Short-Duration Maximal and Long-Duration Submaximal Effort Forearm Exercise Achieve Elevations in Serum Brain-Derived Neurotrophic Factor
Bibliographic record
Abstract
Brain-derived neurotrophic factor (BDNF) is a major orchestrator of exercise-induced brain plasticity and circulating (peripheral) BDNF may have central effects. Approximately 99% of circulating BDNF is platelet-bound, and at rest ~30% of circulating platelets are stored in the spleen. Interestingly, forearm handgrip exercise significantly elevates sympathetic outflow and has been shown to induce splenic constriction, suggesting that small muscle mass exercise could stand as a viable strategy for increasing circulating BDNF; however, the BDNF response to handgrip exercise is currently unknown. Purpose: This study examined BDNF and platelet responses to short-duration maximal (ME) and prolonged submaximal (SE) effort handgrip exercise. Methods: Healthy males (n=18; 21.4 2.1 years, BMI 25.0 1.0 kg/m2) performed 10 minutes of ME and 30 minutes of SE. Blood was sampled for the determination of serum BDNF and platelet count at rest and during the last minute of exercise. Results: Compared to rest, serum BDNF significantly increased during ME (21.2%) and SE (11.2%), which displayed a non-significant trend towards an intensity-dependent response. Platelets increased in an intensity-dependent fashion compared to rest with an 8.0% increase during ME and 3.1% during SE, and these responses were significantly correlated with diastolic blood pressure responses to handgrip exercise. Further, the amount of BDNF per platelet significantly increased compared to rest during ME (13.4%) and SE (8.7%). Conclusions: Handgrip exercise evokes physiologically meaningful significant increases in serum BDNF and platelets, implicating splenic constriction as a key mechanism and confirming efficacy of this exercise model for elevating circulating BDNF.
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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) | 0.002 | 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".