Biomedical subjects

Narendra M Dixit

Publications and source records attributed to Narendra M Dixit.

10 recordsLinked to original sources

PubMed2006

Viral decay dynamics in HIV-infected patients receiving ritonavir-boosted saquinavir and efavirenz with or without enfuvirtide: a randomized, controlled trial (HIV-NAT 012).

The availability of enfuvirtide enables assessment of whether human immunodeficiency virus (HIV) decay can be enhanced by targeting reverse transcriptase, protease, and fusion. We performed a 12-week study of 22 patients randomized to receive ritonavir-boosted saquinavir and efavirenz with (the 3-target arm) or without (the 2-target arm) enfuvirtide. We observed no difference in the mean+/-SD elimination-rate constant for overall decay (0.142+/-0.040 per day and 0.128 +/- 0.033 per day in the 2- and 3-target arms, respectively; P>.1) or for modeled first-phase decay rate (-0.62+/-0.34 per day and -0.51+/-0.16 per day; P>.1). Antiretroviral therapy that inhibits HIV reverse transcriptase and protease exerts potent antiviral effects that might not be augmented by the addition of an HIV fusion inhibitor.

Alkynes↗

PubMed2005

HIV dynamics with multiple infections of target cells.

The high incidence of multiple infections of cells by HIV sets the stage for rapid HIV evolution by means of recombination. Yet how HIV dynamics proceeds with multiple infections remains poorly understood. Here, we present a mathematical model that describes the dynamics of viral, target cell, and multiply infected cell subpopulations during HIV infection. Model calculations reproduce several experimental observations and provide key insights into the influence of multiple infections on HIV dynamics. We find 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 so that the number of triply infected cells is proportional to the cube of the number of infected cells, etc. Despite the expectation from Poisson statistics, we find that this scaling relationship only holds under certain conditions, which we predict. We also find that multiple infections do not influence viral dynamics when the rate of viral production from infected cells is independent of the number of times the cells are infected, a regime expected when viral production is limited by cellular rather than viral factors. This result may explain why extant models, which ignore multiple infections, successfully describe viral dynamics in HIV patients. Inhibiting CD4 down-modulation increases the average number of infections per cell. Consequently, altering CD4 down-modulation may allow for an experimental determination of whether viral or cellular factors limit viral production.

CD4 Antigens↗

PubMed2004

Modelling how ribavirin improves interferon response rates in hepatitis C virus infection.

Nearly 200 million individuals worldwide are currently infected with hepatitis C virus (HCV). Combination therapy with pegylated interferon and ribavirin, the latest treatment for HCV infection, elicits long-term responses in only about 50% of patients treated. No effective alternative treatments exist for non-responders. Consequently, significant efforts are continuing to maximize response to combination therapy. However, rational therapy optimization is precluded by the poor understanding of the mechanism(s) of ribavirin action against HCV. Ribavirin alone induces either a transient early decline or no decrease in HCV viral load, but in combination with interferon it significantly improves long-term response rates. Here we present a model of HCV dynamics in which, on the basis of growing evidence, we assume that ribavirin decreases HCV infectivity in an infected individual in a dose-dependent manner. The model quantitatively predicts long-term response rates to interferon monotherapy and combination therapy, fits observed patterns of HCV RNA decline in patients undergoing therapy, reconciles conflicting observations of the influence of ribavirin on HCV RNA decline, provides key insights into the mechanism of ribavirin action against HCV, and establishes a framework for rational therapy optimization.

Dose-Response Relationship, Drug↗

PubMed2004

Complex patterns of viral load decay under antiretroviral therapy: influence of pharmacokinetics and intracellular delay.

We present a model of HIV dynamics under antiretroviral therapy that combines drug pharmacokinetics and intracellular delay. A two compartment pharmacokinetic model is employed to determine the time evolution of the intracellular concentrations of the active forms of drugs, and thereby drug efficacy. The viral replication period is divided into pre- and post-drug action parts, allowing for the introduction of an intracellular delay in drug action. The standard model of viral dynamics is modified to account for the drug dependence of intracellular delay and continuously varying drug efficacy. Model calculations reveal 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. The commonly assumed exponential decay is only a special case. However, uncertainties in measurement and the low sampling frequencies employed in present clinical studies preclude the identification of these patterns from existing clinical viral load data.

Adenine↗

PubMed2004

Multiplicity of human immunodeficiency virus infections in lymphoid tissue.

Human immunodeficiency virus type 1 (HIV-1)-infected splenocytes in humans were recently shown to harbor three to four proviruses per cell on average (A. Jung et al., Nature 418:144, 2002). However, the mechanisms that lead to such extensive multiple infections are not understood. Here, we find by using mathematical analysis that two mechanisms quantitatively capture the distribution of proviral genomes in HIV-1-infected splenocytes, one where multiple genomes are acquired one at a time in a series of sequential infectious contacts of a target cell with free virions and infected cells, and the other where cell-to-cell transmission of multiple virions or genomes results from a single infectious contact of a target cell with an infected cell. The two mechanisms imply different genetic diversities of proviruses within an infected cell and therefore different rates of emergence of drug resistance via recombination.

HIV Infections↗

PubMed2004

Estimates of intracellular delay and average drug efficacy from viral load data of HIV-infected individuals under antiretroviral therapy.

We analyse viral load data of five patients under ritonavir monotherapy using a model of HIV dynamics under antiretroviral therapy that includes both drug pharmacokinetics and the intracellular delay from the time of cell infection to viral production. Using this approach we separate pharamacokinetic from intracellular delays, and obtain new estimates of intracellular delay and the antiviral efficacy of ritonavir. We find the average intracellular delay to be 1 day, in agreement with experiments. The average viral generation time is now estimated at 2 days, resulting in approximately 180 replication cycles per year. The model also reveals that ritonavir monotherapy is approximately 65% as efficacious as a recently used potent four-drug therapy, suggesting that selection for drug resistance may be facilitated by the relatively low efficacy of individual drugs, contributing in part to the inherent limitations of current therapies in combating HIV-1 infection.

HIV Infections↗

PubMed2003

Competition between crystallization and gelation: a local description.

We develop a model to describe the competition between gelation and crystallization in colloidal suspensions where particle interactions are represented by square well attractions. The competition is discussed locally in terms of the tendencies of individual particles to attain amorphous or crystalline configurations on cluster surfaces. These tendencies are dictated by three independent processes, the aggregation of particles onto, the dissociation of particles from, and the rearrangement of particles on the cluster surfaces. Models are developed to determine the rates of each of these processes. The relative magnitudes of these rates determine the probability that a particle arriving onto a cluster surface reaches a crystalline configuration, remains arrested in an amorphous configuration, or dissociates back into the suspension. These probabilities are employed to determine whether stable crystalline or amorphous clusters nucleate, resulting in predictions of the occurrence of crystallization or gelation as a function of solution conditions. Comparisons of model predictions with recent experiments on globular protein suspensions show excellent agreement, suggesting that the model captures much of the underlying physics of the competition between gelation and crystallization in attractive colloidal suspensions.

Journal Article↗

PubMed2003

Ergodic and non-ergodic phase transitions in globular protein suspensions.

The equilibrium and nonequilibrium phase behavior of a protein suspension is investigated as a function of strength of interparticle attraction and protein concentration. The equilibrium phase behavior suggests that the range of the particle attractions is a small fraction of their diameter. At volume fractions and strengths of attractions smaller than those characterizing the spinodal of a metastable fluid-fluid transition, the suspensions gel before they crystallize. At higher volume fractions and lower strengths of attraction, gels are formed first from which crystals nucleate over a period of time. However, at higher strength of attraction, crystals form first at lower volume fractions while gels are observed at higher volume fractions. We hypothesize that this behavior results from the competition between the rates of gelation and crystal nucleation. The location of the gel line is well predicted by mode coupling theories adapted for low volume fractions and square well fluids. At low strength of attraction, the gel line occurs at small supersaturations suggesting gels will be seen before nucleation. However, at higher strengths of attraction the gel line occurs at greatly increased supersaturations such that crystal nucleation can occur before the gel line is crossed. That mode coupling theories should predict gelation when crystallization does not intervene is tested by investigating the gel dynamics.

Algorithms↗

PubMed2003

Modeling viral and drug kinetics: hepatitis C virus treatment with pegylated interferon alfa-2b.

Administration of peginterferon alfa-2b plus ribavirin results in an early hepatitis C virus (HCV) RNA decay followed by an increase as the drug concentration declines between doses. Upon administration of the next dose 1 week later, the same pattern is observed. We have incorporated pharmacokinetic/pharmacodynamic analysis into a model of viral dynamics to describe the effect that changes in drug concentration and effectiveness can have on viral levels. To illustrate the relationship between pharmacokinetics and viral dynamics, we fit the model to data from four HCV/human immunodeficiency virus co-infected patients, and obtained good agreement with the measured serum HCV RNA levels. We were able to account for the observed increases in HCV RNA, and estimate virion and drug half-lives that are in agreement with previous reports. Models incorporating pharmacokinetics are needed to correctly interpret viral load changes and estimate drug effectiveness in treatment protocols using peginterferon alfa-2b.

Antiviral Agents↗

PubMed2002

Nucleation rates and induction times during colloidal crystallization: links between models and experiments.

A kinetic model for the evolution of the cluster size distribution during crystal nucleation and growth is presented. The model allows one to establish precise links between model parameters and experimental measures of nucleation kinetics. This approach demonstrates the significance of several processes not accounted for in classical nucleation theories. Chief among these is that the driving force for crystal nucleation decreases rapidly due to a reduction of the background monomer concentration as crystallization progresses, resulting in a reduction of nucleation rates. This, coupled with the disparities in the definitions of measured and predicted quantities, leads to significant discrepancies between predictions of extant models and experimental estimates of nucleation rates. Accounting for these effects, calculations of the kinetic model are shown to be in good agreement with experimental estimates of nucleation rates, crystal growth velocities, and induction times during the crystallization of hard sphere colloidal suspensions.

Journal Article↗