Beneficial effect of 3,4,5,6-tetrahydroxyxanthone on dyslipidemia in apolipoprotein E-deficient mice
Bibliographic record
Abstract
Previous investigations have shown that decreased expression of angiopoietin-like protein 3 (Angptl3) is protective against dyslipidemia in atherosclerosis. The present study was conducted to test the effect of 3,4,5,6-tetrahydroxyxanthone, a xanthone compound, on dyslipidemia in apolipoprotein E-deficient (ApoE-/-) mice. Forty mice were randomly divided into 4 groups (n = 10): control group (C57BL/6J mice), ApoE-/-mice group, and two groups of ApoE-/- mice treated with 3,4,5,6-tetrahydroxyxanthone (10 or 30 mg/kg per day). Eight weeks after treatment, lipid levels in the blood and liver, expression of hepatic Angptl3, and adipose tissue lipoprotein lipase (LPL) were determined. Treatment with 3,4,5,6-tetrahydroxyxanthone (10 or 30 mg/kg) significantly decreased plasma and hepatic total cholesterol and triglyceride concentrations, increased plasma high-density lipoprotein cholesterol, and significantly downregulated expression of Angptl3 mRNA and protein concomitantly with upregulated expression of LPL mRNA. In addition, T0901317 (a liver X receptor ligand) caused elevated expression of hepatic Angptl3 mRNA and protein, and the effect of T0901317 was also abrogated by 3,4,5,6-tetrahydroxyxanthone in vivo and in vitro. The present results suggest that the beneficial effect of 3,4,5,6-tetrahydroxyxanthone on dyslipidemia may be related to reduced expression of Angptl3.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".