Evidence map›Paper›PMID 35372970›Full record

ReviewKidney3602021

Monocytes and Macrophages in Kidney Transplantation and Insights from Single Cell RNA-Seq Studies.

Andrew F Malone

Abstract readReview
In one paragraph

Review in Kidney360, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Macrophages-Stealth Cells Below the Radar.Kidney international reports · 2023
    Article
  12. Article
  13. Article
  14. Article
  15. Development of Cell Therapies for Renal Disease and Regenerative Medicine.International journal of molecular sciences · 2022
    Review
  16. Review
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

1 author.

Andrew F MaloneDivision of Nephrology, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri.ORCID 0000-0002-2997-7531

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell RNA sequencing (scRNA-seq) is a powerful technology that allows for the identification of minority cell types in complex tissues, such as immune cells in the kidney. Previously, gene expression from infrequent cell types was missed using bulk RNA-sequencing methods due to an averaging effect. Additionally, scRNA-seq facilitates assignment of cell origin in a sample, a shortcoming of previous bulk sequencing technologies. Thus, scRNA-seq is ideal to study the immune cell landscape and the alloimmune response in the human kidney transplant. However, there are few studies published to date. Macrophages are known to play an important role in health and disease in the kidney. Furthermore, it is known that macrophages play key roles in rejection of the kidney transplant. The definition, ontogeny, and function of these cells is complex and nomenclature has evolved as new technologies have become available. In this review, an overview is provided of monocyte and macrophage nomenclature, ontogeny, and function, with a specific focus on kidney transplantation, and including novel scRNA-seq findings. scRNA-seq offers an unbiased transcriptional approach to defining macrophages and provides insights into macrophage ontogeny and function not possible with contemporary methods.

Indexed as

Kidney TransplantationHumansMacrophagesMonocytesRNA-SeqSingle-Cell Analysisallograftsbasic sciencebiopsykidney transplantmacrophagemonocytesscRNA-seqtranscriptometransplantation

Identifiers

PMID35372970
PMCPMC8785783

What OpenQuestion holds

Textmetadata
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.