Adipocytes modulate vascular smooth muscle cells migration potential through their secretions
Bibliographic record
Abstract
Impairment of vascular smooth muscle cells (VSMC) is recognized as a predisposition factor for atherosclerosis development. We hypothesize that the metabolic syndrome has a direct impact on VSMC migration and phenotypic switching, which may increase the incidence of atherosclerotic events. Aortic VSMC were extracted from 10 weeks old C57BL6 mice and incubated for 24 hr in adipocytes conditioned cell culture medium. Adipocytes were extracted from diabetic C57BL6 male mice fed with either a vegetal or an animal High-Fat-Diet (HFD) for 20 weeks. Migration of VSMC in response to conditioned media stimulations was significantly modulated compared to control. The most extended effects on VSMC were triggered by adipocytes from mice fed with animal HFD. These effects were concurrent with increased leptin concentrations and decreased adiponectin levels in conditioned media. A significant up-regulation of CD36 mRNA level was found in VSMC treated with adipocytes from HFD-fed mice. In conclusion, we have shown that the development of adipocyte-induced VSMC alterations is linked to diet fatty acid composition and the degree of metabolic alterations. The modulation of adipokine secretions in the adipose tissue that is linked to metabolic alterations may alter the physiology of VSMC and thus accelerate the development of metabolic-related vascular diseases.
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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".