Cholesterol kinetics and intestinal sterol transporter gene expression in response to corn fiber oil and its constituents in hamsters
Bibliographic record
Abstract
The objective of this study was to evaluate the cholesterol‐lowering mechanisms of corn fiber oil (CFO), ferulate phytostanyl esters (FPE) and parent compounds including sitostanol and ferulic acid in hamsters. Seventy male golden Syrian hamsters were randomly assigned to six experimental diets for 4 weeks. 1) Control diet without cholesterol 2) Control diet plus 0.1% (w/w) cholesterol. The remaining four groups were given 0.1 % cholesterol diet with: 3) 10% (w/w) CFO 4) 0.5% (w/w) sitostanol, 5) 0.23% (w/w) ferulic acid and 6) 0.73% (w/w) FPE. At the end of four weeks of dietary intervention, plasma cholesterol levels, cholesterol absorption and synthesis as well as mRNA expression of sterol transporters were assessed. Supplementation with corn fiber oil decreased (p< 0.0001) plasma total cholesterol levels by 29% as compared with cholesterol‐control, while feruloyl sitostanol (p< 0.02) and sitostanol (p< 0.02) reduced cholesterolemia by 15% and 14% respectively. Moreover, CFO (p ≤ 0.02) and sitostanol (p ≤ 0.02) decreased cholesterol absorption by 24% compared to cholesterol‐control group. While only moderate changes in mRNA expression of intestinal enterocyte sterol transporters were observed, CFO and sitostanol showed 1.5‐ to 2‐ fold up‐regulation of mRNA expression of ATP‐binding cassette G5 (ABCG5) and ABCG8. Results of present study suggest that CFO and sitostanol‐induced decreases in cholesterol absorption may be due to up‐regulation of intestinal enterocyte efflux sterol transporters such as ABCG5 and ABCG8 in hamsters. Funded by 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) | 0.001 | 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".