Lack of responsiveness to plant sterols in wild type C57BL/6J mice is due to increased HMG‐CoA reductase transcription and higher fractional cholesterol synthesis rate
Bibliographic record
Abstract
Although plant sterols (PS) are effective in reducing plasma cholesterol (C) in humans and various animal models, previous work suggests that wild type C57BL/6J mice do not respond to PS therapy despite reductions in intestinal cholesterol absorption. To explain this non‐responsiveness, we examined changes in hepatic HMG‐CoA reductase (HMG‐CoAr) expression and C synthesis in C57BL/6J mice. Mice (n = 10) were fed a high‐fat control diet or the control diet with 2% PS for 30 d in a randomized block design. Mice received an intraperitoneal injection of deuterium oxide 2h prior to sacrifice and whole‐body C synthesis was measured by deuterium incorporation. Although total C and non‐HDL C did not differ between treatments, PS consumption reduced ( P <0.05) plasma triglycerides by 29% compared to control (0.68±0.02 vs. 0.91±0.17 mmol/L). PS consumption increased hepatic HMG‐CoAr mRNA expression (2.7 fold of control, P <0.05) but did not affect ( P >0.05) HMG‐CoAr protein abundance. In agreement with HMG‐CoAr mRNA expression, PS consumption increased whole‐body fractional C synthesis rate compared to control (2.0±0.16 vs. 1.3±0.43 % day −1 ). HMG‐CoAr mRNA expression was positively correlated with whole‐body C synthesis (r = 0.61, P <0.05). The lack of response of plasma C to PS consumption in C57BL/6J mice is due to an upregulation of hepatic HMG‐CoAr mRNA expression and a compensatory increase in C synthesis. Funded by NSERC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".