Background/Aim: Reattachment of a tooth fragment is a viable alternative to restore a fractured tooth. The aim of this study was to assess the knowledge, awareness and perception of dental practitioners towards tooth fragment reattachment procedures. Material and Methods:The cross-sectional study was conducted during 2019 and comprised dental practitioners working as general dentists or dental specialists. The subjects were asked to fill out a self-administered questionnaire. Questions related to knowledge and practice regarding fragment reattachment procedures were asked, and the responses were recorded. SPSS version 20.0 and the chi-square test were selected as the statistical tools for data analysis with significance level established at p < .05.Results: Eight hundred and fifty-seven subjects participated in the study. Of them, 404 (47%) were general dentists and 453 (53%) were specialist dentists. Out of the 857 subjects, 231 (27%) had clinical experience of less than 5 years, 268 (31.3%) between 5 and 10 years, 190 (22%) between 10 and 20 years and 168 (19.6%) had experience of over 20 years. Of the 857 subjects, 673 (78.5%) had some knowledge about the reattachment procedure and 292 (34.1%) had performed reattachment in clinical practice. The most common storage medium used for the fractured fragment was saline. The bonding material used for reattachment was lightcured composite resin. A subsequent fracture of the reattached fragment was encountered by more than 62% of the subjects.Conclusions: Lack of availability of the fragment and lack of clinical training were the major reasons for clinicians not performing the procedure routinely. The attachment procedure was most often performed by both general dentists and specialist dentists with 5-10 years of clinical experience. Furthermore, the majority of the participants did not have any familiarity with the concept of biological restorations. Cross contamination was a major clinical concern for the limited clinical application of biological restorations.

Appropriate biomechanical preparation of the root canal is the base for successful root canal treatment. The “mechanical” part of this procedure which is the root canal instrumentation is not complete without achieving “glide path”. Clinicians must understand the importance of this small and simple but important concept of glide path which in turn will help to avoid a number of mishaps and give a long term predictable endodontic success. Key Words : “ Glide path, Rotary instrumentation “

Aim: To evaluate the sealing ability of mineral trioxide aggregate (MTA) and resin-modified glass ionomer cement (RMGIC) to seal the furcal perforation with and without internal matrix. Materials and methods: Sixty freshly extracted intact human permanent mandibular molars were selected. After creating furcal perforation, the teeth were randomly divided into four experimental groups containing 15 teeth each according to the furcal perforation repair materials used. Group I-RMGIC without internal matrix. Group II-RMGIC with internal matrix. Group III-MTA without internal matrix. Group IV-MTA with internal matrix. To evaluate the sealing ability of furcal perforation, dye extraction method was performed using 2% methylene blue dye and 65% concentrated nitric acid. Spectrophotometer was used for measuring dye absorbance at 550 nm. Results: Group I (RMGIC without internal matrix) showed highest microleakage followed by group II (RMGIC with internal matrix), group III (MTA without internal matrix), and group IV (MTA with internal matrix). There was a significant difference found between group I and group II, but there was no significant difference seen between group III and group IV. Conclusion:Mineral trioxide aggregate has excellent sealing ability and can be used with and without internal matrix in repair of furcation perforation. Resin-modified glass ionomer cement should be used with internal matrix to repair furcation perforations. Clinical significance: Mineral trioxide aggregate with and without internal matrix whereas RMGIC with internal matrix have been successfully used in repair of furcation perforation.

Aim The aim of this study was to compare the canal transportation and canal centric ability of One Shape (Micro Mega, Besançon, France) and Mani Silk (Mani Utsunomiya, Tochigi, Japan) nickel-titanium (NiTi) rotary files in curved canals with the help of cone beam computed tomography (CBCT). Materials and Methods Total 40 mesiobuccal canals of maxillary molars with an angle of curvature ranging between 25 and 45 degrees were divided according to the instrument used in canal preparation into two groups 20 samples each: One Shape (group 1) and Mani Silk (group 2). Pre- and post-instrumentation scans were performed using CBCT (Carestream CS 9300 scanner) to evaluate the transportation and centric ability at apical, middle, and coronal levels using unpaired Student's t-test. Results Mani Silk file showed significantly less canal transportation and better canal centric ability compared to One Shape system. Conclusion Mani Silk file maintained original canal curvature better than One Shape NiTi rotary file.

Aims: The aim of the study is to justify the need of deep learning predictive model in obtaining molecular phenotypes of overall cancer survival. Study Design: The study is based on the secondary qualitative data analysis through usage of systematic review. Methodology: A qualitative study has been conducted to analyse the necessity of deep learning.  It also includes the need for deep learning models to obtain the imaging of the cancer cells. In the study, a detailed discussion on deep learning has been made. The analysis of the primary sources has been obtained by evaluating the quality of the resources in the study. The study also comprises of a thematic analysis that enlightens the benefits of deep learning. The study is based on the analysis of 14 primary research-based articles out of 112 quantitative articles and structuring of a systematic review from the collected data. Results: The morphological and physiological changes that occur in the cancerous cells have been clearly evaluated in the research. The result signifies the prediction can be made by implementing deep learning in terms of cancer survival. Advancements in terms of technology in the medical field can thus be improved with the help of the deep learning process. It states the advancements of the deep learning models that are helpful in predicting the model of cancer to determine survival rate. Conclusion: Deep learning is a process that is considered to be a subset of artificial intelligence. Deep learning programmes are meant to be performed for complex learning models. Although there is difference in the concept of deep learning and image processing still artificial intelligence brings both together so as to ensure better performance in image processing. The need for deep learning models has become invasive, and it helps to build a strong ground for cancer survival.