Microglia-derived Pronerve Growth Factor Promotes Photoreceptor Cell Death via p75 Neurotrophin Receptor
Bibliographic record
Abstract
Reports implicating microglia-derived nerve growth factor (NGF) during programmed cell death in the developing chick retina led us to investigate its possible role in degenerative retinal disease. Freshly isolated activated retinal microglia expressed high molecular weight forms of neurotrophins including that of nerve growth factor (NGF), brain-derived neurotrophic factor, neurotrophin-3, and neurotrophin-4. Conditioned media from cultured retinal microglia (MGCM) consistently yielded a approximately 32-kDa NGF-reactive band when supplemented with bovine serum albumin (BSA) or protease inhibitors (PI); and promoted cell death that was suppressed by NGF immunodepletion in a mouse photoreceptor cell line (661w). The approximately 32 kDa protein was partially purified (MGCM/p32) and was highly immunoreactive with a polyclonal anti-pro-NGF antibody. Both MGCM/p32 and recombinant pro-NGF protein promoted cell death in 661w cultures. Increased levels of pro-NGF mRNA and protein were observed in the RCS rat model of retinal dystrophy. MGCM-mediated cell death was reversed by p75NTR antiserum in p75NTR(+)/trkA(-) 661w cells. Our study shows that a approximately 32 kDa pro-NGF protein released by activated retinal microglia promoted degeneration of cultured photoreceptor cells. Moreover, our study suggests that defective post-translational processing of NGF might be involved in photoreceptor cell loss in retinal dystrophy.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".