Evidence map›Paper›PMID 41335266›Full record

ArticleBulletin of mathematical biology2025

Investigation of a Two-Patch Within-Host Model of Hepatitis B Viral Infection.

StancaKeoni Castellano, StancaOmar Saucedo, Stanca M Ciupe

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

StancaKeoni Castellano *Department of Mathematics, Virginia Tech, 225 Stanger St., Blacksburg, 24060, VA, United States.ORCID http://orcid.org/0000-0003-4827-8055
StancaOmar Saucedo *Department of Mathematics, Virginia Tech, 225 Stanger St., Blacksburg, 24060, VA, United States.ORCID http://orcid.org/0000-0003-3900-7712
Stanca M Ciupe *Department of Mathematics, Virginia Tech, 225 Stanger St., Blacksburg, 24060, VA, United States. stanca@vt.edu.ORCID http://orcid.org/0000-0002-5386-6946

Funding

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
National Science Foundation 2051820NIGMS NIH HHS 1R01GM152743-01NIGMS NIH HHS R01 GM152743
6 · The paper itself

Abstract

Chronic infection with hepatitis B virus (HBV) can lead to formation of abnormal nodular structures within the liver. To address how changes in liver anatomy affect overall virus-host dynamics, we developed within-host ordinary differential equation models of two-patch hepatitis B infection, one that assumes irreversible and one that assumes reversible movement between nodular structures. We investigated the models analytically and numerically, and determined the contribution of patch susceptibility, immune responses, and virus movement on within-patch and whole-liver virus dynamics. We explored the structural and practical identifiability of the models by implementing a differential algebra approach and the Monte Carlo approach for a specific HBV data set. We determined conditions for viral clearance, viral localization, and systemic viral infection. Our study suggests that cell susceptibility to infection within modular structures, the movement rate between patches, and the immune-mediated infected cell killing have the most influence on HBV dynamics. Our results can help inform intervention strategies.

Indexed as

Hepatitis B, ChronicHepatitis B virusModels, BiologicalComputer SimulationHost-Pathogen InteractionsHumansLiverMathematical ConceptsMonte Carlo MethodAsymptotic dynamicsHepatitis B virusIdentifiability analysisOrdinary differential equationsTwo-patch model

Identifiers

PMID41335266
PMCPMC12675571

What OpenQuestion holds

Textmetadata
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.