Evidence map›Paper›PMID 31767174›Full record

ReviewMolecular metabolism2019

The challenge of correctly reporting hormones content and secretion in isolated human islets.

Jean-Claude Henquin

Open access · goldAbstract readReview
In one paragraph

Review in Molecular metabolism, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.6field-weighted citation impact, top 5% 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

17 citing papers in PubMed, 39 citations in OpenAlex.

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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 at 1 institution in 1 country.

Jean-Claude HenquinUnit of Endocrinology and Metabolism, Faculty of Medicine, University of Louvain, Brussels, Belgium. Electronic address: Jean-Claude.Henquin@uclouvain.be.
UCLouvain · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn increased access of research laboratories to isolated human islets has improved our understanding of the biology of the endocrine pancreas and hence the mechanisms causing diabetes. However, in vitro studies of human islets remain technically challenging, and optimal use of such precious material requires a minimum of rigor and coordination to optimize the reliability and share of the information. A detailed report of the demographics of pancreas donors and of the procedures of islet handling after isolation is important but insufficient. Correct characterization of islet basic functions (a token of quality) at the time of experimentation is also crucial. SCOPE OF REVIEW: I have analyzed the literature reporting measurements of insulin and glucagon in the human pancreas or isolated human islets. The published information is often fragmentary. Elementary features such as islet size, insulin content, or rate of hormone secretion are either unreported or incorrectly reported in many papers. Although internal comparisons between control and test groups may remain valid, comparisons with data from other laboratories are problematic. The drawbacks, pitfalls and errors of common ways of expressing hormone content or secretion rates are discussed and alternatives to harmonize data presentation are proposed. MAJOR

conclusionsGreater coherence and rigor in the report of in vitro studies using human islets are necessary to ensure optimal progress in our understanding of the pathogenesis of diabetes.

Indexed as

Diabetes MellitusGlucagonGlucoseHumansInsulinInsulin SecretionIslets of LangerhansPancreasReproducibility of ResultsSpecimen HandlingGlucagonGlucoseInsulinDiabetesGlucagonHormone contentInsulinIsolated human isletsSecretion

Identifiers

PMID31767174
PMCPMC6829677
OpenAlexW2980377140

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.