Adverse drug reaction monitoring study in hospitalized patients: support for pharmacovigilance at a tertiary care hospital

Background: Adverse drug reaction (ADR) reporting is an integral component of pharmacovigilance. However, under-reporting of ADR is commonly observed. The present study has been planned with aim to assess the pattern of reported ADRs in terms of its frequency, causality and severity so as to reinforce pharmacovigilance activities.Methods: This prospective observational study was conducted with the aim to evaluate suspected ADRs in hospitalized patients in departments of Medicine, Surgery and Orthopaedics of a tertiary care hospital in North India for a period of 6 months. The ADRs were assessed in terms of the demographic parameters, organ system affected, drugs implicated, type of ADRs by Rawlin’s and Thompson classification, causality using WHO-UMC scale and severity of ADR by Modified Hartwig’s and Siegel scale.Results: A total of 111 ADRs were reported during the study period. There was male preponderance (54.96%) with majority of ADRs in age group of 18-60 years (79.28%). Gastrointestinal system was most commonly affected (36.36%). The most common drug implicated in causing ADRs was Ceftriaxone (11.71%). Majority of ADRs were Type A reactions (86.49%). Causality assessment using WHO-UMC scale depicted that 74.77% of ADRs were possible. Severity analysis showed that 82.88% of ADRs were mild as per Modified Hartwig’s and Siegel scale.Conclusions: ADR reporting should be encouraged among health-care professionals, para-medical staff and patients in general so that the ultimate goal of pharmacovigilance can be fulfilled

Improving Accuracy of Integrated Neuro-Fuzzy Classifier with FCM based Clustering for Diagnosis of Psychiatric Disorder

Parkinson’s disease (PD) is a progressive neurodegenerative disorder. Autism spectrum disorder (ASD) is a neurodevelopment disorder. Clinical decision-making process is complex. Due to complex nature of disease sign and its symptoms clinical decision making may lead to misclassification. To deal with such complex medical problems methods or approaches of soft computing play an important role. This paper will focus on presenting an integrated Neuro-fuzzy model. This integrated model has the learning strength of neural network and knowledge representation ability of fuzzy logic. Modified Adaptive Neuro –Fuzzy inference system (M-ANFIS) is used here for classification and predication. Here Fuzzy C-mean (FCM) Clustering is used first to make classes of data before presenting in to ANFIS. This FCM based class will reduce the classifier computational overhead. Precision error and recall, F-measure and accuracy matrices are used to compare the experimental results with other classic methods

Enhancing Feature Selection Accuracy using Butterfly and Lion Optimization Algorithm with Specific Reference to Psychiatric Disorder Detection & Diagnosis

As the complexity of medical computing increases the use of intelligent methods based on methods of soft computing also increases. During current decade this intelligent computing involves various meta-heuristic algorithms for Optimization. Many new meta-heuristic algorithms are proposed in last few years. The dimension of this data has also wide. Feature selection processes play an important role in these types of wide data. In intelligent computation feature selection is important phase after the pre-processing phase. The success of any model depends on how better optimization algorithms is used. Sometime single optimization algorithms are not enough in order to produce better result. In this paper meta-heuristic algorithm like butterfly optimization algorithm and enhanced lion optimization algorithm are used to show better accuracy in feature selection. The study focuses on nature based integrated meta-heuristic algorithm like Butterfly Optimization and lion-based optimization. Also, in this paper various other Optimization algorithms are analyzed. The study shows how integrated methods are useful to enhance the accuracy of any computing model to solve Complex problems. Here experimental result has shown by proposing and hybrid model for two major psychiatric disorders one is known as autism spectrum and second one is Parkinson's disease

Molecular mechanisms of oncolytic properties of Newcastle disease virus (NDV) in human cancer cells

Newcastle disease virus (NDV) is a single-stranded, non-segmented, negative-sense enveloped RNA virus, which belongs to the Orthoavulavirus genus of Paramyxoviridae family. It is a well-known, economically important poultry pathogen worldwide. Over the last five decades, NDV is known to have oncolytic properties based on its tumourselective replication sparing the healthy cells and immunostimulation affirming potential candidate for oncovirotherapy. In this PhD project, the efficacy of naturally occurring and genetically modified GFP expressing non-pathogenic NDV strains investigated in various human cancer cell lines as an oncolytic virus. This study has demonstrated that the heterogeneous colorectal cancer cell line Caco-2 was the most susceptible to the cytotoxicity induced by avirulent NDV strains amongst the panel of diverse cell lines tested. Despite the high levels of cell cytotoxicity induced by NDV in Caco-2 cells, a small population of surviving cells was isolated from NDV superinfected Caco-2 cells 12 days post infection and named VR Caco-2 cells (virus-resistant Caco-2 cells). The persistent infection with avirulent strains of NDV was demonstrated in VR Caco-2 cells for the first time. An integrated approach of cellular, transcriptomic, and proteomic data was used to study differences between persistently NDV-infected VR Caco-2 cells,and acutely NDVinfected and uninfected Caco-2 cells. This study has shown that persistent NDVinfection resulted in slower cell proliferation of VR Caco-2 cells than parental Caco-2 cells, and production of recoverable and replicating virus at lower titres. VR Caco-2 cells have demonstrated resistance to NDV re-infection. In contrast, VR Caco-2 cells were susceptible to other viruses such as avian influenza virus (H9N2) and vesicular stomatitis virus (VSV). Persistent NDV infection in VR Caco-2 cells resulted in reduced NDV-induced cytotoxicity, although VR Caco-2 cells were still sensitive to the increased cell cytotoxicity induced by the VSV infection. This would suggest that a combination of oncolytic viruses could be used to overcome the effects of NDV persistent infection. Potential mechanisms of persistence of NDV in Caco-2 cells were explored. Both Caco2 and VR Caco-2 cells demonstrated the lack of efficient induction of IFN-β and ISG15 mRNAs, which could be a potential reason for the establishment of NDV persistent infection. RNA-seq data analysis demonstrated extensive regulation of thousands of genes and hundreds of cellular pathways in VR Caco-2 cells while maintaining 50-times lower viral load compared to acute NDV-infection (in Caco-2 cells). Fluctuation in SQSTM1/p62, a multifunctional and multidomain signalling adapter protein required in selective autophagy, was also demonstrated suggesting the induction of autophagy in NDV-infected Caco-2 cells. The results generated in this PhD project strongly suggest that NDV not only establishes persistent infection but that too reduces NDV-induced cytotoxicity while regulating thousands of genes in Caco-2 cells. It also suggests the need for detailed investigation of persistent NDV-infection in vitro and in vivo models of Caco-2 cells before and after developing the NDV as an oncolytic therapeutic vaccine for cancer

Ionic Liquids as Green Corrosion Inhibitors for Industrial Metals and Alloys

Present chapter describes recent advances in the field of development of ionic liquids as green and sustainable corrosion inhibitors for metals and alloys. The present chapter has been divided into several sections and subsections. Recently, development of the green and sustainable technologies for the corrosion prevention is highly desirable due to increasing ecological awareness and strict environmental regulations. In the last two decades, corrosion inhibition using ionic liquids has attracted considerable attention due to its interesting properties such as low volatility, non-inflammability, non-toxic nature, high thermal and chemical stability and high adorability. Several types of ionic liquids have been developed as “green corrosion inhibitors” for different metals and alloys such as mild steel, aluminum, copper, zinc, and magnesium in several electrolytic media. The ionic liquids are promising, noble, green and sustainable candidates to replace the traditional volatile corrosion inhibitors

Diffuse retro-reflective imaging for improved mosquito tracking around human baited bednets

Robust imaging techniques for tracking insects have been essential tools in numerous laboratory and field studies on pests, beneficial insects and model systems. Recent innovations in optical imaging systems and associated signal processing have enabled detailed characterisation of nocturnal mosquito behaviour around bednets and improvements in bednet design, a global essential for protecting populations against malaria. Nonetheless, there remain challenges around ease of use for large scale in situ recordings and extracting data reliably in the critical areas of the bednet where the optical signal is attenuated. Here we introduce a retro-reflective screen at the back of the measurement volume, which can simultaneously provide diffuse illumination, and remove optical alignment issues whilst requiring only one-sided access to the measurement space. The illumination becomes significantly more uniform, although, noise removal algorithms are needed to reduce the effects of shot noise particularly across low intensity bednet regions. By systematically introducing mosquitoes in front and behind the bednet in lab experiments we are able to demonstrate robust tracking in these challenging areas. Overall, the retro-reflective imaging setup delivers mosquito segmentation rates in excess of 90% compared to less than 70% with back-lit systems

First Principles Study on Structural and Electronic Properties of REAg (RE= Y, La, Pr and Er) Intermetallics

We The structural, electronic and mechanical properties of binary B2 – type CsCl structured intermetallic compounds of Ag (ReAg, Re= Y, La, Pr and Er) have been studies systematically by means of first principles density functional theory within generalized gradient approximation. Ground state properties such as lattice constant (a0), bulk modulus (B) and its pressure derivative (B?) are obtained. The present results are in good agreement with the experimental and other theoretical calculation available. Amongst all the Intermetallics is found ErAg to be most ductile due to the presence of strong metallic bonding. Keywords: Intermetallic compounds; Density Functional Theory; Ductility; Electronic Structure

A First Principle Study of Pressure Induced Structural and Electronic Properties in Neptunium Bismuthide

We have examined the pressure induced structural and electronic   properties of neptunium monobismuthides. The total energy as a function of volume is obtained by means of self-consistent tight binding linear muffin-tin-orbital (TB-LMTO) method within the local density approximation (LDA). It is found that NpBi is stable in NaCl – type structure under ambient pressure. We predict a structural phase transition from NaCl-type (B1-phase) sructure to CsCl-type (B2-phase) structure for NpBi in the pressure range of 11 GPa. We also calculate the lattice parameter (a0), bulk modulus (B0), band structure and density of states. From energy band diagram it is observed that NpBi exhibit metallic behaviour. The calculated equilibrium lattice parameters and bulk modulus are in general good agreement with available experimental data. Keywords: Structural phase transition; Electronic band structure; Metallic

Chitosan-Based Green and Sustainable Corrosion Inhibitors for Carbon Steel

Development of non-toxic and environmental friendly corrosion inhibitors is highly desirable owing to the increasing demands of “green chemistry” throughout the world. In view of these several forms of green corrosion inhibitors such as drugs or medicines, plant extracts, ionic liquids and synthetic inhibitors derived from multicomponent reactions (MCRs) and mechanochemical mixing are being employed. Nowadays, MCRs in association with microwave and ultrasound irradiations represent one of the best green strategies. Natural polysaccharides particularly chitosan derivatives gained substantial advancement. Chitosan and its several derivatives have been employed effective as corrosion inhibitors for metals and alloys in various aggressive media. The present chapter features the collection of major works that have been published on the inhibition effect of chitosan and its derivatives. The utilization of the chitosan and its derivatives as effective corrosion inhibitors is based on the fact that they contain several polar functional groups such as amino (-NH2), hydroxyl (-OH) and acetyl (-COCH3) groups that effectively bind with metallic surface and behave as adsorption centers