Insights on the role of cytokines in carious lesions
Bibliographic record
Abstract
Objectives: The dentin-pulp immune response to caries pathogenesis is still poorly understood due to the complexinterplay of the involving processes. The aim of this review was to explore the role of cytokines and its relevance inthe pathogenesis of dental caries. Results: Dental caries can result in a host inflammatory response in the dentalpulp, characterized by the accumulation of inflammatory cells leading to the release of inflammatory cytokinessuch as Interleukin-4 (IL-4), Interleukin (IL-6), Interleukin-8 (IL-8) and Tumor necrosis factor–a (TNF-a). IL-4seems to be correlated to the depth of carious lesions; IL-6 is strongly correlated to caries disease and is considereda potent biomarker; IL-8 can be a potent biomarker for both caries and other changes present in the pulp and,its release is correlated to TNF-a and IL-6; TNF-a plays an important role not only in caries progression, but alsoin other pathological processes. Conclusion: Specific mediators have a great potential to serve as biomarkersalluding to the presence and progress of caries disease, urging further investigations in the field. KEYWORDSBiomarkers; Cytokines; Dental caries; Dental pulp; Interleukins.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".