Evidence map›Paper›PMID 37126420›Full record

ReviewAnnual review of immunology2023

Modeling T Cell Fate.

Rob J De Boer, Andrew J Yates

Abstract readReview
In one paragraph

Review in Annual review of immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. CCR2Cellular & molecular immunology · 2025
    Article
  11. Ginkgolic acid inhibits CD8Journal of pharmaceutical analysis · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. A guide to adaptive immune memory.Nature reviews. Immunology · 2024
    Review
  17. Article
  18. The dynamics and longevity of circulating CD4bioRxiv : the preprint server for biology · 2024
    Article
  19. 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.

Rob J De BoerTheoretical Biology and Bioinformatics, Department of Biology, Utrecht University, Utrecht, The Netherlands; email: r.j.deboer@uu.nl.
Andrew J YatesDepartment of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA; email: andrew.yates@columbia.edu.

Funding

Modeling the development, structure and regulation of T cell memoryR01AI093870 · NIAID · UNIVERSITY OF GLASGOW · PI YATES, ANDREW · 2011 to 2025
$5.9M
Modeling the ecology of tissue-resident T cellsU01AI150680 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FARBER, DONNA L., YATES, ANDREW · 2020 to 2024
$5.0M
NIAID NIH HHS R01 AI093870NIAID NIH HHS U01 AI150680
6 · The paper itself

Abstract

Many of the pathways that underlie the diversification of naive T cells into effector and memory subsets, and the maintenance of these populations, remain controversial. In recent years a variety of experimental tools have been developed that allow us to follow the fates of cells and their descendants. In this review we describe how mathematical models provide a natural language for describing the growth, loss, and differentiation of cell populations. By encoding mechanistic descriptions of cell behavior, models can help us interpret these new datasets and reveal the rules underpinning T cell fate decisions, both at steady state and during immune responses.

Indexed as

Immunologic MemoryT-LymphocytesAnimalsCD8-Positive T-LymphocytesCell DifferentiationHumansT-Lymphocyte Subsetsfate determinationmathematical modelingT cells

Identifiers

PMID37126420
PMCPMC11100019

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.