The microsomal triglyceride transfer protein inhibitor lomitapide improves vascular function in mice with obesity
Bibliographic record
Abstract
OBJECTIVE: In this study, the effect of lomitapide, a microsomal triglyceride transfer protein inhibitor, on the cardiovascular function in obesity was investigated. METHODS: Eight-week-old C57BL/6 mice were fed with high-fat diet for 12 weeks in the presence and absence of lomitapide. Lomitapide was administered by gavage (1 mg/kg/d) during the last 2 weeks of high-fat feeding. Body weight, blood glucose, body composition, and lipid profile were determined. Vascular function and endothelial function markers were studied in the aorta and mesenteric resistance arteries. RESULTS: Lomitapide treatment reduced body weight in mice with obesity. Blood glucose, percentage of fat mass, total cholesterol, and low-density lipoprotein levels were significantly reduced, and the percentage of lean mass was significantly increased after lomitapide treatment. The vascular response to sodium nitroprusside in the aorta and mesenteric arteries was similar among groups. However, the vascular response to acetylcholine was improved in the treated group. This was associated with decreased levels of vascular endoplasmic reticulum stress, inflammation, and oxidative stress. CONCLUSIONS: Treatment with lomitapide attenuated the increase in body weight in mice with obesity and restored the lipid profile and vascular function. These effects were accompanied by a decrease in inflammation and oxidative stress.
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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 | 0.000 | 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 | 0.001 |
| 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".