Reactive oxygen species can be traced locally and systemically in apical periodontitis: A systematic review
Bibliographic record
Abstract
OBJECTIVES: The aim of this systematic review was to summarize the existing evidence on the local production and systemic traces of reactive oxygen species (ROS) in apical periodontitis (AP). DESIGN: A search of MEDLINE-PubMed and EMBASE was conducted up to January 12 of 2021 to identify studies in 6 different languages. Eligibility was evaluated and data were extracted from the eligible studies following the predefined objective. The Newcastle-Ottawa Scale was used for quality assessment of the included studies. RESULTS: After screening, 21 papers met the inclusion criteria. Six studies were about systemic oxidative stress, 14 studies examined local production of reactive oxygen species and one studied both. ROS modulate cell signalling and cause oxidant imbalance locally at the site of AP. Cell signalling leads to a pro-inflammatory response, activation of MMPs and formation and progression of the AP lesion. Simultaneously, these oxidative stress biomarkers are also found in blood and saliva of subjects with AP. CONCLUSIONS: Understanding the mechanism of ROS generation, involved in chronic inflammation, can provide us with important information to enhance local and systemic healing and possibly improve diagnostic tools. Future research considerations would be to use antioxidants to accelerate the return to oxidative balance.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| 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".