Retinal plasma extravasation in streptozotocin‐diabetic rats mediated by kinin B<sub>1</sub>and B<sub>2</sub>receptors
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: We investigated whether or not kinin receptors play a role in diabetic blood-retinal barrier breakdown, which is a leading cause of vision loss. EXPERIMENTAL APPROACH: Blood-retinal barrier breakdown was quantified using Evans blue, and expression of kinin B(1) receptor mRNA was measured using quantitative reverse transcrition-PCR. Diabetic rats (streptozotocin (STZ), 65 mg kg(-1)) received a single intraocular injection of bradykinin (BK) or des-Arg(9)-BK, alone, or in combination with antagonists for B(1) (des-Arg(10)-Hoe140, R-715) and/or B(2) (Hoe140) receptors, given intraocularly or intravenously (i.v.). KEY RESULTS: In control rats, BK (0.1-10 nmol) dose-dependently increased plasma extravasation, which was inhibited by Hoe140 (0.2 nmol), whereas des-Arg(9)-BK (0.1 and 1 nmol) was without effect. B(1) receptor mRNA was markedly increased in retinas of diabetic rats, and this was prevented by N-acetyl-L-cysteine (1 g kg(-1) day(-1) for 7 days). Plasma extravasation in retinas of STZ-diabetic rats was higher than in controls and enhanced by des-Arg(9)-BK. Response to des-Arg(9)-BK was inhibited by intraocular or i.v. injection of B(1) receptor antagonists. Diabetes-induced plasma extravasation was inhibited only by a combination of des-Arg(10)-Hoe140 and Hoe 140 (100 nmol kg(-1), i.v. 15 min earlier) or by R-715 (1 micromol kg(-1), i.v.) injected daily for 7 days. CONCLUSIONS AND IMPLICATIONS: Kinin B(1) receptors are upregulated in retinas of STZ-diabetic rats through a mechanism involving oxidative stress. Both kinin B(1) and B(2) receptors contribute to increased plasma extravasation in diabetic retinopathy. Chronic inhibition of both kinin receptors, possibly with antioxidant adjuvants, may be a novel therapeutic strategy for diabetic retinopathy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".