Evidence map›Paper›PMID 28123385›Full record

ArticleFrontiers in immunology2016

Tissue Dimensionality Influences the Functional Response of Cytotoxic T Lymphocyte-Mediated Killing of Targets.

Saikrishna Gadhamsetty, Athanasius F M Marée, Rob J de Boer, Joost B Beltman

Abstract read
In one paragraph

Article in Frontiers in immunology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
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  3. Article
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  6. Article
  7. Global sensitivity analysis of biological multi-scale models.Current opinion in biomedical engineering · 2019
    Article
  8. Towards multiscale modeling of the CD8Wiley interdisciplinary reviews. Systems biology and medicine · 2019
    Review
  9. Article
  10. Article
  11. 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

4 authors.

Saikrishna GadhamsettyTheoretical Biology, Utrecht University , Utrecht , Netherlands.
Athanasius F M MaréeDepartment of Computational and Systems Biology, John Innes Centre , Norwich , UK.
Rob J de BoerTheoretical Biology, Utrecht University , Utrecht , Netherlands.
Joost B BeltmanDivision of Toxicology, Leiden Academic Centre for Drug Research, Leiden University , Leiden , Netherlands.

Funding

Biotechnology and Biological Sciences Research Council BBS/E/J/000C0645
6 · The paper itself

Abstract

Cytotoxic T lymphocyte (CTL)-mediated killing of virus infections and tumors occurs over a wide range of conditions. The spatial environments in which CTLs encounter target cells vary from narrow vessels, to two-dimensional epithelial tissues, to densely populated 3-dimensional (3D) T cell areas within lymphoid tissues. How such spatial environments alter the functional response of CTL-mediated killing, i.e., how the killing efficiency depends on cell densities, is unclear. In this study, we perform cellular Potts model simulations in different spatial configurations to investigate how the dimensionality of the space affects the functional response of CTL-mediated killing. Irrespective of the spatial configuration, the function with separate saturation constants for CTL and for target cell densities that we previously proposed can in all cases describe the response, demonstrating its generality. However, the tissue dimensionality determines at which cell densities the killing rate starts to saturate. We show that saturation in a fully 3D environment is stronger than in a "flat" 3D environment, which is largely due to accompanying differences in the CTL-target encounter rates.

Indexed as

cellular Potts modelCTLfunctional responsekilling ratetissue dimensionality

Identifiers

PMID28123385
PMCPMC5225319

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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.