AB006. The co-receptor CD36 as a target in regulation of subretinal inflammation
Bibliographic record
Abstract
Subretinal inflammation plays a critical role in retinal degenerative diseases. Although activated macrophages have been shown to play a key role in the progression of retinopathies and specifically in age-related macular degeneration, little is known about the mechanisms involved in the loss of photoreceptors leading to vision impairment. In our study on retinal damages induced by photo-oxidative stress, we have observed that CD36-deficient mice featured less subretinal macrophage accumulation with attenuated photoreceptor degeneration compared to wild-type (WT) mice. Treatment with CD36-selective azapeptide ligand (labelled MPE-001) as modulator of the inflammatory environment of the retina reduced subretinal macrophage/activated microglia accumulation with preservation of photoreceptor layers and function assessed by ERG in WT, in a CD36-dependent manner. The azapeptide modulated the transcriptome of subretinal macrophage/activated microglia by reducing pro-inflammatory markers. In isolated macrophages, the CD36-selective azapeptide induced dissociation of the CD36-TLR2/6 heterodimer complex (using FRET) altering the TLR2 signaling pathway, thus decreasing NF-KB activation and inflammasome activity. The azapeptide also incurred cytoprotection against photoreceptor apoptosis elicited by activated macrophages. These findings suggest that the azapeptide as ligand of co-receptor CD36 decreases the inflammatory response by modulating CD36-TLR2/6 complex signaling pathway in macrophages, and suggests its potential application in the treatment of retinal degenerative diseases.
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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) | 0.011 | 0.003 |
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".