URB597, an inhibitor of fatty acid amide hydrolase, reduces hyperalgesia in diabetic rats
Bibliographic record
Abstract
Diabetic rats display increased pain responses after injection of formalin into the paw or thermal stimulation of the tail, suggesting the presence of hyperalgesia. In this study, we investigated the efficacy of URB597 (0.1, 0.3, and 0.5 mg/kg, i.p.), an inhibitor of endocannabinoids metabolism, on 2 models of experimental hyperalgesia in streptozotocin (STZ)-induced diabetic rats. Animals were divided into control, URB597-treated control (0.1, 0.3, and 0.5 mg/kg), diabetic, and URB597-treated diabetic (0.1, 0.3, and 0.5 mg/kg) groups. Formalin and tail-flick tests were performed 4 and 8 weeks after the onset of hyperglycemia, respectively. Diabetes caused significant hyperalgesia during these tests. URB597 (0.3 and 0.5 mg/kg) reversed chemical and thermal hyperalgesia in diabetic rats. Administration of URB597 at a dose of 0.1 mg/kg did not alter pain-related behaviors in control and diabetic groups compared with those of the respective control groups. URB597 treatment did not affect body weight or plasma glucose level of treated animals compared with nontreated animals. This study shows that increasing endocannabinoid neurotransmission with URB597 displays efficacy in chemical and thermal models of diabetic hyperalgesia. It also suggests that URB597 is a promising tool for treatment of painful diabetic neuropathy.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".