Dysfunctional peroxisomal lipid metabolisms and their ocular manifestations
Bibliographic record
Abstract
Retina is rich in lipids and dyslipidemia causes retinal dysfunction and eye diseases. In retina, lipids are not only important membrane component in cells and organelles but also fuel substrates for energy production. However, our current knowledge of lipid processing in the retina are very limited. Peroxisomes play a critical role in lipid homeostasis and genetic disorders with peroxisomal dysfunction have different types of ocular complications. In this review, we focus on the role of peroxisomes in lipid metabolism, including degradation and detoxification of very-long-chain fatty acids, branched-chain fatty acids, dicarboxylic acids, reactive oxygen/nitrogen species, glyoxylate, and amino acids, as well as biosynthesis of docosahexaenoic acid, plasmalogen and bile acids. We also discuss the potential contributions of peroxisomal pathways to eye health and summarize the reported cases of ocular symptoms in patients with peroxisomal disorders, corresponding to each disrupted peroxisomal pathway. We also review the cross-talk between peroxisomes and other organelles such as lysosomes, endoplasmic reticulum and mitochondria.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".