals due to disproportion in mechanical loading is detected and then corrected for, removing the cause of the initial error (Frost 2003). Having a feedback loop allows for errors to be removed without over correction, by remaining in constant communication with the responding mechanisms (Li and Jee 2005). If the error is fixed then the signal turns off. Conversely, if the mechanism over compensates for the error then a different mechanism is activated to remedy the problem.

In addition to the negative feedback loop, the mechanostat hypothesis requires the following mechanisms: 1) a threshold that positions the minimum effective strains, determining when modeling and remodeling should be activated to fit the “typical peak voluntary mechanical loads” (Frost 2003); 2) a sensor mechanism that can perceive mechanical force and translate it into detectable signals and determine their positioning in relation to the threshold (Martin 2000); and 3) a mechanism that can respond to the signal and effectively adapt bone to maintain its mechanical competence (modeling and remodeling).

Frost’s threshold mechanism is termed minimally effective strains (MES), and determines the course of action for all other biologic mechanisms. This is based on set points that delineate a range of strain values produced by mechanical loads (Li and Jee

2005). If the strain is within the acceptably determined set point range then no mechanistic response is needed. However, if the strain is below or above this range, or threshold, then bone will respond by either modeling or remodeling to adjust bone’s strength accordingly. When strain levels are below the threshold (resulting from disuse) then remodeling on bone’s endosteal and trabecular surfaces will occur to lower the

32 level. This usually results in a net bone loss, since the amount of bone replaced is less than the quantity resorbed. In contrast, if the strain levels exceed the threshold then modeling ensues, depositing lamellar bone to increase the strain level (Fig. 2.5).

Figure 2.5 Simplified schematic diagram illustrating the negative feedback loop of Frost’s mechanostat. Strain within the normal threshold generates no mechanistic response. If strain is above the normal threshold, fatigue occurs, initiating modeling to strengthen the matrix and return strain levels to the normal threshold. If strain is below the normal threshold due to disuse, then future strains activate remodeling to return these levels back to near normal.

For the threshold mechanism to work, bone must be able to detect strain. There are several theories for how this occurs, most of them centered on the lacunocanalicular network. As discussed above, osteocytes form a syncytium with BLCs via fluid-filled canaliculi that span throughout the cortical and trabecular matrices.

Applied mechanical strains cause bending moments, resulting in compression and tension, subsequently moving interstitial fluid stored in the osteocyte cytoplasm (Burger et al. 2003). The resulting deformation is transformed into a signal that is relayed via gap junctions to bone lining cells resting on the endosteal surface. Bone lining cells then activate RANK-L receptors for cell differentiation. This intricate network is also believed to sense abnormal strain through other means, such as microdamage; however Frost’s model does not directly deal with this, with only brief mention of microdamage resulting from high strain levels (detailed discussion below).

As mentioned before, nonmechanical factors may be responsible for activating remodeling by influencing the positioning of threshold set points. Frost (1992) suspects that a reduction in estrogen, following menopause, may shift the remodeling threshold upwards. This would provide an explanation for why aging females have higher bone turnover than males, and thus a greater propensity in reaching an osteopenic state. In contrast, Schiessl et al. (1998) suggest that the threshold moves downwards in females immediately following puberty, when there is a substantial increase in estrogen levels.

Gunness and Hock (1993) have observed a similar downward movement of the threshold set point in relation to low levels of parathyroid hormone.

2.7 Role of the lacunocanalicular network

The lacunocanalicular network provides hydraulic conductance of fluid and solutes between the blood supply and bone cells, with disruptions (fatigue damage) attributed to mechanical strain. Fatigue damage is characterized by microfractures that

34 sever canaliculi, causing osteocyte apoptosis upon propagation. It is theorized that this somehow alerts BLCs for the activation of BMUs, and subsequently remodeling of cortical bone in the damage area (Marotti 1996; Martin 2000). In terms of efficiency, the lacunocanalicular architecture must be optimal for transporting fluid and solutes. If the radial distance of the network is too great or small, then nutrient transport will not be viable in relation to minimal energy expenditure needed to maintain the highest hydraulic conductance (Mishra and Knothe-Tate 2003). Therefore resistance must be low to allow for efficient conductance. Experimental studies by Mishra and Knothe-Tate

(2003) suggest this is achieved when the number of canaliculi is increased and arranged in a parallel fashion. Increasing the number of passages minimizes resistance, while increasing the safety factor. If some canaliculi are severed or blocked, they will not disrupt the conductance of the entire network. Branching of the canaliculi from each lacuna is presumed to be optimal, providing alternative pathways and increased distances of nutrient transport.

From an evolutionary standpoint this may explain the differences between vertebrates in terms of bone microstructure. Amphibians and other small vertebrates have thin cortical cortices providing short radial distances for nutrients to travel from the endosteum to the periosteum, and a low factor of safety (Mishra and Knothe-Tate

2003). Therefore, they typically have simple hydraulic architecture with little, if any parallel organization and branching of the canaliculi. In contrast, larger mammals and reptiles have a much thicker cortical cortex that spans several centimeters, requiring a

35 branched network with some parallel canalicular organization, as the demand for long distance transportation and a higher safety factor increases.

Figure 2.6 Evolution of the lacunocanalicular network. (A) Simple hydraulic network. (B) Some branching and parallel networks between periosteal and endosteal envelopes. (C) Comparable to B but with more complex parallel networking, increasing the safety factor, similar to canalicular pattern of amphibians and other small vertebrates. (D) Demonstrates more complex branching with a composite of network C linked via Haversian and Volkmann’s canals within the intracortical matrix. Adapted from Mishra and Knothe- Tate (2003)

Thus, over the course of evolution, vascular and lacunocanalicular networking has become more complex with the increasing size and metabolic requirements of bone. Based on these observations, it would appear that the complexity of the lacunocanalicular network evolved to accommodate large cortical cross sections, thereby lending more structural support to terrestrial vertebrates, while simultaneously maintaining calcium homeostasis.

2.8 BMU response to microdamage

The presence of microdamage is presumed to activate osteocyte signals by disrupting the lacunocanalicular network, and thus the mechanotransduction of signals

(Martin 2000). Theories addressing this work are in tandem with the mechanostat hypothesis, suggesting that like Frost, modeling increases when strain levels exceed a given threshold. However they also suggest that while modeling within this window increases bone strength, targeted remodeling is also activated to replace fatigue damaged bone. Marotti (1996) hypothesized that signals transduced by osteocytes during the BMU cycle are inhibitory in nature. Thus, they would effectively regulate osteoblasts by slowing osteoid production in those osteoblasts most affected by the signal, allowing them to become trapped in the matrix, and essentially expanding the functional syncytium. Martin (2000) extended this theory, suggesting two functions for such an inhibitory signal. The first function is that proposed by Marotti that slows matrix production in nearby osteoblasts, allowing them to become trapped in order to become new osteocytes. The second function suggests that this signal continues to be

37 generated once the BMU is complete, inhibiting the “inherent tendency” of BLCs to activate additional remodeling sequences. Therefore Martin’s hypothesis proposes that

BLCs are restrained from remodeling activation through the bombardment of inhibitory signals being sent from osteocytes to the bone surface via gap junctions. This is where the shared origins within the osteoblastic lineage and the ability of BLCs to initiate cell differentiation, discussed above, becomes most important. If Martin’s hypothesis proves correct, then the activation of remodeling would only occur when the inhibitory signal is diminished.

What factors would lead to the diminishment of an osteocytic inhibitory signal?

One theory, which is in tune with the mechanostat, is that disuse would increase remodeling since strain-levels are insufficient for mechanotransduction of inhibitory signals to the normally quiescent BLCs. This could explain remodeling in response to not only global disuse but also local disuse resulting from isolated incidences of fatigue damage (Martin 2000). Secondly, microfractures could be responsible for remodeling if they sever canaliculi, and thus result in inhibitory signals not being sent to connected

BLCs. Lastly, osteocyte apoptosis would activate remodeling, as the effected cells are no longer inhibiting BLCs associated with them in the functional syncytium. Apoptosis can occur as a result of microdamage, but also through disuse (Noble et al. 1997) and estrogen withdrawal (Tomkinson et al. 1997), potentially shedding light on observations of increased remodeling associated with aging. Again this would be in tune with the predictions of the mechanostat.

2.9 Detecting mechanical strain levels in bone

As mentioned earlier, bone is anisotropic in that its mechanical properties change depending on direction and location of applied forces. This concept is attributed to Julius Wolff (1892), who recognized that trabecular arrangements within the proximal femur are a response to mechanical stimuli. In cortical bone, calcified tissue volume within a particular region reflects stress magnitude, while shape indicates directionality of applied stress (Lanyon and Rubin 1985; Martin 2003c). These adaptive changes can be observed in the macro- and microstructure of bone.

2.9.1 Macrostructure

Macro skeletal adaptation to mechanical loading is assessed using longstanding engineering principles that predict bending and torsional strengths of structural beams

(Lovejoy et al. 1976; Ruff 2008). Long bones are analogous to hollow beams, making this method useful for estimating the volume and distribution of bone in cross-section.

Cross-sectional geometry is based on the premise that cortical area is indicative of compressive strength, with inertial values about the diaphysis indicative of torsional and bending strengths (Pearson and Lieberman 2004; Ruff 2008). These variables allow anthropologists to reconstruct general activity levels, particularly mobility differences, in human skeletal populations (Bridges 1989; Fresia et al. 1990; Larsen 1995; Larsen and

Ruff 1990; Ledger et al. 2000; Lovejoy et al. 1976; Ruff 1994; Ruff and Hayes 1983; Stock and Pfeiffer 2001). Therefore, active individuals yield greater diaphysial bending and torsional rigidity in comparison to more passive individuals.

Six variables are required to estimate the overall strength of bone (Biknevicius and Ruff 1992; Burr 1980; Fresia et al. 1990; Ruff 1992; Ruff and Hayes 1983; Runestead et al. 1993). Total area (TA) reflects the relative distribution of bone accumulated during growth. Medullary area (MA) indicates the expanse of endosteal remodeling throughout life. The subtraction of MA from TA yields the cortical area (CA), reflecting bone’s compressive strength. Bending rigidity, represented by the second moment of

8 area (SMA), is reflected along the mediolateral plane (IX) and the anterioposterior plane

(IY); each plane designated as either the one of greatest (Imax) or least (Imin) rigidity. The sum of IX and IY yields bone’s polar SMA, torsional rigidity (J). Once standardized, exhibited increases in J, Imax, and Imin indicate increases in load applied to bone during strenuous activity (Ruff 2000; Ruff and Larsen 1990; Trinkaus et al. 1994).

Greater SMAs are predominately achieved during skeletal growth, with subadults demonstrating an increase in periosteal apposition via modeling and a decrease in endosteal remodeling, or bone turnover (Frost 1997a). In adults, periosteal apposition is minimal while endosteal resorption via remodeling is restrained during physical activity (Frost 1990; Lanyon 1990). Thus, individuals exposed to frequent activity, especially during skeletal development, display greater periosteal apposition and less endosteal resorption than those whom are more passive. Therefore, subperiosteal area (reflected in TA) is largely determined during childhood growth, while endosteal remodeling (reflected in MA) is prevalent throughout life (Ruff et al.

2006).

8 Second moments of area are a measurement of bone’s axial resistance to bending. 40

Nonmechanical factors influencing bone’s macrostructure must be controlled before activity levels may be estimated. Body mass is known to significantly affect long bone’s SMA, wherein heavier individuals will have a greater SMA compared to lighter individuals (Ruff 1994; Ruff et al. 1991; Ruff et al. 1997). Bone length also significantly affects SMAs. As bone lengthens, force generated at the proximal end of a cantilever beam increases (Robling and Stout 2003). Standardizing geometric properties to account for these variables allows for assessing the degree of mechanical influence in bone attributable to physical activity.

2.9.2 Microstructure

Strenuous, repetitive activity also microscopically affects bone. Fatigue damage, evident in cortical bone as microfractures, occurs when strain levels exceed the remodeling threshold. This reduces stiffness, decreasing bone’s capacity to withstand further stress-induced strain (Currey 2002). As mentioned above, the presence of microdamage is presumed to activate osteocyte signals by disrupting the lacunocanalicular network, and thus the mechanotransduction of signals (Burr 2002;

Burr et al. 1997; Burr et al. 1985; Martin 2000; Parfitt 2002; Vashishth et al. 2000;

Verborgt et al. 2000).

Experimentally generated microfractures in the intracortical matrix have shown to initiate new, or secondary, osteon formation (Martin 2003c). Similar results are reported for abnormally stressed rats, which under normal circumstances do not remodel cortical bone (Bentolila et al. 1998). In relation to humans, anthropologists

41 have observed significant correlations between activity levels and bone remodeling in prehistoric populations, by measuring location, density, and size of secondary osteons in cross-sectional profile (Agarwal 2001a; Agarwal 2001b; Agarwal et al. 2000; Burr et al.

1990; Martin and Armelagos 1979; Martin and Armelagos 1985; Mulhern and Van

Gerven 1997; Pfeiffer and Lazenby 1994; Robling and Stout 2003; Stout 1983; Stout and

Lueck 1995). This is based on the premise that if an osteonal remodeling event is initiated by the emergence of microfractures, then the activation frequency of these events should be proportional to the rate of microdamage in individuals, once normalized for any metabolic and/or hormonal effects (Frost 1969; Parfitt 2002; Robling and Stout 2000). Therefore, as microdamage increases, BMU activation also increases

(Martin et al. 1998), maintaining bone’s mechanical competence while extending its fatigue life (Frost 2003; Martin 2003b). Measuring the mean activation frequency, once adjusted for age, should then be indicative of one’s physical activity level, or mechanical loading history. Thus, higher activation frequencies suggest greater physical activity.

Frost (1990) originally proposed an inverse relationship between osteon diameter and the magnitude of applied strains, with larger osteons concentrated within the endosteal envelope where strain levels are lower, and smaller osteons periosteally where strain magnitudes increase. Research conducted by Skedros et al. (2001) support this hypothesis, concluding that in artiodactyl calcanei larger osteons are more prevalent in regions undergoing tension opposed to more heavily strained compressed areas. Additionally, van Oers et al. (2008) experimentally demonstrated that osteoclastic bone resorption is inhibited by osteocyte signals generated via strain,

42 resulting in osteons with smaller diameters in cortical regions subjected to high strain magnitudes. The authors’ propose three explanations for this inverse relationship between loading magnitude and osteon size.

First, the generation of new osteons produces a smaller cutting cone, minimizing the effects of porosity, and thus the overall strength of the intracortical matrix. Second, dense concentrations of smaller osteons absorb energy more efficiently than larger ones as the effects resulting from accumulated microdamage are reduced, with demineralized cement lines serving to limit fracture propagation (O'Brien et al.

2005; Sobelman et al. 2004). Third, smaller osteons in regions of high strain may enhance the resistance towards osteon pullout or debonding of the osteon along the cement line surface (Skedros et al. 2007). Following the conclusions of these studies, regions of bone with an elevated OPD should have osteons with smaller diameters.

Collectively these observations are indicative of a region of bone subjected to higher strain magnitudes.

As noted above, not all remodeling is in response to fatigue damage. Systemic influences, such as hormones, genes, and diet, also affect remodeling rates. Systemic influences affect global, not local (targeted) remodeling. Global factors induce remodeling in all bone, while mechanical influences generate remodeling only in localized loaded regions (Frost 1962; Lanyon 1984). Thus, biomechanical influences on remodeling rates are superimposed on globally influenced bone, such as secondary osteons (Robling and Stout 2003). Systemic influences vary between individuals and populations (Bouvier and Hylander 1997; Frost 1963; Stout 1983; Stout 1986; Stout and

Lueck 1995). This reality requires that remodeling observed in loaded bones be corrected for global systemic influences on bone turnover if osteon population densities

(OPD) are to be used as a measure of physical activity. Consequently remodeling behavior in a dynamically loaded bone (radius) and one that experiences more uniform, static loads (rib) in each individual should be compared (Stout and Lueck 1995). The rib serves as an ideal control since the majority of applied loads result from steady chest respiration, which minimally varies between individuals (Epker and Frost 1964).

Therefore any significant variation in rib turnover between individuals can be attributed to differences in systemic influences (Robling and Stout 2003). For example, previous studies show rib remodeling rates between static and dynamic loads to be equal in exercised pigs (Tommerup et al. 1993), whereas the associated femora display large increases in remodeling rates which presumably are related to direct mechanical loading

(Raab et al. 1991).

Chapter 3: Tendon Biology and Physiology

The human skeleton does not operate in isolation, for it is the muscles and their associated tendons that exert the predominant mechanical forces to which bone adapts.

There are three main functions related to the attachment of tendon to bone, or the enthesis. First, the tendon allows for the muscle to be located away from the joint(s) on which the muscle acts. For instance, the forearm flexors and extensors that operate on the hand and its associated digits have long tendons that cross the wrist, metacarpals, and phalanges so as not to impede joint motion while allowing for a degree of flexibility.

Second, tendons enable the transmission of forces around corners, via retinacula

(collagenous sheaths) and pulley mechanisms (Benjamin et al. 2004; Benjamin and

Ralphs 1998; Currey 2002; Gelberman et al. 1988). Thus, tendons of forearm muscles are bound by retinacula that serve to keep tendons close to the bones they are acting on while allowing them to slide freely within the surrounding tissue matrix.

Additionally, the presence of retinacula prevents the increase of a muscle’s moment arm9 as the joint flexes (Currey 2002; Spoor 1991). The third primary function of tendons is to store energy when they are passively stretched, allowing tendons to

9 The moment arm of a muscle is defined as its mechanical advantage in relation to the rotation center of a joint (Spoor 1991). 45 shorten their length for contractile force, and thus minimizing the energy exerted by the muscle belly itself (Currey 2002).

3.1 Tendon development

Tendons begin developing in utero in conjunction with myogenesis, or muscle growth. The coordination of muscle and tendon cells is imperative to ensure proper tendon placement. Furthermore, the muscle-tendon unit is partially responsible for driving endochondral ossification of long bone diaphyses (Frost 1972). How tendons and their osseous insertions coordinate to achieve long bone growth and proper locales for tendon insertion remains unclear. However, research has demonstrated a unique relationship between bone’s periosteal envelope and the fibrocartilaginous matrix of tendons (detailed in Chapter 4).

Postnatally, development is primarily driven by tensile force magnitudes transmitted from the muscle to the associated bone. In juveniles, growth is achieved via an increase in collagen fibril diameter as transmitted forces are elevated (Jozsa and

Kannus 1997; Scott and Hughes 1986). Additionally, cell volume increases followed by a morphological change from primarily tenoblasts to tenocytes10 (Moore and De Beaux

1987). Once an individual reaches puberty, tendons begin reaching a mature state as they increase in thickness and tensile strength. By age 20, further change in tendon structure is minimal (Jozsa and Kannus 1997), though there appears to be population

10 Tenoblasts are collagen producers predominately found in developing tendons, while tenocytes are more common in mature tendons where their primary role is maintenance and repair (Moore and De Beaux 1987). 46 differences in their ultimate structural thickness in relation to blood cholesterol levels and individual height (Bude et al. 1993; Gattereau et al. 1973; Koivunen-Niemela and

Parkkola 1995; Lehtonen et al. 1981; Liem et al. 1992; Mabuchi 1978; Yuzava et al.

1989).

3.2 Structural properties

Microscopically, tendons consist of sparsely spaced fibroblasts surrounded by an abundance of extracellular matrix (ECM). The ECM accounts for approximately 80% of connective tissue, which is primarily water (70%) with roughly one-third (30%) consisting of collagen, ground substance, and some elastin. Fibroblasts in tendons arrange themselves in longitudinal rows separated by collagen fibers and other organic minerals (Benjamin and Ralphs 1998). Collectively, these cells communicate with one another via gap junctions, allowing for the uninhibited diffusion of various ions and molecules (McNeilly et al. 1996). This may provide the method in which tendons detect and respond to stress/strain accordingly, mimicking lacunocanalicular networks between osteocytes and bone lining cells within bone’s intracortical matrix (Aarden et al. 1994; Cowin and Moss 2001; Lanyon 1993; Marotti 1996; Martin 2000; Martin 2003c;

Skerry et al. 1989).

Within the ECM, dense, parallel collagen fibers provide strength and flexibility to tendons. Similar to bone’s organic matrix, the predominant component of these tissues is type I collagen that is secreted by cells of the fibroblast lineage, tenoblasts and tenocytes, which differentiate from the same mesenchymal stem cells that give origin to

47 osteoblasts (Moore and De Beaux 1987). Collagen is the strongest fibrous protein, providing tendons high tensile strength that surpasses most soft tissues in the human body (Gelberman et al. 1988). This strength is primarily attributable to how tropocollagen, the basic collagen unit, arranges itself. Each tropocollagen molecule is composed of three alpha chains that individually coil in a left-handed helix, and then collectively coil in a right-handed one. This forms a molecule consisting of glycine, praline, and hydroxyproline amino acid sequences, vital to forming proper helixes

(Ramachandran 1963). Additionally, these amino acids aid in cross-linking and staggering collagen molecules, while aggregating them into fibrils. The complex molecular union provides connective tissues with their strength, enabling them to function under stress (Nordin and Frankel 2001). Aggregation of collagenous materials continues as fibrils cooperatively form fibers. Fiber bundles aggregate forming fascicles ensheathed in loose connective tissue known as endotenon. Fascicles unify forming the tendon, which is similarly ensheathed in epitenon (Fig. 3.1). Fascicles and tendons slide across one another, thus their associated sheaths are imperative for reducing friction.

This movement presumably minimizes failure, allowing structural adaptation to both compressive and shearing forces (Benjamin and Ralphs 1998; Clark and Sidles 1990).

Figure 3.1 Schematic diagram of tendon microstructure demonstrating the intricate bundling of collagen fibrils allowing for slippage within their respective bundle sheaths to minimize friction during elongation.

The two remaining components of tendons organic matrix are ground substance and elastin. Ground substance primarily consists of highly aggregated proteoglycans that bind extracellular fluid, essentially forming a gelled matrix (Nordin and Frankel

2001). This amassed material may provide stability to collagenous fibers, contributing to their general strength. The presence of elastin in tendons is minimal, accounting for only about 2% of the matrix, but it provides some flexibility to the structure.

3.3 Mechanical properties

The biomechanical properties of tendons are in many respects analogous to bone, as both are viscoelastic materials. Using a load-elongation curve (Fig. 3.2), tensile deformation occurring in tendons following strain is measurable to the point of tissue avulsion. The connective tissue stretches freely as relaxed wavy collagen fibers

49 straighten, or shear past one another, under applied load (Currey 2002; Hirsch 1974;

Viidik et al. 1982; Woo et al. 1994). Once fibers have elastically stiffened, the tissue linearly progresses with stress and strain proportional to one another. As cyclic loading continues with elongation surpassing the yield point, tissue deformation becomes plastically nonrecoverable. Here, fiber bundles begin to unpredictably fail as the tendon deforms, eventually causing avulsion.

Figure 3.2 Stress/strain curve for tendon tested to failure. (A) Toe region where wavy collagen fibers begin straightening under initial stress. (B) Linear region where tissue deformation is proportionate to applied load. (C) Yield point where subsequent loading results in small force reductions (dips) as collagen fibers begin failing. (D) Point of maximum loading, followed by rapid failure and avulsion.

Tendons have very high tensile strength with a modulus of around 200 megapascals (MPa) (Thomopoulos et al. 2011). However, their compressive strength is much lower as they lose shape and collapse. This is attributable to immeasurable fibril

50 beams having small second moments of area whereby shear stiffness is low (Currey

2002). In comparison, bone has considerably more shear stiffness and a tensile strength on the magnitude of approximately 20 gigapascals (GPa) (Hems and Tillmann 2000;

Thomopoulos et al. 2011). However, tendon fibers have an elastic modulus ten times smaller than that of bone (Hems and Tillmann 2000). This variability between soft and hard tissues requires a complex structure, the enthesis, which both balances differing elastic moduli and secures tendons to bone.

Metabolic turnover in tendons is very slow in comparison to their associated muscle body and bone. Tendons are poorly vascularized and subsequently have limited nutrient circulation throughout their collagenous matrix (Kannus et al. 1992). Despite these complications, experimental animal studies have demonstrated an increase in their size, collagen content, and tensile strength given sufficient time and continual training (Archambault et al. 1995; Maffulli and King 1992; Tipton et al. 1975; Viidik 1969;

Woo et al. 1982; Woo et al. 1980). In addition to these dynamic cellular responses to variable exercise, tendons are also capable of repair following injury (Benjamin and

Ralphs 1998; Bloebaum and Kopp 2004; Frank et al. 1988; Woo et al. 1988). This behavior is comparable to mechanotransduction in bone, wherein tenocytes sense and respond to changes in mechanical load, making any necessary microstructural repairs in the tissue.

In contrast, the disuse of muscles following limb immobilization has some, albeit slow, atrophic effect in tendons (Kannus et al. 1992). Observations include a decrease in tensile strength, elastic stiffness, and total weight following limb immobilization (Amiel

51 et al. 1982; Tipton et al. 1975; Woo et al. 1982). At the microscopic level collagen fibers become thinner and increasingly disorganized in response to infrequent tendon use

(Jozsa 1984). Similar changes are observed in relation to age, with older individuals demonstrating decreased tensile strength as tenocytes and collagen fibers degenerate, while lipids and calcium deposits accumulate within the tissue matrix (Kannus and Jozsa

1991).

Chapter 4: The Enthesis

An enthesis is the interface where tendon meets bone. Entheses, in engineering terms, are sites of stress concentration at the hard and soft tissue junction where mechanical properties differ (Benjamin et al. 2002; Benjamin et al. 2006). Opposing elastic moduli balance tensile loads, dissipating stress away from the osteotendinous interface and into bone or tendon or both (Benjamin et al. 2002; Biermann 1957; Knese and Biermann 1958). In addition to force transmission, another crucial role of entheses is to anchor tendons, enabling static and dynamic load resistance. To achieve this, tendon fibers splay, forming a plexus at the insertion point that provides a firm anchor, equally resistive to insertion angle change in response to variable directional loads occurring during joint movement (Benjamin et al. 2006; Thomopoulos et al. 2006). This enthesial design is commonly related to that of tree roots, noting that both plants and tendons require a relatively small proportion of material for anchorage (Benjamin et al.

2006; Ennos et al. 1993; Suzuki et al. 2005). Often entheses intermingle with one another (e.g. the insertion of vastus lateralis, vastus intermedius, adductor magnus, and adductor brevis mm. along the lateral lip of the linea aspera) overlapping attachment sites for greater tendon security (Benjamin et al. 2004). Additionally, Knese and

Biermann (1958) have proposed that the splaying of entheses is not only vital for

53 anchorage, but also in limiting the degree to which a tendon stretches. As tendons stretch they narrow, increasing their vulnerability to rupture.

Entheses define two categorical units –fibrous and fibrocartilaginous- depending on tissue type present at the osteotendinous junction. Fibrocartilaginous entheses are only present on the epiphyseal or apophyseal long bone ends, whereas fibrous entheses attach to long bone diaphyses. This distinction between enthesis type and location corresponds to bone origin, either intramembranous or endochondral ossification

(Biermann 1957; Doschak et al. 2005; Francois et al. 2001; Knese and Biermann 1958).

Entheses rooted in thick layers of cortical bone are fibrous, ossifying intramebranously, while those attaching to thin cortical layers are fibrocartilaginous, ossifying endochondrally. Benjamin et al. (2002) suggest this may relate to nutrient foramen access. However, our understanding of early postnatal enthesial development is limited.

Research on osteotendinous development in animal models has yielded some information on the presence of early enthesial signatures and the intricate relationship between the contrasting tissues during long bone maturity. For example, Hurov (1986) described the periosteal surface of diaphysial entheses in fetal rabbit long bones to be coarse-fibered, compositely falling between fibrocartilage and lamellar bone.

Additionally, in their research of intermediate filament presence in human enthesial development, Abe et al. (2010) found both the proteins vimentin and desmin to potentially play significant roles in the remodeling of the periosteal surface as mechanical strain is applied both in utero and postnatally to the emerging skeletal

54 scaffold. The periosteum has a separate pathway for growth compared to the associated bone. As the bone elongates at the epiphyseal plates, the periosteum interstially expands in conjunction with the underlying bone (Muhl and Gedak 1986). As this envelope migrates, so to do the attached tendons, forming a complex union that occurs once the emerging muscle tendons seek out nearby ossifying bone during the later fetal stages.

4.1 Fibrous attachments

Fibrous entheses, characterized by ‘fleshy fibers,’ attach either directly (Fig. 4.1) to bone or indirectly via the periosteum (Fig. 4.2) (Benjamin et al. 2002; Benjamin et al.

2006; Hems and Tillmann 2000). These entheses are associated with large, powerful muscle bodies, such as the quadriceps group and deltoideus m. (Biermann 1957).

Periosteal attachments dissipate stress over a large expanse of bone, limiting their ability to stretch (Benjamin et al. 2002; Biermann 1957). Fibrous entheses that lack tendons typically insert dense connective tissue fibers directly into the periosteum, equally allowing stress transmission over a large area. With age, many periosteal fibrous entheses become bony attachments as the periosteum disintegrates over time

(Benjamin et al. 2002; Matyas et al. 1990). Mechanical strain transmitted from a tendon to the outer periosteal envelope of bone may be responsible for the morphological indicators used in behavioral reconstructions, such as pit features forming via compressive forces or small protuberances or both developing via tensile forces (Rogers

55 et al. 1987). However, there is little evidence to support this assumption clinically

(Kumai and Benjamin 2002).

Figure 4.1 Fibrous bony insertion of temporal muscle along inferior temporal line. Note the perforating fibers (arrows) embedded within the interstitial lamellae, but not crossing the cement line of the secondary osteon. Adapted from Hems and Tillmann (2000).

Figure 4.2 Fibrous periosteal insertion of hamstring muscle to the proximal tibia of a rat leg. Note the fleshy fibers of muscle (M) attaching to the outer periosteum (O) and meshing with the osteogenic layer of periosteum (I). Adapted from Benjamin et al. (2002).

4.2 Fibrocartilaginous attachments

Fibrocartilaginous entheses typically attach tendons to small, localized regions of bone lacking a thick cortical layer and periosteum. This allows for more precise limb movements about the joint and may potentially dissipate stress as the thin cortical shell deforms under loading (Benjamin et al. 2002; Benjamin et al. 2006). All of these entheses indirectly insert into bone through a structure consisting of four distinct zones that progressively shift between structural materials (Fig. 4.3) (Benjamin et al. 2002;

Benjamin et al. 2006; Thomopoulos et al. 2011; Thomopoulos et al. 2006). Moving distally towards the insertion site, the first zone is a dense fibrous connective tissue

57 containing type I collagen and proteoglycans, forming the tendon proper. The second zone is uncalcified fibrocartilage (UF), containing multiple collagen types, with types II and III most prevalent. The third zone contains calcified fibrocartilage (CF), which is predominantly type II collagen. This zone serves to anchor tendon to bone, forming a highly irregular junction between collagen fibers and lamellae (Benjamin and Ralphs

1998; Clark and Stechschulte 1998). Cartilage that anchors tendons during endochondral ossification remains and calcifies via metaplasia; thus CF is the functional equivalent of collagenous fibers present in fibrous entheses that calcify within interstitial bone (Benjamin et al. 2006; Haines and Mohuiddin 1968; Ishikawa et al.

2001; Matyas et al. 1990). Separating the UF and CF zones is an avascular calcification front, or tidemark (TM), that serves as a boundary between soft and hard tissues

(Benjamin et al. 1986; Benjamin et al. 2002; Benjamin et al. 2006). Mineralization at the

TM produces a straight, flat surface, minimizing damage as soft tissue insertion angles change from their natural perpendicular approach during movement (Benjamin et al.

1986; Benjamin et al. 2002; Evans et al. 1990; Thomopoulos et al. 2006). Therefore, the

TM reduces tendon wear and tear by promoting a gradual bend in collagen, reducing fiber splay within bone’s immediate vicinity (Benjamin et al. 1986; Benjamin and Ralphs

1998; Evans et al. 1990; Schneider 1956). Lastly, the fourth zone is bone, containing mostly type I collagen.

Figure 4.3 Tracing of entire fibrocartilaginous insertion of biceps brachii m. onto the radial tuberosity. Fibrocartilaginous zones are labeled as the following: compressed fibrocartilage (CFC), uncalcified fibrocartilage (UF), tidemark (TM), and calcified fibrocartilage (CF) embedded in the intracortical bone matrix (B). Adapted from Benjamin et al. (1992).

It appears that a gradual shift from soft to hard tissue may enable efficient load transfer, and reduce stress concentrations (Benjamin et al. 2002; Benjamin et al. 2006;

Thomopoulos et al. 2011; Thomopoulos et al. 2003); essentially balancing tensile force between two materials of widely varying elasticity (Hems and Tillmann 2000). Doschak and Zernicke (2005) suggest these four regions correspond to the transitional zones of increased stiffness outlined on stress/strain curves for tendon. Additionally, tendon failure studies consistently demonstrate the biomechanical efficiency of fibrocartilaginous entheses, with avulsion fractures often occurring within adjacent

59 subchondral bone (Chu et al. 2003; Gao et al. 1996; Lam et al. 1995; Lieber et al. 1992;

Thomopoulos et al. 2003). There also may be an association between subchondral avulsion fractures and accumulated microdamage adjacent to entheses (Benjamin et al.

2002). For example, in a study administering bisphosphonates for osteoporosis treatment, a high incidence of avulsion fractures along the long vertebral spines where soft tissue attaches was noted (Hirano et al. 2000). Benjamin et al. (2004) propose a reduction in tendon rupture where an ‘enthesis organ’ is present. They define an enthesis organ as an interface where a subtendinous bursa is present for friction reduction as the insertion angle of collagen fibers changes during joint movement. This allows direct tendon-bone contact (pulley mechanisms), dissipating stress away from the enthesis (Benjamin et al. 2002; Benjamin et al. 2006), similar to mechanics involved in fibrous attachments.

4.3 Osteologic enthesial remnants

Despite the biomechanical efficiency of entheses in dissipating stress away from the tendon insertion point, wear and tear is inevitable. In dry skeletal material, tendon attachment sites are visible along external bone surfaces. Tissue type present at insertion defines the morphology of an enthesis. Bony fibrous attachments along the diaphyses leave rugous landmarks characterized as raised ridges and roughened bone

(Fig. 4.4). In contrast, periosteal fibrous entheses appear osteologically as smooth markings (Hems and Tillmann 2000). Fibrocartilaginous attachments are also smooth, often slightly depressed and better circumscribed (Fig. 4.5), resulting from the TM

60 boundary separating UF from penetrating CF (Benjamin et al. 2002; Benjamin et al.

2006).

Figure 4.4 Pronator teres m. insertion along the lateral diaphysis of the radius. This is an example of moderate fibrous enthesis development.

Figure 4.5 Radial tuberosity. This is a fibrocartilaginous enthesis with a thin cortical shell that presumably flexes under strain generated via biceps brachii m. contraction.

Hawkey and Merbs (1995) fail to distinguish between tissue type in their ordinal ranking method of MSM expression (Fig 4.6). This is a fundamental flaw considering the histological and biomechanical differences between fibrous and fibrocartilaginous entheses noted above. In their method, they collectively characterize enthesial morphology as robust, pitted, or ossified. In their method ranking varying degrees of

62 enthesial expression, it is argued that robust markers, or rugged markings (e.g. sharp ridges and crests), are produced through normal activity, resulting from an increase in attachment area to avoid tendon avulsion. Stress lesions, or pitting, are stated to result from regular microtrauma at the insertion site that induce periosteal resorption and/or necrosis due to an interruption in the blood supply as tendon fibers avulse and reattach.

Lastly, exostosis is attributed to macrotrauma, or complete tendon avulsion, that results in the ossification of tendon tissue during healing. Although this method does not account for varying types of enthesial morphology, it remains the most employed method by bioarchaeologists conducting behavioral reconstructions. Many have made small revisions to the methodology, such as removing indicators of exostosis demonstrating less frequently occurring tendon avulsions, or combining the ranked scores of robusticity and pitting to calculate total muscle use (Molnar 2006; Weiss

2007). Additionally, Weiss (2003) noted that muscle groups work in tandem when performing activities, and thus enthesial scores should be aggregated to enhance statistical predictability and subsequently assess entheses collectively as biological units.

However, the core statistical and observational limitations with the method remain, since populational variation among enthesial insertions continues to be accounted for using serial ranking methodology.

Figure 4.6 Serial ranking of robusticity scores of radial tuberosity where biceps brachii m. inserts. Faint demonstrates a slight indentation with no definition of the surrounding periosteal margins. Moderate demonstrates roughening of the insertion site with a defined periosteal margin. Strong demonstrates a deep indentation with defined periosteal margins. Adapted from Hawkey (1998).

The 2008 MSM Workshop in Portugal, following the lead of earlier research conducted by Havelkova and Villotte (2007), corrected for the lack of distinction between enthesis type in Hawkey and Merb’s method, with the development of methodology focused upon fibrocartilaginous entheses. Since this publication, Villotte et al. (2010a; 2010b) has continued to employ and revise this method, ultimately reducing the inter and intra observer error. Their recording technique distinguishes between varying expanses of tendon fiber insertion along the attachment site, along with morphological signatures found within the distinct smooth attachment surface of fibrocartilaginous entheses.

4.4 Entheses and activity-related studies

Anthropologists and clinicians often presume morphological variability of long bone entheses result from strenuous, habitual activity, where muscle contractions are frequently recruited for limb movement (Benjamin et al. 2002; Benjamin et al. 2006;

Chapman 1997; Cook and Dougherty 2001; Eshed et al. 2004; Hawkey 1988; Hawkey and Merbs 1995; Kennedy 1983; Lai and Lovell 1992; Nagy 1998; Peterson 1998; Steen and Lane 1998; Stirland 1998). However, the relationship between soft and hard tissues, and its effect on enthesis morphology, lacks sufficient analysis. Activity reconstructions using entheses profiles are frequently conducted using subjective methods of macroscopic analysis that are regularly questioned as to their relevance and accuracy in assessing enthesis morphology (Bryant and Seymour 1990; Knusel 2002;

Robb 1998; Wilczak 1998). Further concerns arise with the regular failure to account for potential nuances that may affect entheses response to applied load, such as body mass, age, genetic precursors, skeletal maturity, and muscle contractile rates (Stirland

1998; Wilczak 1998; Zumwalt 2006). Moreover, previous studies frequently lack explicit biological justification for why particular parameters are initially chosen for profile assessment (Robb 1998; Wilczak 1998; Zumwalt 2005; Zumwalt 2006).

That larger, more active muscles induce skeletal hypertrophy in relation to tendon insertion sites appears to be a reasonable statement. Therefore, it is suggested that enlarged entheses are advantageous, allowing stress applied to the periosteal surface to be proportional within each square unit of surface area, ultimately reducing the effect of contractile forces at the osteotendinous junction (Biewener 1992; Zumwalt

2006). This may occur as blood flow increases within the periosteum in response to forceful muscle contractions, initiating the proliferation of bone cells, and ultimately increasing skeletal hypertrophy (Chamay and Tschantz 1972; Herring 1994; Weiss 2003;

Woo et al. 1981; Zumwalt 2006). Support for this hypothesis is often drawn from Dysart et al., (1989), wherein denervation of the deltoideus m. within a sample rat population is followed by bone resorption at the associated tendon insertion site (deltoid tuberosity).

This is an example of subnormal loading, or disuse, which occurs when an applied load is reduced (Frost 1987; Martin 2003c). However, remodeling initiated due to the loss of muscle innervation may be more a result of decreased muscle weight via atrophy rather than diminished contractile force. More recent studies using both myostatin-null and dystrophin-null mice, wherein muscle growth continues unregulated, challenge the validity of this relationship between contractile forces and enthesial development

(Hamrick et al. 2000; Montgomery et al. 2005). Both studies found enthesis rugosity to correlate with an increase in muscle size, and subsequently body mass, and thus not necessarily dependent on muscle strength. These findings suggest enthesial development is more attributable to tendon fiber volume rather than tensile forces

(Elkasrawy and Hamrick 2010). Therefore, differences in activity patterns among males and females, which are often reported in enthesial-based studies, may be more attributable to sexually dimorphic morphological dissimilarities, rather than behavior related to divisions of labor.

Additionally, if one considers the biomechanical principles of entheses and their role in balancing variable elastic moduli, it would appear this interface between soft and

66 hard tissues is reasonably protected. Therefore, stress magnitudes at the osteotendinous junction resulting from habitual activity may not exceed remodeling thresholds, and thus not require additional morphological changes within the adjacent periosteum. In fact, according to Frost’s (1987; 2003) mechanostat, if entheses were to significantly respond to applied strains via increased periosteal remodeling, then mechanical loads would have to be outside the realm of normal activity levels and so infrequent as to not shift the threshold range to accommodate the new strain levels.

This begs the fundamental question: Is rugous enthesial morphology indicative of accumulated microtrauma resulting from habitual activity, or is it more reflective of sporadic strenuous mechanical loads that occasionally exceed remodeling thresholds inducing a more drastic remodeling response?

Similar to bone remodeling thresholds, age has been shown to compound the concerns associated with uncovering enthesis etiology (Hawkey and Merbs 1995; Weiss

2003; Zumwalt 2006). If normal daily activity falls within an individual’s predetermined remodeling threshold, and thus serves to maintain bone’s mechanical competence, then the degree of insertion site development may be more indicative of periosteal degradation following regular stress accumulated over one’s lifetime via normal long bone movement rather than elevated strains generated through physically taxing exercises. It is well known that subadults demonstrate more periosteal apposition during skeletal development compared to that of adults who have achieved skeletal maturity (Frost 1997b; Ruff et al. 2006). However, as stress accumulates intracortically in long bones via physical activity, some bone modeling may occur with new bone

67 formation along the periosteal envelope in conjunction with bone resorption endosteally. In this event bone apposition is minimal, and thus significant periosteal changes via high strain activity would not be expected. This is consistent with Hawkey and Merbs (1995) observation that in their Thule Eskimo skeletal collection enthesial insertions become more rugous with age, yet statistically these differences are insignificant.

Conversely, a number of studies have found age to significantly correlate with enthesis size (Belcastro et al. 2006; Cardoso and Henderson 2010; Weiss 2003; Weiss

2007), suggesting that morphological development may be partially indicative of life- long periosteal wear and tear following routine activity. However, this conclusion is confounded by the issue of assessing age, since most of these studies consisted of archaeologically excavated individuals of imprecisely known age and sex. In the interest of discovering etiological markers of enthesial development, initial studies should consist of skeletal populations with known demographics (e.g., recorded cemetery plots or donated medical cadavers) in order to control these factors and potentially discover age-related correlations applicable in use with archaeologically assessed populations.

Further complications in interpreting activity patterns from osteological markers arise when considering the affects systemic influences have on bone remodeling. The role of genetic factors in enthesial development is poorly understood. Following chapter 2, Frost (2003) suggests that genetics predetermine the baseline conditions in bone in utero. These baseline conditions are predominately driven by Hox gene expression, which current research postulates is responsible for canalized limb

68 patterning, basic neuromuscular and physiologic anatomy, and the biologic machinery necessary for increasing bone strength following birth (Capdevila and Belmonte 2001;

Chiu and Hamrick 2002; Shubin et al. 1997). Lovejoy (2002) also suggests that genetic precursors play a more significant role than environmental factors in the primary development of morphological indicators on bone. Earlier prenatal observations support these findings with the appearance of distinguishable hypotrochanteric fossa on the femoral diaphysis where a portion of the gluteus maximus m. inserts (Hrdlicka

1934). In fact, Enlow (1990) noted that enthesial development is insignificant during adolescence, suggesting that mechanical strain during growth and development merely provides threshold levels for bone growth. Therefore, threshold levels set during adolescence likely preserve throughout adult life, with mechanical strain maintaining bone strength; thus the focus is on bone retention not deposition (Lovejoy et al. 2003).

Hypothetically, these observations account for deposition and resorption reduction observed in adult long bones when exposed to increased strain levels, since mechanical mechanisms are bound to predetermined threshold levels set during initial growth and development. Accordingly, proponents of this position suggest that genetics dominate long bone morphogenesis, and that environmental factors have little impact on skeletal development.

Regardless of whether mechanical loading or genetic regulation is predominately responsible for bone development and maintenance, it is apparent that a complex interaction exists between these two factors that cannot be ignored when attributing morphological signatures to physical activity. Especially since it is unlikely that

69 individuals or populations osteologically respond to similar physical activities in the same manner. Of equal concern is the influence hormones have on bone remodeling in localized regions associated with tendon insertion sites, which is minimally researched and thus unclear.

Recent research has sought to resolve some of these uncertainties in enthesial interpretations using objective, metrically quantified insertion profile data. Weiss

(2003) correlated aggregated ranked scores of enthesial expression from seven muscles in the upper limbs of 91 Native British Columbians with body mass, age, and long bone robusticity (composite of cross-sectional geometric properties). She found all three variables to significantly correlate with insertion development; age being the best predictor. These findings suggest muscle insertion development is intricately linked with age, skeletal build, and overall body mass. Schlecht’s (2004; 2008) analysis of an

Anglo-Saxon and Norman cemetery population revealed a significant correlation between the length and width of the linea aspera and associated femoral geometric properties when controlling for age and body mass. Additionally, a recent study conducted by Weiss (2012) found that among a pre-European (2180-250 BP) contact population in California, sex differences interpreted from standardized aggregate MSM scores were more indicative of variable body mass than perceived role differences.

Zumwalt (2006) has conducted the most direct investigation exploring the presumed relationship between enthesial development and normal physical activity.

Using 20 adult female sheep at least four years of age, she trained 10 to run on treadmills one hour a day, five days a week for 90 days. The 10 remaining sheep were

70 used as a control and were only exposed to normal enclosure activity. At the end of the experiment, all 20 sheep were euthanized and six entheses of the fore and hind limbs were dissected. Using a sophisticated method of capturing three-dimensional enthesis profiles followed by fractal analysis quantification, Zumwalt found little difference in insertion site development within the exercised population and the control group. This suggests that within her population of adult sheep enthesial morphology is not indicative of muscle size or activity. However, more conclusive evidence may be found in future experiments involving skeletal development amongst growing subadults, wherein the macrostructural properties of bone are much more malleable (Ruff et al.

2006).

In light of the variable results derived from these pioneering studies seeking to find direct correlations between tendon insertion sites and activity, incorporation of enthesial data in activity-related studies should be used cautiously, if at all, especially since it remains unknown if enthesial morphology significantly remodels following the cessation of skeletal growth.

Chapter 5: Materials and Methods

5.1 Materials

5.1.1 Human radius

For this study, the radius was used as a straightforward model for assessing remodeling activity levels in association with osseous enthesial landmarks along the outer periosteum. The human radius is well suited for this investigation, as it plays no weight-bearing role in normal locomotive activities, and only provides tendon insertion points for a few muscles within the forearm compartment, allowing fluid rotation of the long bone during pronation. Additionally, the human radius and its contribution to forearm dexterity is paramount in understanding bipedal advantages of upper limb use throughout hominin evolution.

Strains applied to the forearm are only partially transmitted through the radial diaphysis. The ligamentous tissues at the proximal and distal radioulnar joints along with the centrally aligned interosseous ligament, serve to share axial loads with the ulna to form a single reciprocal unit of force distribution (Shaaban et al. 2006). Experiments have demonstrated that the radius bears the brunt of axial load transmission throughout its rotation arc, with estimates ranging from 60-80% (Birkbeck et al. 1997;

Palmer and Werner 1984). However, the minimally loaded static ulna has a more prominent role in anchoring the forearm muscles, and thus for biomechanical clarity is omitted from this study.

5.1.2 Population selection

Individuals selected for this study were selected from more than 300 human cadavers donated to The Ohio State University Medical School over a 4-year time span for use in gross anatomy instruction. Cadaveric material, rather than an archaeological sample, was employed to meet various control criteria. Cadavers by nature have intact soft tissues, allowing for well-defined specimen harvesting at the exact point of enthesial insertion. Additionally the accompanying documentation of individuals allows for known age, sex, and cause-of-death; minimizing estimation errors in constructing a biological profile from skeletal tissue and reducing the inclusion of pathologies and subsequent medical treatments that may impact normal bone turnover rates. Lastly, microscopic investigation is unhampered by preservation concerns and invasively destructive methodology.

5.1.3 Population sample demographics

The chronological age of donated cadavers is skewed towards the latter years of the spectrum, with many individuals falling above 60 years of age. Therefore, a small sample of 14 individuals (Table 5.1), evenly split between males and females, was slowly compiled in order to avoid an analysis heavily biased towards post-menopausal and

73 potentially osteopenic individuals. Ultimately, an age range of 21-81 years was achieved, ideal for assessing the earlier findings of a significant relationship between age and adult enthesial development (Belcastro et al. 2006; Cardoso and Henderson

2010; Weiss 2003; Weiss 2007).

Cadaver ID Sex Age (years) Cause of Death A F 61 Thyroid cancer B M 73 Lung cancer C M 49 Metastatic melanoma D F 57 Metastatic melanoma E M 57 Lung cancer F F 58 Chronic heart failure G F 81 Chronic heart failure H F 43 Pancreatic cancer Acute intracranial I F 49 hemorrhage Arteriosclerotic J F 63 cardiovascular disease K M 51 Lung cancer L M 42 Liver cirrhosis M M 29 Suicide (gun) N M 21 Suicide (hanging) Table 5.1 Sample data for 14 individuals included in study.

5.1.4 Specimen selection

Bone specimens approximately 3cm in length were removed from both the left and right radii of each individual using a Stryker autopsy saw. Notching the proximal surface of each specimen with the saw and placing them in labeled bags maintained the orientation of the removed sections. For each radius, removal of bone sections was

74 performed at points along the diaphysis where the primary muscles involved in pronation and supination of the forearm insert. From proximal to distal this includes the biceps brachii, the supinator, the pronator teres, and the pronator quadratus muscles. These four muscles encompass the primary enthesial insertions along the radial diaphysis, and work in tandem to rotate the forearm during both extension and flexion.

5.1.5 Muscle actions

Each of the muscles that primarily perform radial rotation has specific actions to enable pronation and supination at various angles of forearm flexion (Fig. 5.1). The supinators of the forearm consist of the biceps brachii and supinator muscles, which span the elbow joint and insert proximally along the radial diaphysis. In contrast, the aptly named pronator teres and pronator quadratus muscles insert about the midshaft and distal diaphysis respectively, and are the primary performers of forearm pronation.

The biceps brachii m. has two heads originating from the supraglenoid tubercle and coracoid process of the scapula, that collectively insert into the proximally located radial tuberosity. Since this muscle crosses a hinge joint (elbow), it is primarily involved in flexion of the forearm, however in the flexed state is also a powerful supinator.

Acting in conjunction with the biceps brachii m., and predominately solo when the forearm is extended, is the proximally located supinator m. The supinator m. originates from the lateral humeral epicondyle, the annular and radial ligaments, and the supinator crest of the ulna. This forms a muscle belly with multiple planes of fibers

75 positioned both superficial and deep, that collectively insert along the lateral boundary of the radial tuberosity and the oblique line of the radius as far distally as the lateral insertion of pronator teres. This convergent shape not only enables forearm supination at all angles of flexion, but the multiple fiber origins provide joint stability by securing the radial head during limb movement.

Though one of the pronator muscles crosses the elbow joint neither is impacted by the angle of forearm flexion. The pronator teres m. originates proximally from the medial humeral epicondyle and medial edge of the ulnar coronoid process, inserting along the lateral radial diaphysis approximately at the midshaft and apex of radial curvature, just below the most distal insertion of the supinator m. This muscle is responsible for rotation at the proximal radioulnar joint, and carries the majority of radial weight during axial movement. Pronator quadratus is a much smaller, square- shaped muscle, which lies upon the distal anterior surfaces of the ulna and radius. The radial insertion assists in pronation of the radius, while stabilizing the distal radioulnar joint by binding the two bones together.

Figure 5.1 Illustration identifying the four muscle bodies predominately responsible for the pronation and supination of the forearm, and thus rotation of the radius upon the ulna. Adapted from Davis (1913).

5.2 Methods

5.2.1 Specimen preparation

Preparation of the specimens was done at The Ohio State University

Bioarchaeology Research Laboratory, where all large-scale equipment needed for this study is stored. Following transportation from the Medical School morgue to the

Bioarchaeology Research Laboratory, kitchen string was tied around the specimens and an identification tag was affixed to each transverse bone segment to clearly label them.

The labeled sections were then simmered in a diluted mild detergent within an enclosed fume ventilation hood until completely macerated, approximately 3-4 hours. After rinsing the specimens and allowing them to fully dry, they were degreased in acetone for 24 hours. The clean bone sections were then anatomically oriented (i.e., anteriomedial and posteriolateral axes), and placed in disposable embedding molds, clearly labeling the two principal axes upon the outer surface of the plastic container.

The sections were then vacuum embedded with Buehler Epo-Thin low viscosity epoxy

(Buehler Ltd.) and allowed to harden for 48 hours. The resulting blocks were removed from the molds and the block surfaces were relabeled with the two orienting axes.

Finished blocks were transversely cut at the center of the region of interest using a Buehler IsoMet 1000 precision saw (Buehler Ltd.) with a diamond wafering blade.

Following this, the proximal halves of the original blocks were mounted to petrographic microscope slides using a few drops of the Epo-thin epoxy, maintaining the same medium used for embedding to ensure voids within the marrow cavity were completely

78 filled. After the mounted blocks dried for at least 24 hours, the diamond wafering blade was used to remove the majority of the block material from the mounted slides, leaving approximately 200-300 µm of material affixed to the slide.

The resulting thick sections were then ground to a thickness of 60-80 µm with a

Buehler MetaServ 2000 grinder/polisher (Buehler Ltd.) to achieve a translucency appropriate for transmitted-light microscopy. Specimens were cleared in xylene and a protective cover glass was affixed using Permount, a toluene based medium. The anatomical orientations were marked directly on the slide to assure recognition of the correct axes, and subsequently the precise region tendons of interest insert.

In total this process was performed for all three bone sections from each radius.

Thus the entire sample comprises six sections per individual, three from both the left and right radii, and totals 84 slides for analysis.

5.2.2 Histomorphometric field sampling

Finished slides were read using an Olympus BX51 transmitted light microscope equipped with a rotatable stage and polarizing light (Olympus America, Inc., Center

Valley, PA), at magnifications ranging between 100x and 400x.

Each of the three radial cross-sections per individual were sampled in a manner that accounts for variability in remodeling and the dissipation of strain. Mediolateral and anterioposterior planes about the centroid, along with their 45° intersects, were drawn onto the cover glass overlying the section using a fine point permanent marker,

79 forming a starburst pattern that encompasses 8 separate sampling rays that account for the entire cross-section (Fig. 5.2).

Figure 5.2 Microscopic image of radial midshaft cross-section overlaid with the 8 specified zones (rays) analyzed. Micrograph viewed using red quartz cross-polarized filter (hilfsobject). Magnification 40x.

The superimposed axes were then identified under the microscope, and signified regions for histomorphometric sampling. Using a Mertz (1967) eyepiece reticule (Fig.

5.3), one column extending from the periosteum to the endosteum is read at each of the eight marked rays. The entire intracortical matrix along each defined ray was read at a magnification of 100x, quantifying the total intact and fragmentary secondary osteons.

Figure 5.3 Mertz grid as seen through a microscope eyepiece. The grid consists of 36 transecting points. The point count method is based on the number of superimposed test points, or hits, that fall within the cortical matrix. Micrograph viewed using red quartz cross-polarized filter (hilfsobject). Magnification 100x.

For osteon size, each secondary osteon within the quantified zones consisting of an intact reversal cement line, and a near circular canal, which minimizes the chance of measuring a tangentially sectioned osteon, was photomicrographed at 400x using a mounted Insight QE live image camera. Using ImageJ freeware (NIH), photomicrographs were digitally displayed and the reversal cement line of each osteon was hand traced for automated calculation of osteon area. A high magnification of 400x was chosen to reduce potential error when outlining the selected osteon, since deviations from the actual cement line are miniscule at this level. Captured photomicrographs taken of each

81 intact osteon along the sampled rays were then stored in a database to assist in the analysis of microscopic features quantified in this study.

5.2.2.1 Observed and derived variables for microstructural analysis

From each of the eight zones, or rays, within a radial cross-section the following variables were quantified:

1) Total bone area sampled (Sa.Ar): Using a Mertz grid and Parfitt’s (1983) point count

method (see Fig. 5.3), the total area of bone sampled was quantified (mm2).

2) Total number of intact secondary osteons (N.On): Intact secondary osteons are

those Haversian systems exhibiting a Haversian canal that is at least 90% complete.

3) Total number of fragmentary secondary osteons (N.On.Fg): Fragmentary secondary

osteons are those Haversian systems exhibiting only a fraction of the original

lamellar area and more than 10% removal of the Haversian canal via subsequent

remodeling events.

4) Mean intact osteonal area (On.Ar): Mean area of secondary osteons exhibiting an

intact cement line and a single, uninterrupted Haversian canal (mm2).

Using the first three observed variables from above, the following derived variable was calculated:

1) Osteon population density (OPD): The total number of intact and fragmentary

secondary osteons per mm2. The calculation is made by summing the intact and

fragmentary counts and then dividing by the total bone area sampled:

OPD = (N.On + N.On.Fg)/Sa.Ar

5.2.3 Data analysis

Data analysis was conducted using visual observations and Minitab 16.1.1 statistical software. Prior to analysis, a random subset of the total OPD and osteon area were independently analyzed for inter-observer error. Collectively, the error of variance was approximately 5%, deeming the methodology employed reliable. The demarcation of intact and fragmentary osteons was the most subjective. This inconsistency in delineating between intact osteons and fragments is not a major concern, since both of these morphological features are ultimately summed to generate OPD. Thus misidentification of intact osteons versus fragments, and vice versa, should have little effect since the total numbers of each are summed together prior to applying the OPD algorithm.

Other preliminary investigations of the data included tests for normality and asymmetry between the left and right radii. In terms of normality, much of the data was skewed either positively or negatively and was leptokurtotic. Therefore, the entire dataset was logarithmically transformed to achieve a near normal distribution with

83 some platykurtosis resulting. The transformed data was then analyzed using Pearson correlations to assess asymmetric differences between the left and right radii at the respective region of interests. Neither OPD or osteonal area significantly correlated (p <

0.05), thus the left and right radii for each individual were analyzed separately.

Left and right cross-sectional comparisons of OPD and osteonal area were conducted using a nonparametric mean square successive difference test. This test evaluates the randomness of a series of continuous scores, provided the data is derived from a normal distribution. Therefore, both OPD and osteonal scores are tested individually for randomness in all cross-sections. If these variables are directly influenced by strain magnitude, then a nonrandom pattern should be observed between individual scores within a given section.

To determine whether rays (e.g., anterior, anteriomedial, medial) with high OPD coincide with a small osteon diameter, serial distributions of the scores for each variable were charted by ray for each respective cross-section derived from the population. The data were then visually compared, assessing whether patterns emerge in the concentration of considerable strain-related scores along particular cross-sectional rays.

To assess the significance of association between OPD and osteon size for all eight rays, the data for all three cross-sections was tested using ANOVA and angular-linear correlations. Angular-linear correlations assess the relationship between variables on an angular or circular scale (rays distributed about the cross-section) and those on a linear scale (OPD and On.Ar). Significance of r2 correlation coefficients is based on the

2 chi-square critical value for two degrees of freedom and 95% confidence (Χ 2, 0.05 =

5.991). If the scores are significant (p < 0.05) and fall along similar rays, then a strong relationship between strain-related variables exists, with higher OPD scores associated with smaller osteons.

Both of these variables are a reflection of strain magnitude generated through muscle contractile forces. Thus, they should both be concentrated along the same rays, specifically those in association with enthesial insertions, between the respective cross- sections of all 14 individuals.

Chapter 6: Results

The results of all observations and statistical analyses for the left and right radii of the 14 individuals included in this study are presented below. To determine whether patterns exist between the remodeling variables and the specific enthesial insertions associated with forearm pronation and supination, each radial cross-section (e.g., proximal, midshaft, and distal) was analyzed independently. The descriptive statistics of the mean and standard deviations for OPD and osteon area for all 14 individuals by side, zone (ray) and cross-section are presented in Appendix A.

6.1 Proximal cross-sections

The proximal radial cross-sections proved problematic with cortical bone in this region being very thin along rays associated with the radial tuberosity (discussed in

Chapter 7). Therefore, the sample size of osteons quantified was much lower in the proximal diaphysis compared to the other cross-sectional regions included in this study.

Pearson tests between OPD and osteon area confirm the difficulty in analyzing this region with no significant negative correlation (p < 0.05) between the variables in either the left (p = 0.010) or right (p = 0.169). Thus, previously demonstrated associations

86 between increased strain and osteon size (Skedros et al. 2001; van Oers et al. 2008) are unfounded in the proximal region of the radius.

Assessing OPD separately, visual observation of the plotted means for all 8 rays quantified in both the left and right radii reveal some pattern consistency (Figs. 6.1 –

6.4). An increase in osteon density, and thus heightened bone turnover, is not distributed along rays associated with the insertion of the biceps brachii m. where strain generated through the regular contraction of this muscle is hypothesized to be concentrated. However, there is an inverse relationship along the anteriolateral ray, where the central portion of the radial tuberosity is positioned, with a relative reduction in osteon density. ANOVA tests found no significant differences (p < 0.05) demonstrated between OPD and the respective cross-sectional rays in either the left (p

= 0.226) or right (p = 0.564) radii (Table 6.1). Similarly angular-linear correlations found no significant differences (p < 0.05) in either the left (r2 = 4.280) or right (r2 = 5.576) radii

(Table 6.2).

Results for osteon area generated from the proximal cross-sections are similar to that of OPD, with some pattern consistency revealed within the left and right radii when the means from all 8 rays are plotted and visually assessed. However, osteon size is not consistently smaller along rays where OPD is high, which is unsurprising considering the before-mentioned lack of a significant negative correlation between OPD and osteon area. Contrasting with OPD, ANOVA tests demonstrate significant osteonal area differences (p < 0.05) between the 8 quantified rays for both the left (p = 0.001) and right (p = 0.051) radii (Table 6.1). Tukey pairwise comparisons reveal that the anteriorly

87 positioned rays associated with the biceps brachii m. are significantly different from the remaining rays. However, this is probably more attributable to the lack of measurable osteons in the vicinity of the radial tuberosity, rather than ray differences in the concentration of applied strain. Despite the ANOVA scores, angular-linear correlations found osteon area to not be significantly different (p < 0.05) between rays for either the left (r2 = 0.048) or right (r2 = 0.872) radii (Table 6.2).

Interval Plot of OPD for Right Proximal Sections 95% CI for the Mean 2.9 2.8

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Figure 6.1 95% confidence interval plot illustrating logged OPD means for the proximal cross-sections of the right radii. Biceps enthesis falls between the anterior and medial rays.

Interval Plot of OPD for Left Proximal Sections 95% CI for the Mean

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Figure 6.2 95% confidence interval plot illustrating logged OPD means for the proximal cross-sections of the left radii. Biceps enthesis falls between the anterior and medial rays.

Interval Plot of O.Ar for Right Proximal Sections 95% CI for the Mean

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Figure 6.3 95% confidence interval plot illustrating logged On.Ar means for the proximal cross-sections of the right radii. Biceps enthesis falls between the anterior and medial rays.

Interval Plot of O.Ar for Left Proximal Sections 95% CI for the Mean

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Figure 6.4 95% confidence interval plot illustrating logged On.Ar means for the proximal cross-sections of the left radii. Biceps enthesis falls between the anterior and medial rays.

Side Variable DF F-stat P-value Right OPD 7 0.83 0.564 (n=8) On.Ar 7 4.84 0.001

Left OPD 7 1.37 0.226 (n=8) On.Ar 7 2.09 0.051 Table 6.1 ANOVA of proximal cross-sections. Left and right radii are presented with corresponding OPD and On.Ar results. Significant p-values are in bold.

2 2 Side Variable DF ral r al nr al Right OPD 2 0.834 0.697 5.576 On.Ar 2 0.077 0.006 0.048

Left OPD 2 0.731 0.535 4.280 On.Ar 2 0.330 0.109 0.872 Table 6.2 Angular-linear correlation coefficients for proximal cross-sections. Left and right are presented 2 with corresponding OPD and On.Ar results. Critical chi-square value for significance is Χ 2, 0.05 = 5.991.

6.2 Midshaft cross-sections

In general, the midshaft radial cross-sections better fit the remodeling distributions expected within the central diaphyses of long bones. Pearson tests between OPD and osteon area demonstrate significant negative correlations (p < 0.01) between the variables of both the left (p = 0.532) and the right (p = 0.561) radii. Visual plots of the means for both OPD and osteon area with respect to the left and right limbs reveal some patterning that may reflect elevated strains associated with the pronator teres m. inserting along the lateral diaphysis, as well as the distal supinator m. insertion about the lateral and posteriolateral rays (Figs. 6.5 – 6.8).

ANOVA tests revealed no significant differences (p < 0.05) between cross- sectional rays in regard to either OPD or osteon area (Table 6.3). Variance of OPD between zones is near harmonious in the right radii (p = 0.919), and much more variable in distribution within the left radii (p = 0.465). Distribution of osteon areal measures is similar with the right radii showing little variation between rays (p = 0.941), with more variability in osteon size between rays of the left radii (p = 0.747).

Angular-linear correlations found inconsistent significant differences (p < 0.05) between rays for the midshaft cross-sections and OPD and osteon area (Table 6.4).

Correlation coefficients for OPD demonstrated significant differences in the left radii (r2

= 6.856) but not in the more dominant right radii (r2 = 2.712). In terms of osteon area, no significant differences were found within the left (r2 = 1.896) or right (r2 = 0.616) radii.

Interval Plot of OPD for Right Midhshaft Sections 95% CI for the Mean 3.1

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Figure 6.5 95% confidence interval plot illustrating logged OPD means for the midshaft cross-sections of the right radii. Pronator teres and supinator entheses fall along the posteriolateral and lateral rays.

Interval Plot of OPD for Left Midshaft Sections 95% CI for the Mean 3.1

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Figure 6.6 95% confidence interval plot illustrating logged OPD means for the midshaft cross-sections of the left radii. Pronator teres and supinator entheses fall along the posteriolateral and lateral rays.

Interval Plot of O.Ar for Right Midshaft Sections 95% CI for the Mean -3.0

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Figure 6.7 95% confidence interval plot illustrating logged On.Ar means for the midshaft cross-sections of the right radii. Pronator teres and supinator entheses fall along the posteriolateral and lateral rays.

Interval Plot of O.Ar for Left Midshaft Sections 95% CI for the Mean

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Figure 6.8 95% confidence interval plot illustrating logged On.Ar means for the midshaft cross-sections of the left radii. Pronator teres and supinator entheses fall along the posteriolateral and lateral rays.

Side Variable DF F-stat P-value Right OPD 7 0.37 0.919 (n=8) On.Ar 7 0.33 0.941

Left OPD 7 0.96 0.465 (n=8) On.Ar 7 0.61 0.747 Table 6.3 ANOVA of midshaft cross-sections. Left and right radii are presented with corresponding OPD and On.Ar results.

2 2 Side Variable DF ral r al nr al Right OPD 2 0.582 0.339 2.712 On.Ar 2 0.277 0.077 0.616

Left OPD 2 0.925 0.857 6.856 On.Ar 2 0.357 0.237 1.896 Table 6.4 Angular-linear correlation coefficients for midshaft cross-sections. Left and right are presented 2 with corresponding OPD and On.Ar results. Critical chi-square value for significance is Χ 2, 0.05 = 5.991. Significant correlation coefficients are in bold.

6.3 Distal cross-sections

The distal radial cross-sections have the clearest associations between the right and left radii and the respective rays. Pearson tests conducted between OPD and osteon area reveal significant negative correlations (p < 0.01) between the variables of both the left (p = 0.490) and right (p = 0.600) radii. Similar to the midshaft radial cross- sections, there appears to be some visual patterning between the 8 quantified rays and both OPD and osteon area in relation to the pronator quadratus enthesis (Figs. 6.9 –

6.12). Though weak in relation to the combined rays of each cross-section, there is an elevation in OPD and a reduction in osteon size along the anteriomedial ray, where the pronator quadratus m. inserts. The largest density of small osteons is concentrated

94 along the posterior ray and may be associated with gross biomechanical influences in this region.

Once again ANOVA tests found no significant differences between the remodeling variables and the respective cross-sectional rays. However, there is less asymmetry between the distal left and right radii in relation to ray differences of both

OPD and osteon area. ANOVA results for OPD reveal near-equal variance between the left (p = 0.746) and right (p = 0.710) limbs, followed by similar results for osteon area between the left (p = 0.787) and right (p = 0.784) elements (Table 6.5).

Angular-linear correlations confirm the lack of significant differences (p < 0.05) between distal cross-sectional rays. For OPD the correlation coefficient for the left radii is r2 = 3.744, and for the right radii it is r2 = 5.608. Similarly, osteon area has correlation coefficients of r2 = 3.752 for the left radii, with r2 = 5.544 for the right radii (Table 6.6).

Interval Plot of OPD for Right Distal Sections 95% CI for the Mean

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Figure 6.9 95% confidence interval plot illustrating logged OPD means for the distal cross-sections of the right radii. Pronator quadratus enthesis falls between the anterior and medial rays.

Interval Plot of OPD for Left Distal Sections 95% CI for the Mean 2.9 2.8

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Figure 6.10 95% confidence interval plot illustrating logged OPD means for the distal cross-sections of the left radii. Pronator quadratus enthesis falls between the anterior and medial rays.

Interval Plot of O.Ar for Right Distal Sections 95% CI for the Mean -2.9

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Figure 6.11 95% confidence interval plot illustrating logged On.Ar means for the distal cross-sections of the right radii. Pronator quadratus enthesis falls between the anterior and medial rays.

Interval Plot of O.Ar for Left Distal Sections 95% CI for the Mean -3.0

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Figure 6.12 95% confidence interval plot illustrating logged On.Ar means for the distal cross-sections of the left radii. Pronator quadratus enthesis falls between the anterior and medial rays.

Side Variable DF F-stat P-value Right OPD 7 0.65 0.710 (n=8) On.Ar 7 0.56 0.784

Left OPD 7 0.61 0.746 (n=8) On.Ar 7 0.56 0.787 Table 6.5 ANOVA of distal cross-sections. Left and right radii are presented with corresponding OPD and On.Ar results.

2 2 Side Variable DF ral r al nr al Right OPD 2 0.837 0.701 5.608 On.Ar 2 0.832 0.693 5.544

Left OPD 2 0.684 0.468 3.744 On.Ar 2 0.684 0.469 3.752 Table 6.6 Angular-linear correlation coefficients for distal cross-sections. Left and right are presented 2 with corresponding OPD and On.Ar results. Critical chi-square value for significance is Χ 2, 0.05 = 5.991.

6.4 Additional comparisons

In addition to analyses conducted on the three radial cross-section regions, further comparisons were made in relation to the radial diaphysis as a whole, by age, and by sex for both OPD and osteon area. These analyses were conducted on the left and right radii separately and were found to be very similar within both, thus the data provided below is generated from side-averaged means.

6.4.1 Cross comparisons of three cross-sectional regions

ANOVA tests between OPD and the three elements demonstrate a significant difference (p < 0.01) between the three diaphyseal regions (p = 0.0001), and their respective rays (p = 0.009) (Table 6.7). When the means for each ray within the three elements are plotted a clear pattern emerges (Figs. 6.13 and 6.14). The midshaft

98 reflects the highest bone turnover rate, followed by the proximal region, and the least remodeled distal regions. However, osteon area does not follow this pattern, with

ANOVA results demonstrating no significance between the three cross-sectional regions

(p = 0.112), yet significance between rays (p = 0.014). This is probably attributable to the complications regarding the radial tuberosity, which is best observed in the corresponding mean plots. Here, the midshaft and distal cross-sections conform to the plotted OPD; however the proximal region is much more variable in osteonal size distributions.

Variable Factor DF F-stat P-value OPD Zone 7 2.70 0.009 Cross-section 2 55.68 0.001

On.Ar Zone 7 2.53 0.014 Cross-section 2 2.19 0.112 Table 6.7 ANOVA of all three radial cross-sections by rays. Significant p-values are in bold.

Line Plot of OPD for All 3 Cross-Sectional Regions

2.9 Element Proximal 2.8 Midshaft Distal

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Figure 6.13 Line plot of mean OPD for each side-averaged radial cross-section by ray. Enthesial locations are as follows: biceps brachii (between proximal anterior and medial zones), supinator and pronator teres (along posteriolateral and lateral midshaft), pronator quadratus (between anterior and medial zones).

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Line Plot of O.Ar for All 3 Cross-Sectional Regions

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Figure 6.14 Line plot of mean On.Ar for each side-averaged radial cross-section by ray. Enthesial locations are as follows: biceps brachii (between proximal anterior and medial zones), supinator and pronator teres (along posteriolateral and lateral midshaft), pronator quadratus (between anterior and medial zones).

6.4.2 Age comparisons

For all three radial diaphyseal cross-sections, osteons are expected to reduce in size while density increases among older individuals, as primary bone is increasingly diminished and accumulated remodeling compiled throughout life should be greater as individuals age (Robling and Stout 2000). This relationship is revealed in ANOVA tests with significant differences (p < 0.01) demonstrated for both OPD (p = 0.0001) and osteon area (p = 0.0001) (Table 6.8). However, when the means for both variables are plotted in regards to age, only the midshaft and distal cross-sections appear to comply, with the proximal cross-section once again appearing highly variable (Figs 6.15 – 6.20).

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Variable DF F-stat P-value OPD 5 46.41 0.001

On.Ar 5 21.42 0.001 Table 6.8 ANOVA of all three radial cross-sections by age. Significant p-values are in bold.

Interval Plot of OPD for Proximal Sections by Age 95% CI for the Mean

3.1 3.0 2.9

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Figure 6.15 95% confidence interval plot illustrating logged OPD means for the proximal radial cross- sections by age range.

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Interval Plot of O.Ar for Proximal Sections by Age 95% CI for the Mean

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Figure 6.16 95% confidence interval plot illustrating logged On.Ar means for the proximal radial cross- sections by age range.

Interval Plot of OPD for Midshaft Sections by Age 95% CI for the Mean 3.2

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Figure 6.17 95% confidence interval plot illustrating logged OPD means for the midshaft radial cross- sections by age range.

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Interval Plot of O.Ar for Midshaft Sections by Age 95% CI for the Mean -2.9

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Figure 6.18 95% confidence interval plot illustrating logged On.Ar means for the midshaft radial cross- sections by age range.

Interval Plot of OPD for Distal Sections by Age 95% CI for the Mean 3.0

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Figure 6.19 95% confidence interval plot illustrating logged OPD means for the distal radial cross-sections by age range.

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Interval Plot of O.Ar for Distal Sections by Age 95% CI for the Mean

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Figure 6.20 95% confidence interval plot illustrating logged On.Ar means for the distal radial cross- sections by age range.

6.4.3 Sex comparisons

An ANOVA test between the three diaphyseal cross-sections and the sex of individuals incorporated into the study yield significant results (p < 0.01). Both OPD and osteonal area distributions between males and females are significant at p = 0.0001

(Table 6.9). When the combined means of each of the three cross-sections are plotted, it becomes apparent that for both OPD and osteon size, females demonstrate the highest bone turnover rates with the largest concentration of smaller osteons (Figs 6.21 and 6.22). This is most likely a reflection of the mean age distributions of males and females included in this study. For the 7 males the mean age is 46 years, while the 7 females have a mean age of 58.9 years.

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Variable DF F-stat P-value OPD 1 62.05 0.001

On.Ar 1 206.36 0.001 Table 6.9 ANOVA of all three radial cross-sections by sex. Significant p-values are in bold.

Individual Value Plot of OPD for All 3 Cross-Sections by Sex 3.0

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Figure 6.21 Bar chart illustrating mean OPD for all three radial cross-sections by males and females.

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Individual Value Plot of O.Ar for All 3 Cross-Sections by Sex

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Figure 6.22 Bar chart illustrating mean On.Ar for all three radial cross-sections by males and females.

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Chapter 7: Discussion

7.1 Relationships between OPD and On.Ar

7.1.1 Mechanical loading

The premise of this study is based on the well-established association between osteon density per unit of area and mechanical loading. Experiments regularly demonstrate that as strains increase, resulting in various forms of cortical microdamage, new osteons are created to replace the damaged matrix (Burr et al. 1985; Martin 2002;

Martin 2007; O'Brien et al. 2005). Therefore, cortical regions exposed to strains that exceed the normal threshold level have greater bone turnover than less loaded regions, which is histomorphometrically observed as densely packed osteons (Forwood 2001;

Lieberman et al. 2003; Robling 1998; Robling and Stout 2003; Stout 1982). Additionally, it is suggested that demineralized cement lines assist in arresting crack propagation to prevent catastrophic tissue failure (Burr et al. 1988). Thus, densely packed osteons increase tissue strength to prevent further damage in regions subjected to excessive strain.

Presumably related to the density of intracortical osteon creations is the size of these basic multicellular units. Experimental studies suggest that regions exposed to high strain have smaller osteon diameters than those that are less stressed (Skedros et 108 al. 2001; van Oers et al. 2008). Smaller osteons allow for them to be densely packed, which increases cement line surface area making the matrix more efficient at absorbing transmitted energy (Yeni et al. 1997).

Based on these principles, histomorphometric analysis of targeted remodeling should reveal a negative correlation between the density and size of osteon creations.

This association is confirmed in two of the diaphyseal regions included in this study, with significant negative correlations between OPD and On.Ar observed in the total midshaft and distal cross-sections. However, this relationship was not confirmed in the proximal cross-sections, which is most likely a result of complications surrounding the reduced cortical volume along rays aligned with the radial tuberosity (discussed below).

Despite confirmation of a significant relationship between OPD and On.Ar within gross diaphyseal regions, correlations of these variables between the independent cross-sectional rays of the three diaphyseal regions were not statistically significant.

However, visual assessment of mean plots for both variables found that most rays agree, even within most of the proximal zones, with elevated OPD resulting in smaller osteons. The statistical lack of association when independently assessing each of the 8 rays may be a reflection of sampling differences between this study and previously mentioned research that found strong associations between mechanical strain levels and osteon size. Prior studies focused on remodeling differences between major diaphyseal axes (e.g. anteriomedial and posteriolateral) and thus a large region of the cortical matrix was sampled. This exploratory study was more thorough in its analysis of the diaphysis with the inclusion of the diagonal intercepts of the major axial orientations

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(e.g. anteriomedial, medioposterior, posteriolateral, and anteriolateral), however this reduced the cortical volume sampled for each respective ray, increasing the variability of both OPD and On.Ar between quantified zones.

7.1.2 Age influences

Previous studies have also found strong associations between remodeling activity and age, with older individuals demonstrating increased bone turnover resulting in elevated osteon densities and increased intracortical porosity (Chan et al. 2007; Cho et al. 2002; Crowder 2005; Kerley 1965; Stout 1992; Thompson 1979). Therefore, a linear progression should be present with OPD increasing and presumably osteon diameter decreasing as individuals age. This relationship is driven not only by accumulated alterations via lifetime mechanical loading, but also through a suite of systemic influences outlined in Chapter 2.

The sample included in this study confirms this association between remodeling activity and age with individuals of later years demonstrating higher mean OPD and correspondingly smaller osteons. This can also be observed in the bar charts illustrating differences in bone turnover and osteon size for both males and females. Females have larger osteon densities and osteon diameters within all diaphyseal regions sampled compared to that of males. One might assume this suggests stronger, more active females. However this pattern is most likely attributable to the higher mean age of females compared to males. Additionally, most of the females included in this study are at a post-menopausal age, leaving them with depleted estrogen production and thus

110 greater uninhibited remodeling activity compared to the predominately younger men that have yet to be exposed to remodeling consequences arising from drastic hormonal shifts as they age.

7.2 Entheses and associated histomorphometry

Following analysis of OPD and On.Ar in diaphyseal regions where the primary muscles involved in forearm rotation insert along the radial shaft, mechanical influences on enthesial development remain enigmatic. It was anticipated that there would be heightened remodeling activity and smaller osteon diameters associated with enthesial landmarks along the radial diaphysis. The results suggest enthesial development is even more complex than previously thought.

None of the rays associated with the four entheses included in this study demonstrated bone turnover or osteonal area disparities that were statistically significant compared to the remaining unassociated rays. This was not completely unexpected considering the small number of individuals and unique sampling methods employed, which ultimately narrowed statistical exploration.

Despite the lack of statistical significance observed between rays, interval mean plots highlight remodeling differences along enthesial rays compared to those not within the proximity of diaphysial tendon insertion. In all but the biceps brachii enthesis, which is problematic, cross-sectional rays aligned with radial entheses contain smaller, more densely packed osteons, relative to the remaining rays.

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7.2.1 Biceps brachii m.

The proximal region containing the biceps brachii enthesis was histomorphometrically complex and thus difficult to analyze using standard methods.

Due to regional complexity and methodological inadequacies, the proximal diaphysis proved to be least informative when assessing axial strain differences in osteon concentration and size. Between anterior and medial rays, where the radial tuberosity supporting the enthesis is normally positioned, the cortical matrix is very thin. Often within this bone shell is a large volume of calcified fibrocartilage subchondrally anchoring the biceps brachii enthesis. Therefore, osteon densities aligned with the anteriomedial ray are abnormally low since reduced cortical volume, and differences within collagenous materials, limit available space for osteon creations to arise. Thus few, if any, intact osteons are available for areal measurement, lowering the number of sampled osteons and skewing statistical analyses. Mean interval plots demonstrate this with notable reductions in OPD and increased osteon diameters along the anteriomedial ray associated with the macroscopic apex of the radial tuberosity.

Compounding these complications is a large volume of trabecularized bone and resorptive space associated with the radial tuberosity, which inherently removes previously remodeled bone, obscuring the true remodeling history within these rays

(Fig. 7.1). It is for these reasons that OPD and osteon size most likely fail to demonstrate a significant negative correlation as would normally be expected.

The unique composure of cortical bone along these rays in the proximal diaphysis may allow for efficient stress dissipation that requires minimal cortical

112 remodeling. Benjamin et al. (2002; 2006) hypothesize that the reduction in compact bone at this site allows for flexibility as the biceps brachii m. contracts and the associated tendon affixed at the osteotendinous junction shortens.

Figure 7.1 Microscopic image of proximal radial cross-section. The radial tuberosity is positioned between the anterior and medial rays. Note the thin compact bone along the anterior and anteriomedial intracortical envelope. The arrows indicate the calcified fibrocartilage (yellow) from the biceps brachii enthesis. The bracket highlights the large expanse of trabecular bone (blue). Micrograph viewed using red quartz cross-polarized filter (hilfsobject). Magnification 40x.

The large volume of trabecular bone is a consequence of ongoing trabecularization of the cortical matrix as endocortical resorption results in large porosities that coalesce (Burr 2010; Zebaze et al. 2010). Negative effects on bone

113 strength are minimal since much of the porosity is located along the endosteum, which is closely aligned with the neutral bending axis. In fact, the large volume of trabecularized cortex may be a localized adaptation to increased strains, with the trabecular envelope providing a scaffold mechanism that not only supports the expansion and contraction of the cortical shell, but also distributes forces throughout the radial diaphysis.

7.2.2 Pronator teres and supinator mm.

The midshaft radial diaphyses appear to have more patterned remodeling throughout the cross-sectional rays. Relating to the posteriolateral and lateral insertions of the supinator and pronator teres mm. respectively, there is an elevation in

OPD compared to the remaining rays. This would suggest that, though the ray differences are statistically insignificant, the tensile force generated from these muscles during forearm rotation have some minor influence on bone turnover in this region.

Osteon size, though less distinct across rays, also appears to be associated with these two entheses. Despite these potential associations, it is important to note that the collective density and size of osteons is not unique to these two rays.

In relation to all eight rays quantified, the medial ray demonstrates the lowest collective strain with relatively low osteon density and large osteons. This is the point of attachment for the interosseous membrane that spans between the radial and ulnar diaphyses, forming the major portion of the radio-ulnar syndesmosis, or fibrous joint.

That the remodeling signatures indicate the least cross-sectional strain along this ray is

114 not unexpected, since experimental models and cadaveric studies found this diaphysial union to effectively dissipate strain from one bone to the next, thus reducing the load placed on either (Shaaban et al. 2006). Though strains are shared, this relationship is not equal, with the radius carrying upwards of 60-80% of the load (Birkbeck et al. 1997;

Palmer and Werner 1984). Thus analysis of the lateral ray of the ulna should reveal even lower strain levels than that of the radius in respect to the remaining cross- sectional rays.

7.2.3 Pronator quadratus m.

From the very beginning of this study, it was assumed that the distal radial cross- sections would provide the clearest picture of how the two remodeling signatures relate to entheses. This is due to the presence of only one muscle body, pronator quadratus, which inserts along this diaphyseal region. The other radial attachment in this region is the brachioradialis m., which is below pronator quadratus inserting not on the diaphysis but on the even more distally positioned styloid process. With only one muscle acting on the cross-section, patterns that may emerge should be easier to interpret than that of the more dynamically loaded midshaft and proximal diaphysis.

Visual mean plots for the 8 radial rays somewhat confirm these assumptions.

Between the anterior and medial zones there is a slight peak in osteon density along the anteriomedial ray that corresponds with the fibrous pronator quadratus enthesis. This is loosely confirmed in terms of osteon size as well, though the right distal radii demonstrate larger osteons in relation to the surrounding anterior and medial rays,

115 which may relate to the number of intact osteons sampled. The elevation in density and reduction in osteon size within this ray is greater in the remaining posteriorly and laterally aligned zones, however strain generated via the pronator quadratus m. would be minimal, and thus large perturbations associated with this enthesis would not be expected.

7.2.4 Additional considerations

Ray remodeling differences are relatively small within intracortical regions where entheses are found along the periosteum. This does not necessarily suggest contractile forces have minimal effect on enthesial development. Mechanical loads transferred across the osteotendinous junction may not exceed the normal threshold levels required to activate basic multicellular units. This would not be unexpected considering the intricate tendon-bone relationship beginning with the formation of primary ossification centers during the ninth week of fetal development (Moore and Persaud

2003), when the baseline conditions for mechanical competence are achieved (Frost

2003), and continuing throughout skeletal growth and maturity. Additionally, the enthesial structure formed in utero between contrasting biological materials is very efficient at dissipating transferred strains and resisting tendon avulsion. In fact, this union of hard and soft tissues is so biologically complex, that modern science is unable to clinically reconstruct the strength and efficiency of entheses following significant damage. Clinical studies reveal a failure rate in repairing rotator cuff enthesial tears ranging from 20-94% depending on injury severity (Galatz et al. 2004; Harryman et al.

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1991). Therefore it would appear the osteotendinous junction is intricately designed to resist strains generated through normal, habitual activity.

7.3 Diaphyseal asymmetry

Asymmetric differences between the left and right proximal diaphyses are visually apparent, though due to the above-mentioned complications with this region, they remain unclear. The left and right limbs are in agreement along most rays in regards to the remodeling factors, however the left radii appear to be more variable compared to the frequently dominant right radii.

Asymmetric differences between the left and right midshaft and distal radii are minimal. Visually, zones between the two sides appear to agree very well with ANOVA tests confirming a relatively strong symmetry. Distal radii appear to be less influenced by biomechanical forces acting on the forearm that that of the more proximally positioned cross-sections. During histomorphometric analysis of this region, a much larger volume of unremodeled primary bone was noted, visually confirming this interpretation.

7.4 Gross diaphyseal observations

Comparisons of all three radial cross-sections found the posteriorly aligned rays to collectively have the largest amount of bone turnover with the smallest osteons.

Most likely this is related to how the forearm functions as a 3rd class lever to provide rapid flexion (Aiello and Dean 1990) (Fig. 7.2). In the forearm, the fulcrum is the elbow

117 joint and the effort is provided by the biceps brachii m. Since the insertion of the biceps brachii m. is close to the elbow, a large amount of effort is needed to counter the resistance in the hand, which due to its distal positioning has covered a much greater distance than the effort. Therefore a much greater effort is needed to overcome a relatively small resistance in the hand. Thus the forearm provides speed at the detriment of strength.

Figure 7.2 Schematic diagram illustrating how the forearm serves as a 3rd class lever.

The histomorphometric results appear to convey the lever function of the radius, since the largest amount of remodeling occurs in the posteriorly aligned rays. With the effort and potential resistance considerably apart from one another there is a large diaphyseal expanse subjected to bending when load is applied to the hand. Thus loaded

118 flexion of the forearm would cause considerable compression within the posterior diaphysis, activating remodeling in response to increased strain and subsequent microdamage.

7.5 Hypotheses revisited

Based on the results of this study, the original null and alternate hypotheses can be assessed. Table 7.1 summarizes the findings in relation to the stated hypotheses and they are reaffirmed below with those accepted highlighted in bold.

Hypotheses HO HA

H1 Accept Reject

H2 Accept Reject

H3 Reject Accept

Table 7.1 Summary of acceptance or rejection of null and alternate hypotheses

H1O: OPD scores in each radial cross-section are not significantly (p < 0.05) higher along rays related to muscle insertions, relative to those not directly associated with entheses.

H1A: OPD scores in each radial cross-section are significantly (p < 0.05) higher along rays related to muscle insertions, relative to those not directly associated with entheses.

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The null hypothesis was accepted over the alternate hypothesis. Interval plots of means demonstrate an association between higher OPD scores and rays related to the enthesis. However, this relationship is no statistically significant.

H2O: Mean osteon size in each radial cross-section is not significantly (p < 0.05) smaller along rays related to muscle insertions, relative to those not directly associated with entheses.

H2A: Mean osteon size in each radial cross-section is significantly (p < 0.05) smaller along rays related to muscle insertions, relative to those not directly associated with entheses.

The null hypothesis was accepted over the alternate hypothesis. Interval plots of means demonstrate loose associations between smaller osteons and rays related to the enthesis. However, this relationship is less predictable than that of OPD and not statistically significant.

H1O: Higher OPD scores and smaller osteon diameters are not consistently found within similarly positioned rays.

H2A: Higher OPD scores and smaller osteon diameters are consistently found within similarly positioned rays.

The alternate hypothesis was accepted over the null hypothesis. Though this relationship was found to not be statistically significant, a clear relationship has emerged between OPD and smaller osteons when mean confidence intervals are

120 plotted for each ray. Additionally, OPD and osteon size demonstrate a significant negative correlation that suggests when osteon density rises, subsequent osteon creations will be smaller, accounting for both matrix availability and energy absorption requirements. It is anticipated that if the sample size is increased and the cortical area quantified within each axial zone is expanded, statistically significant associations between the remodeling variables and entheses will be observed.

7.6 Research limitations

There were a number of limitations that arose throughout the course of this study. Most notably was the small sample size of only 14 individuals, limiting generalizations made surrounding enthesial etiology. Every attempt was made to include individuals that encompassed an age range of 20-80 years and that were relatively healthy throughout the majority of their life. Inclusion of individuals that voluntary donated their bodies for medical research created many of the issues surrounding sample size, with the majority of available subjects being elderly, and those with an age-at death of less than 45 years few and far between. Additionally, recent changes in The Ohio State University’s body donation enrollment, omitted potentially critical factors for analysis such as ancestry and occupation. Though the included individuals appeared to be of Caucasian descent, Cho et al. (2006) have noted that ancestry can affect bone turnover rates. Therefore, reported results should only be considered for this group, as they are not necessarily true of other samples.

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Additional concerns arose with the intracortical sampling methods using cross- sectional rays. To avoid ray overlap and thus maintain the histomorphometric uniqueness of each individual zone, only a thin strip was read at a magnification of 100x.

Therefore, for each quantified zone, only 2-4 fields were read for each ray, depending on the cortical volume present between the periosteal and endosteal envelopes. This undoubtedly hampered statistical analysis and the ability to confidently acquire significant relationships, particularly when considering osteon areal averages for each ray were acquired from as few as 5-10 intact osteons in some cases. With few osteons sampled, outliers demonstrating biological variation unquestionably skewed the resulting On.Ar averages. The effects from sampling small regions were most apparent within the proximal diaphysis with anteriorly oriented rays frequently containing few intact osteons suitable for either OPD assessment or areal measurement.

Further limitations concern the inability to subtract potential global systemic factors influencing remodeling rates within the localized diaphyseal regions quantified in the radius. As mentioned in Chapter 2, accounting for factors such as genetics, diet, and hormones, is traditionally accomplished by using turnover rates present in the rib as a control. Since the rib is presumed to be uniformly loaded through respiratory activity

(Epker and Frost 1964), quantified bone turnover rates should predominately reflect systemically driven remodeling. Thus, the rib can be used to subtract potential global systemic remodeling from dynamically loaded bones, resulting in an OPD measure more indicative of mechanically driven remodeling (Robling and Stout 2003). To address this in the present study the sixth rib of all 14 individuals was obtained and OPD was

122 acquired in the hopes of providing a control for systemic remodeling within the radial cross-sections. However, it became readily apparent that this method, which had previously been conducted only on the heavily loaded lower limbs (Robling 1998), was not suitable for the radius as the respective ribs demonstrated much higher OPD scores than practically all radial diaphyseal regions within each individual. Therefore, linear regressions accounting for stochastic remodeling in the radius were not possible since the rib scores incorrectly suggested that all remodeling in the radius was systemic rather than mechanical. In light of these observations, the rib was not included in the following research. There may be other statistical methods that account for these influences in the upper limb bones, however this would encompass an entirely different investigation outside the purview of this study.

7.7 Future directions

Based on the stated limitations, there are several sampling and methodological issues that can be addressed in future histomorphometric analyses concerning enthesial etiology. Most notably is the expansion of the number of individuals included in the study. With a small sample size it is difficult to observe significant differences since total biological variation may not be accounted for and statistical power is low, increasing the probability that a type II error is made, wherein a false null hypothesis fails to be rejected. Based on the results charted in the interval mean plots, it is believed that increasing the sample size may increase the likelihood of observing statistically

123 significant differences between cross-sectional rays, providing a more sound interpretation of whether remodeling activity is associated with enthesial location.

Aside from gross sample size are concerns raised when a relatively small subset of cortical bone is quantified within each cross-sectional ray. Resolution of this problem may be achieved if histomorphometric analysis is conducted on the entire cross-section, followed by the superimposition of the 8 rays, assessing whether statistical differences between them occur. This would expand the volume of cortical volume analyzed, and would definitely increase the mean number of intact osteons quantified, which was the single greatest obstacle encountered in the current investigation. Additionally, serial thin sections should be taken from the entire expanse of macroscopic enthesial markings to account for potential stress dissipation. In the current study, thin sections were only prepared from the central locale of each respective enthesis. However, the central point of tendon insertion might not be the most strained region of the enthesis.

With their intricate design and efficiency in resisting normal strains, statistically significant differences may lie within the outer margins of enthesial attachments, as applied stress is believed to dissipate along the diaphysis to resist strain concentrations in the immediate vicinity of tendon insertion. Regardless of the results, analysis of serial sections will provide a more thorough assessment of intracortical remodeling and how this relates to the entire region impacted by particular entheses.

Also favorable in future explorations is the inclusion of the macroscopically observable enthesis. Though previous research has found measurement of the enthesis to be problematic, particularly when accounting for height (Schlecht 2004), a unique

124 method that quantifies 3D laser scans of entheses using fractal analysis is promising

(Zumwalt 2005). If quantitative analysis of chosen entheses is achievable, then a more complete assessment of this complex mechanism can be attained, as both micro- and macroscopic parameters are evaluated for statistically significant cross-sectional patterns.

Additional concerns arising during the current study center on the inability to use the rib as a control for stochastic remodeling within the radial diaphysis, which would afford a better representation of mechanically driven target remodeling. At present it remains unclear how to account for systemic influences in the non-weight bearing upper limb, however further investigation should be conducted that would allow for statistical accounts of these two remodeling functions via linear regression. Failure to account for systemic factors potentially impacting OPD in the current study, may explain the lack of observed statistical differences along quantified rays.

Providing the necessary facilities and funding are available, inclusion of animal models may be more beneficial than investigations conducted on static osteological samples, where activity levels and factors influencing skeletal growth and development are unknown. This would require adult animals (e.g., sheep, pigs, dogs) that can be trained to follow an exercise regimen for at least 90 days, depending on the species specific bone formation period. Varying the exercise intensity to strain bone outside normal remodeling thresholds, radiographic analysis of specific tendon insertions and their response to activity intensity may be achieved, followed by macro- and microscopic investigation of the skeletal region in question at the conclusion of the

125 study. Experimental animal studies would provide better controls and potentially reveal how tendon insertion sites osteologically respond to mechanical strains following both routine and irregular locomotive activities. Furthermore, use of animals would eliminate age and preservation concerns that inherently arise when incorporating human cadavers or archaeological samples, respectively.

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Chapter 8: Conclusions

The purpose of this study was to histomorphometrically investigate the relationship between entheses and mechanically driven bone remodeling, shedding light on the osseous etiology of these insertion sites along the periosteum. The radius was chosen for this investigation because it is not weight bearing, has only a few well- defined enthesial placements, and has an important evolutionary role in human forearm and hand dexterity. This unique exploratory study was focused on examining how mechanical strain is transferred and subsequently dissipated into the radial diaphysis via osteotendinous junctions, clarifying whether or not macroscopic enthesial morphology is indicative of localized muscular activity levels.

Thin sections for histological examination were made from both the left and right proximal, midshaft, and distal radial diaphyses of 14 post-mortem individuals donated for scientific research. Diaphyseal regions were chosen based on the insertion sites for muscles acting on forearm rotation, which include biceps brachii (proximal), pronator teres and supinator (midshaft), and pronator quadratus (distal). To reveal remodeling differences related to enthesial regions, the anterioposterior and mediolateral axes along with their diagonal intersections (e.g. anteriomedial, medioposterior, posteriolateral, and anteriolateral) were defined for each cross-section.

127

Osteon population density (OPD) per unit area and osteon area (On.Ar) were quantified and analyzed for each of the eight radial axes.

Results revealed clear associations between OPD and On.Ar, demonstrating elevated bone turnover along axes aligned with three of the four considered entheses, though they were not statistically significant. The biceps brachii enthesis was not associated with increased remodeling, reflecting the reduced cortical volume and calcified fibrocartilage present within the radial tuberosity. These results confirm a potential relationship between entheses and mechanical strain. However, they are not as conclusive as was expected. The unique construction of this osteotendinous region is unmatched in orthopaedic medicine, demonstrating the well-designed efficiency of entheses. Additionally, mechanical strain generated from repeated muscular contractions may not exceed normal threshold levels to activate the remodeling process, and therefore enthesial morphology may be more indicative of sporadic strains that are outside one’s normal activity level.

This exploratory study has led to the following conclusions. First, enthesial morphology appears to be partially influenced by mechanical strain, though normal activity levels may not account for the majority of gross periosteal changes observed macroscopically. Further research should investigate strain levels required to initiate periosteal remodeling within designated enthesial zones, determining whether earlier hypotheses stated by Chamay and Tschantz (1972) and Woo et al. (1981) regarding an increase in periosteal capillary volume following muscular contraction is confirmed.

Second, OPD and On.Ar are intricately linked, with osteon creations becoming

128 increasingly smaller within highly strained intracortical regions where remodeling activity is high and thus osteon density is relatively larger. This confirms the earlier findings of Skedros et al. (2001) and van Oers (2008) in their exploratory research.

Third, fibrocartilaginous entheses such as the radial tuberosity are much more complex than previously thought and must be interpreted separately from the diaphyseal fibrous entheses anchoring large muscle bodies. These entheses have stratified layers of varying material compositions and a relatively small cortical volume, presumably allowing for greater elasticity under strain. Furthermore, they have a different etiology all together compared to the more direct fibrous insertions. Fourth, distribution of the material properties within the radius appears to primarily be guided by gross diaphyseal biomechanics related to leverage, rather than localized contractile strain.

Based on these conclusions, bioarchaeological and forensic profiles that macroscopically attribute varying degrees of enthesial development to general activity levels of individuals should be employed cautiously. Entheses of muscles crossing joints are both compositely and mechanically different from those that originated and insert along the same long bone diaphysis, and thus deserve separate analytical and interpretive considerations. Additionally there remain large knowledge gaps in understanding the development and maintenance of entheses throughout their functional life, requiring further investigation into alternate mechanical and systemic influences before gaining confidence in their anthropological validity.

129

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Appendix A: Total Data

157

Zone Cadaver ID Cross-section Anterior AnteriorMedial Medial MedialPosterior Posterior PosteriorLateral Lateral AnteriorLateral A RDR 8.263182358 12.24852252 11.76470588 17.02641841 12.3294754 16.01947969 18.2803421 14.13324236 B RDR 15.7593614 12.55473559 17.06403754 17.7861139 22.81455569 21.85394282 16.41380534 12.41161426 C RDR 6.75162461 7.339834329 8.253706232 5.632896113 9.54540031 6.590871643 9.171634635 8.728451635 D RDR 8.164534816 9.648655842 10.41421709 9.719684305 14.71582548 13.84083045 11.68989058 11.66814195 E RDR 15.28928945 15.89825119 10.38062284 17.89762558 17.82531194 17.88421912 15.04438092 14.73157696 F RDR 26.76764379 17.66147636 19.37716263 37.48558247 37.99443653 26.55508168 28.96918001 27.13888323 G RDR 13.94412023 22.54377687 11.85002607 16.68314385 25.28613255 18.67413632 20.76124567 13.52265044 H RDR 11.39336653 10.26655006 8.073817762 10.17708121 12.44119591 9.948096886 7.008015418 11.39336653 I RDR 8.8615073 6.291286568 10.4527105 11.4151179 11.42521381 14.03669126 9.570787013 7.639419404 J RDR 12.68742791 21.62629758 10.57285659 11.16196004 20.22890604 18.78398418 16.80672269 12.83625405 K RDR 8.263182358 9.362914716 7.68935025 10.81314879 9.582113388 5.767012687 9.81252905 10.49725905 L RDR 6.519231734 9.043724442 9.337068161 5.190311419 6.041632339 6.239718645 7.54147813 6.1514802 M RDR 5.831810583 8.503900065 7.68935025 9.159373092 8.169934641 10.71016642 7.775747444 6.451234532 N RDR 4.772700155 5.818048198 4.828196669 6.487889273 7.077697389 4.27186125 4.99411408 6.393861893 A RMR 17.0027443 17.30103806 15.15628128 20.91334271 20.09152807 19.77261493 16.22929234 16.99209095 B RMR 18.19812892 22.49134948 17.9664626 23.50329699 17.62142766 23.35640138 17.44891018 20.25924664 C RMR 15.61313191 14.68956062 13.23020558 14.87565889 13.35518728 9.026628554 12.11072664 14.8294612 D RMR 20.47877975 18.91912076 17.15059425 20.62143931 27.10495963 14.69822703 16.14763552 16.11241713 E RMR 17.83612171 16.60899654 16.03510845 15.09908776 14.56929521 14.53287197 15.89825119 16.16654376 F RMR 28.45059592 27.18734553 25.37485582 29.65892239 35.17877739 34.60207612 29.08580312 29.58728248 G RMR 26.09336888 24.82322852 25.12205527 22.51219411 14.6393399 16.14763552 20.44668135 23.2260511 H RMR 20.09152807 16.65224913 15.54586029 16.34743754 17.30103806 21.90635035 18.82352941 20.60276288 I RMR 13.09267745 9.436929852 9.626141478 10.35337711 14.21156698 19.82815598 13.26412918 14.67128028 J RMR 16.51462724 14.53868745 17.30103806 21.87487571 18.21161901 20.29988466 18.03725245 17.49115936 K RMR 19.63002396 16.92763436 13.69665513 15.0210563 16.91657055 17.71626298 19.68191486 20.70881829 L RMR 9.688581315 9.886307464 10.69518717 13.25185894 13.30849082 14.93614797 11.83755236 7.61680921 M RMR 14.31810047 13.50324922 12.81558375 15.26562182 17.30103806 19.87049916 18.09954751 17.563175 N RMR 12.28858778 11.53402537 12.1799308 15.34526854 11.03254601 11.72951733 11.44320628 9.436929852 A RPR 6.247597078 7.569204152 9.075954393 17.66914526 9.886307464 17.30103806 16.77676418 4.828196669 B RPR 11.1220959 3.295435821 20.76124567 22.70761246 23.06805075 24.07100948 17.87773933 20.67137015 C RPR 11.82602602 9.533225055 10.17708121 10.0922722 11.53402537 10.11947509 5.375079786 6.615102789 D RPR 15.30476444 8.439530762 15.10794873 10.61654608 10.92697141 10.32897795 14.31810047 18.8738597 E RPR 11.27483379 9.492604955 21.69960706 16.75468949 21.50939867 13.75210718 18.4942131 18.23622931 F RPR 14.19572354 21.37187055 23.06805075 20.42089738 19.3364543 17.30103806 22.62443439 24.50980392 G RPR 15.59530192 22.42727156 10.38062284 16.35734508 19.37716263 17.30103806 17.30103806 12.63250398 H RPR 16.33986928 11.2986371 11.78752044 13.65871426 19.41953252 22.27804901 16.57000829 15.72821642 I RPR 9.611687812 17.30103806 13.10175698 9.470041887 13.57802987 8.98755224 10.47168093 10.0782746 J RPR 5.931784478 12.97577855 16.93293087 16.54881902 15.4605021 16.94795565 13.07189542 10.53106665 K RPR 22.35826457 10.68593527 24.26122579 17.66147636 17.53171857 16.43598616 15.0620802 16.47717911 L RPR 14.33514582 16.59487324 14.8294612 11.7516485 10.99505223 9.54540031 7.68935025 14.8294612 M RPR 12.91122243 11.72005804 12.76981381 17.30103806 14.95151437 13.37946943 12.87519112 15.93516664 N RPR 13.71025658 6.487889273 3.615142282 6.76132522 10.84542685 8.073817762 6.528693608 10.50420168

Table A.1 Mean OPD scores for right radii of all 14 individuals by cross-section and quantified zone. RDR = right proximal radius, RMR = right midshaft radius, RDR = right distal radius

158

Zone Cadaver ID Cross-section Anterior AnteriorMedial Medial MedialPosterior Posterior PosteriorLateral Lateral AnteriorLateral A LDR 10.78506269 12.81558375 15.69578711 13.37946943 16.20603565 14.62059555 14.49546432 13.98807333 B LDR 14.77392014 14.73792131 11.76470588 14.56929521 15.53562602 15.99529934 14.48459001 13.22193153 C LDR 12.16776303 8.820137051 7.569204152 6.697176024 9.470041887 9.301633367 9.943125323 11.08610206 D LDR 7.190041792 9.798818018 8.073817762 9.2272203 12.12856277 11.67298954 12.97577855 11.53402537 E LDR 14.38008358 16.12523936 12.67600809 13.30849082 19.3364543 16.32906963 12.05240854 12.60923113 F LDR 18.51942102 20.76124567 20.47877975 31.8881878 32.36968412 33.96129694 31.83391003 29.49685178 G LDR 15.57093426 15.33501101 17.30103806 16.60899654 20.76124567 18.97533207 14.15539478 13.93694733 H LDR 10.14994233 13.60755803 6.487889273 7.884017345 11.90609071 12.52265612 9.2272203 13.47659807 I LDR 6.920415225 4.99411408 7.726677193 9.125822275 10.91056454 10.96303402 8.929568032 5.641642846 J LDR 12.35788433 16.14763552 9.2272203 7.549543882 15.5112755 16.39045711 13.30849082 12.21249746 K LDR 8.98755224 8.123965699 10.02958728 9.961203733 8.416721219 7.255274026 5.632896113 13.21877065 L LDR 5.164488974 6.590871643 5.164488974 5.767012687 8.109861592 3.579525116 8.787828857 7.262164125 M LDR 6.920415225 9.673698701 9.2272203 9.582113388 7.734581722 7.028546713 6.035245836 8.650519031 N LDR 4.735020943 7.723677706 8.185437363 7.775747444 10.3070014 7.775747444 6.666455033 5.719351426 A LMR 20.35416243 17.46580985 17.81493028 17.60998517 19.57289155 17.13626627 17.77721342 17.93016672 B LMR 18.90298603 16.24179083 18.17482786 18.06431915 18.5467128 17.30103806 21.3801446 22.51504953 C LMR 20.37318501 12.46921662 9.395265703 13.07795003 16.28332994 17.62142766 15.84581056 19.16805656 D LMR 15.97018898 12.74813331 16.6939841 15.3787005 18.28564998 17.7861139 19.9856819 23.06805075 E LMR 17.15316594 15.54161046 14.90550972 16.28332994 14.67966866 19.12219996 16.6939841 15.09486542 F LMR 30.757401 28.47006263 22.54377687 27.35978112 31.97407034 35.66675539 32.03895937 28.36235748 G LMR 21.44354013 21.38330547 21.57541217 23.06805075 19.59394672 19.05621584 21.71832438 22.95385248 H LMR 21.99010445 20.9647873 16.73379091 21.14571319 17.15316594 18.56696768 17.66914526 18.26817684 I LMR 10.02490056 8.17371877 6.590871643 10.41421709 9.848283205 10.66680542 13.69665513 14.31810047 J LMR 14.41753172 17.91893228 16.17270949 18.23622931 18.33910035 19.77261493 17.69424347 19.5576952 K LMR 13.48894493 13.73098259 14.30219146 12.23004415 16.53935714 19.81755269 14.87031371 13.5200165 L LMR 9.092516354 10.75205755 7.89577576 10.70423938 13.14002891 18.72304119 13.20342378 8.535178777 M LMR 11.88620936 14.11923796 11.97764174 13.48463261 13.09267745 14.87565889 11.43870285 11.96763535 N LMR 9.886307464 9.712863474 8.86499471 10.83195427 9.717021377 13.5554525 12.76306087 10.43554677 A LPR 10.87493821 14.48459001 11.53402537 12.32402711 14.8294612 16.64403662 17.75632854 9.938894206 B LPR 18.93321146 10.44590977 13.59367276 19.77261493 30.08876185 25.23068051 21.55539168 16.6506231 C LPR 12.90246906 8.238589553 10.67965312 8.749950284 10.19850665 7.726677193 11.86356896 9.92929141 D LPR 14.41753172 7.746733461 14.33514582 9.402738077 12.01460977 12.89096954 10.42802294 14.96305995 E LPR 7.159050233 12.65022138 19.77261493 23.86350078 17.91166294 16.62697164 8.827060236 17.05736147 F LPR 24.02921953 16.39045711 19.12219996 16.80672269 24.37873545 22.24419179 25.70439941 9.54540031 G LPR 5.597394667 13.39435205 17.01741449 16.68314385 16.68314385 13.56944162 14.46995911 6.784720809 H LPR 14.05709343 12.97577855 15.85928489 16.70445054 18.41723407 17.30103806 18.4544406 15.02918458 I LPR 12.90246906 10.47168093 8.322018308 9.886307464 7.481529973 10.0054196 9.7788476 17.50457969 J LPR 10.81314879 12.74813331 19.06645011 17.30103806 14.8294612 14.46995911 12.87519112 9.886307464 K LPR 11.04321578 9.996155325 20.97095523 18.10573751 19.09080062 15.85928489 18.07571141 15.72821642 L LPR 11.07266436 2.414098334 11.27483379 8.749950284 11.53402537 7.4709028 12.24381155 10.27784439 M LPR 11.05344098 11.34948097 14.09714212 14.22003128 13.92522576 17.05029838 14.8294612 16.31240732 N LPR 12.21249746 10.64679265 9.383613864 2.402921953 9.436929852 10.04576404 9.570787013 5.767012687

Table A.2 Mean OPD scores for left radii of all 14 individuals by cross-section and quantified zone. LDR = left proximal radius, LMR = left midshaft radius, LDR = left distal radius

159

Zone Cadaver ID Cross-section Ant. Ant.Med. Med. Med.Pos. Pos. Pos.Lat. Lat. Ant.Lat. A RDR 0.037 0.032052632 0.027928571 0.0256 0.021133333 0.02275 0.027357143 0.028411765 B RDR 0.038142857 0.0542 0.045227273 0.037448276 0.039 0.037142857 0.046714286 0.050666667 C RDR 0.0864 0.0413 0.046368421 0.041769231 0.053923077 0.051 0.045166667 0.053555556 D RDR 0.029058824 0.02925 0.031928571 0.03148 0.031791667 0.034925926 0.03535 0.038083333 E RDR 0.039230769 0.03555 0.061833333 0.044818182 0.047235294 0.038941176 0.032846154 0.037111111 F RDR 0.020277778 0.027551724 0.028866667 0.02165 0.017 0.0176 0.023083333 0.016357143 G RDR 0.036230769 0.032277778 0.021357143 0.03475 0.030153846 0.034411765 0.034142857 0.029352941 H RDR 0.039764706 0.038571429 0.039142857 0.0405 0.039916667 0.0341875 0.03625 0.033368421 I RDR 0.022285714 0.0429375 0.033266667 0.027038462 0.021413793 0.028806452 0.0277 0 J RDR 0.0205 0.037636364 0.05475 0.024666667 0.028333333 0.042 0.03125 0.042125 K RDR 0.043666667 0.073857143 0.045125 0.0331 0.042222222 0.0505 0.045833333 0.047818182 L RDR 0.055375 0.039636364 0.0266 0.0372 0.035555556 0.034 0.046 0.040833333 M RDR 0.061111111 0.0537 0.059222222 0.044375 0.058 0.0513 0.047555556 0.053571429 N RDR 0.08 0.05975 0.045333 0.057154 0.0754 0.0338 0.091667 0.055833 A RMR 0.032025 0.03512766 0.035777778 0.033933333 0.028034483 0.023571429 0.031787879 0.031028571 B RMR 0.033939394 0.028097561 0.037133333 0.025064516 0.0295 0.024103448 0.034958333 0.03925 C RMR 0.039421053 0.048764706 0.042863636 0.031636364 0.0595 0.071833333 0.038473684 0.048954545 D RMR 0.028820513 0.036608696 0.034741935 0.0325 0.027 0.035189189 0.035551724 0.037 E RMR 0.047352941 0.04328 0.037130435 0.03945 0.05876 0.055666667 0.0381 0.039066667 F RMR 0.02465 0.025857143 0.024357143 0.02376 0.019689655 0.020884615 0.029241379 0.026678571 G RMR 0.039833333 0.036666667 0.033153846 0.027136364 0.047875 0.0238 0.029538462 0.028333333 H RMR 0.031966667 0.036864865 0.03175 0.03852 0.039939394 0.042806452 0.03525 0.036148148 I RMR 0.028416667 0.029357143 0.0399375 0.026714286 0.026625 0.032411765 0.045708333 0.033421053 J RMR 0.041916667 0.05225 0.036368421 0.030375 0.034111111 0.033083333 0.0338 0.033833333 K RMR 0.040391304 0.039133333 0.054142857 0.038357143 0.045857143 0.041 0.045590909 0.043818182 L RMR 0.049315789 0.043684211 0.047 0.03744 0.033923077 0.0374375 0.049263158 0.050235294 M RMR 0.036666667 0.052625 0.054 0.044272727 0.052647059 0.060555556 0.045636364 0.041111111 N RMR 0.05275 0.057727273 0.057666667 0.067916667 0.058272727 0.049166667 0.0557 0.054417 A RPR 0.013 0.055714286 0.022 0.0307 0.0315 0.032076923 0.036846154 0 B RPR 0.017 0.0275 0.035916667 0.0375 0.033055556 0.0451875 0.041428571 0.039714286 C RPR 0.0295 0.048555556 0.0449 0.0676 0.048857143 0.040181818 0.0894 0 D RPR 0.022375 0.020666667 0.034863636 0.039 0.0325 0.028923077 0.038142857 0.031444444 E RPR 0.0294 0.028 0.037 0.04295 0.036578947 0.035384615 0.033 0.0259 F RPR 0.012888889 0.016714286 0.029 0.0188 0.021666667 0.0305 0.020846154 0.018571429 G RPR 0.025428571 0.033625 0.0298 0.052444444 0.054 0.034777778 0.0435 0.017 H RPR 0.0094 0.039333333 0.0424 0.046411765 0.0376 0.0464 0.033625 0.037142857 I RPR 0.01 0.0322 0.033416667 0.044909091 0.0504 0.038933333 0.0378 0.0435 J RPR 0 0.0358 0.052833333 0.031 0.029666667 0.0402 0.038 0.011 K RPR 0.0186 0 0.035272727 0.049875 0.030363636 0.042375 0.043928571 0.044 L RPR 0.0385 0.043222222 0.041142857 0.0448 0.056714286 0.052333333 0.052875 0.030555556 M RPR 0.031285714 0.049333333 0.044 0.049090909 0.051875 0.049 0.043666667 0.0735 N RPR 0.0296 0.0266 0.05 0.0764 0.035428571 0.0624 0.0516 0.0605

Table A.3 Mean On.Ar scores for right radii of all 14 individuals by cross-section and quantified zone. RDR = right proximal radius, RMR = right midshaft radius, RDR = right distal radius

160

Zone Cadaver ID Cross-section Ant. Ant.Med. Med. Med.Pos. Pos. Pos.Lat. Lat. Ant.Lat. A LDR 0.036882353 0.032791667 0.037941176 0.035277778 0.03095 0.03195 0.030789474 0.033434783 B LDR 0.053411765 0.044571429 0.044111111 0.040266667 0.028375 0.033458333 0.0399375 0.048782609 C LDR 0.050571429 0.0338 0.042444444 0.053272727 0.052352941 0.033142857 0.0445625 0.0598 D LDR 0.030615385 0.02747619 0.0325 0.023894737 0.027032258 0.03625 0.025142857 0.030545455 E LDR 0.034521739 0.038103448 0.036 0.04225 0.036583333 0.033090909 0.039894737 0.042636364 F LDR 0.02173913 0.0234 0.021615385 0.019208333 0.021344828 0.0195 0.019740741 0.024470588 G LDR 0.039642857 0.032333333 0.037923077 0.031571429 0.030833333 0.038846154 0.037538462 0.033882353 H LDR 0.034388889 0.031904762 0.0385 0.0324 0.038764706 0.033608696 0.033647059 0.039470588 I LDR 0.032571429 0.0437 0.033333333 0.019466667 0.019 0.029666667 0.0243125 0 J LDR 0.069333333 0.03075 0.0335 0.037333333 0.038733333 0.025363636 0.0382 0.039625 K LDR 0.0491 0.050571429 0.038363636 0.045727273 0.039571429 0.0305 0.04325 0.035083333 L LDR 0.0496 0.044444444 0.065333333 0.0625 0.034833333 0.027666667 0.040833333 0.030666667 M LDR 0.0535 0.048142857 0.0505 0.0432 0.07 0.045333333 0.048857143 0.04125 N LDR 0.026 0.075666667 0.073555556 0.057375 0.049666667 0.0706 0.0742 0.077 A LMR 0.031241379 0.027058824 0.030565217 0.029411765 0.031428571 0.036074074 0.032821429 0.027 B LMR 0.026935484 0.035761905 0.03496 0.029694444 0.029441176 0.027176471 0.031 0.028651163 C LMR 0.045612903 0.0506875 0.049 0.036333333 0.044555556 0.038185185 0.048111111 0.046470588 D LMR 0.034137931 0.032066667 0.039107143 0.034153846 0.0284 0.031178571 0.031178571 0.0375 E LMR 0.03775 0.040571429 0.039241379 0.0399 0.065769231 0.051875 0.06075 0.052230769 F LMR 0.027090909 0.029354839 0.027291667 0.022756757 0.02332 0.027076923 0.023521739 0.025952381 G LMR 0.035176471 0.03175 0.02848 0.031142857 0.034857143 0.035625 0.0405 0.03464 H LMR 0.032785714 0.029933333 0.038115385 0.037826087 0.036782609 0.039818182 0.032888889 0.033677419 I LMR 0.0254 0.0340625 0.028461538 0.03536 0.03673913 0.02625 0.034533333 0.044727273 J LMR 0.040533333 0.050833333 0.0425 0.0385 0.03773913 0.029181818 0.052 0.0486 K LMR 0.048722222 0.043642857 0.043 0.045315789 0.042928571 0.04225 0.039333333 0.063230769 L LMR 0.033210526 0.044115385 0.03552 0.037304348 0.0467 0.040333333 0.04347619 0.045454545 M LMR 0.044045455 0.043266667 0.0638 0.0425 0.065615385 0.048866667 0.044666667 0.055352941 N LMR 0.0515 0.062308 0.064875 0.051727 0.068583 0.060222 0.060385 0.0698 A LPR 0.01175 0.028235294 0.0255 0.038071429 0.029428571 0.029529412 0.03105 0.020818182 B LPR 0.035 0 0.048666667 0.03447619 0.030235294 0.039153846 0.042909091 0.044461538 C LPR 0.014875 0.033857143 0.0565 0.0415 0.044111111 0.058 0.0427 0.049 D LPR 0.017 0.02925 0.045785714 0.029272727 0.030875 0.026222222 0.0365625 0.031647059 E LPR 0.024 0.035272727 0.021583333 0.034444444 0.033083333 0.045545455 0.0315 0.0335 F LPR 0.01525 0.016125 0.017333333 0.023222222 0.024923077 0.031307692 0.024375 0.0125 G LPR 0.043333333 0.0474 0.047 0.049428571 0.0459 0.033571429 0.0502 0.020333333 H LPR 0.064333333 0.0582 0.0521 0.058411765 0.047 0.038 0.024857143 0.063111111 I LPR 0.0145 0.024666667 0.04125 0.035125 0.035666667 0.022333333 0.049 0.025071429 J LPR 0.026333333 0.0665 0.029272727 0.041625 0.032666667 0.022 0.048 0.041666667 K LPR 0.036 0.03625 0.039166667 0.051125 0.045272727 0.051111111 0.038125 0.0498 L LPR 0.018 0.091 0.033333333 0.041666667 0.0529 0.0706 0.050285714 0.0635 M LPR 0.027714286 0.0547 0.0568 0.060142857 0.0666 0.037222222 0.0866 0.047909091 N LPR 0.0422 0 0.0335 0.03125 0.043429 0.0575 0.01975 0.0395

Table A.4 Mean On.Ar scores for left radii of all 14 individuals by cross-section and quantified zone. LDR = left proximal radius, LMR = left midshaft radius, LDR = left distal radius

161

Zone Cross-section Side Anterior AnteriorMedial Medial MedialPosterior Posterior PosteriorLateral Lateral AnteriorLateral Proximal Right 12.91175526 12.08523946 14.82631157 14.84082652 15.60143908 14.70163675 13.93116208 14.31790234 Left 12.64773891 10.99664096 14.64493034 13.92665249 15.77286347 14.79540256 14.74521295 12.52677884

Midshaft Right 17.80692841 16.74998017 15.84971142 18.18881701 17.91738462 18.45880528 17.03960231 17.51885915 Left 16.83865317 15.69232208 14.54583446 16.27779619 16.91185031 18.54772217 17.6268331 17.54962492

Distal Right 10.94778452 12.05771245 10.55341632 13.3311676 15.39127367 13.65543522 13.13141951 11.69267404 Left 10.6159247 11.80396268 10.68627582 11.66602121 14.19312479 13.31224693 12.03774118 12.28962187

Table A.5 Mean OPD scores for combined individuals by cross-section and quantified zone for both the left and right radii.

Zone Cross-section Side Anterior AnteriorMedial Medial MedialPosterior Posterior PosteriorLateral Lateral AnteriorLateral Proximal Right 0.020498441 0.032661763 0.038038992 0.045105801 0.039300462 0.041333813 0.043189927 0.030916327 Left 0.027877806 0.037246917 0.039127984 0.040697277 0.040149389 0.040149766 0.041136746 0.038772744

Midshaft Right 0.037676142 0.040431733 0.040430254 0.035505457 0.040123903 0.039393568 0.03918573 0.038806844 Left 0.036724452 0.039672374 0.040351238 0.036566159 0.042347107 0.038150945 0.041083304 0.043806275

Distal Right 0.043503157 0.042733638 0.040496409 0.035824987 0.038648485 0.03652612 0.040779738 0.037649134 Left 0.041562736 0.039832588 0.041830075 0.038838853 0.03700294 0.034926947 0.038636165 0.038331981

Table A.6 Mean On.Ar scores for combined individuals by cross-section and quantified zone for both the left and right radii.

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