Cholesterol Accumulation by Macrophages Impairs Phagosome Maturation
Bibliographic record
Abstract
Macrophages are key to the pathogenesis of atherosclerosis. They take up and store excessive amounts of cholesterol associated with modified low density lipoprotein, eventually becoming foam cells that display altered immune responsiveness. We studied the effects of cholesterol accumulation on phagosome formation and maturation, using lipid transport antagonists and cholesterol transport-deficient mutants. In macrophages treated with U18666A, a transport antagonist that prevents cholesterol exit from late endosomes/lysosomes, the early stages of maturation proceeded normally; phagosomes acquired Rab5, phosphatidylinositol 3-phosphate, and EEA1 and merged with LAMP-containing vesicles. However, fusion with lysosomes was impaired. Rab7, which is required for phagolysosome formation, was acquired by phagosomes but remained inactive. Maturation was also studied in fibroblasts from Niemann-Pick type C individuals that have defective cholesterol transport. Transfection of FcgammaIIA receptors was used to confer phagocytic capability to these fibroblasts. Niemann-Pick type C phagosomes failed to fuse with lysosomes, whereas wild type fibroblasts formed normal phagolysosomes. These findings indicate that cholesterol accumulation can have a detrimental effect on phagosome maturation by impairing the activation of Rab7, sequestering it and its effectors in cholesterol-enriched multilamellar compartments.
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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) | 0.001 | 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 | 0.001 | 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".