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2017
Association of various concentrations of cat's claw herb (Uncaria tomentosa) on lymphocyte proliferation and nitric oxide expression: An in-vitro study of osteoarthritis
Noha Fadlalddin University of Northern Iowa
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2017
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ASSOCIATION OF VARIOUS CONCENTRATIONS OF CAT’S CLAW HERB
(UNCARIA TOMENTOSA) ON LYMPHOCYTE PROLIFERATION AND NITRIC
OXIDE EXPRESSION: AN IN-VITRO STUDY OF OSTEOARTHRITIS
An Abstract of a Dissertation
Submitted
In Partial Fulfillment
Of the Requirements for the Degree
Doctor of Education
Approved:
Dr. Catherine Zeman, Committee Chair
Dr. Patrick Pease Interim Dean of the Graduate College
Noha Fadlalddin
University of Northern Iowa
December, 2017 ABSTRACT
Uncaria tomentosa, also known as cat’s claw, is an indigenous herb which originates from the Amazon River basin and has proven to be highly effective via case report and limited epidemiological evaluation in the pallative treatment of a number of inflammatory conditions. The herb is particularly preferred on the American market due to its various uses for healing, which provides the impetus for this research. The herb is being used to treat osteoarthritis and claims have been made for its ability to: enhance the
repair of deoxyribonucleic acid (DNA), support joint health and improve immune
function, enable normal division of cells, and, thus, prevent proliferation of cancer.
Various studies have illustrated impacts on: cell death, inducible nitric oxide synthase
(iNOS gene) expression induced by lipopolysaccharide, the activation of TNFα, and NF-
kB, the formation of nitrates, and also the production of hormone prostaglandin (PGE2)
(Hardin, 2007; Sandoval et al., 2000; & Valerio & Gonzales, 2005). In this study, its
impact on lymphocytes (immunity) and potential long-term use implications to
osteoarthritis are explored.
The purpose of this study was to examine the association of cat’s claw at various
dosages on lymphocyte proliferation and nitric oxide expression in osteoarthritis patients.
This has implications for both the long-term safe use of the herb and provides valuable
information for osteoarthritis patients who may be currently using pharmaceutical
prescriptions to manage the condition. Osteoarthritis patients may have concerns about
side effects of those prescription medications and may be considering use of this herb to
supplement or replace prescription medications. Further, a brief survey of key demographics often associated with the etiology of osteoarthritis was used to explore any
possible relationships between these established risk factors and lymphocyte proliferation
and nitric oxide expression at differing treatments of cat’s claw exposure.
A total of 25 participants between ages 35 to 65 years old, with osteoarthritis,
were recruited as a convenience sample through distributed flyers and outreach at
physical therapy centers. Participants having any other immunological diseases were
excluded from participation as were individuals taking immunosuppressive drugs. This
study was designed using in-vitro cell culture techniques on cases serving as their own
controls at the 0 ppm dosage level. Additional treatment groups included 10, 100, 150,
250, and 450 ppm of pharmaceutical grade cat’s claw herb. This was done under both a
mitogen stimulated and non-stimulated treatment condition in standard micro-cell well
plates. Following incubation, the cells were analyzed through flow cytometry for
proliferation counts and through additional assay tagged procedures and flow cytometry
for nitric oxide expression.
While descriptive findings illustrate some strong directional tendencies between
various demographic factors and cell proliferation/nitric oxide expression and simple
linear regression illustrated a difference in means, more advanced ANOVA did not
illustrate significance. ANOVA tests examining the relationship between decreased
lymphocyte proliferation and decreased nitric oxide expression at the various treatment levels did not illustrate a significant relationship. Therefore, the exact biomolecular mechanism of action for cat’s claw herb is not through these modalities. Given the small sample size of this study and trends in the data, larger samples exploring the full panel of both pro and anti-inflammatory cytokines associated with osteoarthritis should be conducted. It also suggests the possibility that the herb may be having direct effects on pain receptors which should also be investigated.
ASSOCIATION OF VARIOUS CONCENTRATIONS OF CAT’S CLAW HERB
(UNCARIA TOMENTOSA) ON LYMPHOCYTE PROLIFERATION AND NITRIC
OXIDE EXPRESSION: AN IN-VITRO STUDY OF OSTEOARTHRITIS
A Dissertation Submitted in Partial Fulfillment
Of the Requirements for the Degree of
Doctor of Education
Approved:
Dr. Catherine Zeman, Chair
Dr. Michele Devlin, Committee Member
Dr. Robin Lund, Committee Member
Dr. Gowri Betrabet, Committee Member
Noha Noor Fadlalddin
University of Northern Iowa
December, 2017 ii
DEDICATION
This doctoral dissertation is dedicated to: 1) my soul and beloved parents, Noor and Nadia, for endless prayers, immeasurable care, commitment, and values they instilled in me during my upbringing. Also, for their support of taking care of my family, specially my children, during all of my school life. 2) My devoted husband Fahad, and to our dear children Omar, Nabeel, and Yousuf, for their numerous lifestyle sacrifices they individually made to permit this degree to become a reality; and my youngest son
Abdalmalik for the joy he brought me throughout the process-the desire to get the task accomplished. 3) To my beloved sisters, Nedaa and Naima, for supporting me by their love. 4) And, to Dr. Catherine Zeman, my chair, who worked endlessly, no matter the time of day, to support me in my endeavors to achieve this milestone. My heartfelt appreciation goes out to her. Without her dedication and support, this work would not have been successfully accomplish. Finally, I express my gratitude to king Abdullah Bin
Abdul-Aziz may God bless his soul for giving me this opportunity to accomplish my dad’s dream and my dream to complete my doctoral degree. I am very grateful for getting all the support that I needed to complete my degree. My deepest love is extended to all of them.
iii
ACKNOWLEDGEMENTS
First and foremost, I would like to express my heartfelt gratitude to Dr. Catherine
Zeman, my dissertation Chair for her support, assistance, and guidance in this research project. I am grateful for the time and knowledge that Dr. Zeman provided in putting together all my research projects. I shall remember the countless support given to me by her throughout the research process.
Special thanks goes out to all my Committee Members, Dr. Michele Devlin, Dr.
Robin Lund, and Dr. Gowri Betrabet, to have such a highly dedicated team of academics, providing me with full support on research was a supreme gift in itself. I sincerely thank my dissertation committee for supporting me to complete this work.
This study would not have been successfully undertaken without the cooperation of the staff at Student Health Clinic at the University of Northern Iowa, and their help in scheduling my participants for blood draws. My heartfelt thanks for them to making this research project successful. I would like also to acknowledge Ms. Junu Shrestha, doctoral student at UNI, for helping with my methodology process and Ms. Theodora Jn Baptiste, doctoral student at UNI, for helping edit my dissertation. I would like to acknowledge the
Recycling and Reuse Technology Transfer (RRTTC) at the University of Northern Iowa
(UNI) for providing funding and opportunity to be a part of this institution.
I cannot end the thanks to those beloved members of my family, particularly, my parents and my sisters for their endless support, prayers, and encouragement. A sincere and heartwarming level of appreciation goes to my immediate family; my husband, iv
Fahad and my children, Omar, Nabeel, Yousuf and Abdalmalik, for tolerating my absence during the days and sometimes during the nights, to accomplish my goal and my parents’ dream for me to achieve my doctorate degree. To friends and colleagues who prayed continuously for me, many thanks to all of you.
Finally, I would like to thank all the participants for their willingness and tenaciousness in being involved with this study. I am thankful that they provided me with their valuable time to fill out the questionnaire and provide their blood sample to work on my project.
v
TABLE OF CONTENTS
PAGE
LIST OF TABLES ...... xiii
LIST OF FIGURES ...... xiv
ABBREVIATIONS ...... xv
CHAPTER 1: INTRODUCTION ...... 1
Purpose of the Study ...... 8
CHAPTER 2: LITERATURE REVIEW ...... 9
Pathophysiology of Osteoarthritis ...... 12
Osteoarthritis Effects on Other Joint Tissues and Bones ...... 16
Subchondral Bone ...... 16
Bone Marrow Lesions ...... 17
Risk Factors ...... 17
Aging ...... 17
Abnormal Loading and Repetitive Injury ...... 18
Genetic Factors ...... 20
Gender...... 21
Lifestyle ...... 22 vi
Environment and Osteoarthritis ...... 22
Impacts of Osteoarthritis ...... 25
Clinical Features of Osteoarthritis ...... 28
Diagnostic Procedures ...... 29
Treatment ...... 30
Non-Pharmacologic Therapies ...... 30
Pharmacological Therapy ...... 33
Surgery ...... 35
Cat’s Claw (Uncaria Tomentosa) ...... 36
Background of Cat’s Claw (Uncaria Tomentosa) Use ...... 37
Historical and Most Common Uses of Cat’s Claw ...... 38
Antioxidant and Anti-Inflammatory Properties of the Cat’s Claw Herb...... 39
Cat’s Claw (Uncaria Tomentosa) and Osteoarthritis ...... 41
Overview of the Relationship between Cat’s Claw and Osteoarthritis ...... 41
Cat’s claw Action in the Treatment of Osteoarthritis ...... 42
Benefits of Using Cat’s Claw (Uncaria Tomentosa) in the Treatment of
Osteoarthritis ...... 43
Cat’s Claw and Implication for Osteoarthritis ...... 44
Health Impacts of Cat’s Claw on Slowing Progression of Osteoarthritis ...... 45 vii
Cat’s Claw and Osteoarthritis: Studies and Research ...... 46
Negative-Side Effects of Cat’s Claw ...... 49
CHAPTER 3: METHODOLOGY, RESEARCH HYPOTHESES, QUESTIONS, AND
OBJECTIVES ...... 52
Null Hypotheses ...... 52
Alternate Hypotheses ...... 53
Research Questions ...... 53
Objectives ...... 54
Significance of the Study ...... 54
Limitation ...... 55
Methodology ...... 55
Study Design ...... 55
Participant Selection ...... 59
Details of Questionnaire Survey ...... 60
Laboratory Preparation Prior to Analysis ...... 60
Preparing Chemicals ...... 61
Contamination Quality Control/Evaluation ...... 61
Statistical Analysis ...... 62
Equipment Quality Control and Assurance ...... 63 viii
Muse System Check ...... 63
Incubator Cleaning and Disinfecting ...... 63
Pipettes Calibration ...... 63
CHAPTER 4: RESULTS ...... 64
Demographic Information ...... 64
Age and Body Mass Index (BMI) ...... 64
Gender...... 65
Medication Information ...... 65
Herbs, Vitamins, and Pharmaceutical Exposure ...... 65
Health Information ...... 67
Cold or Flu, Life Change or Loss, Allergies, and Immunological Diseases ...... 67
Osteoarthritis History ...... 68
Length of Osteoarthritis ...... 68
Family History of Osteoarthritis ...... 69
Injuries ...... 70
Pain Severity ...... 70
Physical Activity ...... 72
Lymphocytes Proliferation Statistical Results ...... 73 ix
Association of Various Concentrations of Cat’s Claw on Lymphocytes
Proliferation ...... 73
Nitric Oxide Expression Statistical Trends ...... 76
Association of Various Concentrations of Cat’s Claw on Nitric Oxide Expression .. 76
Proliferation Response Quotient by Cat’s Claw Treatment ...... 82
Nitric Oxide Quotient of Live Cells by Cat’s Claw Dosages ...... 83
Nitric Oxide Quotient of Dead Cells by Cat’s Claw Dosages ...... 84
Nitric Oxide Quotient of Total Cells (live and dead) by Cat’s Claw Dosages ...... 85
CHAPTER 5: DISCUSSION, CONCLUSIONS, AND RECOMMENDATIONS ...... 86
Discussion ...... 86
Lymphocytes Proliferation and Osteoarthritis ...... 87
Nitric Oxide Expression and Osteoarthritis ...... 87
Aging and Osteoarthritis ...... 88
BMI and Osteoarthritis ...... 89
Gender and Osteoarthritis ...... 89
Herbs and Osteoarthritis ...... 90
Vitamins and Osteoarthritis ...... 90
Nonsteroidal Anti-inflammatory Drugs (NSAIDs) and Osteoarthritis ...... 91
Joint Steroid Injection and Osteoarthritis ...... 93 x
Stress, Depression and Osteoarthritis ...... 93
Environmental Triggers and Osteoarthritis ...... 94
Family History and Osteoarthritis ...... 95
Common Pain Areas in Osteoarthritis Patients ...... 96
Physical Limitation and Osteoarthritis ...... 97
Physical Activity and Osteoarthritis Patients ...... 98
ANOVA Analysis of Quotient of Proliferation and Nitric Oxide Expression by Cat’s
Claw Treatment ...... 100
Conclusions and Recommendations ...... 101
REFERENCES ...... 104
APPENDIX A: IRB LETTER ...... 120
APPENDIX B: INVITATION FLYER ...... 121
APPENDIX C: PARTICIPANT INFORMED CONSENT ...... 122
APPENDIX D: QUESTIONNAIRE ...... 125
APPENDIX E: PROJECT CHECKLIST ...... 130
APPENDIX F: MAKE RPMI* MIXTURE ...... 131
APPENDIX G: MAKE RPMI+ MIXTURE ...... 132
APPENDIX H: RECONSTITUTE PHYTOHAEMAGGLUTININ (PHA) ...... 133
APPENDIX I: MAKE CAT’S CLAW SOLUTION ...... 135 xi
APPENDIX J: PREPARATION OF PERIPHERAL BLOOD MONONUCLEAR
CELLS ...... 139
APPENDIX K: UNITED STATES PHARMACOPEIA (USP) CERTIFICATE ...... 142
APPENDIX L: MATERIAL SAFETY DATA SHEET ...... 145
APPENDIX M: SEPARATION OF BLOOD COMPONENTS ON A FICOLL-
HYPAQUE GRADIENT ...... 149
APPENDIX N: TISSUE CULTURE PLATE ...... 150
APPENDIX O: PREPARING NITRIC OXIDE TEST ...... 151
APPENDIX P: TISSUE CULTURE PLATE OF NITRIC OXIDE TEST ...... 152
APPENDIX Q: TISSUE CULTURE PLATE OF NITRIC OXIDE TEST UNDER THE
TISSUE CULTURE SCOPE ...... 153
APPENDIX R: COUNTS AND VIABILITY TEST...... 154
APPENDIX S: TISSUE CULTURE PLATE OF COUNTS AND VIABILITY TEST .. 155
APPENDIX T: TISSUE CULTURE PLATE OF COUNTS AND VIABILITY TEST
UNDER THE TISSUE CULTURE SCOPE ...... 156
APPENDIX U: ASPETIC TECHNIQUE FOR THE LABORATORY WORK ...... 157
APPENDIX V: USING MUSE UNIT FOR NITRIC OXIDE TEST ...... 158
APPENDIX W: USING MUSE UNIT FOR COUNTS AND VIABILITY TEST ...... 159
APPENDIX X: STATISTICAL ANALYSIS ...... 160 xii
X1: Distribution analysis of demographic information...... 160
X2: Distribution analysis of medication information ...... 163
X3: Distribution analysis of health information ...... 170
APPENDIX Y: PROLIFIRATION STATISTICAL RESULTS ...... 181
APPENDIX Z: NITRIC OXIDE STATISTICAL RESULTS ...... 241
APPENDIX AA: ANOVA TEST OF PROLIFERATION RESPONSE QUOTIENT BY
CAT’S CLAW DOSAGE ...... 319
APPENDIX BB: ANOVA TEST OF NITRIC OXIDE LIVE CELL RESPONSE
QUOTIENT BY CAT’S CLAW DOSAGE ...... 321
APPENDIX CC: ANOVA TEST OF NITRIC OXIDE DEAD CELL RESPONSE
QUOTIENT BY CAT’S CLAW DOSAGE ...... 323
APPENDIX DD: ANOVA TEST OF NITRIC OXIDE TOTAL CELL (LIVE AND
DEAD CELLS) RESPONSE QUOTIENT BY CAT’S CLAW DOSAGE ...... 325
xiii
LIST OF TABLES
TABLE PAGE
1: Distributions among age, weight, and height ...... 64
2: Health information among participants ...... 68
3: Pain severity among participants ...... 71
4: Descriptive trends between demographics, cat's claw treatments and lymphocyte
proliferation ...... 75
5: Statistically significant associations between demographics, cat’s claw treatments and
lymphocytes proliferation, bivariate fit...... 76
6: Descriptive trends between demographics, treatment levels, and nitric oxide
expression ...... 80
7: Statistically significant associations between demographics, cat's claw treatments and
nitric oxide expression, bivariate fit ...... 81
8: ANOVA of proliferation response quotient by cat's claw treatments ...... 82
9: ANOVA of nitric oxide live cells response quotient by cat's claw treatments ...... 83
10: ANOVA of nitric oxide expression, dead cells quotient by cat's claw treatments ...... 84
11: ANOVA of nitric oxide response, total cells, quotient by cat's claw treatments ...... 85
xiv
LIST OF FIGURES
FIGURE PAGE
1: Number of population with osteoarthritis compared to a total number of population ....4
2: Flowchart of research design ...... 58
3: Gender distribution of study participants ...... 65
4: Distributions among herb, vitamin, prescribed medication, and joint steroid
injection ...... 66
5: Distributions among common herbs, vitamins, and medications...... 67
6: Common allergies among participants ...... 68
7: Length of osteoarthritis among participants...... 69
8: Family history of osteoarthritis among participants ...... 69
9: Common injuries among participants ...... 70
10: Specific pain areas among participants ...... 71
11: Physical activity among participants ...... 72
12: ANOVA test of proliferation response quotient by cat's claw dosage ...... 82
13: ANOVA test of nitric oxide response quotient (live cells) by cat's claw
treatments ...... 83
14: ANOVA test of nitric oxide response quotient (dead cells) by cat's claw
treatments ...... 84
15: ANOVA test of nitric oxide response quotient (total cells) by cat's claw
treatments…………………………………………………………………………...85
16: Isolation of whole mononuclear cells from peripheral blood and cord blood ...... 149 xv
ABBREVIATIONS
ACL: Anterior Cruciate Ligament
AIDS: Acquired Immune Deficiency Syndrome
AZT: Zidovudine (Anti-HIV Drug)
B-FGF: Fibroblast Growth Factor
BMI: Body Mass Index
CDC: Center for Disease Control
C-MED-100: Novel Proprietary Extract of the Uncaria tomentosa
CO2: Carbon dioxide
COX-2: Cyclooxygenase-2 Inhibitors
CWA: Clean Water Act
DF: Degree of Freedom
DNA: Deoxyribonucleic acid
FDA: Food and Drug Administration
HBSS: Hank’s Balanced Salt Solution
HIV: human Immunodeficiency Virus
IGF: Insulin-Like Growth Factor
IL: Interleukin xvi
iNOS gene: Nitric Oxide Synthase
IRB: Institutional Review Board
MCF7: Proliferation of a Human Breast Cancer Cell Line
MMPs: Matrix Metalloproteases
NF-ĸB: Nuclear Factor-Kappa-Beta
NO: Nitric Oxide
NSAIDs: Non-Steroidal Anti-Inflammatory Drugs
OA: Osteoarthritis
PBMCs: Peripheral Blood Mononuclear Cell
PBS: Phosphate Buffered Saline
PGE2: Production of Hormone Prostaglandin
PHA: Phytohaemagglutinin
POA: Pentacyclic Oxindole Alkaloids
RPMI: Roswell Park Memorial Institute medium
RPM: Revolution per Minute
SAMe: S-Adenosylmethionine
SHC: Student Health Center
SLE: Systemic Lupus Erythematosus xvii
TGF : Transforming Growth Factor
𝛽𝛽 𝛽𝛽 TIMPs: Tissue Inhibitors Metalloproteinases
TNFa: Tumor Necrosis Factor-Alpha
TOA: Tetracyclic Alkaloids
USP: United States Pharmacopeia
UV: Ultra Violet
YMCA: Young Men's Christian Association
7- AAD: Dead Cell Marker
µl: Microliter 1
CHAPTER 1
INTRODUCTION
Osteoarthritis (OA) is a chronic disease where the joints of the affected person degenerate leading to adult disability. It is a condition which affects the entire joint by degrading articular cartilage. Articular cartilage is a combination of collagen, water, proteoglycans, and chondrocytes. Chondrocyte components control the cell matrix of the cartilage by turnover of the matrix (Sandell & Aigner, 2001). The destruction of the cartilage leads to friction and fibrotic conversion of articulating cartilage in synovial joints such as the knees, hips, hands, and lower spine region, resulting in pain and stiffness in the joints; which undermines the individual's mobility (Dieppe & Lohmander,
2005). Since osteoarthritis is not curable, the only option offered in contemporary medical care is its management.
Osteoarthritis is the most common type of arthritis that weakens the whole joint.
According to the Centers for Disease Control and Prevention, 52.5 million adults around
the world have arthritis. The number of osteoarthritis patients in the United States
increased from 21 million in 1990 to 26.9 million in 2005 (CDC, 2017). In the United
States, U.S. health care costs for this condition where an estimated $82.4 billion per year
(Tanna, 2004).
Pharmacological therapy such as non-steroidal anti-inflammatory drugs
(NSAIDs), Cyclooxygenase-2 (COX-2) inhibitors and Viscosupplements-Hyaluronic acid, are used in pain management (Goldberg, Von Feldt, & Lonner, 2002). However, the 2
side effects of non-steroidal anti-inflammatory drugs (NSAIDs) can lead to gastrointestinal and cardiovascular problems and steroid use is associated with
hypertension, neurological and psychological effects (Slipman, 2008). The side effect
associated with COX-2 inhibitors is gastrointestinal toxicity, while hyaluronate is
associated with hypertension upon long term consumption (Mukherjee, Nissen & Topol,
2001).
Complementary and alternative supplements are increasingly being used to diversify the health care and medication options for osteoarthritis patients. This allows for improved healthcare outcomes by minimizing drug side effects (Synovitz & Larson,
2012). People use alternative supplements, particularly natural herbs, to treat or improve the management of some diseases, such as osteoarthritis, that they perceive are ineffectively tackled using conventional methods. Cat’s claw is one of the alternative supplements that has been used to treat osteoarthritis symptoms (Johnson, Sohn, Inman,
Bjeldanes, & Rayburn, 2013).
Cat's claw, which is scientifically known as Uncaria tomentosa, has been historically used to treat and prevent inflammatory disorders, particularly osteoarthritis
(Khanna et al. 2007). Traditionally, it has been used to treat chronic viral infections, bacterial infections, numerous inflammatory and immunological disorders, asthma, dysentery, cancers, arthritis, and as a birth control agent (Heitzman, Neto, Winiarz,
Vaisberg, & Hammond, 2005). Nutraceuticals, including food or products containing cat’s claw, can be used to prevent and modify symptoms in osteoarthritis patients. So, cat’s claw is possibly effective in reducing the pain in patient’s joints (Hardin, 2007). 3
This in-vitro study will examine the impact of cat’s claw (Uncaria tomentosa), a herbal
treatment, that is reported to provide anti-inflammatory benefits, without major side
effects, to identify effect differences between exposed and non-exposed cells on nitric
oxide stress, and lymphocyte characteristics proliferation. Using quantitative research
methodology, the aim is to compile the data and information that would assist in
increasing existing knowledge and awareness, and encourage further research which will
assist in exploring the potential of cat’s claw in treating osteoarthritis patients.
A total of 25 participants between ages 35 to 65 years old, with osteoarthritis,
were selected as a convenience sample by invitation and distributed flyers. Participants
were excluded who hand other immunological diseases or major immunological
stressors, except osteoarthritis, and who were using drugs that altered the immune
response. This study is designed using an in-vitro, self-control approach. Each
participant’s lymphocytes serving as their own control at the 0 ppm treatment level. The
remaining cells were treated with cat’s claw at 10, 100, 150, 250 and 450 ppm.
Osteoarthritis is among the highest-ranking musculoskeletal disease accounting
for 50% of disease burden in this category. Osteoarthritis of the knee is expected to
become the fourth major cause of disability in women (Jordan et al., 2003). Destruction
of the articular cartilage occurs when catabolic enzymes release and decrease the
production of chondrocytes which ultimately breaks down the matrix. During the
breakdown of the matrix, inflammatory cytokines are released such as Interleukin-1 (IL-
1), Interleukin-17 (IL-17), Interleukin-18 (IL-18), Interleukin-15 (IL-15), Interleukin-6
(IL-6), Interleukin-1(IL-1), and tumor necrosis factor alpha (TNFα) (Wojdasiewicz, 4
Poniatowski, & Szukiewicz, 2014). According to Hardin (2007), nitric oxide (NO) and
Nuclear factor-kappa-beta (NF-ĸB) are also released during the breakdown of the matrix.
Hardin (2007) describes NF-ĸB as a biomolecule which, “regulates genes involved in the inflammatory process. NF-ĸB regulates the production of matrix metalloproteases
(MMPs) by chondrocytes. During injury, chondrocytes release MMPs, which degrades the matrix” (2007, p.26).
According to Tanna (2004), prevalence rates of osteoarthritis are varied across the world. Overall, osteoarthritis affects 13.9% of adults aged 25 years and older and 33.6% of adults aged 65+. In the United Kingdom, an estimated 10% to 15% of adults above the age of 60 have osteoarthritis. In Canada, it is estimated that over 4 million people have arthritis. Over 41 million people out of 321 million people have arthritis in the U.S.
(American Public Health Association, 2016). The healthcare cost of osteoarthritis is estimated at $82.4 billion each year in the United States and $18 billion per year in
Canada (See Figure 1).
Figure 1: Number of population with osteoarthritis compared to a total number of population. (Source: Tanna, 2004) 5
According to Miller and colleagues (2005), osteoarthritis is usually a very painful
joint condition affecting millions of people in the world. Patients with osteoarthritis
suffer from pain and loss of function. The management of osteoarthritis is aimed at
reducing pain, inflammation, slow degradation of cartilage, and improving function.
Prevention of osteoarthritis includes non-pharmacological treatment, pharmacological
treatment, intra-articular treatment, and surgical treatment (Tanna, 2004).
Non-pharmacological treatment of osteoarthritis includes education, exercise,
nutrition, weight loss, and physical aides such as knee braces (Jordan et al. 2003).
Effective education techniques such as individualized education, group education, and
patient coping skills was found to be 20% as effective as NSAIDs in reducing joint pain
(Walker-Bone, Javaid, Arden, & Cooper, 2000). According to Tanna (2004), the effect of exercise on osteoarthritis is considered the most significant intervention. Exercise improves motion, joint flexibility, and muscle strength and endurance. Weight loss reduces pain and the risk of developing symptomatic osteoarthritis in women (Tanna,
2004).
Pharmacological therapy controls pain and improves function. However, it does not provide a cure and can produce side-effects from drug therapy (Gamble, Wyeth-
Ayerst, Johnson, Searle & Beecham, 2000). For example, paracetamol and acetaminophen are used in pain management but provide no cure. Non-steroidal anti- inflammatory drugs (NSAIDs) are recommended for patients who are unresponsive to paracetamol. Cyclooxygenase-2 (COX-2) inhibitors are also used in pain management. 6
Corticosteroids and glucocorticoids are used in management of knee arthritis to reduce
inflammation of swollen joints. Viscosupplements such as hyaluronan and hylan G-F 20 are also used in management of knee osteoarthritis (Goldberg et al., 2002). However, the side effects of Non-steroidal anti-inflammatory drugs (NSAIDs) can lead to gastrointestinal and cardiovascular problems, while those of steroidal origin lead to
increased hypertension and neurological and psychological effects (Slipman, 2008). In
addition, the side effects associated with COX-2 inhibitors is the gastrointestinal toxicity
while hyaluronate is associated with hypertension upon long term consumption
(Mukherjee et al., 2001).
The prevalence of osteoarthritis, lack of cure from pharmacological therapy, and
therapy’s adverse effect on the patient, among other issues, have increased the interest on
the part of patients to use complementary and alternative supplements. Cat’s claw is one of the identified alternative supplements that has been used for the treatment of many health conditions including osteoarthritis and rheumatoid arthritis (Vitetta, Cicuttini, &
Sali, 2008). In 1997, cat’s claw herb ranked as the seventh most important herb in the
U.S. as an alternative supplement (Chauhan, Singh, Bajaj, & Chauhan, 2015). According to Schulman and Dean (2006), cat’s claw is possibly effective in reducing the pain and stiffness in patients’ joints, improving function, and reducing the need to use
pharmacological treatment.
It is hypothesized that the bio-pharmacological activities of cat’s claw results
from the presence of many secondary metabolites. Cat's claw contains two different
alkaloidal constituents: pentacyclic oxindoles and tetracyclic oxindoles (Montoro, 7
Carbone, de Dioz Zuniga Quiroz, De Simone, & Pizza, 2004). The most active constituent alkaloid in cat's claw is pentacyclic oxindole. It appears to have an immune regulating factor that produces immunomodulatory and anti-inflammatory effects through some, as yet, unspecified means (Vitetta, Cicuttini, & Sali, 2008). Pentacyclic alkaloids can stimulate white blood cells to surround and destroy pathogens through phagocytosis
(Talbott, 2003). Pentacyclic alkaloids from cat's claw extract was tested clinically for 24 weeks in a double-blind of 40 patients with active rheumatoid arthritis. Placebo versus cat’s claw extract of 60 mg showed a reduction in the tender joints in patents with RA
(53.2% vs 24.1%). The study reported minor side effects such as diarrhea and dyspepsia in three subjects (0.0075%). The extract was considered to be well tolerated (Mur,
Harting, Eibl, & Schirmer, 2002). Another study showed that the ingestion of freeze- dried cat’s claw relieves knee pain experienced during physical activities within four weeks of treatment (Piscoya et al., 2001).
According to available animal toxicological studies, cats’ claw has not been associated with severe toxicity from oral intake. However, it could have side effects such as mild diarrhea, constipation, mild lymphocytosis, or digestive upset (Kuhn & Winston,
2008). The use of cat’s claw should be avoided during pregnancy or by those wishing to have children because of its traditional use as a contraceptive (Valerio & Gonzales,
2005). It should also be avoided for children under three years old because of its unknown pharmacokinetics and toxicity in that age cohort (Vitetta, Cicuttini, & Sali,
2008). It is clear that individuals are utilizing cat’s claw to self-medicate for osteoarthritis and finding relief through use of the herb, given the limited amount of 8
research and the need to understand precise biomolecular mechanisms of its action, this study on the impacts of cat’s claw to innate immunity (lymphocytes) is timely.
Purpose of the Study
According to Vitetta and other researchers (2008), there is a need for studies which test the effectiveness of the recommended doses of cat’s claw because the precise biomolecular action and interactions with immunity are not entirely clear. While past studies have shown that cat’s claw is a possible treatment for some health conditions including osteoarthritis, more understanding is needed.
This alternative supplement has proved to be a potential palliative treatment with minimal adverse effects for most users, a solution that the current medical treatment has not been able to offer (Rosenbaum, O"Mathuna, Chavez & Shields, 2010). In fact, pharmacological treatment increased the risk of gastrointestinal toxicity, hypertension, congestive heart failure, and liver injury (Tanna, 2004). If the effective mechanisms of action can be further elucidated, this would assist in reducing doubts about the mechanisms of action for the alternative supplement and the safety of its long-term use, perhaps increasing the number of patients treated using the alternative. In regard to long- term use side effects, cat’s claw has mild to moderate gastrointestinal effects that have been reported such as nausea, diarrhea, gas, and bloating (Kuhn & Winston, 2008).
However, studies to date do not discuss its impact on lymphocyte suppression and long- term immune system vigor which could have implications for its long-term safe use.
9
CHAPTER 2
LITERATURE REVIEW
Osteoarthritis remains one of the greatest challenges faced by the global health system. The disease features in the list of the top five causes of disability, especially for people with family history of arthritis, the elderly and professional sports players.
Globally, osteoarthritis sufferers increased from 10.5 million in 1990 to 17.1 million in
2010 (Cross et al., 2014). The annual estimated costs for direct and indirect osteoarthritis- related treatments is $128 billion, including drugs, non-pharmacological procedures, and surgeries (Fuller‐Thomson, Stefanyk, & Brennenstuhl, 2009). Such costs are greater in developing countries where members do not have access to information about the disease. Therefore, understanding the pathophysiology of osteoarthritis plays a leading role in minimizing its adverse impacts.
Osteoarthritis attacks the joint causing chronic pain, stiffness, and swelling. It often degenerates the entire articular cartilage. This is a specialized connective tissue comprising collagen, water, chondrocytes, and proteoglycans that provides a surface for smooth articulation as an individual walks, runs, or stretches (Leung, Rainsford, & Kean,
2013). Normal joints move easily, the opposing articular surface does not create friction and distribute the load unevenly across the tissues; unlike in patients with osteoarthritis.
The proper joint functioning relies on its biomechanical properties. The joints have several composites, such as subchondral bones, connective tissues, ligaments, cartilage surfaces, and capsule. The bone plates define the shape whereas the articular surface together with the synovial membrane, cells, and capsules, regulate the biological 10
functions such as synthesis and absorption of enzymes and other chemicals during
movements. The ligaments control the mechanical stability and flexibility while the
synovial membrane secretes the enzymes (cytokines, growth factors) and hyaluronic acid
(McAlindon et al., 2014).
Osteoarthritis destroys the cartilage in the synovial joints, such as in the hands,
knees, and spinal cord, which in turn leads to pain and stiffness (Omoigui, 2007).
Osteoarthritis ranks among the most prevalent musculoskeletal diseases accounting for
50% of disease burdens in this category. Researchers believe that the incidences of
osteoarthritis will increase significantly and have greater effects on U.S. society as the baby boomer generations are reaching middle and old age. Not all countries experience the same prevalence rates as the Centers of Disease Control and Prevention’s (CDC) statistics show that over 52.2 adults have arthritis globally and prevalence is not
consistent, the U.S. having one of the higher rates. For example, the number of the United
States’ citizens with this chronic type of arthritis increased from less than 21 million in
1990 to 27 million in 2005 (CDC, 2017).
Overall, 13.9% of adults aged between 25 and 64 years old and 33.6% (12.4
million) aged above 65years old have osteoarthritis (CDC, 2017). Similarly, between 10
and 15% of United Kingdom citizens are osteoarthritis patients, while about 4 million
(11%) Canadians have the condition. Consequently, osteoarthritis places a heavy burden
on a country’s health care system. Given that osteoarthritis cure and cause are not known,
the disease is one of the greatest debilitating, chronic concerns facing the global health
system. 11
This chronic disease is not curable. However, patients who comply with the
recommended treatment and management plan report better health outcomes than their
counterparts that may lack access to proper medical care. As such, these management procedures aim at reducing inflammation, pain, and slowing the degradation of cartilage.
Pharmacological therapy such as non-steroidal anti-inflammatory drugs (NSAIDs) and viscosupplements-Hyaluronic acid help such patients in pain management (Allen &
Golightly, 2016; Man & Mologhianu, 2014).
Osteoarthritis is also associated with regular hospitalizations and mortality. It constitutes the majority or arthritis related hospitalizations (69.9%) accounting for 814,
900 hospitalizations in 2006. (Lethbridge-Cejku, Helmick, & Popovic, 2003).
Osteoarthritis sufferers with comorbidities such as cardiovascular disease and dementia experience death rates that are more than 1.6 times higher than those for individuals without the osteoarthritis co-diagnosis (Silverwood et al., 2015). Individuals with osteoarthritis incur substantial expenses in related procedures, such as hip and knee joint replacement procedures. According to Kurtz and his partners (2011), the statics reveal that knee replacement surgeries tripled in the U.S. between 1990 and 2003. The percentage of female patients who underwent knee replacement surgeries was 62.4% and the percentage of patients under 65 years old was 43.6%.
12
Pathophysiology of Osteoarthritis
As explained by Hardin (2007), the disease is a common degenerative joint condition that affects over 20 million adults in the U.S.. Research reports that by the time individuals reach the age of 40 years, about 90 percent of them are expected to have radiographic properties in joints that bear weight which is an indication of osteoarthritis
(Hardin, 2007). Degenerative joint disease is reported to affect some or all of the metacarpophalangeal, interphalangeal, spine, cervical as well as carpometatarsophalangeal joints (Hardin, 2007; Malemud, Islam, & Haqqi, 2003). On the other hand, the secondary category of such diseases can be seen in any joint due to acute or chronic articular trauma. Also, several factors such as biomechanical, proteases, and pro-inflammatory mediators influence the pathophysiology of osteoarthritis. In the past, researchers viewed osteoarthritis in terms of cellular inflammation that resulted from the increase in leukocytes in the affected joint. The scholars categorized the condition with other rheumatoid arthritis that resulted whenever the number of leukocytes exceeded
1000 cells per milliliter (Allen & Golightly, 2015).
However, recent studies indicate that synovial inflammation characterizes osteoarthritis. The inflammation in osteoarthritis does not only occur through nitric oxide inflammatory pathways but is also triggered, impacted or moderated by chemokines and cytokines (Silverwood et al., 2015). The proinflammatory mediators trigger the manufacturing of proteolytic enzymes that degrades the extracellular matrix. Also, mechanical factors, wear and tear, and excessive joint loading all play significant roles in the joint tissue destruction. 13
In simple terms, osteoarthritis is a disease that attacks the cartilage, a viscoelastic tissue
that controls movement and other functions of the joints. The cartilage has three
components including the cellular, liquids, and solid phase portions that account for 1-
2%, 70% - 80%, and 20% - 30% respectively of the tissue. When cells are injured the
breakdown of the articular cartilage cell matrix releases cytokines (catabolic mediators).
Examples of cytokines include: Interleukin-1 (IL-1), tumor necrosis factor alpha (TNFα),
and also nitric oxide (NO), and they are all triggered by the inflammatory cells,
synoviocytes, chondrocytes and fibroblasts (Hardin, 2007; Malemud et al., 2003). It is
essential to note that joint injury is a complicated event that usually involves acute trauma
of the cartilage. After cartilage injury various effects arise such as cell death (apoptosis,
necrosis, or even both), production of cartilage proteoglycans, and also increased
sensitivity to cytokines (Hardin, 2007). Due to the inflammatory response upon the
release of nitric oxide and inflmmatory cytokines there is increased water content in tissues leading to swelling, pain and eventually, decreased mechanical functionality. As
further elaborated by Hardin (2007), the pathophysiology of this form of arthritis
involves continuous injury which is followed by repair, and over time, there is failure to
repair, and lastly, there is the destruction of the cartilage.
The cellular constituents mainly include the chondrocytes while the solid phase
contains substances such as collagen and proteoglycans. According to Lahm et al. (2010)
collagen has relatively slow turnover. On the other hand, proteoglycan exhibits rapid turnover. Normal joints maintain this matrix as they balance the degradation and anabolic enzyme activities. The synovium is responsible for helping orchestrate the remodeling by 14
motivating the cells to synthesize transforming growth factor ß (TGFß). Besides, promoting the matrix synthesis TGFß minimizes cartilage destruction by inhibiting the production of IL-1 and tissue inhibitors metalloproteinases (TIMPs). Cartilage also produces fibroblast growth factor and Insulin-like growth factor (B-FGF and IGFs) to assist in the repair process (Fang, Xu, Li, & Zhao, 2016).
On the contrary, this is not the case in the osteoarthritis patient as the matrix degradation exceeds the anabolic enzyme synthesis, thereby resulting in a decrease in collagen and proteoglycans. Chondrocytes, in turn, synthesize more proteoglycan and collagen molecules to restore the equilibrium (Lahm et al., 2010). However, the enhanced cartilage degradation often outpaces the attempts to achieve reversal of matrix loss.
Consequently, erosion, cracking, and fibrillation occur at the cartilages’ superficial layer.
As the degradation progresses to the deeper layers, the patient’s condition worsens. This will also be evident through clinically noticeable symptoms, such as swelling of the joints and excessive pain during movement (Leung et al., 2013).
According to Garlanda, Dinarello, and Mantovani (2013), inflammatory cytokines, such as Interleukin-1 (IL-1), Interleukin-6 (IL-6), Interleukin-15 (IL-15),
Interleukin-17 (IL-17), Interleukin-18 (IL-18), and tumor necrosis factor alpha (TNFα), are released during the matrix breakdown. These cytokines induce the synovial cells to synthesize the MMPs and proteoglycan which inhibit type II collagen and proteoglycans synthesis. For example, IL-1 has been found not to stimulate cartilage destruction but to also hinder the attempts to repair the damaged tissues (Garlanda et al., 2013). 15
Nitric oxide, a pro-inflammatory ion, can also cause apoptosis (cell death with
minimal inflammation) through a mutation in mitochondria. Nitric oxide components
have been observed to cause fragmentation of DNA, the dysfunction of mitochondria,
remodeling of cytoskeletal tissue, and induce the release of cytochrome C. All these
factors lead to the development of apoptosis. This process demonstrates the pleiotropic
(multiple actions) effects of nitric oxide (Vuolteenaho, Moilanen, Knowles, & Moilanen,
2007).
Moreover, the cytokines produce nitric oxide (NO) and NF-ĸB, as well as
promote chondrocyte apoptosis that further supports cartilage deterioration (Kashyap,
Carter, Sauer, & Chen, 2013) In this case, NF-ĸBs are chemicals that regulate the production of matrix metalloproteases (MMPs). In other words, the chondrocytes often create MMPs that degrades the matrix during an injury. The synovial cells and chondrocytes produce MMPs that are categorized as collagenases, gelatinases, and
stromelysins. The joint synthesizes the substances as inactive enzymes regulated or
activated through a process known as enzymatic cleavage (Kashyap et al., 2013). Having
been activated, the MMPs lose the ability to resist against plasma-derived (alpha-2- macrglubulin) and tissue inhibitors (TIMPS). According to Man and Mologhianu (2014), osteoarthritis enhances the MMPs synthesis to such a high level that it overwhelms the inhibitors, thereby, resulting in net degradation. It is clear that excess or deficiency in the cytokines expressed plays a heretofore unclarified role in the diseases etiology and progression. 16
Osteoarthritis Effects on Other Joint Tissues and Bones
Several recent studies have revealed that osteoarthritis does not only affect the
cartilage but the entire joint. Martel-Pelletier and Pelletier (2010) found that the articular cartilage degradation involves several cellular changes, biomechanical processes, bone remodeling, the formation of marrow lesions, and synthesis of enzymes by the synovium cells.
Subchondral Bone
This is the bone that lies just below the articular cartilage. Cortical bone joins the
articular cartilage via a zone called calcified cartilage. Subchondral bone maintains
healthy bone by reabsorbing excess secretions and forming new bones (Martel-Pelletier
& Pelletier, 2010). However, the osteoarthritis process usually interferes with these functions. It can cause sclerosis and bone marrow lesions. The inflammation may also thicken the subchondral bone plate. The MMPs do not only modify the trabecular bone architecture, but also inhibit the development of the new bones along the joint margins.
Osteoarthritis patients have high bone resorption indices that indicate the loss of the bone
(Lahm et al. 2010). The synovial fluids in such joints come into contact with the bone
marrow that, in turn, causes bone cysts to form (Ondrouch, Prague, & Czechoslovakia,
1963). Lahm et al. (2010) note that the osteoarthritis affected subchondral bone produces a type of collagen, type I, which stimulates abnormal mineralization. The normal bone α1 and α2 type I collagen chains ratio averages are 2.4:1, while affected bones ratios vary
between 4:1 and 17:1. This abnormal mineralization pattern adversely affects the
homeostatic processes and contributes to the pathophysiology. 17
Bone Marrow Lesions
The articular cartilage destruction is significantly associated with bone marrow abnormalities. The damage impacts negatively the formation of the bone marrow as well as bone marrow necrosis and fibrosis. The abnormalities accentuate the cartilage loss.
Martel-Pelletier and Pelletier (2010) found that the cartilage loss is always higher in joint areas with high bone marrow lesions. The defective bone marrow is also responsible for cysts that block the synovial fluids from synthesizing important anabolic enzymes.
Risk Factors Aging
Osteoarthritis is more common among the elderly than the young. Doctors previously perceived osteoarthritis as an inevitable condition of old age. According to
McAlindon and colleagues (2014), physicians previously hypothesized that frequent movements over the life course wore out the articular cartilage. In contrast, recent studies have indicated that regular, active physical exercise minimizes the chances of cartilage degeneration. However, age is also known to bring about degenerative joint transformation, which leads to wearing out of joints (Scharstuhl et al., 2007). Cartilage repair is likely to deteriorate as one grows old. The regressive joint transformation prevents normal healing process in the joints after wear-and-tear, which in turn leads to an increased risk of suffering osteoarthritis.
Researchers have also dedicated their time to exploring differences between osteoarthritis cartilages and non-arthritic, aging joint tissues (Aftab, Siddiqui, Babur, &
Memon, 2015). The studies reveal that there are denatured type II collagens in both the 18
cartilages. However, these collagens are more predominant in osteoarthritis suffers than
normal, aging cartilages. Moreover, a significant difference exists in the liquid phase and
chemical components, such as the ratio of keratin sulfate to chondroitin sulfate. Möller et
al., (2016) found that osteoarthritis patients are more likely to have chondroitin sulfate
epitope 846 and carboxy propeptide which is normally found in fetal and neonatal cartilages. This means that old age increases the chances of osteoarthritis, but not all older adults have the disease.
Abnormal Loading and Repetitive Injury
The joints can withstand normal physiologic loads. Occupations which produce
excessive joint loading may initiate or accelerate latent disease processes. Heavy manual
labor, trauma, obesity and weight problems are leading risk factors of osteoarthritis.
Moreover, higher body mass is medically associated with low metabolism. The low rate
of metabolism in obese people is believed to increase the chances of progression of
osteoarthritis in people who are predisposed to the disease (Roubenoff, 2000). Fat tissue
in the body is known to trigger the release of particular hormones that alter growth
factors. An excess of fat tissue in the body exposes joints to increased chances of
developing osteoarthritis. Excess fat tissue may also trigger the advancement of
osteoarthritis in patients who already have the disease (Messier et al., 2004).
Individuals in occupations that require heavy load bearing on joints such as
manual laborers, floor cleaners, those self-employed in construction, professional
sportsmen, truck/taxi drivers, and farmers experience higher rates of hip and knee
osteoarthritis than the general population (Rossignol et al., 2005). Kerkhof and his 19
colleagues (2014), also note that cumulative trauma such as microfracture can stimulate enzymatic activity or cause wear and tear, consequently causing an imbalance between the degradation and repair of the cartilage. Further, the accumulation of joint debris from wear may alter the ability of the synovial cells to maintain homeostasis. For example, retired athletes, soccer, football, and rugby players record high incidences of knee osteoarthritis due to the numerous cruciate ligament injuries they suffer during the course of their careers.
Injuries cause trauma to bones and joints by causing degeneration of cartilage, ligament injuries, and dislocated joints. Trauma on vital joints such as knees, which are weight-bearing joints, particularly from anterior cruciate ligament (ACL) tear and strain, may lead to osteoarthritis (Shrier, 2004). Joint injuries, mainly in weight-bearing joints, affect muscles, bursas, and ligaments surrounding the joint area. In severe and repeated cases of joint injury, cartilage may tear and menisci may wear-out. Continuous injuries around the same area lead to accumulation of dead and damaged cells, which trigger inflammatory processes causing the swelling of joints. Repetitive damage of cartilage results in inflammation that increases the chance of suffering from osteoarthritis.
According to Muthuri, McWilliams, Doherty, and Zhang (2011), bodily injuries, particularly to articulating joints, may lead to rupture of blood vessels and clots around the joint. It reduces the free circulation of blood in and out of the joints, leading to stiffness and pain. In severe cases, it may cause inflammation and severe pain, leading to osteoarthritis. 20
The injuries cause subluxation of the joint as well as abnormal load distribution.
In this case, subluxation refers to the altering of the collagen fibrils and ligaments. As a
result, the tendons stiffen, thereby, decreasing the joint flexibility. Similarly,
osteoarthritis risks among obese people with a body mass index of between 30 and 35 is
four times higher than other individuals (Aftab et al., 2015).
Genetic Factors
Family history plays a significant role in the risk of developing osteoarthritis. The
disease has been associated with the presence of several genes, such as those responsible
for extracellular matrix proteins. Generally speaking, most osteoarthritis patients have strong body builds, wide geometrical bone measurement, and high bone mineral density
(Kerkhof et al., 2014; Nevitt et al., 1995). This means that all the young people who inherit these traits from their parents are at a significant disadvantage. In fact, family and, thus, genetic factors have been found to be present in about 65% of all osteoarthritis cases
(Manek, Hart, Spector, & MacGregore, 2003). Individuals from families with a history of other forms of arthritic and auto-immune diseases where arthritis symptoms predominate, such as lupus, ankylosing spondylitis, rheumatoid, and psoriatic arthritis, are at significantly higher risk of osteoarthritis than the general population. Individuals with endocrine problems, such as hemochromatosis and Wilson's disease, also fall under the
disadvantaged group. The conditions often affect the blood supply along the joints and
trigger buildup of toxic materials around the articular cartilage (Allen & Golightly, 2015).
Hemophilia, which is a genetic bleeding condition, causes bleeding from minor
trauma and weight bearing. It leads to bleeding in the skin and mucus membranes and 21
reduced blood circulation to the joints. Recurrent bleeding and reduced blood circulation
in the joints cause the degeneration of joint tissue and cartilage. It results in osteoarthritis
of the joints in this population (Fernández-Moreno, Rego, Carreira-Garcia, & Blanco,
2008).
Gender
Gender also plays a key role in osteoarthritis prevalence. Several studies suggest that more senior women suffer from the disease than senior men. Issa and Sharma (2006)
found that the prevalence increases after in women after they reach menopause. The
researchers attribute the increasing risk to the loss of estrogen. Estrogen prevents
cartilage inflammation and women lose this protection after menopause when estrogen
levels drop. Roman-Blas, Castañeda, Largo, and Herrero-Beaumont (2009), explain that
research has produced compelling evidence on estrogen deficiency’s effects on the joint.
For example, estrogen often impairs the secretion of type II collagen. Leung and his team
(2013), confirm the findings that indicate that the osteoarthritis prevalence rate was
higher in men below 45 years old than women in the same age range. However,
osteoarthritis incidence is significantly higher in females above 55 years than in their
male peers. The study showed that women were 2.6 times more likely to develop hand
osteoarthritis after their 50th birthday than men of the same age. The difference is
attributed to the decline in estrogen levels. Therefore, hormonal therapy may be effective
for treating this group of senior women, but comes with increasing risk of heart attack
and stroke, especially as aging continues (Leung et al., 2013). Further, women have
wider hips than their knees in comparison to men, leading to higher rates of injuries than 22
men. For example, researchers have observed that females playing soccer are three to
four times more likely to experience joint problems as their male counterparts (Shrier,
2004).
Child birth is also believed to increase the risk of suffering osteoarthritis in
women. With each birth, the risk of suffering knee and hip osteoarthritis increases by
eight and two percent respectively. The wide alignment of women’s hips creates
instability in the knee joints, which increases the chances of cartilage degeneration of the
knee joints over the course of multiple pregnancies. This makes females more likely to
develop osteoarthritis of the knee (Prieto-Alhambra et al., 2014).
Lifestyle
Diet, the level of physical activity, smoking, and drinking, play key roles in
developing and living with osteoarthritis. Micronutrient deficiencies such as vitamins C,
D, and K have been found to trigger arthritis. Leung and his partners (2013), cite that a lack of Vitamin C in feeding studies with mice caused chondrocytes to degenerate at a faster rate than in mice that were provided with adequate vitamin C. Similarly, humans who consume adequate Vitamin C and D achieve increases in bone density which lowers the progression of osteoarthritis. Furthermore, Vitamin K supports the coagulation process that regulates cartilage mineralization and may reduce the risk of developing osteoarthritis (Leung et al., 2013).
Environment and Osteoarthritis
Environmental toxins such as chemical pollutants, heavy metals, and pesticides
have been associated with an inflammatory effect on the immune response of the body. 23
Some of these toxins bioaccumulate in the body and lead to on-going, low-grade inflammation. (Spector & MacGregor, 2004). Dust, fibers, and prolonged smoking also lead to inflammation of joints and deterioration of joint tissues, which result in severe pain and reduced flexibility (Meggs, 1993). Additionally, Zeman et al. (2014) found an association between drinking water nitrate level and complaints of arthritis in an in vivo study of 150 individuals. Low- level nitrate exposure below 10 mg/L is not considered acutely lethal to humans but the research found that people consuming well water as their primary drinking water source below 10 ppm had osteoarthritis complaint, poorer health, lower recreational activity, muscle, and nerve pain. The effect became pronounced at the
5ppm level of nitrate-nitrogen in the drinking water (P = .0150, f = 6.0533; Zeman et al.,
2011).
According to Keysor et al. (2009), cold weather has been identified as a cause of stiffness and reduced flexibility in patients suffering from acute osteoarthritis. However, the cold helps comfort inflammation, which reduces pain and numbness on painful joints.
Heat, on the other hand, has also been discovered to be therapeutic to patients suffering from osteoarthritis. Heat helps reduce stiffness around joints by increasing blood flow, hence making joints more flexible, thereby increasing a patient’s mobility (Dieppe &
Lohmander, 2005).
Food allergy and intolerance have been associated with osteoarthritis (Haugen et al., 1991). Most patients suffering from the disease are sensitive and allergic to foods such as eggplants, white potatoes, sweet pepper, tomatoes, and hot peppers. This group of foods contains Belladonna, which is a natural toxin that induces food allergies (Wetherell 24
et al., 2004). They also contain alkaloids, which affect metabolism of calcium in the body and cause inflammations in joints. Patients suffering from osteoarthritis are believed to experience a reduction in pain and inflammation after these foods are removed from their diets (Wetherell et al., 2004). Furthermore, fibrin, the mesh-like protein that helps to heal wounds after injury, is often produced by the body in the event of inflammation in joints.
Fibrin has been proven to be a strong gauge of inflammatory joint disease. Deposits of fibrin are a conspicuous feature of arthritis (Gregory, Sperry, & Wilson, 2008).
Omega 6 fatty acids used in excess cause inflammation, which leads to production of fibrin. Fibrin is fundamental to the processes that produce the majority of arthritis pain.
Alternatively, proteolytic enzymes ease pain associated with osteoarthritis by moderating the response of lymphocytes. As people grow old, their production of proteolytic enzymes decreases, creating more pain for those with osteoarthritis (Yelland et al., 2006).
Proteolytic enzymes eat away fibrin and other scar tissues, which prevent natural anti- inflammatory processes from decreasing inflammation in osteoarthritic joints.
Proteolytic enzymes help fight inflammatory tissues, boost cardiovascular and immune functions of the body, and dissolve scars (Kullich, 2012). In that manner they ease pain caused by osteoarthritis. For example, bromelain, a substance that is found in pineapples is proven to help in the production of proteolytic enzymes. It assists in removing toxins from the body, reducing, and preventing inflammation in the body as well as decreasing swelling in the body. Another dietary substance and spice, turmeric has anti-oxidant powers, which ease pain and inflammation. It shuts down the COX2 enzyme, which is responsible for pain in the joints (Gregory et al., 2008). Papain, an 25
enzyme found in unripe papayas, helps replenish proteolytic enzymes in the body. Citrus bioflavonoids act as anti-oxidants in the body and enhance quick and effective absorption of vitamin C. They inhibit elastase and collagenase enzymes, which aid in the degeneration of cartilage tissue at the articular surfaces of the joints. Finally, citrus bioflavonoids help joints remain healthy and flexible and protect against free-radical damage in the joints.
Impacts of Osteoarthritis
Osteoarthritis has multiple and adverse social, financial, and psychological impacts on patients and their families. Since the pain level from osteoarthritis is not predictable, osteoarthritis restricts the patient from social activities. According to Vignon et al. (2006), virtually all the people suffering from osteoarthritis complain about distress due to the loss of ability to control their lives. At first, individuals experience physical challenges while participating in intense activities such as sports (Vignon et al., 2006).
Eventually, the individuals begin to experience more painful episodes during light movements. This, in turn, leads to sleep disturbance and distress, sleep disturbance being a major predictor of poor physical and mental health outcomes. On the other hand, quality of sleep is positively correlated with positive treatment outcomes. A study by
Vitiello, Rybarczyk, Von Korff, and Stepanski, (2009) has shown that osteoarthritis patients who sleep at least four and half hours per night cope better with the disease than their counterparts getting less sleep. Further, those having careers in sports or those that are involved in heavy manual labor may lose their source of living. Understandably, the impacts are greater among low-income families than wealthy households. This is at least 26
in part due to the inability of these households to absorb the increased medical costs and loss of primary income. Further, most of these manual labor occupations outside of professional sports are broadly characterized by poor compensation and lack of benefits,
such as health insurance, life isurace, and retirement benefits. Consequently, these individuals’ health and wellbeing deteriorates, thereby, exposing them to other chronic co-morbidities, such as psychological distress and heart diseases (Hootman, Macera,
Helmick, & Blair, 2003).
Socially, patients with low self-esteem suffer more from chronic morbidity than
their peers who quickly form and maintain social support relationships. Phyomaung et al.,
(2014) found that pessimistic individuals with osteoarthritis withdraw from
recommended management procedures more readily, for example, they do not like
performing light exercises and healthy physical activities such as walking and yoga. This
can lead to high pain prevalence and increased dissatisfaction with life. According to
Katon, Lin, and Kroenke (2007), stress for osteoarthritis patients increases with the
intensity of pain, unmet psychological needs, physical disability and decreasing financial
security. This is intensified with age as depression levels among older patients with
osteoarthritis are higher (Sale, Gignac & Hawker, 2008). Therefore, caregivers should
prioritize such disadvantaged patients’ psychological needs. Around 15% of the people
with osteoarthritis experience depression and anxiety, with 8-10% of that among the
elderly patients exclusively. Further complicating increased functional disability on the
part of elderly patients is a reduced quality of life, and increased risk of falls that are
higher with osteoarthritis patients (Stubbs, Aluko, Myint, & Smith, 2016). 27
Being in pain may trigger stress or depression in patients. However, if a patient
suffering osteoarthritis suffers co-morbidities as well, pain associated with the disease often
increases. Surveys that have been done by medical researchers have revealed that people with
mild osteoarthritis who are also experiencing stress or depression, due to their condition, feel
twice as much reported pain as individuals not experiencing stress and/or depression (Yudoh
et al., 2005). When the two conditions, osteoarthritis and depression, overlap, the pain is
multiplied. Medical studies reveal that osteoarthritis-related pain in the knee is often
associated with stress or depression. The latter leads to reduced muscle conditioning. It
becomes a vicious cycle which translates into increased pain associated with osteoarthritis
and makes the patients stay isolated from other people; it worsens their depression condition
and so on (Mishra et al., 2012). The latter increases the progression of osteoarthritis in
patients.
Further complicating disease management, the higher the negative emotions are, the lower is the patient’s ability to adhere to chronic disease management plans.
Phyomaung et al., (2014), demonstrated that anxiety results in greater pain episodes than depression following joint surgery. This is attributable to the fact that anxiety reduces the quality of life both before and after undergoing surgery. On the other hand, self-efficacy is positively correlated with good coping strategies and better chronic disease management. Patients with high self-esteem report adhering to treatment and dietary plans more closely and honor all their doctors’ appointments. These individuals also report that having close relationships with the caregivers is an important step towards 28
achieving better post-surgical and chronic disease management outcomes. (Phyomaung et al., 2014).
Clinical Features of Osteoarthritis
Osteoarthritis patients often suffer from extreme pain accompanied with stiffness.
The individuals’ discomfort increases during joint use and they feel relieved while resting. However, advanced stages cause persistent pain all the time, whether the patient is resting or not. According to Dieppe and Lohmander (2005), the loss of cartilage cushion results in friction between the bones causing severe pain even during a period of inactivity. In other words, the pain cannot be linked to specific stimuli. Swift (2012) notes that several studies exploring the brain’s role in pain perception and osteoarthritis reveal that the discomfort does not necessarily result from movement, pressure, or loading. They hypothesized that the pain may originate from the mechanical irritation of the synovial and capsular inflammation or bone sclerosis. As a result, the patient does not get enough sleep and struggles to engage in daily activities, such as walking and climbing stairs.
The joints also become tender and may not move freely. This is not only because the muscles weaken but also due to the thickening of the synovial membrane. Such symptoms often vary with external conditions. That is, some patients experience pain during weather changes while others record bad and good spells all year round (Sutton et al., 2009). Osteoarthritis symptoms may also depend on the part of the body affected and individual risk factors, for example, osteoarthritis of the knees is highly associated with gender, obesity and repeated injuries (Silverwood et al., 2015). The excess upper body 29
weight together with the progressive cartilage degeneration can deform the knees. A significant number of patients are forced to go for knee surgery as their conditions hardly respond to medications because of the etiological factors involved (Dieppe et at., 1999).
Osteoarthritis of the fingers is associated with growth or spurs next to the joint.
According to Tan et al., (2005), patients with osteoarthritis of the hands may develop two types of bony enlargement, the Heberden and Bouchard’s node. This is abnormal bone growth that occurs at the end of the fingers, named after Dr. Herberden, a famous British physician, while the bony knob at the middle joint of the fingers got the name from Dr.
Bouchard, a French doctor who made several discoveries about arthritis treatment in the
1800s(Tan et al., 2005). The fingers also swell and become tender. Similarly, individuals’ that develop osteoarthritis of the cervical spine suffer from extreme pain in their necks and low back. Swelling in these areas prevents the normal functioning of spinal nerves, leading to numbness. At the same time, the pain intensity varies from one patient to another. Swift (2012), found that the pain episodes are often inconsistent, making the development of standardized pain scales difficult for osteoarthritis sufferers. Moreover, the pain may come either every day or in episodes. Some patients describe the pain as intense and sharp while others say that it is dull and aching.
Diagnostic Procedures
The diagnosis focuses on the symptoms. The physician should examine the affected joints for swelling, tenderness, pain, and any other damage. He/she must supplement the physical examinations with imaging (x-rays and Magnetic Resonance
Imaging (MRI) and laboratory tests (joint fluid analysis and blood tests; Leung et al., 30
2013). X-rays will not only reveal the cartilage loss but also show spurs and nodes around the joint. X-ray radiography may indicate osteoarthritis evidence before some patients develop severe symptoms. MRI also utilizes strong magnetic fields and radio waves to depict better details about the joint and the surrounding bone and soft tissues than X-ray.
Joint fluid analysis, using a needle to withdraw fluids from the affected hip, knee, leg, or spine, indicates whether there are inflammation indicators while additional blood tests help to determine whether the joint discomfort results from other types of arthritis or other diseases. For example, the blood examination will indicate erythrocyte sedimentation or the presence of other antibodies and rheumatoid factors (McAlindon et al., 2014).
Treatment
Osteoarthritis’ treatment entails a mix of pharmacological, non-pharmacological, intra-articular, and surgical procedures. The treatment begins with safe and low-cost therapies before advancing to more complex, costly and higher-risk interventions. The first treatment should include non-pharmacological activities, such as stress management and disease management education, exercise, nutrition, weight loss, and physical aids, such as knee braces (Allen & Golightly, 2015).
Non-Pharmacologic Therapies
Non-pharmacological interventions include creating physical exercise programs and other behavioral therapies aimed at strengthening the joint muscles, easing pain, and minimizing other risk factors, such as on-going weight gain problems. Aerobics, jogging, walking, swimming, cycling, and other upper body exercises are effective in attaining 31
healthy body weight. Clinical studies indicate that low impact exercise presents some of
the most significant intervention measures for living positively with osteoarthritis.
Individuals who exercise regularly also achieve appropriate weight loss, a factor which has been shown to reduce pain for current osteoarthritis suffers and even the risk of developing symptomatic osteoarthritis in women. According to Hawkeswood and Reebye
(2010), losing at least 5% of one’s body weight is adequate to reduce disability. At the same time, physical activities improve motion, joint flexibility, and muscle strength and endurance. Every loss of 1-kilogram of body weight leads to a reduction of 4 kg load per step and 4,800 kg per each kilometer a patient walks (Hawkeswood & Reebye, 2010).
Behavioral therapy plays a critical role in managing osteoarthritis. Effective education techniques, such as individualized and group discussions, equip the patient with adequate coping skills for chronic pain and disease management, making the stress
and disease management process learning processes 20% as effective as pharmacological strategies (Walker-Bone et al., 2000). According to Aftab et al., (2015), a sound chronic
disease and pain management plan will consider each patient’s expectations, the severity
of the disease, occupation, and social/psychological needs. Pessimistic patients, for
example, require more counseling sessions than individuals with higher self-esteem and
more optimistic outlooks. Treatment plans should be collaborative with care providers so
as to engage the patient in setting appropriate treatment goals (Aftab et al., 2015)
Both the literature and evidenced based practices document the benefits of
patient-driven therapies over passive treatment procedures (Hawkeswood & Reebye,
2010). Patients adhere to behavioral modifications more easily when they have unlimited 32
access to information and fully understand the needs for certain treatments rather than when health professionals impose the procedures on them without adequate education.
Ideally, the first session should focus on informing individuals about osteoarthritis and outlining its treatment procedures. The second visit should concentrate on discussions of
standardized exercise procedures, healthy diets, and other weight loss activities. Leung et al., (2013), found that following such a staggered program intervention results in greater weight loss and pain relief than traditional non-pharmacologic treatment. The patients also benefit from one-to-one interaction with experienced physical therapists and
nutritionists.
During interactions with physical therapist’s patients can learn about and access
joint supportive devices, such as compression wear, braces, canes and walkers.
Alternatively, the individual can use orthotic shoes that reduce stress on joints and splints
to stabilize affected areas. Furthermore, the new knowledge gathered through
consultation with nutritionists helps ensure the patient maintains low-fat food
consumption and increases Vitamins C, D, and K in their diets. Individuals with severe
conditions can employ a transcutaneous electrical nerve stimulation device, TENS to
manage the pain. This equipment disrupts the transmission of the pain stimuli and has
been proven to reduce pain perception for many individuals (Man & Mologhianu, 2014).
33
Pharmacological Therapy
Several medications help to minimize pain and improve musculoskeletal function
in osteoarthritis patients. The drugs are categorized as pain management medications,
nonsteroidal anti-inflammatory drugs (NSAIDS), and joint injections (Garlanda et al.,
2013). For example, NSAIDS and acetaminophen relieve moderate to mild pain. In
contrast, narcotics are preferable for severe osteoarthritis exacerbations. Like the
analgesics, it is recommended to administer non-steroidal anti-inflammatory drugs
(NSAIDs) to patients who are unresponsive to the non-pharmacologic measures because of their side effects. The drugs both reduce pain and minimize inflammation. Joint injections are effective for patients that are allergic to the NSAIDS. Injecting glucocorticoids into arthritic joints reduces osteoarthritis symptoms. Similarly, cyclooxygenase-2 (COX-2) inhibitors and glucocorticoids are used in the management of knee arthritis to reduce inflammation of swollen joints. Viscosupplements, such as hyaluronan and Hylan G-F 20, have similar effects (Wobig et al., 1999).
However, these medications have several side effects that make long-term use unattractive. For example, non-steroidal anti-inflammatory drugs (NSAIDs) often lead to gastrointestinal and cardiovascular problems, while steroid use may cause hypertension
and psychological disorders (Slipman, 2008). Steroid injections lead to increased
inflammation in joints over the long term; brought about by the crystallization of
corticosteroid. It further reduces the rate of healing in patients who are suffering from
osteoarthritis, since their joints remain sore, immunity is suppressed, and the crystals increase
friction, which affect movement. Medical research has proved that repeated steroid injections 34
cause injury to joint tissues and irritate the nerves around the joint (Arroll & Goodyear-
Smith, 2004). They also expose joints to higher chances of infection from bacteria and other diseases. This complicates the healing process of osteoarthritis and increases chances of advancement of the disease, which exposes the patient to more pain.
As a result, some physicians and patients are increasingly using complementary and alternative supplements to diversify the health care and medication options for osteoarthritis treatment. The fact that pharmacological interventions are palliative and not curative therapies, as well as various adverse effects of drug treatments, has increased interest on the part of patients to use complementary and alternative supplements (March,
Amatya, Osborne, & Brand, 2010). These supplements mostly include natural herbs. For example, S- Adenosylmethionine (SAMe), cat’s claw (Uncaria tomentosa), and capsaicin are some of the alternative supplements that have been used to manage osteoarthritis symptoms (Kuhn & Winston, 2008; Noureddin, Mato & Lu, 2015). These alternative supplements allow for improved healthcare outcomes by eliminating the adverse side- effects associated with conventional treatment methods (the drugs’ side effects). SAMe contains dietary supplements derived from natural foods that claim to be more effective than many pain medications (Kuhn & Winston, 2008). Similarly, capsaicin is an herbal medicine made from chili peppers. It contains substance “P” which is believed to block stimulation and transmission of pain signals normally triggered by inflammatory substances in the joints (Noureddin et al., 2015). Moreover, cat’s claw has been used for centuries by folk healers to treat health problems such as osteoarthritis. It has provided 35
significant reductions in pain and number of swollen joints in self-report case studies
(Kuhn & Winston, 2008).
Surgery
Given the cost impacts and the risks associated with surgery, this treatment
modality is reserved for osteoarthritis cases that do not respond to other treatment procedures. When surgery is indicated, however, patients should undergo surgery early
enough to avoid experiencing complications such as, joint deformities and excessive
muscle loss (Tanna, 2004). The arthroscopic procedure entails removing damaged/torn
cartilage in the affected joint, irrigation, realignment, and cartilage grafting (Martel-
Pelletier et al., 2016). In joint replacement, the entire joint is removed and an artificial
one attached to the bone ends. Arthroscopic surgery and joint replacement involve
extended recovery times, sometimes taking more than six months to achieve the intended
benefits (Charousset et al., 2008).
Several complex factors determine osteoarthritis prognosis. Osteoarthritis cannot
currently be cured, but developing the right attitude and adapting appropriate lifestyle
changes minimizes the burden of living with osteoarthritis. Although most of the risk
factors are not avoidable, osteoarthritis patients have the opportunity and responsibility to
take control of their lives through appropriate lifestyle management and self-care.
However, such positive outcomes are possible only when physicians and other medical
practitioners invest adequate resources in patient and public education, raising awareness
about this disease and its heavy health burden worldwide. Sharing knowledge about
osteoarthritis causes and management strategies has yielded breakthroughs in the 36
treatment of the disease over the past few decades. Current patients can access better
informed and higher-quality health care more cost effectively than ever before.
Cat’s Claw (Uncaria Tomentosa)
Uncaria tomentosa, also known as Cat’s Claw, is a woody herb native to South
and Central America. The common name of the plant is uña de gato, which is a definition for several plants in this species. There are more than 30 species of cat’s claw (Uncaria)
herb known, with the two most commonly used of medicinal interest being, Uncaria
tomentosa and Uncaria guianensis (Piscoya et al., 2001). In the Western world’s
tradition, the latter is more popular as compared to the first one, but since both are in the
same family of Rubiaceae, they share a common ethno medical use. The Uncaria
tomentosa genus has been the most thoroughly examined within the western research
community and its variety of uses catalogued. This explains, to some extent, its
popularity amongst American consumers (Valerio & Gonzales, 2005).
As further explained by Piscoya et al., (2001), the species cat’s claw is an
indigenous herb from the Amazon River basin. For many years, the plant has been used
as a traditional folk supplement, particularly by local natives and their shamans, in
overcoming various health complaints, especially chronic inflammatory diseases such as
arthritis (Caon et al., 2014; Piscoya et al., 2001). The reported health benefits of the herb have motivated researchers, most notably in the U.S., to study it users’ claims of positive health impacts. Findings of the studies conducted to date, generally conclude that the species is associated with powerful antioxidant and anti-inflammatory actions that have 37
proven to be efficient in managing osteoarthritis and supporting joint health (Williams,
2001).
Background of Cat’s Claw (Uncaria Tomentosa) Use
Cat’s claw herb was initially discovered by Arturo Brell, a German researcher of natural resources, who moved from Munich to Pozuzo, a small town in the Peruvian rainforest (Williams, 2001). The first evidence of the health benefits of cat's claw was found when Dr. Brell used it to treat a patient who was suffering from terminal lung cancer. After other therapies had failed, the patient started taking the plant’s root tea. As a result, he showed remarkable improvement, and after one year, he was cancer-free. The plant is a tropical liana, or a perennial vine that is rarely cultivated (Reinhard, 1999). The plant is harvested from either primary or secondary (logging) managed forest. The herb is known as “cat’s claw” as it has thorns similar in appearance to a cat’s claws. Most of the commercial supply of the cat’s claw is from Peru, but other nations are currently producing it due to its numerous health benefits and expanding market.
The plant has far-reaching branches carrying long shoots that have large and oval leaves, approximately 10 cm long (Reinhard,1999). During blossoming, inflorescences that are panicle-shaped form instead of the usual thorns that are shaped like claws
(Keplinger, Laus, Wurm, Dierich & Teppner, 1999). The bark, which is removed from the vine, is the major part traditionally used, and the outer layer has to be scrapped to remove fungal growth, tiny insects and other elements that could degrade the bark. In addition, Hoyos et al., (2015), explain that leaves of cat’s claw (Uncaria tomentos)a are the parts of the herb with the highest potential for use by scientists to obtain phenolic 38
extracts in standardized amounts and in a way that can be perceived as sustainable. Thus,
the leaves of cat's claw are most often used for cosmetic, food, and pharmaceutical
applications (Hoyos et al., 2015; Wagner, 1985).
Cat’s claw has high concentrations of phytochemicals. It has over 30 known
chemical constituents including 17 alkaloids, glycosides, sterol fractions, tannins,
flavonoids, and related beneficial compounds (Hoyos et al., 2015). Williams (2001),
noted that researchers tend to attribute the efficacy of the cat’s claw plant to compounds
known as oxindole alkaloids. However, more recent evidence suggests that water-soluble
extracts of cat’s claw that have no oxindole alkaloids present were found to contain
powerful anti-inflammatory as well as antioxidant impacts (Williams, 2001). According to a study conducted by Sheng et al., (2005), other compounds known as quinic acid esters are considered the active components of water-soluble extracts of the cat’s claw plant, and thus, they are responsible for the health effects in human beings. It is clear that further research is needed to understand both the active compounds in this herb and its precise biomolecular means of achieving its effects.
Historical and Most Common Uses of Cat’s Claw
According to Kemper (1999), cat’s claw (Uncaria tomentosa) has been used by
the people in the Ashaninka Peruvian rain forest for more than 2000 years. Among the
historical uses of the cat’s claw plant are: as a general tonic to ward off illnesses, as an
abortifacient, to treat inflammatory diseases such as diarrhea, for gastrointestinal tumors,
gastric ulcers, gonorrhea, rheumatism, acne, arthritis, diabetes, cancer, as well as diseases
of the urinary tract (Keplinger et al., 1999). As further explained by Kemper (1999), cat’s 39
claw is sometimes used in combination with other herbs that are found locally, such as
chuchuhuasi, in the treatment of arthritis. The Ashaninka also believe that specific
species of cat’s claw, comprising species that contain pentacyclic oxide alkaloids such as
Uncaria tomentosa, have a magnificent power that can only be realized by healing priests
who are highly ranked in that society (Ganzera, Ilias, Khan, & Khan, 2001; Kośmider,
2017; Reinhard, 1999; Valerio & Gonzales, 2005). Therefore, there are numerous
historical health applications of the cat’s claw plant. In that light, the Ashaninka people
placed great value on the plant due to its diverse applications and purported health
benefits.
Today the cat’s claw species is being used in alternative health applications as a
cancer remedy and immune stimulant besides being considered significant in treating
inflammatory conditions, such as atopic disorders, arthritis, gastritis and other related intestinal conditions, viral infections such as HIV and prostate problems (Kemper, 1999).
Other medicinal uses of the drug include treatment of chronic fatigue, environmental and chemical sensitivities, and also fibromyalgia. The demand for the cat’s claw herb has risen dramaticaly since many HIV patients are currently combining cat’s claw with the
anti-HIV drug (AZT) (Kemper, 1999). Steinberg (1995) also notes that cat’s claw is often
included in combination treatments with other herbs such as with capsaicin in the,
“Nikken Anti-Arthritis” cream.
Antioxidant and Anti-Inflammatory Properties of the Cat’s Claw Herb
Through laboratory analysis, extracts of cat’s claw have been proven to possess
powerful antioxidant impacts in neutralizing the lethal superoxide and peroxyl radicals 40
(Aguilar et al., 2002; Aquino, DeFeo, DeSimone, Pizza, & Cirino, 1991; Pilarski,
Zielinski, Ciesiolka, & Gulewicz, 2006). It has been shown that the antioxidant power of the cat’s claw herb is greater than that found in many extracts of vegetables, cereals, fruits, and also other medicinal herbs.
As a cardinal sign of many illnesses affecting aging adults, chronic inflammation has been effectively managed by use of cat’s claw since it has a powerful anti- inflammatory factor (Aquino et al., 1991). As explained by Bors et al., (2011), it is believed that cat's claw extracts inhibit the secretion of an inflammatory messenger known as TNFa. The messenger is pertinent for setting the stage, not only for acute, but also for chronic inflammation. Cat’s claw is also believed to inhibit the activation of NF- kB that acts as an inflammatory "switch" linked with a variety of diseases including cancer (Heitzman et al., 2005; Piscoya et al., 2001). According to a laboratory study conducted by European researchers, cat’s claw not only prevents the growth of human leukemia cells, but also induces the cells to go through apoptosis (a programmed self- destruction; Hayakawa & Smyth, 2006; Sheng, Pero, Amiri, & Bryngelsson, 1998).
Similarly, research conducted by Piscoya et al. (2001) showed that extracts of the medicinal herb reduced the experimentally-driven production of PGE2. The hormone is believed to mediate inflammation, hence it is linked with chronic inflammatory illnesses such as arthritis (Aguilar et al., 2002; Piscoya et al., 2001). Researchers have also explored the effectiveness of the cat's claw herb in the protection of DNA from oxidative stress. Mammone et al., (2006), conducted a laboratory study of cultured human skin cells. According to the study, co-incubation with cat’s claw water extract, a proprietary 41
extract of cat’s claw (C-Med-100), greatly reduced the death of skin cells following
exposure to UV light (Mammone et al., 2006). As elaborated by Mammone et al., (2006),
the protection was explained by an increase in the repair of the genetic material (DNA)
attributed to the cat’s claw water extract.
Cat’s Claw (Uncaria Tomentosa) and Osteoarthritis
Overview of the Relationship between Cat’s Claw and Osteoarthritis
Cat's claw use in osteoarthritis treatment is a form of alternative and
complementary therapy (Vitetta, Cicuttini, & Sali, 2008). There are different reasons for
using alternative and complementary therapies and supplements among different racial
and ethnic groups in the U.S. Among those reasons are prohibitive costs associated with
conventional treatments, a concern conventional treatment might fail to work as the patients would expect, cultural ties to traditional cultures using herbal medicine, or
concern that pharmaceuticals may produce too many side effects (Vitetta, Cicuttini, &
Sali, 2008).
Another reason as to why individuals may use complementary supplements is the
search for greater relief of disability and/or symptoms without the increased likelihood of
side-effects associated with pharmaceutical treatment. In addition, individuals seek
complementary supplements such as cat's claw in efforts to reduce the stress linked with
living with a chronic disease, and hence, to cope better with the illness (Vitetta, Cicuttini,
& Sali, 2008). There is also the belief that alternative and complementary treatments are not only safer, but also more “natural”. The belief is in part influenced by the widespread advertisement and marketing claims linked to various products. 42
As explained by Vitetta, Cicuttini, and Sali (2008), musculoskeletal diseases are a
fundamental cause of disability, and arthritis is the most prevalent form of such
degenerative diseases. The use of the herb to treat a form of arthritis known as
osteoarthritis has been highly adopted by people in the U.S. and throughout the world.
Cat’s claw extracts have been associated with properties such as, antioxidant,
immunomodulatory, and also anti-inflammatory (Vitetta, Cicuttini, & Sali, 2008). The
pentacyclic oxindole alkaloids are the most researched of the active components in cat’s
claw extract for anti-inflammatory and immunomodulatory health impacts. Scientists
report that the alkaloids induce a factor that regulates the immune system (Ahmed,
Anuntiyo, Malemud, & Haqqi, 2005). It is believed that such properties make cat’s claw effective in the osteoarthritis therapy although this is only partially understood.
Cat’s claw Action in the Treatment of Osteoarthritis
According to Sandoval et al., (2002), cat’s claw inhibits iNOS gene expression
that is induced by lipopolysaccharide, cell death, formation of nitrates, production of
hormone prostaglandin (PGE2), and also the activation of TNFα, and NF-kappaB
(Hardin,2007; Sandoval et al., 2002). There is also evidence in rat models, that cat’s claw
stimulates IL-1 and -6 (Hardin, 2007). Further, extracts of cat’s claw (both Uncaria
tomentosa and guianensis) have been shown to inhibit the redox-sensitive control of gene
expressesion, suppress apoptosis, TNFα, act to scavenge free radicals, and also
cryoprotect cells against such oxidants as peroxynnitrite in murine cell line and human
colon adenocarcinoma cell line (Sandoval-Chacón et al., 1998). 43
It seems clear that cat’s claw has powerful antioxidant properties, its alkaloids
binding with free radicals, stoping redox reactions (oxidation and reduction reactions) before they damage other biomolecules (Sandoval-Chacón et al., 1998). According to the
study (n = 45, ages 45-75) done by Piscoya et al., (2001), TNFα suppression was reported
to be at treatment levels that are considerably less compared to that required for
antioxidants. Cat’s claw was also reported to inhibit the activation of NK-kappaB
(Hardin,2007; Piscoya et al., 2001). Winyard and Blake (1997) conducted a study on
mice, which explains that NK-kappaB (the transcription factor) is sensitive to redox
reactions and it thus controls the expression of genes that lead to inflammatory
degenerative diseases (i.e., osteoarthritis). According to another study conducted by Beg
and Baltimore (1996), on mouse embryonic fibroblast cells, cat’s claw’s inhibition of NF-
kappaB, is pertinent in osteoarthritis therapy as two widely applied anti-inflammatory
agents, namely glucorticoids and salicylates, play a role in NF-kappaB suppression.
Benefits of Using Cat’s Claw (Uncaria Tomentosa) in the Treatment of Osteoarthritis
As explained by Vitetta, Cicuttini, and Sali (2008), there are minimal side effects
associated with the use of cat’s claw to treat osteoarthritis. Use of the herb is associated with relative safety as well as modest benefits to tender joints. A number of case studies,
series and epidemiological studies have documented the efficacy and minimal side-
effects of cat’s claw. Reearchers have reported that the herb appears to be non-toxic and
that it has no known drug interactions or contraindications (Chrubasik, Roufogalis, &
Chrubasik, 2007; Hardin, 2007; Sandoval et al., 2002). 44
Another benefit associated with the use of the cat’s claw herb in osteoarthritis
therapy is its ease of standardization, particularly in its commercial preparation (Hardin,
2007). Hardin (2007) notes that genera Uncaria tomentosa is a bit different from its
closely related genera Unacari guianensis in that the former has a higher content of
alkaloids, hence its effectiveness in the treatment of osteoarthritis. The herb is also being
increasingly adopted by individuals due to the belief that naturally occurring plants are
considerably more effective and give satisfactory health results as compared to
conventional medicines (Vitetta, Cicuttini, & Sali, 2008).
Cat’s Claw and Implication for Osteoarthritis
As explained by Vitetta, Cicuttini, and Sali (2008), even though cardiovascular
diseases and cancer (highest mortality) receive much attention from the medical and
public health community, rheumatic or musculoskeletal conditions are the main cause of
morbidity (chronic disease suffering) in the world. Musculoskeletal and immune
moderated conditions such as, osteoarthritis, fibromyalgia, gout, rheumatic arthritis as
well as systemic lupus erythematosus (SLE) have substantial impact on health and quality
of life and also inflict a great economic burden on the economy (Vitetta, Cicuttini, & Sali,
2008). Arthritis is the most common form of chronic musculoskeletal disease, and by the
year 2007, it affected about 43 million adults (20.8%) in the U.S.. Another implication of
the disease is that it is the greatest cause of disability in the U.S.. Osteoarthritis is also the most prevalent disorder of the joints in the world (Vitetta, Cicuttini, & Sali, 2008).
Osteoarthritis is also one of the most frequent sources of severe pain, disability and loss of joint function in adults. As further explained by Vitetta, Cicuttini, and Sali 45
(2008), radiographic evidence of osteoarthritis is seen in most people when they attain the
age of 65 years and in approximately 80 percent of individuals over 75 years of age.
Given these considerations, the use of low-cost, herbal therapies to manage this disease remains pertinent. Cat’s claw users have considerable faith in the effectiveness of the herb to treat osteoarthritis, citing a belief that the herb is safer and natural, and noting the fear of side-effects associated with pharmaceutical therapy (Hemingway & Phillipson,
1974; Vitetta, Cicuttini, & Sali, 2008). Also, most users cite not only short-term, but also
long-term health benefits as reasons for its use. Similarly, the cost of pharmaceutical
treatment is higher, compared to using naturally-occurring herbs, hence the increased
preference of cat’s claw (Vitetta, Cicuttini, & Sali, 2008).
Health Impacts of Cat’s Claw on Slowing Progression of Osteoarthritis
Two general properties of cat’s claw, preventing inflammation and oxidation,
cannot be stressed enough when describing the health benefits of the herb in osteoarthritis therapy. As explained by Sandoval et al., (2002), the active chemicals in cat’s claw have been identified as sterols, quivonic acid glycosides, and oxindoles. Extracts of cat's claw suppress inflammation and thus enable the development of healthy joint function and structure. Relievng the inflammation also relieves the pain and feeling of discomfort brought about by osteoarthritis. What remains unclear is the precise biomolecular mechanisms by which this effect is achieved. Whether the herb accomplishes this by
reduction in lymphocyte proliferation, modulation of cytokines, supression of the
biomolecular pathways of inflammation and redox reactions or a combination of all these
modalities needs to be understood. 46
According to Hardin (2007), cat’s clawis capable of protecting cartilage. Loss of cartilage is a defining feature of osteoarthritis, and it sets in when the rate of cartilage breakdown exceeds that of its regeneration. A study done by Miller, Ahmed, Bobrowski, and Haqqi (2006) showed that cat’s claw helped to restore Insulin-like growth factor-1
(which protects joints) levels after cells of human cartilage were subjected to interleukin-
1 beta, an agent that destroys joints (Miller et al., 2006 ). Patients with osteoarthritis suffer from immense pain and discomfort due to the destruction of protective cartilage.
According to Piscoya et al., (2001), cat’s claw’s benefits for relieving osteoarthritis in general are due to these powerful anti-inflammatory and antioxidant properties. Cat's claw therapy has been used as the sole medication for patients with osteoarthritis, and it has also been used along with pharmecutical medications as complementary and or alternative treatment (Vitetta, Cicuttini, & Sali, 2008).
Cat’s Claw and Osteoarthritis: Studies and Research
Scientists have conducted a number of studies to establish the health benefits of cat’s claw in osteoarthritis therapy. Most of the studies revolve around the plant’s potential to prevent inflammation and oxidation. Klaus Keplinger conducted the first documented research on cat’s claw in the 1970s and 1980s. According to the research by
Keplinger, cat’s claw is endowed with immune “strengthening” properties which are explainable due to the presence of oxindole alkaloids (Keplinter et al., 1999). Another study was conducted by Piscoya et al., (2001), to investigate the efficacy and safety of freeze-dried cat's claw in osteoarthritis of the knee. Even though the study was assessing a less used genera (Uncaria guianensis) of uña de gato, the researchers have stressed that 47
this genera of the herb has similar anti-inflammatory and antioxidant features as U. tomentosa, for treating symptoms of osteoarthritis. Piscoya et al., (2001), showed that patients who had pain that was associated with activity as well as patient/medical assessment scores were all significantly improved, and that the patients benefited within
the first week of treatment with cat’s claw extracts. Piscoya et al., (2001) concluded that
cat’s claw should be considered a significant therapy in alleviation of chronic
inflammation; hence the herb is highly regarded in South America and now throughout
the world.
Miller et al., (2006), assessed the effects of cat’s claw when human cartilage cells were subjected to interleukin-1 beta, an agent that triggers erosion of joint cartilage
matrix. The study concluded that the use of cat’s claw was pertinent in the treatment of
degenerative diseases as it helped to bring to normal the levels of Insulin-like growth factor-1 which slows matrix erosion and helps protect joints (Miller et al., 2006).
According to the study, cat’s claw was positively associate with the preservation of
healthy cartilage in aging joints (Miller et al., 2006).
Mur et al., (2002), conducted research to assess the effectiveness of cat’s claw for degenerative conditions with a particular focus on rheumatoid arthritis. The disease is characterized by multiple immune system modulated systemic effects as well as severe joint inflammation and stiffness, the synovial joint impacts also define osteoarthritis. The study indicated that the participats experienced significant improvement in swollen and painful joints (Mur et al., 2002). Mur et al., (2002) concluded that the improvement in joint pain was due to treatment with cat’s claw extract. This study indicates the need 48
fully understand the biomolecular mechanisms of cat’s claw function as rheumatoid
arthiritis is a condition of autoimmune disfunction.
Ahmed et al., (2005), explored the biological basis for a number of botanicals
used in osteoarthritis and rheumatoid arthritis. Among the numerous herbs the researchers
examined were the two most common genera of cat’s claw, Uncaria tomentosa and
Uncaria guianensis. They discovered that concentration of pentacyclic oxindole alkaloids in each genera provided immunomodulating, antioxidant, and anti-inflammatory effects
(Ahmed et al., 2005; Kośmider, 2017;Williams, 2001).
Chrubasik et al., (2007) also conducted a study to explore the proof of effectiveness of herbal anti-inflammatory drugs in the therapy for chronic low back pain and osteoarthritis. The researchers conducted systematic reviews of various medical journals and libraries to obtain data to prove the applicability of herbal drugs that are orally administered to treat these degenerative conditions. The authors concluded that use of cat’s claw herb was effective due to the presence of naturally occurring alkaloids that aid in fighting inflammation and amelioraiton of low back pain (Chrubasik et al., 2007)
Hardin (2007), studied the development of osteoarthritis, particularly the suppression of collagen fiber degradation by blocking the action of cytokines (NF-kB, and TNFα), and also cat’s claw’s antioxidant benefits. The herb action according to
Hardin can in part be expalined by the ability to slow or prevent the destruction of cartilage with at least one cytokine involved in this as well as the well researched antiinflammatory and antioxidant actions (Kessler, Davis, Foster, Rompay, Walters, &
Wilkey, 2001). In light of this research the action of cat’s claw on the immune system 49
deserves further study in order that its biomolecular actions and long-term safety be understood.
Negative-Side Effects of Cat’s Claw
Even though cat’s claw herb is associated with numerous health benefits, it still
has some negative effects. Being a herb, cat’s claw has both desirable and undesirable
properties associated with the constituent alkoloids providing its effects; hence the
alkoloid extraction and supplement preparation process should receive utmost
consideration. The herb contains tetracyclic alkaloids (TOA) which most manufacturing
companies claim are toxic or harmful to human beings and must be removed from
supplements for human consumption. Further, cat’s claw also has other beneficial
oxindole alkaloids known as pentacyclic alkaloids (POA) which must be isolated and concentrated at an effective consistent dosage (Caon et al., 2014; Ganzera et al., 2001).
Further, since not all benefits or uses of cat's claw have been validated by the Food and
Drug Administration (FDA), usage of the the herb cannot be medically recommended as
a substitute in place of drugs prescribed by physicians (Caon et al., 2014).
Among the most common potential concerns about the use of cat’s claw include
the fact that it is sold as an herbal and thus, nutritional, supplement with no regulated
standards of manufacturing overseen by the U.S. FDA in place. Many marketed
supplements have been found to contain other drugs or toxic metals; hence cat’s claw has
similar risks when unregulated. Therefore it is essential to purchase herbal supplements
from a known, reliable manufacturing source (i.e. Standard Process) that uses thrid party 50
certification and scientific methods to assure the removal of harmful alkaloids, standard dosage of active alkaloids, and minimization of contamination (Scott & Elmer, 2002).
For most people, cat's claw has been found to be possibly safe when taken orally for short periods of time (Cat’s Claw, 2014). Nonetheless, side effects such as dizziness, headache, and vomiting have been reported among some users. Due to a lack of long- term and pregnancy/lactation studies precautions against using the herb when pregnant or during breastfeeding have been issued by researchers and medical authorities (Hardin,
2007). It is advisable that pregnant mothers as well as those breastfeeding refrain from its intake. It also necessary for women seeking to be pregnant, as well as children who are below three years of age, to avoid the use of cat’s claw until there is a full biomolecular and long term-use understanding of the pharmacological actions and health impacts of the herb (Hardin, 2007; Williams, 2001). The other negative effect of cat’s claw is that it might contribute to hyperactivity or pertubations of the immune system (Kemper, 1999).
As a result, there could be an increase in the symptoms of auto-immune illnesses such as lupus (systemic lupus erythematosus) and multiple sclerosis (Kemper, 1999). Therefore, any individual with any auto-immune disease should avoid using cat’s claw unless it is prescribed by their healthcare provider.
Researchers suggest that it might also cause bleeding disorders as it has the potential to slow blood clotting (Spaulding-Albright, 1997). With such a potential risk, there is a concern that the herb is likely to heighten the risk of bleeding or bruising, particularly for people with such preexisting bleeding disorders or who may already be taking blood thinners for other medical conditions such as atrial fibrillation. Another 51
potential side effect of cat’s claw use is complications during surgery as it might make the control of blood pressure and/or bleeding difficult. In that light, patients scheduled for surgery are advised to stop taking cat’s claw. Lastly, use of cat’s claw is believed to pose side effects to patients with leukemia due to the difficulties it presents in the control of bleeding and/or blood pressure (Spaulding-Albright, 1997).
52
CHAPTER 3
METHODOLOGY, RESEARCH HYPOTHESES, QUESTIONS, AND OBJECTIVES
Given the previous discussion of cat’s claws reported benefits and the limited understanding of its biomolecular and immune system actions, the need for additional information is clear. Therefore, this study was envisioned to provide additional information to the body of knowledge concerning this herb by studying the in vitro responses of human lymphocytes from individuals with active osteoarthritis under varying treatment levels of cat’s claw. Thus, three null hypotheses and three alternate hypotheses were developed to guide this study:
Null Hypotheses
H : Cat’s claw (Uncaria tomentosa) will have no significant difference of effect, from
0 individuals with osteoarthritis, within treatments or between exposed and non-exposed
cells for the following:
H : Cat’s claw will have no significant difference between exposed and non-exposed
01 cells, nor between treatment gradients on lymphocyte proliferation.
H : Cat’s claw will have no significant difference between exposed and non-exposed
02 cells, nor between treatments on nitric oxide stress.
H03: There will be no significant difference between various questionnaire items such as
demographics, weight, length of disease, medications taken, etc. between exposed and
non-exposed cells, nor between proliferation and nitric oxide stress.
53
Alternate Hypotheses
H : Cat’s claw (Uncaria tomentosa) will have a significant difference of effect on
𝑎𝑎 lymphocytes, from individuals with osteoarthritis, within or between exposed and non-
exposed cells for the following:
H : Cat’s claw will have a significant difference on exposed and non-exposed cells by
𝑎𝑎1 treatment gradient on lymphocyte proliferation.
H : Cat’s claw will have a significant difference between exposed and non-exposed
𝑎𝑎2 cells by treatment gradient on nitric oxide stress.
Ha3: There will be a significant difference between various questionnaire items such as
demographics, weight, length of disease, medications taken, etc. between exposed and
non-exposed cells, nor between proliferation and nitric oxide stress.
Research Questions
Several research questions have been developed to guide this study. These include
the following: (1) Are there differences in lymphocyte proliferation between the different
treatments? (2) Are there differences in nitric oxide expression between the different
treatments? (3) Are either proliferation and/or nitric oxide expression significantly
associated with specific demographics at any treatment levels?
54
Objectives
This study has several objectives. One objective is to monitor the effectiveness of cat’s claw at various treatment levels on nitric oxide stress and lymphocyte proliferation.
Another is to increase awareness and understanding of the possible benefits of natural herbs as an alternative to pharmaceutical products as well as identify any potential long- term use concerns. The third objective is to reduce risks from the use of pharmaceutical products, since adverse effects are common, and the long-term efficacy of these drugs is variable. And the fourth objective is to improve health and well-being of the population by providing further information about the safety and effectiveness of low-cost, minimal side-effect alternatives.
Significance of the Study
The benefit of cat’s claw has been widely researched. This study is significant for several reasons. First, it will increase existing knowledge and awareness about osteoarthritis treatment. Secondly, it has the potential to increase awareness and understanding of the possible benefits of natural herbs as an alternative to pharmaceutical products. Thirdly, it will contribute to the understanding of the biomolecular mechanisms of cat’s claw’s effectiveness. Finally, it will aid in the identification of areas for further research on the mechanisms of cat’s claws action, potential other uses, and long-term safety.
55
Limitation The limitations of the study are as follows:
1. The sample size of the study is relatively small with only 25 participants.
2. The research will be done in the lab in vitro versus in vivo.
3. Participants will self-identify themselves as osteoarthritis patients.
4. Participants may not be not totally accurate in their responses to the questionnaire.
Methodology
This study was approved by the Institutional Review Board (IRB; See Appendix
A). This in vitro study examined the effects of different concentrations (treatments at 0,
10, 100, 150, 250, and 450 ppm) of cat's claw (Uncaria tomentosa) on nitric oxide stress and lymphocyte proliferation of individuals with osteoarthritis disease. This was accomplished by application of standard cell culture techniques, in vitro and using the participant as their own control (0 ppm treatment).
Study Design
The study was designed in-vitro (micro-cell well plates) with blood samples taken from each participant and processed to extract mononuclear cells. Peripheral blood mononuclear cells (PBMCs) consist of lymphocytes and monocytes that are used for various experiments, including human immunology, (proliferation studies) production of cytokines and nitric oxide expression (Hunziker, Lippuner, Keel, & Shintani, 2015).
Following full, informed consent and a prescreening discussion with participants to eliminate anyone with preexisting autoimmune disease, a blood draw for each participant in the study was done with a total of 15 – 20 milliliters of blood obtained 56
(four, 5 ml vials). The blood sample obtained falls within Red Cross guidelines. Blood
draws were scheduled through the Student Health Clinic (SHC) at University of Northern
Iowa. Thus, blood was drawn by a qualified phlebotomist. At the time of the blood draw
a short questionnaire was completed by each participant with sections covering
demographics and factors known to be associated with immune system function
(osteoarthritis history, general health, medications, herbs, supplements, smoking history,
and psychosocial stress) (see Appendix D ).
In all cases, samples were obtained and transported to the lab, under ice, for
immediate processing of mononuclear cells (lymphocytes) within the required time frame
of 2-3 hours. Failure to accomplish this within the required time frame, could have
affected the results. However, once timely processing was started, the length of the
experiment did not affect the findings. Mononuclear cells were isolated using cell
separation techniques involving the use of a Ficoll-Hypaque density-gradient
centrifugation method, according to standard immunology procedures as detailed by
Kanof, Smith and Zola (1996; see Appendix J). The viable isolated mononuclear cells were processed to obtain counts and viability using a Millipore MUSE Unit
(7200121194) flow cytometer. The mononuclear cells were then plated into the micro- cell well plates and treated with different concentrations of USP grade cat’s claw ranging
from 0, 10, 100, 150, 250, 450 ppm, where 0 ppm indicated untreated control. All
controls and treatments were then challenged with a mitogen to encourage cell
proliferation. The cells were then incubated at 35 with 5% CO level for 48 hours as 2 per standard procedure. ℃ 57
After 48 hours, the cells (both unchallenged and challenged) were evaluated for nitric oxide expression using the Millipore MUSE flow cytometer. This allowed the researcher to determine the impact of treatment on nitric oxide expression. After and additional 96 hours, both unchallenged and challenged cells were counted to find total number of viable cells by counts and viability test via flow cytometry, allowing the researcher to evaluate lymphocyte proliferation as per standard procedures (see Appendix R, S, & T).
All bio-hazardous waste was properly handled via University of Northern Iowa-
Environmental Health and Safety. MS Excel program and JMP13, SAS Institute software were used for analysis of collected data from questionnaire survey, lymphocytes proliferation and nitric oxide expression. Data was analyzed by standard statistical procedure that included univariate (generating mean, standard deviation, mode, etc.), bivariate (for continuous values), and ANOVA analysis (for categorical and continuous values; See Figure 2). Detailed aspects of the study design having bearing on the reliability and generalizability of the research are further discussed below. 58
Figure 2: Flowchart of research design
59
Participant Selection
Participants were selected as a convenience sample by invitation. This was
accomplished by the distribution of flyers throughout departments at the University of
Northern Iowa and outreach to local physician’s offices or venues where individuals with osteoarthritis could be found (such as, Cedar Valley SportsPlex, Young Men's Christian
Association (YMCA), and churches). The researcher provided e-mails and phone contact
information for participants interested in signing-up, and for those selected to participate,
so they could have questions and concerns addressed. Participation in the study was voluntary and the participant could withdraw from the study at any time. This research study had 25 participants on or between the ages 35 to 65 years old, with osteoarthritis.
Participants selected for this study could have no other immunological diseases such as
Grave’s disease or major immunological stressors, except osteoarthritis, and could not be using drugs that would alter the immune response. Participants were excluded from the study if they confirmed having diagnosed autoimmune diseases or if they were taking immunosuppressive drugs. All participants received a $10.00 Kwik Star gas card per blood draw to offset the inconvenience and cost of driving to the UNI Student Health
Center for a professional blood draw.
60
Details of Questionnaire Survey
Participants were given a consent form that described the nature and purpose of
the study, gave an explanation of the blood draw procedure risks/benefits, as well as
rights of refusal to participate and confidentiality (See Appendix C).
The researchers obtained basic demographics and immunological status from
participants via the questionnaire. The questionnaire was divided into three parts:
demographic information, medication information, and health information. The
demographic information section included questions pertaining to age, gender, weight,
and height. The medication information section had various questions on different
medications for osteoarthritis such as herbs, vitamins, prescribed medication, and steroid
injections. In the health information section, there were various questions on different
health conditions; for instance, blood type, joint pain, joint injury, and a history of
osteoarthritis in their family. The questionnaire included questions on how long they have
suffered from osteoarthritis, and how physically limited by the pain they were. A copy of
the questionnaire used is included as Appendix D. The researcher assumed that the
information provided by each participant was correct and not biased (See Appendix E for
the project checklist).
Laboratory Preparation Prior to Analysis
All necessary glassware and equipment was sterilized 24 hours prior to obtaining blood samples. Researchers wore lab coats, sterile gloves, head caps, safety glasses, and
masks before starting any analysis (See Appendix U). All equipment and the sterile hood were cleaned with 99.8% Isopropanol prior to starting any analysis. Further, the hood’s 61
ventilation fan was at high airflow speed at least 15 minutes prior to beginning and was
treated with UV light for complete sterilization for at least 30 minutes prior to starting
any analysis. Apparatus that were needed (50ml conical centrifuge tube, 1.5ml centrifuge
tube, 10 and 5ml sterile pipets, sterile syringe, pipets, pipet tips, and beakers) were placed
inside the hood. If any new glassware or equipment was needed during laboratory work,
they were wiped with 99.8% Isopropanol before placing them inside the hood.
Preparing Chemicals
For our study we prepared Roswell Park Memorial Institute Medium (RPMI*)
mixture, RPMI+ mixture, phytohaemagglutinin (PHA), and cat’s claw solution. For a
detailed description of the preparation of these mixtures see the Appendices as indicated
in the list below.
1. Make RPMI* mixture (See Appendix F).
2. Make RPMI+ mixture (See Appendix G).
3. Reconstitute Phytohaemagglutinin (PHA; See Appendix H).
4. Make cat’s claw treatment solutions (See Appendix I).
Contamination Quality Control/Evaluation
After 48 hours, we took a quick look at the culture plate under the tissue culture scope on the highest magnification. The color should be pale pink to light yellow but
should not be bright yellow; and there should be no signs of bacteria or fungal
contamination (See Appendix O, P, & Q). This was an extra check on the sterile
procedure and quality control for the plating techniques. 62
Statistical Analysis
The data collected from the questionnaire survey, lymphocytes proliferation, and nitric oxide stress was entered into MS Excel program and then imported to JMP 13 software from SAS institute. Data was analyzed by standard statistical procedures that include univariate, bivariate, and ANOVA analysis.
63
Equipment Quality Control and Assurance
Muse System Check
Before running any test using the Millipore MUSE unit (flow cytometer), a
system check procedure was ran to assure the Muse Unit was providing reliable and
accurate results. To run the system check procedure, we added 20µl of bead reagent
(control faux cells) with 380µl of system check diluent in a micro-centrifuge tube; both
reagents were mixed thoroughly, system check was ran, and the return of standard cell
counts verified.
Incubator Cleaning and Disinfecting
It is very important to ensure that there is not any contamination in the incubator
environment. Between experimental sets the incubator was sterilized with 99.8%
isopropanol which was then left to dry completely. The humidity tray was filled with 2.5
liters of reverse osmosis and microfiltered water with a teaspoonful of copper sulphate added. Intermittently between test runs, high temperature disinfection was used to heat internal surfaces to 120°C for 4 hours, and then cooled to the programmed temperature of
37°C before being placed back into service.
Pipettes Calibration
Calibration was required of all pipettes to maintain their accuracy and precision to obtain correct volumes of liquids. Calibration/adjustment was completed by the manufacturer according to the recommend one year to six months guidelines based on frequency of use and degree of accuracy needed for the intended application. 64
CHAPTER 4
RESULTS
This chapter presents the results of data collected via survey and through laboratory work conducted on osteoarthritis patients cultured, treated and challenged mononuclear cells (lymphocytes). Univariate and bivariate tests were performed on the data using JMP13, SAS Institute software explore the impact on the lymphocyte proliferation and nitric oxide stress under experimental conditions.
Demographic Information
Age and Body Mass Index (BMI)
This table below indicates the following information about the age and BMI of the participants (Table 1). The minimum age was 37 and maximum age was 65 with a mean of 56.2, median of 57, and standard deviation of 6.8617296. The BMI of the participants ranged from a minimum of 21.63 to a maximum of 49.6 with a mean of
31.5652, median of 30.54, and standard deviation of 7.2626052. Detailed distribution statistics of demographic information can be found in Appendix X1.
Table 1: Distributions among age, weight, and height
Distributions N Minimum Maximum Mean Median Std.
Deviation
Age (years) 25 37 65 56.2 57 6.8617296
BMI 25 21.63 49.6 31.5652 30.54 7.2626052
65
Gender
There were a total of 25 participants, including 21 females and four males (Figure3).
Figure 3: Gender distribution of study participants
Medication Information
Herbs, Vitamins, and Pharmaceutical Exposure
This study included information on participants who were taking herbs, vitamins, prescribed medications, and joint steroid injection. Of the 24 participants 20 participants did not take any herbs and four participants took herbs (Figure 4). Turmeric was the most common herb taken by participants (Figure 5). The detailed distribution statistics of herbs are available in Appendix X2.
Also, this section indicates how many participants were taking vitamins daily.
Nineteen out of 25 participants were taking vitamins and the remaining six were not
(Figure 4). The most common vitamins were multivitamin, vitamin D, calcium, and omega-3 and 6 fatty acid supplements (figure 5; see Appendix X2). 66
Additionally, the study examined if participants were taking any pharmaceutical medications or not. Of 25 participants, 22 were taking prescribed medication and three
were not taking any prescribed medication (figure 4). The top prescribed medications
used were: cardiovascular, antihistamines, pain relievers (NSAIDs), anti-depressants, and anti-inflammatories (NSAIDs; figure 5). Detailed information is provided in Appendix
X2.
This graph below indicates the number of participants who took joint steroid injections to manage arthritis pain. Eleven participants did not take any joint steroid injections and 14 did take joint steroid injections out of a total of 25 (Figure 5).
Figure 4: Distributions among herb, vitamin, prescribed medication, and joint steroid injection 67
Figure 5: Distributions among common herbs, vitamins, and medications
Health Information
Cold or Flu, Life Change or Loss, Allergies, and Immunological Diseases
This study examined the number of participants who have had a cold or flu in the past two weeks, any major life change/loss, and any immunological diseases. There were a total of 25 participants of which none had had a cold or flu (Table 2). Of the 25 participants six had experienced a major life change/loss while 19 participants did not have any major life change/loss (Table 2).
Participants were also asked if they had any immunological diseases other than osteoarthritis. Of the 25 participants none had had any diagnosed immunological diseases other than osteoarthritis (Table 2).
The table below also shows the number of participants who suffered from allergies. Seventeen out of 25 participants suffered from allergies and eight participants did not suffer from allergies (Table 2). The highest category of allergies reported was environmental (See Figure 6). Detailed information is provided in Appendix X3.
68
Table 2: Health information among participants
Respond Cold or Flu Immunological Allergies Life Diseases Change/Loss Yes 0 0 17 6 No 25 25 8 19 Total 25 25 25 25
Figure 6: Common allergies among participants
Osteoarthritis History
Length of Osteoarthritis
The participants were asked about the maximum length of time they had osteoarthritis. The maximum length of time the participant’s reported having osteoarthritis was 30 years and the minimum was four years. (Figure 7). 69
Figure 7: Length of osteoarthritis among participants
Family History of Osteoarthritis
Figure 8, illustrates whether participants had any history of osteoarthritis in their family. Twenty participants out of 25 reported having a family history of osteoarthritis.
Of the family members’ history of osteoarthritis, the most commonly reported relative was the mother followed by the father.
Figure 8: Family history of osteoarthritis among participants
70
Injuries
The figure below shows the number of participants who had previous injuries in
the affected joint(s). Ten participants out of a total of 25 previously had injuries and 15 participants never had any injuries (Figure 9). The figure below also shows the most common injuries among participants. The most common injury was knee injuries followed by spine injury, and hip injury (Figure 9; See Appendix X3).
Participants 16 14 12 10 8 6 4 2 0 Injuries knee spine injury hip injury injuries
YES NO
Figure 9: Common injuries among participants
Pain Severity
This table indicates the level and severity of pain experienced in the last 30 days
among participants. Twelve participants experienced lots of pain and 13 participants
experienced some pain (Table 3). Also, the figure below points out the areas in which
participants most often feel the pain. Most participants identify the knees, hands, hip, and
spine as the area of greatest pain (Figure 10; see Appendix X3). 71
Table 3: Pain severity among participants
Pain Level Participants Lots of pain 12 (48%) Some pain 13 (52%) Total 25
Figure 10: Specific pain areas among participants
72
Physical Activity
This figure below indicates the number of participants who reported being physically active or physically limited by osteoarthritis pain. Twenty out of 25 participants reported being physically active and five participants were not physically active (Figure 11). Additionally, the figure below shows the frequency of participants’ physical activities on a weekly basis. The most frequently reported rate for physical activity was seven times a week and the least frequent was two times a week (Figure 11).
Participants 25
20
15
10
5
0 YES NO 2x/week 3x/week 5x/week 6x/week 7x/week
Physically Limited Physically Active Work-out Frequently
Figure 11: Physical activity among participants
73
Lymphocytes Proliferation Statistical Results
The tables below illustrate bivariate fit tests of lymphocyte proliferation at various
concentrations of cat’s claw herb 0 ppm, 10 ppm, 100 ppm, 150 ppm, 250 ppm, and 450 ppm, following stimulation with mitogen, and based on the following factors: age, number of prescribed medications, joint steroid injections, length of osteoarthritis,
physically limited, physically active (workout y/n), pain severity (lots of pain and some
pain), pain area (hip and knee), family history, and allergies.
Association of Various Concentrations of Cat’s Claw on Lymphocytes Proliferation
A bivariate fit test/simple linear regression at control and the various treatment
levels of cat’s claw compared with demographics was used to examine proliferation
response. Table 4 illustrates the direction of cell proliferation following stimulation and
at different treatment dosages based on the mean and the trend of the bivariate fit test.
Additionally, Table 5 demonstrate statistically significant trends between demographics
and cat’s claw treatments, trends where the p value was between 0.06 and 0.09 and the
absolute t was significant at ≤ 0.05. These trends are reported as the sample size is small
and future studies may find this useful.
The findings of Table 4 indicate that when age increased the cell proliferation
decreased. Also, when the number of prescribed medication increased, the proliferation
decreased. For those who took joint steroid, the proliferation decreased, while it increased
in those who did not take joint steroid. Participants who had osteoarthritis for a longer
time period, and those who were physically limited had a decrease in proliferation. Those
participants who were not physically limited had an increase in proliferation. There was 74
no association between proliferation and participants who were physically active, whereas there was a decrease for those who were not physically active. Regarding pain severity, participants who had some pain had proliferation increases while participants who had lots of pain, had proliferation decreases. Also, those who had knee pain had proliferation increases, while those who had hip pain had proliferation decreases. Where there was family history of osteoarthritis, proliferation increased. However, there was a decrease where there was no family history of osteoarthritis. Proliferation increased for participants who had allergies but decreased for those who had no allergies. None of these relationships were statistically significant but are reported due to the small sample size of the study. Detailed analyses are provided in Appendix Y.
The findings of Table 5 illustrate that the number of prescribed medications taken at 100 ppm and 150 ppm cat’s claw treatment was associated with lymphocyte proliferation. This was statistically significant at p<0.05.
75
Table 4: Descriptive trends between demographics, cat's claw treatments and lymphocyte proliferation
10 100 150 250 450 Demographics 0 ppm ppm ppm ppm ppm ppm Age (D) (D) (D) (D) (D) (D) Number of Prescribed Medication (D) (D) (D) (D) (D) (D) (Increasing Numbers) Joint Steroid (Yes/No) (D / I) (D / I) (D / I) (D / I) (D / I) (D / I) (Taking injections) Length of Osteoarthritis (D) (D) (D) (D) (D) (D) (Longer Duration) Physically Limited (Yes/No) (D / I) (D / I) (D / I) (D/ I) (D/ I) (D / I) (Reporting Limitations) Physically Active (Yes/No) (NA/D) (NA/D) (NA/D) (NA/D) (NA /D) (NA/D) Pain Severity (Lots of Pain/Some Pain) (D / I) (D / I) (D/ I) (D/ I) (D / I) (D / I) (More Severe) Pain Area (Hip/Knee) (D / I) (D / I) (D / I) (D / I) (D / I) (D / I) (Hip Pain) Family History (Yes/No) (I / D) (I / D) (I / D) (I / D) (I / D) (I / D) (Positive History) Allergies (Yes/No) (I / D) (I / D) (I / D) (I / D) (I / D) (I / D) I: Increase, D: Decrease, NA: No Association
76
Table 5: Statistically significant associations between demographics, cat’s claw treatments and lymphocytes proliferation, bivariate fit.
Demographics Doses R Adj R F Ratio P Value Abs. t test square square
Number of 100ppm 0.186443 0.135596 3.6667 0.0736 <.0001* Prescribed 0.281692 150ppm 0.323945 7.6667 0.0137* <.0001* Medication
Nitric Oxide Expression Statistical Trends
The tables below illustrate trends in nitric oxide stress at various treatment levels:
0 ppm, 10 ppm, 100 ppm, 150 ppm, 250 ppm, and 450 ppm based on the following factors: age, herbs, vitamins, number of prescribed medications, joint steroid injections, length of osteoarthritis, physically limited, physically active (workout), pain severity (lots of pain and some pain), pain area (hip and knee), family history, and allergies.
Association of Various Concentrations of Cat’s Claw on Nitric Oxide Expression
A bivariate fit/simple linear regression test at various treatment levels of cat’s claw compared with demographics was used to examine nitric oxide response of the lymphocytes following mitogenic challenge. Table 6 indicates the trends and direction of nitric oxide expression following stimulation and at different treatment dosages, while
Table 7 demonstrates statistically significant relationships at p<0.05. Trends where the p value was between 0.06 and 0.09 and the absolute t was significant at ≤ 0.05 were reported as the sample size is small and future studies may find this useful. 77
Results indicated that age and various concentrations of cat’s claw exhibited a trend toward increased nitric oxide expression at 10 ppm, 100 ppm, 150 ppm, 250 ppm and 450 ppm and a decrease at 0 ppm. With regards to the number of the cells that expressed the nitric oxide, there was a decrease at all concentration levels for those who had osteoarthritis for longer periods of time, except at 150ppm and 450ppm, wherein which the trend was toward an increase.
Participants who took herbs exhibited a trend toward a decrease in number of cells that expressed nitric oxide in all different concentrations of cat’s claw, while those who did not take any herbs had an increase in the number of cells that expressed nitric oxide at 0 ppm and 100 ppm, and no association at 10 ppm, 150 ppm, 250 ppm, and 450 ppm. For participants who took vitamins, the number of cells that expressed nitric oxide decreased at 0 ppm and 100 ppm, and had no association at 10 ppm, 150 ppm, 250 ppm, and 450 ppm. There was an increase in the number of cells that expressed nitric oxide at all concentration levels for participants who did not take any vitamins.
A trend was seen when the number of prescribed medications increased the number of cells expressing nitric oxide decreased at 0 ppm, 10 ppm, 100 ppm, and 250 ppm, but increased at 150 ppm and 450 ppm. At all concentrations of cat’s claw, the number of cells that expressed nitric oxide increased for participants who had joint steroid injections, except at 100 ppm, which had no association, and decreased for those who had no joint steroid injections. 78
Participants who were physically limited had an increase in the number of cells that expressed nitric oxide at all concentrations levels, except 0ppm and 100ppm, which had no discernable trend. There was no trend between physically active participants and the number of cells expressing nitric oxide at all levels of cat’s claw concentrations.
However, those participants who were not physically active had a decrease in nitric oxide expression at all levels of cat’s claw concentration, except at 100 ppm which had no discernable trend. For participants who worked out 2 times a week, there was a decrease in the number of cells that expressed nitric oxide at all concentrations, except 0ppm and
100ppm, which had an increase. Those participants who worked out 3 times a week had a decrease in the number of the cells that expressed nitric oxide at all concentration levels, except at 0ppm, which had an increase, and no observable trend at 10ppm. For those who worked out 5 times per week, there was an increase in the number of cells that expressed nitric oxide at all concentration levels, except at 0ppm and 150ppm which had a decrease and no discernable trend at 450ppm. Additionally, for those who worked out 6 times a week, there was an increase in the number of the cells that expressed nitric oxide at 0ppm and 450ppm, and a decrease at the other treatment levels. Finally, for those indicating they worked out daily, there was an increase in the number of the cells that expressed nitric oxide at all concentration levels, except 0 ppm which had no discernable trend.
In the category of pain severity, the number of cells that expressed nitric oxide decreased at all concentration levels for those reporting greater pain severity, except at
100 ppm, which exhibited an increasing trend of nitric oxide expression. On the other hand, there was an increase of nitric oxide expression at all treatment levels for those who 79
had some pain, except at 100 ppm which had a decrease in the number of cells that expressed nitric oxide. Participants who had pain in the hip area, had an increase in the number of the cells that expressed nitric oxide at 0 ppm, 10 ppm, 150 ppm, 250 ppm, and
450 ppm, and decreasing trend at 100 ppm. Additionally, there was also an increase in the number of cells that expressed nitric oxide at all concentrations of cat’s claw, except at
100 ppm, which had a decrease, for those who had pain in the knee area.
The number of the cells expressing nitric oxide exhibited no discernable trend at any treatment level for participants who had a positive family history of osteoarthritis, except at the 100ppm treatment level which exhibited an increase. For those who had no family history of osteoarthritis, there was an increase in nitric oxide expression at all treatment levels except for 100 ppm which had a decrease in the number of the cells that expressed nitric oxide. In regard to allergies (individuals reporting having allergies), there was a decrease in the number of the cells that expressed the nitric oxide at 10 ppm, 150 ppm, 250 ppm, and 450, and an increase at 100 ppm, with no association at 0 ppm. While for those who had no allergies, there was an increase in the number of the cells that expressed nitric oxide, except at100 ppm where there was an observable decrease.
Table 7 illustrates that age, length of osteoarthritis, and how often participants worked out, were found to be associated with nitric oxide expression. This illustrates a statistically significant bivariate fit at p<0.05 at100 ppm for age, 0ppm and 100ppm for the length of osteoarthritis, and 100ppm, 150 ppm, and 450 ppm for how often the participants worked out (Table 7; See Appendix Z). 80
Table 6: Descriptive trends between demographics, treatment levels, and nitric oxide expression
10 100 150 250 Demographics 0 ppm 450 ppm ppm ppm ppm ppm Age (D) (I) (I) (I) (I) (I) Length of Osteoarthritis (D) (D) (D) (I) (D) (I) (Longer Duration) Herbs (Yes/No) (I/D) (I/NA) (I/D) (I/NA) (I/NA) (I/NA) (Taking Herbs) Vitamins (Yes/No) (D/I) (NA/I) (D/I) (NA/I) (NA/I) (NA/I) (Taking Vitamins) Number of Prescribed Medication (D) (D) (D) (I) (D) (I) (Increasing number) Joint Steroid (Yes/No) (NA/ (I/D) (I/D) (I/D) (I/D) (I/D) (Taking Injections) NA) Physically Limited (Yes/No) (NA / (NA/ (I/D) (I/D) (I/D) (I/D) (Reporting Limitation) NA) NA) (NA/ (NA/D Physically Active (Yes/No) (NA/D) (NA/D) (NA/D) (NA/D) NA) ) How Often you Workout/ 2x/w (I) (D) (I) (D) (D) (D) How Often you Workout/ 3x/w (I) (NA) (D) (D) (D) (D) How Often you Workout/ 5x/w (D (I) (I) (D) (I) (NA) How Often you Workout/ 6x/w (I) (D) (D) (D) (D) (I) How Often you Workout/ 7x/w (NA) (I) (I) (I) (I) (I) Pain Area (Hip/Knees) (D/I) (D/I) (I/D) (D/I) (D/I) (D/I) (Hip Pain) Pain Severity (Lots of pain/Some Pain) (I/D) (I/D) (D/I) (I/D) (I/D) (I/D) (More Severe) Family History (Yes/No) (NA/I) (NA/I) (I/D) (NA/I) (NA/I) (NA/I) (Positive History) Allergies (Yes/No) (NA/I) (D/I) (I/D) (D/I) (D/I) (D/I) I: Increase; D: Decrease; NA: No Association
81
Table 7: Statistically significant associations between demographics, cat's claw treatments and nitric oxide expression, bivariate fit
Demographics Doses R Adj R F P Abs. t test square square Ratio Value
Age 100ppm 0.14681 0.109714 3.9576 0.0587 0.1664
Length of 0ppm 0.281584 0.245663 7.8390 0.0111* 0.3548 Osteoarthritis 100ppm 0.258956 0.221904 6.9890 0.0156* 0.9298
100ppm 0.64926 0.309209 3.0143 0.0036* * How Often 150ppm 0.425028 0.26075 2.5872 0.0826 * you Workout 450ppm 0.64926 0.549048 6.4789 0.0036* *
82
Proliferation Response Quotient by Cat’s Claw Treatment
A quotient of the stimulated and non-stimulated proliferation response was conducted to compare the magnitudes of proliferation following stimulation under the various treatments and test for statistically significant trends using ANOVA. The findings indicate there was no statistically significant association between dosages of cat’s claw
and proliferation. (See Figure 12; Appendix AA for more detailed information).
Table 8: ANOVA of proliferation response quotient by cat's claw treatments
Doses Mean Lower Upper R square DF F Ratio P Value 95% 95% 0ppm 289.244 -57.8 636.32 0.001509 5 0.0435 0.9989 10ppm 254.468 -92.6 601.54 100ppm 249.710 -97.4 596.78 150ppm 207.991 -139.1 555.06 250ppm 310.985 -36.1 658.06 450ppm 239.332 -107.7 586.40
Figure 12: ANOVA test of proliferation response quotient by cat's claw dosage 83
Nitric Oxide Quotient of Live Cells by Cat’s Claw Dosages
A quotient of the stimulated and non-stimulated conditions for only live cells was
conducted to explore the association between live cells’ nitric oxide expression under different treatments. The result demonstrated that there was no association between live cells’ nitric oxide expression and treatment levels in this sample population. See Figure
13; Appendix BB).
Table 9: ANOVA of nitric oxide live cells response quotient by cat's claw treatments
Doses Mean Lower Upper R square DF F Ratio P Value 95% 95% 0ppm 1.50174 -1.344 4.3471 0.011101 5 0.3211 0.8997 10ppm 2.27938 -0.566 5.1247 100ppm 0.91432 -1.931 3.7596 150ppm 1.19661 -1.707 4.1006 250ppm 2.70405 -0.141 5.5494 450ppm 2.86532 0.020 5.7106
Figure 13: ANOVA test of nitric oxide response quotient (live cells) by cat's claw treatments
84
Nitric Oxide Quotient of Dead Cells by Cat’s Claw Dosages
It is important to note the quotient response of stimulated and non-stimulated cells which consequently died although they expressed nitric oxide prior to or following their death. Thus, an ANOVA was conducted to determine the potential association of the dead cells’ nitric oxide expression under different treatments of cat’s claw. There was no statistically significant association found between nitric oxide expression by dead cells and cat’s claw treatments. (See Figure 14; Appendix CC).
Table 10: ANOVA of nitric oxide expression, dead cells quotient by cat's claw treatments
Doses Mean Lower Upper R square DF F Ratio P Value 95% 95% 0ppm 0.50708 -0.4506 1.4648 0.041547 5 1.2484 0.2897 10ppm 0.70548 -0.2522 1.6632 100ppm 1.63780 0.6801 2.5955 150ppm 0.22405 -0.7336 1.1817 250ppm 0.27556 -0.6821 1.2333 450ppm 0.25068 -0.7070 1.2084
Figure 14: ANOVA test of nitric oxide response quotient (dead cells) by cat's claw treatments 85
Nitric Oxide Quotient of Total Cells (live and dead) by Cat’s Claw Dosages
The magnitude of response of both live and dead cells’ nitric oxide expression
was explored together under the various treatments. A quotient of the stimulated and non-
stimulated conditions for the total cells was generated and an ANOVA was ran under the
various treatments. The results demonstrate that there was no statistically significant
association between nitric oxide expression from total cells and cat’s claw treatments in this test population. See Figure 15; Appendix DD for further details).
Table 11: ANOVA of nitric oxide response, total cells, quotient by cat's claw treatments
Doses Mean Lower Upper R square DF F Ratio P Value 95% 95% 0ppm 2.0147 -90.66 94.69 0.029413 5 0.8728 0.5011 10ppm 94.9661 2.29 187.64 100ppm 15.5591 -77.11 108.23 150ppm 93.1723 0.50 185.84 250ppm 2.6213 -90.05 95.29 450ppm 22.0538 -70.62 114.73
Figure 15: ANOVA test of nitric oxide response quotient (total cells) by cat's claw treatments 86
CHAPTER 5
DISCUSSION, CONCLUSIONS, AND RECOMMENDATIONS
Discussion
This chapter discusses the laboratory findings and data derived from questionnaire/survey of 25 osteoarthritis sufferers in light of the previously discussed
literature. It discusses the trends and associations between different levels of cat’s claw
treatments (0 ppm, 10 ppm, 100 ppm, 150 ppm, 250 ppm, and 450 ppm) lymphocyte
proliferation, nitric oxide expression, and various questionnaire associated findings.
Participant questionnaire, completed at the time of the blood draw, gathered
information pertaining to aging, number and type of prescribed medications, herbs,
vitamins, joint steroid injections, family history, length of osteoarthritis, allergy, pain
severity, pain area, physically limiting condition, and physical activity. This was
analyzed using univariate statistics, bivariate fit, and ANOVA to look for both descriptive
trends in the data and for statistically significant associations between survey data and
treatments as well as treatment levels and lymphocyte proliferation and nitric oxide
expression. Overall, relationships between treatments and proliferation as well as nitric
oxide expression did not reject the null hypothesis. However, select questionnaire items
and certain treatment levels did reject the null hypothesis at a p-value of < 0.05. Further,
some of the results were marginally statistically significant or showed a trend toward
significance when the p-value and absolute t-value where considered together. Given the
small sample size, p-values of between 0.06 and 0.09 where the absolute t was significant
were also reported. These findings are discussed below. 87
Lymphocytes Proliferation and Osteoarthritis
Lymphocyte proliferation is the process whereby lymphocytes in the body begin to replicate DNA and multiply. It occurs after the cells cross-link antigen/antibody receptors, occurring either after the recognition of an antigen in the body or after stimulation from a polyclonal activator. It is a fundamental characteristic of the response of lymphocytes following antigen stimulation (Hallab, Anderson, Stafford, Glant, &
Jacobs, 2005). According to Bocelli-Tyndall et al. (2006), lymphocyte proliferation leads to T-cell hypo-responsiveness and immunosuppression, which are common characteristics of osteoarthritis. The level of lymphocyte proliferation dramatically increases in people with osteoarthritis. This study found descriptive statistical trends between questionnaire reported items and lymphocyte proliferation, and under specific treatment levels, some questionnaire items demonstrated statistically significant associations which are further discussed below.
Nitric Oxide Expression and Osteoarthritis
Nitric Oxide is a catabolic destructive factor in osteoarthritis. Presence of Nitric
Oxide (NO) in the bodies of patients with osteoarthritis is exhibited by the presence of
INOS in the superficial layer of chondrocytes. Nitric Oxide prevents the stimulation of collagen synthesis in cartilage. Nitric Oxide causes an increase in the coalescence of matrix metalloproteinases, in a cyclic GMP-dependent manner. An increase in the synthesis of metalloproteinase leads to damage of the extracellular matrix and cartilage breakdown. Nitric Oxide also causes the coalescence of the body’s IL-1-converting enzyme and release of additional pro-inflammatory cytokines (Meggs, 1993). These 88
bio-molecular processes are partly responsible for the pain and inflammation associated
with the condition. This study found descriptive trends between questionnaire reported
items and nitric oxide expression, and under specific treatment levels, some questionnaire
items demonstrated statistically significant associations which are further discussed
below.
Aging and Osteoarthritis Osteoarthritis is common in people over the age of 60 years old. One in every 12
individuals over the age of 60 has osteoarthritis (CDC, 2017). According to medical
research, the probability of developing osteoarthritis increases with age. All participants
in this study had osteoarthritis, and ranged in age from 36 years old to 65 years old, with
52% around 50 years old and 36% around 60 years old. This study found a descriptive
trend of decreasing cell proliferation with increasing age under different levels of cat’s
claw treatment. For nitric oxide expression, the number of cells expressing nitric oxide increased at 10mppm, 100 ppm, 150 ppm, 250 ppm, and 450 ppm, and decreased at
0ppm. Age was found to be statistically associated with nitric oxide expression at the 100
ppm treatment level (p<0.05; Bivariate fit, f = 3.9576; Table 7). Medical research has
shown that aging is stochastic in nature and is characterized by the accumulation of
random cell damage in tissues, such as oxidative damage, somatic mutations, and
accumulation of defective proteins (Fazzalari, Kuliwaba, & Forwood, 2002).
Length of osteoarthritis in participants ranged between 3 years to 30 years with a mode of 10 years. Results of the study indicated that out of 25 participants, 8% were
around 40 years old and 4% around 37 years old. This supports Fazzalari et al. (2002), 89
view that there are rare cases of osteoarthritis affecting people below the age of 40 years
old. In relation to length of osteoarthritis, the study revealed that participants who had osteoarthritis for a longer time had a decreasing descriptive trend in proliferation. With
regards to the number of the cells that expressed nitric oxide, there was a decreasing trend
at all concentration levels for those who had osteoarthritis for longer periods of time,
except at 150ppm and 450ppm, which had an increase. Length of osteoarthritis, was
found to be significantly associated with nitric oxide expression at 0ppm and 100ppm
(p < 0.05; Bivariate fit, f = 0ppm 7.8390; 100ppm 69890; Table 7)
BMI and Osteoarthritis
According to Aspden (2011), obesity is one of the factors that accelerates
progression of osteoarthritis, mainly in the knee joints. Higher body mass translates to an
increase in pressure on the main support joints of the body such as hips, ankles, and
knees, which results in stress and physical strain on these joints. The increased physical
strain and pressure on knee joints and hips from increased body weight, has been proven
to cause an increase in severity of the pain associated with knee and hip osteoarthritis.
Therefore, an increase in body weight enhances the chances of suffering osteoarthritis.
Twelve percent of participants were normal weight, 68% were overweight, and 20% of
them were obese confirming the notion that weight is associated with the development
and progression of osteoarthritis.
Gender and Osteoarthritis
According to Paradowski, Bergman, Sundén-Lundius, Lohmander, and Roos
(2006), women are more likely to suffer from osteoarthritis than men, due to many 90
factors such as child birth, obesity, and estrogen. For example, estrogen, a female hormone, is believed to protect cartilage from deteriorating. However, the production of estrogen drops precipitously after menopause, leaving women’s cartilage at greater risk of inflammation leading to osteoarthritis. Despite intentional recruitment of both genders, this study had 84% female participants and 16% male participants confirming the perception that women are more susceptible to osteoarthritis than men.
Herbs and Osteoarthritis
There are several herbs that contain natural substances which are known to regulate pain and inflammation that comes with osteoarthritis. Nonetheless, people are often unaware of such herbs, which were mostly used traditionally, to manage osteoarthritis conditions (Mckenzie, Baker, Buffinton, & Doe, 1996). In this study 16%
(4) took herbs to reduce osteoarthritis pain and 80% (20) did not take any herbs, indicating a possible lack of awareness about the potential benefits of different herbs.
Participants who took herbs had a decreasing trend in the number of cells that expressed nitric oxide at all treatment levels. However, those who did not take any herbs had an increasing trend in the number of cells that expressed nitric oxide at 0 ppm and 100 ppm, and no noted trend at 10 ppm, 150 ppm, 250 ppm, and 450 ppm.
Vitamins and Osteoarthritis
Vitamins levels such as D and B12 have been found to have a strong association with the risk of developing osteoarthritis (Canter, Wider, & Ernst, 2007). Seventy-six percent of the participants took some variety of vitamins and 60% took vitamin D, specifically. Research has revealed that patients with low levels of vitamin D in their 91
bodies stand a three-percent higher chance of osteoarthritis progression (Canter et al.,
2007). Vitamin D is responsible for maintaining healthy calcium and phosphorous levels in the body. The latter helps keep teeth and bones strong. Low levels of vitamin D in the body leads to soft and brittle bones, weak teeth, and fragile muscles. It increases both the chances of developing osteoarthritis and the progression of osteoarthritis. According to
Canter et al., (2007), women with high levels of vitamin D in their bodies have a 30%
lower chance of suffering from osteoarthritis.
In this study 48% of the participants took vitamin B12 which helps the body to
produce healthy red blood cells. Vitamin B12 also helps lower homocysteine amino acid,
which is responsible for weak bones and associated with the decline of cartilage between
bones. Additionally, it decreases inflammation of joints, mainly around the hips,
shoulders, and knees. A reduction of B12 in the body, therefore, increases the chances of
the development and pain of osteoarthritis (Canter et al., 2007). For participants who took
vitamins, there was a trend of decreasing numbers of cells expressing nitric oxide at 0
ppm and 100 ppm treatment levels, and no apparent trends at 10 ppm, 150 ppm, 250 ppm,
and 450 ppm. There was an increasing trend in the number of lymphocytes expressing
nitric oxide at all concentration levels for participants who did not take any vitamins.
Nonsteroidal Anti-inflammatory Drugs (NSAIDs) and Osteoarthritis
Nonsteroidal anti-inflammation (NSAIDs) drugs are the most prescribed
medications to manage osteoarthritis pain and inflammation. NSAIDs cause rapid weight
gain, which may lead to obesity (Wahli & Michalik, 2012). According to medical
researchers, higher body weight increases the progression of osteoarthritis in patients who 92
already suffer the disease. Higher body weight causes growing pressure in the knee and hip joints, which translates to stress and deterioration of cartilage (Lin, Zhang, Jones, &
Doherty, 2004)
NSAIDs are known to cause tingling, numbness and muscle cramps when used to treat osteoarthritis. A common side effect of NSAIDs is the retention of fluids around joints. The retention of fluids around the joints sometimes leads to edema and causes the swelling of knee, shoulder, wrist, hip, and other body joints. Further, it prevents the maintenance of healthy cartilage in the body and creates more pressure and stress on the joints (Milder, Williams, Ritchie, Lipworth, & Day, 2010). Extra fluids around the joints reduces the rate of healing from osteoarthritis. It decreases a patient’s mobility and increases their chance of osteoarthritis progression. Forty-eight percent of the participants took anti-inflammatory drugs (NSAIDs), indicating that a huge percentage of osteoarthritis patients are taking NSAIDs, and are susceptible to their side effects. The findings indicated a descriptive trend of increasing overall prescription medicine use and decreasing lymphocyte proliferation. The number of prescribed medications at 100 ppm and 150 ppm was significantly associated with lymphocyte proliferation (p<0.05;
Bivariate fit, f = 100ppm 0.0736, 150 ppm 7.6667; Table 5). Further, a descriptive trend was observed between the overall number of prescribed medications and a decreasing number of cells expressing nitric oxide at 0 ppm, 10 ppm, 100 ppm, and 250 ppm, but this trend was reversed at 150 ppm and 450 ppm where the number of cells expressing nitric oxide increased. 93
Joint Steroid Injection and Osteoarthritis
Joint steroid injection is used to treat inflammatory diseases and conditions such as osteoarthritis. It is injected directly into joints to treat such conditions. Continuous injection of joint steroids causes the thinning of cartilage on bones in the joint regions.
Thinning cartilage causes bones to rub on each other during movements, which leads to severe pain (Arroll & Goodyear-Smith, 2004). Thinning cartilage also advances the progression of osteoarthritis and reduces the rate of healing in patients already suffering the disease. The steroid injections also cause whitening of the skin around the joint area as well as the thinning of ligaments in the joints. Of the 25 participants, 44% took joint steroid injections and 56% did not, which translates to more side effects and potential increases in joint deterioration. For participants who took joint steroid, there was a decreasing trend in lymphocyte proliferation, while it increased in those who did not take joint steroid. At all concentrations of cat’s claw, the number of cells that expressed nitric oxide increased for participants who had joint steroid injections, except at 100 ppm, which had no discernable trend. For those who did not use joint steroid injections a trend of decreasing nitric oxide expression was observed, except at 100ppm which had no discernable trend.
Stress, Depression and Osteoarthritis
Being in pain may trigger stress or depression in patients. However, if a patient suffering osteoarthritis suffers these conditions as well, pain associated with the disease often increases. Antidepressants have been proven to have adverse psychological and medical effects on patients using them. When administered to patients suffering from osteoarthritis, 94
some of these side effects lead to worsening of the condition. Antidepressants cause headaches, nausea, and abdominal pains fatigue, dizziness, and blurred vision. Fatigue and dizziness from antidepressants prevents patients suffering from osteoarthritis from performing simple physical exercises to keep their joints active and flexible. It leads to stiffness in the joints, which limits mobility in patients suffering from osteoarthritis (Fava et al., 2006).
According to Bet, Hugtenburg, Penninx, and Hoogendijk (2013), antidepressants may cause an increase in the weight of the person using them. This is dangerous for patients suffering from osteoarthritis, as it exerts increased pressure and stress on weight bearing joints such as hip and knee joints. Twenty-eight percent of the osteoarthritis patients who participated in this study indicated that were taking antidepressants, which could potentially worsen their situation.
Environmental Triggers and Osteoarthritis
Environmental toxins such as chemical pollutants, heavy metals, and pesticides have been medically proven to have an inflammatory effect on the immune response of the body (Spector & MacGregor, 2004). Cold weather has been reported to cause stiffness and reduced flexibility in patients suffering from acute osteoarthritis (Keysor et al., 2009). Also, food allergy and intolerance have been verified to trigger inflammatory episodes in osteoarthritis patients (Haugen, Kjeldsen-Krach & Forre, 1991). For example, food that contains alkaloids, gluten, omega 6, and proteolytic enzymes, lead to inflammation of joints and deterioration of joint tissues, which trigger increased pain and reduced flexibility for osteoarthritis patients (Wetherell et al., 2004; Gregory et al., 2008; 95
&Yelland et al., 2006). In this study, 68% of participants reported environmental allergies
and 32% did not. Proliferation trends increased for participants who had reported a
history of allergies but decreased for those who had no allergies. In the area of nitric
oxide, there was a decrease in the number of the cells that expressed nitric oxide at 10
ppm, 150 ppm, 250 ppm, and 450, and an increase at 100 ppm, with no association at 0
ppm. However, for those who had no allergies, there was an increasing trend in the
number of cells that expressed nitric oxide at all treatment levels, except at100 ppm
which exhibited a decrease.
Family History and Osteoarthritis
According to Loughlin (2011), 60% of osteoarthritis cases report family histories
of osteoarthritis in close relatives. In this study, 80% of the participants who had
osteoarthritis had a family history of osteoarthritis while only 20% did not have a family
history of osteoarthritis; confirming the observation of Loughlin (2011). For participants
who reported a positive family history of osteoarthritis, there was no observable trend in
the number of cells expressing nitric oxide at the majority of treatment levels except at
100ppm which exhibited an increase. For those who had no family history of
osteoarthritis, there was an increase at all treatment levels, except at 100 ppm which had
a decrease in the number of the cells that expressed nitric oxide. Where there was family history of osteoarthritis, the proliferation trend increased. However, there was a decrease in proliferation where there was no family history of osteoarthritis. 96
Common Pain Areas in Osteoarthritis Patients
According to Dieppe and Lohmander (2005), knee, hip, hands, and spine are the
most affected joint areas for osteoarthritis patients. This study supports those findings as
68% of participants had knee pain, 64% had hand pain, 44% had spine pain, and 60% hip
pine. Pain is increased by continuous or increased movement, movement over long
distances, and running. The pain can also be accentuated by carrying heavy loads and
excess body weight, which exerts more pressure on the weight bearing joints. The level
of pain reduces with rest, but inflammation can increase, mainly at night. Pain in the hand
is common in women with osteoarthritis. It is caused by an over-growth of bones in
finger joints causing finger joints to be painful, red, and swollen. (Dieppe & Lohmander,
2005).
The hip region is the second most commonly affected area of osteoarthritis. The
pain in the hip area is caused by high weight bearing and any extra body weight only
exacerbates this. The pain in the hip area may extend to the groin region and can make
walking difficult. Upper cervical and lower lumbar sections of the spine are the most
common sites of spinal osteoarthritis. It causes pain that runs from the neck down to the
lower back, pelvis and to the thighs (Van Weeren & de Grauw, 2010; & Dieppe &
Lohmander, 2005). This pain makes it hard to bend over or sleep in certain positions.
Participants in this study who had knee pain exhibited a trend of increasing proliferation across all treatments, while those who had hip pain exhibited a trend toward decreasing proliferation across all treatments. Participants who had pain in the hip area, had an
increasing trend in the number of cells that expressed nitric oxide at 0 ppm, 10 ppm, 150 97
ppm, 250 ppm, and 450 ppm, and a decreasing trend at 100 ppm. Additionally, for those
who predominantly experienced knee pain there was also an increasing trend in the
number of cells that expressed nitric oxide at all concentrations of cat’s claw, except at
100 ppm, which showed a decrease.
Physical Limitation and Osteoarthritis
Osteoarthritis leads to stiffness of joints and pain, reducing the range of motion in
affected joints and causing a reduction in the flexibility of the joints. A decreased range
of motion in the knees and hips inhibits free mobility of a patient, creating significant
physical limitations (Dillon, Rasch, Gu, & Hirsch, 2006). Forty-eight percent of the study
participants reported lots of pain while 52% had some pain. Participants who indicated
they had milder pain exhibited trends of increasing proliferation at all treatment levels,
while participants who had lots of pain had decreasing trends of proliferation. For
individuals who indicated that they experienced severe pain, the number of cells that
expressed nitric oxide exhibited a decreasing trend at all treatment levels of cat’s claw, except at 100 ppm where the trend reversed. For those who experienced milder pain, there was an increasing trend at all concentration levels, except at 100 ppm, which exhibited a decreasing trend in the number of cells that expressed nitric oxide.
Osteoarthritis conditions limit patients’ ability to be physically active, since
increased physical activity only worsens the severity of the pain and may cause swelling
around the joints. In this sample, 80% of participants were physically limited by the pain.
Broken cartilage, damaged vessels in the joints, and degeneration of the tissues, cause
friction on the joints during motion, since there are no shock absorbers around them. 98
Continuous friction around the joint may result in pain in patients suffering from
osteoarthritis (Dillon et al., 2006). Therefore, these individuals limit their movement as
much as possible in order to limit friction that originates from the grinding of joint bones.
Participants who reported being physically limited had a decreasing trend in proliferation
at all treatment levels whereas those who were not physically limited had an increasing trend in proliferation. Participants who were physically limited had an increasing trend in
the number of cells that expressed nitric oxide at all concentrations levels, except 0ppm
and 100ppm, which had no observable trend.
Physical Activity and Osteoarthritis Patients
Mild, low-impact aerobic exercise has been proven to be of much help to
osteoarthritis patients. The exercises increase blood circulation in the body. Repeated
physical activity and aerobics help burn excess calories, thereby preventing accumulation
of extra body weight, which increases pressure on joints leading to severe pain in patients
with osteoarthritis, particularly of the knees, hips and lower spine (Nelson et al., 2007).
Water aerobics helps to ease pain in sore joints by lowering the temperature around the
joints and increasing the circulation of blood around the joints. Physical activities help to
prevent mobility impairment that is associated with osteoarthritis, because they help keep
muscles and joints healthy and flexible (Haskell et al., 2007). There was no observable
trend between proliferation or nitric oxide expression for participants who reported being
physically active, whereas, there was a decreasing trend in proliferation and nitric oxide
expression for those who were not physically active, except at 100ppm, where there was
no observable trend. 99
The most frequent regularity (mode) of physical exercise reported by participants
was three times a week and the least frequent was two times a week. How often
participants worked out was found to be significantly associated with nitric oxide
expression at the 450 ppm treatment level (p<0.05; Bivariate fit, f = 100ppm 3.0143, 150
ppm 2.5872, 450ppm 6.4789; Table 7). For participants who reported exercising less than
2 times a week, there was a decreasing trend in the number of cells expressing nitric
oxide at all treatment levels, except 0ppm and 100ppm, which exhibited an increasing
trend. Those participants who worked out 3 times a week exhibited a decreasing trend in
the number of the cells that expressed nitric oxide at all treatment levels, except at 0ppm, which exhibited an increasing trend. There was no observable trend at 10ppm. For those individuals that indicated they worked out 5 times per week there was an increasing trend
in the number of cells that expressed nitric oxide at all treatment levels, except at 0ppm
and 150ppm which exhibited a decreasing trend and no observable trend at 450ppm. For
those who reported working out 6 times a week, there was an increasing trend in the
number of the cells that expressed nitric oxide at 0ppm and 450ppm, and a decreasing
trend at the rest of the treatment levels. Finally, for those reporting work outs 7 times per
week there was an increasing trend in the number of cells that expressed nitric oxide at all
concentration levels, except 0 ppm, which had no observable trend.
100
ANOVA Analysis of Quotient of Proliferation and Nitric Oxide Expression by Cat’s
Claw Treatment
Bivariate ANOVA (multiple regression) test was conducted on the quotient of the
stimulated and non-stimulated conditions for proliferation, nitric oxide live cell, nitric oxide dead cell, and nitric oxide total cells (live cell and dead cell) to explore the association between these lymphocyte responses and different treatments of cat’s claw.
The result showed no statistically significant association between proliferation and
different doses of cat’s claw. There was also no statistically significant association
between nitric oxide expression and different concentrations of cat’s claw.
This study accepted the null hypothesis which signifies that there was no
statistically significant difference between treatment groups for lymphocyte proliferation and nitric oxide stress. Bimolecular action of cat’s claw in this sample does not appear to
be through proliferation nor nitric oxide expression across the treatment range of 10-
450ppm. This does not further elucidate the mechanisms of cat’s claw’s action, but it
does indicate how it is likely not acting (keeping in mind this is a small sample size).
Additionally, if this finding holds true at larger sample sizes, by not affecting lymphocyte
proliferation and nitric oxide expression, it illustrates that cat’s claw does not
dramatically reduce the ability of the immune system to function in warding off disease.
It also challenges researchers to continue to explore the broad range of cytokines and
interleukins whereby cat’s claw may be having its primary impacts. Or perhaps even to
consider that it may be acting at the level of the pain receptors. 101
Conclusions and Recommendations
Osteoarthritis is a chronic disease where the joints of affected patients degenerate
leading to adult disability. It is a condition which affects the entire joint by degrading
articular cartilage. Osteoarthritis is among the most prevalent of musculoskeletal diseases
accounting for 50% of disease burden in this category (Jordan et al., 2003). Osteoarthritis
is usually a very painful joint condition affecting millions of people around the world diminishing their quality of life. According to the CDC (2017), 56.3 million adults around the world have arthritis and about 41 million in the U.S. Osteoarthritis attacks the
joint causing chronic pain, stiffness, and swelling. It often degenerates the entire articular
cartilage. Patients with osteoarthritis suffer from pain and loss of function (Miller et al,
2005). Since osteoarthritis is not curable, the only option offered by contemporary
medicine is its management.
The health care and medication options for osteoarthritis patients are continuously
being reevaluated. Complementary and alternative supplements are being used to
diversify options, which allows for improved healthcare outcomes by minimizing drug
side effects (Synovitz & Larson, 2012). Alternative supplements, particularly natural
herbs, are used to treat or improve the management of some autoimmune diseases such as
osteoarthritis. Cat’s claw is one of the alternative supplements that has been used to treat
osteoarthritis symptoms (Johnson, Sohn, Inman, Bjeldanes, & Rayburn, 2013). 102
There is mounting evidence that individuals with osteoarthrosis risk multiple side effects by long-term use of pharmaceutical medications with sometimes even more
serious outcomes than those caused by the original condition (Slipman, 2008). Further,
supplement use, and herbal medication use is a strong and growing market of self-care
(Synovitz & Larson, 2012). Research on the biomolecular action of alternative supplements for osteoarthritis has been lacking, therefore more clinical research needs to be done to facilitate understanding of the safety and mechanisms of action of these supplements.
There are very few conclusive studies elucidating the biomolecular action of cat’s claw, despite being on the market for several decades (Vitetta et al., 2008). In this study it was determined that the action of cat’s claw was not through proliferation nor nitric oxide modulation across the treatment ranges of 10-450ppm. This indicates that more work needs to be done to verify the biomolecular action of cat’s claws’ effectiveness, especially in light of studies suggesting that modulation of iNOS induction may be one of the mechanisms of action (Hardin, 2007; Sandoval et al., 2000; & Valerio & Gonzales,
2005).
Further biomedical studies need to be done on the toxicity and pharmacokinetics of cat’s claw in humans, because both of these are poorly understood, and the long-term safety of the herb is not well established (Kuhn & Winston, 2008). Likewise, cat’s claw use has not been adequately evaluated for pregnant and lactating women, and children under three years old (Piscoya et al., 2001; Vitetta, Cicuttini, & Sali, 2008). Further, very few people have taken cat’s claw in careful scientific studies because cat’s claw is not 103
certified by the Food and Drug Administration (FDA). Finally, research should be done to check whether similar compounds from different parts of the plant have the same medicinal value for the treatment of osteoarthritis (Sandoval et al., 2002). It is only by fully understanding the biomolecular actions and long-term safety implications of this herb that it will be able to be validated for use by the (FDA) for osteoarthritis patients, diversifynig their options for treatment and bring a greater degree of health and wellbeng to their lives.
104
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Wobig, M., Bach, G., Beks, P., Dickhut, A., Runzheimer, J., Schwieger, G., … Balazs, E. (1999). The role of elastoviscosity in the efficacy of viscosupplementation for osteoarthritis of the knee: a comparison of hylan GF 20 and a lower-molecular- weight hyaluronan. Clinical Therapeutics, 21(9), 1549-1562.
Wojdasiewicz, P., Poniatowski, L. A., & Szukiewicz, D. (2014). The role of inflammatory and anti-inflammatory cytokines in the pathogenesis of osteoarthritis. Mediators of Inflammatory, 2014(561459), 1-19.
Yelland, M. J., Nikles, C. J., McNairn, N., Del Mar, C. B., Schluter, P. J., & Brown, R. M. (2006). Celecoxib compared with sustained-release paracetamol for osteoarthritis: a series of n-of-1 trials. Rheumatology, 46(1), 135
Yudoh, K., Van Trieu, N., Nakamura, H., Hongo-Masuko, K., Kato, T., & Nishioka, K. (2005). Potential involvement of oxidative stress in cartilage senescence and development of osteoarthritis: Oxidative stress induces chondrocyte telomere instability and down regulation of chondrocyte function. Arthritis Research & Therapy, 7(2), R380.
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APPENDIX A
IRB LETTER
121
APPENDIX B
INVITATION FLYER
122
APPENDIX C
PARTICIPANT INFORMED CONSENT
Environmental Health Sciences Lab
CONSENT TO ACT AS A SUBJECT IN AN EXPERIMENTAL STUDY
TITLE: In-vitro study of the impact of varying concentrations of cat’s claw (Uncaria tomentosa) on osteoarthritis: a cohort study of individual response.
INVESTIGATOR: Noha Fadlalddin Doctoral Student at University of Northern Iowa / HPELS
CO-INVESTIGATOR: Dr. Catherine Zeman University of Northern Iowa / HPELS Office Phone number: 319-273-7090 Departmental phone number: 319-273-2456
INVITATION TO PARTICIPANT: I would like to request your participation in a research project to be conducted through the University of Northern Iowa, Allied Health (Environmental Health focus), Recreation, & Community Services Doctoral program. University policy requires participants’ signed consent to participate in research. The following information is provided to help you make an informed decision whether or not to participate.
NATURE AND PURPOSE: You are invited to participate as a subject in an investigation of the abilities of various compounds to alter human immune responses in vitro (test-tube based study). This project will study the effects of different concentrations of cat's claw (Uncaria tomentosa) on human immune cells for osteoarthritis disease. Will there be any changes at the level of immune cells? If there is any change observed, in what concentration? This is a purely experimental toxicology study. There are no immediate health implication for the participants. You will at no time be exposed to any cat’s claw compound. We will require a sample of your blood to study the effects of different concentrations of cat’s claw (Uncaria tomentosa) on your lymphocytes and associated cytokines involved with osteoarthritis disease. This is going to help determine if there is 123
any change at the level of pro-inflammatory cytokines and nitric oxide stress when your lymphocytes are exposed to Uncaria tomentosa.
EXPLANATION OF PROCEDURES: As a participant in the study we will collect 20-25 ml of blood (6-8 teaspoons) from the vein at the elbow into a 30 ml syringe in a session that will take approximately 10 minutes. Contact information will be maintained and you will remain eligible to be contacted by phone to donate blood, if you are willing, for up to 4 years. You must give consent for each occasion.
All blood samples will be used within 4 hours and will not be stored after that time. Samples will be identified by numbers to keep general demographic information and donor’s identities anonymous from all individuals except the investigator. Any white blood cells that are remaining after the immune assays are set up will be autoclaved and thus destroyed.
DISCOMFORT AND RISKS: There are no anticipated adverse effects, except possibly minimal discomfort associated with drawing blood or the causation of a bruise, or sometimes clot (hematoma). Additionally, there is an unlikely chance that one may get light-headed from blood drawing. Consequently if one has a history of light-headed, one has to tell phlebotomist that one has grown light-headed on previous blood draws. Finally, there is always a small risk of infection with a blood draw, although this is highly unlikely.
BENEFITS: This research will not be of any direct benefit to you but you will get to contribute to scientific knowledge and further research. You will receive a $10 University Book and Supply Gift Card for your participation following each draw. The name of any faculty receiving this gift card will have to be submitted to the Office of Business Operations for tax purposes. Faculty may refuse the gift card if they do not want their name to be submitted.
REFUSAL TO PARTICIPATE: Your participation is completely voluntary. You are free to withdraw from participation at any time or to choose not to participate at all, and that by doing so, you will not be penalized or lose benefits to which you are otherwise entitled. Refusal to donate blood will not involve a penalty or loss of course credits.
124
CONFIDENTIALITY: Any information which will identify you will be treated as confidential. While information from this study may be published in an academic journal or presented at a scholarly conference, you will not be in any way personally identified.
VOLUNTARY CONSENT: Dr. Zeman has explained all of this to you and has answered all of your questions. Any future questions you have about this research will be answered by Dr. Zeman, whom you may call at 319-273-7090 or write to at the School of HPELS, The University of Northern Iowa, Cedar Falls, IA 50614. You may also contact the office of the Human Subjects Coordinator, University of Northern Iowa, (319) 273-6148, for answers to questions about the research and about the rights of research subjects.
Please indicate your willingness to participate by completing and signing the following:
I am fully aware of the nature and extent of my participation in this project as stated above and the possible risks arising from it. I hereby agree to participate in this project. I acknowledge that I have received a copy of this consent statement. I am 18 years of age or older.
(Signature of participant) (Date)
(Printed name of participant)
(Signature of investigator) (Date)
(Signature of instructor/advisor) (Date)
125
APPENDIX D
QUESTIONNAIRE
Name: Email: Phone Number:
Study Title: In-vitro study of the impact of various concentrations of cat’s claw (Uncaria tomentosa) on osteoarthritis: a cohort study of individual response.
1. Age: 2. Gender: 3. Weight: 4. Height:
1. Are you currently taking any Herbs?
Yes No If yes, please list all herbs, dosage and frequency A. B. C. D.
126
2. Are you currently taking any vitamins? Yes No If yes, please list all vitamins, dosage and frequency. A. B. C. D.
3. Are you currently taking any prescribed Medication? Yes No If yes, please list all medication, dosage/frequency, and condition. A. B. C. D.
4. Have you taken any joint steroid injection/shot to manage your arthritis pain?
Yes
No
5. Have you received an immunization in the last 4 weeks?
Yes
No
If yes, please explain
127
6. Do you become faint during blood draws?
Yes
No
7. Do you know your Blood Type? Yes
No
If yes, then please indicate blood type______
8. Have you had a cold or flu in the past two weeks? Yes
No
9. Have you had a major life change/loss in last six months? (Death of a loved- one, new job, job loss, marriage, etc.) Yes
No
10. How long have you had osteoarthritis?
128
11. Do you have (knees, hips, hands, spine) injury? Yes
No If yes, explain
12. Are you physically limited by the pain? Yes No
13. Where do you frequently feel the pain?
Hips
Knees
Spine
Hands
Other please stat______
14. Pain severity in the past 30 days No pain Some pain Lots of pain
15. Any Diagnosed Immunological diseases other than osteoarthritis?
16. Is there any history of osteoarthritis in your family? Yes
No
If yes, state who ______129
17. Do you suffer from allergies?
Yes No If yes please describe: 18. Do you smoke? Yes No If yes, how many per day ______
19. Are you physically active? Yes No If yes, how often do you work out?
130
APPENDIX E
PROJECT CHECKLIST
Environmental Health Sciences Lab Participant ID#
Project Checklist
In-vitro study of the impact of various concentrations of cat’s claw (Uncaria tomentosa) on osteoarthritis: a cohort study of individual response.
□ Study explained
□ Verbal consent
□ Participant questions answered
□ Appointment made with Student Health Center
□ Study re-explained at Student Health Center site
□ Blood draw risks explained
□ Participant questions answered
□ Copy of written consent signed
□ Participant questionnaire completed
□ Completed blood-draw, vials labeled
□ Notified WRC lab (call 273-7090 for pick-up)
□ Transferred samples to WRC lab.
□ Subject given participation incentive 131
APPENDIX F
MAKE RPMI* MIXTURE
RPMI* mixture included RPMI 1640 medium with GlutaMAX and 100µl/1ml
Pen Strep. RPMI 1640 is a growth culture medium that has been used for cells growth
(Nakabayashi, Taketa, Miyano, Yamane & Sato, 1982).
Calculation:
• 100µl/1ml Pen Strep mean that we should add 100µl of Pen Strep in 1ml of RPMI
1640.
• 500ml of RPMI 1640 should contain 100*500µl of Pen Strep
• 50000µl of Pen Strep = 50ml of Pen Strep
• So, 500ml of RPMI 1640 should contain 50ml of Pen Strep
Method:
1. First, take 500 ml of RPMI 1640 with GlutaMAX.
2. Now add 50ml of Pen Strep in 500 ml of RPMI 1640 with GlutaMAX.
3. Mix well.
132
APPENDIX G
MAKE RPMI+ MIXTURE
From our RPMI* mixture we made RPMI+ mixture which included RPMI* and
10% of Fetal Bovine Serum (FBS). FBS is growth factor that provide nutrients for cells culture as alternative of human supplements (Bieback. et al, 2009).
Calculation:
• 10% of 40ml RPMI* mixture
• 10/100*40= 4ml of FBS
Method:
1. In a 50ml centrifuge tube, add 4ml of FBS in 36ml of RPMI*.
2. This make 10%
3. Now we have 10% FBS solution in 40 ml of RPMI* which is RPMI+ mixture
4. Mix well
133
APPENDIX H
RECONSTITUTE PHYTOHAEMAGGLUTININ (PHA)
Phytohaemagglutinin (PHA) has a rapid effect on the cell membrane that help synthesize DNA in lymphocytes while the cell culture incubated (Kay, 1968).
Calculations:
We have 5mg/ml of powdered PHA to be reconstituted.
Calculation 1
C1= 5mg or 5000µg
V1= 1ml
C2=8µg
V2=?
From Formula, V2=C1*V1/C2
V2=5000*1/8
V2= 625ml of RPMI*
So we need to add 625ml of RPMI* in PHA and reconstitute it.
Calculation 2:
We need 10% of FBS in 625ml RPMI*
10/100*625= 62.5ml of FBS 134
Add 62.5ml of FBS to make total volume of 625ml
Calculation 3:
Each cell culture plate need 5.4 ml of PHA mixture
625/5.4=115
This mixture is sufficient for 138 individuals
Method:
Reconstitute PHA in mixture of 625 ml RPMI*
Filter the mixture through 0.2-micron filter
Then add 10% of FBS
Take a sterile snap cap and fill the final mixture.
Place these snap caps in freezer and store it in -20oC
135
APPENDIX I
MAKE CAT’S CLAW SOLUTION
We obtained powdered cat’s claw extract from Sigma-Aldrich Company U.S.
Pharmacopeia certified (See Appendix K & L). To make cat’s claw solution, we prepared
450 ppm by adding 4.5g of powdered cat’s claw in 10ml of RPMI+. Cat’s claw solution was incubated in a water bath at 37°C for 30 minutes. From 450ppm we made 250,
150,100, and 10ppm.
Calculation:
Molecular weight of cat’s claw= 1g
Converting 10 ml to liter= 0.01
450/1000*1*0.01
0.45*1*0.01= 0.0045g
0.0045g*1000mg= 4.5mg
Method:
1. Weigh 4.5mg of cat’s claw and dilute in 10 ml of RPMI+
2. Placed our mixture in the water bath and incubated at 37 for 30 minutes (Sandoval-
Chacoan, Thompson, Zhang, Liu, & Mannick, 1998, & Lifeline℃ Cell Technology, 2016).
3. We removed our mixture from the water bath and run through 0.20micron syringe
filter and store in sterilized tube (Sandoval-Chacoan, Thompson, Zhang, Liu, & Mannick,
1998). 136
4. Dilute this stock solution into desired concentration such as 10, 100, 150, 250, and
450ppm.
Make 450 ppm of cat’s claw in 10ml of RPMI+:
Therefore, 4.5mg of cat’s claw in 10ml of RPMI+ makes 450 ppm of cat’s claw which is
the stock solution
Dilution Factor:
Formula, C1*V1=C2*V2
C1= concentration of stock solution
V1=volume of stock solution needed to make new solution
C2= Final concentration of new solution
V2= Final volume of new solution
From 450ppm solution make different concentrations
Make 250ppm from 450ppm solution in 2ml RPMI+:
C1= 450ppm
V1=?
C2= 250ppm
V2= 2ml
C1*V1=C2*V2
V1= 250*2/450 137
V1= 1.1ml (converting gives 1100µl). Therefore, take 1100µl from stock solution and
then add 900µl of RPMI+ to make final volume of 2000µl which is equal to 2ml.
Make 150ppm from 450ppm solution in 2ml RPMI+:
C1= 450ppm
V1=?
C2= 150ppm
V2= 2ml
C1*V1=C2*V2
V1= 150*2/450
V1= 0.66ml (converting gives 660µl). Therefore, take 660µl from stock solution and then add 1340µl of RPMI+ to make final volume of 2000µl which is equal to 2ml
Make 100ppm from 450ppm solution in 2ml RPMI+:
C1= 450ppm
V1=?
C2= 100ppm
V2= 2ml
C1*V1=C2*V2
V1= 100*2/450 138
V1= 0.44ml (converting gives 440µl). Therefore, take 440µl from stock solution and then
add 1560µl of RPMI+ to make final volume of 2000µl which is equal to 2ml
Make 10ppm from 450ppm solution in 2ml RPMI+:
C1= 450ppm
V1=?
C2= 10ppm
V2= 2ml
C1*V1=C2*V2
V1= 10*2/450
V1= 0.04ml (converting gives 40µl). Therefore, take 40µl from stock solution and then add 1960µl of RPMI+ to make final volume of 2000µl that is equal to 2ml
139
APPENDIX J
PREPARATION OF PERIPHERAL BLOOD MONONUCLEAR CELLS
1. Added 20ml of room temperature of phosphate-buffered saline (PBS) using sterile
pipet and mix well.
2. Slowly by using sterile pipet add 3ml of Ficoll-Hypaque per 10ml of blood/PBS
mixture by holding the centrifuge tube at a 45° angle and place the tip of the pipet
containing the Ficoll-Hypaque at the bottom of the sample tube. Therefore, added
12ml of Ficoll-Hypaque to the blood/PBS (3/10*40= 12ml).
3. Centrifuge 45 minutes at 1300rpm, at 20° C room temperature.
4. After centrifugation, we had different layers as shown on Figure 16 (See
Appendix M).
5. We used sterile pipet to transfer lymphocytes from centrifuge tube into a new
50ml sterile centrifuge tube.
6. Several washings occurred; to wash the cells, we added 5ml of hank’s balanced
salt solution (HBSS) to the lymphocytes and centrifuge for 10 minutes at 1300
rpm.
7. We repeated this wash step by removing supernatant, re-suspend lymphocytes by
adding 5ml of HBSS and centrifuge for 10 minutes at 1300 rpm as before.
8. Obtain the pellet from the final wash and re-suspend cells in 1ml of RPMI+
solution, and we flicked the tube with our finger gently a couple of times to assure
cell dispersion. 140
9. Refer to the MUSE Count and Viability Kit Users Guide, we used 20µl of cell
suspension volume and added 380µl of count and viability regent volume. Using
the Muse Procedure, we counted cells and determine count and viability.
10. Depending on the viable cell concentration, we diluted the cells to the cell
experimental concentration with RPMI+.
11. We added 50µl of cells to each experimental well on the culture plates under
each experimental condition (lymphocyte proliferation and nitric oxide stress).
12. Control wells of 0 only received 150µl of RPMI+ per well and 50µl of cells.
13. The next steps involve challenging all experimental wells (except control) with
the agent of concern (cat’s claw herb). This was followed by adding RPMI+ to
the non-stimulated wells and PHA to the stimulated wells of each experimental
plate condition (lymphocyte proliferation and nitric oxide stress).
14. In the non-stimulated experimental challenge wells, proceed to all wells/cells with
various cat’s claw concentrations of 10, 100, 150, 250, and 450ppm across all
three experimental plates a total of 50µl per well and added 100µl of RPMI+ to
all wells except 0.
15. In the stimulated experiential challenge wells, proceed to all wells/cells with
various cat’s claw concentrations of 10, 100, 150, 250, and 450ppm across all
three experimental plates a total of 50µl per well and added 100µl of PHA to all
wells except 0 (See Appendix N).
• Non-Stimulated: 141
. Control: 50µl cells + 150µl RPMI+
. Challenged: 50µl cells + 50µl cat’s claw + 100µl RPMI+
• Stimulated:
. Control: 50µl cells + 100µl PHA + 50µl RPMI+
. Challenged: 50µl cells + 50µl cat’s claw + 100µl PHA
Final total volume in all wells was 200µl/ml and was incubated at 37°C, 5% CO . 2
142
APPENDIX K
UNITED STATES PHARMACOPEIA (USP) CERTIFICATE
143
144
145
APPENDIX L
MATERIAL SAFETY DATA SHEET
146
147
148
149
APPENDIX M
SEPARATION OF BLOOD COMPONENTS ON A FICOLL-HYPAQUE GRADIENT
Figure 16: Isolation of whole mononuclear cells from peripheral blood and cord blood (Source: Kanof, Smith & Zola, 1996)
150
APPENDIX N
TISSUE CULTURE PLATE
151
APPENDIX O
PREPARING NITRIC OXIDE TEST
1. Nitric oxide culture plate used for Nitric Oxide Test using MUSE Unit.
2. Prepare nitric oxide reagent working solution: for 12 tests, we mixed 1.5µl of
nitric oxide reagent with 1,498.5µl of 1× assay buffer.
3. Prepare 7-AAD working solution: for 12 tests, we mixed 30µl of 7-AAD stock solution with 1,320µl of 1× assay buffer. 4. Add 100µl of nitric oxide reagent working solution to each micro-centrifuge tube. 5. Add 10µl of cell suspension in each micro-centrifuge tube and mix thoroughly. 6. Incubate samples for 30 minutes in the 37°C incubator with 5% carbon dioxide (CO2). 7. After incubation, we added 90µl of 7-AAD working solution to each tube and mix thoroughly. 8. Incubate at room temperature for 5 minutes, protected from light. 9. Use muse unit (See Appendix V). 10. Clean the lab and deal with all biological waste per established, general laboratory procedures.
152
APPENDIX P
TISSUE CULTURE PLATE OF NITRIC OXIDE TEST
153
APPENDIX Q
TISSUE CULTURE PLATE OF NITRIC OXIDE TEST UNDER THE TISSUE
CULTURE SCOPE
154
APPENDIX R
COUNTS AND VIABILITY TEST
1. We saved those pictures by participant ID number. 2. Lymphocyte proliferation culture plate used for counts and viability test using
MUSE Unit.
3. We added 380µl of count and viability reagent to each micro-centrifuge tube.
4. Add 20µl of cells suspension to each tube and mix thoroughly.
5. Incubate for 5 minutes at room temperature.
6. Use Muse Unit (See Appendix W).
7. Clean the lab and deal with all biological waste per established, general laboratory
procedures.
155
APPENDIX S
TISSUE CULTURE PLATE OF COUNTS AND VIABILITY TEST
156
APPENDIX T
TISSUE CULTURE PLATE OF COUNTS AND VIABILITY TEST UNDER THE
TISSUE CULTURE SCOPE
157
APPENDIX U
ASPETIC TECHNIQUE FOR THE LABORATORY WORK
1. Wear PPE such as Lab coat, sterile gloves, heap cap, and mask before starting
laboratory work.
2. Wipe the hood thoroughly with ethanol (70% v/v) and Kim wipes.
3. Further, sterilize the hood by UV light for about 30 minutes.
4. Wipe all equipment necessary for laboratory work with ethanol (70% v/v) such as
pipet aid, sharps container, biohazard waste can, test tube holder and so on.
5. Place all equipment inside the hood.
6. During laboratory work if any new glassware or equipment is needed then first
wipe it with ethanol before placing inside the hood.
158
APPENDIX V
USING MUSE UNIT FOR NITRIC OXIDE TEST
159
APPENDIX W
USING MUSE UNIT FOR COUNTS AND VIABILITY TEST
160
APPENDIX X
STATISTICAL ANALYSIS
X1: Distribution analysis of demographic information
Age:
Quantiles Summary Statistics
100.0% maximum 65 Mean 56.2 99.5% 65 Std Dev 6.8617296 97.5% 65 Std Err Mean 1.3723459 90.0% 65 Upper 95% Mean 59.032383 75.0% quartile 62 Lower 95% Mean 53.367617 50.0% median 57 N 25 25.0% quartile 51.5 10.0% 48.2 2.5% 37 0.5% 37 0.0% minimum 37
161
Gender:
Frequencies Level Count Probability Female 21 0.84000 Male 4 0.16000 Total 25 1.00000
162
BMI:
Quantiles 100.0% maximum 49.6 99.5% 49.6 97.5% 49.6 90.0% 43.356 75.0% quartile 33.795 50.0% median 30.54 25.0% quartile 26.47 10.0% 21.714 2.5% 21.63 0.5% 21.63 0.0% minimum 21.63
Summary Statistics Mean 31.5652 Std Dev 7.2626052 Std Err Mean 1.452521 Upper 95% Mean 34.563056 Lower 95% Mean 28.567344 N 25
163
X2: Distribution analysis of medication information
Are you currently taking any Herbs?
Frequencies Level Count Probability No 20 0.83333 Yes 4 0.16667 Total 24 1.000
If yes, please list all herbs Frequencies Level Count Probability Apple cider vinegar 1 0.14286 Cinnamon 1 0.14286 Cumin 1 0.14286 Gluten Cutter 1 0.14286 Gngko biloba 1 0.14286 Turmeric 2 0.28571 Total 7 1.00000
164
Are you currently taking any vitamins?
Frequencies Level Count Probability No 6 0.24000 Yes 19 0.76000 Total 25 1.00000
If yes, please list all vitamins Frequencies Level Count Prob B-Complex 1 0.02381 Biotin 2 0.04762 Calcium 6 0.14286 Chlorophyll 1 0.02381 Eye Health Vitamin 1 0.02381 Hair and Nail Vitamin 1 0.02381 Iron 2 0.04762 Multivitamin 9 0.21429 Neurobion 1 0.02381 Omega XL 1 0.02381 Omega-3 4 0.09524 Vitamin B12 2 0.04762 Vitamin c 1 0.02381 Vitamin D 8 0.19048 Vitamin D-3 2 0.04762 Total 42 1.00000 165
Are you currently taking any prescribed medication
Frequencies Level Count Probability No 3 0.12000 Yes 22 0.88000 Total 25 1.00000
166
If yes, please list all medications
167
List of Medications
Level Count Probability Acid Reflex 1 0.01351 Albiterol 1 0.01351 Allegra 1 0.01351 Amlodipine Besylate 1 0.01351 Aspirin 3 0.04054 Atenolo 1 0.01351 Atltace 1 0.01351 Atorvastatin 2 0.02703 Benicar 1 0.01351 Blood pressure medication 1 0.01351 Bone Maximizer 1 0.01351 Cholesterol 2 0.02703 Clarinex D 1 0.01351 Clonidine HCL 1 0.01351 Crestor 2 0.02703 Cymbalta 1 0.01351 Depakote 1 0.01351 Dexilant 1 0.01351 Ditropan 1 0.01351 Eligard 1 0.01351 Esther 1 0.01351 Estradiol 1 0.01351 Evista 1 0.01351 Exemestane 1 0.01351 FiberCon 1 0.01351 Finasteride 1 0.01351 Fluoxetine 1 0.01351 Fluoxitine 1 0.01351 Fluticason Propionate 1 0.01351 Furrosemide 1 0.01351 Gabapentin 1 0.01351 Generic Cymbalta 1 0.01351 Generic Plaguenil 1 0.01351 HCTZ 2 0.02703 Hydrochlorothiazide 1 0.01351 Ibuprofen 1 0.01351 Imitrix 1 0.01351 Inhaler 1 0.01351 Isosorbide 1 0.01351 168
Level Count Probability Levothyroxine 2 0.02703 Liothyronnie 1 0.01351 Lipitor 1 0.01351 Lisinopril 1 0.01351 Losartan 1 0.01351 Meloxicam 1 0.01351 Mevacor 1 0.01351 Mitrophal 1 0.01351 Mobic 1 0.01351 Morphine 1 0.01351 Ocuvite 1 0.01351 Omeprazole 1 0.01351 Pazeo 1 0.01351 ProAie HFA Albuterol Sulfate 1 0.01351 Reclast 1 0.01351 Simthyroid 1 0.01351 Simvastatin 1 0.01351 Singulair 2 0.02703 Synthroid 2 0.02703 Tamsuloosin 1 0.01351 Tizidine 1 0.01351 Trazadone 1 0.01351 Venlafaxine 1 0.01351 Xanex 1 0.01351 Xyzal 1 0.01351 Zyrtec 1 0.01351 Total 74 1.00000
169
Have you taken any joint steroid injection/shot to manage your arthritis pain?
Frequencies Level Count Probability No 11 0.44000 Yes 14 0.56000 Total 25 1.00000
Have you received an immunization in the last 4 weeks?
Frequencies Level Count Probability No 20 0.80000 Yes 5 0.20000 Total 25 1.00000
170
X3: Distribution analysis of health information
Do you know your Blood Type?
Frequencies Level Count Probability No 7 0.28000 Yes 18 0.72000 Total 25 1.00000
Blood Type
Frequencies Level Count Probability A Negative 1 0.05556 A Positive 6 0.33333 AB Positive 1 0.05556 B Positive 2 0.11111 O Negative 4 0.22222 O Positive 4 0.22222 Total 18 1.00000 171
Have you had a cold or flu in the past two weeks?
Frequencies Level Count Probability No 25 1.00000 Total 25 1.00000
Have you had a major life change/loss in last six months? (Death of a loved-one, new job, job loss, marriage, etc.)
Frequencies Level Count Probability No 19 0.76000 Yes 6 0.24000 Total 25 1.00000
172
How long have you had osteoarthritis?
Quantiles 100.0% maximum 30 99.5% 30 97.5% 30 90.0% 23.8 75.0% quartile 15 50.0% median 10 25.0% quartile 6.5 10.0% 4 2.5% 3 0.5% 3 0.0% minimum 3
Summary Statistics Mean 11.48 Std Dev 7.0717749 Std Err Mean 1.414355 Upper 95% Mean 14.399085 Lower 95% Mean 8.5609148 N 25 173
Do you have (knees, hips, hands, spine) injury?
Frequencies Level Count Probability No 10 0.40000 Yes 15 0.60000 Total 25 1.00000
If yes, explain
174
Frequencies Level Count Probability Left collar bone-double fracture 1 0.03846 Anterior discectomy w/fusion (cadaver bone) 1 0.03846 Carpal tunnel surgery 2 0.07692 Dislocated right subtalar-surgery 1 0.03846 Hands 1 0.03846 Hip Injury 2 0.07692 Hip replacement 1 0.03846 Het by car from back 1 0.03846 Injury L12-L16 L2 1 0.03846 Injury L3, L4, L5, S1 1 0.03846 Knees Injury 8 0.30769 Missing backbone 1 0.03846 Right shoulder injury 1 0.03846 Rotator cuff 1 0.03846 Spine injury 2 0.07692 Thump joint replacement 1 0.03846 Total 26 1.00000
Are you physically limited by the pain?
Frequencies Level Count Probability No 11 0.44000 Yes 14 0.56000 Total 25 1.00000 175
Where do you frequently feel the pain? Hips, knees, spine, hands, other please state
Frequencies Level Count Probability Ankles 1 0.01449 Everywhere 1 0.01449 Hands 16 0.23188 Hip 15 0.21739 Knees 17 0.24638 Lower back 5 0.07246 Nick 1 0.01449 Shoulder 2 0.02899 Spine 11 0.15942 Total 69 1.00000
176
Pain severity in the past 30 days: No pain - some pain - lots of pain
Frequencies Level Count Probability Lots of pain 12 0.48000 Some pain 13 0.52000 Total 25 1.00000
Any Diagnosed Immunological diseases other than osteoarthritis?
Frequencies Level Count Probability No 25 1.00000 Total 25 1.00000
177
Is there any history of osteoarthritis in your family?
Frequencies Level Count Probability No 5 0.20000 Yes 20 0.80000 Total 25 1.00000
If yes, state who Frequencies Level Count Probability Brother 3 0.10714 Father 6 0.21429 Grandfather 1 0.03571 Grandmother 3 0.10714 Mother 12 0.42857 Sister 3 0.10714 Total 28 1.00000
178
Do you suffer from allergies?
Frequencies Level Count Probability No 8 0.32000 Yes 17 0.68000 Total 25 1.00000
If yes please describe Frequencies Level Count Probability Antibiotics 1 0.04762 Cats 2 0.09524 Dust 1 0.04762 Environmental 5 0.23810 Food 1 0.04762 Hay fever 4 0.19048 Lanolin 1 0.04762 Medication 2 0.09524 Penicillin 1 0.04762 Perch 1 0.04762 Smoking 1 0.04762 Sulfa 1 0.04762 Total 21 1.00000
179
Do you smoke?
Frequencies Level Count Probability No 25 1.00000 Total 25 1.00000
180
Are you physically active?
Frequencies Level Count Probability No 5 0.20000 Yes 20 0.80000 Total 25 1.00000
If yes, how often do you work out?
Frequencies Level Count Probability 2X /week 2 0.09524 3X /week 10 0.47619 5X /week 4 0.19048 6X /week 1 0.04762 7X /week 4 0.19048 Total 21 1.00000 181
APPENDIX Y
PROLIFIRATION STATISTICAL RESULTS
Bivariate Fit of Proliferation at 0 ppm
Age:
Summary RSquare 0.065202 RSquare Adj 0.024559 Root Mean Square Error 886.9519 Mean of Response 289.2443 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Model 1 1262040 1262040 1.6043 Error 23 18093724 786684 Prob > F C. Total 24 19355764 0.2180
Parameter Estimates Term Estimate Std Error t Ratio Prob>|t| Intercept 2167.409 1493.423 1.45 0.1602 Age -33.4193 26.38523 -1.27 0.2180
182
Number of medication:
Summary RSquare 0.017101 RSquare Adj -0.04433 Root Mean Square Error 0.12638 Mean of Response 0.942722 Observations (or Sum Wgts) 18
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Model 1 0.00444631 0.004446 0.2784 Error 16 0.25555130 0.015972 Prob > F C. Total 17 0.25999761 0.4050
Parameter Estimates Term Estimate Std Error t Ratio Prob>|t| Intercept 0.969164 0.0583 16.62 <.0001* Number of -0.006704 0.012705 -0.53 0.4050 Medication 183
Joint steroid:
Summary Rsquare 0.052295 Adj Rsquare 0.01109 Root Mean Square Error 893.0543 Mean of Response 289.2443 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F Joint Steroid 1 1012206 1012206 1.2692 0.2715 Error 23 18343558 797546 C. Total 24 19355764
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% No 11 516.248 269.27 -40.8 1073.3 Yes 14 110.885 238.68 -382.9 604.6
184
Length of osteoarthritis:
Summary RSquare 0.075055 RSquare Adj 0.028808 Root Mean Square Error 323.3649 Mean of Response 70.91077 Observations (or Sum Wgts) 22
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Model 1 169699.2 169699 1.6229 Error 20 2091296.8 104565 Prob > F C. Total 21 2260996.0 0.2173
Parameter Estimates Term Estimate Std Error t Ratio Prob>|t| Intercept 217.96648 134.4545 1.62 0.1207 Length of -12.25464 9.619525 -1.27 0.2173 Osteoarthritis 185
Physically limited:
Summary Rsquare 0.049396 Adj Rsquare 0.008065 Root Mean Square Error 894.4191 Mean of Response 289.2443 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F Phisically Limited 1 956098 956098 1.1951 0.2856 Error 23 18399666 799985 C. Total 24 19355764
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% No 11 509.866 269.68 -48.0 1067.7 Yes 14 115.898 239.04 -378.6 610.4
186
Pain severity:
Summary Rsquare 0.03052 Adj Rsquare -0.01163 Root Mean Square Error 903.2555 Mean of Response 289.2443 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F Pain Severity 1 590744 590744 0.7241 0.4036 Error 23 18765021 815870 C. Total 24 19355764
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% Lots of pain 12 129.248 260.75 -410.1 668.64 Some pain 13 436.933 250.52 -81.3 955.17
187
Pain area:
Summary Rsquare 0.066777 Adj Rsquare 0.026202 Root Mean Square Error 886.2044 Mean of Response 289.2443 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F Pain area 1 1292526 1292526 1.6458 0.2123 Error 23 18063238 785358 C. Total 24 19355764
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% Hip 15 103.590 228.82 -369.8 576.9 Knees 10 567.725 280.24 -12.0 1147.5
188
Family history:
Summary Rsquare 0.026827 Adj Rsquare -0.01548 Root Mean Square Error 904.9742 Mean of Response 289.2443 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F Family History 1 519262 519262 0.6340 0.4340 Error 23 18836502 818978 C. Total 24 19355764
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% No 5 1.005 404.72 -836.2 838.23 Yes 20 361.304 202.36 -57.3 779.91
189
Allergies:
Summary Rsquare 0.050517 Adj Rsquare 0.009235 Root Mean Square Error 893.8914 Mean of Response 289.2443 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F Allergies 1 977800 977800 1.2237 0.2801 Error 23 18377964 799042 C. Total 24 19355764
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% No 8 0.951 316.04 -652.8 654.73 Yes 17 424.912 216.80 -23.6 873.40
190
Physically active (workout):
Summary Rsquare 0.02683 Adj Rsquare -0.01548 Root Mean Square Error 904.973 Mean of Response 289.2443 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F Physically 1 519315 519315 0.6341 0.4340 Active(Work out) Error 23 18836449 818976 C. Total 24 19355764
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% No 5 0.990 404.72 -836.2 838.21 Yes 20 361.308 202.36 -57.3 779.92
191
Bivariate Fit of Proliferation at 10 ppm
Age:
Summary RSquare 0.064319 RSquare Adj 0.023637 Root Mean Square Error 811.8501 Mean of Response 254.4681 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Model 1 1042058 1042058 1.5810 Error 23 15159314 659101 Prob > F C. Total 24 16201372 0.2212
Parameter Estimates Term Estimate Std Error t Ratio Prob>|t| Intercept 1961.1122 1366.968 1.43 0.1648 Age -30.36733 24.15108 -1.26 0.2212
192
Number of medication:
Summary RSquare 0.040618 RSquare Adj -0.01934 Root Mean Square Error 0.178958 Mean of Response 0.977889 Observations (or Sum Wgts) 18
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Model 1 0.02169450 0.021695 0.6774 Error 16 0.51241327 0.032026 Prob > F C. Total 17 0.53410778 0.4226
Parameter Estimates Term Estimate Std Error t Ratio Prob>|t| Intercept 1.0362959 0.082554 12.55 <.0001* Number of -0.014807 0.017991 -0.82 0.4226 Medication
193
Joint steroid:
Summary Rsquare 0.051604 Adj Rsquare 0.01037 Root Mean Square Error 817.3475 Mean of Response 254.4681 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F Joint Steroid 1 836062 836062 1.2515 0.2748 Error 23 15365310 668057 C. Total 24 16201372
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% No 11 460.776 246.44 -49.0 970.58 Yes 14 92.369 218.45 -359.5 544.26
194
Length of osteoarthritis:
Summary RSquare 0.074986 RSquare Adj 0.028736 Root Mean Square Error 268.7397 Mean of Response 59.12555 Observations (or Sum Wgts) 22
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Model 1 117092.3 117092 1.6213 Error 20 1444420.5 72221 Prob > F C. Total 21 1561512.8 0.2175
Parameter Estimates Term Estimate Std Error t Ratio Prob>|t| Intercept 181.27913 111.7415 1.62 0.1204 Length of -10.17947 7.994524 -1.27 0.2175 Osteoarthritis
195
Physically limited:
Summary Rsquare 0.053892 Adj Rsquare 0.012757 Root Mean Square Error 816.3611 Mean of Response 254.4681 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F Phisically Limited 1 873126 873126 1.3101 0.2641 Error 23 15328246 666445 C. Total 24 16201372
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% No 11 465.300 246.14 -43.9 974.48 Yes 14 88.815 218.18 -362.5 540.16
196
Pain severity:
Summary of Fit Rsquare 0.030739 Adj Rsquare -0.0114 Root Mean Square Error 826.2898 Mean of Response 254.4681 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F Pain Severity 1 498010 498010 0.7294 0.4019 Error 23 15703362 682755 C. Total 24 16201372
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% Lots of pain 12 107.565 238.53 -385.9 601.00 Some pain 13 390.071 229.17 -84.0 864.15
197
Pain area:
Summary Rsquare 0.0655 Adj Rsquare 0.024869 Root Mean Square Error 811.3377 Mean of Response 254.4681 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain area 1 1061187 1061187 1.6121 0.2169 Error 23 15140184 658269 C. Total 24 16201372
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Hip 15 86.247 209.49 -347.1 519.6 Knees 10 506.800 256.57 -24.0 1037.6
198
Family history:
Summary Rsquare 0.024791 Adj Rsquare -0.01761 Root Mean Square Error 828.8212 Mean of Response 254.4681 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Family History 1 401646 401646 0.5847 0.4523 Error 23 15799726 686945 C. Total 24 16201372
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 0.966 370.66 -765.8 767.73 Yes 20 317.844 185.33 -65.5 701.23
199
Allergies:
Summary Rsquare 0.046682 Adj Rsquare 0.005233 Root Mean Square Error 819.466 Mean of Response 254.4681 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Allergies 1 756307 756307 1.1263 0.2996 Error 23 15445065 671525 C. Total 24 16201372
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 8 0.921 289.72 -598.4 600.26 Yes 17 373.784 198.75 -37.4 784.93
200
Physically active (Workout):
Summary Rsquare 0.024785 Adj Rsquare -0.01762 Root Mean Square Error 828.8239 Mean of Response 254.4681 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Physically 1 401544 401544 0.5845 0.4523 Active(Work out) Error 23 15799828 686949 C. Total 24 16201372
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 0.998 370.66 -765.8 767.77 Yes 20 317.836 185.33 -65.6 701.22
201
Bivariate Fit of Proliferation at 100 ppm
Age:
Summary RSquare 0.063146 RSquare Adj 0.022413 Root Mean Square Error 829.899 Mean of Response 249.7101 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 1067703 1067703 1.5502 Error 23 15840843 688732 Prob > F C. Total 24 16908546 0.2256
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 1977.2271 1397.359 1.41 0.1705 Age -30.73874 24.68801 -1.25 0.2256
202
Number of medication:
Summary RSquare 0.186443 RSquare Adj 0.135596 Root Mean Square Error 0.118509 Mean of Response 1.050278 Observations (or Sum Wgts) 18
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.05149660 0.051497 3.6667 Error 16 0.22470901 0.014044 Prob > F C. Total 17 0.27620561 0.0736
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 0.9602908 0.054669 17.57 <.0001* Number of 0.0228136 0.011914 1.91 0.0736 Medication 203
Joint steroid:
Summary Rsquare 0.052214 Adj Rsquare 0.011005 Root Mean Square Error 834.727 Mean of Response 249.7101 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Joint Steroid 1 882855 882855 1.2671 0.2719 Error 23 16025691 696769 C. Total 24 16908546
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 461.713 251.68 -58.9 982.35 Yes 14 83.136 223.09 -378.4 544.63
204
Length of osteoarthritis:
Summary RSquare 0.075122 RSquare Adj 0.028878 Root Mean Square Error 241.3969 Mean of Response 53.26259 Observations (or Sum Wgts) 22
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 94662.2 94662.2 1.6245 Error 20 1165448.8 58272.4 Prob > F C. Total 21 1260111.0 0.2171
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 163.09496 100.3724 1.62 0.1198 Length of -9.152697 7.181123 -1.27 0.2171 Osteoarthritis 205
Physically limited:
Summary Rsquare 0.055895 Adj Rsquare 0.014846 Root Mean Square Error 833.1045 Mean of Response 249.7101 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Phisically 1 945095 945095 1.3617 0.2552 Limited Error 23 15963450 694063 C. Total 24 16908546
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 469.059 251.19 -50.6 988.69 Yes 14 77.365 222.66 -383.2 537.96
206
Pain severity:
Summary Rsquare 0.031921 Adj Rsquare -0.01017 Root Mean Square Error 843.6157 Mean of Response 249.7101 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain Severity 1 539734 539734 0.7584 0.3928 Error 23 16368812 711687 C. Total 24 16908546
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Lots of pain 12 96.777 243.53 -407.0 600.56 Some pain 13 390.879 233.98 -93.1 874.90
207
Pain area:
Summary Rsquare 0.065672 Adj Rsquare 0.025049 Root Mean Square Error 828.7792 Mean of Response 249.7101 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain area 1 1110420 1110420 1.6166 0.2163 Error 23 15798125 686875 C. Total 24 16908546
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Hip 15 77.631 213.99 -365.0 520.3 Knees 10 507.829 262.08 -34.3 1050.0
208
Family history:
Summary Rsquare 0.022856 Adj Rsquare -0.01963 Root Mean Square Error 847.556 Mean of Response 249.7101 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Family History 1 386468 386468 0.5380 0.4707 Error 23 16522078 718351 C. Total 24 16908546
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 1.044 379.04 -783.1 785.15 Yes 20 311.877 189.52 -80.2 703.93
209
Allergies:
Summary Rsquare 0.043039 Adj Rsquare 0.001432 Root Mean Square Error 838.7573 Mean of Response 249.7101 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Allergies 1 727727 727727 1.0344 0.3197 Error 23 16180818 703514 C. Total 24 16908546
Means Anova Level Number Mean Std Lower Upper 95% Error 95% No 8 1.000 296.55 -612.5 614.45 Yes 17 366.750 203.43 -54.1 787.57
210
Physically active (Workout):
Summary Rsquare 0.022867 Adj Rsquare -0.01962 Root Mean Square Error 847.5513 Mean of Response 249.7101 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Physically 1 386652 386652 0.5383 0.4706 Active(Work out) Error 23 16521894 718343 C. Total 24 16908546
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 0.985 379.04 -783.1 785.08 Yes 20 311.891 189.52 -80.2 703.94
211
Bivariate Fit of Proliferation at 150 ppm
Age:
Summary RSquare 0.062473 RSquare Adj 0.021711 Root Mean Square Error 653.8796 Mean of Response 207.9914 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 655287 655287 1.5326 Error 23 9833845 427558 Prob > F C. Total 24 10489133 0.2282
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 1561.3505 1100.982 1.42 0.1696 Age -24.08112 19.45174 -1.24 0.2282
212
Number of medication:
Summary RSquare 0.323945 RSquare Adj 0.281692 Root Mean Square Error 0.281042 Mean of Response 1.090556 Observations (or Sum Wgts) 18
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.6055540 0.605554 7.6667 Error 16 1.2637545 0.078985 Prob > F C. Total 17 1.8693084 0.0137*
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 0.7819764 0.129646 6.03 <.0001* Number of 0.0782313 0.028254 2.77 0.0137* Medication 213
Joint steroid:
Summary Rsquare 0.036103 Adj Rsquare -0.00581 Root Mean Square Error 663.0118 Mean of Response 207.9914 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Joint 1 378687 378687 0.8615 0.3630 Steroid Error 23 10110445 439585 C. Total 24 10489133
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 346.839 199.91 -66.7 760.38 Yes 14 98.897 177.20 -267.7 465.46
214
Length of osteoarthritis:
Summary RSquare 0.075192 RSquare Adj 0.028952 Root Mean Square Error 287.5975 Mean of Response 63.3105 Observations (or Sum Wgts) 22
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 134499.8 134500 1.6261 Error 20 1654246.1 82712 Prob > F C. Total 21 1788745.9 0.2169
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 194.22953 119.5825 1.62 0.1200 Length of -10.90992 8.555509 -1.28 0.2169 Osteoarthritis
215
Physically limited:
Summary Rsquare 0.068422 Adj Rsquare 0.027918 Root Mean Square Error 651.8018 Mean of Response 207.9914 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Phisically 1 717684 717684 1.6893 0.2066 Limited Error 23 9771449 424846 C. Total 24 10489133
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 399.137 196.53 -7.4 805.68 Yes 14 57.806 174.20 -302.6 418.17
216
Pain area:
Summary Rsquare 0.047804 Adj Rsquare 0.006404 Root Mean Square Error 658.9751 Mean of Response 207.9914 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain area 1 501423 501423 1.1547 0.2937 Error 23 9987709 434248 C. Total 24 10489133
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Hip 15 92.357 170.15 -259.6 444.33 Knees 10 381.443 208.39 -49.6 812.52
217
Pain severity:
Summary Rsquare 0.018948 Adj Rsquare -0.02371 Root Mean Square Error 668.8857 Mean of Response 207.9914 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain 1 198746 198746 0.4442 0.5117 Severity Error 23 10290386 447408 C. Total 24 10489133
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Lots of 12 115.189 193.09 -284.2 514.63 pain Some pain 13 293.655 185.52 -90.1 677.42
218
Family history:
Summary Rsquare 0.025528 Adj Rsquare -0.01684 Root Mean Square Error 666.6389 Mean of Response 207.9914 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Family 1 267763 267763 0.6025 0.4455 History Error 23 10221369 444407 C. Total 24 10489133
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 1.008 298.13 -615.7 617.74 Yes 20 259.737 149.06 -48.6 568.10
219
Allergies:
Summary Rsquare 0.04806 Adj Rsquare 0.006671 Root Mean Square Error 658.8867 Mean of Response 207.9914 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Allergies 1 504104 504104 1.1612 0.2924 Error 23 9985029 434132 C. Total 24 10489133
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 8 0.992 232.95 -480.9 482.89 Yes 17 305.403 159.80 -25.2 635.98
220
Physically active (Workout):
Summary Rsquare 0.025535 Adj Rsquare -0.01683 Root Mean Square Error 666.6364 Mean of Response 207.9914 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Physically 1 267838 267838 0.6027 0.4455 Active (Work out) Error 23 10221294 444404 C. Total 24 10489133
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 0.979 298.13 -615.7 617.71 Yes 20 259.745 149.06 -48.6 568.11
221
Bivariate Fit of Proliferation at 250 ppm
Age:
Summary RSquare 0.058619 RSquare Adj 0.01769 Root Mean Square Error 1165.156 Mean of Response 310.9853 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 1944334 1944334 1.4322 Error 23 31224517 1357588 Prob > F C. Total 24 33168851 0.2436
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 2642.2012 1961.854 1.35 0.1912 Age -41.48071 34.66129 -1.20 0.2436 222
Number of medication:
Summary RSquare 0.068563 RSquare Adj 0.010348 Root Mean Square Error 0.124018 Mean of Response 1.038778 Observations (or Sum Wgts) 18
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.01811447 0.018114 1.1778 Error 16 0.24608664 0.015380 Prob > F C. Total 17 0.26420111 0.2939
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 0.9854071 0.05721 17.22 <.0001* Number of 0.0135306 0.012468 1.09 0.2939 Medication
223
Joint steroid:
Summary Rsquare 0.050761 Adj Rsquare 0.00949 Root Mean Square Error 1170.008 Mean of Response 310.9853 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Joint 1 1683697 1683697 1.2299 0.2789 Steroid Error 23 31485154 1368920 C. Total 24 33168851
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 603.757 352.77 -126.0 1333.5 Yes 14 80.950 312.70 -565.9 727.8
224
Length of osteoarthritis:
Summary RSquare 0.075199 RSquare Adj 0.028959 Root Mean Square Error 235.086 Mean of Response 51.89014 Observations (or Sum Wgts) 22
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 89877.4 89877.4 1.6263 Error 20 1105308.2 55265.4 Prob > F C. Total 21 1195185.6 0.2168
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 158.91068 97.74833 1.63 0.1197 Length of -8.918379 6.993386 -1.28 0.2168 Osteoarthritis
225
Physically limited:
Summary Rsquare 0.060251 Adj Rsquare 0.019392 Root Mean Square Error 1164.145 Mean of Response 310.9853 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Phisically Limited 1 1998460 1998460 1.4746 0.2369 Error 23 31170390 1355234 C. Total 24 33168851
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 629.952 351.00 -96.2 1356.1 Yes 14 60.369 311.13 -583.3 704.0
226
Pain severity:
Summary Rsquare 0.032675 Adj Rsquare -0.00938 Root Mean Square Error 1181.102 Mean of Response 310.9853 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain Severity 1 1083788 1083788 0.7769 0.3872 Error 23 32085063 1395003 C. Total 24 33168851
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Lots of pain 12 94.273 340.95 -611.0 799.6 Some pain 13 511.027 327.58 -166.6 1188.7
227
Pain area:
Summary Rsquare 0.062629 Adj Rsquare 0.021873 Root Mean Square Error 1162.672 Mean of Response 310.9853 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain area 1 2077318 2077318 1.5367 0.2276 Error 23 31091533 1351806 C. Total 24 33168851
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Hip 15 75.624 300.20 -545.4 696.6 Knees 10 664.028 367.67 -96.6 1424.6
228
Family history:
Summary Rsquare 0.018105 Adj Rsquare -0.02459 Root Mean Square Error 1189.964 Mean of Response 310.9853 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Family History 1 600529 600529 0.4241 0.5214 Error 23 32568321 1416014 C. Total 24 33168851
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 1.010 532.17 -1100 1101.9 Yes 20 388.479 266.08 -162 938.9
229
Allergies:
Summary Rsquare 0.034074 Adj Rsquare -0.00792 Root Mean Square Error 1180.248 Mean of Response 310.9853 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Allergies 1 1130204 1130204 0.8114 0.3771 Error 23 32038647 1392985 C. Total 24 33168851
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 8 1.038 417.28 -862.2 864.2 Yes 17 456.843 286.25 -135.3 1049.0
230
Physically active (Workout):
Summary Rsquare 0.018103 Adj Rsquare -0.02459 Root Mean Square Error 1189.965 Mean of Response 310.9853 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Physically 1 600453 600453 0.4240 0.5214 Active(Work out) Error 23 32568397 1416017 C. Total 24 33168851
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 1.030 532.17 -1100 1101.9 Yes 20 388.474 266.08 -162 938.9
231
Bivariate Fit of Proliferation at 450 ppm
Age:
Summary RSquare 0.063601 RSquare Adj 0.022888 Root Mean Square Error 778.1972 Mean of Response 239.3317 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 946044 946044 1.5622 Error 23 13928589 605591 Prob > F C. Total 24 14874633 0.2239
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 1865.4526 1310.305 1.42 0.1680 Age -28.93454 23.14997 -1.25 0.2239
232
Number of medication:
Summary RSquare 0.011262 RSquare Adj -0.05053 Root Mean Square Error 0.17379 Mean of Response 1.061 Observations (or Sum Wgts) 18
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.00550454 0.005505 0.1823 Error 16 0.48324946 0.030203 Prob > F C. Total 17 0.48875400 0.6751
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 1.0315794 0.08017 12.87 <.0001* Number of 0.0074587 0.017471 0.43 0.6751 Medication 233
Joint steroid:
Summary Rsquare 0.049854 Adj Rsquare 0.008544 Root Mean Square Error 783.8886 Mean of Response 239.3317 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Joint Steroid 1 741563 741563 1.2068 0.2833 Error 23 14133070 614481 C. Total 24 14874633
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 433.631 236.35 -55.3 922.56 Yes 14 86.668 209.50 -346.7 520.06
234
Length of osteoarthritis:
Summary RSquare 0.075176 RSquare Adj 0.028935 Root Mean Square Error 251.8907 Mean of Response 55.55286 Observations (or Sum Wgts) 22
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 103150.9 103151 1.6257 Error 20 1268978.4 63449 Prob > F C. Total 21 1372129.2 0.2169
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 170.20403 104.7357 1.63 0.1198 Length of -9.554264 7.493296 -1.28 0.2169 Osteoarthritis
235
Physically limited:
Summary Rsquare 0.057093 Adj Rsquare 0.016097 Root Mean Square Error 780.8967 Mean of Response 239.3317 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Phisically Limited 1 849240 849240 1.3927 0.2500 Error 23 14025394 609800 C. Total 24 14874633
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 447.260 235.45 -39.8 934.32 Yes 14 75.960 208.70 -355.8 507.70
236
Pain severity:
Summary Rsquare 0.029714 Adj Rsquare -0.01247 Root Mean Square Error 792.153 Mean of Response 239.3317 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain Severity 1 441988 441988 0.7044 0.4100 Error 23 14432646 627506 C. Total 24 14874633
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Lots of pain 12 100.938 228.67 -372.1 573.99 Some pain 13 367.080 219.70 -87.4 821.57
237
Pain area:
Summary Rsquare 0.063247 Adj Rsquare 0.022519 Root Mean Square Error 778.3443 Mean of Response 239.3317 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain area 1 940775 940775 1.5529 0.2253 Error 23 13933858 605820 C. Total 24 14874633
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Hip 15 80.942 200.97 -334.8 496.68 Knees 10 476.917 246.13 -32.3 986.08
238
Family history:
Summary Rsquare 0.023856 Adj Rsquare -0.01859 Root Mean Square Error 794.5409 Mean of Response 239.3317 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Family History 1 354845 354845 0.5621 0.4610 Error 23 14519789 631295 C. Total 24 14874633
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 1.056 355.33 -734.0 736.11 Yes 20 298.901 177.66 -68.6 666.43
239
Allergies:
Summary Rsquare 0.044887 Adj Rsquare 0.003361 Root Mean Square Error 785.9349 Mean of Response 239.3317 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Allergies 1 667680 667680 1.0809 0.3093 Error 23 14206953 617694 C. Total 24 14874633
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 8 1.103 277.87 -573.7 575.92 Yes 17 351.439 190.62 -42.9 745.76
240
Physically active (Workout):
Summary Rsquare 0.023865 Adj Rsquare -0.01858 Root Mean Square Error 794.537 Mean of Response 239.3317 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Physically 1 354987 354987 0.5623 0.4609 Active(Work out) Error 23 14519646 631289 C. Total 24 14874633
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 1.009 355.33 -734.0 736.06 Yes 20 298.913 177.66 -68.6 666.44
241
APPENDIX Z
NITRIC OXIDE STATISTICAL RESULTS
Bivariate Fit of Nitric Oxide at 0 ppm
Age:
Summary RSquare 0.004371 RSquare Adj -0.03892 Root Mean Square Error 3.222058 Mean of Response 1.501744 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 1.04818 1.0482 0.1010 Error 23 238.77807 10.3817 Prob > F C. Total 24 239.82625 0.7535
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept -0.209908 5.425202 -0.04 0.9695 Age 0.0304564 0.09585 0.32 0.7535 242
Length of osteoarthritis:
Summary RSquare 0.281584 RSquare Adj 0.245663 Root Mean Square Error 1.758112 Mean of Response 1.064695 Observations (or Sum Wgts) 22
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 24.230050 24.2301 7.8390 Error 20 61.819190 3.0910 Prob > F C. Total 21 86.049240 0.0111*
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept -0.692496 0.73102 -0.95 0.3548 Length of 0.1464327 0.052301 2.80 0.0111* Osteoarthritis 243
Herbs:
Summary Rsquare 0.038508 Adj Rsquare -0.0052 Root Mean Square Error 3.225911 Mean of Response 1.555192 Observations (or Sum Wgts) 24
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Herbs 1 9.16918 9.1692 0.8811 0.3581 Error 22 228.94308 10.4065 C. Total 23 238.11226
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 20 1.83162 0.7213 0.336 3.3276 Yes 4 0.17308 1.6130 -3.172 3.5181 244
Vitamins:
Summary Rsquare 0.055492 Adj Rsquare 0.014427 Root Mean Square Error 3.138248 Mean of Response 1.501744 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Vitamins 1 13.30848 13.3085 1.3513 0.2570 Error 23 226.51778 9.8486 C. Total 24 239.82625
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 6 0.20338 1.2812 -2.447 2.8537 Yes 19 1.91175 0.7200 0.422 3.4011
245
Number of medication:
Summary RSquare 0.000949 RSquare Adj -0.06149 Root Mean Square Error 2.298633 Mean of Response 1.13365 Observations (or Sum Wgts) 18
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.080278 0.08028 0.0152 Error 16 84.539408 5.28371 Prob > F C. Total 17 84.619687 0.9034
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 1.2460042 1.06037 1.18 0.2572 Number of -0.028484 0.231086 -0.12 0.9034 Medication
246
Joint steroid:
Summary Rsquare 0.01471 Adj Rsquare -0.02813 Root Mean Square Error 3.205284 Mean of Response 1.501744 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Joint 1 3.52786 3.5279 0.3434 0.5636 Steroid Error 23 236.29840 10.2738 C. Total 24 239.82625
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 1.92554 0.96643 -0.0737 3.9247 Yes 14 1.16876 0.85665 -0.6033 2.9409
247
Physically limited:
Summary Rsquare 0.003046 Adj Rsquare -0.0403 Root Mean Square Error 3.2242 Mean of Response 1.501744 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Phisically Limited 1 0.73059 0.7306 0.0703 0.7933 Error 23 239.09567 10.3955 C. Total 24 239.82625
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 1.69460 0.97213 -0.3164 3.7056 Yes 14 1.35021 0.86170 -0.4324 3.1328
248
Pain area:
Summary Rsquare 0.067706 Adj Rsquare 0.027171 Root Mean Square Error 3.117891 Mean of Response 1.501744 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain area 1 16.23766 16.2377 1.6703 0.2090 Error 23 223.58859 9.7212 C. Total 24 239.82625
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Hip 15 0.84371 0.80504 -0.8216 2.5091 Knees 10 2.48879 0.98596 0.4492 4.5284
249
Pain Severity:
Summary Rsquare 0.027384 Adj Rsquare -0.0149 Root Mean Square Error 3.184602 Mean of Response 1.501744 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain 1 6.56744 6.5674 0.6476 0.4292 Severity Error 23 233.25881 10.1417 C. Total 24 239.82625
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Lots of 12 0.96828 0.91932 -0.9335 2.8700 pain Some pain 13 1.99418 0.88325 0.1670 3.8213
250
Family History:
Summary Rsquare 0.017747 Adj Rsquare -0.02496 Root Mean Square Error 3.20034 Mean of Response 1.501744 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Family 1 4.25622 4.2562 0.4156 0.5255 History Error 23 235.57004 10.2422 C. Total 24 239.82625
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 0.67652 1.4312 -2.284 3.6373 Yes 20 1.70805 0.7156 0.228 3.1884 251
Allergies:
Summary Rsquare 0.005857 Adj Rsquare -0.03737 Root Mean Square Error 3.219652 Mean of Response 1.501744 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Allergies 1 1.40461 1.4046 0.1355 0.7162 Error 23 238.42164 10.3662 C. Total 24 239.82625
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 8 1.15621 1.1383 -1.199 3.5110 Yes 17 1.66435 0.7809 0.049 3.2797
252
Physically Active (Workout):
Summary Rsquare 0.019813 Adj Rsquare -0.0228 Root Mean Square Error 3.196972 Mean of Response 1.501744 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Physically 1 4.75179 4.7518 0.4649 0.5021 Active (Workout) Error 23 235.07446 10.2206 C. Total 24 239.82625
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 0.62980 1.4297 -2.328 3.5874 Yes 20 1.71973 0.7149 0.241 3.1985
253
How Often you Workout:
Summary Rsquare 0.288227 Adj Rsquare 0.084863 Root Mean Square Error 1.736032 Mean of Response 0.886805 Observations (or Sum Wgts) 19
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares How Often 4 17.085823 4.27146 1.4173 0.2793 Error 14 42.193295 3.01381 C. Total 18 59.279118
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% 2X /week 2 0.64680 1.2276 -1.986 3.2797 3X /week 9 0.32467 0.5787 -0.916 1.5658 5X /week 3 2.99533 1.0023 0.846 5.1450 6X /week 1 0.00000 1.7360 -3.723 3.7234 7X /week 4 0.91193 0.8680 -0.950 2.7736 254
Bivariate Fit of Proliferation at 10 ppm
Age:
Summary RSquare 0.041183 RSquare Adj -0.0005 Root Mean Square Error 8.619956 Mean of Response 2.279384 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 73.4037 73.4037 0.9879 Error 23 1708.9838 74.3036 Prob > F C. Total 24 1782.3875 0.3306
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 16.603109 14.51402 1.14 0.2644 Age -0.254871 0.256428 -0.99 0.3306
255
Length of Osteoarthritis:
Summary RSquare 0.013173 RSquare Adj -0.03617 Root Mean Square Error 0.549659 Mean of Response 0.474909 Observations (or Sum Wgts) 22
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.0806595 0.080659 0.2670 Error 20 6.0425063 0.302125 Prob > F C. Total 21 6.1231658 0.6110
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 0.373525 0.228547 1.63 0.1178 Length of 0.0084487 0.016351 0.52 0.6110 Osteoarthritis 256
Herbs:
Summary Rsquare 0.012558 Adj Rsquare -0.03233 Root Mean Square Error 8.940333 Mean of Response 2.330608 Observations (or Sum Wgts) 24
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Herbs 1 22.3629 22.3629 0.2798 0.6021 Error 22 1758.4502 79.9296 C. Total 23 1780.8131
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 20 2.76230 1.9991 -1.384 6.9082 Yes 4 0.17215 4.4702 -9.098 9.4427
257
Vitamins:
Summary Rsquare 0.011979 Adj Rsquare -0.03098 Root Mean Square Error 8.750244 Mean of Response 2.279384 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Vitamins 1 21.3517 21.3517 0.2789 0.6025 Error 23 1761.0358 76.5668 C. Total 24 1782.3875
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 6 0.63483 3.5723 -6.755 8.0246 Yes 19 2.79872 2.0074 -1.354 6.9514
258
Number of Medication:
Summary RSquare 0.038163 RSquare Adj -0.02195 Root Mean Square Error 0.575124 Mean of Response 0.479167 Observations (or Sum Wgts) 18
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.2099853 0.209985 0.6348 Error 16 5.2922732 0.330767 Prob > F C. Total 17 5.5022585 0.4372
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 0.2974542 0.265307 1.12 0.2788 Number of 0.0460679 0.057818 0.80 0.4372 Medication
259
Joint Steroid:
Summary Rsquare 0.03944 Adj Rsquare -0.00232 Root Mean Square Error 8.627787 Mean of Response 2.279384 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Joint 1 70.2971 70.2971 0.9444 0.3413 Steroid Error 23 1712.0904 74.4387 C. Total 24 1782.3875
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 4.17115 2.6014 -1.210 9.5525 Yes 14 0.79300 2.3059 -3.977 5.5631 260
Physically Limited:
Summary Rsquare 0.048042 Adj Rsquare 0.006652 Root Mean Square Error 8.58907 Mean of Response 2.279384 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Phisically 1 85.6287 85.6287 1.1607 0.2925 Limited Error 23 1696.7588 73.7721 C. Total 24 1782.3875
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 4.36727 2.5897 -0.990 9.7245 Yes 14 0.63890 2.2955 -4.110 5.3876
261
Pain area:
Summary Rsquare 0.064741 Adj Rsquare 0.024078 Root Mean Square Error 8.513401 Mean of Response 2.279384 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain area 1 115.3936 115.394 1.5921 0.2197 Error 23 1666.9939 72.478 C. Total 24 1782.3875
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Hip 15 0.52520 2.1982 -4.022 5.072 Knees 10 4.91066 2.6922 -0.659 10.480
262
Pain Severity:
Summary Rsquare 0.0341 Adj Rsquare -0.0079 Root Mean Square Error 8.651737 Mean of Response 2.279384 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain 1 60.7789 60.7789 0.8120 0.3769 Severity Error 23 1721.6086 74.8525 C. Total 24 1782.3875
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Lots of 12 0.65650 2.4975 -4.510 5.8231 pain Some pain 13 3.77743 2.3996 -1.186 8.7413
263
Family History:
Summary Rsquare 0.00674 Adj Rsquare -0.03645 Root Mean Square Error 8.773415 Mean of Response 2.279384 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Family 1 12.0129 12.0129 0.1561 0.6964 History Error 23 1770.3746 76.9728 C. Total 24 1782.3875
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 0.89300 3.9236 -7.224 9.0096 Yes 20 2.62598 1.9618 -1.432 6.6843
264
Allergies:
Summary Rsquare 0.021445 Adj Rsquare -0.0211 Root Mean Square Error 8.708226 Mean of Response 2.279384 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Allergies 1 38.2240 38.2240 0.5041 0.4849 Error 23 1744.1635 75.8332 C. Total 24 1782.3875
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 8 0.47688 3.0788 -5.892 6.8459 Yes 17 3.12762 2.1121 -1.241 7.4967
265
Physically Active (Workout):
Summary Rsquare 0.0053 Adj Rsquare -0.03795 Root Mean Square Error 8.779773 Mean of Response 2.279384 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Physically 1 9.4462 9.4462 0.1225 0.7295 Active (Work out) Error 23 1772.9413 77.0844 C. Total 24 1782.3875
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 1.05000 3.9264 -7.072 9.1724 Yes 20 2.58673 1.9632 -1.474 6.6480
266
How Often you Workout:
Summary Rsquare 0.11309 Adj Rsquare -0.14031 Root Mean Square Error 0.605977 Mean of Response 0.489263 Observations (or Sum Wgts) 19
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares How Often 4 0.6555209 0.163880 0.4463 0.7734 Error 14 5.1409208 0.367209 C. Total 18 5.7964417
Means for Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 2X /week 2 0.246500 0.42849 -0.673 1.1655 3X /week 9 0.462111 0.20199 0.029 0.8953 5X /week 3 0.786333 0.34986 0.036 1.5367 6X /week 1 0.000000 0.60598 -1.300 1.2997 7X /week 4 0.571250 0.30299 -0.079 1.2211
267
Bivariate Fit of Proliferation at 100 ppm
Age:
Summary RSquare 0.14681 RSquare Adj 0.109714 Root Mean Square Error 0.994054 Mean of Response 0.91432 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 3.910718 3.91072 3.9576 Error 23 22.727305 0.98814 Prob > F C. Total 24 26.638023 0.0587
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept -2.391851 1.673758 -1.43 0.1664 Age 0.0588287 0.029571 1.99 0.0587
268
Length of Osteoarthritis:
Summary RSquare 0.258956 RSquare Adj 0.221904 Root Mean Square Error 0.969641 Mean of Response 0.951045 Observations (or Sum Wgts) 22
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 6.571034 6.57103 6.9890 Error 20 18.804067 0.94020 Prob > F C. Total 21 25.375101 0.0156*
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 0.0359658 0.403175 0.09 0.9298 Length of 0.0762566 0.028845 2.64 0.0156* Osteoarthritis 269
Herbs:
Summary Rsquare 0.0912 Adj Rsquare 0.049891 Root Mean Square Error 1.044565 Mean of Response 0.933667 Observations (or Sum Wgts) 24
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Herbs 1 2.408900 2.40890 2.2077 0.1515 Error 22 24.004547 1.09112 C. Total 23 26.413447
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 20 1.07535 0.23357 0.5910 1.5597 Yes 4 0.22525 0.52228 -0.8579 1.3084
270
Vitamins:
Summary Rsquare 0.051368 Adj Rsquare 0.010123 Root Mean Square Error 1.04818 Mean of Response 0.91432 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Vitamins 1 1.368334 1.36833 1.2454 0.2760 Error 23 25.269689 1.09868 C. Total 24 26.638023
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 6 0.49800 0.42792 -0.3872 1.3832 Yes 19 1.04579 0.24047 0.5483 1.5432
271
Number of Medication:
Summary RSquare 0.003262 RSquare Adj -0.05903 Root Mean Square Error 1.23809 Mean of Response 0.969944 Observations (or Sum Wgts) 18
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.080255 0.08026 0.0524 Error 16 24.525860 1.53287 Prob > F C. Total 17 24.606115 0.8219
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 0.8576064 0.571136 1.50 0.1527 Number of 0.0284801 0.124468 0.23 0.8219 Medication
272
Joint Steroid:
Summary Rsquare 0.002524 Adj Rsquare -0.04084 Root Mean Square Error 1.074827 Mean of Response 0.91432 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Joint 1 0.067227 0.06723 0.0582 0.8115 Steroid Error 23 26.570796 1.15525 C. Total 24 26.638023
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 0.855818 0.32407 0.18542 1.5262 Yes 14 0.960286 0.28726 0.36604 1.5545
273
Physically Limited:
Summary Rsquare 0.000192 Adj Rsquare -0.04328 Root Mean Square Error 1.076082 Mean of Response 0.91432 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Phisically 1 0.005116 0.00512 0.0044 0.9476 Limited Error 23 26.632908 1.15795 C. Total 24 26.638023
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 0.898182 0.32445 0.22700 1.5694 Yes 14 0.927000 0.28760 0.33206 1.5219
274
Pain area:
Summary Rsquare 0.003741 Adj Rsquare -0.03958 Root Mean Square Error 1.074171 Mean of Response 0.91432 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain area 1 0.099640 0.09964 0.0864 0.7715 Error 23 26.538384 1.15384 C. Total 24 26.638023
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Hip 15 0.965867 0.27735 0.39213 1.5396 Knees 10 0.837000 0.33968 0.13431 1.5397
275
Pain Severity:
Summary Rsquare 0.041808 Adj Rsquare 0.000147 Root Mean Square Error 1.053449 Mean of Response 0.91432 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain 1 1.113676 1.11368 1.0035 0.3269 Severity Error 23 25.524347 1.10975 C. Total 24 26.638023
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Lots of 12 1.13400 0.30410 0.50491 1.7631 pain Some pain 13 0.71154 0.29217 0.10713 1.3159 276
Family History:
Summary Rsquare 0.03748 Adj Rsquare -0.00437 Root Mean Square Error 1.055825 Mean of Response 0.91432 Observations (or Sum 25 Wgts)
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Family 1 0.998401 0.99840 0.8956 0.3538 History Error 23 25.639623 1.11477 C. Total 24 26.638023
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 1.31400 0.47218 0.33722 2.2908 Yes 20 0.81440 0.23609 0.32601 1.3028 277
Allergies:
Summary Rsquare 0.029696 Adj Rsquare -0.01249 Root Mean Square Error 1.060086 Mean of Response 0.91432 Observations (or Sum 25 Wgts)
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Allergies 1 0.791048 0.79105 0.7039 0.4101 Error 23 25.846975 1.12378 C. Total 24 26.638023
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 8 1.17363 0.37480 0.39830 1.9490 Yes 17 0.79229 0.25711 0.26042 1.3242
278
Physically Active (Workout):
Summary Rsquare 3.561e-5 Adj Rsquare -0.04344 Root Mean Square Error 1.076166 Mean of Response 0.91432 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Physically 1 0.000949 0.00095 0.0008 0.9774 Active (Work out) Error 23 26.637075 1.15813 C. Total 24 26.638023
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 0.902000 0.48128 -0.0936 1.8976 Yes 20 0.917400 0.24064 0.4196 1.4152
279
How Often you Workout:
Summary Rsquare 0.462718 Adj Rsquare 0.309209 Root Mean Square Error 0.759216 Mean of Response 0.774526 Observations (or Sum Wgts) 19
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares How Often 4 6.949812 1.73745 3.0143 0.0548 Error 14 8.069735 0.57641 C. Total 18 15.019547
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% 2X /week 2 1.75000 0.53685 0.599 2.9014 3X /week 9 0.24100 0.25307 -0.302 0.7838 5X /week 3 1.33000 0.43833 0.390 2.2701 6X /week 1 0.00000 0.75922 -1.628 1.6284 7X /week 4 1.26425 0.37961 0.450 2.0784
280
Bivariate Fit of Nitric Oxide at 150 ppm
Age:
Summary RSquare 0.048064 RSquare Adj 0.006676 Root Mean Square Error 25.73581 Mean of Response 6.348748 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 769.159 769.159 1.1613 Error 23 15233.628 662.332 Prob > F C. Total 24 16002.787 0.2924
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 52.715332 43.33316 1.22 0.2361 Age -0.825028 0.765594 -1.08 0.2924
281
Length of Osteoarthritis:
Summary RSquare 0.009015 RSquare Adj -0.04053 Root Mean Square Error 1.923289 Mean of Response 1.247 Observations (or Sum Wgts) 22
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.673001 0.67300 0.1819 Error 20 73.980799 3.69904 Prob > F C. Total 21 74.653800 0.6743
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 1.5398531 0.7997 1.93 0.0685 Length of -0.024404 0.057214 -0.43 0.6743 Osteoarthritis 282
Herbs:
Summary Rsquare 0.00928 Adj Rsquare -0.03575 Root Mean Square Error 26.81287 Mean of Response 6.600988 Observations (or Sum Wgts) 24
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Herbs 1 148.149 148.149 0.2061 0.6543 Error 22 15816.464 718.930 C. Total 23 15964.612
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 20 7.71210 5.996 -4.72 20.146 Yes 4 1.04543 13.406 -26.76 28.849
283
Vitamins:
Summary Rsquare 0.01152 Adj Rsquare -0.03146 Root Mean Square Error 26.22514 Mean of Response 6.348748 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Vitamins 1 184.360 184.360 0.2681 0.6096 Error 23 15818.427 687.758 C. Total 24 16002.787
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 6 1.51633 10.706 -20.63 23.664 Yes 19 7.87477 6.016 -4.57 20.321
284
Number of Medication:
Summary RSquare 0.00977 RSquare Adj -0.05212 Root Mean Square Error 2.107365 Mean of Response 1.3575 Observations (or Sum Wgts) 18
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.701039 0.70104 0.1579 Error 16 71.055782 4.44099 Prob > F C. Total 17 71.756821 0.6964
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 1.6895177 0.972137 1.74 0.1014 Number of -0.084173 0.211858 -0.40 0.6964 Medication
285
Joint Steroid:
Summary Rsquare 0.05156 Adj Rsquare 0.010323 Root Mean Square Error 25.68851 Mean of Response 6.348748 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Joint Steroid 1 825.100 825.100 1.2503 0.2750 Error 23 15177.687 659.899 C. Total 24 16002.787
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 12.8299 7.7454 -3.19 28.852 Yes 14 1.2564 6.8655 -12.95 15.459
286
Physically Limited:
Summary Rsquare 0.049562 Adj Rsquare 0.008239 Root Mean Square Error 25.71555 Mean of Response 6.348748 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Phisically Limited 1 793.133 793.133 1.1994 0.2848 Error 23 15209.654 661.289 C. Total 24 16002.787
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 12.7031 7.7535 -3.34 28.742 Yes 14 1.3561 6.8728 -12.86 15.573
287
Pain Area:
Summary Rsquare 0.059885 Adj Rsquare 0.01901 Root Mean Square Error 25.57552 Mean of Response 6.348748 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain area 1 958.320 958.320 1.4651 0.2384 Error 23 15044.467 654.107 C. Total 24 16002.787
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Hip 15 1.2935 6.6036 -12.37 14.954 Knees 10 13.9316 8.0877 -2.80 30.662
288
Pain Severity:
Summary Rsquare 0.037642 Adj Rsquare -0.0042 Root Mean Square Error 25.87631 Mean of Response 6.348748 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain Severity 1 602.370 602.370 0.8996 0.3527 Error 23 15400.417 669.583 C. Total 24 16002.787
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% Lots of pain 12 1.2397 7.4698 -14.21 16.692 Some pain 13 11.0648 7.1768 -3.78 25.911
289
Family History:
Summary Rsquare 0.008748 Adj Rsquare -0.03435 Root Mean Square Error 26.26189 Mean of Response 6.348748 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Family History 1 139.993 139.993 0.2030 0.6565 Error 23 15862.794 689.687 C. Total 24 16002.787
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 1.61600 11.745 -22.68 25.912 Yes 20 7.53194 5.872 -4.62 19.680
290
Allergies:
Summary Rsquare 0.01621 Adj Rsquare -0.02656 Root Mean Square Error 26.16286 Mean of Response 6.348748 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Allergies 1 259.399 259.399 0.3790 0.5442 Error 23 15743.389 684.495 C. Total 24 16002.787
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 8 1.65313 9.2500 -17.48 20.788 Yes 17 8.55845 6.3454 -4.57 21.685
291
Physically Active (Workout):
Summary Rsquare 0.012349 Adj Rsquare -0.03059 Root Mean Square Error 26.21414 Mean of Response 6.348748 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Physically 1 197.624 197.624 0.2876 0.5969 Active(Work out) Error 23 15805.163 687.181 C. Total 24 16002.787
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 0.72560 11.723 -23.53 24.977 Yes 20 7.75454 5.862 -4.37 19.880
292
How Often you Workout:
Summary Rsquare 0.425028 Adj Rsquare 0.26075 Root Mean Square Error 1.6841 Mean of Response 1.249579 Observations (or Sum Wgts) 19
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares How Often 4 29.351747 7.33794 2.5872 0.0826 Error 14 39.706683 2.83619 C. Total 18 69.058431
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% 2X /week 2 0.61500 1.1908 -1.939 3.1691 3X /week 9 0.84500 0.5614 -0.359 2.0490 5X /week 3 0.17333 0.9723 -1.912 2.2587 6X /week 1 0.00000 1.6841 -3.612 3.6120 7X /week 4 3.59675 0.8420 1.791 5.4028
293
Bivariate Fit of Nitric Oxide at 250 ppm
Age:
Summary RSquare 0.025487 RSquare Adj -0.01688 Root Mean Square Error 10.21742 Mean of Response 2.704048 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 62.7972 62.797 0.6015 Error 23 2401.1016 104.396 Prob > F C. Total 24 2463.8988 0.4459
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 15.952568 17.20378 0.93 0.3634 Age -0.235739 0.30395 -0.78 0.4459
294
Length of Osteoarthritis:
Summary RSquare 0.12777 RSquare Adj 0.084158 Root Mean Square Error 1.378783 Mean of Response 0.745818 Observations (or Sum Wgts) 22
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 5.569528 5.56953 2.9297 Error 20 38.020868 1.90104 Prob > F C. Total 21 43.590395 0.1024
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept -0.096646 0.573296 -0.17 0.8678 Length of 0.0702053 0.041016 1.71 0.1024 Osteoarthritis 295
Herbs:
Summary Rsquare 0.014083 Adj Rsquare -0.03073 Root Mean Square Error 10.49832 Mean of Response 2.791008 Observations (or Sum Wgts) 24
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Herbs 1 34.6354 34.635 0.3143 0.5807 Error 22 2424.7261 110.215 C. Total 23 2459.3615
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 20 3.32825 2.3475 -1.54 8.197 Yes 4 0.10480 5.2492 -10.78 10.991
296
Vitamins:
Summary Rsquare 0.018222 Adj Rsquare -0.02446 Root Mean Square Error 10.25544 Mean of Response 2.704048 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Vitamins 1 44.8963 44.896 0.4269 0.5200 Error 23 2419.0025 105.174 C. Total 24 2463.8988
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 6 0.31933 4.1868 -8.342 8.9803 Yes 19 3.45712 2.3528 -1.410 8.3242
297
Number of Medication:
Summary RSquare 0.004257 RSquare Adj -0.05798 Root Mean Square Error 1.616953 Mean of Response 0.844667 Observations (or Sum Wgts) 18
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.178848 0.17885 0.0684 Error 16 41.832594 2.61454 Prob > F C. Total 17 42.011442 0.7970
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 0.6769669 0.745908 0.91 0.3776 Number of 0.0425154 0.162556 0.26 0.7970 Medication
298
Joint Steroid:
Summary Rsquare 0.04674 Adj Rsquare 0.005294 Root Mean Square Error 10.10539 Mean of Response 2.704048 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Joint 1 115.1633 115.163 1.1277 0.2993 Steroid Error 23 2348.7355 102.119 C. Total 24 2463.8988
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 5.12538 3.0469 -1.178 11.428 Yes 14 0.80157 2.7008 -4.785 6.389
299
Physically Limited:
Summary Rsquare 0.047169 Adj Rsquare 0.005741 Root Mean Square Error 10.10312 Mean of Response 2.704048 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Phisically 1 116.2190 116.219 1.1386 0.2970 Limited Error 23 2347.6798 102.073 C. Total 24 2463.8988
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 5.13645 3.0462 -1.165 11.438 Yes 14 0.79287 2.7002 -4.793 6.379
300
Pain area:
Summary Rsquare 0.06728 Adj Rsquare 0.026727 Root Mean Square Error 9.995929 Mean of Response 2.704048 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain area 1 165.7713 165.771 1.6591 0.2105 Error 23 2298.1275 99.919 C. Total 24 2463.8988
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Hip 15 0.60153 2.5809 -4.738 5.941 Knees 10 5.85782 3.1610 -0.681 12.397
301
Pain Severity:
Summary Rsquare 0.039828 Adj Rsquare -0.00192 Root Mean Square Error 10.14196 Mean of Response 2.704048 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain 1 98.1320 98.132 0.9540 0.3389 Severity Error 23 2365.7668 102.859 C. Total 24 2463.8988
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Lots of 12 0.64192 2.9277 -5.415 6.698 pain Some pain 13 4.60755 2.8129 -1.211 10.426
302
Family History:
Summary Rsquare 0.012518 Adj Rsquare -0.03042 Root Mean Square Error 10.28519 Mean of Response 2.704048 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Family 1 30.8427 30.843 0.2916 0.5944 History Error 23 2433.0561 105.785 C. Total 24 2463.8988
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 0.48260 4.5997 -9.033 9.9978 Yes 20 3.25941 2.2998 -1.498 8.0170
303
Allergies:
Summary Rsquare 0.01847 Adj Rsquare -0.0242 Root Mean Square Error 10.25414 Mean of Response 2.704048 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Allergies 1 45.5093 45.509 0.4328 0.5171 Error 23 2418.3895 105.147 C. Total 24 2463.8988
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 8 0.73725 3.6254 -6.762 8.2369 Yes 17 3.62960 2.4870 -1.515 8.7743
304
Physically Active (Workout):
Summary Rsquare 0.017914 Adj Rsquare -0.02479 Root Mean Square Error 10.25705 Mean of Response 2.704048 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Physically 1 44.1377 44.138 0.4195 0.5236 Active (Work out) Error 23 2419.7611 105.207 C. Total 24 2463.8988
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 0.04660 4.5871 -9.443 9.5357 Yes 20 3.36841 2.2935 -1.376 8.1130
305
How Often you Workout:
Summary Rsquare 0.2602 Adj Rsquare 0.048828 Root Mean Square Error 1.153745 Mean of Response 0.591474 Observations (or Sum Wgts) 19
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares How Often 4 6.554508 1.63863 1.2310 0.3422 Error 14 18.635791 1.33113 C. Total 18 25.190299
Means for Anova Level Number Mean Std Error Lower 95% Upper 95% 2X /week 2 0.00000 0.8158 -1.750 1.7498 3X /week 9 0.21456 0.3846 -0.610 1.0394 5X /week 3 1.61000 0.6661 0.181 3.0387 6X /week 1 0.00000 1.1537 -2.475 2.4745 7X /week 4 1.11925 0.5769 -0.118 2.3565 306
Bivariate Fit of Nitric Oxide at 450 ppm
Age:
Summary RSquare 0.040652 RSquare Adj -0.00106 Root Mean Square Error 10.84252 Mean of Response 2.86532 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 114.5766 114.577 0.9746 Error 23 2703.8833 117.560 Prob > F C. Total 24 2818.4599 0.3338
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 20.760872 18.2563 1.14 0.2672 Age -0.318426 0.322545 -0.99 0.3338 307
Length of Osteoarthritis:
Summary RSquare 0.000578 RSquare Adj -0.04939 Root Mean Square Error 1.138166 Mean of Response 0.6515 Observations (or Sum Wgts) 22
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.014992 0.01499 0.0116 Error 20 25.908453 1.29542 Prob > F C. Total 21 25.923446 0.9154
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 0.6077903 0.473248 1.28 0.2137 Length of 0.0036425 0.033858 0.11 0.9154 Osteoarthritis
308
Herbs:
Summary Rsquare 0.014037 Adj Rsquare -0.03078 Root Mean Square Error 11.22515 Mean of Response 2.972625 Observations (or Sum Wgts) 24
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Herbs 1 39.4648 39.465 0.3132 0.5814 Error 22 2772.0865 126.004 C. Total 23 2811.5513
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 20 3.54610 2.5100 -1.66 8.752 Yes 4 0.10525 5.6126 -11.53 11.745
309
Vitamins:
Summary Rsquare 0.012054 Adj Rsquare -0.0309 Root Mean Square Error 11.00293 Mean of Response 2.86532 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Vitamins 1 33.9750 33.975 0.2806 0.6014 Error 23 2784.4850 121.065 C. Total 24 2818.4599
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 6 0.79083 4.4919 -8.501 10.083 Yes 19 3.52042 2.5242 -1.701 8.742
310
Number of Medication:
Summary RSquare 0.011392 RSquare Adj -0.0504 Root Mean Square Error 1.225248 Mean of Response 0.680722 Observations (or Sum Wgts) 18
Analysis of Variance Source DF Sum of Mean Square F Ratio Squares Model 1 0.276794 0.27679 0.1844 Error 16 24.019712 1.50123 Prob > F C. Total 17 24.296506 0.6734
Parameter Estimates Term Estimate Std t Ratio Prob>|t| Error Intercept 0.8893481 0.565212 1.57 0.1352 Number of -0.052891 0.123177 -0.43 0.6734 Medication 311
Joint Steroid:
Summary Rsquare 0.054716 Adj Rsquare 0.013617 Root Mean Square Error 10.76275 Mean of Response 2.86532 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Joint 1 154.2149 154.215 1.3313 0.2604 Steroid Error 23 2664.2451 115.837 C. Total 24 2818.4599
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 5.66727 3.2451 -1.046 12.380 Yes 14 0.66379 2.8765 -5.287 6.614
312
Physically Limited:
Summary Rsquare 0.056171 Adj Rsquare 0.015135 Root Mean Square Error 10.75446 Mean of Response 2.86532 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Phisically 1 158.3146 158.315 1.3688 0.2540 Limited Error 23 2660.1453 115.658 C. Total 24 2818.4599
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 11 5.70427 3.2426 -1.004 12.412 Yes 14 0.63471 2.8743 -5.311 6.581
313
Pain area:
Summary Rsquare 0.055678 Adj Rsquare 0.014621 Root Mean Square Error 10.75727 Mean of Response 2.86532 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain area 1 156.9262 156.926 1.3561 0.2562 Error 23 2661.5338 115.719 C. Total 24 2818.4599
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Hip 15 0.81967 2.7775 -4.926 6.565 Knees 10 5.93380 3.4017 -1.103 12.971
314
Pain Severity:
Summary Rsquare 0.032177 Adj Rsquare -0.0099 Root Mean Square Error 10.8903 Mean of Response 2.86532 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Pain 1 90.6905 90.691 0.7647 0.3909 Severity Error 23 2727.7694 118.599 C. Total 24 2818.4599
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% Lots of 12 0.88292 3.1438 -5.620 7.386 pain Some pain 13 4.69523 3.0204 -1.553 10.943
315
Family History:
Summary Rsquare 0.005493 Adj Rsquare -0.03775 Root Mean Square Error 11.03941 Mean of Response 2.86532 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Family 1 15.4827 15.483 0.1270 0.7248 History Error 23 2802.9773 121.869 C. Total 24 2818.4599
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 1.29140 4.9370 -8.922 11.504 Yes 20 3.25880 2.4685 -1.848 8.365 316
Allergies:
Summary Rsquare 0.015104 Adj Rsquare -0.02772 Root Mean Square Error 10.98594 Mean of Response 2.86532 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Allergies 1 42.5688 42.569 0.3527 0.5584 Error 23 2775.8912 120.691 C. Total 24 2818.4599
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 8 0.96313 3.8841 -7.072 8.9980 Yes 17 3.76047 2.6645 -1.751 9.2724 317
Physically Active (Workout):
Summary Rsquare 0.01199 Adj Rsquare -0.03097 Root Mean Square Error 11.00329 Mean of Response 2.86532 Observations (or Sum Wgts) 25
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Physically 1 33.7945 33.794 0.2791 0.6023 Active (Work out) Error 23 2784.6655 121.072 C. Total 24 2818.4599
Means for Anova Level Number Mean Std Lower Upper 95% Error 95% No 5 0.54000 4.9208 -9.639 10.719 Yes 20 3.44665 2.4604 -1.643 8.536
318
How Often you Workout:
Summary Rsquare 0.64926 Adj Rsquare 0.549048 Root Mean Square Error 0.619204 Mean of Response 0.557 Observations (or Sum Wgts) 19
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares How Often 4 9.936378 2.48409 6.4789 0.0036* Error 14 5.367786 0.38341 C. Total 18 15.304164
Means for Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 2X /week 2 0.00000 0.43784 -0.939 0.9391 3X /week 9 0.24789 0.20640 -0.195 0.6906 5X /week 3 0.60333 0.35750 -0.163 1.3701 6X /week 1 3.43000 0.61920 2.102 4.7581 7X /week 4 0.77800 0.30960 0.114 1.4420
319
APPENDIX AA
ANOVA TEST OF PROLIFERATION RESPONSE QUOTIENT BY CAT’S CLAW
DOSAGE
Level Minimum 10% 25% Median 75% 90% Maximum 0 0.613 0.768 0.964 1.01 1.025 1568 4060 10 0.455 0.8234 0.97 1.01 1.065 1250 3830 100 0.919 0.9522 0.975 1 1.17 1102 4000 150 0.814 0.9562 0.985 1.02 1.155 1025.6 3010 250 0.733 0.958 0.977 1.02 1.135 947.2 5800 450 0.931 0.9496 0.985 1.03 1.16 1110 3710
Summary of Fit Rsquare 0.001509 Adj Rsquare -0.03316 Root Mean Square Error 877.9644 Mean of Response 258.6218 Observations (or Sum 150 Wgts)
320
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Dosage 5 167797 33559 0.0435 0.9989 CC_proliferation Error 144 110998299 770822 C. Total 149 111166096
Means for ANOVA Level Number Mean Std Lower Upper 95% Error 95% 0 25 289.244 175.59 -57.8 636.32 10 25 254.468 175.59 -92.6 601.54 100 25 249.710 175.59 -97.4 596.78 150 25 207.991 175.59 -139.1 555.06 250 25 310.985 175.59 -36.1 658.06 450 25 239.332 175.59 -107.7 586.40
Means and Std Deviations Level Number Mean Std Dev Std Err Lower Upper 95% Mean 95% 0 25 289.244 898.05 179.61 -81.5 659.94 10 25 254.468 821.62 164.32 -84.7 593.62 100 25 249.710 839.36 167.87 -96.8 596.18 150 25 207.991 661.10 132.22 -64.9 480.88 250 25 310.985 1175.60 235.12 -174.3 796.25 450 25 239.332 787.26 157.45 -85.6 564.30
321
APPENDIX BB
ANOVA TEST OF NITRIC OXIDE LIVE CELL RESPONSE QUOTIENT BY CAT’S
CLAW DOSAGE
Level Minimum 10% 25% Median 75% 90% Maximum 0 0 0 0 0.509 1.165 6.832 13.6 10 0 0 0 0.38 0.9885 2.384 43.5 100 0 0 0 0.45 1.535 2.694 3.54 150 0 0 0.006175 0.42 1.2525 4.81 6.59 250 0 0 0 0.0602 0.8415 4.854 50.9 450 0 0 0 0 1.61 3.558 54.6
Summary of Fit Rsquare 0.011101 Adj Rsquare -0.02348 Root Mean Square Error 7.197172 Mean of Response 1.915028 Observations (or Sum 149 Wgts)
322
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Dosage CC 5 83.1515 16.6303 0.3211 0.8997 NO+ Error 143 7407.2976 51.7993 C. Total 148 7490.4490
Means for ANOVA Level Number Mean Std Lower Upper 95% Error 95% 0 25 1.50174 1.4394 -1.344 4.3471 10 25 2.27938 1.4394 -0.566 5.1247 100 25 0.91432 1.4394 -1.931 3.7596 150 24 1.19661 1.4691 -1.707 4.1006 250 25 2.70405 1.4394 -0.141 5.5494 450 25 2.86532 1.4394 0.020 5.7106
Means and Std Deviations Level Number Mean Std Dev Std Err Lower Upper 95% Mean 95% 0 25 1.50174 3.1611 0.6322 0.197 2.8066 10 25 2.27938 8.6178 1.7236 -1.278 5.8366 100 25 0.91432 1.0535 0.2107 0.479 1.3492 150 24 1.19661 1.8188 0.3713 0.429 1.9646 250 25 2.70405 10.1322 2.0264 -1.478 6.8864 450 25 2.86532 10.8368 2.1674 -1.608 7.3385
323
APPENDIX CC
ANOVA TEST OF NITRIC OXIDE DEAD CELL RESPONSE QUOTIENT BY CAT’S
CLAW DOSAGE
Level Minimum 10% 25% Median 75% 90% Maximum 0 0 0 0 0 0.03545 1.972 6.44 10 0 0 0 0 0 3.444 9 100 0 0 0 0 0.1345 6.83 24.4 150 0 0 0 0 0.036719 1.40043 2.041958 250 0 0 0 0 0 1.3594 3.56 450 0 0 0 0 0 1.1544 3.38
Summary of Fit Rsquare 0.041547 Adj Rsquare 0.008268 Root Mean Square Error 2.422608 Mean of Response 0.600107 Observations (or Sum 150 Wgts)
324
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Dosage-2 5 36.63538 7.32708 1.2484 0.2897 Error 144 845.14052 5.86903 C. Total 149 881.77590
Means for ANOVA Level Number Mean Std Lower Upper Error 95% 95% 0 25 0.50708 0.48452 -0.4506 1.4648 10 25 0.70548 0.48452 -0.2522 1.6632 100 25 1.63780 0.48452 0.6801 2.5955 150 25 0.22405 0.48452 -0.7336 1.1817 250 25 0.27556 0.48452 -0.6821 1.2333 450 25 0.25068 0.48452 -0.7070 1.2084
Means and Std Deviations Level Number Mean Std Dev Std Err Mean Lower Upper 95% 95% 0 25 0.50708 1.42734 0.2855 -0.0821 1.0963 10 25 0.70548 2.15432 0.4309 -0.1838 1.5947 100 25 1.63780 5.16462 1.0329 -0.4941 3.7697 150 25 0.22405 0.54646 0.1093 -0.0015 0.4496 250 25 0.27556 0.93476 0.1870 -0.1103 0.6614 450 25 0.25068 0.83071 0.1661 -0.0922 0.5936
325
APPENDIX DD
ANOVA TEST OF NITRIC OXIDE TOTAL CELL (LIVE AND DEAD CELLS)
RESPONSE QUOTIENT BY CAT’S CLAW DOSAGE
Level Minimum 10% 25% Median 75% 90% Maximum 0 0.445 0.5502 0.825 1.14 2.505 5.102 9.59 10 0.0448 0.3994 0.6435 0.885 1.615 16.97 2310 100 0.423 0.5196 0.6745 1.07 2.75 29.88 296 150 0.000991 0.02608 0.4365 0.906 2.285 393.44 1330 250 0.0378 0.1272 0.5375 0.746 1.1915 7.694 31.9 450 0.103 0.3962 0.5055 1.14 2.43 8.472 507
Summary of Fit Rsquare 0.029413 Adj Rsquare -0.00429 Root Mean Square Error 234.424 Mean of Response 38.39786 Observations (or Sum 150 Wgts)
326
Analysis of Variance Source DF Sum of Mean Square F Ratio Prob > F Squares Dosage -3 5 239815.9 47963.2 0.8728 0.5011 Error 144 7913463.0 54954.6 C. Total 149 8153278.8
Means for ANOVA Level Number Mean Std Lower Upper 95% Error 95% 0 25 2.0147 46.885 -90.66 94.69 10 25 94.9661 46.885 2.29 187.64 100 25 15.5591 46.885 -77.11 108.23 150 25 93.1723 46.885 0.50 185.84 250 25 2.6213 46.885 -90.05 95.29 450 25 22.0538 46.885 -70.62 114.73
Means and Std Deviations Level Number Mean Std Dev Std Err Lower Upper 95% Mean 95% 0 25 2.0147 2.119 0.424 1.14 2.89 10 25 94.9661 461.509 92.302 -95.54 285.47 100 25 15.5591 59.002 11.800 -8.80 39.91 150 25 93.1723 320.928 64.186 -39.30 225.64 250 25 2.6213 6.551 1.310 -0.0829 5.33 450 25 22.0538 101.060 20.212 -19.66 63.77