Evidence map›Paper›PMID 37410389›Full record

ReviewThe Biochemical journal2023

Respiratory epithelial cell types, states and fates in the era of single-cell RNA-sequencing.

Oleksandr Dudchenko, Jose Ordovas-Montanes, Colin D Bingle

Open access · hybridAbstract readReview
In one paragraph

Review in The Biochemical journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.2field-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

12 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Multifaceted roles of mitochondria in asthma.Cell biology and toxicology · 2024
    Review
  10. Article
  11. Article
  12. Epithelial stem cells and niches in lung alveolar regeneration and diseases.Chinese medical journal pulmonary and critical care medicine · 2024
    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

3 authors at 2 institutions in 2 countries.

Oleksandr DudchenkoDepartment of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, South Yorkshire, U.K.
Jose Ordovas-MontanesDivision of Gastroenterology, Hepatology and Nutrition, Boston Children's Hospital, Boston, MA, U.S.A.
Colin D BingleDepartment of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, South Yorkshire, U.K.ORCID 0000-0002-5405-6988
University of Sheffield · GBBoston Children's Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Standalone and consortia-led single-cell atlases of healthy and diseased human airways generated with single-cell RNA-sequencing (scRNA-seq) have ushered in a new era in respiratory research. Numerous discoveries, including the pulmonary ionocyte, potentially novel cell fates, and a diversity of cell states among common and rare epithelial cell types have highlighted the extent of cellular heterogeneity and plasticity in the respiratory tract. scRNA-seq has also played a pivotal role in our understanding of host-virus interactions in coronavirus disease 2019 (COVID-19). However, as our ability to generate large quantities of scRNA-seq data increases, along with a growing number of scRNA-seq protocols and data analysis methods, new challenges related to the contextualisation and downstream applications of insights are arising. Here, we review the fundamental concept of cellular identity from the perspective of single-cell transcriptomics in the respiratory context, drawing attention to the need to generate reference annotations and to standardise the terminology used in literature. Findings about airway epithelial cell types, states and fates obtained from scRNA-seq experiments are compared and contrasted with information accumulated through the use of conventional methods. This review attempts to discuss major opportunities and to outline some of the key limitations of the modern-day scRNA-seq that need to be addressed to enable efficient and meaningful integration of scRNA-seq data from different platforms and studies, with each other as well as with data from other high-throughput sequencing-based genomic, transcriptomic and epigenetic analyses.

Indexed as

COVID-19Single-Cell AnalysisEpithelial CellsGene Expression ProfilingHumansRNASequence Analysis, RNARNAcell biologycell faterespiratory epitheliumscRNA-seq

Identifiers

PMID37410389
PMCPMC10422933
OpenAlexW4383301729

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.