ReviewFrontiers in cell and developmental biology2023
Multi-omic analyses in immune cell development with lessons learned from T cell development.
Review in Frontiers in cell and developmental biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review and quantitative meta-analysis of age-dependent human T-lymphocyte homeostasis.Frontiers in immunology · 2025Pooled it
- Peripheral immune landscape in pancreatic ductal adenocarcinoma reveals expansion of effector states with disease progression.iScience · 2026Article
- Spatial pharmacology of anti-cancer immunomodulators: a comprehensive review.Frontiers in pharmacology · 2026Review
- Deciphering the Complexities of Adult Human Steady State and Stress-Induced Hematopoiesis: Progress and Challenges.International journal of molecular sciences · 2025Review
- The recombinase activating genes: architects of immune diversity during lymphocyte development.Frontiers in immunology · 2023Review
- Using combined single-cell gene expression, TCR sequencing and cell surface protein barcoding to characterize and track CD4+ T cell clones from murine tissues.Frontiers in immunology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Traditionally, flow cytometry has been the preferred method to characterize immune cells at the single-cell level. Flow cytometry is used in immunology mostly to measure the expression of identifying markers on the cell surface, but-with good antibodies-can also be used to assess the expression of intracellular proteins. The advent of single-cell RNA-sequencing has paved the road to study immune development at an unprecedented resolution. Single-cell RNA-sequencing studies have not only allowed us to efficiently chart the make-up of heterogeneous tissues, including their most rare cell populations, it also increasingly contributes to our understanding how different omics modalities interplay at a single cell resolution. Particularly for investigating the immune system, this means that these single-cell techniques can be integrated to combine and correlate RNA and protein data at the single-cell level. While RNA data usually reveals a large heterogeneity of a given population identified solely by a combination of surface protein markers, the integration of different omics modalities at a single cell resolution is expected to greatly contribute to our understanding of the immune system.
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What OpenQuestion holds
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.