Phytosterols induce changes in hepatic protein expression patterns and increase cholesterol biosynthesis and sterol efflux in a hypercholesterolemic animal model
Bibliographic record
Abstract
Although phytosterols (PS) modulate intestinal cholesterol metabolism, the role of PS on hepatic sterol trafficking is not known. The objective of this study was to identify hepatic molecular targets responding to oral PS in hamsters (n = 8) fed 0.25% cholesterol diets with or without 2% PS for 28 d. Consumption of PS reduced ( P <0.002) plasma total cholesterol (7.8±0.5 vs. 5.3±0.4 mmol/L) vs control. Increased hepatic sterol efflux was suggested by higher LXRβ ( P = 0.06, 1.4 fold of control) and ABCG5 ( P <0.03, 1.4 fold of control) expression. High sterol fecal output was obersved in PS fed animals. A compensatory increase in fractional absorption of [3, 4]‐ 13 C cholesterol (67.5‰ vs 47.6‰; P<0.02) and 3.7 fold increase (P=0.02) in fractional cholesterol synthesis was also noted in PS animals. Similarly, PS increased ( P <0.01) HMGCoA‐R expression to 1.4 fold of control. While PS increased the cytosolic precursor form of SREBP2 ( P <0.001) by 3.9 fold, the nuclear active form of SREBP2 was reduced ( P <0.005) 2.4 fold relative to control, confirmed in vitro in HepG2 cells treated with PS. This differential regulation might reflect high intracellular levels of both C synthesis intermediates and PS, thereby interfering with normal SREBP2 processing. These data confirm that PS directly affects the expression of hepatic proteins regulating cholesterol trafficking, important for lowering blood cholesterol. Funding: NSERC.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".