ReviewAmerican journal of reproductive immunology (New York, N.Y. : 1989)2019
Single-cell technologies in reproductive immunology.
Review in American journal of reproductive immunology (New York, N.Y. : 1989), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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
8 citing papers in PubMed, 14 citations in OpenAlex.
- The maternal-fetal interface at single-cell resolution: uncovering the cellular anatomy of the placenta and decidua.American journal of obstetrics and gynecology · 2025Review
- Characteristics of the Dynamic Evolutionary Pathway of ADSCs Induced Differentiation into Astrocytes Based on scRNA-Seq Analysis.Molecular neurobiology · 2025Article
- The significance of single-cell transcriptome analysis in epididymis research.Frontiers in cell and developmental biology · 2024Article
- Immune Dysfunction in Polycystic Ovary Syndrome.ImmunoHorizons · 2023Review
- Roles of immune microenvironment in the female reproductive maintenance and regulation: novel insights into the crosstalk of immune cells.Frontiers in immunology · 2023Review
- Single-Cell Immunobiology of the Maternal-Fetal Interface.Journal of immunology (Baltimore, Md. : 1950) · 2022Review
- Human placental biology at single-cell resolution: a contemporaneous review.BJOG : an international journal of obstetrics and gynaecology · 2022Review
- Technological advances in cancer immunity: from immunogenomics to single-cell analysis and artificial intelligence.Signal transduction and targeted therapy · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The maternal-fetal interface represents a unique immune privileged site that maintains the ability to defend against pathogens while orchestrating the necessary tissue remodeling required for placentation. The recent discovery of novel cellular families (innate lymphoid cells, tissue-resident NK cells) suggests that our understanding of the decidual immunome is incomplete. To understand this complex milieu, new technological developments allow reproductive immunologists to collect increasingly complex data at a cellular resolution. Polychromatic flow cytometry allows for greater resolution in the identification of novel cell types by surface and intracellular protein. Single-cell RNA-seq coupled with microfluidics allows for efficient cellular transcriptomics. The extreme dimensionality and size of data sets generated, however, requires the application of novel computational approaches for unbiased analysis. There are now multiple dimensionality reduction (tSNE, SPADE) and visualization tools (SPICE) that allow researchers to efficiently analyze flow cytometry data. Development of computational tools has also been extended to RNA-seq data (including scRNA-seq), which requires specific analytical tools. Here, we provide an overview and a brief primer for the reproductive immunology community on data acquisition and computational tools for the analysis of complex flow cytometry and RNA-seq data.
Indexed as
Identifiers
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.