Metabolomic Response of Skeletal Muscle to Aerobic Exercise Training in Insulin Resistant Type 1 Diabetic Rats
Bibliographic record
Abstract
The etiology of insulin resistance in Type 1 Diabetes (T1D) is unknown, however it affects approximately 20% of T1D patients. Intramyocellular lipids (IMCL) have been identified as a mechanism of insulin resistance. We examined skeletal muscle of T1D rats to determine if alterations in lipid metabolism were evident and whether aerobic exercise training improves IMCL and insulin resistance. To do so, 48 male Sprague-Dawley rats were divided into control (C), sedentary diabetes (D) and diabetes exercise (DX) groups. Following multiple low-dose Streptozotocin (STZ) injections (20 mg/kg), glycemia (9-15 mM) was maintained using insulin treatment. DX were treadmill trained at high intensity (~75% V02max; 5days/week) for 10 weeks. The results demonstrate that D exhibited insulin resistance compared with C and DX, indicated by decreased glucose infusion rate during a hyperinsulinemic-euglycemic clamp (p < 0.05). There were no differences between C and DX, suggesting that exercise improved insulin resistance (p < 0.05). Metabolomics analysis revealed a significant shift in lipid metabolism whereby notable fatty acid metabolites (arachidonic acid, palmitic acid and several polyunsaturated fatty acids) were significantly elevated in D compared to C and DX. Based on the intermediates observed, insulin resistance in T1D is characterized by an insulin-desensitizing intramyocellular fatty acid metabolite profile that is ameliorated with exercise training.
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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) | 0.000 | 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 | 0.001 |
| 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".