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Enregistrement W2894310979 · doi:10.1113/jp276912

Finding the metabolic stress ‘sweet spot’: implications for sprint interval training‐induced muscle remodelling

2018· letter· en· W2894310979 sur OpenAlexafffundabout
Lauren E. Skelly, Jenna B. Gillen

Notice bibliographique

RevueThe Journal of Physiology · 2018
Typeletter
Langueen
DomaineMedicine
ThématiqueAdipose Tissue and Metabolism
Établissements canadiensUniversity of TorontoMcMaster University
Organismes subventionnairesCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
Mots-clésSprintHigh-intensity interval trainingInterval trainingTraining (meteorology)Sweet spotInternal medicineMedicineCardiologyPhysical medicine and rehabilitationPhysical therapyComputer sciencePhysicsSimulationSpeed skating

Résumé

récupéré en direct d'OpenAlex

Exercise-induced homeostatic disturbances initiate the activation of signalling cascades in skeletal muscle that coordinate increases in gene transcription and facilitate cellular remodelling. These acute skeletal muscle responses have been proposed to regulate training-induced increases in mitochondrial proteins. Traditional continuous moderate-intensity training is an effective strategy for inducing mitochondrial biogenesis. Sprint interval training (SIT), characterized by brief intermittent bouts of 'all-out' exercise interspersed with recovery periods, is also a potent stimulus for inducing skeletal remodelling despite involving a low total exercise volume. The high metabolic stress associated with low-volume SIT may be an important factor mediating the skeletal muscle adaptive response to this form of training. However, our understanding of how the magnitude of the metabolic disturbance induced by intense intermittent exercise impacts mitochondrial remodelling is limited. A recent article in The Journal of Physiology by Fiorenza et al. (2018) examined the activation of signalling proteins and mitochondrial gene expression in response to two work-matched, low-volume SIT protocols and a higher volume, continuous moderate-intensity protocol. The authors' findings provide important insight into the relationship between exercise-induced cellular disturbances and the acute skeletal muscle response to low-volume SIT. The study by Fiorenza et al. (2018) involved 12 endurance-trained male cyclists, who completed three experimental trials on separate days in a randomized, counter-balanced manner. Diet and activity were carefully controlled prior to each experimental trial. The protocols involved either intermittent exercise, characterized as 'repeated-sprint' (RS) or 'speed endurance' (SE), or continuous, moderate-intensity (CM) cycling. RS consisted of 18 × 5 s all-out intervals interspersed with 30 s of passive recovery and SE involved 6 × 20 s all-out sprints interspersed with 2 min of passive recovery. The two SIT protocols were matched for total exercise volume and work to rest ratio but were hypothesized to elicit distinct degrees of intramuscular stress owing to differences in interval duration. The CM protocol involved 50 min of cycling at 70% and thus was hypothesized to elicit a milder but more prolonged metabolic stress. Mean power output was ∼902, ∼669 and ∼218 W during RS, SE and CM, respectively. Muscle biopsies were obtained from the vastus lateralis prior to, immediately following and 3 h following exercise for analyses of a comprehensive set of metabolites, intracellular signalling proteins and genes associated with mitochondrial biogenesis. The authors also employed multiple linear regression analyses to probe metabolic factors that might predict exercise-induced increases in mitochondrial gene expression. The authors concluded that (1) for a given volume of high-intensity exercise, the initial events associated with mitochondrial biogenesis are dependent on metabolic stress (RS vs. SE), and (2) high-intensity exercise can compensate for reduced exercise volume only when marked metabolic perturbation occurs (SE vs. CM). A strength of the study was the direct comparison between two work-matched low-volume SIT protocols. Consistent with the authors' hypothesis, SE elicited a greater metabolic stress than RS, as evidenced by a higher exercise-induced increase in muscle lactate and plasma adrenaline, and lower muscle pH. Importantly, the greater metabolic disturbance associated with SE was associated with a higher increase in peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α) mRNA expression in post-exercise recovery compared to RS. Moreover, the response between SE and CM was largely comparable, such that both protocols evoked similar increases in mitochondrial gene expression, despite large differences in exercise volume. These findings are noteworthy and serve as a reminder that all low-volume SIT protocols are not equivalent. The greater glycolytic contribution to energy provision associated with 20 s as compared to 5 s sprints may be an important signal for the superior exercise-induced skeletal muscle remodelling in SE. Training using only 3 × 20 s all-out sprints per session is a profound stimulus to induce mitochondrial biogenesis and improve markers of cardiometabolic health, at least in previously inactive adults (Gillen et al. 2014). Interestingly, the protocol by Gillen et al. (2014) evoked large increases in mitochondrial content despite involving half the number of 20 s sprints as Fiorenza and colleagues. Whether reducing the number of 20 s efforts in the SE protocol would provide a sufficient metabolic stress in endurance-trained men is unknown. It is possible that a greater number of intervals is required to initiate mitochondrial responses in well-trained adults compared to the inactive population studied by Gillen et al. (2014). Nonetheless, the findings from Fiorenza et al. (2018) provide further support for the potency of repeated 20 s sprints for inducing skeletal muscle remodelling in a time-efficient manner. The present study advances our understanding of the mechanisms by which brief bursts of intense intermittent exercise may induce skeletal muscle responses, similar to longer bouts of traditional moderate-intensity exercise. While these diverse exercise stimuli have been shown to converge on mutual signalling pathways believed to regulate mitochondrial biogenesis, the present study demonstrates that the initial signalling events that trigger the induction of mitochondrial pathways are distinct. For the low-volume protocols RS and SE, multiple linear regression analyses revealed that exercise-induced increases in plasma adrenaline and muscle H+ concentration, along with muscle glycogen and phosphocreatine utilization during exercise, were important predictors of the post-exercise transcription of mitochondrial genes. The authors were able to manipulate the metabolic perturbation of low-volume interval training by adjusting the interval duration, which evoked a response similar to that seen when combining interval training with nutritional manipulation. For example, ingestion of 0.4 g kg−1 body weight of sodium bicarbonate (NaHCO3) before performing 10 × 1 min intervals at 90% maximal heart rate with 1 min recovery augmented skeletal muscle glycogenolysis during exercise and enhanced PGC-1α mRNA expression during recovery (Percival et al. 2015). We postulated that the enhanced muscle glycogen utilization and resultant lactate accumulation associated with NaHCO3 supplementation were important contributors to the elevated mitochondrial response, which is consistent with results of the present investigation. It would be interesting to determine if combining NaHCO3 supplementation with SE could augment rates of muscle glycogenolysis and PGC-1α mRNA expression further than observed by Fiorenza and colleagues, in an effort to 'optimize' the acute exercise stimulus. Additional research is also needed to confirm/refute whether these relatively small differences in mRNA expression between protocols lay the foundation for elevated protein responses with training. The present study was conducted in men only and it will be important to determine whether the responses are similar in women, given other work suggesting the potential for some subtle sex-based differences in the response to SIT (Gillen et al. 2014). Multiple linear regression analyses revealed an important role of plasma adrenaline, muscle glycogen utilization and lactate accumulation in predicting the skeletal muscle response to RS and SE. For example, increased plasma adrenaline and muscle glycogen utilization were significant predictors of the PGC-1α mRNA response, while greater lactate accumulation predicted an increased expression of heat shock protein (HSP) 72. Research has shown, however, that in response to repeated 30 s sprints, women have a lower catecholamine response, reduced rate of muscle glycogen utilization and lower blood lactate accumulation (Esbjornsson-Liljedahl et al. 2002). Repeated all-out sprints may therefore evoke a lower metabolic stress in women, which in light of the current findings, may result in a dampened signal for up-regulating pathways linked to skeletal muscle adaptation. It has been observed that following 6 weeks of high-volume intermittent or continuous aerobic training, skeletal muscle HSP content increased in men but not women (Morton et al. 2009). The lack of adaptation in this cellular defence protein in response to training has been suggested to relate to a lower exercise-induced disruption in homeostasis during acute exercise sessions in women. Considering the importance of the acute 'metabolic insult' for induction of the molecular pathways observed in the present study, future research is needed to clarify the impact of SE and RS on skeletal muscle responses in women. In summary, Fiorenza et al. (2018) demonstrate the importance of exercise-induced metabolic stress in mediating skeletal muscle mitochondrial responses to low-volume SIT. These findings provide valuable information for the design of future investigations that seek to maximize skeletal muscle remodelling to low-volume SIT via manipulation of the exercise stimulus and/or incorporation of nutritional interventions. These efforts may help enhance skeletal muscle mitochondrial adaptations to time-efficient exercise protocols in both healthy and clinical populations. The authors have no conflicts of interest to declare. Both authors have approved the final version of the manuscript and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All persons designated as authors qualify for authorship and all those who qualify for authorship are listed. L.E.S. is supported by a Natural Sciences and Engineering Research Council of Canada Vanier Canada Graduate Scholarship. J.B.G is supported by a Canadian Institutes of Health Research Postdoctoral Fellowship. We apologize for not citing all relevant articles due to reference limitations. We thank Dr Martin Gibala for his helpful review of the manuscript prior to submission.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,009

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,112
Tête enseignante GPT0,346
Écart entre enseignants0,234 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2018
Routes d'admission3
Résumé présentoui

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