Acute submaximal exercise does not impact aspects of cognition and BDNF in people with spinal cord injury: A pilot study
Bibliographic record
Abstract
Objective To investigate the effect of acute submaximal exercise, based on the spinal cord injury (SCI) Exercise Guidelines, on cognition and brain-derived neurotrophic factor (BDNF) in people with SCI. Design Eight adults (7 males) with traumatic SCI volunteered in this pre-registered pilot study. In randomized order, participants completed submaximal intensity arm cycling (60% of measured peak-power output at 55–60 rpm) for 30 min or time-matched quiet rest (control condition) on separate days. Blood-borne BDNF was measured in serum and plasma at pre-intervention, 0 min and 90 min post-intervention. Cognition was assessed using the Stroop Test and Task-Switching Test on an electronic tablet pre- and 10 min post-intervention. Results Submaximal exercise had no effect on plasma [F(2,12) = 1.09; P = 0.365; η² = 0.069] or serum BDNF [F(2,12) = 0.507; P = 0.614; η² = 0.024] at either 0 min or 90 min post-intervention. Similarly, there was no impact of exercise on either Stroop [F(1,7) = 2.05; P = 0.195; η² = 0.065] or Task-Switching performance [F(1,7) = 0.016; P = 0.903; η² < 0.001] compared to the control condition. Interestingly, there was a positive correlation between years since injury and resting levels of both plasma (r = 0.831; P = 0.011) and serum BDNF (r = 0.799; P = 0.023). However, there was not relationship between years since injury and the BDNF response to exercise. Conclusions Acute guideline-based exercise did not increase BDNF or improve aspects of cognition in persons with SCI. This work establishes a foundation for continued investigations of exercise as a therapeutic approach to promoting brain health among persons with SCI.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".