Relationships Between Internal and External Training Load in Team Sport Athletes: Evidence for an Individualised Approach

Purpose:The aim of this study was to quantify and predict relationships between rating of perceived exertion (RPE) and GPS training-load (TL) variables in professional Australian football (AF) players using group and individualized modeling approaches.Methods:TL data (GPS and RPE) for 41 professional AF players were obtained over a period of 27 wk. A total of 2711 training observations were analyzed with a total of 66 ± 13 sessions/player (range 39–89). Separate generalized estimating equations (GEEs) and artificial-neural-network analyses (ANNs) were conducted to determine the ability to predict RPE from TL variables (ie, session distance, high-speed running [HSR], HSR %, m/min) on a group and individual basis.Results:Prediction error for the individualized ANN (root-mean-square error [RMSE] 1.24 ± 0.41) was lower than the group ANN (RMSE 1.42 ± 0.44), individualized GEE (RMSE 1.58 ± 0.41), and group GEE (RMSE 1.85 ± 0.49). Both the GEE and ANN models determined session distance as the most important predictor of RPE. Furthermore, importance plots generated from the ANN revealed session distance as most predictive of RPE in 36 of the 41 players, whereas HSR was predictive of RPE in just 3 players and m/min was predictive of RPE in just 2 players.Conclusions:This study demonstrates that machine learning approaches may outperform more traditional methodologies with respect to predicting athlete responses to TL. These approaches enable further individualization of load monitoring, leading to more accurate training prescription and evaluation.</jats:sec

The effect of sleep restriction, with or without high-intensity interval exercise, on myofibrillar protein synthesis in healthy young men

© 2020 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society. Key points: Sleep restriction has previously been associated with the loss of muscle mass in both human and animal models. The rate of myofibrillar protein synthesis (MyoPS) is a key variable in regulating skeletal muscle mass and can be increased by performing high-intensity interval exercise (HIIE), although the effect of sleep restriction on MyoPS is unknown. In the present study, we demonstrate that participants undergoing a sleep restriction protocol (five nights, with 4 h in bed each night) had lower rates of skeletal muscle MyoPS; however, rates of MyoPS were maintained at control levels by performing HIIE during this period. Our data suggest that the lower rates of MyoPS in the sleep restriction group may contribute to the detrimental effects of sleep loss on muscle mass and that HIIE may be used as an intervention to counteract these effects. Abstract: The present study aimed to investigate the effect of sleep restriction, with or without high-intensity interval exercise (HIIE), on the potential mechanisms underpinning previously-reported sleep-loss-induced reductions to muscle mass. Twenty-four healthy, young men underwent a protocol consisting of two nights of controlled baseline sleep and a five-night intervention period. Participants were allocated into one of three parallel groups, matched for age, (Formula presented.), body mass index and habitual sleep duration; a normal sleep (NS) group [8 h time in bed (TIB) each night], a sleep restriction (SR) group (4 h TIB each night), and a sleep restriction and exercise group (SR+EX, 4 h TIB each night, with three sessions of HIIE). Deuterium oxide was ingested prior to commencing the study and muscle biopsies obtained pre- and post-intervention were used to assess myofibrillar protein synthesis (MyoPS) and molecular markers of protein synthesis and degradation signalling pathways. MyoPS was lower in the SR group [fractional synthetic rate (% day–1), mean ± SD, 1.24 ± 0.21] compared to both the NS (1.53 ± 0.09) and SR+EX groups (1.61 ± 0.14) (P < 0.05). However, there were no changes in the purported regulators of protein synthesis (i.e. p-AKTser473 and p-mTORser2448) and degradation (i.e. Foxo1/3 mRNA and LC3 protein) in any group. These data suggest that MyoPS is acutely reduced by sleep restriction, although MyoPS can be maintained by performing HIIE. These findings may explain the sleep-loss-induced reductions in muscle mass previously reported and also highlight the potential therapeutic benefit of HIIE to maintain myofibrillar remodelling in this context

The effect of sleep restriction, with or without high-intensity interval exercise, on behavioural alertness and mood state in young healthy males

Mood state and alertness are negatively affected by sleep loss, and can be positively influenced by exercise. However, the potential mitigating effects of exercise on sleep-loss-induced changes in mood state and alertness have not been studied comprehensively. Twenty-four healthy young males were matched into one of three, 5-night sleep interventions: normal sleep (NS; total sleep time (TST) per night = 449 ± 22 min), sleep restriction (SR; TST = 230 ± 5 min), or sleep restriction and exercise (SR + EX; TST = 235 ± 5 min, plus three sessions of high-intensity interval exercise (HIIE)). Mood state was assessed using the profile of mood states (POMS) and a daily well-being questionnaire. Alertness was assessed using psychomotor vigilance testing (PVT). Following the intervention, POMS total mood disturbance scores significantly increased for both the SR and SR + EX groups, and were greater than the NS group (SR vs NS; 31.0 ± 10.7 A.U., [4.4–57.7 A.U.], p = 0.020; SR + EX vs NS; 38.6 ± 14.9 A.U., [11.1–66.1 A.U.], p = 0.004). The PVT reaction times increased in the SR (p = 0.049) and SR + EX groups (p = 0.033) and the daily well-being questionnaire revealed increased levels of fatigue in both groups (SR; p = 0.041, SR + EX; p = 0.026) during the intervention. Despite previously demonstrated physiological benefits of performing three sessions of HIIE during five nights of sleep restriction, the detriments to mood, wellness, and alertness were not mitigated by exercise in this study. Whether alternatively timed exercise sessions or other exercise protocols could promote more positive outcomes on these factors during sleep restriction requires further research

Exercise mitigates sleep-loss-induced changes in glucose tolerance, mitochondrial function, sarcoplasmic protein synthesis, and diurnal rhythms

Objective Sleep loss has emerged as a risk factor for the development of impaired glucose tolerance. The mechanisms underpinning this observation are unknown; however, both mitochondrial dysfunction and circadian misalignment have been proposed. Because exercise improves glucose tolerance and mitochondrial function, and alters circadian rhythms, we investigated whether exercise may counteract the effects induced by inadequate sleep. Methods To minimize between-group differences of baseline characteristics, 24 healthy young males were allocated into one of the three experimental groups: a Normal Sleep (NS) group (8 h time in bed (TIB) per night, for five nights), a Sleep Restriction (SR) group (4 h TIB per night, for five nights), and a Sleep Restriction and Exercise group (SR+EX) (4 h TIB per night, for five nights and three high-intensity interval exercise (HIIE) sessions). Glucose tolerance, mitochondrial respiratory function, sarcoplasmic protein synthesis (SarcPS), and diurnal measures of peripheral skin temperature were assessed pre- and post-intervention. Results We report that the SR group had reduced glucose tolerance post-intervention (mean change ± SD, P value, SR glucose AUC: 149 ± 115 A.U., P = 0.002), which was also associated with reductions in mitochondrial respiratory function (SR: -15.9 ± 12.4 pmol O2.s−1.mg−1, P = 0.001), a lower rate of SarcPS (FSR%/day SR: 1.11 ± 0.25%, P < 0.001), and reduced amplitude of diurnal rhythms. These effects were not observed when incorporating three sessions of HIIE during this period (SR+EX: glucose AUC 67 ± 57, P = 0.239, mitochondrial respiratory function: 0.6 ± 11.8 pmol O2.s−1.mg−1, P = 0.997, and SarcPS (FSR%/day): 1.77 ± 0.22%, P = 0.971). Conclusions A five-night period of sleep restriction leads to reductions in mitochondrial respiratory function, SarcPS, and amplitude of skin temperature diurnal rhythms, with a concurrent reduction in glucose tolerance. We provide novel data demonstrating that these same detrimental effects are not observed when HIIE is performed during the period of sleep restriction. These data therefore provide evidence in support of the use of HIIE as an intervention to mitigate the detrimental physiological effects of sleep loss

Development of a Kemp\u27s Ridley Sea Turtle Stock Assessment Model

We developed a Kemp’s ridley (Lepidochelys kempii) stock assessment model to evaluate the relative contributions of conservation efforts and other factors toward this critically endangered species’ recovery. The Kemp’s ridley demographic model developed by the Turtle Expert Working Group (TEWG) in 1998 and 2000 and updated for the binational recovery plan in 2011 was modified for use as our base model. The TEWG model uses indices of the annual reproductive population (number of nests) and hatchling recruitment to predict future annual numbers of nests on the basis of a series of assumptions regarding age and maturity, remigration interval, sex ratios, nests per female, juvenile mortality, and a putative ‘‘turtle excluder device effect’’ multiplier starting in 1990. This multiplier was necessary to fit the number of nests observed in 1990 and later. We added the effects of shrimping effort directly, modified by habitat weightings, as a proxy for all sources of anthropogenic mortality. Additional data included in our model were incremental growth of Kemp’s ridleys marked and recaptured in the Gulf of Mexico, and the length frequency of stranded Kemp’s ridleys. We also added a 2010 mortality factor that was necessary to fit the number of nests for 2010 and later (2011 and 2012). Last, we used an empirical basis for estimating natural mortality, on the basis of a Lorenzen mortality curve and growth estimates. Although our model generated reasonable estimates of annual total turtle deaths attributable to shrimp trawling, as well as additional deaths due to undetermined anthropogenic causes in 2010, we were unable to provide a clear explanation for the observed increase in the number of stranded Kemp’s ridleys in recent years, and subsequent disruption of the species’ exponential growth since the 2009 nesting season. Our consensus is that expanded data collection at the nesting beaches is needed and of high priority, and that 2015 be targeted for the next stock assessment to evaluate the 2010 event using more recent nesting and in-water data

Uncovering the influence of sleep in recovery, training and team-sport competition

There is an emerging consensus that sleep is an important part of the post-exercise recovery process for athletes. Evidence suggests that a lack of sleep, or sleep of poor quality, can negatively influence markers of physical, physiological, and perceptual recovery that may impact the subsequent training and performance outcomes of athletes. Moreover, recent findings suggest that increasing total sleep time can improve performance, yet comprehensive evidence is lacking. This has seen an increased focus on the investigation of the sleep behaviours of athlete populations; however, this research often does not consider many important contextual factors, such as the physical sleep environment, competition factors including location, travel and timing, and training-related factors like periodisation and training load exposure. Furthermore, little is known about the physical and physiological influences of sleep on the post-exercise recovery process, and information regarding the amount of sleep that is required to maximise recovery and athletic performance is lacking. The aim of the first study in this thesis was to investigate the influence of physical sleep environment during a pre-season training camp on the sleep behaviours of professional Australian Rules footballers. The results of Study 1 (Chapter 4) describe the sleep behaviours of professional Australian Rules footballers between the home environment and a pre-season camp environment, both during the pre-season training period. Australian Rules footballers went to bed and woke earlier when on camp, spending longer in bed without a significant increase in sleep duration, caused by significantly increased wake after sleep onset. Relative changes to time in bed and wake after sleep onset on camp had a strong negative correlation with absolute home values, suggesting those who spend longer time in bed at home are more likely to experience reduced time in bed in the camp environment. Although there was no significant change in total session rating of perceived exertion (s-RPE) training load, when accounting for daily variations of within-player s-RPE load, both increased and decreased s-RPE load had weak correlations with changes in total sleep time in the home environment. Comparatively, in the camp environment, decreases in s-RPE load displayed a moderate positive relationship with total sleep time, whereas increases in s-RPE load displayed moderate negative correlation with total sleep time. However, daily ambient temperature was ~5°C hotter during the camp environment, compared to the normal home environment, which may have influenced results. A change in physical sleep environment, without external influences such as circadian phase-shifting, altered training schedules or increased total training load reduces the quality of sleep and effects the attainment of increased duration of sleep, despite spending longer periods of time in bed. Furthermore, the individual variation in response to a change in environment stresses the importance of assessing sleep on a case-by-case basis, especially if assessment leads to the provision of interventions designed at improving the sleep of athletes during time spent in unfamiliar physical sleeping environments. The aim of the second study in this thesis was to investigate the role that individual contextual factors (age and chronotype) and environmental factors (competitive matches, competition level, and competition location) have on the sleep behaviours across the pre-season and in-season periods in professional Australian Rules footballers. Study 2 (Chapter 5) found that the individual-specific factor chronotype influences the sleep behaviours of Australian Rules footballers. Furthermore, players went to bed and woke later, resulting in increased time in bed and total sleep time, during the in-season compared to the pre-season. On the night before a match, and the two nights following a match, players spent longer in bed and obtained more sleep compared to the pre-season. In contrast, on match nights players spent less time in bed and obtained less sleep, compared to the night before and the two nights following a match; but obtained similar sleep durations on match nights to during the pre-season. No differences in sleep behaviours were observed between matches played at home or away; however, time in bed and sleep duration were reduced following National-level competition, compared to State-level competition. Collectively, these results suggest that individual chronotype needs to be considered in the evaluation of athlete sleep behaviours, and that sleep behaviours vary between season phases, nights surrounding competition, and between competitive levels. The aim of the third study in this thesis was to determine the influence of changes in load variables during both the pre-season and in-season across 1-, 7-, 14-, 21- and 28-day periods and their relationships with objectively measured sleep behaviours in Australian Rules footballers. Study 3 (Chapter 6) found that same-day increases in volume (total distance and s-RPE) and intensity (relative total distance, high-speed running and very high-speed running) have negative associations with sleep behaviours during both the pre-season and in-season. Cumulative 7-day loads during the pre-season have minimal associations with sleep behaviours, whereas sleep duration was negatively associated with higher 7-day cumulative loads during the in-season period. Increased load measures detrimentally influence sleep behaviours over 14-day, 21-day and 28-day cumulative periods during the in-season. These results suggest that heightened short- and long-term exposure to increased loads have a negative effect on the sleep behaviours of Australian Rules footballers. Therefore, consideration of both the acute and cumulative demands of training and competition should be made in the context of monitoring of Australian Rules footballers sleep. The aim of the fourth study in this thesis was to determine the effect of a single night of sleep extension on physiological, physical, and perceptual recovery. Study 4 (Chapter 7) found that whilst the novel high-intensity intermittent exercise session induced similar post-exercise responses to that of team-sport competition, a single night of increased sleep duration (sleep extension) did not influence markers of neuromuscular, autonomic, perceptual, and hormonal function and status on the morning following a session of high-intensity interval exercise under laboratory-controlled conditions. Longer periods of sleep-intervention may be required to have a beneficial effect on markers of recovery and function following exercise. Finally, the aim of the fifth study in this thesis was to determine the effects of multiple days of post-exercise sleep extension (where a total of 10 h per day for 3 days was obtained) on the status of physiological, physical, and perceptual recovery and physical performance. Study 5 (Chapter 8) found that 2-hour afternoon naps (following 8 h of sleep each night) improves the recovery rate of neuromuscular function. Furthermore, both overnight sleep extension (10 h) and afternoon naps improved the recovery of sprint performance following a session of high-intensity interval eercise that was followed by a night comprised of a 6-hour sleep. Overnight sleep extension appears to enhance recovery of perceptual wellbeing measures after, compared to afternoon naps. These results suggest that both overnight extension and afternoon naps have a postive influence on post-exercise recovery. However, caution should be exercised, as afternoon naps may increase sleep onset latency and wake after sleep onset, and reduce sleep efficiency of subsequent night sleep when performed on consecutive days

Effects of a 2-Week High-Intensity Training Camp on Sleep Activity of Professional Rugby League Athletes

Purpose: To investigate the effects of a training camp on the sleep characteristics of professional rugby league players compared with a home period. Methods: During a 7-d home and 13-d camp period, time in bed (TIB), total sleep time (TST), sleep efficiency (SE), and wake after sleep onset were measured using wristwatch actigraphy. Subjective wellness and training loads (TL) were also collected. Differences in sleep and TL between the 2 periods and the effect of daytime naps on nighttime sleep were examined using linear mixed models. Pearson correlations assessed the relationship of changes in TL on individuals’ TST. Results: During the training camp, TST (–85 min), TIB (–53 min), and SE (–8%) were reduced compared with home. Those who undertook daytime naps showed increased TIB (+33 min), TST (+30 min), and SE (+0.9%). Increases in daily total distance and training duration above individual baseline means during the training camp shared moderate (r = –.31) and trivial (r = –.04) negative relationships with TST. Conclusions: Sleep quality and quantity may be compromised during training camps; however, daytime naps may be beneficial for athletes due to their known benefits, without being detrimental to nighttime sleep

The impact of self-reported sleep quantity on perceived decision-making in sports officials during a competitive season

Objectives: While sleep research in athletes is extensive, no research has investigated sleep in sports officials during a competitive season. This study explored the (a) self-reported quantity and quality of sleep obtained by sports officials according to the time of competition (day or evening) and (b) impact of reduced sleep on perceived decision-making ability. Design: Sports officials (n = 371) from various sporting codes completed an online questionnaire that evaluated self-reported sleep quantity and quality on habitual nights, before competition, and after competition, as well as perceived decision-making constructs. Results: With sleep restriction defined as less than 7 h of sleep, mixed-effects logistic regression revealed that the estimated probability of reporting reduced sleep quantity increased (p< .05) on habitual nights (0.58), before competition (0.48), and after competition (0.56). The estimated probability of reporting poor sleep quality was 0.01-0.04 across all nights. When considering time of competition (day or evening), reduced sleep quantity was experienced after evening competition (odds ratio [OR] = 3.33, p < .05), while poorer sleep quality (p< .05) was experienced following day (OR = 2.1) and evening (OR = 12.46) competition compared to habitual nights. Furthermore, the impact of reduced sleep on perceived decision-making constructs was negative, with the estimated probability of reporting impaired perceived decision-making between 0.13 and 0.21. Conclusion: Overall, sports officials are vulnerable to reduced quantity and quality of sleep before and after competition, with impaired perceived decision-making ability following nights of less than average sleep

Pulse-level noisy quantum circuits with QuTiP

The study of the impact of noise on quantum circuits is especially relevant to guide the progress of Noisy IntermediateScale Quantum (NISQ) computing. In this paper, we address the pulse-level simulation of noisy quantum circuits with the Quantum Toolbox in Python (QuTiP). We introduce new tools in qutip-qip, QuTiP’s quantum information processing package.These tools simulate quantum circuits at the pulse level, leveraging QuTiP’s quantum dynamics solvers and control optimization features. We show how quantum circuits can be compiled on simulated processors, with control pulses acting on a target Hamiltonian that describes the unitary evolution of the physical qubits. Various types of noise can be introduced based on the physical model, e.g., by simulating the Lindblad densitymatrix dynamics or Monte Carlo quantum trajectories. In particular, the user can define environment induced decoherence at the processor level and include noise simulation at the level of control pulses. We illustrate how the DeutschJozsa algorithm is compiled and executed on a superconducting-qubit-based processor, on a spin-chain-based processor and using control optimization algorithms. We also show how to easily reproduce experimental results on cross-talk noise in an ion-based processor, and how a Ramsey experiment can be modeled with Lindblad dynamics. Finally, we illustrate how to integrate these features with other software frameworks