Origin of fundus hyperautofluorescent spots and their role in retinal degeneration in a mouse model of Goldmann-Favre syndrome
Bibliographic record
Abstract
Goldmann-Favre syndrome, also known as enhanced S-cone syndrome, is an inherited retinal degeneration disease in which a gain of photoreceptor cell types results in retinal dysplasia and degeneration. Although microglia have been implicated in the pathogenesis of many neurodegenerative diseases, the fundamental role of these cells in this disease is unknown. In the current study, sequential analyses suggest that microglia are recruited and appear after outer nuclear layer folding. By crossing rd7 mice (a model for hereditary retinal degeneration owing to Nr2e3 mutation) with mice carrying the macrophage Fas-induced apoptosis (Mafia) transgene, we generated double-mutant mice and studied the role of the resident retinal microglia. Microglial cells in these double-mutant mice express enhanced green fluorescent protein (EGFP) and a suicide gene that can trigger Fas-mediated apoptosis via systemic treatment with AP20187 (FK506 dimerizer). We demonstrated that more than 80% of the EGFP+ cells in retinas from rd7/rd7;Tg/Tg mice express Iba-1 (a microglial marker), and resident microglia are still present in the retina because AP20187 does not cross the blood-brain barrier. Hence, only circulating bone marrow (BM)-derived microglia are depleted. Depletion of circulating BM-derived microglia accelerates retinal degeneration in rd7 mice. An increased number of autofluorescent (AF) spots is a consequence of resident microglia proliferation, which in turn establishes an inflammatory cytokine milieu via the upregulation of IL-1β, IL-6 and TNFα expression. This inflammation is likely to accelerate retinal degeneration. This study not only identifies inflammation as a crucial step in the pathogenesis of retinal degeneration, but also highlights the involvement of specific cytokine genes that could serve as future treatment targets in retinal degenerations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".