ArticlePLoS computational biology2016
Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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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.
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Who cites it
39 citing papers in PubMed, 79 citations in OpenAlex.
- IL-7 promotes naïve T cell motility to enable T cell scanning of dendritic cells in the LN.Cytokine · 2026Article
- Interleukin-7R and chemokine receptor type 7 differentially regulate metabolism in CD4+ and CD8+ T cells.ImmunoHorizons · 2026Article
- Bigger is faster in the adaptive immune response.Scientific reports · 2025Article
- FIRST PASSAGE TIMES TO T CELL ACTIVATION.ArXiv · 2025Article
- Behavioral investigation of reactive and neoplastic lymphocytes in human lymph nodes in 4D.PloS one · 2025Article
- Understanding the interplay between extracellular matrix topology and tumor-immune interactions: Challenges and opportunities.Oncotarget · 2024Review
- Decoding Immuno-Competence: A Novel Analysis of Complete Blood Cell Count Data in COVID-19 Outcomes.Biomedicines · 2024Article
- Quantitative analyses of T cell motion in tissue reveals factors driving T cell search in tissues.eLife · 2023Article
- Article
- Random walk informed heterogeneity detection reveals how the lymph node conduit network influences T cells collective exploration behavior.PLoS computational biology · 2023Article
- Interpreting T-cell search "strategies" in the light of evolution under constraints.PLoS computational biology · 2023Article
- New definitions of human lymphoid and follicular cell entities in lymphatic tissue by machine learning.Scientific reports · 2022Article
- High resolution microfluidic assay and probabilistic modeling reveal cooperation between T cells in tumor killing.Nature communications · 2022Article
- Article
- Integrative lymph node-mimicking models created with biomaterials and computational tools to study the immune system.Materials today. Bio · 2022Review
- Article
- From Antibody Repertoires to Cell-Cell Interactions to Molecular Networks: Bridging Scales in the Germinal Center.Frontiers in immunology · 2022Review
- Article
- Review
- Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection.PLoS computational biology · 2021Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Effective search strategies have evolved in many biological systems, including the immune system. T cells are key effectors of the immune response, required for clearance of pathogenic infection. T cell activation requires that T cells encounter antigen-bearing dendritic cells within lymph nodes, thus, T cell search patterns within lymph nodes may be a crucial determinant of how quickly a T cell immune response can be initiated. Previous work suggests that T cell motion in the lymph node is similar to a Brownian random walk, however, no detailed analysis has definitively shown whether T cell movement is consistent with Brownian motion. Here, we provide a precise description of T cell motility in lymph nodes and a computational model that demonstrates how motility impacts T cell search efficiency. We find that both Brownian and Lévy walks fail to capture the complexity of T cell motion. Instead, T cell movement is better described as a correlated random walk with a heavy-tailed distribution of step lengths. Using computer simulations, we identify three distinct factors that contribute to increasing T cell search efficiency: 1) a lognormal distribution of step lengths, 2) motion that is directionally persistent over short time scales, and 3) heterogeneity in movement patterns. Furthermore, we show that T cells move differently in specific frequently visited locations that we call "hotspots" within lymph nodes, suggesting that T cells change their movement in response to the lymph node environment. Our results show that like foraging animals, T cells adapt to environmental cues, suggesting that adaption is a fundamental feature of biological search.
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Registered trials
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.