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Record W3008175177 · doi:10.1113/jp278828

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

2020· article· en· W3008175177 on OpenAlexafffund
Nicholas J. Saner, Matthew J-C Lee, Nathan W. Pitchford, Jujiao Kuang, Gregory D. Roach, Andrew Garnham, Tanner Stokes, Stuart M. Phillips, David J. Bishop, Jonathan D. Bartlett

Bibliographic record

VenueThe Journal of Physiology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsMcMaster University
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsSleep restrictionSleep (system call)Skeletal muscleInternal medicineMedicineBody mass indexEndocrinologyIntensity (physics)CardiologySleep deprivationPhysical therapyCircadian rhythm

Abstract

fetched live from OpenAlex

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, , 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‐AKT ser473 and p‐mTOR ser2448 ) 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.233
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations67
Published2020
Admission routes2
Has abstractyes

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