Measurement of B(/\c->pKpi)

The /\c->pKpi yield has been measured in a sample of two-jet continuum events containing a both an anticharm tag (Dbar) as well as an antiproton (e+e- -> Dbar pbar X), with the antiproton in the hemisphere opposite the Dbar. Under the hypothesis that such selection criteria tag e+e- -> Dbar pbar (/\c) X events, the /\c->pkpi branching fraction can be determined by measuring the pkpi yield in the same hemisphere as the antiprotons in our Dbar pbar X sample. Combining our results from three independent types of anticharm tags, we obtain B(/\c->pKpi)=(5.0+/-0.5+/-1.2)

Medical encounters at community-based physical activity events (parkrun) in the UK

Objective: To determine the incidence, clinical correlates and exposure risk of medical encounters during community-based physical activity events in the UK. // Methods: An analysis of medical data from weekly, community-based physical activity events (parkrun) at 702 UK locations over a 6-year period (29 476 294 participations between 2014 and 2019) was conducted in order to define the incidence and clinical correlates of serious life-threatening, non-life-threatening and fatal medical encounters. // Results: 84 serious life-threatening encounters (overall incidence rate=0.26/100 000 participations) occurred including 18 fatalities (0.056/100 000 participations). Statistical modelling revealed that the probabilities of serious life-threatening encounters were exceptionally low, however, male sex, increasing age, slower personal best parkrun time and less prior running engagement/experience (average number of runs per year and number of years as a parkrun participant) were associated with increased probability of serious life-threatening encounters. These were largely accounted for by cardiac arrest (48/84, 57%) and acute coronary syndromes (20/84, 24%). Non-life-threatening medical encounters were mainly attributed to tripping or falling, with a reported incidence of 39.2/100 000 participations. // Conclusions: Serious life-threatening and fatal medical encounters associated with parkrun participation are extremely rare. In the context of a global public health crisis due to inactivity, this finding underscores the safety and corollary public health value of community running/walking events as a strategy to promote physical activity

Genetic Polymorphisms Related to VO2max Adaptation Are Associated With Elite Rugby Union Status and Competitive Marathon Performance

PURPOSE: Genetic polymorphisms have been associated with the adaptation to training in maximal oxygen uptake (V˙O2max). However, the genotype distribution of selected polymorphisms in athletic cohorts is unknown, with their influence on performance characteristics also undetermined. This study investigated whether the genotype distributions of 3 polymorphisms previously associated with V˙O2max training adaptation are associated with elite athlete status and performance characteristics in runners and rugby athletes, competitors for whom aerobic metabolism is important. METHODS: Genomic DNA was collected from 732 men including 165 long-distance runners, 212 elite rugby union athletes, and 355 nonathletes. Genotype and allele frequencies of PRDM1 rs10499043 C/T, GRIN3A rs1535628 G/A, and KCNH8 rs4973706 T/C were compared between athletes and nonathletes. Personal-best marathon times in runners, as well as in-game performance variables and playing position, of rugby athletes were analyzed according to genotype. RESULTS: Runners with PRDM1 T alleles recorded marathon times ∼3 minutes faster than CC homozygotes (02:27:55 [00:07:32] h vs 02:31:03 [00:08:24] h, P = .023). Rugby athletes had 1.57 times greater odds of possessing the KCNH8 TT genotype than nonathletes (65.5% vs 54.7%, χ2 = 6.494, P = .013). No other associations were identified. CONCLUSIONS: This study is the first to demonstrate that polymorphisms previously associated with V˙O2max training adaptations in nonathletes are also associated with marathon performance (PRDM1) and elite rugby union status (KCNH8). The genotypes and alleles previously associated with superior endurance-training adaptation appear to be advantageous in long-distance running and achieving elite status in rugby union

ACTN3 R577x genotype is not associated with elite european caucasian marathon performance

Objectives A common nonsense polymorphism (R577X) in the ACTN3 (α-actinin-3 protein) has been associated with elite athlete status previously. Specifically, the X allele has been positively associated with elite endurance status, however, this remains inconclusive due to contradictory reports within the literature. Thus, the current study aimed to compare ACTN3 R577X genotype and allele frequency distributions in ‘elite’ and ‘sub-elite’ marathon runners with those of a non-athletic, control population and to determine whether marathon personal best time was associated with ACTN3 R577X genotype.Method Four hundred and eighty four elite and sub-elite European Caucasian marathon runners and 554 ethnically matched controls provided a DNA sample from which the ACTN3 R577X polymorphism was genotyped using real-time PCR. Personal best (PB) times were used to determine elite (men < 2 h 30 min, n = 111; women < 3 h 00 min, n = 105) or sub-elite (men 2 h 30 min – 2 h 45 min, n = 189; women 3 h 00 min – 3 h 15 min, n = 79) status. Genotype and allele frequencies were compared between athletes and controls using Chi-square analyses. One-way ANOVAs were implemented to identify any genotype-dependent differences in PB times for men and women, which were subject to correction for multiple comparisons.Results The X allele was ∼3% more frequent in the marathon runners than in non-athlete controls (see Table 1 and Figure 1), although this small difference did not approach statistical significance. There were no significant differences in genotype (χ2 = 3.40; P = 0.182) or allele (χ2 = 2.31; P = 0.128) frequency distributions between athletes (RR = 29.1%, RX = 50.6% XX = 20.2%; R = 54.4%, X = 45.6%) and controls. There were also no differences between elite and sub-elite genotype (P = 0.968, χ2 = 0.66) and allele frequencies (P = 0.916, χ2 = 0.11). Similarly, no differences in genotype or allele frequencies were found between either elite (P = 0.439, χ2 = 1.65; P = 0.265, χ2 = 1.24) or sub-elite (P = 0.254, χ2 = 2.74; P = 0.183, χ2 = 1.77) runners and the control group. Neither were PB times genotype-dependent for either men (P = 0.864) or women (P = 0.966).Conclusion No differences in genotype and allele frequencies were observed between athletes and controls, elite vs sub-elite, nor elite and sub-elite comparisons with the control group. Additionally, there was no genotype-dependent influence on PB time, which further emphasises that the ACTN3 R577X polymorphism does not influence elite endurance athlete status or determine marathon performance in European Caucasian runners. This is congruent with some previous findings and suggests other genetic variants or environmental factors may play a more prominent role in achieving elite endurance athlete status

Does Relative Energy Deficiency in Sport (REDs) Syndrome Exist?

Relative energy deficiency in sport (REDs) is a widely adopted model, originally proposed by an International Olympic Committee (IOC) expert panel in 2014 and recently updated in an IOC 2023 consensus statement. The model describes how low energy availability (LEA) causes a wide range of deleterious health and performance outcomes in athletes. With increasing frequency, sports practitioners are diagnosing athletes with “REDs,” or “REDs syndrome,” based largely upon symptom presentation. The purpose of this review is not to “debunk” REDs but to challenge dogmas and encourage rigorous scientific processes. We critically discuss the REDs concept and existing empirical evidence available to support the model. The consensus (IOC 2023) is that energy availability, which is at the core of REDs syndrome, is impossible to measure accurately enough in the field, and therefore, the only way to diagnose an athlete with REDs appears to be by studying symptom presentation and risk factors. However, the symptoms are rather generic, and the causes likely multifactorial. Here we discuss that (1) it is very difficult to isolate the effects of LEA from other potential causes of the same symptoms (in the laboratory but even more so in the field); (2) the model is grounded in the idea that one factor causes symptoms rather than a combination of factors adding up to the etiology. For example, the model does not allow for high allostatic load (psychophysiological “wear and tear”) to explain the symptoms; (3) the REDs diagnosis is by definition biased because one is trying to prove that the correct diagnosis is REDs, by excluding other potential causes (referred to as differential diagnosis, although a differential diagnosis is supposed to find the cause, not demonstrate that it is a pre-determined cause); (4) observational/cross-sectional studies have typically been short duration (< 7 days) and do not address the long term “problematic LEA,” as described in the IOC 2023 consensus statement; and (5) the evidence is not as convincing as it is sometimes believed to be (i.e., many practitioners believe REDs is well established). Very few studies can demonstrate causality between LEA and symptoms, most studies demonstrate associations and there is a worrying number of (narrative) reviews on the topic, relative to original research. Here we suggest that the athlete is best served by an unbiased approach that places health at the center, leaving open all possible explanations for the presented symptoms. Practitioners could use a checklist that addresses eight categories of potential causes and involve the relevant experts if and when needed. The Athlete Health and Readiness Checklist (AHaRC) we introduce here simply consists of tools that have already been developed by various expert/consensus statements to monitor and troubleshoot aspects of athlete health and performance issues. Isolating the purported effects of LEA from the myriad of other potential causes of REDs symptoms is experimentally challenging. This renders the REDs model somewhat immune to falsification and we may never definitively answer the question, “does REDs syndrome exist?” From a practical point of view, it is not necessary to isolate LEA as a cause because all potential areas of health and performance improvement should be identified and tackled

Collagen Gene Polymorphisms Previously Associated with Resistance to Soft-Tissue Injury Are More Common in Competitive Runners Than Nonathletes

Dines, HR, Nixon, J, Lockey, SJ, Herbert, AJ, Kipps, C, Pedlar, CR, Day, SH, Heffernan, SM, Antrobus, MR, Brazier, J, Erskine, RM, Stebbings, GK, Hall, ECR, and Williams, AG. Collagen gene polymorphisms previously associated with resistance to soft-tissue injury are more common in competitive runners than nonathletes. J Strength Cond Res XX(X): 000-000, 2022-Single-nucleotide polymorphisms (SNPs) of collagen genes have been associated with soft-tissue injury and running performance. However, their combined contribution to running performance is unknown. We investigated the association of 2 collagen gene SNPs with athlete status and performance in 1,429 Caucasian subjects, including 597 competitive runners (354 men and 243 women) and 832 nonathletes (490 men and 342 women). Genotyping for COL1A1 rs1800012 (C > A) and COL5A1 rs12722 (C > T) SNPs was performed by a real-time polymerase chain reaction. The numbers of "injury-resistant" alleles from each SNP, based on previous literature (rs1800012 A allele and rs12722 C allele), were combined as an injury-resistance score (RScore, 0-4; higher scores indicate injury resistance). Genotype frequencies, individually and combined as an RScore, were compared between cohorts and investigated for associations with performance using official race times. Runners had 1.34 times greater odds of being rs12722 CC homozygotes than nonathletes (19.7% vs. 15.5%, p = 0.020) with no difference in the rs1800012 genotype distribution (p = 0.659). Fewer runners had an RScore 0 of (18.5% vs. 24.7%) and more had an RScore of 4 (0.6% vs. 0.3%) than nonathletes (p < 0.001). Competitive performance was not associated with the COL1A1 genotype (p = 0.933), COL5A1 genotype (p = 0.613), or RScore (p = 0.477). Although not associated directly with running performance among competitive runners, a higher combined frequency of injury-resistant COL1A1 rs1800012 A and COL5A1 rs12722 C alleles in competitive runners than nonathletes suggests these SNPs may be advantageous through a mechanism that supports, but does not directly enhance, running performance

Genetic Polymorphisms Related to Vo2max Adaptation are Associated with Elite Rugby Union Status and Competitive Marathon Performance

Purpose: Genetic polymorphisms have been associated with the adaptation to training in maximal oxygen uptake (V̇O2max). However, the genotype distribution of selected polymorphisms in athletic cohorts is unknown, with their influence on performance characteristics also undetermined. This study investigated whether the genotype distributions of three polymorphisms previously associated with V̇O2max training adaptation are associated with elite athlete status and performance characteristics in runners and rugby athletes, competitors for whom aerobic metabolism is important. Methods: Genomic DNA was collected from 732 men, including 165 long-distance runners, 212 elite rugby union athletes and 355 non-athletes. Genotype and allele frequencies of PRDM1 rs10499043 C/T, GRIN3A rs1535628 G/A and KCNH8 rs4973706 T/C were compared between athletes and non-athletes. Personal best marathon times in runners, as well as in-game performance variables and playing position of rugby athletes, were analysed according to genotype. Results: Runners with PRDM1 T alleles recorded marathon times ~3 min faster than CC homozygotes (02:27:55 ± 00:07:32 h vs. 02:31:03 ± 00:08:24 h, p = 0.023). Rugby athletes had 1.57 times greater odds of possessing the KCNH8 TT genotype than non-athletes (65.5% vs. 54.7%, χ2 = 6.494, p = 0.013). No other associations were identified. Conclusions: This study is the first to demonstrate that polymorphisms previously associated with V̇O2max training adaptations in non-athletes are also associated with marathon performance (PRDM1) and elite rugby union status (KCNH8). The genotypes and alleles previously associated with superior endurance training adaptation appear to be advantageous in long-distance running and achieving elite status in rugby union

Collagen Gene Polymorphisms Previously Associated with Resistance to Soft-Tissue Injury Are More Common in Competitive Runners Than Nonathletes

Single-nucleotide polymorphisms (SNPs) of collagen genes have been associated with soft-tissue injury and running performance. However, their combined contribution to running performance is unknown. We investigated the association of 2 collagen gene SNPs with athlete status and performance in 1,429 Caucasian subjects, including 597 competitive runners (354 men and 243 women) and 832 nonathletes (490 men and 342 women). Genotyping for COL1A1 rs1800012 (C > A) and COL5A1 rs12722 (C > T) SNPs was performed by a real-time polymerase chain reaction. The numbers of “injury-resistant” alleles from each SNP, based on previous literature (rs1800012 A allele and rs12722 C allele), were combined as an injury-resistance score (RScore, 0–4; higher scores indicate injury resistance). Genotype frequencies, individually and combined as an RScore, were compared between cohorts and investigated for associations with performance using official race times. Runners had 1.34 times greater odds of being rs12722 CC homozygotes than nonathletes (19.7% vs. 15.5%, p = 0.020) with no difference in the rs1800012 genotype distribution (p = 0.659). Fewer runners had an RScore 0 of (18.5% vs. 24.7%) and more had an RScore of 4 (0.6% vs. 0.3%) than nonathletes (p < 0.001). Competitive performance was not associated with the COL1A1 genotype (p = 0.933), COL5A1 genotype (p = 0.613), or RScore (p = 0.477). Although not associated directly with running performance among competitive runners, a higher combined frequency of injury-resistant COL1A1 rs1800012 A and COL5A1 rs12722 C alleles in competitive runners than nonathletes suggests these SNPs may be advantageous through a mechanism that supports, but does not directly enhance, running performance

Autoregulation in resistance training : addressing the inconsistencies

Autoregulation is a process that is used to manipulate training based primarily on the measurement of an individual's performance or their perceived capability to perform. Despite being established as a training framework since the 1940s, there has been limited systematic research investigating its broad utility. Instead, researchers have focused on disparate practices that can be considered specific examples of the broader autoregulation training framework. A primary limitation of previous research includes inconsistent use of key terminology (e.g., adaptation, readiness, fatigue, and response) and associated ambiguity of how to implement different autoregulation strategies. Crucially, this ambiguity in terminology and failure to provide a holistic overview of autoregulation limits the synthesis of existing research findings and their dissemination to practitioners working in both performance and health contexts. Therefore, the purpose of the current review was threefold: first, we provide a broad overview of various autoregulation strategies and their development in both research and practice whilst highlighting the inconsistencies in definitions and terminology that currently exist. Second, we present an overarching conceptual framework that can be used to generate operational definitions and contextualise autoregulation within broader training theory. Finally, we show how previous definitions of autoregulation fit within the proposed framework and provide specific examples of how common practices may be viewed, highlighting their individual subtleties