Handgrip exercise increases platelet‐bound BDNF in an intensity‐dependent manner
Bibliographic record
Abstract
Introduction Brain‐derived neurotrophic factor (BDNF) is a major orchestrator of exercise‐induced brain plasticity, and evidence suggests that peripheral BDNF has central effects. Consequently, exploration into the mechanisms that increase peripheral BDNF has important implications for improving brain health through exercise. The majority of blood‐borne BDNF is bound to platelets, which sequester, store, and release the neurotrophin under physiological conditions. At rest, ~30% of circulating platelets are stored in the spleen, suggesting that by extension, a significant portion of blood‐borne BDNF is also stored in the spleen at rest. Interestingly, exercise evokes the transient release of platelets from the spleen into circulation via sympathetically mediated splenic contraction (exercise‐induced thrombocytosis). As such, this exercise‐induced thrombocytosis may account for the consistent observation that acute, whole‐body exercise transiently increases serum BDNF; however, the direct relationship between platelet and BDNF responses to exercise has yet to be examined. Interestingly, very brief (60 s) submaximal forearm contraction induces splenic constriction and a 2% elevation in platelet levels. If small muscle exercise is sufficient enough of a stimulus to increase platelet levels, then it could stand as a viable strategy for increasing circulating BDNF; however, the BDNF response to dynamic handgrip exercise (HGEX) is currently unknown. Further, given the purported role of sympathoexcitation in platelet release, exercise intensity may mediate this response. Purpose To examine the BDNF and platelet responses following both short‐duration maximal and prolonged submaximal intensity dynamic HGEX. Methods Healthy males (n = 12; 21.7 ±2.5 yrs) performed exercise on two separate days. Maximal‐effort exercise (ME) consisted of maximal, dynamic contractions for 10 minutes. Submaximal exercise (SE) was performed for 30 minutes and intensity was based off of a percentage of ME force output. Blood samples were drawn before exercise during rest and during the last minute of exercise. Serum BDNF was measured via enzyme‐linked immunosorbent assay. Platelets were derived from a complete blood count analyzed by a haematology lab. Results ME evoked an 8% increase in platelets (201.6 vs. 220.2 ×10 9 /L; p < 0.05), which was accompanied by a 14% increase in serum BDNF (22,964.9 vs. 26,709.1 pg/mL; p < 0.05). Interestingly, while there was no significant correlation between platelet and BDNF responses to ME, there was an increasing trend in the amount of BDNF per platelet from rest to ME (114 vs. 122 pg/10 9 /L; p = 0.07), suggesting the contribution of de novo BDNF from a cellular source. Conversely, there was no change in serum BDNF (22,010.1 vs. 22,644.2 pg/mL; p = 0.41) following SE despite a 5% increase in platelets (197.5 vs. 207.5 ×10 9 /L, p < 0.05). Conclusion Maximal‐intensity small muscle mass exercise significantly increases serum BDNF, which cannot be fully explained by an increase in platelets. These findings suggest the possible contribution of a cellular source to circulating BDNF. A follow‐up study is underway to further examine the platelet and BDNF responses to exercise and non‐exercise stimuli known to cause splenic constriction. Support or Funding Information Natural Sciences and Engineering Research Council of Canada (NSERC) Doctoral Scholarship
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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) | 0.000 | 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) | 0.003 | 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".