<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

(SoNS) School of Natural Sciences

We propose an exact calculation of the probability density function (PDF) and cumulative distribution function (CDF) of mutual information (MI) for a two-user multiple-input multiple-output (MIMO) multiple access channel (MAC) network over block Rayleigh fading channels. This scenario can be found in the uplink channel of MIMO non-orthogonal multiple access (NOMA) system, a promising multiple access technique for 5G networks. So far, the PDF and CDF have been numerically evaluated since MI depends on the quotient of two Wishart matrices, and no closed form for this quotient was available. We derive exact results for the PDF and CDF of extreme (the smallest/the largest) eigenvalues. Based on the results of quotient ensemble, the exact calculation for PDF and CDF of mutual information is presented via Laplace transform approach and by direct integration of joint PDF of quotient ensemble’s eigenvalues. Furthermore, our derivations also provide the parameters to apply the Gaussian approximation method, which is comparatively easier to implement. We show that approximation matches the exact results remarkably well for outage probability, i.e., CDF, above 10\%. However, the approximation could also be used for 1\% outage probability with a relatively small error. We apply the derived expressions to investigate the effects of adding antennas in the receiver and its ability to decode the weak user signal. By supposing no channel knowledge at transmitters and successive decoding at receiver, the capacity of the weak user increases and its outage probability decreases with the increment of extra antennas at the receiver end. © 2017, The Author(s).

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Physics

Fulltext

Eurasip Journal on Wireless Communications and Networking

On the Exact Distribution of Mutual Information of Two-User MIMO MAC Based on Quotient Distribution of Wishart Matrices

Volume estimates of metric balls in manifolds find diverse applications in various applied sciences including information theory and coding theory. In this paper, the focus is on the exact volume of metric balls in real Grassmann manifold, extending recent results of the complex case. Firstly, we formulate the exact volume as a multi-dimensional integral, which is then represented as an inverse Laplace transform of a Pfaffian. The Pfaffian structure arises as a result of the de-Bruijn formula for multi-dimensional integrals. Using the exact representation, examples of explicit volume formulas are given. As an application, we study the performance bound of the worst-case coherence of Grassmannian frames. © 2016 IEICE.

Proceedings of 2016 International Symposium on Information Theory and Its Applications, ISITA 2016

Volume of metric balls in real Grassmann manifold with an application to frames

Alumina nanoparticles were incorporated in blends of benzoxazine monomers synthesized from bio- and petrobased phenols, cardanol and bisphenol A, respectively, by way of a one-pot solventless methodology. The structures of the monomers were characterized by proton (1H) nuclear magnetic resonance and Fourier transform infrared spectroscopy. Thermal characterization was performed using differential scanning calorimetry and thermogravimetry. The size of bare alumina nanoparticles and those in the polymer nanocomposite was analyzed by powder X-ray diffraction. Blending of alumina particles resulted in lowering of curing temperature of benzoxazine monomer. The effect of nanoparticle incorporation was reflected in the curing behavior and adhesive properties. The adhesive strength is found to be dependent on whether solution or solventless processing is used and on the weight percent of the nanoparticles in the monomer blend. The replacement of 75\% bisphenol A content with cardanol in the benzoxazine resulted in a copolymer which showed a better or comparable adhesive strength. The adhesion was found to improve further with the incorporation of alumina nanoparticles. The lower viscosity of cardanol-based benzoxazine allowed both solventless synthesis and application of monomers, which is a way forward toward greener chemistry and low volatile organic compound processing strategies. © 2017 ICE Publishing. All rights reserved.

Chemistry

Green Materials

Nanoparticles as curing and adhesive aid for biobased and petrobased polybenzoxazines

PXR is a member of nuclear receptor superfamily and a well-characterized mediator of xenobiotic metabolism. The classical mode of PXR activation involves its binding to appropriate ligand and subsequent heterodimerization with its partner RXR. However, various factors such as post-translational modifications and crosstalk with different cellular factors may also regulate the functional dynamics and behavior of PXR. In the present study, we have identified that TIP60, an essential lysine acetyltransferase protein interacts with unliganded PXR and together this complex promotes cell migration & adhesion. TIP60 utilizes its NR Box to interact with LBD region of PXR and acetylates PXR at lysine 170 to induce its intranuclear reorganization. Also, RXR is not required for TIP60-PXR complex formation and this complex does not induce ligand-dependent PXR target gene transactivation. Interestingly, we observed that PXR augments the catalytic activity of TIP60 for histones. This is the first report demonstrating the exclusive interaction of TIP60 with PXR and uncovers a potential role for the TIP60-PXR complex in cell migration and adhesion. © 2017 The Author(s).

Life Sciences

Scientific Reports

Novel complex of HAT protein TIP60 and nuclear receptor PXR promotes cell migration and adhesion

Thalidomide [α-(N-phthalimido)glutarimide] (1) is a sedative and antiemetic drug originally introduced into the clinic in the 1950s for the treatment of morning sickness. Although marketed as entirely safe, more than 10000 babies were born with severe birth defects. Thalidomide was banned and subsequently approved for the treatment of multiple myeloma and complications associated with leprosy. Although known for more than 5 decades, the mechanism of teratogenicity remains to be conclusively understood. Various theories have been proposed in the literature including DNA damage and ROS and inhibition of angiogenesis and cereblon. All of the theories have their merits and limitations. Although the recently proposed cereblon theory has gained wide acceptance, it fails to explain the metabolism and low-dose requirement reported by a number of groups. Recently, we have provided convincing structural evidence in support of the presence of arene oxide and the quinone-reactive intermediates. However, the ability of these reactive intermediates to impart toxicity/teratogenicity needs investigation. Herein we report that the oxidative metabolite of thalidomide, dihydroxythalidomide, is responsible for generating ROS and causing DNA damage. We show, using cell lines, the formation of comet (DNA damage) and ROS. Using DNA-cleavage assays, we also show that catalase, radical scavengers, and desferal are capable of inhibiting DNA damage. A mechanism of teratogenicity is proposed that not only explains the DNA-damaging property but also the metabolism, low concentration, and species-specificity requirements of thalidomide. © 2017 American Chemical Society.

Chemical Research in Toxicology

The Dihydroxy Metabolite of the Teratogen Thalidomide Causes Oxidative DNA Damage

Long non-coding RNAs (lncRNAs) make up a significant portion of non-coding RNAs and are involved in a variety of biological processes. Accurate identification/annotation of lncRNAs is the primary step for gaining deeper insights into their functions. In this study, we report a novel tool, PLncPRO, for prediction of lncRNAs in plants using transcriptome data. PLncPRO is based on machine learning and uses random forest algorithm to classify coding and long non-coding transcripts. PLncPRO has better prediction accuracy as compared to other existing tools and is particularly well-suited for plants. We developed consensus models for dicots and monocots to facilitate prediction of lncRNAs in non-model/orphan plants. The performance of PLncPRO was quite better with vertebrate transcriptome data as well. Using PLncPRO, we discovered 3714 and 3457 high-confidence lncRNAs in rice and chickpea, respectively, under drought or salinity stress conditions. We investigated different characteristics and differential expression under drought/salinity stress conditions, and validated lncRNAs via RT-qPCR. Overall, we developed a new tool for the prediction of lncRNAs in plants and showed its utility via identification of lncRNAs in rice and chickpea. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nucleic Acids Research

PLncPRO for prediction of long non-coding RNAs (lncRNAs) in plants and its application for discovery of abiotic stress-responsive lncRNAs in rice and chickpea

Auxin response factors (ARFs) are the transcription factors that regulate auxin responses in various aspects of plant growth and development. Although genome-wide analysis of ARF gene family has been done in some species, no information is available regarding ARF genes in chickpea. In this study, we identified 28 ARF genes (CaARF) in the chickpea genome. Phylogenetic analysis revealed that CaARFs can be divided into four different groups. Duplication analysis revealed that 50\% of CaARF genes arose from duplication events. We analyzed expression pattern of CaARFs in various developmental stages. CaARF16.3, CaARF17.1 and CaARF17.2 showed highest expression at initial stages of flower bud development, while CaARF6.2 had higher expression at later stages of flower development. Further, CaARF4.2, CaARF9.2, CaARF16.2 and CaARF7.1 exhibited differential expression under different abiotic stress conditions, suggesting their role in abiotic stress responses. Co-expression network analysis among CaARF, CaIAA and CaGH3 genes enabled us to recognize components involved in the regulatory network associated with CaARFs. Further, we identified microRNAs that target CaARFs and TAS3 locus that trigger production of trans-acting siRNAs targeting CaARFs. The analyses presented here provide comprehensive information on ARF family members and will help in elucidating their exact function in chickpea. © 2017 The Author(s).

Genome-wide identification and co-expression network analysis provide insights into the roles of auxin response factor gene family in chickpea

Seed development is an intricate process regulated via a complex transcriptional regulatory network. To understand the molecular mechanisms governing seed development and seed size/weight in chickpea, we performed a comprehensive analysis of transcriptome dynamics during seed development in two cultivars with contrasting seed size/weight (small-seeded, Himchana 1 and large-seeded, JGK 3). Our analysis identified stage-specific expression for a significant proportion (>13\%) of the genes in each cultivar. About one half of the total genes exhibited significant differential expression in JGK 3 as compared with Himchana 1. We found that different seed development stages can be delineated by modules of coexpressed genes. A comparative analysis revealed differential developmental stage specificity of some modules between the two cultivars. Furthermore, we constructed transcriptional regulatory networks and identified key components determining seed size/weight. The results suggested that extended period of cell division during embryogenesis and higher level of endoreduplication along with more accumulation of storage compounds during maturation determine large seed size/weight. Further, we identified quantitative trait loci-associated candidate genes harboring single nucleotide polymorphisms in the promoter sequences that differentiate small- and large-seeded chickpea cultivars. The results provide a valuable resource to dissect the role of candidate genes governing seed development and seed size/weight in chickpea. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd

Plant Journal

Global transcriptome and coexpression network analyses reveal cultivar-specific molecular signatures associated with seed development and seed size/weight determination in chickpea

Nucleoside reverse transcriptase inhibitors (NRTIs) with L-stereochemistry have long been an effective treatment for viral infections because of the strong D-stereoselectivity exhibited by human DNA polymerases relative to viral reverse transcriptases. The D-stereoselectivity of DNA polymerases has only recently been explored structurally and all three DNA polymerases studied to date have demonstrated unique stereochemical selection mechanisms. Here, we have solved structures of human DNA polymerase $\beta$ (hPol$\beta$), in complex with single-nucleotide gapped DNA and L-nucleotides and performed presteady-state kinetic analysis to determine the Dstereoselectivity mechanism of hPol$\beta$. Beyond a similar 180° rotation of the L-nucleotide ribose ring seen in other studies, the pre-catalytic ternary crystal structures of hPol$\beta$, DNA and L-dCTP or the triphosphate forms of antiviral drugs lamivudine ((-)3TC-TP) and emtricitabine ((-)FTC-TP) provide little structural evidence to suggest that hPol$\beta$ follows the previously characterized mechanisms of D-stereoselectivity. Instead, hPol$\beta$ discriminates against L-stereochemistry through accumulation of several active site rearrangements that lead to a decreased nucleotide binding affinity and incorporation rate. The two NRTIs escape some of the active site selection through the base and sugar modifications but are selected against through the inability of hPol$\beta$ to complete thumb domain closure.

Structural basis for the D-stereoselectivity of human DNA polymerase $\beta$

Membrane proteins plays significant role in living cells. Transmembrane proteins are estimated to constitute approximately 30\% of proteins at genomic scale. It has been a difficult task to develop specific alignment tools for transmembrane proteins due to limited number of experimentally validated protein structures. Alignment tools based on homology modeling provide fairly good result by recapitulating 70-80\% residues in reference alignment provided all input sequences should have known template structures. However, homology modeling tools took substantial amount of time, thus aligning large numbers of sequences becomes computationally demanding. Here we present TM-Aligner, a new tool for transmembrane protein sequence alignment. TM-Aligner is based on Wu-Manber and dynamic string matching algorithm which has significantly improved its accuracy and speed of multiple sequence alignment. We compared TM-Aligner with prevailing other popular tools and performed benchmarking using three separate reference sets, BaliBASE3.0 reference set7 of alpha-helical transmembrane proteins, structure based alignment of transmembrane proteins from Pfam database and structure alignment from GPCRDB. Benchmarking against reference datasets indicated that TM-Aligner is more advanced method having least turnaround time with significant improvements over the most accurate methods such as PROMALS, MAFFT, TM-Coffee, Kalign, ClustalW, Muscle and PRALINE. TM-Aligner is freely available through http://lms.snu.edu.in/TM-Aligner/. © 2017 The Author(s).