Induction of apolipoprotein A-I gene expression by black seed ( <i>Nigella sativa</i> ) extracts
Bibliographic record
Abstract
CONTEXT: Black seed [Nigella sativa L. (Ranunculaceae)] has been shown in animal models to lower serum cholesterol levels. OBJECTIVES: In order to determine if extracts from black seed have any effects on high-density lipoprotein (HDL), we characterized the effects of black seed extract on apolipoprotein A-I (apo A-I) gene expression, the primary protein component of HDL. MATERIALS AND METHODS: Hepatocytes (HepG2) and intestinal cells (Caco-2) were treated with black seed extracts, and Apo A-I, peroxisome proliferator-activated receptor α (PPARα), and retinoid-x-receptor α (RXRα) were measured by Western blot analysis. Apo A-I mRNA levels were measured by quantitative real-time polymerase chain reaction and apo A-I gene transcription was measured by transient transfection of apo A-I reporter plasmids. RESULTS: Extracts from black seeds significantly increased hepatic and intestinal apo A-I secretion, as well as apo A-I mRNA and gene promoter activity. This effect required a PPARα binding site in the apo A-I gene promoter. Treatment of the extract with either heat or trypsin had no effect on its ability to induce apo A-I secretion. Treatment with black seed extract induced PPARα expression 9-fold and RXRα expression 2.5-fold. Furthermore, the addition of PPARα siRNA but not a control siRNA prevented some but not all the positive effects of black seed on apo A-I secretion. DISCUSSION: Black seed extract is a potent inducer of apo A-I gene expression, presumably by enhancing PPARα/RXRα expression. CONCLUSIONS: We conclude that black seed may have beneficial effects in treating dyslipidemia and coronary heart disease.
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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".