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The Autophagic Response to Acute Exercise in Young Men is Exercise Intensity Dependent and Influenced by Exposure to Heat

2022· article· en· W4225368765 on OpenAlexafffund
Kelli E. King, James J. McCormick, Melissa D. Côté, Morgan K. McManus, Nicholas Goulet, Karol Dokładny, Glen P. Kenny

Bibliographic record

VenueThe FASEB Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAutophagyExercise intensityHeat stressAnalysis of varianceMedicineEndocrinologyInternal medicineChemistryBiologyHeart rateBiochemistryAnimal science

Abstract

fetched live from OpenAlex

Autophagy is a vital cellular mechanism that maintains normal cellular function during acute stressors, including exercise and heat stress, by degrading and recycling damaged or dysfunctional cellular constituents, thereby enabling normal cellular processes to survive the stress insult. Despite implications of exercise being a potent stimulus of autophagy, the relationship between exercise intensity and activation of autophagy remains unclear in humans. Further, while cellular stress associated with exercise is exacerbated when performed in the heat, it is unknown if this is associated with a corresponding change in autophagy. Therefore, we evaluated the hypothesis that autophagy would be exercise‐intensity dependent and that the autophagic response would be enhanced during exercise in the heat. To evaluate this hypothesis, on four separate days, 10 young men (mean [SD]; 22 [2] years) performed 30‐minutes of low‐, moderate‐, and high‐intensity semi‐recumbent cycling (equivalent to 40, 55, and 70% of maximal oxygen consumption) in a non‐heat stress environment (25°C). To assess the superimposing effects of an environmental heat stress, high‐intensity exercise was also performed in the heat (40°C). Mean body temperature (MBT; 0.64*rectal temperature + 0.36*skin temperature) was measured throughout, while autophagy‐related proteins (microtubule associated protein 1 light chain 3 (LC3)‐II and sequesterome‐1/p62 (p62)) were assessed via Western blot before, immediately after, and following 3h and 6h post‐exercise recovery. All proteins were normalized to β‐actin and reported as fold change relative to the respective baseline. Data were compared via a two‐way repeated measures ANOVA with Tukey’s test (α=0.05). No change in MBT occurred during low‐intensity exercise, although a step‐wise increase was observed at end‐exercise during moderate‐ (36.01 [0.36]°C; p<0.01), and high‐intensity exercise (36.32 [0.35]°C; p<0.01), with further increases in the heat (37.40 [0.50]°C; p<0.01) as assessed in the high‐intensity exercise only. While autophagy proteins did not change during low‐intensity exercise, LC3‐II was elevated at the end of moderate‐intensity exercise (1.31 [0.38]; p=0.02), which returned to baseline within 3h. During high‐intensity exercise, LC3‐II increased at end‐exercise (1.59 [0.16]; p<0.01), which remained elevated above baseline at 3h (1.46 [0.28]; p<0.01) and 6h (1.31 [0.22]; p=0.04). Similarly, while LC3‐II was elevated at end‐exercise in the heat above the non‐heat stress condition (2.38 [0.98]; p=0.01), the recovery response was similar between conditions. Changes in p62 were only observed during high‐intensity exercise with (0.65 [0.27]; p=0.03) and without (0.69 [0.10]; p=0.04) heat, which returned to basal levels within 3‐h in both conditions, with no differences between conditions. Taken together, we show that autophagy is exercise‐intensity dependent (given LC3‐II accumulation and p62 degradation are indicative of elevated autophagy) and this response is amplified by the added burden of heat.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 head0.262
Teacher spread0.254 · 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 designObservational
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

Citations0
Published2022
Admission routes2
Has abstractyes

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