Summary Objectives To assess the socio‐demographic profile, pattern and treatment outcomes of pesticides poisoning. Methods A prospective observational study was conducted at the department of emergency medicine of a South Indian tertiary care hospital for 1.5 years to study the pattern and outcomes of poisoning cases due to pesticides. Level of significance (P) <0.05 was considered as statistically significant. Results A total of 375 poisoning victims with intentional/accidental exposure to pesticides were followed up and documented. The male–female ratio was 1:0.32; mean age was 31.65 ± 13.10 years. 72% of cases were rural residents. Organophosphorus compounds were the most implicated pesticides. Mean Glasgow Comatose Score (GCS) of the patients was 12.22 ± 3.86. 80.3% of patients recovered while 6.4% died. About 13.3% patients were lost to follow‐up as they were discharged against medical advice (DAMA). Conclusion There was a statistical significance seen in the implication of pesticides for intentional poisoning with age, route of administration, area of residence and occupation of the victims. However, there was a strong association of the outcomes of poisoning with the toxic agent implicated for the poisoning.

Medical devices, being life-saving tools, are considered to be a boon for healthcare system. However, in addition to their therapeutic effects, there are several ill consequences that are caused by these devices. An effective cohort vigilant system was needed to manage such adverse effects. This had led to the introduction of materiovigilance. Materiovigilance is the study and follow-up of occurrences that arise as a result from the usage of the medical equipment. It not only manages adverse events (AE) but also creates harmonization among countries. Keeping these objectives in focus, the principles, perspectives, and practices with regard to materiovigilance that are followed in the USA, Europe, China, Japan, Australia, Canada, and India are being compared. Such a comparison is essential, which will help us to understand the gaps in the current regulatory systems in the above-mentioned countries and furthermore will provide a comprehensive picture to the regulatory authorities to amend any existing laws if required. These amendments may ensure optimal patient safety by providing them a benign experience from the use of medical devices.

: In December 2019 in Wuhan, China, the Severe Acute Respiratory Syndrome - Corona Virus - 2 (SARS-CoV-2) (also 2019 nCoV) was first discovered. Later WHO declared that SARS-CoV-2 was responsible for Coronavirus Disease 2019 (COVID-19). The round, elliptical or pleomorphic shape of the 2019-nCoV is 60–140 nm in diameter. It comprises a single stranded genome of RNA that comprises 29891 nucleotides, a lipid shell and spike protein, envelops membrane, and hemagglutinin-esterase (HE) proteins. Several therapeutic approaches have been proposed to combat with this disease as this disease became global pandemic. Bacillus Calmette–Guérin (BCG) vaccine could be another approach and at present it is the only TB prevention vaccine approved. Both TB and COVID-19 causes severe pneumonia. In this review, we have tried to correlate the pathophysiology of both these disease condition. . In this review, we also have shown the history and current BCG practice throughout the world and it is hypothesized that the countries which strictly maintained and made mandatory call to recommend BCG vaccination are relatively less affected by COVID-19 pandemic. When BCG is exposed to a subsequent viral infection, it is allowed to lead to cross-reactive T cell responses which result in increased activity of Cluster of differentiation (CD) 4 + and Cluster of differentiation (CD) 8 + T cells and this may be a ray of hope in treating the SARS infection.

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With the growing world, the human mind has grown too much with its own complexities. Gone are the days where people used to express themselves through speech or by verbal contact. Now, the era of social media has brought an interface to the world where they can convey their opinions as well as their inner most thoughts through various social networks. People are more comfortable to express their emotions on these social media rather in the real world. This all has led to the need of Sentiment analysis. It has a major role in detecting stress in humans and how surrounding environment is affecting the population of the world. The project analyses the stress among people through tweets. Self-report questionnaires face to face interviews wearable sensors is the main basis of psychological stress that is caused traditionally. The project covers all possible aspects of interactions on social media. Firstly, by fetching tweets from twitter dynamically based on keyword entered by user and segregating them into positive, negative and neutral categories using Naive Bayes algorithm. Secondly, performing sentiment analysis on a dataset containing movie reviews and thirdly, on a very large dataset containing 5 million tweets using Hadoop and an added algorithm of logistic regression for improved performance and efficiency. The entire project was carried out using a distinct step by step procedure consisting of data collection, data cleaning, training of data, data modelling, algorithm application and visualization. Experiments were conducted on an extensive basis to verify the superior theory algorithms and credibility of the project.