Methods for Experimental Manipulations after Optic Nerve Transection in the Mammalian CNS
Bibliographic record
Abstract
Retinal ganglion cells (RGCs) are CNS neurons that output visual information from the retina to the brain, via the optic nerve. The optic nerve can be accessed within the orbit of the eye and completely transected (axotomized), cutting the axons of the entire RGC population. Optic nerve transection is a reproducible model of apoptotic neuronal cell death in the adult CNS 1-4. This model is particularly attractive because the vitreous chamber of the eye acts as a capsule for drug delivery to the retina, permitting experimental manipulations via intraocular injections. The diffusion of chemicals through the vitreous fluid ensures that they act upon the entire RGC population. Viral vectors, plasmids or short interfering RNAs (siRNAs) can also be delivered to the vitreous chamber in order to infect or transfect retinal cells 5-12. The high tropism of Adeno-Associated Virus (AAV) vectors is beneficial to target RGCs, with an infection rate approaching 90% of cells near the injection site 6, 7, 13-15. Moreover, RGCs can be selectively transfected by applying siRNAs, plasmids, or viral vectors to the cut end of the optic nerve 16-19 or injecting vectors into their target the superior colliculus 10. This allows researchers to study apoptotic mechanisms in the injured neuronal population without confounding effects on other bystander neurons or surrounding glia. RGC apoptosis has a characteristic time-course whereby cell death is delayed 3-4 days postaxotomy, after which the cells rapidly degenerate. This provides a window for experimental manipulations directed against pathways involved in apoptosis. Manipulations that directly target RGCs from the transected optic nerve stump are performed at the time of axotomy, immediately after cutting the nerve. In contrast, when substances are delivered via an intraocular route, they can be injected prior to surgery or within the first 3 days after surgery, preceding the initiation of apoptosis in axotomized RGCs. In the present article, we demonstrate several methods for experimental manipulations after optic nerve transection.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.110 | 0.054 |
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".