Manipal College of Dental Sciences, Mangalore was founded in 1987 and recognised by the Dental Council of India in 1992 and by the Malaysian Dental Council in 2003. It was certified for ISO9001:2000 in 2006 and was re-certified for ISO9001:2008 in 2009. The college is a part of Manipal University. The college offers undergraduate (BDS) and postgraduate (MDS) programme..
This narrative review aims to evaluate the current landscape of Digital Smile Design (DSD) software platforms, with a focus on the integration of Artificial Intelligence (AI) to enhance clinical workflows. DSD is increasingly used in interdisciplinary dentistry to plan and simulate esthetic treatments, and AI has the potential to improve precision, efficiency, and patient engagement. The purpose was to analyze how AI-enabled DSD systems may influence treatment predictability, efficiency, and patient outcomes in digital dentistry. Literature was identified from PubMed Central, EBSCOhost, Scopus, and Web of Science over the past 15 years, focusing on peer-reviewed studies describing the progression of DSD from basic 2D visualization tools to advanced AI-assisted 3D platforms. A total of 12 software platforms and 6 peer-reviewed studies reporting AI integration in DSD were analyzed. The review highlights how such systems enable more precise smile simulations, semi-automated treatment planning, and interdisciplinary collaboration across orthodontics, prosthodontics, and implantology. Reported outcomes indicate reduced design time, improved interdisciplinary communication, and enhanced patient engagement. However, the limited number and heterogeneity of available studies constrain definitive conclusions. Thus, AI integration shows potential benefits, but further controlled studies are required before definitive clinical recommendations can be made. This review identifies current applications, limitations, and future research needs for integrating AI technologies into patient-centered digital dentistry.
Dental materials education poses unique challenges due to the complex integration of scientific principles with clinical applications. Traditional teaching methods often fail to promote deep conceptual understanding. This study investigated whether the process of generating multiple-choice questions (MCQs) by students could enhance deeper learning, knowledge application, and critical thinking in dental materials education. A prospective, randomized crossover study was conducted among second-year dental students (n = 64) at the Nair Hospital Dental College, Mumbai. The study comprised of two phases examining different topics of similar difficulty (dental restorative composites and glass ionomer cements). Following the didactic lectures, all students completed the pre-tests and were randomly allocated to the intervention (MCQ generation activity with faculty-moderated discussion) or control group (additional study time). After a washout period of two weeks, the groups were crossed over. The primary outcome was the difference in post-test performance between the groups. The secondary outcomes included performance across cognitive domains and student feedback. Data were analyzed using paired and independent t-tests, with mixed-effects models for crossover analysis. Sixty-two students completed both study phases. The intervention group demonstrated significantly higher post-test scores compared to controls in both phases: Phase 1 (approximately 76.8
IntroductionThe integration of artificial intelligence (AI) in healthcare has garnered significant scholarly attention, particularly in areas such as medical image analysis, prognosis, and treatment. Despite its potential, concerns regarding AI's reliability and application persist, prompting the development of guidelines aimed at standardizing its use in medicine. This study aims to evaluate the current content and quality of AI guidelines in healthcare, focusing on identifying gaps and providing a critical appraisal of existing checklists.MethodologyComprehensive bibliometric analysis, Altmetric analysis, and systematic review were conducted, utilizing the AGREE II Tool for quality appraisal. The systematic search spanned Scopus, PubMed, and Dimension AI databases, focusing on English-language, open-access articles related to AI reporting guidelines. Two reviewers independently evaluated the data, with manual extraction performed in Microsoft Excel. The AGREE II Tool assessed six domains of guideline quality.ResultsThe search yielded 2477 articles, ultimately identifying 27 AI-specific reporting guidelines published between 2020 and 2025. The analysis revealed significant variations in quality across the AGREE II domains. Among the very first and most impactful were SPIRIT-AI, CONSORT-AI, MINIMAR, and CLAIM, all prioritized structured reporting but were hampered by their timing-based when there were few AI trials-resulting in limited applicability and risk of missing older AI terminologies. However, STAR-machine learning (ML), APPRAISE-AI, and CLEAR exhibited more general, domain-specific frameworks, whereas checklists such as CHEERS-AI, CREMLS, and MI-CLEAR-large language model (LLM) showcased limited author diversity in contribution. However, many guidelines exhibited weaknesses in methodological rigor and stakeholder involvement, limiting their practical applicability.ConclusionThe findings emphasize the need for evidence-based updates to AI reporting guidelines to ensure methodological integrity amid rapid advancements. Increased expert involvement and stakeholder engagement are crucial for enhancing the guidelines' applicability and rigor, addressing AI complexities in health research, and adapting reporting frameworks to evolving AI technologies in healthcare.
INTRODUCTION:There is a need for safe and potent antibiofilm agents for root canal irrigation. The aim of this study was to investigate the antibiofilm activity of enzymatic irrigants (Bromelain and Papain) and their cytocompatibility to mammalian cells. METHODS:Biofilms of Enterococcus faecalis were developed on dentin discs and treated with 0.05% bromelain, 4% papain, 2.5% sodium hypochlorite (NaOCl) or saline for 15 min. The antibiofilm effectiveness was characterized by quantifying the colony forming units (CFU) and confocal microscopic examination of the bacterial cells (live/dead staining) and extracellular matrix polysaccharide using a selective fluorophore binding assay. Cytotoxicity of 0.05% bromelain, 4% papain and 2.5% NaOCl to human periodontal ligament fibroblasts was investigated using a metabolic activity assay. Data were analyzed using analysis of variance and nonparametric tests, with significance set at P < .05. RESULTS:Papain (4%) and Bromelain (0.05%) demonstrated 5 log CFU reduction, which was comparable to 2.5% NaOCl (P > .05). Confocal microscopy further confirmed that bromelain, sodium hypochlorite, and papain caused significantly greater bacterial cell death compared to saline (P < .05). Papain significantly reduced the extracellular matrix polysaccharide content within the biofilm compared to all other groups (P < .05). CONCLUSION:This study demonstrated that bromelain and papain showed comparable antibiofilm activity as 2.5% NaOCl and were more biocompatible than NaOCl, highlighting their potential to be developed as root canal irrigants.
