Delivery of Ciliary Neurotrophic Factor via Lentiviral-Mediated Transfer Protects Axotomized Retinal Ganglion Cells for an Extended Period of Time
Bibliographic record
Abstract
Ciliary neurotrophic factor (CNTF) has recently been demonstrated to be one of the most promising neurotrophic factors to improve both the survival and regeneration of injured retinal ganglion cells (RGCs). In the present study, we used optic nerve transection as an in vivo model to evaluate the effectiveness of a self-inactivating, replication-deficient lentiviral-mediated transfer of human ciliary neurotrophic factor (SIN-PGK-CNTF) on the survival of axotomized adult rat RGCs. Counts of dextran-fluorescein isothiocyanate conjugated (D-FITC)-retrogradely labeled RGCs revealed that the percentage of RGCs was drastically reduced (<90% cell death) 21 days after optic nerve transection. Retinal sections stained with X-gal revealed that intravitreal injection of the control LacZ-expressing lentiviral vector (LV-LacZ) resulted in the transduction of RGCs and retinal pigment epithelium (RPE) cells. A single intravitreal injection of LV-CNTF at the time of axotomy significantly enhanced RGC survival at 14 and 21 days postaxotomy compared to controls. These results demonstrate for the first time that rapid and prolonged delivery of CNTF using lentiviral-mediated gene transfer to the retina is an effective treatment for rescuing axotomized RGCs for an extended period of time. These results suggest that early and continuous administration of CNTF could serve as a potential treatment for retinal disorders involving optic neuropathy and RGC injury such as in glaucoma.
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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 | 0.001 |
| 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".