Structural abnormalities in the temporalis musculo-aponeurotic complex in chronic muscular temporomandibular disorders
Bibliographic record
Abstract
Some forms of chronic pain are thought to be driven and maintained by nociceptive input, which can drive plasticity within nociceptive pathways. We have previously identified abnormalities along the entire nociceptive pathway in chronic myalgic temporomandibular disorders (mTMD), including the trigeminal nerves, brainstem pathways, and in the thalamus and somatosensory cortex. These data suggest that there is a peripheral nociceptive drive in mTMD, but the source of this nociceptive activity remains unknown. Here, our aim was to determine whether structural abnormalities exist in the muscles of mastication of patients with chronic mTMD. Specifically, we tested whether the volume of the temporalis muscle and its tendon-aponeurosis complex (TAC, a structure that dissipates forces in a muscle) in mTMD patients differ compared to age- and sex-matched controls. To do so, we segmented these structures on T1-weighted structural magnetic resonance images. We found that muscle volumes in mTMD were not different to controls. However, the mTMD group had significantly smaller volumes of the bilateral temporalis TAC, and thus a smaller TAC-to-muscle volume ratio. These findings were consistent across 2 independent cohorts of 17 mTMD patients, compared to 17 age- and sex-matched controls. We propose a model where reduced TAC-to-muscle ratio could result in a predisposition to muscle tissue injury. In sum, abnormalities of the temporalis muscles in mTMD supports our hypothesis that chronic mTMD pathophysiology may be related to peripheral nociceptive barrage originating from the muscles of mastication.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".