<?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%">Gokhale, S.</style></author><author><style face="normal" font="default" size="100%">Gadgil, Chetan J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mathematical model identifies conditions for 'unexpected' increase in target protein levels due to miRNA regulation</style></title><secondary-title><style face="normal" font="default" size="100%"> Mol. BioSyst.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">MAR</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">760-765</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">3</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom2><style face="normal" font="default" size="100%">&lt;p&gt;Council of Scientific &amp;amp; Industrial Research (CSIR) - India&lt;/p&gt;</style></custom2><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;3.35&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%">Nyayanit, Dimpal</style></author><author><style face="normal" font="default" size="100%">Gadgil, Chetan J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mathematical modeling of combinatorial regulation suggests that apparent positive regulation of targets by miRNA could be an artifact resulting from competition for mRNA</style></title><secondary-title><style face="normal" font="default" size="100%">RNA-A Publication of the RNA Society</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">combinatorial binding</style></keyword><keyword><style  face="normal" font="default" size="100%">mathematical model</style></keyword><keyword><style  face="normal" font="default" size="100%">miRNA</style></keyword><keyword><style  face="normal" font="default" size="100%">post-transcriptional regulation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">MAR</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">3</style></number><publisher><style face="normal" font="default" size="100%">COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT</style></publisher><pub-location><style face="normal" font="default" size="100%">1 BUNGTOWN RD, COLD SPRING HARBOR, NY 11724 USA</style></pub-location><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">307-319</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;MicroRNAs bind to and regulate the abundance and activity of target messenger RNA through sequestration, enhanced degradation, and suppression of translation. Although miRNA have a predominantly negative effect on the target protein concentration, several reports have demonstrated a positive effect of miRNA, i.e., increase in target protein concentration on miRNA overexpression and decrease in target concentration on miRNA repression. miRNA-target pair-specific effects such as protection of mRNA degradation owing to miRNA binding can explain some of these effects. However, considering such pairs in isolation might be an oversimplification of the RNA biology, as it is known that one miRNA interacts with several targets, and conversely target mRNA are subject to regulation by several miRNAs. We formulate a mathematical model of this combinatorial regulation of targets by multiple miRNA. Through mathematical analysis and numerical simulations of this model, we show that miRNA that individually have a negative effect on their targets may exhibit an apparently positive net effect when the concentration of one miRNA is experimentally perturbed by repression/overexpression in such a multi-miRNA multitarget situation. We show that this apparent unexpected effect is due to competition and will not be observed when miRNA interact noncompetitively with the target mRNA. This result suggests that some of the observed unusual positive effects of miRNA may be due to the combinatorial complexity of the system rather than due to any inherently unusual positive effect of the miRNA on its target.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom2><style face="normal" font="default" size="100%">&lt;p&gt;Council of Scientific &amp;amp; Industrial Research (CSIR) - India&lt;/p&gt;</style></custom2><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%">4.936</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%">Singh, Archana</style></author><author><style face="normal" font="default" size="100%">Gotherwal, Vishvabandhu</style></author><author><style face="normal" font="default" size="100%">Junni, Paivi</style></author><author><style face="normal" font="default" size="100%">Vijayan, Vinaya</style></author><author><style face="normal" font="default" size="100%">Tiwari, Manisha</style></author><author><style face="normal" font="default" size="100%">Ganju, Parul</style></author><author><style face="normal" font="default" size="100%">Kumar, Avinash</style></author><author><style face="normal" font="default" size="100%">Sharma, Pankaj</style></author><author><style face="normal" font="default" size="100%">Fatima, Tanveer</style></author><author><style face="normal" font="default" size="100%">Gupta, Aayush</style></author><author><style face="normal" font="default" size="100%">Holla, Ananthaprasad</style></author><author><style face="normal" font="default" size="100%">Kar, Hemanta K.</style></author><author><style face="normal" font="default" size="100%">Khanna, Sangeeta</style></author><author><style face="normal" font="default" size="100%">Thukral, Lipi</style></author><author><style face="normal" font="default" size="100%">Malik, Garima</style></author><author><style face="normal" font="default" size="100%">Natarajan, Krishnamurthy</style></author><author><style face="normal" font="default" size="100%">Gadgil, Chetan J.</style></author><author><style face="normal" font="default" size="100%">Lahesmaa, Riitta</style></author><author><style face="normal" font="default" size="100%">Natarajan, Vivek T.</style></author><author><style face="normal" font="default" size="100%">Rani, Rajni</style></author><author><style face="normal" font="default" size="100%">Gokhale, Rajesh S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mapping architectural and transcriptional alterations in non-lesional and lesional epidermis in vitiligo</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%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">AUG</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">7</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In vitiligo, chronic loss of melanocytes and consequent absence of melanin from the epidermis presents a challenge for long-term tissue maintenance. The stable vitiligo patches are known to attain an irreversible depigmented state. However, the molecular and cellular processes resulting in this remodeled tissue homeostasis is unclear. To investigate the complex interplay of inductive signals and cell intrinsic factors that support the new acquired state, we compared the matched lesional and non-lesional epidermis obtained from stable non-segmental vitiligo subjects. Hierarchical clustering of genome-wide expression of transcripts surprisingly segregated lesional and non-lesional samples in two distinct clades, despite the apparent heterogeneity in the lesions of different vitiligo subjects. Pathway enrichment showed the expected downregulation of melanogenic pathway and a significant downregulation of cornification and keratinocyte differentiation processes. These perturbations could indeed be recapitulated in the lesional epidermal tissue, including blunting of rete-ridges, thickening of stratum corneum and increase in the size of corneocytes. In addition, we identify marked increase in the putrescine levels due to the elevated expression of spermine/spermidine acetyl transferase. Our study provides insights into the intrinsic self-renewing ability of damaged lesional tissue to restore epidermal functionality in vitiligo.</style></abstract><issue><style face="normal" font="default" size="100%">Article Number: 9860</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%">5.228</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%">Dnyane, Pooja A.</style></author><author><style face="normal" font="default" size="100%">Puntambekar, Shraddha S.</style></author><author><style face="normal" font="default" size="100%">Gadgil, Chetan J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Method for identification of sensitive nodes in boolean models of biological networks</style></title><secondary-title><style face="normal" font="default" size="100%">IET Systems Biology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">biological networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Boolean functions</style></keyword><keyword><style  face="normal" font="default" size="100%">Boolean models</style></keyword><keyword><style  face="normal" font="default" size="100%">fly segment polarity network</style></keyword><keyword><style  face="normal" font="default" size="100%">human melanogenesis signalling network</style></keyword><keyword><style  face="normal" font="default" size="100%">perturbation methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Perturbation theory</style></keyword><keyword><style  face="normal" font="default" size="100%">physiological models</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%">FEB</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">1-6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Biological systems are often represented as Boolean networks and analysed to identify sensitive nodes which on perturbation disproportionately change a predefined output. There exist different kinds of perturbation methods: perturbation of function, perturbation of state and perturbation in update scheme. Nodes may have defects in interpretation of the inputs from other nodes and calculation of the node output. To simulate these defects and systematically assess their effect on the system output, two new function perturbations, referred to as not of function' and function of not', are introduced. In the former, the inputs are assumed to be correctly interpreted but the output of the update rule is perturbed; and in the latter, each input is perturbed but the correct update rule is applied. These and previously used perturbation methods were applied to two existing Boolean models, namely the human melanogenesis signalling network and the fly segment polarity network. Through mathematical simulations, it was found that these methods successfully identified nodes earlier found to be sensitive using other methods, and were also able to identify sensitive nodes which were previously unreported.&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%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">1.048</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%">Sreejan, Ashley</style></author><author><style face="normal" font="default" size="100%">Gadgil, Mugdha</style></author><author><style face="normal" font="default" size="100%">Gadgil, Chetan J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mathematical model of the multi-amino acid multi-transporter system predicts uptake flux in CHO cells</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Biotechnology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino acid transport</style></keyword><keyword><style  face="normal" font="default" size="100%">CHO cell</style></keyword><keyword><style  face="normal" font="default" size="100%">Exchanger</style></keyword><keyword><style  face="normal" font="default" size="100%">mathematical model</style></keyword><keyword><style  face="normal" font="default" size="100%">Multiple transporters</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2022</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%">344</style></volume><pages><style face="normal" font="default" size="100%">40-49</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Supply and uptake of amino acids is of great importance to mammalian cell culture processes. Mammalian cells such as Chinese hamster ovary (CHO) cells express several amino acid (AA) transporters including uniporters and exchangers. Each transporter transports multiple AAs, making prediction of the effect of changed medium composition or transporter levels on individual AA transport rate challenging. A general kinetic model for such combinatorial amino acid transport, and a simplified analytical expression for the uptake rate as a function of amino acid concentrations and transporter levels is presented. From this general model, a CHO cell-specific AA transport model, to our knowledge the first such network model for any cell type, is constructed. The model is validated by its prediction of reported uptake flux and dependencies from experiments that were not used in model construction or parameter estimation. The model defines theoretical conditions for synergistic/repressive effect on the uptake rates of other AAs upon external addition of one AA. The ability of the CHO-specific model to predict amino acid interdependencies experimentally observed in other mammalian cell types suggests its robustness. This model will help formulate testable hypotheses of the effect of process changes on AA initial uptake, and serve as the AA transport component of kinetic models for cellular metabolism.</style></abstract><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%">3.307</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%">Kumar, T. Anand</style></author><author><style face="normal" font="default" size="100%">Birua, Shalini</style></author><author><style face="normal" font="default" size="100%">Mallojjala, Sharath Chandra</style></author><author><style face="normal" font="default" size="100%">Mukherjee, Piyali</style></author><author><style face="normal" font="default" size="100%">Singh, Samsher</style></author><author><style face="normal" font="default" size="100%">Kaul, Grace</style></author><author><style face="normal" font="default" size="100%">Ramachandran, Aparna</style></author><author><style face="normal" font="default" size="100%">Akhir, Abdul</style></author><author><style face="normal" font="default" size="100%">Chopra, Sidharth</style></author><author><style face="normal" font="default" size="100%">Gadgil, Chetan J.</style></author><author><style face="normal" font="default" size="100%">Hirschi, Jennifer S.</style></author><author><style face="normal" font="default" size="100%">Singh, Amit</style></author><author><style face="normal" font="default" size="100%">Chakrapani, Harinath</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mycobacteria-specific prodrug to overcome phenotypic AMR in mycobacterium tuberculosis</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Medicinal Chemistry</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">68</style></volume><pages><style face="normal" font="default" size="100%">24935-24952</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Most front-line tuberculosis (TB) drugs are ineffective against hypoxic nonreplicating Mycobacterium tuberculosis (Mtb), largely due to poor permeability, leading to reduced drug accumulation and target engagement. To overcome this phenotypic antimicrobial resistance (AMR), we developed nitroheteroaryl prodrugs for Moxifloxacin (MXF), a front-line TB drug. These prodrugs are activated by bacterial nitroreductases (NTR), which are overexpressed in hypoxic Mtb. NTR-mediated electron transfer and protonation facilitate rapid cleavage of the protective group, releasing active MXF. The lead prodrug exhibited comparable efficacy to MXF in replicating Mtb and significantly enhanced lethality in nonreplicating Mtb. Drug accumulation studies confirmed a modest but significant increase in MXF levels in nonreplicating Mtb treated with the prodrug, suggesting improved permeability. A mathematical model integrating growth and drug-killing kinetics further elucidated how permeability differences impact lethality. Together, these findings highlight enzyme-activated prodrugs as a promising strategy to address phenotypic AMR in Mtb&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">23</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;
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	7.2&lt;/p&gt;
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