Evidence map›Paper›PMID 31221802›Full record

ArticleDiabetes2019

Navigating the Depths and Avoiding the Shallows of Pancreatic Islet Cell Transcriptomes.

Alex M Mawla, Mark O Huising

Open access · bronzeAbstract read
In one paragraph

Article in Diabetes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
84citing papers in PubMed, 2 pooled it
15.0field-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

84 citing papers in PubMed, 2 syntheses or guidelines pooled it, 124 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  11. Review
  12. Role of complexin 2 in the regulation of hormone secretion from the islet of Langerhans.American journal of physiology. Endocrinology and metabolism · 2025
    Article
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  17. Review
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24 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.

Alex M MawlaDepartment of Neurobiology, Physiology and Behavior, College of Biological Sciences, University of California, Davis, Davis, CA.
Mark O HuisingDepartment of Neurobiology, Physiology and Behavior, College of Biological Sciences, University of California, Davis, Davis, CA mhuising@ucdavis.edu.ORCID 0000-0002-6594-2205
University of California, Davis · US

Funding

PARACRINE FEEDBACK BY PANCREATIC DELTA CELLS TO CONTROL GLUCAGON AND INSULIN RELEASE AND MANAGE DIABETESR01DK110276 · NIDDK · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Mark O. Huising · 2017 to 2026
$3.9M
NIDDK NIH HHS R01 DK110276
6 · The paper itself

Abstract

Islet gene expression has been widely studied to better understand the transcriptional features that define a healthy β-cell. Transcriptomes of FACS-purified α-, β-, and δ-cells using bulk RNA-sequencing have facilitated our understanding of the complex network of cross talk between islet cells and its effects on β-cell function. However, these approaches were by design not intended to resolve heterogeneity between individual cells. Several recent studies used single-cell RNA sequencing (scRNA-Seq) to report considerable heterogeneity within mouse and human β-cells. In this Perspective, we assess how this newfound ability to assess gene expression at single-cell resolution has enhanced our understanding of β-cell heterogeneity. We conduct a comprehensive assessment of several single human β-cell transcriptome data sets and ask if the heterogeneity reported by these studies showed overlap and concurred with previously known examples of β-cell heterogeneity. We also illustrate the impact of the inevitable limitations of working at or below the limit of detection of gene expression at single cell resolution and their consequences for the quality of single-islet cell transcriptome data. Finally, we offer some guidance on when to opt for scRNA-Seq and when bulk sequencing approaches may be better suited.

Indexed as

AnimalsGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansInsulin-Secreting CellsMiceRNASequence Analysis, RNASingle-Cell AnalysisSoftwareTranscriptomeRNA

Identifiers

PMID31221802
PMCPMC6609986
OpenAlexW2952872148

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.