Journal of Health & Medical Informatics

TB is a deadly disease and MDR-TB is spreading even DOTS drug regime has rigorously maintained with at least ten new drugs like isoniazid, capreomycin, dapsone, linezolid, pyrazinamide, ethambutol and Beda quinolone apart from traditional drugs like rifampicin, streptomycin, amikacin and clarithromycin. Rifampicin inhibits RNA polymerase and mutations in rpo gene codons give resistance. Streptomycin inhibits protein synthesis and mutation of ribosomal proteins and rRNA genes give resistance but no strAB or mphA1-9 mdr genes reported in Mycobacterium. Bedaquiline kills M. tuberculosis by inhibition of the membrane-bound F1F0-ATP synthase complex. Ciprofloxacin and ofloxacin were replaced by moxifloxacin that binds to DNA gyrase inhibiting DNA replication and/or transcription and mutations of gyrA at position 90 and 94 and gyrB at position 74, 88 and 91 give resistance. Kanamycin and amikacin inhibit protein synthesis and mutation of rrs gene gives resistance. However, aac2’-Ic type acetylating enzymes have also been suggested for multi-resistance. Ethambutol interferes with the biosynthesis of arabinogalactan in the cell wall and embB gene mutation at position 306 gives resistance. Erm^MT methyl transferase adds methyl group to 23S rRNA at A2058 giving resistance to azithromycin and clarithromycin where capreomycin or viomycin peptide antibiotics may be effective drug. Ethionamide is a derivative of isonicotinic acid inhibits mycolic acid synthesis disrupting membrane function. Ethionamide resistance were linked due to mutations in etaA, ethA, ethR and inhA genes. Isoniazid is also a pro-drug and katG gene (S315T) mutation was reported for its resistance. Pyrazinamide after conversion to pyrazinoic acid disrupts membrane function inhibiting ATP synthesis and pncA or rpsA gene mutation likely gives resistance. Cycloserine is a peptidoglycan synthesis inhibitor competing D-Alanine ligase. We find beta-lactamase (BlaC) and penicillin binding protein (penA) as well as well studied emrB and qacB drug efflux proteins by genome wide search. But no 50-500 kb MDR plasmid carrying five or more mdr genes as found in most Enterobacteriaceae, have not sequenced in M. tuberculosis. We conclude that search for Mycobacterium plasmids must be accelerated pointing multi-resistance. Surely, phage therapy and gene medicines also have got momentum to overcome multi-resistance and antibiotics void.

Heart is the central organ that pumps pure blood to whole body through blood vessels. This circulation system involves functioning of large number of genes that interacts for proper functioning. Any malfunctioning of single gene leads to the cardiovascular diseases (CVDs) Aging is an inevitable part of life and unfortunately the risk of CVDs increases with ageing. Although numerous studies were carried on cardiovascular diseases that considered both young and aged humans, but still there are many unanswered questions as to how the genetic pathways that regulate aging influence cardiovascular disease and vice versa. Therefore, this is of great interest to identify the interaction between cardiovascular diseases and ageing genes. Genes for CVDs and ageing were collected from various databases and a network was created for their common genes. Network in analyzed to find the interaction between ageing and cardiovascular disease genes.

One of the chronic respiratory diseases that affect a large proportion of the population is Asthma. Asthma is more prevalent in children of age groups 6-14 years. Early identification of the risk factors is an important intervention towards the management of the disease as the disease is progressive in nature. In our work, we assess the performance of the two machine learning approaches with respect to their accuracy in predicting the outcome of asthma disease after identifying the critical risk factors that help in the prognosis of the disease. We perform an empirical analysis of ensemble and hybrid machine learning models to deduce the best performing approach for the prediction of the outcome of asthma. The Neyveli rural asthma dataset of India, representing cross sectional study data gathered through questionnaires formulated under ISAAC study was used to validate our approach. The outcome is predicted using both, sequential and parallel ensemble learning techniques as well as the hybrid machine learning model and we suggest the best performing ensemble learning technique on the dataset under consideration. The problem of class imbalance is well handled before presenting the data to the model as unbalanced data sets are seen to have a negative impact on classification performance.

A wide variety of human population is infected with different species of Salmonella causing salmonellosis. At present, the major hurdle in treating infection is the development of resistance to existing antibiotics. Therefore, there is a need to identify new drug targets so that new drugs can be designed that can cure the infection efficiently. Here, we have design an interactome for all species of Salmonella using its essential and non-homologous protein to humans. So that, all types of infections of Salmonella can be treated with single antibiotic. 1399 essential proteins of Salmonella have been analyzed using interactome studies. We found 09 proteins as putative drug targets that can be used to treat all species of Salmonella.