Effect Of Cooling Centers On Renal And Gastrointestinal Stress In Older-adults During Daylong Heat Exposure
Bibliographic record
Abstract
Heatwaves pose a significant risk to human health (e.g., heat stroke, major cardiovascular events), especially in older adults due to age-related declines in thermoregulatory and cardiovascular function. Health agencies, such as Centers for Disease Control, recommend visiting a cooled location (e.g. cooling center) to reduce the risk of heat-related injuries. However, there is limited experimental evidence supporting their effectiveness. While we recently showed that a brief (2-h) reprieve from the heat during a 9-h heatwave simulation causes transient reductions in core temperature and cardiovascular strain, effects on other critical systems that may underlie the pathogenesis of heat injury, including gastrointestinal barrier and renal function, have not been evaluated. PURPOSE: To assess the impact of a brief cooling intervention during prolonged heat exposure on biomarkers of gastrointestinal barrier function and renal ischemia in older adults. METHODS: We assessed serum protein responses (ELISA) in 19 older adults [mean age 71 [2] years; 9 females] before and after a 9-hour heat exposure (40.3 °C, 9.3% RH). Participants in the cooling group moved to a cooler environment (~23 °C) during hours 5 and 6. Responses were compared to a control group of 17 older adults [72 [4] years; 7 females] who remained in the heat for the full 9 hours. RESULTS: Brief cooling led to significant but temporary reductions in both core temperature and heart rate. Serum intestinal fatty acid binding protein (IFABP), a marker of enterocyte damage, increased by ~175 pg/mL in both groups throughout the heat exposure. Consequently, changes in soluble cluster of differentiation 14 (sCD14), indicative of immune activation, were not significantly different between groups from the start to the end of the 9-h exposure (cooling - control mean difference -7.3 ng/mL; 95% CI: -14.4 to 0.4 ng/mL; P = 0.059). However, serum neutrophil gelatinase-associated lipocalin (NGAL), a marker of renal ischemia, was 3.2 pg/mL [1.9 to 6.1] lower in the cooling compared to the control group (P = 0.040). CONCLUSIONS: Although the pronounced, transient reductions in thermal and cardiovascular strain during the 2-h ambient cooling intervention did not significantly mitigate gastrointestinal barrier dysfunction, it may provide renal protection for older adults. Supported by: Canadian Institutes of Health Research
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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".