About: Improving the estimation of the death rate of infected cells from time course data during the acute phase of virus infections: application to acute HIV-1 infection in a humanized mouse model

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About: Improving the estimation of the death rate of infected cells from time course data during the acute phase of virus infections: application to acute HIV-1 infection in a humanized mouse model Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Improving the estimation of the death rate of infected cells from time course data during the acute phase of virus infections: application to acute HIV-1 infection in a humanized mouse model
Creator	Aihara, Kazuyuki Koyanagi, Yoshio Misawa, Naoko Sato, Kei Iwami, Shingo »more»
source	Medline; PMC
abstract	BACKGROUND: Mathematical modeling of virus dynamics has provided quantitative insights into viral infections such as influenza, the simian immunodeficiency virus/human immunodeficiency virus, hepatitis B, and hepatitis C. Through modeling, we can estimate the half-life of infected cells, the exponential growth rate, and the basic reproduction number (R(0)). To calculate R(0) from virus load data, the death rate of productively infected cells is required. This can be readily estimated from treatment data collected during the chronic phase, but is difficult to determine from acute infection data. Here, we propose two new models that can reliably estimate the average life span of infected cells from acute-phase data, and apply both methods to experimental data from humanized mice infected with HIV-1. METHODS: Both new models, called as the reduced quasi-steady state (RQS) model and the piece-wise regression (PWR) model, are derived by simplification of a standard model for the acute-phase dynamics of target cells, viruses and infected cells. By having only a limited number of parameters, both models allow us to reliably estimate the death rate of productively infected cells. Simulated datasets with plausible parameter values are generated with the standard model to compare the performance of the new models with that of the major previous model (i.e., the simple exponential model). Finally, we fit models to time course data from HIV-1 infected humanized mice to estimate the several important parameters characterizing their acute infection. RESULTS AND CONCLUSIONS: The new models provided much better estimates than the previous model because they more precisely capture the de novo infection process. Both models describe the acute phase of HIV-1 infected humanized mice reasonably well, and we estimated an average death rate of infected cells of 0.61 and 0.61, an average exponential growth rate of 0.69 and 0.76, and an average basic reproduction number of 2.30 and 2.38 in the RQS model and the PWR model, respectively. These estimates are fairly close to those obtained in humans.
has issue date	2014-05-21(xsd:dateTime)
bibo:doi	10.1186/1742-4682-11-22
bibo:pmid	24885827
has license	cc-by
sha1sum (hex)	33222702ba2e2e7e5f526c667d64beb5bd2cda96
schema:url	https://doi.org/10.1186/1742-4682-11-22
resource representing a document's title	Improving the estimation of the death rate of infected cells from time course data during the acute phase of virus infections: application to acute HIV-1 infection in a humanized mouse model
has PubMed Central identifier	PMC4035760
has PubMed identifier	24885827
schema:publication	Theor Biol Med Model
resource representing a document's body	covid:33222702ba2e2e7e5f526c667d64beb5bd2cda96#body_text
is schema:about of	named entity 'HUMANIZED MOUSE' named entity 'DATA' named entity 'limited' named entity 'estimated' named entity 'Both' »more»

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