The effect of exercise training on upregulation of molecular markers of bile acid metabolism in the liver of ovariectomized rats fed a cholesterol-rich diet.
Bibliographic record
Abstract
BACKGROUND: Small heterodimer partner (SHP) is an important transcriptional factor involved in the regulation of glucose, lipid, and bile acid metabolism in the liver. SHP has been reported to be down-regulated in ovariectomized (Ovx) mice and up-regulated by estrogens suggesting a link between estrogens and SHP. The aim of the present study was to determine the effects of exercise training on SHP and key molecular markers of cholesterol and bile acid homeostasis in Ovx rats under cholesterol feeding. METHODS: Our main experimental group was composed of Ovx rats fed a high-cholesterol diet (Ovx-Chol) that was compared to a group of Ovx rats fed a standard diet (Ovx-SD) and a group of sham operated rats fed the cholesterol diet (Sham-Chol). These three groups of Ovx and sham rats were subdivided into either voluntary wheel running (Tr) or sedentary (Sed) groups for 5 weeks. The mRNA expression of all genes was measured by quantitative real-time polymerase chain reaction. RESULTS: Liver total cholesterol levels were not affected by exercise training in any of the experimental conditions. Cholesterol feeding in both sham and Ovx rats resulted in significantly higher hepatic cholesterol accumulation than in Ovx-SD (P < 0.001). Hepatic low density lipoprotein receptor (LDL-R) involved in cholesterol uptake from circulation was not influenced by training. A main effect of training was, however, found for transcripts of SHP and cholesterol 7 alpha-hydroxylase (CYP7A1, P < 0.050). CYP7A1 is the main gene involved in bile acid biosynthesis from cholesterol. CONCLUSION: These results suggest that voluntary wheel running modulates cholesterol metabolism in Ovx animals through up-regulation of SHP and bile acid formation.
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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".