Changes In Plasma Irisin And BDNF In Response To 7-day Cold-water Acclimation In Young Males
Bibliographic record
Abstract
Cold water immersion can elicit strong physiological responses (i.e., shivering, hemodynamics), and has garnered interest for its potential therapeutic benefits when repeated via an acclimation. Irisin is a myokine that increases the expression of mitochondrial uncoupling and may affect metabolic activity during acute bouts of cold exposure. Further, irisin potentially plays a role in neural protection via stimulation of brain-derived neurotropic factor (BDNF), a circulating cytoprotective protein that also increases during acute cold exposure. While it is known that cold acclimation can alter thermoregulatory responses, such as shivering, it is unclear how acclimation may alter circulating cytoprotective proteins. PURPOSE: To evaluate the effect of 7-day cold-water acclimation on circulating irisin and BDNF concentrations during cold-water immersion throughout acclimation. METHODS: Six healthy, habitually active young males (23 ± 3 years) underwent a 7-day cold-water acclimation using 14 °C water for 60 min per day. Core temperature (esophageal) was measured continuously throughout each exposure. Plasma was collected intravenously before and after cold exposure on the first, fourth, and last day of acclimation. Lactate (a surrogate for changes in shivering), irisin, and BDNF were analyzed via enzyme-linked immunosorbent assays (ELISA), reported as changes from baseline values (means [SD]), and were analyzed via a one-way repeated measures ANOVA with Bonferroni correction (α = 0.05). RESULTS: No changes in BDNF were observed following cold exposure between any of the assessed days (p ≥ 0.397). Similarly, although core temperature significantly reduced with each day (-0.6 °C, p = 0.001), no changes between days were observed (p = 0.161). Irisin was significantly lower (p = 0.041) on day 7 (-367 pg/mL [400]) than day 1 (69 pg/mL [380]), but not day 4 (-132 pg/mL [425]). Similarly, lactate was significantly lower on day 7 (0.15 umol/mL [0.28]) compared to day 1 (0.36 umol/mL [0.24], p = 0.047), but not day 4 (28 umol/mL [0.29], p = 0.295). CONCLUSION: Given similar decreases in lactate (indicating reduced shivering) and irisin throughout the acclimation, irisin stimulation may only occur during the acute cold stress response associated with shivering, without influencing BDNF production. Supported by: National Sciences and Engineering Research Council of Canada
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".