Islet Cholesterol Accumulation Due to Loss of ABCA1 Leads to Impaired Exocytosis of Insulin Granules
Bibliographic record
Abstract
OBJECTIVE: The ATP-binding cassette transporter A1 (ABCA1) is essential for normal insulin secretion from β-cells. The aim of this study was to elucidate the mechanisms underlying the impaired insulin secretion in islets lacking β-cell ABCA1. RESEARCH DESIGN AND METHODS: Calcium imaging, patch clamp, and membrane capacitance were used to assess the effect of ABCA1 deficiency on calcium flux, ion channel function, and exocytosis in islet cells. Electron microscopy was used to analyze β-cell ultrastructure. The quantity and distribution of proteins involved in insulin-granule exocytosis were also investigated. RESULTS: We show that a lack of β-cell ABCA1 results in impaired depolarization-induced exocytotic fusion of insulin granules. We observed disturbances in membrane microdomain organization and Golgi and insulin granule morphology in β-cells as well as elevated fasting plasma proinsulin levels in mice in the absence of β-cell ABCA1. Acute cholesterol depletion rescued the exocytotic defect in β-cells lacking ABCA1, indicating that elevated islet cholesterol accumulation directly impairs granule fusion and insulin secretion. CONCLUSIONS: Our data highlight a crucial role of ABCA1 and cellular cholesterol in β-cells that is necessary for regulated insulin granule fusion events. These data suggest that abnormalities of cholesterol metabolism may contribute to the impaired β-cell function in diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".