Antiscarring effect of intraoperative bevacizumab in experimental glaucoma filtration surgery
Bibliographic record
Abstract
PURPOSE: To determine the effects of bevacizumab and mitomycin C alone and in combination on intraocular pressure and the scarring process after modified glaucoma filtration surgery in rabbits. METHODS: The rabbits underwent modified glaucoma filtration surgery and were allocated into three groups to receive intraoperative treatment with subconjunctival bevacizumab (group A), mitomycin C and subconjunctival bevacizumab (group B), or mitomycin C (group C). Intraocular pressure was measured immediately preoperatively and on postoperative days 8, 14, 17, 21, 26, and 30. The scarring process was assessed 30 days after surgery by tissue section using hematoxylin and eosin, Masson's trichrome, and picrosirius. Expression of vascular endothelial growth factor (VEGF) was assessed by immunohistochemical analyses. All analyses were performed by a masked observer. RESULTS: Animals in group A had higher intraocular pressure than those in groups B and C (p<0.01). Intraocular pressure did not differ significantly between groups B and C. The amount of fibrosis was similar with all stains used: group A had the highest level of fibrosis compared with groups B and C (p>0.05). There was less VEGF expression in group A than in groups B and C (p<0.01). Groups B and C did not differ in VEGF expression. CONCLUSION: Mean intraocular pressure and fibrosis were lower in animals receiving bevacizumab in combination with mitomycin C but did not differ from values in animals receiving mitomycin C alone. Inhibition of VEGF was greater when bevacizumab was used alone than when bevacizumab was combined with mitomycin C.
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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) | 0.001 | 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".