Context:Various alternative methods are being used in many medical colleges to reinforce didactic lectures in physiology. Small group teaching can take on a variety of different tasks such as problem-solving, role play, discussions, brainstorming, and debate. Research has demonstrated that group discussion promotes greater synthesis and retention of materials.Aims:The aims of this study were to adopt a problem-solving approach by relating basic sciences with the clinical scenario through self-learning. To develop soft skills, to understand principles of group dynamics, and adopt a new teaching learning methodology.Subjects and Methods:Experimental study design was conducted in Phase I 1st year medical students of 2014–2015 batch (n = 120). On the day of the session, the students were grouped into small groups (15 each). The session started with the facilitator starting off the discussion. Feedback forms from five students in each group was taken (n = 40). A five point Likert scale was used ranging from strongly agree to strongly disagree. Data were analyzed using IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp.Results:Our results show that 70% of the students opined that small group discussion were interactive, friendly, innovative, built interaction between teacher and student. Small group discussion increased their thought process and helped them in better communication.Conclusions:The small group discussion was interactive, friendly, and bridged the gap between the teacher and student. The student's communication skills are also improved. In conclusion, small group discussion is more effective than the traditional teaching methods.

The universe dependence on electronics has confirmed that in several approaches create a problem in the eyes. There is a shortage of literature survey to find out the high exposure to young college students in developing the cell phone vision syndrome. This study was carried out in 30 medical students aged between 18-25 years. This is part of the previous study on impact of self-esteem, personality and behavior among WhatsApp user and non-user. They were selected by using simple random sampling and informed consent was obtained. A pretested well organized questionnaire was used to gather the research information. The mean age was 19.17 years. The acceptable sample size was 30. Most of the students were used smart phone 2 h/day (80% or 26/30) and for texting, browsing, (25/30, 83%). Background of white screen were used (22/30, 73%), black letter (21/20, 70%) and viewing radius was more than 25 cm (20/30, 66%). Symptoms were noted for mostly (25/30, 83%), students out of which (11/25, 44%) had eye strain. Use of smart phone devices for many hours, at near functioning distances, has become familiar among college students. Digital tools will emerge in coming years, it may hold more apps and our eyes will spend more time on that. We need to learn how to interact safely with this tool and create awareness on healthy eye habits.

Summary The state of art to integrate bio‐signals with computer based diagnosis is taking dominance. The man‐machine interface is useful for early and immediate clinical interpretation. The electrocardiogram (ECG) signal plays a vital role in revealing the possible data towards categorizing normal and abnormal cardiac functioning. The fatal conditions exhibited by ventricular arrhythmias (VA) pose a remarkable change in the feature set of the ECG signals. In this work, a novel approach to segregate the superior feature toward the ventricular arrhythmias are extracted using feature ranking score algorithm (FRSA). The FRSA collects feature vectors in three different domains and ranks it to find out the more prevalent feature for diagnosis of VA. The Support Vector Machine (SVM) classifier is administered by supervisory machine learning optimization algorithm Mean Grey Wolf Optimization (MGWO). The performance estimates of SVM‐MGWO is compared for classification of VA signals with other optimization also like SVM‐Particle Swarm Optimization (SVM‐PSO) and SVM‐Grey Wolf Optimization (SVM‐GWO). The non‐parametric and parametric analysis evidently shows the improved performance of feature parameter estimates for classification. The accuracy of classification for SVM‐MGWO attains 100% for finding test data with VA at a minimal convergence iteration while comparing it with the other mentioned supervisory algorithms. The standard deviation during parametric analysis is negligible, which reveals the fact that reductant feature extracted and utilized for testing of ECG data is minimal. The performance estimates attained by the proposed algorithm shows the selection of optimal feature for the findings of VA through ECG. The man‐machine interface aides in the early diagnosis of ventricular arrhythmias using non‐invasive diagnosing tool, the ECG.

No abstract

Treatment of cancer without any side-effects is still a challenge in the medical system. This leads to an increasing search for improved anticancer drugs. Plant products have been used as a traditional medicine for thousands of years as it has been drawing a great deal of attention to overcome cancer. The main objective of this study is to evaluate and compare the anticancer effect of MahaVallathy Leghiyam (MVL) and Neeradi Muthu Vallathy Leghiyam (NMVL) against human oral cancer (KB) cells. Different concentrations of aqueous extracts of MVL and NMVL were subjected to cytotoxic study. The antiproliferative effects were determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and IC50 concentration was found at 3.25 mg/mL for MVL and 1.25 mg/mL for NMVL, also apoptotic activities were studied by PI and AO/EB dual staining. The results acquired from the comparative in-vitro studies on KB cell lines revealed that the unique Siddha medicine NMVL has more potent anticancer activity compared to MVL. There was an increase in the cell growth inhibition when treated with NMVL at lower concentration compared to MVL. The current investigation suggested that the phyto constituents of NMVL are responsible for anticancer activity. Thus, the long-term consumption of NMVL could be considered and promoted as an adjuvant therapy for treating various malignancies.