The analgesic action of topical diclofenac may be mediated through peripheral NMDA receptor antagonism
Bibliographic record
Abstract
The analgesic mechanism underlying the efficacy of topical diclofenac in the treatment of musculoskeletal pain is incompletely understood. The present study investigated whether intramuscular injection of diclofenac (0.1mg/ml, approximately 340microM) could attenuate jaw-closer muscle nociceptor discharge and mechanical sensitization induced by activation of peripheral 5-hydroxytryptamine (serotonin) or excitatory amino acid receptors in anesthetized Sprague-Dawley rats. Diclofenac inhibited nociceptor discharge evoked by NMDA, but had no effect on nociceptor discharge evoked by 5-hydroxytryptamine or AMPA. Subsequent experiments revealed that diclofenac-mediated inhibition of NMDA-evoked nociceptor discharge was competitive. Intramuscular injection of 5-hydroxytryptamine, NMDA and AMPA also decreased nociceptor mechanical threshold, however, only the mechanical sensitization produced by NMDA was reversed by diclofenac. Co-administration of the proinflammatory prostaglandin PGE(2) did not alter the ability of diclofenac to significantly attenuate NMDA-evoked nociceptor discharge or NMDA-induced mechanical sensitization. Intramuscular injection of either diclofenac or the competitive NMDA receptor antagonist DL-2-amino-5-phosphonovalerate (50mM) alone could elevate nociceptor mechanical threshold for a 30min period post-injection. The present study indicates that in vivo, diclofenac can exert a selective, competitive inhibition of peripheral NMDA receptors at muscle concentrations achievable after topical administration of diclofenac containing preparations. This property may contribute to the analgesic effect of topical diclofenac when used for muscle pain.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".