Background The burden of dengue virus (DENV) infection across geographical regions of India is poorly quantified. We estimated the age-specific seroprevalence, force of infection, and number of infections in India. MethodsWe did a community-based survey in 240 clusters (118 rural, 122 urban), selected from 60 districts of 15 Indian states from five geographical regions. We enumerated each cluster, randomly selected (with an Andriod application developed specifically for the survey) 25 individuals from age groups of 5-8 years, 9-17 years, and 18-45 years, and sampled a minimum of 11 individuals from each age group (all the 25 randomly selected individuals in each age group were visited in their houses and individuals who consented for the survey were included in the study). Age was the only inclusion criterion; for the purpose of enumeration, individuals residing in the household for more than 6 months were included. Sera were tested centrally by a laboratory team of scientific and technical staff for IgG antibodies against the DENV with the use of indirect ELISA. We calculated age group specific seroprevalence and constructed catalytic models to estimate force of infection. FindingsFrom June 19, 2017, to April 12, 2018, we randomly selected 17 930 individuals from three age groups. Of these, blood samples were collected and tested for 12 300 individuals (5-8 years, n=4059; 9-17 years, n=4265; 18-45 years, n=3976). The overall seroprevalence of DENV infection in India was 48•7% (95% CI 43•5-54•0), increasing from 28•3% (21•5-36•2) among children aged 5-8 years to 41•0% (32•4-50•1) among children aged 9-17 years and 56•2% (49•0-63•1) among individuals aged between 18-45 years. The seroprevalence was high in the southern (76•9% [69•1-83•2]), western (62•3% [55•3-68•8]), and northern (60•3% [49•3-70•5]) regions. The estimated number of primary DENV infections with the constant force of infection model was 12 991 357 (12 825 128-13 130 258) and for the age-dependent force of infection model was 8 655 425 (7 243 630-9 545 052) among individuals aged 5-45 years from 30 Indian states in 2017.Interpretation The burden of dengue infection in India was heterogeneous, with evidence of high transmission in northern, western, and southern regions. The survey findings will be useful in making informed decisions about introduction of upcoming dengue vaccines in India.

We analyzed whether the cyclic AMP induced down-regulation of the nitric oxide (NO) receptor soluble guanylyl cyclase (sGC) is mediated by the mRNA-protecting protein HuR. Exposure (up to 24 h) of isolated rat aortic segments to the activator of adenylyl cyclase, forskolin (10 M), and to both activators of cAMP-stimulated protein kinase (PKA), 5,6-dichloro-1-␤-D-ribofuranosylbenzimidazole-3Ј,5Ј-cyclic monophosphorothioate, Sp-isomer (Sp-5,6-DCl-cBIMPS; 400 nM), and N 6 -phenylcAMP (10 M), strongly reduced sGC␣ 1 ␤ 1 and HuR protein and mRNA expression in a time-dependent and actinomycin D (10 M)-sensitive fashion. In vitro degradation of sGC␣ 1 and ␤ 1 poly(A) ϩ mRNA by native rat aortic protein was markedly increased by pretreatment of intact aortas with forskolin. Native protein extract from rat aorta shifted the electrophoretic mobility of biotin-labeled riboprobes from the 3Ј-untranslated region of sGC␣ 1 and ␤ 1 mRNA, and these bands was supershifted by a monoclonal antibody directed against the mRNA-stabilizing protein HuR. Forskolin decreased the HuR-sGC␣ 1 and ␤ 1 mRNA interaction and HuR protein expression in rat aorta, and this was prevented by the PKA inhibitory cAMP analog 3Ј,5Ј-cyclic monophosphorothioate, Rp-isomer (Rp-cAMPS). In cultured smooth muscle cells from rat aorta, forskolin induced a rapid increase in Fos/p-Fos protein levels and activator protein 1 (AP-1) binding activity. Inhibition of this transcription factor by an AP-1 decoy prevented the forskolin-induced down-regulation of HuR. We conclude that forskolin/cAMP decrease the expression of heterodimeric sGC in rat aortic smooth muscle cells via activation of Fos/AP-1, which decreases the expression of HuR and thus destabilizes the sGC␣ 1 and ␤ 1 mRNA.

Human embryonic stem cell (hESC)-derived oligodendrocyte progenitor cells (OPCs) are being studied for cell replacement therapies, including the treatment of acute spinal cord injury. Current methods of differentiating OPCs from hESCs require complex, animal-derived biological extracellular matrices (ECMs). Defined, low-cost, robust, and scalable culture methods will need to be developed for the widespread deployment and commercialization of hESC-derived cell therapies. Here we describe a defined culture system that uses a vitronectin-derived synthetic peptide acrylate surface (VN-PAS; commercially available as Corning(®) Synthemax(®) surface) in combination with a defined culture medium for hESC growth and differentiation to OPCs. We show that synthetic VN-PAS supports OPC attachment and differentiation, and that hESCs grown on VN-PAS are able to differentiate into OPCs on VN-PAS. Compared to OPCs derived from hESCs grown on ECM of animal origin, higher levels of NG2, a chondroitin sulfate proteoglycan expressed by OPCs, were observed in OPCs differentiated from H1 hESCs grown on VN-PAS, while the expression levels of Nestin and PDGFRα were comparable. In summary, this study demonstrates that synthetic VN-PAS can replace complex, animal-origin ECM to support OPC differentiation from hESCs.

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Over expression of Protein kinase (CK2) suppresses apoptosis induced by a variety of agents, whereas down-regulation of CK2 sensitizes cells to induction of apoptosis. In this study, we have built quantitative structure activity relationship (QSAR) models, which were trained and tested on experimentally verified 38 enzyme׳s inhibitors having inhibitory value IC50 in µM. These inhibitors were docked at the active site of CK2 (PDB id: 2ZJW) using AutoDock software, which resulted in energy-based descriptors such as binding energy, intermol energy, torsional energy, internal energy and docking energy. For QSAR modeling, Multiple Linear Regression (MLR) model was engendered using energy-based descriptors yielding correlation coefficient r2 of 0.4645. To assess the predictive performance of QSAR models, different cross-validation procedures were adopted. Our results suggests that ligand-receptor binding interactions for CK2 employing QSAR modeling seems to be a promising approach for prediction of IC50 value of a new ligand molecule against CK2.Further, twenty analogues of ellagic acid were docked with CK2 structure. After docking, two compounds CID 46229200 and CID 10003463 had lower docking energy even lower than standard control Ellagic acid with CK2 was selected as potent candidate drugs for Oral cancer. The biological activity of two compounds in terms of IC50 was predicted based on QSAR model, which could be used as a guideline for anticancerous activity of compounds before their synthesis.