Shiv Nadar University

About: Shiv Nadar University is a education organization based out in Dadri, Uttar Pradesh, India. It is known for research contribution in the topics: Population & Graphene. The organization has 1015 authors who have published 1924 publications receiving 18420 citations.

Genome-wide analysis of glutathione S-transferase gene family in chickpea suggests its role during seed development and abiotic stress.

Abstract: Glutathione S-transferases (GSTs) are multifunctional proteins that help in oxidative stress metabolism and detoxification of xenobiotic compounds. Studies pertaining to GST gene family have been undertaken in various plant species, however no information is available with respect to GST genes in chickpea. In the current study, we identified a total of 51 GST encoding genes in chickpea (CaGST) genome. Phylogenetic analysis revealed that GST gene family can be divided into eleven distinct classes. Tau and phi were the major classes in chickpea and one third of the CaGST genes represented segmental duplication and purifying selection was common among these genes. Expression of many CaGST genes, in particular, members of tau class were found to be upregulated under abiotic stress conditions. In addition, CaGST genes displayed differential expression patterns across diverse organs/tissues, suggesting their roles in developmental processes. Many CaGST genes showed opposite expression pattern in small- and large-seeded chickpea cultivars during seed development. Higher expression of CaGST genes in small-seeded cultivar at maturation stages of seed development suggested their important role in seed development and seed size/weight determination in chickpea. Overall, these results provide a comprehensive information on GST gene family members in chickpea and is expected to provide a rational platform to explore versatile role of these genes in semi-arid legume crops.

Decoding Crucial LncRNAs Implicated in Neurogenesis and Neurological Disorders

Abstract: Unraveling transcriptional heterogeneity and the labyrinthine nature of neurodevelopment can probe insights into neuropsychiatric disorders. It is noteworthy that adult neurogenesis is restricted to the subventricular and subgranular zones of the brain. Recent studies suggest long non-coding RNAs (lncRNAs) as an avant-garde class of regulators implicated in neurodevelopment. But, paucity exists in the knowledge regarding lncRNAs in neurogenesis and their associations with neurodevelopmental defects. To address this, we extensively reviewed the existing literature databases as well as performed relevant in-silico analysis. We utilized Allen Brain Atlas (ABA) differential search module and generated a catalogue of ∼30,000 transcripts specific to the neurogenic zones, including coding and non-coding transcripts. To explore the existing lncRNAs reported in neurogenesis, we performed extensive literature mining and identified 392 lncRNAs. These degenerate lncRNAs were mapped onto the ABA transcript list leading to detection of 20 lncRNAs specific to neurogenic zones (Dentate gyrus/Lateral ventricle), among which 10 showed associations to several neurodevelopmental disorders following in-silico mapping onto brain disease databases like Simons Foundation Autism Research Initiative, AutDB, and lncRNADisease. Notably, using ABA correlation module, we could establish lncRNA-to-mRNA coexpression networks for the above 10 candidate lncRNAs. Finally, pathway prediction revealed physical, biochemical, or regulatory interactions for nine lncRNAs. In addition, ABA differential search also revealed 54 novel significant lncRNAs from the null set (∼30,000). Conclusively, this review represents an updated catalogue of lncRNAs in neurogenesis and neurological diseases, and overviews the field of OMICs-based data analysis for understanding lncRNome-based regulation in neurodevelopment.

Activation of the Hg–C Bond of Methylmercury by [S2]-Donor Ligands

Abstract: Here we report that [S2]-donor ligands BmmOH, BmmMe, and BmeMe bind rapidly and reversibly to the mercury centers of organomercurials, RHgX, and facilitate the cleavage of Hg–C bonds of RHgX to produce stable tetracoordinated Hg(II) complexes and R2Hg Significantly, the rate of cleavage of Hg–C bonds depends critically on the X group of RHgX (X = BF4–, Cl–, I–) and the [S2]-donor ligands used to induce the Hg–C bonds For instance, the initial rate of cleavage of the Hg–C bond of MeHgI induced by BmeMe is almost 2-fold higher than the initial rate obtained by BmmOH or BmmMe, indicating that the spacer between the two imidazole rings of [S2]-donor ligands plays a significant role here in the cleavage of Hg–C bonds Surprisingly, we noticed that the initial rate of cleavage of the Hg–C bond of MeHgI induced by BmeMe (or BmmMe) is almost 10-fold and 100-fold faster than the cleavage of Hg–C bonds of MeHgCl and [MeHg]BF4 respectively, under identical reaction conditions, suggesting that the Hg–C bond of [MeH

Graph Signal Processing of EEG signals for Detection of Epilepsy

Abstract: Epileptic Seizure is a chronic nervous system disorder which is analyzed using Electroencephalogram (EEG) signals. This paper proposes a Graph Signal Processing technique called Graph Discrete Fourier Transform (GDFT) for the detection of epilepsy. EEG data points are projected on the Eigen space of Laplacian matrix of graph to produce GDFT coefficients. The Laplacian matrix is generated from weighted visibility graph constructed from EEG signals. It proposes Gaussian kernel based edge weights between the nodes. The proposed GDFT based feature vectors are then used to detect the seizure class from the given EEG signal using a crisp rule based classification. Simulation results show that the proposed GDFT based features from Gaussian Weighted Visibility Graph (VG) can detect epileptic seizure with 100 % accuracy.

Complex concentrated alloy bimodal composite claddings with enhanced cavitation erosion resistance

Abstract: In this current study, we developed SiC (10 wt%) reinforced AlCoCrFeNi complex concentrated alloy composite claddings with different particle sizes (micro, nano and bimodal) on stainless steel 316L substrate using microwave irradiation. Microstructural analysis showed cellular structured claddings with intermetallic phases occupying the intercellular regions along with low porosity (