Electrochemical Exfoliation of Graphene and its Characterisation

A green approach is reported for the production of few layered graphenes (FLGs) via electrochemical route utilising the benefits of anodic exfoliation process, wherein electrochemical intercalation of nitrate ions into pyrolytic graphite resulted in electrochemical exfoliation of nitrate ions-intercalated graphite electrode. The role of applied potential in intercalation and concentrations of nitric acid are well defining factors in controlling the number of layers in FLGs. The success of this approach was confirmed by FTIR, wherein smaller particles of intercalated graphite led to broader peaks due to increased interaction with light wave. The SEM images showed several layers of graphene stacked together and slightly twisted at edges. An increased exfoliation in intercalated graphite was revealed by XRD patterns. Desirable conductive properties of the FLGs synthesised makes it a viable option for utility as conductive ink

Identification of Mannose Interacting Residues Using Local Composition

BACKGROUND: Mannose binding proteins (MBPs) play a vital role in several biological functions such as defense mechanisms. These proteins bind to mannose on the surface of a wide range of pathogens and help in eliminating these pathogens from our body. Thus, it is important to identify mannose interacting residues (MIRs) in order to understand mechanism of recognition of pathogens by MBPs. RESULTS: This paper describes modules developed for predicting MIRs in a protein. Support vector machine (SVM) based models have been developed on 120 mannose binding protein chains, where no two chains have more than 25% sequence similarity. SVM models were developed on two types of datasets: 1) main dataset consists of 1029 mannose interacting and 1029 non-interacting residues, 2) realistic dataset consists of 1029 mannose interacting and 10320 non-interacting residues. In this study, firstly, we developed standard modules using binary and PSSM profile of patterns and got maximum MCC around 0.32. Secondly, we developed SVM modules using composition profile of patterns and achieved maximum MCC around 0.74 with accuracy 86.64% on main dataset. Thirdly, we developed a model on a realistic dataset and achieved maximum MCC of 0.62 with accuracy 93.08%. Based on this study, a standalone program and web server have been developed for predicting mannose interacting residues in proteins (http://www.imtech.res.in/raghava/premier/). CONCLUSIONS: Compositional analysis of mannose interacting and non-interacting residues shows that certain types of residues are preferred in mannose interaction. It was also observed that residues around mannose interacting residues have a preference for certain types of residues. Composition of patterns/peptide/segment has been used for predicting MIRs and achieved reasonable high accuracy. It is possible that this novel strategy may be effective to predict other types of interacting residues. This study will be useful in annotating the function of protein as well as in understanding the role of mannose in the immune system

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Not AvailableToll-like receptors (TLRs), which come under the class of pattern recognition receptors, mediate innate immune responses upon binding to the pathogen-associated molecular patterns (PAMPs). TLRs are present in a wide variety of tissues including the endometrium. Expression and regulation of endometrial TLR during the early postpartum period is important in the clearance of uterine infections in the bovine. This chapter updates the available evidence on the expression pattern of TLR in the endometrium, regulation by phases of the estrous cycle, and their significance in the postpartum clinical endometritis and subclinical endometritis.Not Availabl

Deciphering the Association of Epstein–Barr Virus and Its Glycoprotein M Peptide with Neuropathologies in Mice

The reactivation of ubiquitously present Epstein–Barr virus (EBV) is known to be involved with numerous diseases, including neurological ailments. A recent in vitro study from our group unveiled the association of EBV and its 12-amino acid peptide glycoprotein M146–157 (gM146–157) with neurodegenerative diseases, viz., Alzheimer’s disease (AD) and multiple sclerosis. In this study, we have further validated this association at the in vivo level. The exposure of EBV/gM146–157 to mice causes a decline in the cognitive ability with a concomitant increase in anxiety-like symptoms through behavioral assays. Disorganization of hippocampal neurons, cell shrinkage, pyknosis, and apoptotic appendages were observed in the brains of infected mice. Inflammatory cytokines such as tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) were found to be elevated in infected mouse brain tissue samples, whereas TNF-α exhibited a decline in the serum of these mice. Further, the altered levels of nuclear factor-kappa B (NF-kB) and neurotensin receptor 2 affirmed neuroinflammation in infected mouse brain samples. Similarly, the risk factor of AD, apolipoprotein E4 (ApoE4), was also found to be elevated at the protein level in EBV/gM146–157 challenged mice. Furthermore, we also observed an increased level of myelin basic protein in the brain cortex. Altogether, our results suggested an integral connection of EBV and its gM146–157 peptide to the neuropathologies