Evidence map›Paper›PMID 38792730›Full record

ReviewMicroorganisms2024

Incorporating Intracellular Processes in Virus Dynamics Models.

Stanca M Ciupe, Jessica M Conway

Abstract readReview
In one paragraph

Review in Microorganisms, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Identifiability investigation of within-host models of acute virus infection.Mathematical biosciences and engineering : MBE · 2024
    Article
  4. 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

2 authors.

Stanca M CiupeDepartment of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060, USA.ORCID 0000-0002-5386-6946
Jessica M ConwayDepartment of Mathematics and Center for Infectious Disease Dynamics, Penn State University, State College, PA 16802, USA.

Funding

Modeling Viral and T Lymphocyte DynamicsR01OD011095 · OD · TRIAD NATIONAL SECURITY, LLC · PI PERELSON, ALAN S · 2012 to 2024
$5.0M
Collaborative Research: DMS/NIGMS 1: Identifiability investigation of Multi-scale Models of Infectious DiseasesR01GM152743 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI CIUPE, STANCA M. · 2023 to 2025
$600k
SIV cervicovaginal transmission dynamicsR21AI143443 · NIAID · PENNSYLVANIA STATE UNIVERSITY, THE · PI CONWAY, JESSICA M · 2020 to 2021
$427k
National Science Foundation 2051820NIAID NIH HHS R21 AI143443NIGMS NIH HHS R01 GM152743NIH HHS R01 OD011095NIH HHS R01-OD011095NIH HHS R21-AI143443-01A1NIH NIGMS 1R01GM152743-01
6 · The paper itself

Abstract

In-host models have been essential for understanding the dynamics of virus infection inside an infected individual. When used together with biological data, they provide insight into viral life cycle, intracellular and cellular virus-host interactions, and the role, efficacy, and mode of action of therapeutics. In this review, we present the standard model of virus dynamics and highlight situations where added model complexity accounting for intracellular processes is needed. We present several examples from acute and chronic viral infections where such inclusion in explicit and implicit manner has led to improvement in parameter estimates, unification of conclusions, guidance for targeted therapeutics, and crossover among model systems. We also discuss trade-offs between model realism and predictive power and highlight the need of increased data collection at finer scale of resolution to better validate complex models.

Indexed as

intracellular dynamicsmathematical modelingviral dynamics modelviral life cycle

Identifiers

PMID38792730
PMCPMC11124127

What OpenQuestion holds

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LicenceCC BY
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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.