Expression of intracellular cytokines, HSP72, and apoptosis in monocyte subsets during exertional heat stress in trained and untrained individuals
Bibliographic record
Abstract
This study examined intracellular cytokine, heat shock protein (HSP) 72, and cellular apoptosis in classic and inflammatory CD14(+) monocyte subsets during exertional heat stress (EHS). Subjects were divided into endurance-trained [TR; n = 12, peak aerobic power (Vo(2peak)) = 70 +/- 2 ml.kg lean body mass (LBM)(-1).min(-1)] and sedentary-untrained (UT; n = 11, Vo(2peak) = 50 +/- 1 ml.kg LBM(-1).min(-1)) groups before walking at 4.5 km/h with 2% elevation in a climatic chamber (40 degrees C, 30% relative humidity) wearing protective clothing until exhaustion (Exh). Venous blood samples at baseline and 0.5 degrees C rectal temperature increments (38.0, 38.5, 39.0, 39.5, and 40.0 degrees C/Exh) were analyzed for cytokines (TNF-alpha, IL-1beta, IL-6, IL-1ra, and IL-10) in CD14(++)CD16(-)/CD14(+)CD16(+) and HSP72/apoptosis in CD14(Bri)/CD14(Dim) subsets. In addition, serum levels of extracellular (e)HSP72 were also examined. Baseline and Exh samples were separately stimulated with LPS (1 microg/ml) or heat shocked (42 degrees C) and cultured in vitro for 2 h. A greater temperature-dependent increase in CD14(+)CD16(+) cells was observed in TR compared with UT subjects as well as a greater LPS tolerance following in vitro LPS stimulation. TNF-alpha and IL-1beta cytokine expression was elevated in CD14(+)CD16(+) but not in CD14(++)CD16(-) cells. A greater induction of intracellular HSP72 and eHSP72 was observed in TR compared with UT subjects, which coincided with reduced apoptosis at Exh and following in vitro heat shock. Induced HSP in vitro was not uniform across CD14(+) subsets. Findings suggest that circulating CD14(+)CD16(+), but not CD14(++)CD16(-) monocytes, contribute to the proinflammatory cytokine profiles observed during EHS. In addition, the enhanced HSP72 response in endurance-trained individuals may confer improved heat tolerance through both anti-inflammatory and anti-apoptotic mechanisms.
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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".