Autophagic response to exercise in peripheral blood mononuclear cells from young men is intensity-dependent and is altered by exposure to environmental heat
Bibliographic record
Abstract
Autophagy is essential to maintaining cellular homeostasis in all eukaryotic cells and to tolerance of acute stressors such as starvation, heat, and recovery after exercise. Limited information exists regarding the exercise intensity-dependent autophagic response in humans, and it is unknown how environmental heat stress may modulate this response. Therefore, we evaluated autophagy and accompanying pathways of cellular stress [the heat-shock response (HSR), apoptosis, and acute inflammation] in peripheral blood mononuclear cells (PBMCs) from 10 young men (mean [SD]; 22 [2] years) before, immediately after and up to 6-h postexercise recovery from 30 min of low-, moderate-, and high-intensity semirecumbent cycling [40%, 55%, and 70% of maximal oxygen consumption (V̇o2max), respectively] in a temperate environment (25°C) and at 70% of V̇o2max in a hot environment (40°C). Changes in protein content were analyzed via Western blot. Each increase in exercise intensity was associated with elevations in mean body temperature. LC3-II increased after moderate-intensity exercise, with further increases after high-intensity exercise ( P < 0.05). However, an increase in beclin-2 and ULK1, with a decrease in p62 was only observed after high-intensity exercise, which was paralleled by elevated TNF-α and cleaved-caspase-3, with the HSR peaking at 6 h after exercise ( P < 0.05). When exercise was performed in the heat, greater LC3-II and cleaved-caspase-3 accumulation were observed; however, beclin-2 declined in recovery ( P < 0.05). Therefore, our findings indicate that autophagy in PBMCs during exercise may be associated with greater heat strain exhibited during increasing exercise intensities, which is modulated by exposure to 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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".