Role of socioeconomic factors and interkingdom crosstalk in the dental plaque microbiome in early childhood caries
Bibliographic record
Abstract
SUMMARY Early childhood caries (ECC) is influenced by microbial and host factors, including social, behavioral, and oral health. In this cross-sectional study, we analyzed interkingdom dynamics in the dental plaque microbiome and its association with host variables. The samples collected from the preschool children underwent 16S rRNA and ITS1 rRNA gene sequencing. The questionnaire data were analyzed for social determinants of oral health. The results indicated a significant enrichment of Streptococcus mutans and Candida dubliniensis in ECC samples, in contrast to Neisseria oralis in caries-free children. Our interkingdom correlation analysis revealed that Candida dubliniensis was strongly correlated with both Neisseria bacilliformis and Prevotella veroralis in ECC. Additionally, ECC showed significant associations with host variables, including oral health status, age, place of residence, and mode of childbirth. This study provides empirical evidence associating the oral microbiome with socioeconomic and behavioral factors in relation to ECC, offering insights for developing targeted prevention strategies. HIGHLIGHTS Characterized interkingdom association between cariogenic species of genus Neisseria and Candida Both bacterial and fungal species are important for caries status prediction using artificial intelligence Socioeconomic index is associated with caries status and caries-associated microbial markers
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".