MOLECULAR MODELLING AND DOCKING STUDIES OF HUMAN ACROSIN BINDING PROTEIN (ACRBP/OY-TES-1)

Objective: We have made an attempt to identify inhibitors that are bound with Acrosin binding protein (ACRBP/OY-TES-1) through In silico molecular docking studies.Methods: Modeling of ACRBP/OY-TES-1 was performed using Iterative Threading Assembly Refinement (I-TASSER) software. Docking calculations were carried out using Glide. Glide Score (GS core) was used to rank the ligands on the basis of their relative binding affinities.Results: Food and Drug Administration (FDA)-approved drugs were docked with ACRBP/OY-TES-1 to identify potent inhibitors. Leuprolide a decapeptide interacts with the protein at residues Tyr116, Gly421, Leu433, Asp480 and Gln483 with Glide score-14.188. Other compounds that showed high affinity to the protein are triptorelin, nafatarelin, goserelin and sincalide.Conclusion: The investigation concluded that these drugs could be used as potential inhibitors against ACRBP/OY-TES-1 in cancer treatment.Â

EMR Adoption: A User Perception Study

Despite promise of significant benefits, inadequate user acceptance has frequently limited the impact of EMR implementations. Using an action research approach, our team is participating in an EMR implementation at Aravind Eye Care System (AECS), one of the largest eye hospitals in the world, to observe its current practices, measure user perceptions of EMR, plan interventions, and assess their impact. Our proximate research objective is to develop interventions based on sound conceptual foundations and empirical validation rather than in an ad hoc manner, to facilitate EMR acceptance by AECS hospital staff. The ensuing goal is to learn from the post intervention findings to develop guidelines for EMR implementations, particularly in a developing country context. In this paper we report on the first phase of this study, and these initial results show how even simple analysis of perception patterns can help to customize and shape intervention plans

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure < 100 mmHg (n = 1127), estimated glomerular filtration rate < 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

Big Data and Personalisation for Non-Intrusive Smart Home Automation

With the advent of the Internet of Things (IoT), many different smart home technologies are commercially available. However, the adoption of such technologies is slow as many of them are not cost-effective and focus on specific functions such as energy efficiency. Recently, IoT devices and sensors have been designed to enhance the quality of personal life by having the capability to generate continuous data streams that can be used to monitor and make inferences by the user. While smart home devices connect to the home Wi-Fi network, there are still compatibility issues between devices from different manufacturers. Smart devices get even smarter when they can communicate with and control each other. The information collected by one device can be shared with others for achieving an enhanced automation of their operations. This paper proposes a non-intrusive approach of integrating and collecting data from open standard IoT devices for personalised smart home automation using big data analytics and machine learning. We demonstrate the implementation of our proposed novel technology instantiation approach for achieving non-intrusive IoT based big data analytics with a use case of a smart home environment. We employ open-source frameworks such as Apache Spark, Apache NiFi and FB-Prophet along with popular vendor tech-stacks such as Azure and DataBricks

Temperature Tolerance in the Five Field Strains of Trichogramma chilonis from Northern Districts of Tamil Nadu, India

The egg parasitoid, Trichogramma chilonis is a potential egg parasitoid in the agricultural ecosystem, reducing many lepidopteran pest incidences. The laboratory strains of T. chilonis was significantly inferior to the ecotypes collected from fields in their parasitisation potential and tolerance to temperature due to continuous exposure to temperature extremes in the field. Hence, a study was undertaken to evaluate the laboratory reared strain of T. chilonis with that of other ecotypes to identify a temperature tolerant ecotype for use in pest management programme. Five ecotypes of T. chilonis were collected from farmer's fields on sugarcane and citrus using sentinel egg technique by exposing egg cards of Corcyra cephalonica, mass reared on C. cephalonica for three successive generations and tested for their relative tolerance to temperature in comparison with the laboratory population. The emergence percentage of the parasitoid varied with the ecotypes tested and all the field collected ecotypes recorded increased emergence compared to the laboratory population. At 150 C, the emergence was significantly higher in Chitteri ecotype (83.44%) followed by Arungunam and Amirthapuram ecotype (78.65 and 75.57%). The performance of all the ecotypes were best at 200 C and Chitteri ecotype performed significantly better compared to other ecotypes and the laboratory population with an adult emergence of 95.66 per cent. It was followed by Arungunam ecotype (88.65%) at 200 C. While the laboratory population and other ecotypes failed to develop at 350 C, Chitteri and Arungunam ecotypes were able to develop with 9.66 and 7.25 per cent adult emergence from the parasitised eggs

Investigation of differentially expressed genes and dysregulated pathways involved in multiple sclerosis

Multiple Sclerosis (MS) is a neurodegenerative autoimmune and organ-specific demyelinating disorder, known to affect the central nervous system (CNS). While genetic studies have revealed several critical genes and diagnostic biomarkers associated with MS, the etiology of the disease remains poorly understood. This study is aimed at screening and identifying the key genes and canonical pathways associated with MS. Gene expression profiling of the microarray dataset GSE38010 was used to analyze two control brain samples (control 1; GSM931812, control 2; GSM931813), active inflammation stage samples (CAP1; GSM931815, CAP2; GSM931816) and late subsided stage samples (CP1; GSM931817, CP2; GSM931818) collected from patients ranging between 23 and 54 years and both genders. This analysis yielded a list of 58,866 DEGs (29,433 for active-inflammation stage and 29,433 for late-subsided Stage). The interactions between the DEGs were then studied using STRING, Cytoscape software, and MCODE was employed to find the genes that form clusters. Functional enrichment and integrative analysis were performed using ClueGO/CluePedia and MetaCore. Our data revealed dysregulated key canonical pathways in MS patients. In addition, we identified three hub genes (SCN2A, HTR2A, and HCN1) that may serve as potential biomarkers for the prognosis of MS. Furthermore, the expression patterns of HPCA and PLCB1 provide insights into the progressive stages of MS, indicating that these genes could be used in predicting MS progression. We were able to map potential biomarkers that could be used for the prognosis and diagnosis of MS. 2022 Elsevier Inc.The authors would like to take this opportunity to thank the management of Vellore Institute of Technology (VIT), Vellore, India, and Qatar University, Doha, Qatar, for providing the necessary facilities and encouragement to carry out this work. UKS, HZ, and GPDC were involved in the study's design. UKS, AD, TM, SR, and GR were involved in the data collection and conducted the experiment. UKS, AD, SY, TM, SR, and GR were involved in the acquisition, analysis, and interpretation results. UKS and AD drafted the manuscript. GPDC and HZ supervised the entire study and were involved in the study design, the acquisition, analysis, and understanding of the data, and critically reviewed the manuscript. All authors edited and approved the submitted version of the article. The authors have declared that no conflicts of interest exist.Scopu