Effects of exercise on muscle transverse relaxation determined by MR imaging and in vivo relaxometry
Bibliographic record
Abstract
The purpose of this study was to determine the effects of intense exercise on the proton transverse (T(2)) relaxation of human skeletal muscle. The flexor digitorium profundus muscles of 12 male subjects were studied by using magnetic resonance imaging (MRI; 6 echoes, 18-ms echo time) and in vivo magnetic resonance relaxometry (1,000 echoes, 1.2-ms echo time), before and after an intense handgrip exercise. MRI of resting muscle produced a single T(2) value of 32 ms that increased by 19% (P < 0.05) with exercise. In vivo relaxometry showed at least three T(2) components (>5 ms) for all subjects with mean values of 21, 40, and 137 ms and respective magnitudes of 34, 49, and 14% of the total magnetic resonance signal. These component magnitudes changed with exercise by -44% (P < 0.05), +52% (P < 0.05), and +23% (P < 0.05), respectively. These results demonstrate that intense exercise has a profound effect on the multicomponent T(2) relaxation of muscle. Changes in the magnitudes of all the T(2) components synergistically increase MRI T(2), but changes in the two shortest T(2) components predominate.
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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 | 0.000 | 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) | 0.001 | 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".