<?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%">Maralingannavar, Vishwanathgouda;</style></author><author><style face="normal" font="default" size="100%">Parmar, Dharmeshkumar</style></author><author><style face="normal" font="default" size="100%">Pant, Tejal</style></author><author><style face="normal" font="default" size="100%">Gadgil, Chetan</style></author><author><style face="normal" font="default" size="100%">Panchagnula, Venkateswarlu</style></author><author><style face="normal" font="default" size="100%">Gadgil, Mugdha</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CHO Cells Adapted to Inorganic Phosphate Limitation Show Higher Growth and Higher Pyruvate Carboxylase Flux in Phosphate Replete Conditions</style></title><secondary-title><style face="normal" font="default" size="100%">Biotechnology progress</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%">33</style></volume><pages><style face="normal" font="default" size="100%">749-758</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Inorganic phosphate (P-i) is an essential ion involved in diverse cellular processes including metabolism. Changes in cellular metabolism upon long term adaptation to P-i limitation have been reported in E. coli. Given the essential role of P-i, adaptation to P-i limitation may also result in metabolic changes in animal cells. In this study, we have adapted CHO cells producing recombinant IgG to limiting P-i conditions for 75 days. Not surprisingly, adapted cells showed better survival under P-i limitation. Here, we report the finding that such cells also showed better growth characteristics compared to control in batch culture replete with P-i ( higher peak density and integral viable cell density), accompanied by a lower specific oxygen uptake rate and cytochrome oxidase activity towards the end of exponential phase. Surprisingly, the adapted cells grew to a lower peak density under glucose limitation. This suggests long term P-i limitation may lead to selection for an altered metabolism with higher dependence on glucose availability for biomass assimilation compared to control. Steady state U-C-13 glucose labeling experiments suggest that adapted cells have a higher pyruvate carboxylase flux. Consistent with this observation, supplementation with aspartate abolished the peak density difference whereas supplementation with serine did not abolish the difference. This supports the hypothesis that cell growth in the adapted culture might be higher due to a higher pyruvate carboxylase flux. Decreased fitness under carbon limitation and mutations in the sucABCD operon has been previously reported in E. coli upon long term adaptation to P-i limitation, suggestive of a similarity in cellular response among such diverse species. (C) 2017 American Institute of Chemical Engineers</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%">1.947</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>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maralingannavar, Vishwanathgouda</style></author><author><style face="normal" font="default" size="100%">Parmar, Dharmeshkumar</style></author><author><style face="normal" font="default" size="100%">Pant, Tejal</style></author><author><style face="normal" font="default" size="100%">Gadgil, Chetan</style></author><author><style face="normal" font="default" size="100%">Panchagnula, Venkateswarlu</style></author><author><style face="normal" font="default" size="100%">Gadgil, Mugdha</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Differential responses of CHO cells adapted to limitation of inorganic phosphate, glucose or glutamine</style></title><secondary-title><style face="normal" font="default" size="100%">255th National Meeting and Exposition of the American-Chemical-Society (ACS) - Nexus of Food, Energy, and Water</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">MAR </style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">American-Chemical-Society, 1155 16TH ST, NW, Washington, DC 20036 USA</style></publisher><pub-location><style face="normal" font="default" size="100%">New Orleans, LA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3></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%">Maralingannavar, Vishwanathgouda</style></author><author><style face="normal" font="default" size="100%">Parmar, Dharmeshkumar</style></author><author><style face="normal" font="default" size="100%">Panchagnula, Venkateswarlu</style></author><author><style face="normal" font="default" size="100%">Gadgil, Mugdha</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Superfluous glutamine synthetase activity in Chinese Hamster Ovary cells selected under glutamine limitation is growth limiting in glutamine-replete conditions and can be inhibited by serine</style></title><secondary-title><style face="normal" font="default" size="100%">Biotechnology Progress</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">C-13 tracer analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">CHO cells</style></keyword><keyword><style  face="normal" font="default" size="100%">glutamine limitation</style></keyword><keyword><style  face="normal" font="default" size="100%">Glutamine synthetase</style></keyword><keyword><style  face="normal" font="default" size="100%">GS-CHO</style></keyword><keyword><style  face="normal" font="default" size="100%">GS-NS0</style></keyword><keyword><style  face="normal" font="default" size="100%">selection under nutrient limitation</style></keyword><keyword><style  face="normal" font="default" size="100%">serine</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">SEP-OCT</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">UNSP e2856</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Passaging and expansion of animal cells in lean maintenance medium could result in periods of limitation of some nutrients. Over time, such stresses could possibly result in selection of cells with metabolic changes and contribute to heterogeneity. Here, we investigate whether selection of Chinese Hamster Ovary (CHO) cells under glutamine limitation results in changes in growth under glutamine-replete conditions. In glutamine-limiting medium, compared to control cells passaged in glutamine-rich medium, the selected cells showed higher glutamine synthetase (GS) activity and attained a higher peak viable cell density (PVCD). Surprisingly, in glutamine-replete conditions, selected cells still showed a higher GS activity but a lower PVCD. We show that in glutamine-replete medium, PVCD of selected cells was restored on (a) inhibition of GS activity with methionine sulfoximine, (b) supplementation of aspartate-without affecting GS activity, and (c) supplementation of serine, which is reported to inhibit GS in vitro. Consistent with the reported effect of serine, inhibition of GS activity was observed upon serine supplementation along with reduced growth of cells under glutamine-limiting conditions. The latter observation is important for the design of glutamine-free culture medium and feed used for GS-CHO and GS-NS0. In summary, we show that CHO cells selected under glutamine limitation have superfluous GS activity in glutamine-replete medium, which negatively affects their PVCD. This may be due to its effect on availability of aspartate which was the limiting nutrient for the growth of selected cells in glutamine-replete conditions.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;2.406&lt;/p&gt;
</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%">Parmar, Dharmeshkumar</style></author><author><style face="normal" font="default" size="100%">Bhattacharya, Nivedita</style></author><author><style face="normal" font="default" size="100%">Kannan, Shanthini</style></author><author><style face="normal" font="default" size="100%">Vadivel, Sangeetha</style></author><author><style face="normal" font="default" size="100%">Pandey, Gautam Kumar</style></author><author><style face="normal" font="default" size="100%">Ghanate, Avinash</style></author><author><style face="normal" font="default" size="100%">Ragi, Nagarjuna Chary</style></author><author><style face="normal" font="default" size="100%">Prabu, Paramasivam</style></author><author><style face="normal" font="default" size="100%">Pramodkumar, Thyparambil Aravindakshan</style></author><author><style face="normal" font="default" size="100%">Manickam, Nagaraj</style></author><author><style face="normal" font="default" size="100%">Mohan, Viswanathan</style></author><author><style face="normal" font="default" size="100%">Sripadi, Prabhakar</style></author><author><style face="normal" font="default" size="100%">Kuppan, Gokulakrishnan</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%">Plausible diagnostic value of urinary isomeric dimethylarginine ratio for diabetic nephropathy</style></title><secondary-title><style face="normal" font="default" size="100%">Scientific Reports</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">FEB</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">2970</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Altered circulatory asymmetric and symmetric dimethylarginines have been independently reported in patients with end-stage renal failure suggesting their potential role as mediators and early biomarkers of nephropathy. These alterations can also be reflected in urine. Herein, we aimed to evaluate urinary asymmetric to symmetric dimethylarginine ratio (ASR) for early prediction of diabetic nephropathy (DN). In this cross-sectional study, individuals with impaired glucose tolerance (IGT), newly diagnosed diabetes (NDD), diabetic microalbuminuria (MIC), macroalbuminuria (MAC), and normal glucose tolerance (NGT) were recruited from Dr. Mohans' Diabetes Specialties centre, India. Urinary ASR was measured using a validated high-throughput MALDI-MS/MS method. Significantly lower ASR was observed in MIC (0.909) and MAC (0.741) in comparison to the NGT and NDD groups. On regression models, ASR was associated with MIC [OR: 0.256; 95% CI: 0.158-0.491] and MAC [OR 0.146; 95% CI: 0.071-0.292] controlled for all the available confounding factors. ROC analysis revealed ASR cut-point of 0.95 had C-statistic of 0.691 (95% CI: 0.627-0.755) to discriminate MIC from NDD with 72% sensitivity. Whereas, an ASR cut-point of 0.82 had C-statistic of 0.846 (95% CI: 0.800 - 0.893) had 91% sensitivity for identifying MAC. Our results suggest ASR as a potential early diagnostic biomarker for DN among the Asian Indians.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;3.998&lt;/p&gt;
</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%">Sharma, Sapna</style></author><author><style face="normal" font="default" size="100%">Subrahmanyam, Yalamanchili Venkata</style></author><author><style face="normal" font="default" size="100%">Ranjani, Harish</style></author><author><style face="normal" font="default" size="100%">Sidra, Sidra</style></author><author><style face="normal" font="default" size="100%">Parmar, Dharmeshkumar</style></author><author><style face="normal" font="default" size="100%">Vadivel, Sangeetha</style></author><author><style face="normal" font="default" size="100%">Kannan, Shanthini</style></author><author><style face="normal" font="default" size="100%">Grallert, Harald</style></author><author><style face="normal" font="default" size="100%">Usharani, Dandamudi</style></author><author><style face="normal" font="default" size="100%">Anjana, Ranjit Mohan</style></author><author><style face="normal" font="default" size="100%">Balasubramanyam, Muthuswamy</style></author><author><style face="normal" font="default" size="100%">Mohan, Viswanathan</style></author><author><style face="normal" font="default" size="100%">Jerzy, Adamski</style></author><author><style face="normal" font="default" size="100%">Panchagnula, Venkateswarlu</style></author><author><style face="normal" font="default" size="100%">Gokulakrishnan, Kuppan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Circulatory levels of lysophosphatidylcholine species in obese adolescents: Findings from cross-sectional and prospective lipidomics analyses</style></title><secondary-title><style face="normal" font="default" size="100%">NUTRITION METABOLISM AND CARDIOVASCULAR DISEASES</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adolescent obesity</style></keyword><keyword><style  face="normal" font="default" size="100%">Asian Indians</style></keyword><keyword><style  face="normal" font="default" size="100%">biomarker</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipidomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Lysophosphatidyl- choline</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUL</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">1807-1816</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">7</style></issue><work-type><style face="normal" font="default" size="100%">Journal Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;3.9&lt;/p&gt;
</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%">Sharma, Sapna</style></author><author><style face="normal" font="default" size="100%">Subrahmanyam, Yalamanchili Venkata</style></author><author><style face="normal" font="default" size="100%">Gupta, Payal</style></author><author><style face="normal" font="default" size="100%">Vadivel, Sangeetha</style></author><author><style face="normal" font="default" size="100%">Deepa, Mohan</style></author><author><style face="normal" font="default" size="100%">Tandon, Ansh</style></author><author><style face="normal" font="default" size="100%">Sreedevi, Sreekumar</style></author><author><style face="normal" font="default" size="100%">Ram, Uma</style></author><author><style face="normal" font="default" size="100%">Narad, Priyanka</style></author><author><style face="normal" font="default" size="100%">Parmar, Dharmeshkumar</style></author><author><style face="normal" font="default" size="100%">Anjana, Ranjit Mohan</style></author><author><style face="normal" font="default" size="100%">Raghunathan, Anu</style></author><author><style face="normal" font="default" size="100%">Balasubramanyam, Muthuswamy</style></author><author><style face="normal" font="default" size="100%">Mohan, Viswanathan</style></author><author><style face="normal" font="default" size="100%">Sengupta, Abhishek</style></author><author><style face="normal" font="default" size="100%">Adamski, Jerzy</style></author><author><style face="normal" font="default" size="100%">Saravanan, Ponnusamy</style></author><author><style face="normal" font="default" size="100%">Panchagnula, Venkateswarlu</style></author><author><style face="normal" font="default" size="100%">Usharani, Dandamudi</style></author><author><style face="normal" font="default" size="100%">Gokulakrishnan, Kuppan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Precision integrated identification of predictive first-trimester metabolomics signatures for early detection of gestational diabetes mellitus</style></title><secondary-title><style face="normal" font="default" size="100%">Cardiovascular Diabetology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">First trimester</style></keyword><keyword><style  face="normal" font="default" size="100%">Gestational diabetes mellitus</style></keyword><keyword><style  face="normal" font="default" size="100%">Indian women</style></keyword><keyword><style  face="normal" font="default" size="100%">Mass spectrometry</style></keyword><keyword><style  face="normal" font="default" size="100%">Metabolomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Prediction</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">NOV </style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">434</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Background and aimGestational diabetes mellitus (GDM), a common pregnancy-related metabolic disorder, often goes undiagnosed until the second trimester, limiting early intervention opportunities. Given the higher prevalence of GDM in India, there is a critical need to investigate metabolomic biomarkers among Asian Indians, who exhibit greater insulin resistance and are predisposed to developing type 2 diabetes at an earlier age. This study aimed to identify early pregnancy metabolomic signatures predictive of GDM. MethodsAmong 2115 pregnant women from the STratification of Risk of Diabetes in Early pregnancy (STRiDE) study, we performed untargeted metabolomic profiling using UPLC-MS/MS at early pregnancy (&amp;lt; 16 weeks) plasma samples from 100 women-comprising 50 with GDM and 50 normal (without GDM) based on oral glucose tolerance test (OGTT) at 24-28 weeks. Statistical and machine learning approaches, including logistic regression and random forest (RF), were applied to identify GDM-associated metabolites and construct predictive models. Pathway enrichment analysis was conducted using KEGG database annotations. ResultsA total of 49 metabolites were significantly associated with GDM, primarily involving lipid classes such as phosphatidylcholines, sphingomyelins, and triacylglycerols. RF analysis identified a panel of eight metabolites that achieved best predictive performance (AUC 0.880; 95% CI: 0.809-0.951) for GDM. When combined with conventional clinical risk factors, the integrated model showed comparable prediction of GDM with AUC 0.88;: 95% CI: 0.810-0.952). Enrichment analysis highlighted dysregulated pathways including glycerophospholipid and sphingolipid metabolism, autophagy, and insulin resistance. ConclusionThis study demonstrates the utility of early-pregnancy metabolomic profiling for predicting GDM in Indian women. The eight-metabolite panel offers a promising tool for early risk stratification of GDM, warranting validation in diverse populations.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	10&lt;/p&gt;
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