High-dose supplemental selenite to male Syrian hamsters fed hypercholesterolaemic diets alters<i>Ldlr</i>,<i>Abcg8</i>and<i>Npc1l1</i>mRNA expression and lowers plasma cholesterol concentrations
Bibliographic record
Abstract
The aim of the present study was to elucidate possible cholesterol-lowering mechanism(s) of high-dose supplemental Se in the form of selenite, a known hypocholesterolaemic agent. Male Syrian hamsters (four groups, ten per group) were fed semi-purified diets for 4 weeks containing 0.1 % cholesterol and 15 % saturated fat with selenite corresponding to varying levels of Se: (1) Se 0.15 parts per million (ppm), control diet; (2) Se 0.85 ppm; (3) Se 1.7 ppm; (4) Se 3.4 ppm. Lipids were measured in the bile, faeces, liver and plasma. The mRNA expression of several known regulators of cholesterol homeostasis (ATP-binding cassette transporters g5 (Abcg5) and g8 (Abcg8), 7-hydroxylase, 3-hydroxy-3-methylglutaryl-coenzyme A reductase, LDL receptor (LdLr) and Nieman-Pick C1-like 1 protein (Npc1l1)) were measured in the liver and/or jejunum. Oxysterols including 24-(S)-hydroxycholesterol, 25-hydroxycholesterol and 27-hydroxycholesterol (27-OHC) were measured in the liver. Significantly lower total plasma cholesterol concentrations were observed in hamsters consuming the low (0.85 ppm) and high (3.4 ppm) Se doses. The two highest doses of Se resulted in decreased plasma LDL-cholesterol concentrations and increased mRNA levels of hepatic Abcg8, Ldlr and jejunal Ldlr. Higher hepatic 27-OHC and TAG concentrations and lower levels of jejunal Npc1l1 mRNA expression were noted in the 1.7 and 3.4 ppm Se-treated hamsters. Overall, Se-induced tissue changes in mRNA expression including increased hepatic Abcg8 and Ldlr, increased jejunal Ldlr and decreased jejunal Npc1l1, provide further elucidation regarding the hypocholesterolaemic mechanisms of action of Se in the form of selenite.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".