Sustained and repeated mouth opening leads to development of painful temporomandibular disorders involving macrophage/microglia activation in mice
Bibliographic record
Abstract
Temporomandibular disorder (TMD) is a set of heterogeneous musculoskeletal conditions involving the temporomandibular joint (TMJ) and/or the masticatory muscles. Up to 33% of the population has had at least 1 symptom of TMD with 5% to 10% of them requiring treatment. Common symptoms include limited jaw movement, joint sound, and pain in the orofacial area. Once TMD becomes chronic, it can be debilitating with comorbidities that greatly reduce one's overall quality of life. However, the underlying mechanism of TMD is unclear because of the multicausative nature of the disease. Here, we report a novel mouse model of TMD where a bite block was placed in between the upper and lower incisors such that the mouth was kept maximally open for 1.5 hours per day for 5 days. After sustained mouth opening, mice developed persistent orofacial mechanical allodynia and TMJ dysfunction. At the cellular level, we found masseter muscle dystrophy, and increased proteoglycan deposition and hypertrophic chondrocytes in the mandibular condyle. Increased F4/80 macrophages were also observed in the masseter muscles and the TMJ posterior synovium. We also found ATF3 neuronal injury and increased F4/80 macrophages in the trigeminal ganglia. Microglia activation was observed in the trigeminal subnucleus caudalis. Inhibiting macrophage and microglia activation with a colony stimulating factor-1 receptor inhibitor prevented the development of orofacial mechanical allodynia, but not TMJ dysfunction. This study suggests that mouth opening for an extended period during dental treatments or oral intubations may risk the development of chronic TMD and inflammation associated with macrophage and microglia in the tissue and trigeminal system contributes to the development of 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".