The influence of repeated administration of poloxamer 407 on serum lipoproteins and protease activity in mouse liver and heart
Bibliographic record
Abstract
The effects of repeated administration of poloxamer 407 (P-407) on lipoprotein-cholesterol (LP-C) and lipoprotein-triglyceride (LP-TG) fractions and subfractions, as well as the effect on liver and heart proteases, were studied. Repeated administration of P-407 to male CBA mice resulted in a model of atherosclerosis with increased diastolic blood pressure; there was a drastic increase in total serum cholesterol and especially TG. A novel small-angle X-ray scattering method for the determination of the fractional and subfractional composition of LP-C and LP-TG was used. In chronically P-407-treated mice, P-407 significantly increased atherogenic low-density lipoprotein C (LDL-C) fractions, as well as intermediate-density lipoprotein C (IDL-C), and LDL₁₋₃-C subfractions, and very-low-density lipoprotein-C (VLDL-C) fractions, as well as VLDL₁₋₂-C and VLDL₃₋₅-C subfractions), to a lesser extent, the total anti-atherogenic high-density lipoprotein C (HDL-C) fraction, as well as HDL₂-C and HDL₃-C subfractions. Additionally, we demonstrated an increase in the serum chitotriosidase activity, without significant changes in serum matrix metalloprotease (MMP) activity. Morphological changes observed in P-407-treated mice included atherosclerosis in the heart and storage syndrome in the liver macrophages. P-407 significantly increased the activity of cysteine, aspartate proteases, and MMPs in the heart, and only the activity of cathepsin B and MMPs in the liver of mice. Thus, repeated administration of P-407 to mice induced atherosclerosis secondary to sustained dyslipidemia and formation of foamy macrophages in liver, and also modulated the activity of heart and liver proteases.
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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) | 0.000 | 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) | 0.000 | 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".