N
Narendra M. Dixit
Researcher at Indian Institute of Science
Publications - 103
Citations - 2780
Narendra M. Dixit is an academic researcher from Indian Institute of Science. The author has contributed to research in topics: Population & Viral load. The author has an hindex of 27, co-authored 93 publications receiving 2355 citations. Previous affiliations of Narendra M. Dixit include University of Illinois at Urbana–Champaign & Los Alamos National Laboratory.
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Modelling how ribavirin improves interferon response rates in hepatitis C virus infection.
TL;DR: A model of HCV dynamics is presented in which, on the basis of growing evidence, it is assumed that ribavirin decreases HCV infectivity in an infected individual in a dose-dependent manner and quantitatively predicts long-term response rates to interferon monotherapy and combination therapy.
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Complex patterns of viral load decay under antiretroviral therapy: influence of pharmacokinetics and intracellular delay.
TL;DR: A model of HIV dynamics under antiretroviral therapy that combines drug pharmacokinetics and intracellular delay is presented, revealing that viral load decay in HIV infected patients under monotherapy can exhibit remarkably complex patterns depending on the relative magnitudes of the pharmacokinetic, intrACEllular, and intrinsic viral dynamic time-scales.
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Targeting TMPRSS2 and Cathepsin B/L Together May Be Synergistic Against SARS-CoV-2 Infection
TL;DR: It is found that drugs targeting the two pathways, although independent, could display strong synergy in blocking virus entry, and may help improve the deployability of drug combinations targeting host proteases required for the entry.
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The metabolism, pharmacokinetics and mechanisms of antiviral activity of ribavirin against hepatitis C virus
TL;DR: The current status of the understanding of the metabolism, pharmacokinetics and mechanisms of the antiviral activity of ribavirin against HCV are examined, all of which are central to the rational identification of improved treatment protocols.
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HIV dynamics with multiple infections of target cells.
TL;DR: A mathematical model is presented that describes the dynamics of viral, target cell, and multiply infected cell subpopulations during HIV infection and finds that the experimentally observed scaling law, that the number of cells coinfected with two distinctly labeled viruses is proportional to the square of the total number of infected cells, can be generalized.