High-density lipoprotein metabolism in human apolipoprotein B<sub>100</sub>transgenic/brown adipose tissue deficient mice: a model of obesity-induced hyperinsulinemia
Bibliographic record
Abstract
Obese and diabetic humans display decreased plasma high-density lipoprotein cholesterol (HDL-C) concentrations and an increased risk for coronary heart disease. However, investigation on HDL metabolism in obesity with a particular emphasis on hepatic ATP-binding cassette transporter A1 (ABCA1), the primary factor for HDL formation, has not been well studied. Human apolipoprotein B(100) transgenic (hApoB(tg)) and brown adipose tissue deficient (BATless) mice were crossed to generate hApoB(tg)/BATless mice. Male and female hApoB(tg) and hApoB(tg)/BATless mice were maintained on either a regular rodent chow diet or a diet high in fat and cholesterol until 24 weeks of age. The hApoB(tg)/BATless mice that were fed a HF/HC diet became obese, developed hepatic steatosis, and had significantly elevated plasma insulin levels compared with their hApoB(tg) counterparts, but plasma concentrations of total cholesterol, HDL-C, triglycerides, and free fatty acids and lipoprotein distribution between genotypes were not significantly different. Hepatic expression of genes encoding HDL-modifying factors (e.g., scavenger receptor, class B, type I, hepatic lipase, lecithin:cholesterol acyltransferase, and phospholipid transfer protein) was either altered significantly or showed a trend of difference between 2 genotypes of mice. Importantly, hepatic protein levels of ABCA1 were significantly lowered by ∼35% in male obese hApoB(tg)/BATless mice with no difference in mRNA levels compared with hApoB(tg) counterparts. Despite reduced hepatic ABCA1 protein levels, plasma HDL-C concentrations were not altered in male obese hApoB(tg)/BATless mice. The result suggests that hepatic ABCA1 may not be a primary contributing factor for perturbations in HDL metabolism in obesity-induced hyperinsulinemia.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".