Ocular Application of the Kinin B1 Receptor Antagonist LF22-0542 Inhibits Retinal Inflammation and Oxidative Stress in Streptozotocin-Diabetic Rats
Bibliographic record
Abstract
PURPOSE: Kinin B(1) receptor (B(1)R) is upregulated in retina of Streptozotocin (STZ)-diabetic rats and contributes to vasodilation of retinal microvessels and breakdown of the blood-retinal barrier. Systemic treatment with B(1)R antagonists reversed the increased retinal plasma extravasation in STZ rats. The present study aims at determining whether ocular application of a water soluble B(1)R antagonist could reverse diabetes-induced retinal inflammation and oxidative stress. METHODS: Wistar rats were made diabetic with STZ (65 mg/kg, i.p.) and 7 days later, they received one eye drop application of LF22-0542 (1% in saline) twice a day for a 7 day-period. The impact was determined on retinal vascular permeability (Evans blue exudation), leukostasis (leukocyte infiltration using Fluorescein-isothiocyanate (FITC)-coupled Concanavalin A lectin), retinal mRNA levels (by qRT-PCR) of inflammatory (B(1)R, iNOS, COX-2, ICAM-1, VEGF-A, VEGF receptor type 2, IL-1β and HIF-1α) and anti-inflammatory (B(2)R, eNOS) markers and retinal level of superoxide anion (dihydroethidium staining). RESULTS: Retinal plasma extravasation, leukostasis and mRNA levels of B(1)R, iNOS, COX-2, VEGF receptor type 2, IL-1β and HIF-1α were significantly increased in diabetic retinae compared to control rats. All these abnormalities were reversed to control values in diabetic rats treated with LF22-0542. B(1)R antagonist also significantly inhibited the increased production of superoxide anion in diabetic retinae. CONCLUSION: B(1)R displays a pathological role in the early stage of diabetes by increasing oxidative stress and pro-inflammatory mediators involved in retinal vascular alterations. Hence, topical application of kinin B(1)R antagonist appears a highly promising novel approach for the treatment of diabetic retinopathy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".