2,3,4′,5-tetrahydroxystilbene-2-<i>O</i>-β-<scp>d</scp>-glycoside attenuates atherosclerosis in apolipoprotein E-deficient mice: role of reverse cholesterol transport
Bibliographic record
Abstract
The aim of this study was to evaluate the potential effects of 2,3,4′,5-tetrahydroxystilbene-2-O-β-d-glucoside (TSG) on the development of atherosclerotic plaque in ApoE−/− mice, and explore the mechanisms involved. Our data showed that after 8 weeks of treatment, TSG ameliorated serum levels of total cholesterol, triglyceride, and low density lipoprotein cholesterol, and increased serum levels of high density lipoprotein cholesterol in ApoE−/− mice. TSG suppressed hepatic steatosis, the formation of atherosclerotic lesions, and the formation of macrophage foam cells in ApoE−/− mice. Moreover, TSG improved the expressions of hepatic SR-BI, ABCG5, and CYP7A1, and up-regulated the protein expressions of aortic ABCA1 and ABCG1. An in-vitro study showed that TSG promoted macrophage cholesterol efflux and increased the protein expressions of ABCA1 and ABCG1. Our findings provide evidence for a positive role of TSG in preventing atherosclerosis by promoting reverse cholesterol transport. These effects may be achieved by stimulating cholesterol efflux through ABCA1 and ABCG1, promoting SR-BI-mediated cholesterol uptake in the liver, increasing secretion of cholesterol into bile by ABCG5, and improving cholesterol metabolism by the CYP7A1 pathway. In addition, antioxidative and anti-inflammatory effects of TSG may also contribute to its inhibitory effects on atherosclerosis. Further study is needed to investigate whether other potential mechanisms are involved in TSG-mediated atheroprotection.
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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) | 0.000 | 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 | 0.001 |
| 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".