Investigating the Acute and Chronic Effects of Cardiovascular Exercise on Brain-Derived Neurotrophic Factor in Early Subacute Stroke
Bibliographic record
Abstract
BackgroundFollowing stroke, a growth-promoting response resulting in heightened neuroplasticity occurs during the early subacute stages of recovery, a period during which the brain may be more responsive to therapeutical interventions. Given its central role in regulating neuroplastic processes and brain repair in animal models, brain-derived neurotrophic factor (BDNF) has been targeted as a potential biomarker for stroke recovery in humans, with interventions upregulating BDNF holding therapeutical potential. Cardiovascular exercise (CE) has been recommended for stroke rehabilitation, partly due to its potential to induce neural adaptations, including upregulation of BDNF.ObjectivesTo examine the effects of CE on BDNF in individuals at early subacute stages of recovery.MethodsSeventy-six participants within 3 months of first-ever ischemic stroke were randomly assigned to 8 weeks of either CE plus standard care or standard care alone. To measure the chronic and acute responses to exercise in serum BDNF levels, blood samples were collected before and immediately after a graded exercise test conducted at baseline, 4, and 8 weeks. The potential role of the BDNF Val66Met polymorphism in modulating the BDNF response was also explored. Data were analyzed following an intention-to-treat approach.ResultsDespite clinically important increases in cardiorespiratory fitness, CE did not induce significant chronic or acute changes in serum BDNF. Furthermore, the response to CE was not associated with changes in cardiorespiratory fitness and clinical outcomes or was modulated by Val66Met.ConclusionsThese findings indicate that CE has a limited capacity to upregulate circulating BDNF in subacute stages of stroke recovery.Trial Registration:Exercise and Genotype in Sub-acute Stroke: https://clinicaltrials.gov/study/NCT05076747.
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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 | 0.001 | 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) | 0.002 | 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".