SYM‐2081 A Kainate Receptor Antagonist Reduces Allodynia And Hyperalgesia In A Freeze Injury Model Of Neuropathic Pain
Bibliographic record
Abstract
Cold‐freeze injury at −4 degrees C to the rat sciatic nerve produces mechanical allodynia and thermal hyperalgesia [M.A. Kleive, P.S. Jungbluth, J.A. Uhlenkamp, K.C. Kajander, Cold injury to rat sciatic nerve induces thermal hyperalgesia or analgesia, 8th World Congress on Pain, Vancouver, BC, Canada, August 1996 (Abstract).]. The NMDA receptor, an excitatory amino acid (EAA) receptor, appears to be involved in the development of allodynia and hyperalgesia following nerve injury. The role, if any, of the kainate receptor, another EAA receptor, remains unknown. In the current study, we evaluated whether (2S,4R)‐4‐methylglutamic acid (SYM‐2081), a recently developed kainate receptor antagonist, attenuates increased responsiveness following cold injury to the sciatic nerve. During baseline testing, Sprague‐Dawley rats were evaluated for frequency of withdrawal from van Frey filaments and latency of withdrawal from a radiant thermal source. Animals were then anesthetized, the left sciatic nerve was exposed, and the nerve was cooled to −4 degrees C for 15 min (n = 24). For control rats (n = 24), all procedures were identical except that the nerve was maintained at 37 degrees C. Testing resumed on the third day following surgery. On the fifth post‐operative day, SYM‐2081 (150 or 100 mg/kg), fentanyl citrate (0.04 mg/kg) or vehicle was injected intraperitoneally. Injury to the rat sciatic nerve induced a significant increase in withdrawal frequency and a significant decrease in withdrawal latency (ANOVA, p < 0.05). SYM‐2081 and fentanyl significantly reduced these responses (p < 0.05). These results suggest that kainate and opioid receptors are involved in the mechanical allodynia and thermal hyperalgesia that develop following cold injury to the sciatic nerve.
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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 | 0.002 | 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 | 0.000 |
| 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".