INTELLIGENT WEB SERVER BASED HEALTH CARE SOLUTION SYSTEM

This paper proposes a method The IOT can bring multiple benefits to healthcare through the use of sensors, intelligent equipments, etc. The Internet of Things (IoT) is a new concept that allows users to connect various sensors and smart devices to collect real-time data from the environment. In this project our contribution is twofold. Firstly, we critically evaluate the existing literature, which discusses the effective ways to deploy IoT in the field of medical and smart health care. Secondly, we propose a new semantic model for patients’ e-Health. The program is written in the python language in the raspberry board. The different data will control the arm rotation

Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors

Olfactory receptors (ORs) constitute the largest superfamily of G protein-coupled receptors (GPCRs). ORs are involved in sensing odorants as well as in other ectopic roles in non-nasal tissues. Matching of an enormous number of the olfactory stimulation repertoire to its counterpart OR through machine learning (ML) will enable understanding of olfactory system, receptor characterization, and exploitation of their therapeutic potential. In the current study, we have selected two broadly tuned ectopic human OR proteins, OR1A1 and OR2W1, for expanding their known chemical space by using molecular descriptors. We present a scheme for selecting the optimal features required to train an ML-based model, based on which we selected the random forest (RF) as the best performer. High activity agonist prediction involved screening five databases comprising ~23 M compounds, using the trained RF classifier. To evaluate the effectiveness of the machine learning based virtual screening and check receptor binding site compatibility, we used docking of the top target ligands to carefully develop receptor model structures. Finally, experimental validation of selected compounds with significant docking scores through in vitro assays revealed two high activity novel agonists for OR1A1 and one for OR2W1

iBio-GATS—A Semi-Automated Workflow for Structural Modelling of Insect Odorant Receptors

Insects utilize seven transmembrane (7TM) odorant receptor (iOR) proteins, with an inverted topology compared to G-protein coupled receptors (GPCRs), to detect chemical cues in the environment. For pest biocontrol, chemical attractants are used to trap insect pests. However, with the influx of invasive insect pests, novel odorants are urgently needed, specifically designed to match 3D iOR structures. Experimental structural determination of these membrane receptors remains challenging and only four experimental iOR structures from two evolutionarily distant organisms have been solved. Template-based modelling (TBM) is a complementary approach, to generate model structures, selecting templates based on sequence identity. As the iOR family is highly divergent, a different template selection approach than sequence identity is needed. Bio-GATS template selection for GPCRs, based on hydrophobicity correspondence, has been morphed into iBio-GATS, for template selection from available experimental iOR structures. This easy-to-use semi-automated workflow has been extended to generate high-quality models from any iOR sequence from the selected template, using Python and shell scripting. This workflow was successfully validated on Apocrypta bakeri Orco and Machilis hrabei OR5 structures. iBio-GATS models generated for the fruit fly iOR, OR59b and Orco, yielded functional ligand binding results concordant with experimental mutagenesis findings, compared to AlphaFold2 models

Differential Expression of <em>In Vivo</em> and <em>In Vitro</em> Protein Profile of Outer Membrane of <em>Acidovorax avenae</em> Subsp. <em>avenae</em>

<div><p>Outer membrane (OM) proteins play a significant role in bacterial pathogenesis. In this work, we examined and compared the expression of the OM proteins of the rice pathogen <em>Acidovorax avenae</em> subsp. <em>avenae</em> strain RS-1, a Gram-negative bacterium, both in an <em>in vitro</em> culture medium and <em>in vivo</em> rice plants. Global proteomic profiling of <em>A. avenae</em> subsp. <em>avenae</em> strain RS-1 comparing <em>in vivo</em> and <em>in vitro</em> conditions revealed the differential expression of proteins affecting the survival and pathogenicity of the rice pathogen in host plants. The shotgun proteomics analysis of OM proteins resulted in the identification of 97 proteins <em>in vitro</em> and 62 proteins <em>in vivo</em> by mass spectrometry. Among these OM proteins, there is a high number of porins, TonB-dependent receptors, lipoproteins of the NodT family, ABC transporters, flagellins, and proteins of unknown function expressed under both conditions. However, the major proteins such as phospholipase and OmpA domain containing proteins were expressed <em>in vitro,</em> while the proteins such as the surface anchored protein F, ATP-dependent Clp protease, OmpA and MotB domain containing proteins were expressed <em>in vivo</em>. This may indicate that these <em>in vivo</em> OM proteins have roles in the pathogenicity of <em>A. avenae</em> subsp. <em>avenae</em> strain RS-1. In addition, the LC-MS/MS identification of OmpA and MotB validated the <em>in silico</em> prediction of the existance of Type VI secretion system core components. To the best of our knowledge, this is the first study to reveal the <em>in vitro</em> and <em>in vivo</em> protein profiles, in combination with LC-MS/MS mass spectra, <em>in silico</em> OM proteome and <em>in silico</em> genome wide analysis, of pathogenicity or plant host required proteins of a plant pathogenic bacterium.</p> </div

List of LC-MS/MS identified unique outer membrane protiens under <i>in vivo</i> condition of <i>Acidovorax avenae</i> subsp. <i>avenae</i> strain RS-1 proteome.

<p>List of LC-MS/MS identified unique outer membrane protiens under <i>in vivo</i> condition of <i>Acidovorax avenae</i> subsp. <i>avenae</i> strain RS-1 proteome.</p

Locus of T6SS core and conserved accessory components in <i>Acidovorax avenae</i> subsp. <i>avenae</i> strain RS-1 which also exist in <i>Acidovorax avenae</i> subsp. <i>citrulli</i> strain AAC00-1 or <i>Burkholderia thailandensis</i> strain E264 are represented with a different color.

<p>Locus of T6SS core and conserved accessory components in <i>Acidovorax avenae</i> subsp. <i>avenae</i> strain RS-1 which also exist in <i>Acidovorax avenae</i> subsp. <i>citrulli</i> strain AAC00-1 or <i>Burkholderia thailandensis</i> strain E264 are represented with a different color.</p