Evidence map›Paper›PMID 26920246›Full record

ArticleJournal of theoretical biology2016

A spatial model of the efficiency of T cell search in the influenza-infected lung.

Drew Levin, Stephanie Forrest, Soumya Banerjee, Candice Clay, Judy Cannon, Melanie Moses, Frederick Koster

Abstract read
In one paragraph

Article in Journal of theoretical biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Spatially structured models of viral dynamics: a scoping review.Microbiology and molecular biology reviews : MMBR · 2025
    Article
  3. Quantitatively Mapping Immune Control during Influenza.Current opinion in systems biology · 2024
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. 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

7 authors.

Drew LevinDepartment of Computer Science, University of New Mexico, Albuquerque, NM, USA. Electronic address: drew@cs.unm.edu.
Stephanie ForrestDepartment of Computer Science, University of New Mexico, Albuquerque, NM, USA.
Soumya BanerjeeDepartment of Computer Science, University of New Mexico, Albuquerque, NM, USA.
Candice ClayLovelace Respiratory Research Institute, Albuquerque, NM, USA.
Judy CannonDepartment of Molecular Genetics & Microbiology, Department of Pathology, University of New Mexico, Health Sciences Center, Albuquerque, NM, USA.
Melanie MosesDepartment of Computer Science, University of New Mexico, Albuquerque, NM, USA.
Frederick KosterDepartment of Computer Science, University of New Mexico, Albuquerque, NM, USA; Lovelace Respiratory Research Institute, Albuquerque, NM, USA.

Funding

UNM TRAININGP50GM085273 · NIGMS · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI EDWARDS, JEREMY S · 2009 to 2018
$26.1M
T5000 Diagnostic System in Ferret Model of InfluenzaU01AI074561 · NIAID · LOVELACE BIOMEDICAL & ENVIRONMENTAL RESEARCH INSTITUTE · PI KOSTER, FREDERICK T · 2007 to 2009
$2.2M
The role of PKCtheta in T cell and T-ALL migrationR01AI097202 · NIAID · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI CANNON, JUDY LIN · 2012 to 2016
$1.9M
Modeling influenza virus replication in primary human lung cellsR21AI073607 · NIAID · LOVELACE BIOMEDICAL & ENVIRONMENTAL RESEARCH INSTITUTE · PI KOSTER, FREDERICK T · 2007 to 2008
$529k
NIAID NIH HHS R01 AI097202NIAID NIH HHS R21 AI073607NIAID NIH HHS U01 AI074561NIGMS NIH HHS P50 GM085273
6 · The paper itself

Abstract

Emerging strains of influenza, such as avian H5N1 and 2009 pandemic H1N1, are more virulent than seasonal H1N1 influenza, yet the underlying mechanisms for these differences are not well understood. Subtle differences in how a given strain interacts with the immune system are likely a key factor in determining virulence. One aspect of the interaction is the ability of T cells to locate the foci of the infection in time to prevent uncontrolled expansion. Here, we develop an agent based spatial model to focus on T cell migration from lymph nodes through the vascular system to sites of infection. We use our model to investigate whether different strains of influenza modulate this process. We calibrate the model using viral and chemokine secretion rates we measure in vitro together with values taken from literature. The spatial nature of the model reveals unique challenges for T cell recruitment that are not apparent in standard differential equation models. In this model comparing three influenza viruses, plaque expansion is governed primarily by the replication rate of the virus strain, and the efficiency of the T cell search-and-kill is limited by the density of infected epithelial cells in each plaque. Thus for each virus there is a different threshold of T cell search time above which recruited T cells are unable to control further expansion. Future models could use this relationship to more accurately predict control of the infection.

Indexed as

Models, ImmunologicalCytokinesHumansInfluenza A Virus, H1N1 SubtypeInfluenza A Virus, H5N1 SubtypeInfluenza, HumanLungLymph NodesSeasonsSpecies SpecificityT-LymphocytesCytokinesAgent-based modelComputational biologyImmunologySystems biologyVirology

Identifiers

PMID26920246
PMCPMC4862360

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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.