Inhibitory effect of a novel bradykinin B<sub>1</sub> receptor antagonist, R-954, on enhanced vascular permeability in type 1 diabetic mice
Bibliographic record
Abstract
The morbidity and mortality associated with type 1 diabetes are essentially related to the micro- and macrovascular complications that develop over time and lead to several diabetic complications, including hypertension, atherosclerosis, and retinopathy, as well as coronary and renal failure. Normally absent in physiological conditions, the bradykinin B1 receptor (BKB1-R) was recently found to be overexpressed in pathological conditions, including type 1 diabetes. In the present study, we evaluated the effect of the new BKB1-R antagonist, R-954 (Ac-Orn-[Oic2, alpha-MePhe5, D-betaNal7, Ile8]desArg9-bradykinin, on the increase in vascular permeability in streptozotocin (STZ)-diabetic mice. The capillary permeability to albumin was measured by quantifying the extravasation of albumin-bound Evans blue dye in selected target tissues (liver, pancreas, duodenum, ileum, spleen, heart, kidney, stomach, skin, muscle, and thyroid gland). Acute single administration of R-954 (300 microg/kg, i.v.) to type 1 diabetic mice 4 weeks after STZ significantly inhibited the enhanced vascular permeability in most tissues. These data provide further experimental evidence for the implication of BKB1-R in the enhanced vascular permeability associated with type 1 diabetes.
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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".