A role for polyamines in retinal ganglion cell excitotoxic death
Bibliographic record
Abstract
Neuronal death due to excessive activation of N-methyl-d-aspartate (NMDA) receptors is a hallmark of neurodegenerative diseases. The polyamines: putrescine, spermine, and spermidine, bind to specific sites on the NMDA receptor and promote its activation, but their role in NMDA-induced neuronal death is ill defined. In this study, we characterized the role of polyamines in excitotoxic death of retinal ganglion cells (RGCs), a population of central neurons susceptible to NMDA-induced damage. Our data show that endogenous arginase I, the rate limiting enzyme for polyamine biosynthesis, is expressed in the intact, adult retina. Intraocular injection of NMDA visibly increased arginase I expression in Müller cells, the predominant glial cell-type in the mammalian retina. Inhibition of polyamine synthesis using di-fluoro-methyl-ornithine (DFMO) was markedly neuroprotective, while injection of exogenous polyamines in conjunction with NMDA exacerbated RGC death. Blockade of the polyamine binding sites on NMDA receptors using the non-competitive antagonist ifenprodil was neuroprotective, suggesting that polyamines contribute to excitotoxic death, at least partly, by binding to NMDA receptors. Importantly, we also demonstrate that NMDA leads to activation of both the Erk1/2 and PI3 K/Akt pathways, but only the PI3 K/Akt kinase was required for di-fluoro-methyl-ornithine-induced RGC survival. In summary, our study reveals that polyamines modulate neuronal death in the retina via different mechanisms that potentiate NMDA-triggered excitotoxicity.
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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) | 0.000 | 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 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".