Evidence map›Paper›PMID 35250963›Full record

ArticleFrontiers in immunology2021

How Naive T-Cell Clone Counts Are Shaped By Heterogeneous Thymic Output and Homeostatic Proliferation.

Renaud Dessalles, Yunbei Pan, Mingtao Xia, Davide Maestrini, Maria R D'Orsogna, Tom Chou

Abstract read
In one paragraph

Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Recombinant Molecules as a New Frontier in Mucositis Therapy.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2026
    Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Inferring the T cell repertoire dynamics of healthy individuals.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  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

6 authors.

Renaud DessallesDepartment of Computational Medicine, University of California at Los Angeles (UCLA), Los Angeles, CA, United States.
Yunbei PanDepartment of Mathematics, California State University at Northridge, Los Angeles, CA, United States.
Mingtao XiaDepartment of Mathematics, University of California at Los Angeles (UCLA), Los Angeles, CA, United States.
Davide MaestriniDepartment of Computational Medicine, University of California at Los Angeles (UCLA), Los Angeles, CA, United States.
Maria R D'OrsognaDepartment of Computational Medicine, University of California at Los Angeles (UCLA), Los Angeles, CA, United States.
Tom ChouDepartment of Computational Medicine, University of California at Los Angeles (UCLA), Los Angeles, CA, United States.

Funding

Tracking clonal dynamics during hematopoiesis: mechanistic insight via modeling and data analysisR01HL146552 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CHOU, TOM · 2019 to 2022
$907k
NHLBI NIH HHS R01 HL146552
6 · The paper itself

Abstract

The specificity of T cells is that each T cell has only one T cell receptor (TCR). A T cell clone represents a collection of T cells with the same TCR sequence. Thus, the number of different T cell clones in an organism reflects the number of different T cell receptors (TCRs) that arise from recombination of the V(D)J gene segments during T cell development in the thymus. TCR diversity and more specifically, the clone abundance distribution, are important factors in immune functions. Specific recombination patterns occur more frequently than others while subsequent interactions between TCRs and self-antigens are known to trigger proliferation and sustain naive T cell survival. These processes are TCR-dependent, leading to clone-dependent thymic export and naive T cell proliferation rates. We describe the heterogeneous steady-state population of naive T cells (those that have not yet been antigenically triggered) by using a mean-field model of a regulated birth-death-immigration process. After accounting for random sampling, we investigate how TCR-dependent heterogeneities in immigration and proliferation rates affect the shape of clone abundance distributions (the number of different clones that are represented by a specific number of cells, or "clone counts"). By using reasonable physiological parameter values and fitting predicted clone counts to experimentally sampled clone abundances, we show that realistic levels of heterogeneity in immigration rates cause very little change to predicted clone-counts, but that modest heterogeneity in proliferation rates can generate the observed clone abundances. Our analysis provides constraints among physiological parameters that are necessary to yield predictions that qualitatively match the data. Assumptions of the model and potentially other important mechanistic factors are discussed.

Indexed as

Receptors, Antigen, T-CellT-LymphocytesCell ProliferationCells, CulturedClone CellsReceptors, Antigen, T-Cellclone-count distributionsheterogeneityimmigration-proliferation modelmathematical modelingnaive T cellsrepertoire diversityT-cell receptor

Identifiers

PMID35250963
PMCPMC8891377

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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.