Evidence map›Paper›PMID 27997613›Full record

ArticlePloS one2016

Spatiotemporal Dynamics of Virus Infection Spreading in Tissues.

Gennady Bocharov, Andreas Meyerhans, Nickolai Bessonov, Sergei Trofimchuk, Vitaly Volpert

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
5.1field-weighted citation impact, top 4% 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

8 citing papers in PubMed, 56 citations in OpenAlex.

  1. Review
  2. Spatially structured models of viral dynamics: a scoping review.Microbiology and molecular biology reviews : MMBR · 2025
    Article
  3. Current Perspectives in Antiviral Research.International journal of molecular sciences · 2023
    Article
  4. Article
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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

5 authors at 5 institutions in 4 countries.

Gennady BocharovInstitute of Numerical Mathematics, Russian Academy of Sciences, Moscow, Russian Federation.ORCID http://orcid.org/0000-0002-5049-0656
Andreas MeyerhansInstitute of Numerical Mathematics, Russian Academy of Sciences, Moscow, Russian Federation.
Nickolai BessonovInstitute of Problems of Mechanical Engineering, Russian Academy of Sciences, Saint Petersburg, Russian Federation.
Sergei TrofimchukInstituto de Matemática y Fisica, Universidad de Talca, Talca, Chile.
Vitaly VolpertInstitute of Numerical Mathematics, Russian Academy of Sciences, Moscow, Russian Federation.
Institució Catalana de Recerca i Estudis Avançats · ESInstitute of Problems of Mechanical Engineering · RUPeoples' Friendship University of Russia · RUUniversité Claude Bernard Lyon 1 · FRUniversity of Talca · CL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Virus spreading in tissues is determined by virus transport, virus multiplication in host cells and the virus-induced immune response. Cytotoxic T cells remove infected cells with a rate determined by the infection level. The intensity of the immune response has a bell-shaped dependence on the concentration of virus, i.e., it increases at low and decays at high infection levels. A combination of these effects and a time delay in the immune response determine the development of virus infection in tissues like spleen or lymph nodes. The mathematical model described in this work consists of reaction-diffusion equations with a delay. It shows that the different regimes of infection spreading like the establishment of a low level infection, a high level infection or a transition between both are determined by the initial virus load and by the intensity of the immune response. The dynamics of the model solutions include simple and composed waves, and periodic and aperiodic oscillations. The results of analytical and numerical studies of the model provide a systematic basis for a quantitative understanding and interpretation of the determinants of the infection process in target organs and tissues from the image-derived data as well as of the spatiotemporal mechanisms of viral disease pathogenesis, and have direct implications for a biopsy-based medical testing of the chronic infection processes caused by viruses, e.g. HIV, HCV and HBV.

Indexed as

Models, ImmunologicalHepacivirusHepatitis BHepatitis B virusHepatitis CHIV-1HIV InfectionsHumans

Identifiers

PMID27997613
PMCPMC5173377
OpenAlexW2563470588

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.