In recent years, CRISPR–Cas9 technology is widely acknowledged for having major applications in the field of biotechnology for editing genome of any organism to treat a variety of complex diseases ...and for other purposes. The acronym ‘CRISPR–Cas’ stands for clustered regularly interspaced short palindromic repeats–CRISPR-associated genes. This genetic organization exists in prokaryotic organisms and aids in the development of adaptive immunity since a protein called Cas9 nuclease cleaves specific target nucleic acid sequences from foreign invaders and destroys them. This mode of action has gained interest of the researchers to understand the insights of CRISPR–Cas9 technology. Here, we review that CRISPR–Cas organization is restricted to two classes and possesses different protein effectors. We also review the architecture of CRISPR loci, mechanism involved in genome editing by CRISPR–Cas9 technology and pathways of repairing double-strand breaks (DSBs) generated during the process of genome editing. This review also presents the strategies to increase the Cas9 specificity and reduce off-target activity to achieve accurate genome editing. Further, this review provides information on CRISPR tools used for genome editing, databases that are required for storing data on loci, strategies for delivering CRISPR–Cas9 to cells under study and applications of CRISPR–Cas9 to various fields. Safety measures are implemented on this technology to avoid misuse or ethical issues. We also discuss about the future aspects and potential applications of CRISPR–Cas9 technology required mainly for the treatment of dreadful diseases, crop improvement as well as genetic improvement in human.
Teschovirus A
belongs to the family Picornaviridae and is a causal agent of the disease Teschovirus encephalomyelitis and other infections that remain asymptomatic. The present study was performed to ...design epitope-based peptide vaccine against
Teschovirus A
by identifying the potential T cell and B-cell epitopes from capsid proteins (VP1, VP3 and VP2) of the virus using reverse vaccinology and immunoinformatics approaches. In the current study, hexapeptide T-cell and octapeptide B-cell epitopes were analyzed for immunogenicity, antigenicity and hydrophilicity scores of each epitope. Each potential epitope was further characterized using ExPASy-ProtParam and Antimicrobial Peptide Database (APD3) tools for determining various physical and chemical parameters of the epitope. One linear hexapeptide T-cell epitope, i.e., RPVNDE (epitope position 77–82) and one linear octapeptide B-cell epitope, i.e., AYSRSHPQ (236–243) were identified from the viral capsid protein as they possess the capability to raise effective immunogenic reaction in the host organism against the virus. Pharmaceutical industries could harness the results of this investigation to develop epitope-based peptide vaccines by loading the identified epitopes in combination with targeting signal peptides of T-cells and B-cells and then inserting the combination into virus like particle (vlp) or constructing subunit vaccines for further trial.
Japanese encephalitis (JE) is a serious leading health complication emerging expansively that has severely affected the survival rate of human beings. This fatal disease is caused by JE Virus (JEV). ...The current study was carried out for designing a multi-epitope loaded peptide vaccine to prevent JEV. Based on reverse vaccinology and in silico approaches, octapeptide B-cell and hexapeptide T-cell epitopes belonging to five proteins, viz. E, prM, NS1, NS3 and NS5 of JEV were determined. Hydrophilicity, antigenicity, immunogenicity and aliphatic amino acids of the epitopes were estimated. Further, the epitopes were analyzed for different physicochemical parameters, e.g. total net charges, amino acid composition and Boman index. Out of all the epitopes, a total of four T-cell epitopes namely KRADSS, KRSRRS, SKRSRR and KECPDE and one B-cell epitope i.e. PKPCSKGD were found to have potential for raising immunity in human against the pathogen. Taking into account the outcome of this study, the pharmaceutical industries could initiate efforts to combine the identified epitopes together with adjuvant or carrier protein to develop a multi-epitope-loaded peptide vaccine against JEV. The peptide vaccine, being cost effective, could be administered as a prophylactic measure and in JEV infected individuals to combat the spread of this virus in human population. However, prior to administration into human beings, the vaccine must pass through several clinical trials.
•Potential T and B-cell epitopes of 5 proteins in Japanese encephalitis virus (JEV) were determined using bioinformatics.•All epitopes were analyzed for hydrophilicity, immunogenicity, antigenicity and other physicochemical parameters.•Identified epitopes could be used for developing a multi-epitope-loaded peptide vaccine to combat JEV.
In today world of enormous amounts of data, it is very important to extract useful knowledge from it. This can be accomplished by feature subset selection. Feature subset selection is a method of ...selecting a minimum number of features with the help of which our machine can learn and predict which class a particular data belongs to. We will introduce a new adaptive algorithm called Feature selection Penguin Search optimization algorithm which is a metaheuristic approach. It is adapted from the natural hunting strategy of penguins in which a group of penguins take jumps at random depths and come back and share the status of food availability with other penguins and in this way, the global optimum solution is found. In order to explore the feature subset candidates, the bioinspired approach Penguin Search optimization algorithm generates during the process a trial feature subset and estimates its fitness value by using three different classifiers for each case: Random Forest, Nearest Neighbour and Support Vector Machines. However, we are planning to implement our proposed approach Feature selection Penguin Search optimization algorithm on some well known benchmark datasets collected from the UCI repository and also try to evaluate and compare its classification accuracy with some state of art algorithms.
In today’s world of enormous data, it is important to effectively extract information from the available data. This can be accomplished using feature subset selection. Feature subset selection is a ...method of selecting minimum number of features, with the help of which our machine can learn and accurately predict which class a particular data belongs to. In this chapter, we will introduce a new adaptive algorithm called feature selection penguin search optimization algorithm, which is a metaheuristic feature subset selection method. It is adapted from the natural hunting strategy of penguins, in which a group of penguins take jumps at random depths and come back and share the status of food availability with other penguins, and in this way, a global optimum solution is found, namely penguin search optimization algorithm. It will be combined with different classifiers to find the optimal feature subset. In order to explore the feature subset candidates, the bioinspired approach penguin search optimization algorithm generates during the process a trial feature subset that estimates its fitness value by using three different classifiers for each case: random forest, nearest neighbor, and support vector machines. However, we are planning to implement our proposed feature selection penguin search optimization algorithm on some well-known benchmark datasets collected from the UCI repository and also try to evaluate and compare its classification accuracy with some state-of-the-art algorithms.
In this chapter, the authors work upon feature subset selection using “penguin search algorithm,” inspired by the hunting strategy of the penguins. The catholic optimization process starts based on the individual hunting process of each penguin, who must share information to his group related to the number of fish found of their individual hunting area. The universal solution is chosen by a selection of the best group of penguins who ate the maximum number of fish. All the penguins work as a whole unit to deliver a single objective, to find the maximum amount of food that they can find with a limited number of resources. In contrary to the actual world phenomenon of finding food by the penguins, they look for real-time quantity of food, and based on this quantity of food, they compare the quality of a particular location. The penguins will usually go towards the location that has a better food quantity than the others.
Gene systems are extremely complex, heterogeneous, and noisy in nature. Many statistical tools which are used to extract relevant feature from genes provide fuzzy and ambiguous information. ...High-dimensional gene expression database available in public domain usually contains thousands of genes. Efficient prediction method is demanding nowadays for accurate identification of such database. Euclidean distance measurement and principal component analysis methods are applied on such databases to identify the genes. In both methods, prediction algorithm is based on homology search approach. Digital Signal Processing technique along with statistical method is used for analysis of genes in both cases. A two-level decision logic is used for gene classification as healthy or cancerous. This binary logic minimizes the prediction error and improves prediction accuracy. Superiority of the method is judged by receiver operating characteristic curve.
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•Gene is predicted based on similarity search approach using least Euclidean distance and PCA based distance method.•Discrete Fourier transform technique is used for better and accurate representation of the signal.•Binary mapping technique is considered for simplicity of computation.•Principal component analysis method is used for dimensionality reduction of genes.•ROC curve is used for performance analysis of the methods.
Digital signal processing is gaining popularity in gene classification and prediction. Spectral content of gene is estimated using Blackman–Tukey (BT) method for identification of Homo sapiens cancer ...genes. A data reduction method; principal component analysis (PCA) is used prior to Blackman–Tukey method (PC-BT) for better identification of genes. Selection of proper model order is prime important in PCA method for considering the number of principal components (PCs) and the performance of the method depends on optimal selection of PCs. Cumulative percent variance and scree test residual percent variance are used as measurement metric for selection of PCs. Quality factor is used to judge the performance of the estimators. Simulation results show the clarity of spectrum plot in PC-BT method is 200 % higher than BT method. The spectral peaks observed in cancer genes are used to screen out cancer genes from healthy genes. The methods are successfully tested on breast, prostate and colon Homo sapiens. Healthy and cancer Homo sapiens genes are downloaded from Cancer Genome Anatomy Project (CGAP) site and National Centre for Biotechnology Information (NCBI) site.
The toxicity of any drug against normal cells is a health hazard for all humans. At present, health and disease researchers from all over the world are trying to synthesize designer drugs with ...diminished toxicity and side effects. The purpose of the present study is to enhance the bioavailability and biocompatibility of gemcitabine (GEM) by decreasing its toxicity and reducing deamination during drug delivery by incorporating it inside the hydrophobic cavity of β-cyclodextrin (β-CD) without affecting the drug ability of the parent compound (GEM). The newly synthesized inclusion complex (IC) was characterized by different physical and spectroscopic techniques, thereby confirming the successful incorporation of the GEM molecule into the nanocage of β-CD. The molecular docking study revealed the orientation of the GEM molecule into the β-CD cavity (−5.40 kcal/mol) to be stably posed for ligand binding. Photostability studies confirmed that the inclusion of GEM using β-CD could lead to better stabilization of GEM (≥96%) for further optical and clinical applications. IC (GEM-β-CD) and GEM exhibited effective antibacterial and antiproliferative activities without being metabolized in a dose-dependent manner. The CT-DNA analysis showed sufficiently strong IC (GEM-β-CD) binding (K a = 8.1575 × 1010), and this interaction suggests that IC (GEM-β-CD) may possibly exert its biological effects by targeting nucleic acids in the host cell. The newly synthesized biologically active IC (GEM-β-CD), a derivative of GEM, has pharmaceutical development potentiality.
Homo-sapiens cancer and healthy genes is identified here by estimating correlation coefficient of genes. A model has been realized in Lab VIEW environment for classification of genes based on eigen ...value decomposition (EVD) technique. Breast, Prostate and Colon genes are taken as sample database for analysis of genes. EVD method is used to reduce the dimensionality as well as preserving the class discriminatory information of genes. Feature Vector is calculated based on highest eigen value of data set which is treated as measurement metric to differentiate cancer genes from healthy genes. The EVD model successfully screen out breast cancer genes from breast healthy genes, prostate cancer genes from prostate healthy genes and also colon cancer genes from colon healthy genes.
Background: The World Health Organization (WHO) envisions a world where every pregnant woman and newborn receives comprehensive care throughout the pregnancy, childbirth and the postnatal period. ...This study aims to assess the satisfaction of pregnant women with antenatal care services at selected Upazilla Health Complexes during the Covid-19 pandemic. The aim of this study was to evaluate the satisfaction levels of pregnant women with the antenatal care services provided at selected Upazilla Health Complexes during the COVID-19 pandemic. Methods: This descriptive cross-sectional study was conducted at three selected Upazilla Health Complexes in Kishorganj district, Bangladesh, namely Hussainpur Upazilla Health Complex, Karimganj Upazilla Health Complex, and Pakundia Upazilla Health Complex. Purposive sampling was employed to recruit 163 married pregnant women attending antenatal care services at these health complexes. Data were collected through face-to-face interviews ensuring privacy and analyzed using SPSS 26, employing descriptive statistics, chi-square tests, and odds ratios with 95% confidence intervals. Results: Most pregnant women (54.6%) were aged 18-23 years. Education levels: 40.5% had SSC education, 9.2% were illiterate. Respondents expressed high satisfaction with key aspects at the Upazilla Health Complex, including medicine supply and awareness about ANC services. Continuous monitoring is crucial for patient satisfaction. Medicine supply significantly impacted satisfaction, emphasizing its importance in healthcare quality. Conclusions: Despite challenges during the COVID-19 pandemic, Upazilla Health Complexes have effectively provided antenatal care, satisfying the majority of respondents, highlighting the importance of continuous monitoring.
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