Evidence map›Paper›PMID 26150655›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2015

How is the effectiveness of immune surveillance impacted by the spatial distribution of spreading infections?

Ulrich D Kadolsky, Andrew J Yates

Abstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Spatially structured models of viral dynamics: a scoping review.Microbiology and molecular biology reviews : MMBR · 2025
    Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Within-host dynamics of infection: from ecological insights to evolutionary predictions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2015
    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

2 authors.

Ulrich D KadolskyDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA.
Andrew J YatesDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA Department of Microbiology and Immunology, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA Institute of Infection, Immunity and Inflammation, Glasgow Biomedical Research Centre, University of Glasgow, 120 University Place, Glasgow G12 8TA, UK andrew.yates@glasgow.ac.uk.

Funding

Modeling the development, structure and regulation of T cell memoryR01AI093870 · NIAID · UNIVERSITY OF GLASGOW · PI YATES, ANDREW · 2011 to 2025
$5.9M
Systems biology analysis of in vivo impact of substance abuse on HIV infectionR01DA033788 · NIDA · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI GOLDSTEIN, HARRIS · 2012 to 2016
$3.0M
Arthritis Research UKNIAID NIH HHS R01 AI093870NIDA NIH HHS R01 DA033788
6 · The paper itself

Abstract

What effect does the spatial distribution of infected cells have on the efficiency of their removal by immune cells, such as cytotoxic T lymphocytes (CTL)? If infected cells spread in clusters, CTL may initially be slow to locate them but subsequently kill more rapidly than in diffuse infections. We address this question using stochastic, spatially explicit models of CTL interacting with different patterns of infection. Rather than the effector : target ratio, we show that the relevant quantity is the ratio of a CTL's expected time to locate its next target (search time) to the average time it spends conjugated with a target that it is killing (handling time). For inefficient (slow) CTL, when the search time is always limiting, the critical density of CTL (that required to control 50% of infections, C(*)) is independent of the spatial distribution and derives from simple mass-action kinetics. For more efficient CTL such that handling time becomes limiting, mass-action underestimates C(*), and the more clustered an infection the greater is C(*). If CTL migrate chemotactically towards targets the converse holds-C(*) falls, and clustered infections are controlled most efficiently. Real infections are likely to spread patchily; this combined with even weak chemotaxis means that sterilizing immunity may be achieved with substantially lower numbers of CTL than standard models predict.

Indexed as

Immunologic SurveillanceModels, ImmunologicalAnimalsChemotaxis, LeukocyteComputer SimulationHost-Pathogen InteractionsHumansInfectionsStochastic ProcessesT-Lymphocytes, Cytotoxiccomputational immunologycytotoxic T cellsspatial modelling

Identifiers

PMID26150655
PMCPMC4528487

What OpenQuestion holds

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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.