116 research outputs found

    Residue conservation and dimer-interface analysis of olfactory receptor molecular models

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    Olfactory Receptors (ORs) are members of the Class A rhodopsin like G-protein coupled receptors (GPCRs) which are the initial players in the signal transduction cascade, leading to the generation of nerve impulses transmitted to the brain and resulting in the detection of odorant molecules. Despite the accumulation of thousands of olfactory receptor sequences, no crystal structures of ORs are known tο date. However, the recent availability of crystallographic models of a few GPCRs allows us to generate homology models of ORs and analyze their amino acid patterns, as there is a huge diversity in OR sequences. In this study, we have generated three-dimensional models of 100 representative ORs from Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans and Sacharomyces cerevisiae which were selected on the basis of a composite classification scheme and phylogenetic analysis. The crystal structure of bovine rhodopsin was used as a template and it was found that the full-length models have more than 90% of their residues in allowed regions of the Ramachandran plot. The structures were further used for analysis of conserved residues in the transmembrane and extracellular loop regions in order to identify functionally important residues. Several ORs are known to be functional as dimers and hence dimer interfaces were predicted for OR models to analyse their oligomeric functional state

    Modelling of wetting patterns for surface drip irrigation in dense clay soil

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    The proportion of agricultural water consumption is continuously decreasing due to increased competition for water resources by urban, industrial, and agricultural users. Drip irrigation is more efficient in terms of water and energy utilization. These considerations are critical in view of the ongoing struggle for water resources among various consumers due to water scarcity. Some of the most critical criteria in the effective design and maintenance of drip irrigation systems are the shape and size of the volume of wet soil beneath the emitter. Hence several statistical models were constructed in this research to estimate the dimensions of wetting patterns, which are critical for designing an optimal drip irrigation system. The Nash-Sutcliffe efficiency (NSE), coefficient of correlation (CC), and root mean square error (RMSE) criteria were used to assess the models' performance. The results showed that the Polynomial model was the most accurate for horizontal advance, with 0.94, 0.93, and 1.33 (cm) values for CC, NSE, and RMSE, respectively. For vertical advance, the logarithmic model showed 0.96, 0.96, and 0.72 (cm) values for CC, NSE, and RMSE. Thus, in the absence of a wetting pattern and under identical conditions, these models can be utilized to generate synthetic horizontal and vertical advances data.

    Interfacial Stress Transfer in a Graphene Monolayer Nanocomposite

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    Graphene is one of the stiffest known materials, with a Young's modulus of 1 TPa, making it an ideal candidate for use as a reinforcement in high-performance composites. However, being a one-atom thick crystalline material, graphene poses several fundamental questions: (1) can decades of research on carbon-based composites be applied to such an ultimately-thin crystalline material? (2) is continuum mechanics used traditionally with composites still valid at the atomic level? (3) how does the matrix interact with the graphene crystals and what kind of theoretical description is appropriate? We have demonstrated unambiguously that stress transfer takes place from the polymer matrix to monolayer graphene, showing that the graphene acts as a reinforcing phase. We have also modeled the behavior using shear-lag theory, showing that graphene monolayer nanocomposites can be analyzed using continuum mechanics. Additionally, we have been able to monitor stress transfer efficiency and breakdown of the graphene/polymer interface

    Insights from the analysis of conserved motifs and permitted amino acid exchanges in the human, the fly and the worm GPCR clusters

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    G-protein coupled receptors (GPCRs) belong to biologically important and functionally diverse and largest super family of membrane proteins. GPCRs retain a characteristic membrane topology of seven alpha helices with three intracellular, three extracellular loops and flanking N' and C' terminal residues. Subtle differences do exist in the helix boundaries (TM-domain), loop lengths, sequence features such as conserved motifs, and substituting amino acid patterns and their physiochemical properties amongst these sequences (clusters) at intra-genomic and inter-genomic level (please re-phrase into 2 statements for clarity). In the current study, we employ prediction of helix boundaries and scores derived from amino acid substitution exchange matrices to identify the conserved amino acid residues (motifs) as consensus in aligned set of homologous GPCR sequences. Co-clustered GPCRs from human and other genomes, organized as 32 clusters, were employed to study the amino acid conservation patterns and species-specific or cluster-specific motifs. Critical analysis on sequence composition and properties provide clues to connect functional relevance within and across genome for vast practical applications such as design of mutations and understanding of disease-causing genetic abnormalities

    Energetics Based Spike Generation of a Single Neuron: Simulation Results and Analysis

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    Existing current based models that capture spike activity, though useful in studying information processing capabilities of neurons, fail to throw light on their internal functioning. It is imperative to develop a model that captures the spike train of a neuron as a function of its intracellular parameters for non-invasive diagnosis of diseased neurons. This is the first ever article to present such an integrated model that quantifies the inter-dependency between spike activity and intracellular energetics. The generated spike trains from our integrated model will throw greater light on the intracellular energetics than existing current models. Now, an abnormality in the spike of a diseased neuron can be linked and hence effectively analyzed at the energetics level. The spectral analysis of the generated spike trains in a time–frequency domain will help identify abnormalities in the internals of a neuron. As a case study, the parameters of our model are tuned for Alzheimer’s disease and its resultant spike trains are studied and presented. This massive initiative ultimately aims to encompass the entire molecular signaling pathways of the neuronal bioenergetics linking it to the voltage spike initiation and propagation; due to the lack of experimental data quantifying the inter dependencies among the parameters, the model at this stage adopts a particular level of functionality and is shown as an approach to study and perform disease modeling at the spike train and the mitochondrial bioenergetics level

    3D Printing‐Enabled Design and Manufacturing Strategies for Batteries: A Review

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    Lithium-ion batteries (LIBs) have significantly impacted the daily lives, finding broad applications in various industries such as consumer electronics, electric vehicles, medical devices, aerospace, and power tools. However, they still face issues (i.e., safety due to dendrite propagation, manufacturing cost, random porosities, and basic & planar geometries) that hinder their widespread applications as the demand for LIBs rapidly increases in all sectors due to their high energy and power density values compared to other batteries. Additive manufacturing (AM) is a promising technique for creating precise and programmable structures in energy storage devices. This review first summarizes light, filament, powder, and jetting-based 3D printing methods with the status on current trends and limitations for each AM technology. The paper also delves into 3D printing-enabled electrodes (both anodes and cathodes) and solid-state electrolytes for LIBs, emphasizing the current state-of-the-art materials, manufacturing methods, and properties/performance. Additionally, the current challenges in the AM for electrochemical energy storage (EES) applications, including limited materials, low processing precision, codesign/comanufacturing concepts for complete battery printing, machine learning (ML)/artificial intelligence (AI) for processing optimization and data analysis, environmental risks, and the potential of 4D printing in advanced battery applications, are also presented

    Trauma Hemorrhagic Shock-Induced Lung Injury Involves a Gut-Lymph-Induced TLR4 Pathway in Mice

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    Injurious non-microbial factors released from the stressed gut during shocked states contribute to the development of acute lung injury (ALI) and multiple organ dysfunction syndrome (MODS). Since Toll-like receptors (TLR) act as sensors of tissue injury as well as microbial invasion and TLR4 signaling occurs in both sepsis and noninfectious models of ischemia/reperfusion (I/R) injury, we hypothesized that factors in the intestinal mesenteric lymph after trauma hemorrhagic shock (T/HS) mediate gut-induced lung injury via TLR4 activation.The concept that factors in T/HS lymph exiting the gut recreates ALI is evidenced by our findings that the infusion of porcine lymph, collected from animals subjected to global T/HS injury, into naïve wildtype (WT) mice induced lung injury. Using C3H/HeJ mice that harbor a TLR4 mutation, we found that TLR4 activation was necessary for the development of T/HS porcine lymph-induced lung injury as determined by Evan's blue dye (EBD) lung permeability and myeloperoxidase (MPO) levels as well as the induction of the injurious pulmonary iNOS response. TRIF and Myd88 deficiency fully and partially attenuated T/HS lymph-induced increases in lung permeability respectively. Additional studies in TLR2 deficient mice showed that TLR2 activation was not involved in the pathology of T/HS lymph-induced lung injury. Lastly, the lymph samples were devoid of bacteria, endotoxin and bacterial DNA and passage of lymph through an endotoxin removal column did not abrogate the ability of T/HS lymph to cause lung injury in naïve mice.Our findings suggest that non-microbial factors in the intestinal mesenteric lymph after T/HS are capable of recreating T/HS-induced lung injury via TLR4 activation

    Particles, air quality, policy and health

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    The diversity of ambient particle size and chemical composition considerably complicates pinpointing the specific causal associations between exposure to particles and adverse human health effects, the contribution of different sources to ambient particles at different locations, and the consequent formulation of policy action to most cost-effectively reduce harm caused by airborne particles. Nevertheless, the coupling of increasingly sophisticated measurements and models of particle composition and epidemiology continue to demonstrate associations between particle components and sources (and at lower concentrations) and a wide range of adverse health outcomes. This article reviews the current approaches to source apportionment of ambient particles and the latest evidence for their health effects, and describes the current metrics, policies and legislation for the protection of public health from ambient particles. A particular focus is placed on particles in the ultrafine fraction. The review concludes with an extended evaluation of emerging challenges and future requirements in methods, metrics and policy for understanding and abating adverse health outcomes from ambient particles

    Nanobio Silver: Its Interactions with Peptides and Bacteria, and Its Uses in Medicine

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