Joint Cartilage in Long-Duration Spaceflight

This review summarizes the current literature available on joint cartilage alterations in long-duration spaceflight. Evidence from spaceflight participants is currently limited to serum biomarker data in only a few astronauts. Findings from analogue model research, such as bed rest studies, as well as data from animal and cell research in real microgravity indicate that unloading and radiation exposure are associated with joint degeneration in terms of cartilage thinning and changes in cartilage composition. It is currently unknown how much the individual cartilage regions in the different joints of the human body will be affected on long-term missions beyond the Low Earth Orbit. Given the fact that, apart from total joint replacement or joint resurfacing, currently no treatment exists for late-stage osteoarthritis, countermeasures might be needed to avoid cartilage damage during long-duration missions. To plan countermeasures, it is important to know if and how joint cartilage and the adjacent structures, such as the subchondral bone, are affected by long-term unloading, reloading, and radiation. The use of countermeasures that put either load and shear, or other stimuli on the joints, shields them from radiation or helps by supporting cartilage physiology, or by removing oxidative stress possibly help to avoid OA in later life following long-duration space missions. There is a high demand for research on the efficacy of such countermeasures to judge their suitability for their implementation in long-duration missions

Skin Temperature in Master Long-Distance Runners-Results From a Field Study at the 2018 World Master Athletics Championships.

Older people and athletes show impairments in thermoregulation, but this has not yet been studied during a running competition. The aim of the study was to assess (1) whether there are age-related differences in skin temperature during the last stage of a race in well-trained master athletes and (2) to what extent such differences are related to running speed and sex. To investigate this, we used thermography to measure maximum skin temperatures of the head, legs and hands of participants of the 2018 World Master Athletics (WMA) Championships when they were approximately 9,600 m into a 10,000-m road race. Of the 813 runners, 404 were analyzed (142 women, 262 men) including athletes of age groups 35 to 85. All ≥70-year-old athletes completed the race; all 16 non-finishers were younger. The hand temperature was lower than that of the head and legs (p p p p < 0.001), men having higher leg temperatures than women, with a small negative contribution of speed ( Radj2 increased to 0.069). In conclusion, higher running speed is associated with lower skin temperatures, and leg skin temperature is lower in women than men. The absence of an age effect on skin temperature suggests that there is no impairment in heat dissipation in well-trained older athletes

Accelerated Decline in Javelin Throwing Performance in Master Athletes 70 Years and Older - Do Changes in Technique Play a Role?

While many older adults are immobile and frail, others still participate in competitive sports. World records of javelin throw decrease with increasing age. It is, however, unknown 1) whether the decline is linear or, as in sprint performance, accelerates beyond the age of 69; and 2) to what extent frailty-related changes in throwing technique contribute to decreasing performance. We plotted current world records against age and assessed the performance of 27 male javelin throwers 69 years and older during three master athletics championships. Three to six throws were filmed, and the best throw of each athlete selected. A step-wise linear regression was applied to assess contributions of age, angle of release, angle of attitude, angle of attack and elbow angle just before the pull to performance. The ageing-related decline in javelin-throw performance accelerated after age 69. Age was the main predictor of performance (adjusted R 2 =0.68), with a small contribution of elbow angle (adjusted R 2 increased to 0.76) and angle of attack (R 2 =0.82; all P<0.001) in the older athletes. None of the technique-related parameters correlated with age. Although the technique had some influence on javelin-throwing performance, the accelerated decline was not associated with a characteristic ageing-related change in technique

Declining track and field performance trends in recent years in the Austrian best results 1897-2019.

Objectives: Plateauing of world records in sports has been suggested to reflect the limits of human physiology. Possible explanations include reduced doping or declining popularity that may even lead to a decrease in human performance. Such a decrease, however, has not yet been observed. We hypothesized that rather than a performance plateau, performance has recently declined. Methods: Fifteen athletic disciplines of the Austrian annual rankings were analyzed by regression statistics and the average best performance of the last 20 years compared to earlier periods. Results: The best performances occurred between 1980-1999 and were on average 2.56% (men) and 1.67% (women) better than between 2000-2019. This attenuation was significant in men in 200 m, 800 m, 1500 m, 10 km, long jump, javelin throw (p<0.05), high jump, pole vault, discus throw, shot put and hammer throw (p<0.001); and in women in 400 m, long jump, discus throw (p<0.05) and high jump (p<0.001). The greatest performance declines were observed in the men's shot put (9.11%) and hammer throw (11.44%). Conclusions: The Austrian track and field annual best results show a performance decline following a peak, instead of a plateau. Future studies should address the causes and whether this also applies to other sports and countries

Gait Analysis to Monitor Fracture Healing of the Lower Leg

Fracture healing is typically monitored by infrequent radiographs. Radiographs come at the cost of radiation exposure and reflect fracture healing with a time lag due to delayed fracture mineralization following increases in stiffness. Since union problems frequently occur after fractures, better and timelier methods to monitor the healing process are required. In this review, we provide an overview of the changes in gait parameters following lower leg fractures to investigate whether gait analysis can be used to monitor fracture healing. Studies assessing gait after lower leg fractures that were treated either surgically or conservatively were included. Spatiotemporal gait parameters, kinematics, kinetics, and pedography showed improvements in the gait pattern throughout the healing process of lower leg fractures. Especially gait speed and asymmetry measures have a high potential to monitor fracture healing. Pedographic measurements showed differences in gait between patients with and without union. No literature was available for other gait measures, but it is expected that further parameters reflect progress in bone healing. In conclusion, gait analysis seems to be a valuable tool for monitoring the healing process and predicting the occurrence of non-union of lower leg fractures

Do changes in middle-distance running kinematics contribute to the age-related decline in performance?

OBJECTIVES:The aim of this study was to assess ageing-related changes in middle-distance running kinematics and performance in master athletes. METHODS:Male athletes (n=157; 57±13.3 years) competing in the 800- and 1500-m runs at the German Master Athletics Outdoor Championships 2018 were filmed and the bending-over angle, brake angle, leg-stiffness angle, propulsion angle and hip-flexion angle measured. RESULTS:Leg-stiffness and propulsion angle decreased with age (all p<.001), while bending-over, brake and hip-flexion angle increased (all p<.001). Bending-over, propulsion and hip-flexion angles were smaller in 800- than 1500-m races, while the brake angle was larger in 800- than 1500-m races (all p<.001), with no significant difference in leg-stiffness angle between disciplines. In the last round, hip flexion was lower compared to earlier rounds in both distances (p<.001). Age was the major predictor for performance in both races (800-m Radj2=0.74; p<.001, 1500-m Radj2=0.80; p<.001), with a minor impact of technique (improved Radj2 to 0.84 and 0.86, respectively). CONCLUSIONS:The study revealed that the ageing-related decline in running performance of master athletes was primarily explicable by age with only a small contribution of changes in sprint kinematics

Learning from machine learning: prediction of age-related athletic performance decline trajectories

Factors that determine individual age-related decline rates in physical performance are poorly understood and prediction poses a challenge. Linear and quadratic regression models are usually applied, but often show high prediction errors for individual athletes. Machine learning approaches may deliver more accurate predictions and help to identify factors that determine performance decline rates. We hypothesized that it is possible to predict the performance development of a master athlete from a single measurement, that prediction by a machine learning approach is superior to prediction by the average decline curve or an individually shifted decline curve, and that athletes with a higher starting performance show a slower performance decline than those with a lower performance. The machine learning approach was implemented using a multilayer neuronal network. Results showed that performance prediction from a single measurement is possible and that the prediction by a machine learning approach was superior to the other models. The estimated performance decline rate was highest in athletes with a high starting performance and a low starting age, as well as in those with a low starting performance and high starting age, while the lowest decline rate was found for athletes with a high starting performance and a high starting age. Machine learning was superior and predicted trajectories with significantly lower prediction errors compared to conventional approaches. New insights into factors determining decline trajectories were identified by visualization of the model outputs. Machine learning models may be useful in revealing unknown factors that determine the age-related performance decline

Figure skating: Increasing numbers of revolutions in jumps at the European and World Championships

Figure skating is associated with a high prevalence of sport-specific injuries and overuse symptoms. Impacts are of greater magnitude in jumps with more revolutions that are thus connected to a greater risk of injury. While figure skating programs seem to have recently increased in difficulty, performance trends have not yet been reported in the literature. We hypothesized increasing performance and decreasing age trends of the best athletes who competed at international level in recent years. Furthermore, we aimed to identify and analyse objective performance parameters and to assess a potential link between age and the risk of injury. The development of the number of double, triple and quadruple jumps in the singles figure skating events at the World and European Championships since the introduction of the new ISU Judging System in the 2004/2005 season was analysed using regression statistics and Student's T-Tests. In all groups, the numbers of jumps with fewer rotations significantly decreased in the favour of jumps with more rotations. Women only started to perform jumps with four rotations in 2019. In the men, the number of quadruple jumps increased from an average of less than one to more than three in recent years (European and World Championships, both p < 0.001). In the European, but not in the World Championships, the average age increased in the men and decreased in the women (European Championships, men and women p = 0.006). Our study was the first to assess performance trends in elite figure skating. The incidence of injuries and overuse syndromes in figure skating needs to be monitored cautiously, as increases can be expected following recent gains in performance and jump complexity

Figure skating : Increasing numbers of revolutions in jumps at the European and World Championships

Figure skating is associated with a high prevalence of sport-specific injuries and overuse symptoms. Impacts are of greater magnitude in jumps with more revolutions that are thus connected to a greater risk of injury. While figure skating programs seem to have recently increased in difficulty, performance trends have not yet been reported in the literature. We hypothesized increasing performance and decreasing age trends of the best athletes who competed at international level in recent years. Furthermore, we aimed to identify and analyse objective performance parameters and to assess a potential link between age and the risk of injury. The development of the number of double, triple and quadruple jumps in the singles figure skating events at the World and European Championships since the introduction of the new ISU Judging System in the 2004/2005 season was analysed using regression statistics and Student’s T-Tests. In all groups, the numbers of jumps with fewer rotations significantly decreased in the favour of jumps with more rotations. Women only started to perform jumps with four rotations in 2019. In the men, the number of quadruple jumps increased from an average of less than one to more than three in recent years (European and World Championships, both p < 0.001). In the European, but not in the World Championships, the average age increased in the men and decreased in the women (European Championships, men and women p = 0.006). Our study was the first to assess performance trends in elite figure skating. The incidence of injuries and overuse syndromes in figure skating needs to be monitored cautiously, as increases can be expected following recent gains in performance and jump complexity

Learning from machine learning: prediction of age-related athletic performance decline trajectories

Factors that determine individual age-related decline rates in physical performance are poorly understood and prediction poses a challenge. Linear and quadratic regression models are usually applied, but often show high prediction errors for individual athletes. Machine learning approaches may deliver more accurate predictions and help to identify factors that determine performance decline rates. We hypothesized that it is possible to predict the performance development of a master athlete from a single measurement, that prediction by a machine learning approach is superior to prediction by the average decline curve or an individually shifted decline curve, and that athletes with a higher starting performance show a slower performance decline than those with a lower performance. The machine learning approach was implemented using a multilayer neuronal network. Results showed that performance prediction from a single measurement is possible and that the prediction by a machine learning approach was superior to the other models. The estimated performance decline rate was highest in athletes with a high starting performance and a low starting age, as well as in those with a low starting performance and high starting age, while the lowest decline rate was found for athletes with a high starting performance and a high starting age. Machine learning was superior and predicted trajectories with significantly lower prediction errors compared to conventional approaches. New insights into factors determining decline trajectories were identified by visualization of the model outputs. Machine learning models may be useful in revealing unknown factors that determine the age-related performance decline