Evidence map›Paper›PMID 30581120›Full record

ReviewCell metabolism2019

Single-Cell RNA-Seq of the Pancreatic Islets--a Promise Not yet Fulfilled?

Yue J Wang, Klaus H Kaestner

Open access · bronzeAbstract readReview
In one paragraph

Review in Cell metabolism, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
79citing papers in PubMed, 1 pooled it
12.5field-weighted citation impact, top 1% 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

79 citing papers in PubMed, 1 synthesis or guideline pooled it, 130 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Mapping Cell Atlases at the Single-Cell Level.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  16. Review
  17. Article
  18. Article
  19. β-Cell Regeneration Is Driven by Pancreatic Plasticity.Advances in anatomy, embryology, and cell biology · 2024
    Review
  20. β-Cell Heterogeneity and Plasticity.Advances in anatomy, embryology, and cell biology · 2024
    Review

19 more citing papers are in PubMed but not listed here.

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.

Yue J WangDepartment of Genetics and Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, 12-126 Smilow Center for Translational Research, 3400 Civic Center Boulevard, Philadelphia, PA 19104-6145, USA.
Klaus H KaestnerDepartment of Genetics and Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, 12-126 Smilow Center for Translational Research, 3400 Civic Center Boulevard, Philadelphia, PA 19104-6145, USA. Electronic address: kaestner@pennmedicine.upenn.edu.
Translational Therapeutics (United States) · US

Funding

Penn integrated Human Pancreas procurement and Analysis ProgramUC4DK112217 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI BETTS, MICHAEL R, FELDMAN, MICHAEL D · 2016 to 2020
$17.8M
Epigenetic Rejuvenation of Human Beta-CellsUC4DK104119 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI GLASER, BENJAMIN, KAESTNER, KLAUS H · 2014 to 2014
$3.6M
NIDDK NIH HHS UC4 DK104119NIDDK NIH HHS UC4 DK112217
6 · The paper itself

Abstract

In the past 3 years, we have seen a flurry of publications on single-cell RNA sequencing (RNA-seq) analyses of pancreatic islets from mouse and human. This technology holds the promise to refine cell-type signatures and discover cellular heterogeneity among the canonical endocrine cell types such as the glucagon-producing α and insulin-producing β cells, going as far as suggesting new subtypes. In addition, single-cell RNA-seq has the ability to characterize rare endocrine cell types that are not captured by prior bulk analysis. With transcriptomics data from individual endocrine cells, cellular states can be profiled both along developmental processes and during the emergence of metabolic diseases. However, the promises of this new technology have not yet been met in full. While the methodology for the first time enabled the transcriptional definition of rare endocrine cell types such as ghrelin-producing ɛ cells, some of the conclusions regarding cell-type-specific gene expression changes in type 2 diabetes might need to be revisited once larger sample sizes become available. Data generation and analysis are continuously improving single-cell RNA-seq approaches and are helping us to understand the (mal)adaptations of the islet cells during development, metabolic challenge, and disease.

Indexed as

AnimalsDiabetes Mellitus, Type 2Gene Expression ProfilingGlucagon-Secreting CellsHumansInsulin-Secreting CellsMiceRNA, MessengerRNA-SeqSingle-Cell AnalysisRNA, Messengerisletssingle-cell RNA-seqβ cellβ cell heterogeneity

Identifiers

PMID30581120
PMCPMC6402960
OpenAlexW2905801050

What OpenQuestion holds

Textmetadata
LicenceTDM
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.