Influence of atorvastatin and carboxymethylated glucan on the serum lipoprotein profile and MMP activity of mice with lipemia induced by poloxamer 407
Bibliographic record
Abstract
The effects of atorvastatin and carboxymethylated β-glucan (CMG) on the lipoprotein-cholesterol (LP-C) and lipoprotein-triglyceride (LP-TG) fractions and subfractions at the early stage of murine hyperlipidemia, and its pleiotropic anti-inflammatory effects, were studied. Atorvastatin and CMG were administered in ICR male mice with acute lipemia induced with a single injection of poloxamer 407 (P-407). A novel small-angle X-ray scattering method for the determination of fractional and subfractional composition of LP-C and LP-TG was used. In P-407-treated animals, there was a drastic increase of total cholesterol and especially TG. Atorvastatin decreased both the total cholesterol and TG, but not to control levels. CMG primarily decreased TG and was not as potent as atorvastatin. P-407 increased atherogenic LDL-C (IDL-C and LDL(1-3)-C subfractions) and very low-density lipoprotein-C (VLDL-C) (VLDL(1-2)-C and VLDL(3-5)-C subfractions) fractions, with an increase of the total anti-atherogenic HDL-C fraction (HDL(2)-C subfraction). Atorvastatin treatment of lipemia was followed by a decrease in the total LP-C, total LDL-C (LDL(1-3)-C subfraction), and the LDL(1-3)-TG subfraction. Additionally, atorvastatin treatment resulted in an increase in the serum matrix metalloproteases activity both in control and P-407-treated mice. In general, high-dose atorvastatin therapy exerts its lipid-lowering and pleiotropic effects in the early stages of acute lipemia induced in mice by treatment with P-407.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".