Metabolic effects of prazosin on skeletal muscle insulin resistance in glucocorticoid-treated male rats
Bibliographic record
Abstract
High-dose glucocorticoids (GC) induce skeletal muscle atrophy, insulin resistance, and reduced muscle capillarization. Identification of treatments to prevent or reverse capillary rarefaction and metabolic deterioration caused by prolonged elevations in GCs would be therapeutically beneficial. Chronic administration of prazosin, an α1-adrenergic antagonist, increases skeletal muscle capillarization in healthy rodents and, recently, in a rodent model of elevated GCs and hyperglycemia. The purpose of this study was to determine whether prazosin administration would improve glucose tolerance and insulin sensitivity, through prazosin-mediated sparing of capillary rarefaction, in this rodent model of increased GC exposure. Prazosin was provided in drinking water (50 mg/l) to GC-treated or control rats (400 mg implants of either corticosterone or a wax pellet) for 7 or 14 days ( n = 5–14/group). Whole body measures of glucose metabolism were correlated with skeletal muscle capillarization (C:F) at 7 and 14 days in the four groups of rats. Individual C:F was found to be predictive of insulin sensitivity ( r2= 0.4781), but not of glucose tolerance ( r2= 0.1601) and compared with water only, prazosin treatment decreased insulin values during oral glucose challenge by approximately one-third in corticosterone (Cort)-treated animals. Cort treatment, regardless of duration, induced significant glycolytic skeletal muscle atrophy ( P < 0.05), decreased IRS-1 protein content ( P < 0.05), and caused elevations in FOXO1 protein expression ( P < 0.05), which were unaffected with prazosin administration. In summary, it appears that α1-adrenergic antagonism improves Cort-induced skeletal muscle vascular impairments and reduces insulin secretion during an oral glucose tolerance test, but is unable to improve the negative alterations directly affecting the myocyte, including muscle size and muscle signaling protein expression.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| 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".