The kinin B<sub>1</sub>receptor antagonist SSR240612 reverses tactile and cold allodynia in an experimental rat model of insulin resistance
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Diabetes causes sensory polyneuropathy with associated pain in the form of tactile allodynia and thermal hyperalgesia which are often intractable and resistant to current therapy. This study tested the beneficial effects of the non-peptide and orally active kinin B(1) receptor antagonist SSR240612 against tactile and cold allodynia in a rat model of insulin resistance. EXPERIMENTAL APPROACH: Rats were fed with 10% D-glucose for 12 weeks and effects of orally administered SSR240612 (0.3-30 mg kg(-1)) were determined on the development of tactile and cold allodynia. Possible interference of SSR240612 with vascular oxidative stress and pancreatic function was also addressed. KEY RESULTS: Glucose-fed rats exhibited tactile and cold allodynia, increases in systolic blood pressure and higher plasma levels of insulin and glucose, at 12 weeks. SSR240612 blocked tactile and cold allodynia at 3 h (ID(50)=5.5 and 7.1 mg kg(-1), respectively) in glucose-fed rats but had no effect in control rats. The antagonist (10 mg kg(-1)) had no effect on plasma glucose and insulin, insulin resistance (HOMA index) and aortic superoxide anion production in glucose-fed rats. CONCLUSIONS AND IMPLICATIONS: We provide the first evidence that the B(1) receptors are involved in allodynia in an experimental rat model of insulin resistance. Allodynia was alleviated by SSR240612 most likely through a direct inhibition of B(1) receptors affecting spinal cord and/or sensory nerve excitation. Thus, orally active non-peptide B(1) receptor antagonists should have clinical therapeutic potential in the treatment of sensory polyneuropathy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.002 |
| 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".