Evidence map›Paper›PMID 31263465›Full record

ReviewFrontiers in immunology2019

Distributed Adaptive Search in T Cells: Lessons From Ants.

Melanie E Moses, Judy L Cannon, Deborah M Gordon, Stephanie Forrest

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

10 citing papers in PubMed, 25 citations in OpenAlex.

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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

4 authors at 3 institutions in 1 country.

Melanie E MosesMoses Biological Computation Laboratory, Department of Computer Science, University of New Mexico, Albuquerque, NM, United States.
Judy L CannonThe Cannon Laboratory, Department of Molecular Genetics & Microbiology, University of New Mexico School of Medicine, Albuquerque, NM, United States.
Deborah M GordonSanta Fe Institute, Santa Fe, NM, United States.
Stephanie ForrestSanta Fe Institute, Santa Fe, NM, United States.
Santa Fe Institute · USArizona State University · USUniversity of New Mexico · US

Funding

UNM TRAININGP50GM085273 · NIGMS · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI LIDKE, KEITH A · 2009 to 2018
$26.1M
Unfolded Protein Response and Autophagy in T Helper Cell Effector FunctionP20GM121176 · NIGMS · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI VOJO P DERETIC · 2017 to 2026
$24.9M
COBRE Center for Evolutionary and Theoretical ImmunologyP20GM103452 · NIGMS · UNIVERSITY OF NEW MEXICO · PI LOKER, ERIC SAMUEL · 2012 to 2013
$4.2M
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
NIAID NIH HHS R01 AI097202NIGMS NIH HHS P20 GM103452NIGMS NIH HHS P20 GM121176NIGMS NIH HHS P50 GM085273
6 · The paper itself

Abstract

There are striking similarities between the strategies ant colonies use to forage for food and immune systems use to search for pathogens. Searchers (ants and cells) use the appropriate combination of random and directed motion, direct and indirect agent-agent interactions, and traversal of physical structures to solve search problems in a variety of environments. An effective immune response requires immune cells to search efficiently and effectively for diverse types of pathogens in different tissues and organs, just as different species of ants have evolved diverse search strategies to forage effectively for a variety of resources in a variety of habitats. Successful T cell search is required to initiate the adaptive immune response in lymph nodes and to eradicate pathogens at sites of infection in peripheral tissue. Ant search strategies suggest novel predictions about T cell search. In both systems, the distribution of targets in time and space determines the most effective search strategy. We hypothesize that the ability of searchers to sense and adapt to dynamic targets and environmental conditions enhances search effectiveness through adjustments to movement and communication patterns. We also suggest that random motion is a more important component of search strategies than is generally recognized. The behavior we observe in ants reveals general design principles and constraints that govern distributed adaptive search in a wide variety of complex systems, particularly the immune system.

Indexed as

Models, ImmunologicalAdaptive ImmunityAlgorithmsAnimalsAntsBehavior, AnimalHost-Pathogen InteractionsHumansT-Lymphocytesadaptive searchant foragingant inspired algorithmscollective searchT cells

Identifiers

PMID31263465
PMCPMC6585175
OpenAlexW2949453209

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.