Interstitial glutamate concentration is elevated in the masseter muscle of myofascial temporomandibular disorder patients.
Bibliographic record
Abstract
AIM: To determine if myofascial temporomandibular disorder (TMD) pain patients have elevated interstitial concentrations of glutamate in the masseter muscle. METHODS: Thirteen patients (3 men, 10 women) diagnosed with myofascial TMD pain and 10 (2 men, 8 women) age-matched healthy controls participated in a single microdialysis session. Microdialysis was performed in the patients in the most painful point of the masseter muscle, while in the healthy subjects a standardized point in the muscle was chosen. Two microdialysis samples were collected over 40-minute epochs. A blood sample was also taken for analysis of plasma glutamate concentration. Numeric rating scale (NRS) scores of pain intensity and unpleasantness, McGill Pain Questionnaire data, pain drawing areas, pressure pain thresholds, pressure pain tolerances, maximum voluntary bite force, and maximum voluntary mouth opening were collected as secondary measurements. RESULTS: The median concentration of glutamate in the masseter muscle of the myofascial TMD pain patients (7.5 ± 2.6 ΜM) was significantly higher (P < .023, Mann-Whitney test) than the concentration in healthy controls (0.5 ± 0.4 ΜM). There were, however, no significant correlations between glutamate concentrations in the masseter muscle and NRS pain scores. Plasma concentrations of glutamate were similar in patients and healthy controls. CONCLUSIONS: The present study demonstrates a marked increase in interstitial glutamate concentration in the masseter muscle of myofascial TMD pain patients. These novel findings suggest that peripheral glutamate could be involved in the pathophysiology of myofascial TMD pain.
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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 | 0.000 | 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".