Retinal iron homeostasis: The cellular roles of ceruloplasmin and hephaestin
Bibliographic record
Abstract
Ceruloplasmin and hephaestin are proteins that convert ferrous (Fe 2+) to ferric (Fe3+) iron, thereby facilitating cellular iron export. Although it is known that ceruloplasmin and hephaestin are important for normal retinal iron transport, their roles in the individual retinal cell types, and in the directionality of retinal iron flow, are unclear. As dysregulation of retinal iron transport contributes to retinal diseases such as the rare genetic disease aceruloplasminemia and the more common disease age-related macular degeneration, it is important to study and better understand retinal iron transport. To investigate the roles of ceruloplasmin and hephaestin in retinal cells we used post-mortem human eyes, systemic and conditional knockout mice, primary cultured cells and immortalized retinal cell lines. We found that in humans, ceruloplasmin plays an important role in retinal pigment epithelial (RPE) cells and in the neural retina, as loss of ceruloplasmin resulted in iron accumulation in the neural retina and very high iron accumulation in the RPE cells along with RPE pathology and melanosome degradation. Using mouse models we observed that loss of both ceruloplasmin and hephaestin results in RPE cell iron accumulation, although not to the degree expected. Additionally, loss of ceruloplasmin and hephaestin from both RPE and photoreceptors results in retinal iron redistribution. Both ferroxidases participate in iron export from Muller cells, and both are more important for iron export from the retina than for iron import into the retina. Our results have demonstrated that ceruloplasmin and hephaestin are important in several retinal cell types, and have changed the way that we think about retinal iron transport and its accumulation in RPE cells.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".