Evidence map›Paper›PMID 37333409›Full record

ArticlebioRxiv : the preprint server for biology2023

Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation for analyzing extracellular viral markers.

Kosaku Kitagawa, Kwang Su Kim, Masashi Iwamoto, Sanae Hayashi, Hyeongki Park, Takara Nishiyama, Naotoshi Nakamura, Yasuhisa Fujita, Shinji Nakaoka, Kazuyuki Aihara and 6 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. 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, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 9 institutions in 4 countries.

Kosaku Kitagawainterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University; Nagoya, Japan.
Kwang Su Kiminterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University; Nagoya, Japan.
Masashi Iwamotointerdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University; Nagoya, Japan.
Sanae HayashiDepartment of Gastroenterology and Hepatology, Faculty of Life Sciences, Kumamoto University; Kumamoto, Japan.
Hyeongki Parkinterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University; Nagoya, Japan.
Takara Nishiyamainterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University; Nagoya, Japan.
Naotoshi Nakamurainterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University; Nagoya, Japan.
Yasuhisa Fujitainterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University; Nagoya, Japan.
Shinji NakaokaFaculty of Advanced Life Science, Hokkaido University; Sapporo, Japan.
Kazuyuki AiharaInternational Research Center for Neurointelligence, The University of Tokyo Institutes for Advanced Study, The University of Tokyo; Tokyo, Japan.
Alan S PerelsonTheoretical Biology and Biophysics Group, Los Alamos National Laboratory; Los Alamos, USA.
Lena AllweissDepartment of Internal Medicine, University Medical Center Hamburg-Eppendorf; Hamburg, Germany.
Maura DandriDepartment of Internal Medicine, University Medical Center Hamburg-Eppendorf; Hamburg, Germany.
Koichi WatashiDepartment of Virology II, National Institute of Infectious Diseases; Tokyo, Japan.
Yasuhito TanakaDepartment of Gastroenterology and Hepatology, Faculty of Life Sciences, Kumamoto University; Kumamoto, Japan.
Shingo Iwamiinterdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University; Nagoya, Japan.
Nagoya University · JPKumamoto University · JPUniversität Hamburg · DEHokkaido University · JPKyushu University · JPLos Alamos National Laboratory · USNational Institute of Infectious Diseases · JPThe University of Tokyo · JPTokyo University of Science · JP

Funding

Spatial Models of Intrahepatic Hepatitis C Virus Propagation in HumansR01AI116868 · NIAID · TRIAD NATIONAL SECURITY, LLC · PI ASHWIN BALAGOPAL, Ruy M Ribeiro · 2016 to 2026
$8.5M
Collaborative Integration of HCV Molecular Virology and Mathematical ModelingR01AI078881 · NIAID · UNIVERSITY OF ILLINOIS AT CHICAGO · PI PERELSON, ALAN S, UPRICHARD, SUSAN L. · 2011 to 2025
$7.5M
Modeling Viral and T Lymphocyte DynamicsR01OD011095 · OD · TRIAD NATIONAL SECURITY, LLC · PI PERELSON, ALAN S · 2012 to 2024
$5.0M
NIAID NIH HHS R01 AI078881NIAID NIH HHS R01 AI116868NIH HHS R01 OD011095
6 · The paper itself

Abstract

Chronic infection of hepatitis B virus (HBV) is caused by the persistence of closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Despite available therapeutic anti-HBV agents, eliminating the cccDNA remains challenging. The quantifying and understanding dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, it requires a liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because of the ethical aspect. We here aimed to develop a non-invasive method for quantifying cccDNA in the liver using surrogate markers present in peripheral blood. We constructed a multiscale mathematical model that explicitly incorporates both intracellular and intercellular HBV infection processes. The model, based on age-structured partial differential equations (PDEs), integrates experimental data from in vitro and in vivo investigations. By applying this model, we successfully predicted the amount and dynamics of intrahepatic cccDNA using specific viral markers in serum samples, including HBV DNA, HBsAg, HBeAg, and HBcrAg. Our study represents a significant step towards advancing the understanding of chronic HBV infection. The non-invasive quantification of cccDNA using our proposed methodology holds promise for improving clinical analyses and treatment strategies. By comprehensively describing the interactions of all components involved in HBV infection, our multiscale mathematical model provides a valuable framework for further research and the development of targeted interventions.

Identifiers

PMID37333409
PMCPMC10274663
OpenAlexW4379653850

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.