Quantitative Retinal Protein Analysis after Optic Nerve Transection Reveals a Neuroprotective Role for Hepatoma-Derived Growth Factor on Injured Retinal Ganglion Cells
Bibliographic record
Abstract
PURPOSE: Retinal ganglion cell (RGC) degeneration is an important cause of visual impairment and can be modeled by optic nerve transection, which causes the death of 90% of RGCs within 14 days postaxotomy. We performed a proteomic study to identify and quantify proteins in the rat retina after optic nerve transection. Our goal was to isolate potential targets for therapeutic intervention to prevent RGC degeneration. METHODS: iTRAQ proteomics was used to analyze adult rat retinas at 1, 3, 4, 7, 14, and 21 days postaxotomy. Hepatoma-derived growth factor (HDGF), a target identified by iTRAQ, was delivered by intraocular injections. Wortmannin or PD98059 were coadministered with HDGF to determine if the protective effects of HDGF are dependent on PI3 kinase or MAP kinase activity, respectively. RESULTS: At a false-discovery rate of 5%, 216 proteins were identified by iTRAQ proteomics, 71 of which showed changes in expression (<0.7× or >1.3×) at one time point after injury: 52 proteins had expression peaks, whereas 19 showed downward expression spikes. Levels of GAPDH did not change after axotomy. Among these differentially expressed proteins was HDGF. HDGF delivery significantly increased RGC survival compared with control treatments, and increased Akt phosphorylation in the retina at 24 hours after intraocular injection. RGC rescue by HDGF was dependent on both MAP kinase and PI3 kinase activity in the retina. CONCLUSIONS: We have identified numerous proteins that are differentially regulated at key time points after axotomy, and how the temporal profiles of their expression parallel RGC death. Using these data, we showed that HDGF is a potent neuroprotective factor for injured adult RGCs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".