Brain-derived neurotrophic factor response to daylong exposure to extreme heat in young and older adults: a secondary analysis
Bibliographic record
Abstract
Brain-derived neurotrophic factor (BDNF) is a growth factor associated with a range of neurological, cardioprotective, and metabolic health benefits. While passive heat stress has been observed to increase circulating BDNF, the BDNF response to a given stressor may be attenuated with increasing age. To investigate the influence of age on the BDNF response to heat stress, we compared BDNF responses to daylong (9 h) exposure to hot ambient conditions (40 °C, 9% relative humidity) between 19 young (range: 19–31 years; 9 women) and 37 older adults (61–78 years; 12 women). We also explored whether cumulative thermal strain (area under the curve of rectal and mean body temperatures) impacted comparisons. Serum BDNF concentrations were assessed at pre- and end-exposure using enzyme-linked immunosorbent assays. Circulating BDNF concentrations increased from baseline in both groups ( P < 0.001), but end-exposure concentrations were 2594 [1555–3633] pg/mL lower in older than young adults ( P < 0.001). This age-related difference persisted, albeit to a lesser magnitude, after accounting for the lower pre-exposure BDNF levels in older adults (baseline-adjusted between-group difference: 1648 [667–2630] pg/mL; P < 0.001). Additionally, the BDNF response was not related to indices of thermal strain ( P ≥ 0.562), and baseline-adjusted between-group differences were not appreciably altered by adjusting for area under the curve of rectal (1769 [714–2825] pg/mL; P = 0.002) or mean body temperatures (1745 [727–2763] pg/mL; P = 0.001). Our study is the first to demonstrate an age-related reduction in the BDNF response to prolonged passive heat exposure, which informs our wider understanding of how environmental stressors influence BDNF responses in older adults.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".