Photoreceptor-induced RPE phagolysosomal maturation defects in Stargardt-like Maculopathy (STGD3)
Bibliographic record
Abstract
For many neurodegenerative disorders, expression of a pathological protein by one cell type impedes function of other cell types, which in turn contributes to the death of the first cell type. In transgenic mice modelling Stargardt-like (STGD3) maculopathy, human mutant ELOVL4 expression by photoreceptors is associated with defects in the underlying retinal pigment epithelium (RPE). To examine how photoreceptors exert cytotoxic effects on RPE cells, transgenic ELOVL4 (TG1-2 line; TG) and wild-type (WT) littermates were studied one month prior (preclinical stage) to onset of photoreceptor loss (two months). TG photoreceptor outer segments presented to human RPE cells are recognized and internalized into phagosomes, but their digestion is delayed. Live RPE cell imaging pinpoints decreased numbers of acidified phagolysomes. In vivo, master regulator of lysosomal genes, transcription factor EB (TFEB), and key lysosomal enzyme Cathepsin D are both unaffected. Oxidative stress, as ruled out with high-resolution respirometry, does not play a role at such an early stage. Upregulation of CRYBA1/A3 and phagocytic cells (microglia/macrophages) interposed between RPE and photoreceptors support adaptive responses to processing delays. Impaired phagolysosomal maturation is observed in RPE of mice expressing human mutant ELOVL4 in their photoreceptors prior to photoreceptor death and associated vision loss.
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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) | 0.000 | 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) | 0.002 | 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".