Body-weight-support treadmill training improves blood glucose regulation in persons with incomplete spinal cord injury
Bibliographic record
Abstract
The impact of a 6-mo body-weight-supported treadmill training program on glucose homeostasis and muscle metabolic characteristics was investigated. Nine individuals (31 +/- 3 yr, 8.1 +/- 2.5 yr postinjury; means +/- SE) with incomplete spinal cord injury trained three times weekly for a total of 6 mo. Training session duration and intensity (velocity) increased by 54 +/- 10% (P < 0.01) and 135 +/- 20%, respectively. Muscle biopsies and a modified glucose tolerance test (100 g glucose with [U-(13)C]glucose) were performed before (Pre) and after training (Post). Training resulted in a reduction in area under the curve of glucose x time (-15 +/- 4%) and insulin x time (-33 +/- 8%; both P < 0.05). Oxidation of exogenous (ingested) glucose increased as a result of training (Pre = 4.4 +/- 0.7 g/h, Post = 7.4 +/- 0.6 g/h; P < 0.05), as did oxidation of endogenous (liver) glucose (Pre = 3.8 +/- 0.3 g/h, Post = 5.2 +/- 0.3 g/h; P < 0.05). Training resulted in increased muscle glycogen (80 +/- 23%; P < 0.05) and GLUT-4 content and hexokinase II enzyme activity (126 +/- 34 and 49 +/- 4%, respectively, both P < 0.01). Resting muscle phosphocreatine content also increased after training (Pre = 62.1 +/- 4.3, Post = 78.7 +/- 3.8, both mmol/kg dry wt and P < 0.05). Six months of thrice-weekly body-weight-supported treadmill training in persons with an incomplete spinal cord injury improved blood glucose regulation by increasing oxidation and storage of an oral glucose load. Increases in the capacity for transport and phosphorylation glucose in skeletal muscle likely play a role in these adaptations.
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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) | 0.001 | 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 | 0.000 |
| 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".