Handgrip exercise increases platelet‐bound BDNF in an intensity‐dependent manner
Notice bibliographique
Résumé
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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Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».