<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mahale, Vishal</style></author><author><style face="normal" font="default" size="100%">Singh, Ajeet</style></author><author><style face="normal" font="default" size="100%">Phadke, Gayatri S.</style></author><author><style face="normal" font="default" size="100%">Ghanate, Avinash D.</style></author><author><style face="normal" font="default" size="100%">Oulkar, Dasharath P.</style></author><author><style face="normal" font="default" size="100%">Banerjee, Kaushik</style></author><author><style face="normal" font="default" size="100%">Panchagnula, Venkateswarlu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Determination of triazines and triazoles in grapes using atmospheric pressure matrix-assisted laser desorption/ionization high-resolution mass spectrometry</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Aoac International</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">MAY</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">100</style></volume><pages><style face="normal" font="default" size="100%">640-646</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A chromatography-free atmospheric pressure matrix-assisted laser desorption/ionization high-resolution mass spectrometry (AP-MALDI HRMS) method is described for the simultaneous and quantitative detection of triazines and triazoles in grapes. The analytes were detected reproducibly with high mass accuracy (mass error within 5 ppm) and further confirmed by collision-induced dissociation fragmentation in tandem MS. The LODs and LOQs for all the analytes were found to be in the nanogram per gram level (15-20 ng/g LOQ). Internal standard normalized high-resolution accurate mass extracted (HR-AM) peak intensities of the detected ions were used to generate the concentration response curves. Linearity (with R-2 values around 0.99) was obtained for these curves within a concentration range of 20-200 ng/g of the individual analytes. The accuracy and precision of the method were further established using QC samples. Validation and performance comparison of the AP-MALDI HRMS method with an existing standard method using LC with :triple quadrupole MS was carried out (evaluating sensitivity, accuracy, precision, and analysis time) using 20 table-grape field samples after QuEChERS extraction.</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">0.918</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Banerjee, Deepanwita</style></author><author><style face="normal" font="default" size="100%">Parmar, Dharmeshkumar</style></author><author><style face="normal" font="default" size="100%">Bhattacharya, Nivedita</style></author><author><style face="normal" font="default" size="100%">Ghanate, Avinash D.</style></author><author><style face="normal" font="default" size="100%">Panchagnula, Venkateswarlu</style></author><author><style face="normal" font="default" size="100%">Raghunathan, Anu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Scalable metabolite supplementation strategy against antibiotic resistant pathogen Chromobacterium violaceum induced by NAD(+)/NADH(+) imbalanceA scalable metabolite supplementation strategy against antibiotic resistant pathogen Chromobacterium violaceu</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Syst Biol. </style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Antibiotic resistance; Flux balance analysis; Flux variability analysis; Metabolism; Metabolomic; NAD; NADH; Redox homeostasis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">APR</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;BACKGROUND: The leading edge of the global problem of antibiotic resistance necessitates novel therapeutic strategies. This study develops a novel systems biology driven approach for killing antibiotic resistant pathogens using benign metabolites. RESULTS: Controlled laboratory evolutions established chloramphenicol and streptomycin resistant pathogens of Chromobacterium. These resistant pathogens showed higher growth rates and required higher lethal doses of antibiotic. Growth and viability testing identified malate, maleate, succinate, pyruvate and oxoadipate as resensitising agents for antibiotic therapy. Resistant genes were catalogued through whole genome sequencing. Intracellular metabolomic profiling identified violacein as a potential biomarker for resistance. The temporal variance of metabolites captured the linearized dynamics around the steady state and correlated to growth rate. A constraints-based flux balance model of the core metabolism was used to predict the metabolic basis of antibiotic susceptibility and resistance. CONCLUSIONS: The model predicts electron imbalance and skewed NAD/NADH ratios as a result of antibiotics - chloramphenicol and streptomycin. The resistant pathogen rewired its metabolic networks to compensate for disruption of redox homeostasis. We foresee the utility of such scalable workflows in identifying metabolites for clinical isolates as inevitable solutions to mitigate antibiotic resistance.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%"> 2.05</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Immanuel, Selva Rupa C.</style></author><author><style face="normal" font="default" size="100%">Ghanate, Avinash D.</style></author><author><style face="normal" font="default" size="100%">Parmar, Dharmeshkumar S.</style></author><author><style face="normal" font="default" size="100%">Marriage, Fiona</style></author><author><style face="normal" font="default" size="100%">Panchagnula, Venkateswarlu</style></author><author><style face="normal" font="default" size="100%">Day, Nap J.</style></author><author><style face="normal" font="default" size="100%">Raghunathan, Anu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Integrative analysis of rewired central metabolism in temozolomide resistant cells</style></title><secondary-title><style face="normal" font="default" size="100%">Biochemical and Biophysical Research Communications</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Glutamine</style></keyword><keyword><style  face="normal" font="default" size="100%">Metabolic rewiring</style></keyword><keyword><style  face="normal" font="default" size="100%">Metabolite profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">mRNA abundances</style></keyword><keyword><style  face="normal" font="default" size="100%">Temozolomide resistance</style></keyword><keyword><style  face="normal" font="default" size="100%">U87MG</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JAN</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">495</style></volume><pages><style face="normal" font="default" size="100%">2010-2016</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;An authenticated U87MG clonal glioblastoma cell line was investigated to identify a sub-population of neurospheroidal (NSP) cells within the main epithelial population (U87MG). The NSP cells sorted using Fluorescence Assisted Cell Sorting (FACS) showed varied morphology, 30% lower growth rates, 40% higher IC50 values for temozolomide drug and could differentiate into the glial cell type (NDx). Metabolite profiling using HR-LCMS identified glucose, glutamine and serine in both populations and tryptophan only in U87MG as growth limiting substrates. Glycine, alanine, glutamate and proline were secreted by U87MG, however proline and glycine were re-utilized in NSP. Exo-metabolite profiling and phenotypic microarrays identified differential metabolism of primary carbon sources glucose and derived pyruvate for U87MG; glutamine and derived glutamate metabolism in NSP. Differential mRNA abundance of AKT1, PTEN, PIK3CA controlling metabolism, drug efflux, nutrient transport and epigenetic control MDM2 are potentially critical in shaping DNA methylation effects of temozolomide. Our study provides a new insight into the combined effect of these factors leading to temozolomide resistance in NSP. (C) 2017 Elsevier Inc. All rights reserved.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">2.466</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Immanuel, Selva Rupa Christinal</style></author><author><style face="normal" font="default" size="100%">Ghanate, Avinash D.</style></author><author><style face="normal" font="default" size="100%">Parmar, Dharmeshkumar S.</style></author><author><style face="normal" font="default" size="100%">Yadav, Ritu</style></author><author><style face="normal" font="default" size="100%">Uthup, Riya</style></author><author><style face="normal" font="default" size="100%">Panchagnula, Venkateswarlu</style></author><author><style face="normal" font="default" size="100%">Raghunathan, Anu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Integrated genetic and metabolic landscapes predict vulnerabilities of temozolomide resistant glioblastoma cells</style></title><secondary-title><style face="normal" font="default" size="100%">npj Systems Biology and Applications</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JAN </style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">2</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Metabolic reprogramming and its molecular underpinnings are critical to unravel the duality of cancer cell function and chemo-resistance. Here, we use a constraints-based integrated approach to delineate the interplay between metabolism and epigenetics, hardwired in the genome, to shape temozolomide (TMZ) resistance. Differential metabolism was identified in response to TMZ at varying concentrations in both the resistant neurospheroidal (NSP) and the susceptible (U87MG) glioblastoma cell-lines. The genetic basis of this metabolic adaptation was characterized by whole exome sequencing that identified mutations in signaling pathway regulators of growth and energy metabolism. Remarkably, our integrated approach identified rewiring in glycolysis, TCA cycle, malate aspartate shunt, and oxidative phosphorylation pathways. The differential killing of TMZ resistant NSP by Rotenone at low concentrations with an IC50 value of 5 nM, three orders of magnitude lower than for U87MG that exhibited an IC50 value of 1.8 mM was thus identified using our integrated systems-based approach.&lt;/p&gt;
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