Serum and plasma brain-derived neurotrophic factor concentration are elevated by systemic but not local passive heating
Bibliographic record
Abstract
Brain-derived neurotrophic factor (BDNF) plays a key role in neuronal adaptations. While previous studies suggest that whole-body heating can elevate circulating BDNF concentration, this is not known for local heating protocols. This study investigated the acute effects of whole-body versus local passive heating on serum and plasma BDNF concentration. Using a water-perfused suit, ten recreationally active males underwent three 90 min experimental protocols: heating of the legs with upper-body cooling (LBH), whole-body heating (WBH) and a control condition (CON). Blood samples were collected before, immediately after and 1 h post-heating for the determination of serum and plasma BDNF concentration, platelet count as well as the BDNF release per platelet. Rectal temperature, cardiac output and femoral artery shear rate were assessed at regular intervals. Serum and plasma BDNF concentration were elevated after WBH (serum: 19.1±5.0 to 25.9±11.3 ng/ml, plasma: 2.74±0.9 to 4.58±2.0; p<0.044), but not LBH (serum: 19.1±4.7 to 22.3±4.8 ng/ml, plasma: 3.25±1.13 to 3.39±0.90 ng/ml; p>0.126), when compared with CON (serum: 18.6±6.4 to 16.8±3.4 ng/ml, plasma: 2.49±0.69 to 2.82±0.89 ng/ml); accompanied by an increase in platelet count (p<0.001). However, there was no change in BDNF content per platelet after either condition (p = 0.392). All physiological measures were elevated to a larger extent after WBH compared with LBH (p<0.001), while shear rate and rectal temperature were higher during LBH than CON (p<0.038). In conclusion, WBH but not LBH acutely elevates circulating BDNF concentration. While these findings further support the use of passive heating to elevate BDNF concentration, a larger increase in shear rate, sympathetic activity and/or rectal temperature than found after LBH appears needed to induce an acute BDNF response by passive heating.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".