The Effect of Body Weight-Supported Treadmill Training on Muscle Morphology in an Individual With Chronic, Motor- Complete Spinal Cord Injury: A Case Study
Bibliographic record
Abstract
OBJECTIVE: The purpose of this pilot study was to examine the effects of 4 months of thrice-weekly body weight-supported treadmill training (BWSTT) on skeletal muscle morphology in a woman (age 27 y) with chronic, motor-complete (ASIA B) spinal cord injury (SCI). METHODS: The participant performed passive thrice-weekly BWSTT for 4 months (48 total sessions) with manual assistance from therapists. Muscle biopsies of the vastus lateralis were taken prior to the beginning of the training program as well as following the completion of 4 months of training. Histochemical analysis was utilized to evaluate changes in muscle fiber size and type following training. RESULTS: At baseline, vastus lateralis muscle biopsies showed evidence of fiber atrophy and fiber type redistribution typical of persons with SCI, with mean fiber areas (and % distributions) of type I, type IIa and type IIx fibers being 3474 microm2 (1.3%), 3146 microm2 (30.8%) and 1284 microm2 (68.0%), respectively. Following training, there were increases in treadmill walking speed (pre: 1.0km/h; post: 2.5km/h) and distance walked/session (pre: 500m; post: 1875m). Vastus lateralis mean fiber area increased by 27.1% and type I fiber % distribution increased to 24.6%, whereas type IIa and type IIx fiber % distributions both decreased following training. CONCLUSION: These data indicate that 4 months of thrice-weekly BWSTT improved muscle morphology in an individual with chronic, motor-complete 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".