Impacts of age, diabetes, and hypertension on serum endothelial monocyte‐activating polypeptide‐II after prolonged work in the heat
Bibliographic record
Abstract
BACKGROUND: With rising temperature extremes, older workers are becoming increasingly vulnerable to heat-related injuries because of age- and disease-associated decrements in thermoregulatory function. Endothelial monocyte-activating polypeptide-II (EMAP-II) is a proinflammatory cytokine that has not yet been well-characterized during heat stress, and which may mediate the inflammatory response to high levels of physiological strain. METHODS: ) in temperate (wet-bulb globe temperature [WBGT] 16°C) and hot (WBGT 32°C) environments in heat-unacclimatized, healthy young (n = 13; mean [SD]; 22 [3] years) and older men (n = 12; 59 [4] years), and unacclimatized older men with hypertension (HTN) (n = 10; 60 [4] years) or type 2 diabetes (T2D) (n = 9; 60 [5] years). Core temperature and heart rate were measured continuously. RESULTS: In the hot environment, work tolerance time was lower in older men with HTN and T2D compared to healthy older men (both p < 0.049). While core temperature and heart rate reserve increased significantly (p < 0.001), they did not differ across groups. End-exercise serum EMAP-II concentrations were higher in young men relative to their older counterparts due to higher baseline levels (both p ≤ 0.02). Elevations in serum EMAP-II concentrations were similar between healthy older men and older men with HTN, while serum EMAP-II concentrations did not change in older men with T2D following prolonged work in the heat. CONCLUSION: Serum EMAP-II concentrations increased following prolonged moderate-intensity work in the heat and this response is influenced by age and the presence of HTN or T2D.
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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 | 0.001 |
| 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".