Evidence map›Paper›PMID 24600448›Full record

ArticleFrontiers in immunology2014

Harnessing the heterogeneity of T cell differentiation fate to fine-tune generation of effector and memory T cells.

Chang Gong, Jennifer J Linderman, Denise Kirschner

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

29 citing papers in PubMed, 41 citations in OpenAlex.

  1. Article
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  5. Article
  6. Review
  7. Article
  8. Agent-based models of inflammation in translational systems biology: A decade later.Wiley interdisciplinary reviews. Systems biology and medicine · 2019
    Review
  9. Global sensitivity analysis of biological multi-scale models.Current opinion in biomedical engineering · 2019
    Article
  10. Article
  11. Article
  12. Article
  13. Engineering Platforms for T Cell Modulation.International review of cell and molecular biology · 2018
    Review
  14. Article
  15. Review
  16. The cytokine network in women with an asymptomatic short cervix and the risk of preterm delivery.American journal of reproductive immunology (New York, N.Y. : 1989) · 2017
    Article
  17. Article
  18. Article
  19. Review
  20. 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

3 authors at 2 institutions in 1 country.

Chang GongDepartment of Computational Medicine and Bioinformatics, University of Michigan , Ann Arbor, MI , USA.
Jennifer J LindermanDepartment of Chemical Engineering, University of Michigan , Ann Arbor, MI , USA.
Denise KirschnerDepartment of Microbiology and Immunology, University of Michigan Medical School , Ann Arbor, MI , USA.
University of Michigan–Ann Arbor · USMichigan Medicine · US

Funding

Predicting immune responses that correlate with protection against tuberculosisR01HL110811 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI FLYNN, JOANNE L., KIRSCHNER, DENISE E · 2012 to 2016
$5.9M
Defining how the spectrum of latency affects reactivation of TBR01HL106804 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI FLYNN, JOANNE L., KIRSCHNER, DENISE E · 2010 to 2013
$2.6M
A multi-scale model to predict outcomes of immunomodulation and drug therapy duriR01EB012579 · NIBIB · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI FLYNN, JOANNE L., KIRSCHNER, DENISE E · 2011 to 2014
$2.3M
NHLBI NIH HHS R01 HL106804NHLBI NIH HHS R01 HL110811NIBIB NIH HHS R01 EB012579
6 · The paper itself

Abstract

Recent studies show that naïve T cells bearing identical T cell receptors experience heterogeneous differentiation and clonal expansion processes. The factors controlling this outcome are not well characterized, and their contributions to immune cell dynamics are similarly poorly understood. In this study, we develop a computational model to elaborate mechanisms occurring within and between two important physiological compartments, lymph nodes and blood, to determine how immune cell dynamics are controlled. Our multi-organ (multi-compartment) model integrates cellular and tissue level events and allows us to examine the heterogeneous differentiation of individual precursor cognate naïve T cells to generate both effector and memory T lymphocytes. Using this model, we simulate a hypothetical immune response and reproduce both primary and recall responses to infection. Increased numbers of antigen-bearing dendritic cells (DCs) are predicted to raise production of both effector and memory T cells, and distinct "sweet spots" of peptide-MHC levels on those DCs exist that favor CD4+ or CD8+ T cell differentiation toward either effector or memory cell phenotypes. This has important implications for vaccine development and immunotherapy.

Indexed as

agent-basedbloodcirculationcognatedendritic cellslymph nodessystems biologytwo-compartment model

Identifiers

PMID24600448
PMCPMC3928592
OpenAlexW2035588631

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.