Mild endotoxemia, NF-κB translocation, and cytokine increase during exertional heat stress in trained and untrained individuals
Bibliographic record
Abstract
This study examined endotoxin-mediated cytokinemia during exertional heat stress (EHS). Subjects were divided into trained [TR; n=12, peak aerobic power (VO2peak)=70+/-2 ml.kg lean body mass(-1).min(-1)] and untrained (UT; n=11, VO2peak=50+/-1 ml.kg lean body mass(-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 endotoxin, lipopolysaccharide binding protein, circulating cytokines, and intranuclear NF-kappaB translocation. Baseline and Exh samples were also stimulated with LPS (100 ng/ml) and cultured in vitro in a 37 degrees C water bath for 30 min. Phenotypic determination of natural killer cell frequency was also determined. Enhanced blood (104+/-6 vs. 84+/-3 ml/kg) and plasma volumes (64+/-4 vs. 51+/-2 ml/kg) were observed in TR compared with UT subjects. EHS produced an increased concentration of circulating endotoxin in both TR (8+/-2 pg/ml) and UT subjects (15+/-3 pg/ml) (range: not detected to 32 pg/ml), corresponding with NF-kappaB translocation and cytokine increases in both groups. In addition, circulating levels of tumor necrosis factor-alpha and IL-6 were also elevated combined with concomitant increases in IL-1 receptor antagonist in both groups and IL-10 in TR subjects only. Findings suggest that the threshold for endotoxin leakage and inflammatory activation during EHS occurs at a lower temperature in UT compared with TR subjects and support the endotoxin translocation hypothesis of exertional heat stroke, linking endotoxin tolerance and heat tolerance.
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".