Glutamate-evoked pain and mechanical allodynia in the human masseter muscle
Bibliographic record
Abstract
The present study examined the effect of peripheral administration of the excitatory amino acid (EAA) glutamate on the intensity of perceived pain and pressure pain thresholds (PPTs) in healthy young women (n=17) and men (n=18). Two injections separated by 25 min of 0.2 ml, 1.0M glutamate into the masseter muscle produced significantly higher scores of pain on 0-10 cm visual analogue scales (VAS) in women than in men (analysis of variance, ANOVA: P<0.001). There was no significant difference between the VAS scores for the first and the second injections in either men or women. The PPTs determined in the masseter muscle were significantly reduced following the first injection and further significantly reduced after the second injection (ANOVA: P<0.001). Furthermore, the PPTs were reduced to a similar extent in both women and men (maximum 44-56%), suggesting that gender did not influence the process of sensitization. There were no significant difference in VAS scores or PPTs between women taking oral contraceptives (n=9) and those who did not (n=8) (ANOVAs: P=0.709, P=0.153). It is concluded that the VAS scores produced by intramuscular administration of 1.0M glutamate may reflect a gender-dependent activation of nociceptive pathways which, in part, may be mediated through peripheral EAA receptors. The reduction of PPTs in the masseter muscle following administration of glutamate in a concentration of 1.0M may reflect allodynia to mechanical stimuli. This process of sensitization was not gender-dependent. The present results suggest that injection of 1.0M glutamate into the masseter muscle may provide a useful experimental method to test sensitization and efficacy of peripheral EAA receptor antagonists in human subjects.
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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) | 0.000 | 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) | 0.002 | 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".