Fluid dynamics is a majorly neglected aspect to be studied in root canal irrigation. The fundamental rule to understand mechanics is to observe patterns of flow during the process. Thus, this work is conducted to do a systemic assessment of the in-vitro and ex-vivo based studies to evaluate the effect of various parameters on the irrigant flow and apical pressure on using a manual syringe needle for root canal irrigation. The literature search was conducted through libraries such as PubMed (Medline), CINAHL, Embase, Scopus and other hand literature from Google Scholar, the British medical library etc. The systematic review was reported following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. As they include studies that were in-vitro and ex-vivo based, the risk of bias of the selected articles was assessed using a customized tool based on the previous literature and parameters evaluated in the studies included. The literature search resulted in 101 items of which 19 records were included in this review. Results reported that multiple factors and parameters were assessed to evaluate the flow and apical pressures on using manual syringe needle irrigation. Present systematic review gives insights in-depth about the irrigation dynamics of manual syringe needle irrigation. Besides, it is inconclusive to compile a single factor or a single parameter contributing to the enhanced irrigant flow and least apical pressures.

Introduction: This systematic review investigates the crucial need for solvent use in root canal retreatment, as it effectively removes filling materials, reduces apical debris extrusion, and alleviates postoperative pain, ultimately enhancing treatment success. The review aims to assess the success rates, compare outcomes, explore benefits and drawbacks, and identify subgroups where solvent use may be more effective during root canal retreatment. Materials and Methods: The search was performed in PubMed Central, Scopus, Cochrane, LILAC, ScienceDirect, Google Search, Web of Science, and manually using the search items alone and in combination by means of PUBMED search builder. The studies were assessed for eligibility according to the eligibility criteria by two independent reviewers. Groups containing solvent with nonsolvent groups and randomized control trials were included and in vitro studies, retrospective studies, and animal studies were excluded from the study. Quality assessment was performed using the risk of bias (RoB) 2.0 tool. Results: Out of the 596 articles obtained, 14 were shortlisted for full-text reading and finally two articles were included in the study. The studies were assessed for quality, and data were extracted in a tabulated form. Overall RoB is low, but due to the lack of homogeneity, meta-analysis could not be conducted. Conclusion: The use of solvent does not cause any significant difference in the postoperative pain levels or analgesic intake for retrieval of gutta-percha in cases of root canal retreatment. Due to the limited number of studies available and the lack of clinician-related outcomes such as time taken to retrieve the gutta-percha, these results should be taken into consideration with caution.

Introduction: In the rapidly evolving landscape of health care, artificial intelligence (AI) has emerged as a promising tool to enhance diagnostic accuracy across various medical disciplines. Within the realm of dentistry, one critical area of focus is endodontics, which involves the diagnosis and treatment of dental pulp diseases. This systematic review investigates the diagnostic precision of AI in contrast to dental experts when predicting endodontic outcomes. Materials and Methods: The review was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The review was registered on the Open Science Framework database. A systematic search was performed of the literature on the application of AI versus dental experts in endodontics. The search was conducted on PubMed, Scopus, Web of Science, and OVID until December 2022. The QUADAS-2 tool was used to evaluate the risk of bias. Results: The initial search retrieved 972 records, of which eight articles were included in the study. The studies reported application of AI for working length determination, periapical lesions, pulp and tooth segmentation, apical periodontitis, vertical root fracture, and C-shaped canals. QUADAS-2 tool revealed a low risk of bias in five out of the eight included studies. Conclusion: AI models demonstrated a notable increase in accuracy and effectiveness in endodontic diagnosis and treatment planning. These results suggest that the integration of AI technology in endodontic diagnosis and treatment planning has immense potential to serve as a promising aid.

Background: The role of endogenous Matrix Metallo Proteinases in resin dentin bond deterioration over time has been well documented. The present study aimed to systematically review the literature; in vitro and ex vivo studies that assessed the outcomes of natural cross-linkers for immediate and long-term tensile bond strength were included. Methods: The manuscript search was carried out in six electronic databases—PubMed/MEDLINE, LILACS, SciELO, Cochrane, Web of Science and DOAJ, without publication year limits. Only manuscripts in English (including the translated articles) were selected, and the last search was performed in December 2020. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was followed. Results: From the 128 potentially eligible studies, 48 full-text articles were assessed for eligibility. After eligibility assessment and exclusions, 14 studies were considered for systematic review and seven studies for meta-analysis. Amongst the selected studies for meta-analysis, three had a medium and four had a low risk of bias. Conclusions: It was evidenced by the available data that Proanthocyanidin is the most efficient natural cross-linker to date, in preserving the bond strength even after ageing.

Calotropis procera (C. procera) is a versatile plant often used for fuel, fodder, wood, fiber, phytoremediation, medicine, and synthesis of nanoparticles. Its ability to tolerate abiotic stresses and its morphophysiological adaptation have made it popular worldwide. Currently, it is identified as an environmental weed across the world. C. procera owes its therapeutic qualities to the secondary metabolites like tannins, alkaloids, and phenols present in it. New synthetic drugs are being formulated by using these secondary metabolites as a prototype. This review aimed to provide a summary of the chemometric profile, toxicity, and pharmacological activities of the aqueous leaf extract of C. procera based on the current literature.