Increase of circulating cholesterol in vitamin D deficiency is linked to reduced vitamin D receptor activity via the Insig‐2/SREBP‐2 pathway
Bibliographic record
Abstract
SCOPE: Individuals deficient in vitamin D are more likely to have higher circulating cholesterol levels and cardiovascular diseases. However, the underlying mechanisms are still unclear. METHODS AND RESULTS: A cross-sectional survey, animal study, and in vitro experiments were conducted to investigate the effect and mechanisms of vitamin D deficiency on endogenous cholesterol metabolism. We demonstrated that vitamin D deficiency was positively associated with an increase of total serum cholesterol and low-density lipoprotein cholesterol levels in northern Chinese individuals. The vitamin D deficiency-induced increase of cholesterol concentration was mainly due to enhanced cholesterol biosynthesis rather than reduced catabolism. Under vitamin D deficiency, the transcriptional activity of vitamin D receptor (VDR) was decreased, leading to the downregulation of insulin-induced gene-2 (Insig-2) expression and thus its inhibitory role on sterol regulatory element-binding protein 2 activation; 3-hydroxy-3-methylglutaryl-coenzyme A reductase expression was accordingly increased. Vitamin D3 was protective against vitamin D deficiency-induced cholesterol increase by maintaining the transcriptional activity of VDR and Insig-2 expression. CONCLUSION: Vitamin D deficiency is associated with the increase of circulating cholesterol in the people of northern China by enhancing hepatic cholesterol biosynthesis, which was linked to the reduction of transcriptional activity of VDR.
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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 | 0.001 | 0.001 |
| 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".