Macrophage ATP-Binding Cassette Transporter A1 Overexpression Inhibits Atherosclerotic Lesion Progression in Low-Density Lipoprotein Receptor Knockout Mice
Bibliographic record
Abstract
BACKGROUND: ATP-binding cassette transporter A1 (ABCA1) is a key regulator of cellular cholesterol and phospholipid transport. Previously, we have shown that inactivation of macrophage ABCA1 induces atherosclerosis in low-density lipoprotein receptor knockout (LDLr-/-) mice. However, the possibly beneficial effects of specific upregulation of macrophage ABCA1 on atherogenesis are still unknown. METHODS AND RESULTS: Chimeras that specifically overexpress ABCA1 in macrophages were generated by transplantation of bone marrow from human ABCA1 bacterial artificial chromosome (BAC) transgenic mice into LDLr-/- mice. Peritoneal macrophages isolated from the ABCA1 BAC --> LDLr-/- chimeras exhibited a 60% (P=0.0006) increase in cholesterol efflux to apolipoprotein AI. To induce atherosclerosis, the mice were fed a Western-type diet containing 0.25% cholesterol and 15% fat for 9, 12, and 15 weeks, allowing analysis of effects on initial lesion development as well as advanced lesions. No significant effect of macrophage ABCA1 overexpression was observed on atherosclerotic lesion size after 9 weeks on the Western-type diet (245+/-36x10(3) microm2 in ABCA1 BAC --> LDLr-/- mice versus 210+/-20x10(3) microm2 in controls). However, after 12 weeks, the mean atherosclerotic lesion area in ABCA1 BAC --> LDLr-/- mice remained only 164+/-15x10(3) microm2 (P=0.0008) compared with 513+/-56x10(3) microm2 in controls (3.1-fold lower). Also, after 15 weeks on the diet, lesions in mice transplanted with ABCA1 overexpressing bone marrow were still 1.6-fold smaller (393+/-27x10(3) microm2 compared with 640+/-59x10(3) microm2 in control transplanted mice; P=0.0015). CONCLUSIONS: ABCA1 upregulation in macrophages inhibits the progression of atherosclerotic lesions.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".