Comparison of glutamate-evoked pain between the temporalis and masseter muscles in men and women
Bibliographic record
Abstract
Pain in myofascial temporomandibular disorder (TMD) can affect both the masseter and temporalis muscles. Glutamate injection into the masseter muscle evokes pain that is greater in men than in women and this pain is attenuated by co-injection of the N-methyl-d-aspartate (NMDA) receptor antagonist ketamine (10 mmol/L) in men. Animal studies suggested that pain induced by peripheral NMDA receptor activation could differ between the temporalis and masseter muscles and between men and women. The study aims were to investigate differences in glutamate-evoked pain between these muscles and the effectiveness of ketamine to attenuate glutamate-evoked pain in both genders. Pain and mechanical sensitivity were induced in 2 sessions of an experiment in 14 women and 16 men by repeated injections of glutamate (0.5 mol/L) with and without ketamine (20 mmol/L) into the masseter and temporalis muscles. Two injections were applied into the same masseter muscle and 2 injections into the same anterior temporalis muscle at each session. Visual analogue scale (VAS) pain intensities and pain drawing areas were assessed. Glutamate-evoked pain and pain drawing area were significantly greater from the temporalis muscle than from the masseter muscle (P<.02) in both genders. Women reported significantly greater glutamate-evoked masseter muscle pain than men (P<.03). Co-injection of ketamine, at higher dose than previously used, was equally effective in attenuating glutamate-evoked pain from both muscles in both genders (P<.01). The current findings indicate that the characteristics of pain generated by intramuscular injection of glutamate vary for different masticatory muscles and may be partially generated through activation of peripheral NMDA receptors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".