Retinal and Nonocular Abnormalities in Cyp27a1Cyp46a1 Mice with Dysfunctional Metabolism of Cholesterol
Bibliographic record
Abstract
Cholesterol elimination from nonhepatic cells involves metabolism to side-chain oxysterols, which serve as transport forms of cholesterol and bioactive molecules modulating a variety of cellular processes. Cholesterol metabolism is tissue specific, and its significance has not yet been established for the retina, where cytochromes P450 (CYP27A1 and CYP46A1) are the major cholesterol-metabolizing enzymes. We generated Cyp27a1(-/-)Cyp46a1(-/-) mice, which were lean and had normal serum cholesterol and glucose levels. These animals, however, had changes in the retinal vasculature, retina, and several nonocular organs (lungs, liver, and spleen). Changes in the retinal vasculature included structural abnormalities (retinal-choroidal anastomoses, arteriovenous shunts, increased permeability, dilation, nonperfusion, and capillary degeneration) and cholesterol deposition and oxidation in the vascular wall, which also exhibited increased adhesion of leukocytes and activation of the complement pathway. Changes in the retina included increased content of cholesterol and its metabolite, cholestanol, which were focally deposited at the apical and basal sides of the retinal pigment epithelium. Retinal macrophages of Cyp27a1(-/-)Cyp46a1(-/-) mice were activated, and oxidative stress was noted in their photoreceptor inner segments. Our findings demonstrate the importance of retinal cholesterol metabolism for maintenance of the normal retina, and suggest new targets for diseases affecting the retinal vasculature.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".