Treg and Th17 cells in inflammatory periapical disease: a systematic review
Bibliographic record
Abstract
Abstract: The process involved in periapical lesions, which occur as an outcome of pulpal necrosis, is regulated by the immune system including regulatory T cells (Treg) and T helper 17 cell (Th17) responses. The objective of this study was to conduct a frequency systematic review to determine the presence of Treg/Th17 responses and the influence of these cells in the progression of chronic inflammatory periapical lesions in humans. A systematic computerized search was carried out in Pubmed, Medline, Web of Science and Scopus electronic databases from their date of inception through the first week of May 2017. In addition, the reference lists of the included articles and the grey literature were hand-searched. Articles that evaluated the presence and influence of Treg/Th17 in the progression of human periapical lesions were included. Study selection and the quality assessment of the included articles (using the Newcastle-Ottawa scale) were carried out by two authors. Fifty-seven titles/abstracts were screened and eight studies met the eligibility criteria and were included in this systematic review. The included studies showed large variation in the type of periapical lesion assessed, mean age, age range, type of experiment and findings regarding the participation of Th17 and Treg in the status of inflammatory periapical lesions. The studies showed the involvement of Treg in the modulation of the inflammatory response in radicular cysts and periapical granulomas. This systematic review highlights the relationship between Treg and Th17 acting in a subtle balance inhibiting or promoting the progression of human periapical lesions.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 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".