DDPM: A Dengue Disease Prediction and Diagnosis Model Using Sentiment Analysis and Machine Learning Algorithms.

The aedes mosquito-borne dengue viruses cause dengue fever, an arboviral disease (DENVs). In 2019, the World Health Organization forecasts a yearly occurrence of infections from 100 million to 400 million, the maximum number of dengue cases ever testified worldwide, prompting WHO to label the virus one of the world's top ten public health risks. Dengue hemorrhagic fever can progress into dengue shock syndrome, which can be fatal. Dengue hemorrhagic fever can also advance into dengue shock syndrome. To provide accessible and timely supportive care and therapy, it is necessary to have indispensable practical instruments that accurately differentiate Dengue and its subcategories in the early stages of illness development. Dengue fever can be predicted in advance, saving one's life by warning them to seek proper diagnosis and treatment. Predicting infectious diseases such as dengue is difficult, and most forecast systems are still in their primary stages. In developing dengue predictive models, data from microarrays and RNA-Seq have been used significantly. Bayesian inferences and support vector machine algorithms are two examples of statistical methods that can mine opinions and analyze sentiment from text. In general, these methods are not very strong semantically, and they only work effectively when the text passage inputs are at the level of the page or the paragraph; they are poor miners of sentiment at the level of the sentence or the phrase. In this research, we propose to construct a machine learning method to forecast dengue fever.

Pharmacokinetic and molecular docking studies to design antimalarial compounds targeting Actin I.

OBJECTIVE: Malaria is an ancient disease that still causes more than 200 million of cases 7 with high mortality globally. Identification of new drug targets and development of novel antimalarial drugs with unique mode of action encounter the drug resistance and reduce the mortality by Plasmodium parasites. Actin protein is one of the key proteins in Plasmodium falciparum playing multifarious important roles including transport, cell motility, cell division, and shape determination. This study investigated Actin I as a drug target, in silico screening of diverse molecules through molecular docking was considered. Further, pharmacokinetic parameters of the selected molecules from the docking and interaction studies were planned to propose the lead molecules.b. METHODS: Molecules were selected according to score and protein ligand interaction and selected molecules were subjected for pharmacokinetic studies to investigate important drug parameters. RESULTS: The docked molecules were ranked according to the binding score and good interaction pattern was observed with Actin I within top 20 scoring molecules. The selected molecules also had optimum pharmacokinetic parameters. CONCLUSION: The current study provides a set of hit molecules which can be further explored through in vitro and in vivo experiments for the development of potential drugs against malaria, there by encountering drug resistance and establishing Actin I as an important drug target.

Comparative transcriptome analysis of different stages of Plasmodium falciparum to explore vaccine and drug candidates.

Malaria is a life-threatening disease causes huge burden on human health. Every year >200 million cases of malaria are reported globally. Researchers have carried out research on transcriptome of different stages of Plasmodium species to understand complex pathology of pathogens and to discover therapeutics. Researchers are targeting different stages of Plasmodium falciparum separately. Hence, to target all stages of Plasmodium simultaneously comparative transcriptome analysis of different stages was carried out and 44 commonly expressed proteins from different stages of Plasmodium were identified. These proteins were analyzed for their drug target and vaccine potential in different analysis. Conservation of these proteins in human infecting Plasmodium species was also studied. Current approach is also justified because few of these proteins were found to be known vaccine and drug target candidates in different infectious diseases. These proteins can be taken as drug targets and/or vaccine candidates in further experimentation against malaria.