Evidence map›Paper›PMID 33860365›Full record

ArticleJournal of mathematical biology2021

Dynamics of a new HIV model with the activation status of infected cells.

Ting Guo, Zhipeng Qiu, Mingwang Shen, Libin Rong

Open access · bronzeAbstract read
In one paragraph

Article in Journal of mathematical biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 11 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 2 countries.

Ting GuoSchool of Science, Nanjing University of Science and Technology, Nanjing, 210094, China.
Zhipeng QiuCenter for Basic Teaching and Experiment, Nanjing University of Science and Technology Jiangyin Campus, Jiangyin, 214443, China.
Mingwang ShenDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China.
Libin RongDepartment of Mathematics, University of Florida, Gainesville, FL, 32611, USA. libinrong@ufl.edu.ORCID 0000-0002-1464-6078
University of Florida · USNanjing University · CNXi'an Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The activation status can dictate the fate of an HIV-infected CD4+ T cell. Infected cells with a low level of activation remain latent and do not produce virus, while cells with a higher level of activation are more productive and thus likely to transfer more virions to uninfected cells during cell-to-cell transmission. How the activation status of infected cells affects HIV dynamics under antiretroviral therapy remains unclear. We develop a new mathematical model that structures the population of infected cells continuously according to their activation status. The effectiveness of antiretroviral drugs in blocking cell-to-cell viral transmission decreases as the level of activation of infected cells increases because the more virions are transferred from infected to uninfected cells during cell-to-cell transmission, the less effectively the treatment is able to inhibit the transmission. The basic reproduction number [Formula: see text] of the model is shown to determine the existence and stability of the equilibria. Using the principal spectral theory and comparison principle, we show that the infection-free equilibrium is locally and globally asymptotically stable when [Formula: see text] is less than one. By constructing Lyapunov functional, we prove that the infected equilibrium is globally asymptotically stable when [Formula: see text] is greater than one. Numerical investigation shows that even when treatment can completely block cell-free virus infection, virus can still persist due to cell-to-cell transmission. The random switch between infected cells with different activation levels can also contribute to the replenishment of the latent reservoir, which is considered as a major barrier to viral eradication. This study provides a new modeling framework to study the observations, such as the low viral load persistence, extremely slow decay of latently infected cells and transient viral load measurements above the detection limit, in HIV-infected patients during suppressive antiretroviral therapy.

Indexed as

HIV-1HIV InfectionsModels, BiologicalAnti-Retroviral AgentsCD4-Positive T-LymphocytesHumansViral LoadVirus LatencyAnti-Retroviral AgentsCell-to-cell transmissionGlobal stabilityHIV infection modelHIV persistenceStatus structureViral blips

Identifiers

PMID33860365
PMCPMC8049625
OpenAlexW3155271757

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.