Quantitative iTRAQ Analysis of Retinal Ganglion Cell Degeneration after Optic Nerve Crush
Bibliographic record
Abstract
Retinal ganglion cells (RGCs) are central nervous system (CNS) neurons that transmit visual information from the retina to the brain. Apoptotic RGC degeneration causes visual impairment that can be modeled by optic nerve crush. Neuronal apoptosis is also a salient feature of CNS trauma, ischemia (stroke), and diseases of the CNS such as Alzheimer's, Parkinson's, multiple sclerosis, and amyotrophic lateral sclerosis. Optic nerve crush induces the apoptotic cell death of ∼ 70% of RGCs within the first 14 days after injury. This model is particularly attractive for studying adult neuron apoptosis because the time-course of RGC death is well established and axon regeneration within the myelinated optic nerve can be concurrently evaluated. Here, we performed a large scale iTRAQ proteomic study to identify and quantify proteins of the rat retina at 1, 3, 4, 7, 14, and 21 days after optic nerve crush. In total, 337 proteins were identified, and 110 were differentially regulated after injury. Of these, 58 proteins were upregulated (>1.3 ×), 46 were downregulated (<0.7 ×), and 6 showed both positive and negative regulation over 21 days, relative to normal retinas. Among the differentially expressed proteins, Thymosin-β4 showed an early upregulation at 3 days, the time-point that immediately precedes the induction of RGC apoptosis after injury. We examined the effect of exogenous Thymosin-β4 administration on RGC death after optic nerve injury. Intraocular injections of Thymosin-β4 significantly increased RGC survival by ∼ 3-fold compared to controls and enhanced axon regeneration after crush, demonstrating therapeutic potential for CNS insults. Overall, our study identified numerous proteins that are differentially regulated at key time-points after optic nerve crush, and how the temporal profiles of their expression parallel RGC death. This data will aid in the future development of novel therapeutics to promote neuronal survival and regeneration in the adult CNS.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".