Reproductive success in Zygogramma bicolorata: A role of post-insemination association of male and female

Reproductive success is attained by various mechanisms in insects. Prolonged post insemination association is one such mechanism to increase the reproductive success. The present study was conducted to assess the role of post insemination association of mating partners on reproductive performance in Chrysomelidae beetle, Zygogramma bicolorata Pallister. The matings were disrupted at different time intervals and fecundity and percent egg viability of the females were recorded. In addition, the mounting attempts, mating attempts, time to commencement of mating and latent period were also recorded. It was hypothesized that: (1) the mounting and mating attempts would not exist, (2) copulation duration, would not affect the reproductive performance, and (3) the beetle would not exhibit the mate guarding behaviour. Interestingly, results revealed that 6.00 ± 1.3 and 6.59 ± 0.93 mounting and mating attempts are needed to establish successful mating. The results revealed that males improved their percent egg viability with a mating duration ranging from nearly 30–50 min. While fecundity increased with a mating duration of above 30 min and up to a duration of 60 min. This result concluded that males of this beetle display post copulatory mate guarding behaviour after 60 min in which male rides on female’s back with his aedeagus inserted in the female genital tract.     

Physiological responses of wheat to drought stress and its mitigation approaches

Drought is a polygenically controlled stress and a major agricultural risk that reduces crop productivity and limits the successful insight of land potential throughout the world. This review article has been divided into two parts, i.e., effect of drought stress on physiology of wheat and potential drought mitigation approaches. In the first part, physiological responses of wheat to stress were discussed. Cell membrane stability, relative water content, early maturity, decreased leaf area, small plant size, increased dry weight and root–shoot ratio, and the whole-plant transpiration rate response to enhanced atmospheric vapor pressure deficit are physiological traits associated with drought tolerance in wheat. Reduction of relative water content closes stomata and thereby reduces stomatal conductance. Osmotic adjustment improves drought tolerance by allowing cell enlargement, plant growth, and stomata to stay partially open and by maintaining CO₂ fixation under severe water deficit. The wheat plant accumulates several organic and inorganic solutes in its cytosol to lessen its osmotic potential for maintenance of cell turgor. Drought affects photosynthesis negatively by changing the inner structure of chloroplasts, mitochondria, and chlorophyll content and minerals. Destruction of the photosystem II (PSII) oxygen releasing complex and reaction center can disturb production and use of electrons, causing lipid peroxidation of cell membrane through the production of reactive oxygen species. In the second part, drought mitigation approaches were discussed. Seed, drought, bacterial, and hormonal priming are common approaches used to lessen the effects of water deficit. Physiological trait-based breeding, molecular breeding, marker-assisted backcrossing, aerial phenotyping, water budgeting, and resource allocation are modern approaches used to develop drought tolerant wheat cultivars. Wheat genotypes produced as a result of a combination of all these methodologies will increase food security regarding the currently changing climate.     

Computer aided prediction and identification of potential epitopes in the receptor binding domain (RBD) of spike (S) glycoprotein of MERS-CoV

Middle East Respiratory Syndrome Coronavirus (MERS-CoV) belongs to the coronaviridae family. In spite of several outbreaks inthe very recent years, no vaccine against this deadly virus is developed yet. In this study, the receptor binding domain (RBD) ofSpike (S) glycoprotein of MERS-CoV was analyzed through Computational Immunology approach to identify the antigenicdeterminants (epitopes). In order to do so, the sequences of S glycoprotein that belong to different geographical regions werealigned to observe the conservancy of MERS-CoV RBD. The immune parameters of this region were determined using different insilico tools and Immune Epitope Database (IEDB). Molecular docking study was also employed to check the affinity of the potentialepitope towards the binding cleft of the specific HLA allele. The N-terminus RBD (S367-S606) of S glycoprotein was found to beconserved among all the available strains of MERS-CoV. Based on the lower IC₅₀ value, a total of eight potential T-cell epitopes and19 major histocompatibility complex (MHC) class-I alleles were identified for this conserved region. A 9-mer epitope CYSSLILDYdisplayed interactions with the maximum number of MHC class-I molecules and projected the highest peak in the B-cellantigenicity plot which concludes that it could be a better choice for designing an epitope based peptide vaccine against MERSCoVconsidering that it must undergo further in vitro and in vivo experiments. Moreover, in molecular docking study, this epitopewas found to have a significant binding affinity of -8.5 kcal/mol towards the binding cleft of the HLA-C*12:03 molecule.     

Theory to Predict Shear Stress on Cells in Turbulent Blood Flow

Shear stress on blood cells and platelets transported in a turbulent flow dictates the fate and biological activity of these cells. We present a theoretical link between energy dissipation in turbulent flows to the shear stress that cells experience and show that for the case of physiological turbulent blood flow: (a) the Newtonian assumption is valid, (b) turbulent eddies are universal for the most complex of blood flow problems, and (c) shear stress distribution on turbulent blood flows is possibly universal. Further we resolve a long standing inconsistency in hemolysis between laminar and turbulent flow using the theoretical framework. This work demonstrates that energy dissipation as opposed to bulk shear stress in laminar or turbulent blood flow dictates local mechanical environment of blood cells and platelets universally.     

In-silico network-based analysis of drugs used against COVID-19: Human well-being study

IntroductionResearchers worldwide with great endeavor searching and repurpose drugs might be potentially useful in fighting newly emerged coronavirus. These drugs show inhibition but also show side effects and complications too. On December 27, 2020, 80,926,235 cases have been reported worldwide. Specifically, in Pakistan, 471,335 has been reported with inconsiderable deaths.Problem statementIdentification of COVID-19 drugs pathway through drug-gene and gene−gene interaction to find out the most important genes involved in the pathway to deal with the actual cause of side effects beyond the beneficent effects of the drugs.MethodologyThe medicines used to treat COVID-19 are retrieved from the Drug Bank. The drug-gene interaction was performed using the Drug Gene Interaction Database to check the relation between the genes and the drugs. The networks of genes are developed by Gene MANIA, while Cytoscape is used to check the active functional association of the targeted gene. The developed systems cross-validated using the EnrichNet tool and identify drug genes'' concerned pathways using Reactome and STRING.ResultsFive drugs Azithromycin, Bevacizumab, CQ, HCQ, and Lopinavir, are retrieved. The drug-gene interaction shows several genes that are targeted by the drug. Gene MANIA interaction network shows the functional association of the genes like co-expression, physical interaction, predicted, genetic interaction, co-localization, and shared protein domains.ConclusionOur study suggests the pathways for each drug in which targeted genes and medicines play a crucial role, which will help experts in-vitro overcome and deal with the side effects of these drugs, as we find out the in-silico gene analysis for the COVID-19 drugs.     

RNA-SSPT: RNA Secondary Structure Prediction Tools

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.     

Computational approach to the identification of novel Aurora-A inhibitors

Aurora kinase A has been emerging as a key therapeutic target for the design of anticancer drugs. For the purpose of finding biologically active and novel compounds and providing new ideas for drug-design, we performed virtual screening using commercially available databases. A three-dimensional common feature pharmacophore model was developed with the HipHop program provided in the Catalyst software package, and this model was used as a query for screening the databases. A recursive partitioning (RP) model was developed as a filtering system, which was able to classify active and inactive compounds. Eventually, a step-wise virtual screening procedure was conducted by applying the common feature pharmacophore and the RP model in succession to discover novel potent Aurora-A inhibitors. A total of 68 compounds were selected for testing of their in vitro anticancer activities against various human cancer cell lines. Based on the activity data, we have identified fifteen compounds that warrant further investigation. Several compounds have a high inhibition rate (above 80% at 10 ??M) and a GI₅₀ lower than 5 ??M for the cell lines DU145 and HT29. Enzyme assay for these compounds identified hits with micro molar activity. Compound C11 has the highest activity (IC₅₀ = 5.09 ??M). The hits obtained from this screening scheme could be potential drug candidates after further optimization.     

Down-regulation of hepatic G-6-Pase expression in hyperglycemic rats: Intervention with biogenic gold nanoconjugate

Chronic diabetes extensively complicates the glucose metabolism to onset and progress the complication. Concurrently, several contemporary medicines, especially organo-metallic formulations, are emerging to treat hyperglycemia. The current study aims to emphasize the gold nanoparticles (GNPs) potential for glucose metabolism regulation in Streptozotocin (STZ) induced diabetes. Quantitative real-time polymerase chain reaction (RT-PCR) was carried out to detect the mRNA expression of Glucose transporters 2 (GLUT2), Glucokinase (GK) and Glucose 6 Phosphatase (G-6-Pase). The study shows remarkable results such as the prognostic effect of GNPs in reinforcing the repression of enzyme complex G-6-Pase about 13.3-fold when compared to diabetes control. Also, molecular docking studies showed significant inhibition of G-6-Pase by the terpenoid ligands with alpha and beta amyrin from leaf extract of Couroupita guianensis. Thus the study explored the novel mechanism of G-6-Pase downregulated by GNPs intervention that majorly contributes to the regulation of circulatory glucose homeostasis during diabetes.