Academic literature on the topic 'Cell transmission models'

This research calibrates Cell Transmission Model (CTM) for heterogeneous and non-lane disciplined traffic, as observed in Pakistan and some other developing countries by constructing a flow-density fundamental traffic flow diagram. Currently, most of the traffic simulation packages used for such heterogonous and non-lane-disciplined traffic are not calibrated for local traffic conditions and most of the traffic flow models are developed for comparatively less heterogeneous and lane-disciplined traffic. The flow-density fundamental traffic flow diagram is developed based on extensive field data collected from Karachi, Pakistan. The calibrated CTM model is validated by using actual data from another road and it was concluded that CTM is capable of modelling heterogeneous and non-lane disciplined traffic and performed very reasonably. The calibrated CTM will be a useful input for the application of traffic simulation and optimization packages such as TRANSYT, SIGMIX, DISCO, and CTMSIM.

Despite a growing awareness, hepatitis E virus (HEV) remains understudied and investigations have been historically hampered by the absence of efficient cell culture systems. As a result, the pathogenesis of HEV infection and basic steps of the HEV life cycle are poorly understood. Major efforts have recently been made through the development of HEV infectious clones and cellular systems that significantly advanced HEV research. Here, we summarize these systems, discussing their advantages and disadvantages for HEV studies. We further capitalize on the need for HEV-permissive polarized cell models to better recapitulate the entire HEV life cycle and transmission.

ABSTRACTIt has been proposed that viral cell-to-cell transmission plays a role in establishing and maintaining chronic infections. Thus, understanding the mechanisms and kinetics of cell-to-cell spread is fundamental to elucidating the dynamics of infection and may provide insight into factors that determine chronicity. Because hepatitis C virus (HCV) spreads from cell to cell and has a chronicity rate of up to 80% in exposed individuals, we examined the dynamics of HCV cell-to-cell spreadin vitroand quantified the effect of inhibiting individual host factors. Using a multidisciplinary approach, we performed HCV spread assays and assessed the appropriateness of different stochastic models for describing HCV focus expansion. To evaluate the effect of blocking specific host cell factors on HCV cell-to-cell transmission, assays were performed in the presence of blocking antibodies and/or small-molecule inhibitors targeting different cellular HCV entry factors. In all experiments, HCV-positive cells were identified by immunohistochemical staining and the number of HCV-positive cells per focus was assessed to determine focus size. We found that HCV focus expansion can best be explained by mathematical models assuming focus size-dependent growth. Consistent with previous reports suggesting that some factors impact HCV cell-to-cell spread to different extents, modeling results estimate a hierarchy of efficacies for blocking HCV cell-to-cell spread when targeting different host factors (e.g., CLDN1 > NPC1L1 > TfR1). This approach can be adapted to describe focus expansion dynamics under a variety of experimental conditions as a means to quantify cell-to-cell transmission and assess the impact of cellular factors, viral factors, and antivirals.IMPORTANCEThe ability of viruses to efficiently spread by direct cell-to-cell transmission is thought to play an important role in the establishment and maintenance of viral persistence. As such, elucidating the dynamics of cell-to-cell spread and quantifying the effect of blocking the factors involved has important implications for the design of potent antiviral strategies and controlling viral escape. Mathematical modeling has been widely used to understand HCV infection dynamics and treatment response; however, these models typically assume only cell-free virus infection mechanisms. Here, we used stochastic models describing focus expansion as a means to understand and quantify the dynamics of HCV cell-to-cell spreadin vitroand determined the degree to which cell-to-cell spread is reduced when individual HCV entry factors are blocked. The results demonstrate the ability of this approach to recapitulate and quantify cell-to-cell transmission, as well as the impact of specific factors and potential antivirals.

In this paper, certain delayed virus dynamical models with cell-to-cell infection and density-dependent diffusion are investigated. For the viral model with a single strain, we have proved the well-posedness and studied the global stabilities of equilibria by defining the basic reproductive number [Formula: see text] and structuring proper Lyapunov functional. Moreover, we found that the infection-free equilibrium is globally asymptotically stable if [Formula: see text], and the infection equilibrium is globally asymptotically stable if [Formula: see text]. For the multi-strain model, we found that all viral strains coexist if the corresponding basic reproductive number [Formula: see text], while virus will extinct if [Formula: see text]. As a result, we found that delay and the density-dependent diffusion does not influence the global stability of the model with cell-to-cell infection and homogeneous Neumann boundary conditions.