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In the last few years click chemistry reactions, and in particular copper-catalyzed cycloadditions have been used extensively for the preparation of new bioconjugated molecules such as F-18-radiolabeled radiopharmaceuticals for positron emission tomography (PET). This study is focused on the synthesis of the Siemens imaging biomarker [F-18]RGD-K5. This cyclic peptide contains an amino acid sequence which is a well known binding motif for integrin alpha(v)beta(3) involved in cellular-adhesion to the extracellular matrix. We developed an improved "click" chemistry method using Cu(I)-Monophos as catalyst to conjugate [F-18]fluoropentyne to the RGD-azide precursor yielding [F-18]RGD-K5. A comparison is made with the registered Siemens method with respect to synthesis, purification and quality control. [F-18]RGD-K5 was obtained after 75 min overall synthesis time with an overall radiochemical yield of 35% (EOB). The radiochemical purity was >98% and the specific radioactivity was 100-200 GBq/mu mol at the EOS. (C) 2013 Elsevier Inc. All rights reserved.

Thousands of masters athletes participate quadrennially in the World Masters Games (WMG), yet this cohort of athletes remains proportionately under-investigated. Due to a growing global obesity pandemic in context of benefits of physical activity across the lifespan, the BMI trends for this unique population was of particular interest. The nexus between health, physical activity and aging is complex and has raised much interest in recent times due to the realization that a multifaceted approach is necessary in order to counteract the obesity pandemic. By investigating age based trends within a population adhering to competitive sport at older ages, further insight might be gleaned to assist in understanding one of many factors influencing this relationship.BMI was derived using data gathered on a total of 6,071 masters athletes (51.9% male, 48.1% female) aged 25 to 91 years ( =51.5, s =±9.7), competing at the Sydney World Masters Games (2009). Using linear and loess regression it was demonstrated that the usual tendency for prevalence of higher BMI increasing with age was reversed in the sample. This trend in reversal was repeated for both male and female only sub-sets of the sample participants, indicating the possibility of improved prevalence of BMI with increasing age for both the sample as a whole and these individual sub-groups.This evidence of improved classification in one index of health (reduced BMI) for masters athletes (when compared to the general population) implies there are either improved levels of this index of health with aging due to adherence to sport or possibly the reduced BMI is advantageous and contributes to this cohort adhering (or being attracted) to masters sport at older ages.

Recently, the health of retired National Football League players, particularly lineman has been investigated. A number of studies have reported increased cardiometabolic risk, premature cardiovascular disease and incidence of type 2 diabetes. Rugby union players have somatotypes very similar to National Football League players which suggests that rugby players may have similar health risks. The International Golden Oldies World Rugby Festival (GORF) provided a unique opportunity to investigate the demographics of veteran rugby players. METHODOLOGIES: A cross-sectional, observational study was completed using an online web-based questionnaire that consisted of medical history and physiological measures. Data analysis was completed using a one sample t-test (50yrs) and Chi-square test. RESULTS: A total of 216 veteran rugby competitors (response rate = 6.8%) representing 10 countries, aged 35-72 yrs (mean 51.2, S.D. ±8.0), participated in the online survey. As a group, the incidence of current smokers was low at 8.8% (avg 72.4 cigs/wk) whilst the percentage consuming alcohol was high (93.1% (avg 11.2 drinks/wk). Competitors reported the following top six chronic diseases/disorders; hypertension (18.6%), arthritis (OA/RA, 11.5%), asthma (9.3%), hyperlipidemia (8.2%), diabetes (all types, 7.5%) and gout (6%), there were significant differences between groups with regard to cancer (all types) and migraines. When compared to the Australian general population (Australian Bureau of Statistics data, n=18,000), GORF competitors had a significantly lower incidence of anxiety (p50yrs) with regard to height (180 vs 177cm), weight (97.6 vs 93.1Kg-s), BMI (30 vs 29.7kg/m2) and waist circumference (85.7 vs 93.1cm) however, there were no differences in subsequent parameters of systolic blood pressure, diastolic blood pressure, total cholesterol, HDL-C, LDL-C, triglycerides-C or fasting plasma glucose. CONCLUSIONS: This represents the first collection of demographics on this cohort. GORF participants demonstrated increased cardiometabolic risk with regard to the incidence of hypercholesterolemia, hypertension and type 2 diabetes. Preventative strategies should be developed to reduce this risk with education of these risks for future participants., {"references":["Seldon, M., Helzberg, J., Waeckerle, J., Browne, J., Brewer, J.,\nMonaco, M., Tang, F. & O-Keefe, J. (2009). Cardiometabolic\nabnormalities in current National Football League players.\nAmerican Journal of Cardiology, 103, 969-971.","Chang, A., Fitzgerald, S., Cannaday, J., Zhang, S., Patel, A.,\nPalmer, M., Reddy, G., Ordovas, K., Stillman, A., Janowitz, W.,\nRadford, N., Roberts, A. & Levine, B. (2009). Cardiovascular\nrisk factors and coronary atherosclerosis in retired National\nFootball Leagues players. American Journal of Cardiology,\n104, 805-811.","Tucker, A., Vogel, R., Lincoln, A., Dunn, R., Ahrensfield, D.,\nAllen, T., Castle, LW., Heyer, R., Pellman, E., Strollo, P.,\nWilson, P. & Yates, A. (2009). Prevalence of cardiovascular\ndisease risk factors among national football league pleayers.\nJournal of the American Medical Association, 310(20), 2111-\n2119.","Miller, M., Croft, L., Belanger, A., Romeo-Corral, A., Somers,\nV., Roberts, A. & Goldman, M. (2008). Prevalence of\nmetabolic syndrome in Retired National Football league players.\nAmerican Journal of Cardiology, 101, 1281-1284.","Hu, F., Willett, W., Li, T., Stampfer, M., Colditz, G. & Manson,\nJ. (2004). Adiposity as compared with physical activity in\npredicting mortality. New England Journal of Medicine,\n351(26), 2694-2703.","Olds, T. (2001). The evolution of physique in male rugby union\nplayers in the twentieth century. Journal of Sports Sciences, 19,\n253-262.","Chobanian A., Bakris G., Black H., Cushman W., Green L., Izzo\nJ., Jones D., Materson B., Oparil S., Wright J. & Roccella E.\n(2003). The Seventh Report of the Joint National Committee on\nPrevention, Detection, Evaluation, and Treatment of High Blood\nPressure: the JNC 7 report. Journal of the American Medical\nAssociation, 289(19), 2560-3672.","Carrington, M. & Stewart S. (2010). Australia-s Cholesterol\nCrossroads: An analysis of 199,331 GP patient cholesterol\nrecords from 2004 to 2009. Melbourne, Australia: Baker IDI\nHeart & Diabetes Institute.","Australian Bureau of Statistics (2010). National health survey:\nsummary of results, 2007-2008 (Reissue). Canberra, Australia:\nAustralian Bureau of Statistics.\n[10] Aronne, L. (2002). Classification of obesity and assessment of\nobesity-related health risks. Obesity Research, 10(2), 105S-\n115S."]}

Thousands of masters athletes participate quadrennially in the World Masters Games (WMG), yet this cohort of athletes remains proportionately under-investigated. Due to a growing global obesity pandemic in context of benefits of physical activity across the lifespan, the prevalence of obesity in this unique population was of particular interest. Data gathered on a sub-sample of 535 football code athletes, aged 31-72 yrs ( =47.4, s =±7.1), competing at the Sydney World Masters Games (2009) demonstrated a significantly (p, {"references":["Sydney 2009 World Masters Games Committee. (2009). Sydney 2009\nWorld Masters Games Final Report.","Sawyer, K., & Sceppa, C. (2010). Cardiovascular disease - Review-\nImpact of aerobic physical activity on cardiovascular and\nnoncardiovascular outcomes: is anyone too old to exercise? Aging\nHealth, 6(2), 251-260.","Williamson, J., & Pahor, M. (2010). Evidence Regarding the Benefits of\nPhysical Exercise Archives of Internal Medicine, 170(2), 124-125.","Ryan, A. (2010). Review exercise in aging: it-s important role in\nmortality, obesity and insulin resistance. Aging Health, 6(5), 551-563.","Kenyon, C. (2010). The genetics of aging. Nature 464, 504-512.","King, A., & Guralnik, J. (2010). Maximizing the potential of an aging\npopulation. The Journal of the American Medical Association, 304(17)\n1954-1955.","Doherty, T. (2003). Aging and sarcopenia. Journal of Applied\nPhysiology, 95(4) 1717-1727.","Garabed, E. (2008). Adolphe Quetelet (1796-1874)ÔÇöthe average man\nand indices of obesity. Nephrology Dialysis Transplantation, 23, 47-51","World Health Organisation (2002). The world health report 2002 -\nReducing Risks, Promoting Healthy Life, 4, 60.\n[10] World Health Organisation Media Centre (2011). Obesity and\noverweight, 311\n[11] Australian Institute of Health and Welfare 2008. Australia-s health 2008.\nCat. no. AUS 99. Canberra: Australian Institute of Health and Welfare\n[12] Begg, S., Vos, T., Barker, B., Stevenson, C., Stanley, L., & Lopez, A.\n(2007). The burden of disease and injury in Australia 2003. PHE 82.\nCanberra: Australian Institute of Health and Welfare.\n[13] Access Economics, (2006). The economic costs of obesity. Report for\nDiabetes Australia.\n[14] Ode, J., Pivarnik, J., Reeves, M., & Knous, J. (2007). Body mass index\nas a predictor of percent fat in college athletes and nonathletes. Medicine\n& Science in Sports & Exercise, 39(3) 403-409.\n[15] Australian Bureau of Statistics (2010). National health survey: summary\nof results, 2007-2008 (Reissue).\n[16] Gorber, S., Tremblay, M., Moher, D., Gorber, B. (2007). A comparison\nof direct vs. self-report measures for assessing height, weight and body\nmass index: a systematic review. Obesity reviews, 8, 307-326.\n[17] McCarthy, M. (2004). Curbing the obesity epidemic. The Lancet, 367,\n1549\n[18] Walsh, J. (2010). A Markov States model for touch football:\nProceedings of the tenth Australasian Conference on Mathematics and\nComputers in Sport (pp259-267). Darwin, Australia.\n[19] Okorodudu, D., Jumean, M., Montori, V., Romero-Corral, A., Somers,\nV., Erwin, P., & Lopez-Jimenez, F. (2010). Diagnostic performance of\nbody mass index to indentify obesity as defined by body adiposity: a\nsystemic review and meta-analysis. International Journal of Obesity,\n34,791-799."]}

Whilst there is growing evidence that activity across the lifespan is beneficial for improved health, there are also many changes involved with the aging process and subsequently the potential for reduced indices of health. The nexus between health, physical activity and aging is complex and has raised much interest in recent times due to the realization that a multifaceted approached is necessary in order to counteract a growing obesity epidemic. By investigating age based trends within a population adhering to competitive sport at older ages, further insight might be gleaned to assist in understanding one of many factors influencing this relationship. BMI was derived using data gathered on a total of 6,071 masters athletes (51.9% male, 48.1% female) aged 25 to 91 years ( =51.5, s =±9.7), competing at the Sydney World Masters Games (2009). Using linear and loess regression it was demonstrated that the usual tendency for prevalence of higher BMI increasing with age was reversed in the sample. This trend in reversal was repeated for both male and female only sub-sets of the sample participants, indicating the possibility of improved prevalence of BMI with increasing age for both the sample as a whole and these individual subgroups. This evidence of improved classification in one index of health (reduced BMI) for masters athletes (when compared to the general population) implies there are either improved levels of this index of health with aging due to adherence to sport or possibly the reduced BMI is advantageous and contributes to this cohort adhering (or being attracted) to masters sport at older ages. Demonstration of this proportionately under-investigated World Masters Games population having an improved relationship between BMI and increasing age over the general population is of particular interest in the context of the measures being taken globally to curb an obesity epidemic.

Whilst there is growing evidence that activity across the lifespan is beneficial for improved health, there are also many changes involved with the aging process and subsequently the potential for reduced indices of health. Data gathered on a subsample of 535 football code athletes, aged 31-72 yrs ( = 47.4, s = ±7.1), competing at the Sydney World Masters Games (2009) demonstrated a significantly (p < 0.001), reduced classification of obesity using Body Mass Index (BMI) when compared to the general Australian population. This evidence of improved classification in one index of health (BMI < 30) for master athletes (when compared to the general population) implies there are either improved levels of this index of health due to adherence to sport or possibly the reduced BMI is advantageous and contributes to this cohort adhering (or being attracted) to masters sport. Demonstration of this proportionately under-investigated World Masters Games population having improved health over the general population is of particular interest., {"references":["Sydney 2009 World Masters Games Committee. (2009). Sydney 2009\nWorld Masters Games Final Report.","Sawyer, K., & Sceppa, C. (2010). Cardiovascular disease - Review-\nImpact of aerobic physical activity on cardiovascular and\nnoncardiovascular outcomes: is anyone too old to exercise? Aging\nHealth, 6(2), 251-260.","Williamson, J., & Pahor, M. (2010). Evidence Regarding the Benefits of\nPhysical Exercise Archives of Internal Medicine, 170(2), 124-125.","Ryan, A. (2010). Review exercise in aging: it-s important role in\nmortality, obesity and insulin resistance. Aging Health, 6(5), 551-563.","Kenyon, C. (2010). The genetics of aging. Nature 464, 504-512.","King, A., & Guralnik, J. (2010). Maximizing the potential of an aging\npopulation. The Journal of the American Medical Association, 304(17)\n1954-1955.","Doherty, T. (2003). Aging and sarcopenia. Journal of Applied\nPhysiology, 95(4) 1717-1727.","Garabed, E. (2008). Adolphe Quetelet (1796-1874)ÔÇöthe average man\nand indices of obesity. Nephrology Dialysis Transplantation, 23, 47-51","World Health Organisation (2002). The world health report 2002 -\nReducing Risks, Promoting Healthy Life, 4, 60.\n[10] World Health Organisation Media Centre (2011). Obesity and\noverweight, 311\n[11] Australian Institute of Health and Welfare 2008. Australia-s health 2008.\nCat. no. AUS 99. Canberra: Australian Institute of Health and Welfare\n[12] Begg, S., Vos, T., Barker, B., Stevenson, C., Stanley, L., & Lopez, A.\n(2007). The burden of disease and injury in Australia 2003. PHE 82.\nCanberra: Australian Institute of Health and Welfare.\n[13] Access Economics, (2006). The economic costs of obesity. Report for\nDiabetes Australia.\n[14] Ode, J., Pivarnik, J., Reeves, M., & Knous, J. (2007). Body mass index\nas a predictor of percent fat in college athletes and nonathletes. Medicine\n& Science in Sports & Exercise, 39(3) 403-409.\n[15] Australian Bureau of Statistics (2010). National health survey: summary\nof results, 2007-2008 (Reissue).\n[16] Gorber, S., Tremblay, M., Moher, D., Gorber, B. (2007). A comparison\nof direct vs. self-report measures for assessing height, weight and body\nmass index: a systematic review. Obesity reviews, 8, 307-326.\n[17] McCarthy, M. (2004). Curbing the obesity epidemic. The Lancet, 367,\n1549\n[18] Walsh, J. (2010). A Markov States model for touch football:\nProceedings of the tenth Australasian Conference on Mathematics and\nComputers in Sport (pp259-267). Darwin, Australia.\n[19] Okorodudu, D., Jumean, M., Montori, V., Romero-Corral, A., Somers,\nV., Erwin, P., & Lopez-Jimenez, F. (2010). Diagnostic performance of\nbody mass index to indentify obesity as defined by body adiposity: a\nsystemic review and meta-analysis. International Journal of Obesity,\n34,791-799."]}

Whilst there is growing evidence that activity across the lifespan is beneficial for improved health, there are also many changes involved with the aging process and subsequently the potential for reduced indices of health. The nexus between all forms of health, physical activity and aging is complex and has raised much interest in recent times due to the realization that a multifaceted approached is necessary in order to counteract a growing obesity epidemic. By investigating age based trends within a population adherring to competitive sport at older ages, further insight might be gleaned to assist in understanding one of many factors influencing this relationship. This study evaluated those sport psychological constructs of health, physical fitness, mental health states, and social dimension factors in sport that were associated with factors to participate in sport and physical activity based on responses from the 2009 World Masters Games in Sydney. The sample consisted of 7846 athletes who competed at the games and who completed a 56 item sports participation survey using a 7-point Likert response (1 - not important to 7 - very important). Questions focuses on factors thought to promote participation, such as weight control, living longer, improving mental health (self-esteem, mood states), improving physical health and factors related to the athlete-s competitive perspective. The most significant factors related to participation with this cohort of masters athletes were the socializing environment of sport, getting physically fit and improving competitive personal best performances. Strategies to increase participation in masters sport should focus on these factors as other factors such as weight loss, improving mental health and living longer were not identified as important determinates of sports participation at the World Masters level., {"references":["Sydney 2009 World Masters Games Committee, Sydney 2009 World\nMasters Games Final Report, 2009.","K. Sawyer and C. \"Cardiovascular disease review Impact of aerobic\nphysical activity on cardiovascular and noncardiovascular outcomes: Is\nanyone too old to exercise?\" Aging Health, vol. 6, no. 2, pp. 251-260,\n2010.","J. Williamson and M. Pahor, \"Evidence Regarding the Benefits of Physical\nExercise,\" Archives of Internal Medicine, vol. 170, no. 2, pp. 124-125,\n2010.","A. Ryan, \"Review exercise in aging: It-s important role in mortality,\nobesity and insulin resistance,\" Aging Health, vol. 6, no. 5, pp. 551-563,\n2010.","C. Kenyon, \"The genetics of aging,\" Nature vol. 464, pp. 504-512, 2010.","A. King, and J. Guralnik, \"Maximizing the potential of an aging\npopulation,\" The Journal of the American Medical Association, vol. 304,\nno. 17, pp. 1954-1955, 2010.","T. Doherty, \"Aging and sarcopenia,\" Journal of Applied Physiology, vol.\n95, no. 4, pp. 1717-1727, 2003.","World Health Organisation, Global Recommendations on Physical Activity\nfor Health, Geneva, 2010.","Australian Bureau of Statistics, Participation in Sport and Physical\nRecreation. Canberra: Australian Bureau of Statistics, 2011.\n[10] SPSS Inc, PASW: Statistics 18. User-s Guide. Chicago: SPSS Inc, 2011."]}

Recently, the health of retired National Football League players, particularly lineman has been investigated. A number of studies have reported increased cardiometabolic risk, premature ardiovascular disease and incidence of type 2 diabetes. Rugby union players have somatotypes very similar to National Football league players which suggest that rugby players may have similar health risks. The International Golden Oldies World Rugby Festival (GORF) provided a unique opportunity to investigate the demographics of veteran rugby players. METHODOLOGIES: A cross-sectional, observational study was completed using an online web-based questionnaire that consisted of medical history and physiological measures. Data analysis was completed using a one sample t-test (50yrs) and Chi-square test. RESULTS: A total of 216 veteran rugby competitors (response rate = 6.8%) representing 10 countries, aged 35-72 yrs (mean 51.2, S.D. ±8.0), participated in the online survey. As a group, the incidence of current smokers was low at 8.8% (avg 72.4 cigs/wk) whilst the percentage consuming alcohol was high (93.1% (avg 11.2 drinks/wk). Competitors reported the following top six chronic diseases/disorders; hypertension (18.6%), arthritis (OA/RA, 11.5%), asthma (9.3%), hyperlipidemia (8.2%), diabetes (all types, 7.5%) and gout (6%), there were significant differences between groups with regard to cancer (all types) and migraines. When compared to the Australian general population (Australian Bureau of Statistics data, n=18,000), GORF competitors had a Climstein Mike, Walsh Joe (corresponding author) and Burke Stephen School of Exercise Science, Australian Catholic University, 25A Barker Road, Strathfield, Sydney, NSW, 2016, Australia (e-mail: mike.climstein@acu.edu.au, joe.walsh@acu.edu.au, stephen.burke@acu.edu.au). John Best is with Orthosports, 160 Belmore Rd., Randwick, Sydney,NSW 2031, Australia (e-mail: bestfam@bigpond.net.au). Heazlewood, Ian Timothy is with School of Environmental and Life Sciences, Faculty Education, Health and Science, Charles Darwin University, Precinct Yellow Building 2, Charles Darwin University, NT 0909, Australia (e-mail: an.heazlewood@cdu.edu.au). Kettunen Jyrki Arcada University of Applied Sciences, Jan-Magnus Janssonin aukio 1, FI-00550, Helsinki, Finland (e-mail: jyrki.kettunen@orton.fi). Adams Kent is with California State University Monterey Bay, Kinesiology Department, 100 Campus Center, Seaside, CA., 93955, USA (email: kadams@csumb.edu). DeBeliso Mark is with Department of Physical Education and Human Performance, Southern Utah University, 351 West University Blvd, Cedar City, Utah, USA (e-mail: markdebeliso@suu.edu). significantly lower incidence of anxiety (p50yrs) with regard to height (180 vs 177cm), weight (97.6 vs 93.1Kg-s), BMI (30 vs 29.7kg/m2) and waist circumference (85.7 vs 93.1cm) however, there were no differences in subsequent parameters of systolic blood pressure, diastolic blood pressure, total cholesterol, HDL-C, LDL-C, triglycerides-C or fasting plasma glucose. CONCLUSIONS: This represents the first collection of demographics on this cohort. GORF participants demonstrated increased cardiometabolic risk with regard to the incidence of hypercholesterolemia, hypertension and type 2 diabetes. Preventative strategies should be developed to reduce this risk with education of these risks for future participants., {"references":["Seldon, M., Helzberg, J., Waeckerle, J., Browne, J., Brewer, J., Monaco, M., Tang, F. & O-Keefe, J. (2009). Cardiometabolic\nabnormalities in current National Football League players. American Journal of Cardiology, 103, 969-971.","Chang, A., Fitzgerald, S., Cannaday, J., Zhang, S., Patel, A.,\nPalmer, M., Reddy, G., Ordovas, K., Stillman, A., Janowitz, W.,\nRadford, N., Roberts, A. & Levine, B. (2009). Cardiovascular\nrisk factors and coronary atherosclerosis in retired National\nFootball Leagues players. American Journal of Cardiology,104, 805-811.","Tucker, A., Vogel, R., Lincoln, A., Dunn, R., Ahrensfield, D.,\nAllen, T., Castle, LW., Heyer, R., Pellman, E., Strollo, P.,\nWilson, P. & Yates, A. (2009). Prevalence of cardiovascular\ndisease risk factors among national football league pleayers.\nJournal of the American Medical Association, 310(20), 2111-2119.","Miller, M., Croft, L., Belanger, A., Romeo-Corral, A., Somers,\nV., Roberts, A. & Goldman, M. (2008). Prevalence of\nmetabolic syndrome in Retired National Football league players.\nAmerican Journal of Cardiology, 101, 1281-1284.","Hu, F., Willett, W., Li, T., Stampfer, M., Colditz, G. & Manson, J. (2004). Adiposity as compared with physical activity in predicting mortality. New England Journal of Medicine, 351(26), 2694-2703.","Olds, T. (2001). The evolution of physique in male rugby union\nplayers in the twentieth century. Journal of Sports Sciences, 19,253-262.","Chobanian A., Bakris G., Black H., Cushman W., Green L., Izzo J., Jones D., Materson B., Oparil S., Wright J. & Roccella\nE. (2003). The Seventh Report of the Joint National Committee\non Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. Journal of the American Medical Association, 289(19), 2560-3672.","Carrington, M. & Stewart S. (2010). Australia-s Cholesterol\nCrossroads: An analysis of 199,331 GP patient cholesterol\nrecords from 2004 to 2009. Melbourne, Australia: Baker IDI Heart & Diabetes Institute.","Australian Bureau of Statistics (2010). National health survey:\nsummary of results, 2007-2008 (Reissue). Canberra, Australia:\nAustralian Bureau of Statistics.\n[10] Aronne, L. (2002). Classification of obesity and assessment of\nobesity-related health risks. Obesity Research, 10(2), 105S-115S."]}