ABCA1 in adipocytes regulates adipose tissue lipid content, glucose tolerance, and insulin sensitivity
Bibliographic record
Abstract
Adipose tissue contains one of the largest reservoirs of cholesterol in the body. Adipocyte dysfunction in obesity is associated with intracellular cholesterol accumulation, and alterations in cholesterol homeostasis have been shown to alter glucose metabolism in cultured adipocytes. ABCA1 plays a major role in cholesterol efflux, suggesting a role for ABCA1 in maintaining cholesterol homeostasis in the adipocyte. However, the impact of adipocyte ABCA1 on adipose tissue function and glucose metabolism is unknown. Our aim was to determine the impact of adipocyte ABCA1 on adipocyte lipid metabolism, body weight, and glucose metabolism in vivo. To address this, we used mice lacking ABCA1 specifically in adipocytes (ABCA1(-ad/-ad)). When fed a high-fat, high-cholesterol diet, ABCA1(-ad/-ad) mice showed increased cholesterol and triglyceride stores in adipose tissue, developed enlarged fat pads, and had increased body weight. Associated with these phenotypic changes, we observed significant changes in the expression of genes involved in cholesterol and glucose homeostasis, including ldlr, abcg1, glut-4, adiponectin, and leptin. ABCA1(-ad/-ad) mice also demonstrated impaired glucose tolerance, lower insulin sensitivity, and decreased insulin secretion. We conclude that ABCA1 in adipocytes influences adipocyte lipid metabolism, body weight, and whole-body glucose homeostasis.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".