Individuals with Higher Levels of Physical Activity after Stroke Show Comparable Patterns of Myelin to Healthy Older Adults
Bibliographic record
Abstract
BACKGROUND: Myelin asymmetry ratios (MARs) relate and contribute to motor impairment and function after stroke. Physical activity (PA) may induce myelin plasticity, potentially mitigating hemispheric myelin asymmetries that can occur after a stroke. OBJECTIVE: The aim of this study was to determine whether individuals with higher levels of PA showed lower MAR compared to individuals with lower levels of PA. METHODS: Myelin water fraction was obtained from 5 bilateral motor regions in 22 individuals with chronic stroke and 26 healthy older adults. Activity levels were quantified with wrist accelerometers worn for a period of 72 hours (3 days). Higher and lower PA levels were defined by a cluster analysis within each group. RESULTS: MAR was similar regardless of PA level within the older adult group. Compared to the higher PA stroke group, lower PA stroke participants displayed greater MAR. There was no difference in MAR between the stroke and older adult higher PA groups. Within the lower PA groups, individuals with stroke showed greater MAR compared to the older adults. Arm impairment, lesion volume, age, time since stroke, and preferential arm use were not different between the PA stroke groups, suggesting that motor impairment severity and extent of brain damage did not drive differences in PA. CONCLUSION: Individuals who have had a stroke and are also physically active display lower MAR (i.e., similar myelin in both hemispheres) in motor regions. High levels of PA may be neuroprotective and mitigate myelin asymmetries once a neurological insult, such as a stroke, occurs. Alternately, it is possible that promoting high levels of PA after a stroke may reduce myelin asymmetries.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".