Comparative Analysis of the Anti-inflammatory Effects of E-MTA, Ketac-E, and Sealapex on Human Periodontal Ligament Stem Cells
Bibliographic record
Abstract
Background: Root Canal Treatments play a critical role in managing periapical and pulp diseases, but failure to control the inflammation may result in treatment failure. Newer developments have targeted anti-inflammatory bioactive sealers as potential contenders. The objective of this study was to explore the anti-inflammatory potential of Endoseal E-MTA (E-MTA), Ketac-Endo (Ketac-E), and Sealapex (S-apex) on cultured Human periodontal ligament stem cells. Methods: After Study approval (BMU-EC/06-2022) from Baqai Medical University Karachi, this study was conducted from September 2022 to February 2023. Three Sealers as commercially available products were used on the cultured hPDLSCs via in-vitro experiments and treated with serial concentrations of 20ul, 40ul, and 60ul respectively to perform MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide] cell viability assay. Expression profiling via Real Time-PCR of anti-inflammatory biometers was determined via RNA extract from 24h MTT assay due to its greater reproducibility. Data were subjected to statistical analysis (ANOVA Testing) to compare the effectiveness of each sealer using SPSS version 22 with a significant p-value<0.05. Results: E-MTA elicits a noticeably enhanced production of IL-10 (2.97-fold) and TGF-β (3.12-fold) levels than its parent compound MTA, demonstrating enhanced anti-inflammatory and immunomodulatory potential while Ketac-Endo and Sealapex showed lesser relative gene fold values Conclusion: It has been concluded that E-MTA exhibits more enhanced bioactivity and capacity to improve the RCT outcome due to reduced inflammation and increased tissue regeneration than Ketac-Endo and Sealapex.
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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 | 0.000 |
| 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) | 0.000 | 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".