2023/07/06 by Rupchand Sutradhar, Sutradhar, Rupchand, D. C. Dalal +1
Medicine · #Dynamical Systems (math.DS) #FOS: Mathematics #Hepatitis B Virus Studies #Hepatitis C virus research #Liver Disease Diagnosis and Treatment
paper · pdf · doi:10.48550/arxiv.2307.02835
openalex publication_date 2023/07/06 · openalex created_date 2023/07/09 · openalex updated_date 2026/07/28
Analysis of the cell population generally provides average information about viral infection in a host whereas the intracellular model captures the individual cellular responses. The primary goal of this study is to comprehensively analyze the intracellular dynamics of hepatitis B virus (HBV) infection and to identify the most influential factors. In this study, an intracellular HBV infection dynamics model is proposed by considering several intracellular steps that are observed in the virus life cycle. Upon comparison with the experimental data, it is seen that the model solutions exhibit a good agreement. The well-known fourth-order Runge-Kutta method is applied to numerically solve the proposed model. The effects of HBx proteins, dslDNA containing intermediates, intracellular delay and initial concentration of cccDNAs are explicitly studied. In order to identify the most positively and also the most negatively sensitive parameter of the proposed model, the global sensitivity analysis is performed using the widely-used method, Latin hypercube sampling-partial rank correlation coefficients. As a result, it is observed that HBx proteins have notable impacts on the dynamics of the infection, whereas intracellular delay and dslDNA-containing intermediates may not significantly affect the infection. This study also suggests that sub-viral particles could potentially contribute to the progression of the infection. Furthermore, recycling of capsids (an intracellular process perhaps unique to the HBV life cycle, where a portion of the newly produced capsids return to the nucleus and amplify the cccDNAs) is found to play an important role in enhancing the infection.