High-fat diet reveals the impact of Sar1b defects on lipid and lipoprotein profile and cholesterol metabolism
Bibliographic record
Abstract
Biallelic pathogenic variants of the Sar1b gene cause chylomicron retention disease (CRD) whose central phenotype is the inability to secrete chylomicrons. Patients with CRD experience numerous clinical symptoms such as gastrointestinal, hepatic, neuromuscular, ophthalmic, and cardiological abnormalities. Recently, the production of mice expressing either a targeted deletion or mutation of Sar1b recapitulated biochemical and gastrointestinal defects associated with CRD. The present study was conducted to better understand little-known aspects of Sar1b mutations, including mouse embryonic development, lipid profile, and lipoprotein composition in response to high-fat diet, gut and liver cholesterol metabolism, sex-specific effects, and genotype-phenotype differences. Sar1b deletion and mutation produce a lethal phenotype in homozygous mice, which display intestinal lipid accumulation without any gross morphological abnormalities. On high-fat diet, mutant mice exhibit more marked abnormalities in body composition, adipose tissue and liver weight, plasma cholesterol, non-HDL cholesterol and polyunsaturated fatty acids than those on the regular Chow diet. Divergences were also noted in lipoprotein lipid composition, lipid ratios (serving as indices of particle size) and lipoprotein-apolipoprotein distribution. Sar1b defects significantly reduce gut cholesterol accumulation while altering key players in cholesterol metabolism. Noteworthy, variations were observed between males and females, and between Sar1b deletion and mutation phenotypes. Overall, mutant animal findings reveal the importance of Sar1b in several biochemical, metabolic and developmental processes.
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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".