Effect of orthodontic force on dental pulp histomorphology and tissue factor expression:
Bibliographic record
Abstract
OBJECTIVES: To evaluate the effects of orthodontic force on histomorphology and tissue factor expression in the dental pulp. MATERIALS AND METHODS: Two reviewers comprehensively and systematically searched the literature in the following databases: Latin American and Caribbean Health Sciences, Embase, Cochrane, PubMed, Scopus, Web of Science, and Grey literature (Google Scholar, OpenGrey, and ProQuest) up to September 2020. According to the Population, Intervention, Comparison, Outcomes, Studies criteria, randomized clinical trials (RCTs) and observational studies that evaluated the effects of orthodontic force on dental pulp were included. Case series/reports, laboratory-based or animal studies, reviews, and studies that did not investigate the association between orthodontic force and pulpal changes were excluded. Newcastle-Ottawa Scale and Cochrane risk-of-bias tool were used to assess the risk of bias. The overall certainty level was evaluated with the Grading of Recommendations Assessment, Development and Evaluation tool. RESULTS: 26 observational studies and five RCTs were included. A detailed qualitative analysis of articles showed a wide range of samples and applied methodologies concerning impact of orthodontic force on the dental pulp. The application of orthodontic force seems to promote several pulpal histomorphological changes, including tissue architecture, cell pattern, angiogenesis, hard tissue deposition, inflammation, and alteration of the expression levels of 14 tissue factors. CONCLUSIONS: Although the included articles suggest that orthodontic forces may promote histomorphological changes in the dental pulp, due to the very low-level of evidence obtained, there could be no well-supported conclusion that these effects are actually due to orthodontic movement. Further studies with larger samples and improved methods are needed to support more robust conclusions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 teacher head, 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".