Biomedical Advances in ABCA1 Transporter: From Bench to Bedside
Bibliographic record
Abstract
ATP-binding cassette transporter A1 (ABCA1) has been identified as the molecular defect in Tangier disease. It is biochemically characterized by absence of high-density lipoprotein cholesterol (HDL-C) in the circulation, resulting in the accumulation of cholesterol in lymphoid tissues. Accumulation of cholesterol in arteries is an underlying cause of atherosclerosis, and HDL-C levels are inversely associated with the presence of atherosclerotic cardiovascular disease (ASCVD). ABCA1 increases HDL-C levels by driving the generation of new HDL particles in cells, and cellular cholesterol is removed in the process of HDL generation. Therefore, pharmacological strategies that promote the HDL biogenic process by increasing ABCA1 expression and activity have been intensively studied to reduce ASCVD. Many ABCA1-upregulating agents have been developed, and some have shown promising effects in pre-clinical studies, but no clinical trials have met success yet. ABCA1 has long been an attractive drug target, but the failed clinical trials have indicated the difficulty of therapeutic upregulation of ABCA1, as well as driving us to: improve our understanding of the ABCA1 regulatory system; to develop more specific and sophisticated strategies to upregulate ABCA1 expression; and to search for novel druggable targets in the ABCA1-dependent HDL biogenic process. In this review, we discuss the beginning, recent advances, challenges and future directions in ABCA1 research aimed at developing ABCA1-directed therapies for ASCVD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".