Photodynamic Therapy with Verteporfin in a Rabbit Model of Corneal Neovascularization
Bibliographic record
Abstract
PURPOSE: To determine the efficacy of photodynamic therapy (PDT) with verteporfin (Visudyne; Novartis AG, Basel, Switzerland) for treatment of corneal neovascularization in a rabbit eye model. METHODS: Corneal neovascularization was induced in Dutch belted rabbits by placing an intrastromal silk suture near the limbus. Verteporfin was administered by intravenous injection at a dose of 1.5 mg/kg, and the pharmacokinetics of verteporfin distribution in the anterior segment or PDT-induced (laser energy levels 17, 50, and 150 J/cm(2)) regression of corneal blood vessels were then determined. To assess PDT-induced toxicity of the anterior segment, corneal and iris/ciliary body histology, and IOP were evaluated after PDT. RESULTS: Verteporfin accumulation in vascularized regions of the cornea and the iris/ciliary body tissue were time dependent and maximum levels achieved at 60 minutes after injection. In rabbits, PDT of corneal vessels using laser energy of 17 or 50 J/cm(2) resulted in 30% to 50% regression of corneal neovascularization; however, in these animals, a rapid regrowth of new blood vessels occurred between 3 and 5 days. In the rabbits receiving PDT using laser energies of 150 J/cm(2), the mean vessel regression was 56%. During the nine days of the laser therapy follow-up period, no vessel regrowth was observed in these rabbits. Histologic examination of the anterior segment after PDT (150 J/cm(2)) showed localized degeneration of the corneal blood vessels without observable change in other anterior segment structures. CONCLUSIONS: These results provide evidence that PDT can produce significant regression of neovascular corneal vessels with no observable toxicity to the anterior segments. However, the optimal laser energy necessary to induce long-term regression (150 J/cm(2)) was three times that used to treat choroidal neovascularization.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".