Statin Therapy Alters Lipid Storage in Diabetic Skeletal Muscle
Bibliographic record
Abstract
While statins significantly reduce cholesterol levels and thereby reduce the risk of cardiovascular disease, the development of myopathy with statin use is a significant clinical side effect. Recent guidelines recommend increasing inclusion criteria for statin treatment in diabetic individuals; however, the impact of statins on skeletal muscle health in those with diabetes (who already suffer from impairments in muscle health) is ill defined. Here, we investigate the effects of fluvastatin treatment on muscle health in wild type (WT) and streptozotocin (STZ)-induced diabetic mice. WT and STZ-diabetic mice received diet enriched with 600 mg/kg fluvastatin or control chow for 24 days. Muscle morphology, intra and extracellular lipid levels, and lipid transporter content were investigated. Our findings indicate that short-term fluvastatin administration induced a myopathy that was not exacerbated by the presence of STZ-induced diabetes. Fluvastatin significantly increased ectopic lipid deposition within the muscle of STZ-diabetic animals, findings that were not seen with diabetes or statin treatment alone. Consistent with this observation, only fluvastatin-treated diabetic mice downregulated protein expression of lipid transporters FAT/CD36 and FABPpm in their skeletal muscle. No differences in FAT/CD36 or FABPpm mRNA content were observed. Altered lipid compartmentalization resultant of a downregulation in lipid transporter content in STZ-induced diabetic skeletal muscle was apparent in the current investigation. Given the association between ectopic lipid deposition in skeletal muscle and the development of insulin-resistance, our findings highlight the necessity for more thorough investigations into the impact of statins in humans with diabetes.
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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 | 0.000 | 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".