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Pathogens such as severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), influenza, and rhinoviruses are transmitted by airborne aerosol respiratory particles that are exhaled by infectious subjects. We have previously reported that the emission of aerosol particles increases on average 132-fold from rest to maximal endurance exercise. The aims of this study are to first measure aerosol particle emission during an isokinetic resistance exercise at 80% of the maximal voluntary contraction until exhaustion, second to compare aerosol particle emission during a typical spinning class session versus a three-set resistance training session. Finally, we then used this data to calculate the risk of infection during endurance and resistance exercise sessions with different mitigation strategies. During a set of isokinetic resistance exercise, aerosol particle emission increased 10-fold from 5,400 ± 1,200 particles/min at rest to 59,000 ± 69,900 particles/min during a set of resistance exercise. We found that aerosol particle emission per minute is on average 4.9-times lower during a resistance training session than during a spinning class. Using this data, we determined that the simulated infection risk increase during an endurance exercise session was sixfold higher than during a resistance exercise session when assuming one infected participant in the class. Collectively, this data helps to select mitigation measures for indoor resistance and endurance exercise classes at times where the risk of aerosol-transmitted infectious disease with severe outcomes is high.

Exercise improves the insulin sensitivity of glucose uptake in skeletal muscle. Due to that, exercise has become a cornerstone treatment for type 2 diabetes mellitus (T2DM). The mechanisms by which exercise improves skeletal muscle insulin sensitivity are, however, incompletely understood. We conducted a systematic review to identify all genes whose gain or loss of function alters skeletal muscle glucose uptake. We subsequently cross-referenced these genes with recently generated data sets on exercise-induced gene expression and signaling. Our search revealed 176 muscle glucose-uptake genes, meaning that their genetic manipulation altered glucose uptake in skeletal muscle. Notably, exercise regulates the expression or phosphorylation of more than 50% of the glucose-uptake genes or their protein products. This included many genes that previously have not been associated with exercise-induced insulin sensitivity. Interestingly, endurance and resistance exercise triggered some common but mostly unique changes in expression and phosphorylation of glucose-uptake genes or their protein products. Collectively, our work provides a resource of potentially new molecular effectors that play a role in the incompletely understood regulation of muscle insulin sensitivity by exercise., (© 2021 The Authors. Journal of Cellular Biochemistry published by Wiley Periodicals LLC.)

A training plan, or an exercise prescription, is the point where we translate sport and exercise science into practice. As in medicine, good practice requires writing a training plan or prescribing an exercise programme based on the best current scientific evidence. A key issue, however, is that a training plan or exercise prescription is typically a mix of many interacting interventions (e.g. exercises and nutritional recommendations) that additionally change over time due to periodisation or tapering. Thus, it is virtually impossible to base a complex long-term training plan fully on scientific evidence. We, therefore, speak of evidence-informed training plans and exercise prescriptions to highlight that only some of the underlying decisions are made using an evidence-based decision approach. Another challenge is that the adaptation to a given, e.g. endurance or resistance training programme is often highly variable. Until biomarkers for trainability are identified, we must therefore continue to test athletes, clients, or patients, and monitor training variables via a training log to determine whether an individual sufficiently responds to a training intervention or else re-plan. Based on these ideas, we propose a subjective, pragmatic six-step approach that details how to write a training plan or exercise prescription that is partially based on scientific evidence. Finally, we advocate an athlete, client and patient-centered approach whereby an individual's needs and abilities are the main consideration behind all decision-making. This implies that sometimes the most effective form of training is eschewed if the athlete, client or patient has other wishes., (© 2021. The Author(s).)

Nearly 100 years ago, Otto Warburg investigated the metabolism of growing tissues and discovered that tumors reprogram their metabolism. It is poorly understood whether and how hypertrophying muscle, another growing tissue, reprograms its metabolism too. Here, we studied pyruvate kinase muscle (PKM), which can be spliced into two isoforms (PKM1, PKM2). This is of interest, because PKM2 redirects glycolytic flux towards biosynthetic pathways, which might contribute to muscle hypertrophy too. We first investigated whether resistance exercise changes PKM isoform expression in growing human skeletal muscle and found that PKM2 abundance increases after six weeks of resistance training, whereas PKM1 decreases. Second, we determined that Pkm2 expression is higher in fast compared to slow fiber types in rat skeletal muscle. Third, by inducing hypertrophy in differentiated C2C12 cells and by selectively silencing Pkm1 and/or Pkm2 with siRNA, we found that PKM2 limits myotube growth. We conclude that PKM2 contributes to hypertrophy in C2C12 myotubes and indicates a changed metabolic environment within hypertrophying human skeletal muscle fibers. PKM2 is preferentially expressed in fast muscle fibers and may partly contribute to the increased potential for hypertrophy in fast fibers.

One of the most striking adaptations to exercise is the skeletal muscle hypertrophy that occurs in response to resistance exercise. A large body of work shows that a mammalian target of rapamycin complex 1 (mTORC1)-mediated increase of muscle protein synthesis is the key, but not sole, mechanism by which resistance exercise causes muscle hypertrophy. While much of the hypertrophy signaling cascade has been identified, the initiating, resistance exercise-induced and hypertrophy-stimulating stimuli have remained elusive. For the purpose of this review, we define an initiating, resistance exercise-induced and hypertrophy-stimulating signal as "hypertrophy stimulus," and the sensor of such a signal as "hypertrophy sensor." In this review we discuss our current knowledge of specific mechanical stimuli, damage/injury-associated and metabolic stress-associated triggers, as potential hypertrophy stimuli. Mechanical signals are the prime hypertrophy stimuli candidates, and a filamin-C-BAG3-dependent regulation of mTORC1, Hippo, and autophagy signaling is a plausible albeit still incompletely characterized hypertrophy sensor. Other candidate mechanosensing mechanisms are nuclear deformation-initiated signaling or several mechanisms related to costameres, which are the functional equivalents of focal adhesions in other cells. While exercise-induced muscle damage is probably not essential for hypertrophy, it is still unclear whether and how such muscle damage could augment a hypertrophic response. Interventions that combine blood flow restriction and especially low load resistance exercise suggest that resistance exercise-regulated metabolites could be hypertrophy stimuli, but this is based on indirect evidence and metabolite candidates are poorly characterized.

How force development and time under tension (TUT) during resistance exercise (RE) influence anabolic signalling of skeletal muscle is incompletely understood. We hypothesized that high force development during RE is more important for post-exercise-induced signalling than submaximal and fatiguing RE with lower force development but similar TUT. Twenty-two male subjects (24 ± 6 years, 181 ± 9 cm, 79 ± 2 kg) performed three distinct RE modes in the fed state with equal TUT but distinct force output: (i) maximal eccentric RE (ECC, n = 7) three sets, eight reps, 100% eccentric dynamic force; (ii) standard RE (STD, n = 7), three sets, 10 reps, 75% dynamic force; and (iii) high fatiguing single-set RE (HIT, n = 8), 20 reps, 100% eccentric-concentric force; vastus lateralis biopsies were collected at baseline, 15, 30, 60, 240 min and 24 h after RE, and the signalling of mechanosensitive and mammalian target of rapamycin (mTOR)-related proteins was determined. The phosphorylation levels of pFAK(Tyr397), pJNK(Thr183/Tyr185), pAKT(Thr308/Ser473), pmTOR(Ser2448), p4E-BP1(Thr37/46), p70s6k(Thr389)/(Ser421/Thr424) and pS6(Ser235/236) were significantly higher in ECC than those in STD and HIT at several time points (P < 0.01). pJNK(Thr183/Tyr185) and pS6(Ser235/236) levels were significantly higher in type II myofibres in ECC compared with STD and HIT. HIT exerted throughout the weakest signalling response. We conclude that high force development during acute RE is superior for anabolic skeletal muscle signalling than fatiguing RE with lower force output but similar TUT. Our results suggest that this response is substantially driven by the higher activation of type II myofibres during RE.

Ageing, immobilization, sepsis or cachexia reduce muscle mass and function. The age-related loss, i.e. sarcopenia, contributes to frailty and results in a loss of mobility and autonomy in aging and disease. Affected individuals are often socially isolated, have a greater risk of metabolic disorders and psychosomatic problems. As a result, quality of life and life expectancy are affected. Immobilization and lack of adequate stimuli to the skeletal muscle seem to play a central part in these problems. To overcome them, resistance training (i.e., weightlifting) is an effective intervention. Despite the efficacy of resistance training for increasing muscle mass and function, this treatment is underused in clinical practice. We argue that this is due to a lack of a generally applicable methodology. To address this and related problems, we have formed the Network of Expertise for Immobilization-induced Muscle Disorders (KNIMS) to develop a potential algorithm for treating sarcopenia and other immobilization-related muscle disorders. An important aspect of the proposed method is that it is defined as a formal algorithm that consists of two stages. Stage A aims to recover bed-ridden patients' ability to stand by applying vibration-tilt table technology. Stage B aims at rehabilitating compromised gait, using a combination of squats, lunges and single leg raises. It is anticipated that this algorithm-based approach will enhance the ability for standardization and documentation, whilst reducing resource efforts at the same time, which will be equally useful to clinical practice and to clinical research. [ABSTRACT FROM AUTHOR]

Resistance training promotes metabolic health and stimulates muscle hypertrophy, but the precise routes by which resistance exercise (RE) conveys these health benefits are largely unknown. Aim: To investigate how acute RE affects human skeletal muscle metabolism. Methods: We collected vastus lateralis biopsies from six healthy male untrained volunteers at rest, before the first of 13 RE training sessions, and 45 min after the first and last bouts of RE. Biopsies were analysed using untargeted mass spectrometry-based metabolomics. Results: We measured 617 metabolites covering a broad range of metabolic pathways. In the untrained state RE altered 33 metabolites, including increased 3-methylhistidine and N-lactoylvaline, suggesting increased protein breakdown, as well as metabolites linked to ATP (xanthosine) and NAD (N1-methyl-2-pyridone-5-carboxamide) metabolism; the bile acid chenodeoxycholate also increased in response to RE in muscle opposing previous findings in blood. Resistance training led to muscle hypertrophy, with slow type I and fast/intermediate type II muscle fibre diameter increasing by 10.7% and 10.4%, respectively. Comparison of post-exercise metabolite levels between trained and untrained state revealed alterations of 46 metabolites, including decreased N-acetylated ketogenic amino acids and increased beta-citrylglutamate which might support growth. Only five of the metabolites that changed after acute exercise in the untrained state were altered after chronic training, indicating that training induces multiple metabolic changes not directly related to the acute exercise response. Conclusion: The human skeletal muscle metabolome is sensitive towards acute RE in the trained and untrained states and reflects a broad range of adaptive processes in response to repeated stimulation. [ABSTRACT FROM AUTHOR]

Background: Exercise changes the concentrations of many metabolites, which are small molecules (< 1.5 kDa) metabolized by the reactions of human metabolism. In recent years, especially mass spectrometry-based metabolomics methods have allowed researchers to measure up to hundreds of metabolites in a single sample in a non-biased fashion. To summarize human exercise metabolomics studies to date, we conducted a systematic review that reports the results of experiments that found metabolite concentrations changes after a bout of human endurance or resistance exercise. Methods: We carried out a systematic review following PRISMA guidelines and searched for human metabolomics studies that report metabolite concentrations before and within 24 h after endurance or resistance exercise in blood, urine, or sweat. We then displayed metabolites that significantly changed their concentration in at least two experiments. Results: Twenty-seven studies and 57 experiments matched our search criteria and were analyzed. Within these studies, 196 metabolites changed their concentration significantly within 24 h after exercise in at least two experiments. Human biofluids contain mainly unphosphorylated metabolites as the phosphorylation of metabolites such as ATP, glycolytic intermediates, or nucleotides traps these metabolites within cells. Lactate, pyruvate, TCA cycle intermediates, fatty acids, acylcarnitines, and ketone bodies all typically increase after exercise, whereas bile acids decrease. In contrast, the concentrations of proteinogenic and non-proteinogenic amino acids change in different directions. Conclusion: Across different exercise modes and in different subjects, exercise often consistently changes the average concentrations of metabolites that belong to energy metabolism and other branches of metabolism. This dataset is a useful resource for those that wish to study human exercise metabolism. [ABSTRACT FROM AUTHOR]