Relationship between the salivary concentration of matrix metalloproteinases 8 and 20 and severe early childhood caries
Bibliographic record
Abstract
BACKGROUND: Dental caries is initiated through mineral dissolution by bacterial acids and collagen degradation by endogenous proteolytic enzymes, mainly collagenolytic matrix metalloproteinases (MMPs). OBJECTIVES: The present research aimed to evaluate the relationship between severe early childhood caries (S-ECC) and salivary MMP-8 and MMP-20 concentrations. MATERIAL AND METHODS: Fifty children aged 36-60 months were assigned to either the caries-free (control) group or the S-ECC group. Standard clinical examinations were performed, and approx. 1 mL of expectorated unstimulated whole saliva was collected from all participants. In the S-ECC group, the sampling was repeated 3 months after restorative treatment. All samples were analyzed for the salivary concentrations of MMP-8 and MMP-20, using the enzyme-linked immunosorbent assay (ELISA). Statistical analysis employed the t test, the Mann-Whitney U test, the χ2 test, Fisher's exact test, and the paired samples t test. The level of significance was set at 0.05. RESULTS: At baseline, the subjects in the S-ECC group presented with significantly elevated levels of MMP-8 as compared to the control group. However, the salivary concentration of MMP-20 did not exhibit a significant difference between the 2 groups. A significant reduction occurred in the levels of MMP-8 and MMP-20 3 months after restorative treatment in the S-ECC group. CONCLUSIONS: The salivary levels of MMP-8 and MMP-20 were significantly affected by dental restorative treatment in children. Furthermore, MMP-8 was observed to be a better indicator of the dental caries status than MMP-20.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".