cAMP induces ABCA1 phosphorylation activity and promotes cholesterol efflux from fibroblasts
Bibliographic record
Abstract
ATP-binding cassette transporter A1 (ABCA1) plays a crucial role in apoA-I lipidation, a key step in reverse cholesterol transport. cAMP induces apoA-I binding activity and promotes cellular cholesterol efflux. We investigated the role of the cAMP/protein kinase A (PKA) dependent pathway in the regulation of cellular cholesterol efflux. Treatment of normal fibroblasts with 8-bromo-cAMP (8-Br-cAMP) increased significantly apoA-I-mediated cholesterol efflux, with specificity for apoA-I, but not for cyclodextrin. Concomitantly, 8-Br-cAMP increased ABCA1 phosphorylation in a time-dependent manner. Maximum phosphorylation was reached in <10 min, representing a 260% increase compared to basal ABCA1 phosphorylation level. Forskolin, a known cAMP regulator, increased both cellular cholesterol efflux and ABCA1 phosphorylation. In contrast, H-89 PKA inhibitor reduced cellular cholesterol efflux by 70% in a dose-dependent manner and inhibited almost completely ABCA1 phosphorylation. To determine whether naturally occurring mutants of ABCA1 may affect its phosphorylation activity, fibroblasts from subjects with familial HDL deficiency (FHD, heterozygous ABCA1 defect) and Tangier disease (TD, homozygous/compound heterozygous ABCA1 defect) were treated with 8-Br-cAMP or forskolin. Cellular cholesterol efflux and ABCA1 phosphorylation were increased in FHD but not in TD cells. Taken together, these findings provide evidence for a link between the cAMP/PKA-dependent pathway, ABCA1 phosphorylation, and apoA-I mediated cellular cholesterol efflux.
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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 | 0.000 |
| 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".