Objectives:Diabetes mellitus (DM) is a common chronic metabolic disorder which affects millions of people. At present, India has the highest incidence of diabetes worldwide. Several oral lesions and conditions are associated with diabetes. However, there is a lack of consensus among researchers regarding the relationship between DM and dental caries. Hence, the present study was carried out to assess the dental caries prevalence among type II diabetic and nondiabetic adults attending a hospital in Ahmedabad city.Materials and Methods:A hospital-based cross-sectional study was conducted. One hundred and twenty diabetics individuals attending the diabetic Outpatient Department (OPD) and age and sex-matched 120 nondiabetic individuals from general OPD were included in the study. The data were gathered through semi-close-ended questionnaire and clinical examination. Dental caries was assessed by using the World Health Organization's 2013 proforma. Data was analyzed by applying Student's independent t-test or one-way analysis of variance.Results:Dental caries prevalence among the diabetic group was 73.33% and 33.33% among the nondiabetic group. Dental caries prevalence and mean dental caries was significantly higher among uncontrolled diabetic individuals than that among controlled diabetic individuals. Duration of the disease and dental caries prevalence did not show any significant difference.Conclusion:Dental caries prevalence was significantly high among diabetic individuals compared with nondiabetic individuals. Close collaboration between the patients, healthcare units, and oral health professionals could be a way of improving diabetic patients' general and oral health.

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Aim: The present study was done to determine the activity of licorice root extract on Streptococcus mutans (S. mutans) in comparison to chlorhexidine and fluoride mouthwash. Materials and methods: In the current study, the different concentrations of aqueous and ethanolic licorice root extract were subjected to microbiological assay and zone of inhibition was determined against S. mutans by agar ditch method. Minimum inhibitory concentration (MIC) of aqueous and ethanolic solution was obtained by using broth dilution method and agar dilution method. Chlorhexidine and fluoride mouthwash were kept as a positive control in the present study. One-way ANOVA along with Tukey post hoc test were used at 5% level of significance to analyze data. Results: Mean zone of inhibition of chlorhexidine mouthwash, fluoride mouthwash, aqueous and ethanolic licorice root extracts against S. mutans at 24 hours were 23 mm, 14.2 mm, 15.8 mm and 22.4 mm, respectively. Minimum inhibitory concentration of aqueous and ethanolic licorice root extract on S. mutans was 20 mg/mL and 12.5 mg/mL, respectively by both broth dilution method and agar dilution method. Conclusion:The antibacterial effect produced by ethanolic licorice root extract on S. mutans was comparable to chlorhexidine mouthwash while significantly higher in comparison with aqueous form and fluoride mouthwash. Clinical significance: The interest in the plants with antibacterial and anti-inflammatory activity has increased now days to treat various dental diseases as consequences of current problems associated with the conventional agents. Licorice root is easily available, economically feasible and culturally acceptable and may possess minimal side effects as compared to conventional means of chemicotherapeutic agents used for reduction of S. mutans in oral cavity and hence can be recommended for prevention of dental caries.

In this community review report, we discuss applications and techniques for fast machine learning (ML) in science—the concept of integrating powerful ML methods into the real-time experimental data processing loop to accelerate scientific discovery. The material for the report builds on two workshops held by the Fast ML for Science community and covers three main areas: applications for fast ML across a number of scientific domains; techniques for training and implementing performant and resource-efficient ML algorithms; and computing architectures, platforms, and technologies for deploying these algorithms. We also present overlapping challenges across the multiple scientific domains where common solutions can be found. This community report is intended to give plenty of examples and inspiration for scientific discovery through integrated and accelerated ML solutions. This is followed by a high-level overview and organization of technical advances, including an abundance of pointers to source material, which can enable these breakthroughs.