Targeted inactivation of hepatic Abca1 causes profound hypoalphalipoproteinemia and kidney hypercatabolism of apoA-I
Bibliographic record
Abstract
Patients with Tangier disease exhibit extremely low plasma HDL concentrations resulting from mutations in the ATP-binding cassette, sub-family A, member 1 (ABCA1) protein. ABCA1 controls the rate-limiting step in HDL particle assembly by mediating efflux of cholesterol and phospholipid from cells to lipid-free apoA-I, which forms nascent HDL particles. ABCA1 is widely expressed; however, the specific tissues involved in HDL biogenesis are unknown. To determine the role of the liver in HDL biogenesis, we generated mice with targeted deletion of the second nucleotide-binding domain of Abca1 in liver only (Abca1(-L/-L)). Abca1(-L/-L) mice had total plasma and HDL cholesterol concentrations that were 19% and 17% those of wild-type littermates, respectively. In vivo catabolism of HDL apoA-I from wild-type mice or human lipid-free apoA-I was 2-fold higher in Abca1(-L/-L) mice compared with controls due to a 2-fold increase in the catabolism of apoA-I by the kidney, with no change in liver catabolism. We conclude that in chow-fed mice, the liver is the single most important source of plasma HDL. Furthermore, hepatic, but not extrahepatic, Abca1 is critical in maintaining the circulation of mature HDL particles by direct lipidation of hepatic lipid-poor apoA-I, slowing its catabolism by the kidney and prolonging its plasma residence time.
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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) | 0.001 | 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".