Supragingival Microbiota Alterations in Individuals With Sleep Bruxism: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: Sleep bruxism (SB) is an oral behaviour associated to jaw clenching or grinding of the teeth. Its aetiology is most likely multifactorial; however, recent studies suggested that SB is associated with activation of the sympathetic nervous system. Dysbiosis of the oral microbiota is linked to oral and systemic diseases. The relationship between supragingival microbiota and SB remains unexplored. OBJECTIVE: This study aimed to investigate the association between SB and the composition of the supragingival microbiota. METHODS: Nineteen metabolically and orally healthy subjects were recruited. After SB diagnosis, supragingival microbiota samples were collected. Microbial DNA was extracted and subjected to 16S rRNA gene sequencing. Amplicon sequence variant (ASV) analysis method was used to correlate the composition of supragingival microbiota with SB. RESULTS: Bacterial diversity decreased in the SB group. ASV_200 (Actinomyces) and ASV_94 (Morococcus) were enriched in the SB individuals, whereas ASV_405 (Morococcus) was enriched in the controls. The role of the decreased bacterial diversity as well as the enrichment of specific ASV in the mechanism explaining the genesis of SB remain to be determined. CONCLUSION: The differences in the composition of the supragingival microbiota may lead to the assessment of important questions in the fields of oral microbiota composition and sleep medicine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".