Recently frequent and sequential pattern mining algorithms have been widely used in the field of software engineering to mine various source code or specification patterns. In practice software ...evolves from one version to another is needed for providing extra facilities to user. This kind of task is challenging in this domain since the database is usually updated in all kinds of manners such as insertion, various modifications as well as removal of sequences. If database is optimized then this optimized information will help developer in their development process and save their valuable time as well as development expenses. Some existing algorithms which are used to optimize database but it does not work faster when database is incrementally updated. To overcome this challenges an efficient algorithm is recently introduce, called the Canonical Order Tree that captures the content of the transactions of the database and orders. In this paper we have proposed a technique based on the Canonical Order Tree that can find out frequent patterns from the incremental database with speedy and efficient way. Thus the database will be optimized as well as it gives useful information to recommend software developer.
Coronavirus disease-19 (COVID-19) are deadly and infectious disease that impacts individuals in a variety of ways. Scientists have stepped up their attempts to find an antiviral drug that targets the ...spike protein (S) of Angiotensin converting enzyme 2 (ACE2) (receptor protein) as a viable therapeutic target for coronavirus. The most recent study examines the potential antagonistic effects of 17 phytochemicals present in the plant extraction of
on the anti-SARS-CoV-2 ACE2 protein. Computational techniques like molecular docking, absorption, distribution, metabolism, excretion, and toxicity (ADMET) investigations, and molecular dynamics (MD) simulation analysis were used to investigate the actions of these phytochemicals. The results of molecular docking studies showed that the control ligand (2-acetamido-2-deoxy-β-D-glucopyranose) had a binding potential of -6.2 kcal/mol, but the binding potentials of delphin, β-amyrin, and tulipanin are greater at -10.4, 10.0, and -9.6 kcal/mol. To verify their drug-likeness, the discovered hits were put via Lipinski filters and ADMET analysis. According to MD simulations of the complex run for 100 numbers, delphin binds to the SARS-CoV-2 ACE2 receptor's active region with good stability. In root-mean-square deviation (RMSD) and root mean square fluctuation (RMSF) calculations, delphinan, β-amyrin, and tulipanin showed reduced variance with the receptor binding domain subunit 1(RBD S1) ACE2 protein complex. The solvent accessible surface area (SASA), radius of gyration (Rg), molecular surface area (MolSA), and polar surface area (PSA) validation results for these three compounds were likewise encouraging. The convenient binding energies across the 100 numbers binding period were discovered by using molecular mechanics of generalized born and surface (MM/GBSA) to estimate the ligand-binding free energies to the protein receptor. All things considered, the information points to a greater likelihood of chemicals found in
binding to the SARS-CoV-2 ACE2 active site. To determine these lead compounds' anti-SARS-CoV-2 potential, in vitro and
studies should be conducted.
Islam MN, Pramanik MEA, Hossain MA,
. Identification of Leading Compounds from
(Dudsor) Extracts as a Potential Inhibitor of SARS-CoV-2 ACE2-RBDS1 Receptor Complex: An Insight from Molecular Docking ADMET Profiling and MD-simulation Studies. Euroasian J Hepato-Gastroenterol 2023;13(2):89-107.
This paper describes an automated selection of the ST segment in 12 leads electrocardiogram (ECG) as well as its classification based on cross correlation. Our proposed method classifies five ...categories of ST segment which are (a) Up slop (b) Down slop (c) Horizontal (Normal) (d) Concave (e) Convex using cross correlation process. We compare the main ECG (patient ECG) ST segment with the above-mentioned reference ST segments. In this work we have used MIT-BIH ST change database and European ST-T change database where every database contains minimum 30 min and maximum 1-h episode. Our method contains the following steps (1) Filtering ECG signal and Detrending it (2) R peak and S peak detection (3) Starting and ending point detection of ST segment (4) Comparing with ST segment supervised data (5) Classifying the ST segment. We have used total 1,34,879 beats where 58,331 beats from MIT-BIH ST change database and 74,609 beats from European ST-T change database. We have correctly selected total 126,608 ST segments. ST segment classification accuracy is 88.20% for MIT-BIH ST change database and 96.18% for European ST-T change database. The method confirms satisfactory performance with an overall accuracy of 92.1% which is helpful to the detection of major heart diseases like myocardial ischemia.
Coronavirus disease-2019 (COVID-19) has shattered the public health delivery system of most of the countries of the world. COVID-19 displays variable clinical presentations. The severe COVID-19 ...represents a fulminant pathological condition and most of the patients run a downhill course if extensive medical measures are not adopted. The major challenges about COVID-19 are related to develop strategies to manage huge populations of mild and moderate cases of COVID-19 with two realistic purposes: (1) early negativity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and (2) arrest of progression of moderate COVID-19 patients from developing severe complications. Although several medications have been repurposed for these purposes, none of these have passed the test of time in global perspective. Thus, there remains a pressing need to develop new and novel innovative management strategies for these patients as new variants of SARS-CoV-2 have been destroying the normal public health delivery system of different countries from time to time. The study presented here has checked the safety and efficacy of a herbal medication, leaves of Euphorbia neriifolia Linn (E. neriifolia), in mild and moderate COVID-19 patients. Sixty patients (30 mild COVID-19 and 30 moderate COVID-19) were enrolled in the study. Fifteen mild COVID-19 patients received standard of care (SOC) management, and the remaining 15 patients received SOC plus E. neriifolia. The moderate COVID-19 patients similarly received either SOC (N = 15) or SOC plus E. neriifolia (N = 15). Although there were marked diversity regarding biochemical parameters of these patients at entry, the moderate COVID-19 patients receiving E. neriifolia showed decrease in C-reactive protein and D-dimer and increase in oxygen saturation 7 days after trial commencement. However, these improvements were not detected in moderate COVID-19 patients receiving SOC. Hospital staying was significantly lower in both mild and moderate COVID-19 patients receiving SOC plus E. neriifolia than those receiving only SOC. Taken together, it may be proposed that usage of E. neriifolia may have beneficial effects regarding management for COVID-19 patients, especially for those in developing and resource-constrained countries, although a conclusive statement may not be given due to small sample size. This herbal medication is also pertinent in the context of emergence of OMICRON variant of COVID-19 as the overload of SARS-CoV-2-infecetd patients may be addressed considerably by this medication without hospitalization, if proper communication between patients and physicians can be ensured. How to cite this articlePramanik MEA, Miah MMZ, Ahmed I, et al. Euphorbia neriifolia Leaf Juice on Mild and Moderate COVID-19 Patients: Implications in OMICRON Era. Euroasian J Hepato-Gastroenterol 2022;12(1):10-18.
Bioinformatics deals with biological data and analyzes or processes the data using computer science techniques. With the appearance of modern bioinformatics tools, it is now possible to design a drug ...using these high technologies and open a new area of drug design and development. This research predicts to design a common drug for four associated mental disorders that include bipolar disorder, schizophrenia, coronary heart diseases and stroke. The key to drug design is a biomolecule or protein. To show the protein interactions and evolutions, a protein-protein interaction network is created among the common genes of the four diseases. The genes corresponding to each disease are collected from NCBI gene database. These genes are preprocessed, mined and verified to find the common genes among the diseases. After getting common genes (7 genes), PPI network is created with them. Then a common drug is designed that will work on four investigated diseases. This structure based drug design research will open a new era to discover and develop new drug compounds using different bioinformatics tools.
Depression, Major Depression or mental disorder creates severe diseases. Mental illness such as Unipolar Major Depression, Bipolar Disorder, Dysthymia, Schizophrenia, Cardiovascular Diseases ...(Hypertension, Coronary Heart Disease, Stroke) etc., are known as Major Depression. Several studies have revealed the possibilities about the association among Bipolar Disorder, Schizophrenia, Coronary Heart Diseases and Stroke with each other. The current study aimed to investigate the relationships between genetic variants in the above four diseases and to create a common pathway or PPI network. The associated genes of each disease are collected from different gene database with verification using R. After performing some preprocessing, mining and operations using R on collected genes, seven (7) common associated genes are discovered on selected four diseases (SZ, BD, CHD and Stroke). In each of the iteration, the numbers of collected genes are reduced up to 51%, 36%, 10%, 2% and finally less than 1% respectively. Moreover, common pathway on selected diseases has been investigated in this research.
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