ILs and MMPs Levels in Inflamed Human Dental Pulp: A Systematic Review
Bibliographic record
Abstract
A wide range of mediators are released from the pulp tissue because of bacterial invasion which causes inflammation. Interleukins (ILs) and matrix metalloproteinases (MMPs) have a leading role in initiating and spreading of inflammation because of their synergic action. Biomarkers such as ILs and MMPs can be identified via several methods, establishing the inflammatory response of the dental pulp. The aim of this systematic review is to evaluate the levels of ILs and/or MMPs in human dental pulp. PubMed, OVID, Cochrane, Scopus, Web of Science and Wiley online library databases were searched for original clinical studies. After applying inclusion and exclusion criteria, a quality assessment of studies was performed based on a modified Newcastle-Ottawa scale. In the review were included articles that evaluated the presence of ILs and/or MMPs in pulp tissue using enzyme-linked immunosorbent assay (ELISA) or western blot or multiplex assay. Six articles were included in the present synthesis. Although various diagnostic methods were used, statistically significant higher levels of ILs and/or MMPs were mostly found in the experimental groups compared to healthy pulp samples. The biomarkers studied can be a promising tool to evaluate pulp tissue health or even in pulpitis treatment.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".