Evidence map›Paper›PMID 32125696›Full record

ReviewThe Journal of pathology2020

Applying single-cell technologies to clinical pathology: progress in nephropathology.

Benjamin J Stewart, Menna R Clatworthy

Open access · hybridAbstract readReview
In one paragraph

Review in The Journal of pathology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
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, 19 citations in OpenAlex.

  1. Urinary tract infections in children.Nature reviews. Urology · 2026
    Review
  2. Review
  3. Article
  4. Review
  5. Single-cell and spatial sequencing application in pathology.Journal of pathology and translational medicine · 2023
    Review
  6. Multiplexed droplet single-cell sequencing (Mux-Seq) of normal and transplant kidney.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2022
    Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Recent Advances on Biomarkers of Early and Late Kidney Graft Dysfunction.International journal of molecular sciences · 2020
    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

2 authors at 1 institution in 1 country.

Benjamin J StewartDepartment of Medicine, University of Cambridge, Cambridge, UK.ORCID 0000-0003-4522-0085
Menna R ClatworthyDepartment of Medicine, University of Cambridge, Cambridge, UK.ORCID 0000-0002-3340-9828
University of Cambridge · GB

Funding

Arthritis Research UK 21777Cancer Research UK 21777Cancer Research UK C63442/A25230Department of Health RP-2017-08-ST2-002Medical Research Council MR/N024907/1Medical Research Council MR/S035842/1Wellcome TrustWellcome Trust 216366/Z/19/Z
6 · The paper itself

Abstract

Cells represent the basic building blocks of living organisms. Accurate characterisation of cellular phenotype, intercellular signalling networks, and the spatial organisation of cells within organs is crucial to deliver a better understanding of the processes underpinning physiology, and the perturbations that lead to disease. Single-cell methodologies have increased rapidly in scale and scope in recent years and are set to generate important insights into human disease. Here, we review current practices in nephropathology, which are dominated by relatively simple morphological descriptions of tissue biopsies based on their appearance using light microscopy. Bulk transcriptomics have more recently been used to explore glomerular and tubulointerstitial kidney disease, renal cancer, and the responses to injury and alloimmunity in kidney transplantation, generating novel disease insights and prognostic biomarkers. These studies set the stage for single-cell transcriptomic approaches that reveal cell-type-specific gene expression patterns in health and disease. These technologies allow genome-wide disease susceptibility genes to be interpreted with the knowledge of the specific cell populations within organs that express them, identifying candidate cell types for further study. Single-cell technologies are also moving beyond assaying individual cellular transcriptomes, to measuring the epigenetic landscape of single cells. Single-cell antigen-receptor gene sequencing also enables specific T- and B-cell clones to be tracked in different tissues and disease states. In the coming years these rich 'multi-omic' descriptions of kidney disease will enable histopathological descriptions to be comprehensively integrated with molecular phenotypes, enabling better disease classification and prognostication and the application of personalised treatment strategies. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Indexed as

Gene Expression Regulation, NeoplasticBiomarkers, TumorGenomeHumansKidney NeoplasmsPhenotypeTranscriptomeBiomarkers, Tumorchronic kidney diseaseglomerulonephritiskidneymass cytometrynephropathologyrenal cell carcinomascATACseqscRNAseqsingle-celltransplantation

Identifiers

PMID32125696
PMCPMC8651001
OpenAlexW3009878673

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.