<p>Safety of anti-VEGF treatments in a diabetic rat model and retinal cell culture</p>
Bibliographic record
Abstract
Purpose: To analyze the safety of different concentrations of anti-VEGF on retinal cells. Methods: Non-diabetic and streptozotocin (STZ)-induced diabetic rats received intravitreal rat anti-VEGF injections that had final vitreous concentrations of 0, 0.0625, 0.125 (clinical dose), and 0.25 mg/mL. Rats were also injected with the clinical dose of ranibizumab. TUNEL assay was performed on sectioned eyes to evaluate apoptotic cells. In vitro, rat retinal cell cultures were exposed to 0, 0.0625, 0.125 (clinical dose), and 0.25 mg/mL of ranibizumab for 48 and 72 hrs. Cellular metabolic activity was measured by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, necrosis by lactate dehydrogenase (LDH), and apoptosis by cell death enzyme-linked immunosorbent assay (ELISA). Results: Diabetic rats had a significant increase ( p <0.03) in apoptotic cell death at half the clinical dose, at the clinical dose, and at double the clinical dose. In vitro, MTT showed a significant decrease ( p <0.04) in cellular metabolic activity at the clinical dose and double the clinical dose compared to control at 48 and 72 hrs. LDH showed a significant increase ( p <0.04) in necrosis at the clinical dose and double the clinical dose compared to control at 48 and 72 hrs. ELISA showed a significant increase ( p <0.04) in apoptosis at half the clinical dose, at the clinical dose, and double the clinical dose, compared to control at 48 and 72 hrs. Conclusions: Anti-VEGF treatment may be potentially detrimental to the retina by decreasing cellular metabolic activity and increasing cytotoxicity of retinal cells. The results provide a cautionary note to monitor both the retina and optic nerve status in patients undergoing frequent injections. Keywords: diabetic macular edema, diabetes, retina, anti-VEGF, ranibizumab, safety, cytotoxicity
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".