Evidence map›Paper›PMID 34241569›Full record

ArticleIslets2021

A functional genomic approach to identify reference genes for human pancreatic beta cell real-time quantitative RT-PCR analysis.

Maria Inês Alvelos, Florian Szymczak, Ângela Castela, Sandra Marín-Cañas, Bianca Marmontel de Souza, Ioannis Gkantounas, Maikel Colli, Federica Fantuzzi, Cristina Cosentino, Mariana Igoillo-Esteve and 4 more

Open access · bronzeAbstract read
In one paragraph

Article in Islets, 2021. 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
0.5field-weighted citation impact, top 39% 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, 16 citations in OpenAlex.

  1. From bats to humans: uncoveringbioRxiv : the preprint server for biology · 2026
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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

14 authors at 3 institutions in 3 countries.

Maria Inês AlvelosULB Center for Diabetes Research, Medical Faculty, Université Libre De Bruxelles, Brussels (ULB) Belgium.
Florian SzymczakULB Center for Diabetes Research, Medical Faculty, Université Libre De Bruxelles, Brussels (ULB) Belgium.
Ângela CastelaULB Center for Diabetes Research, Medical Faculty, Université Libre De Bruxelles, Brussels (ULB) Belgium.
Sandra Marín-CañasULB Center for Diabetes Research, Medical Faculty, Université Libre De Bruxelles, Brussels (ULB) Belgium.
Bianca Marmontel de SouzaULB Center for Diabetes Research, Medical Faculty, Université Libre De Bruxelles, Brussels (ULB) Belgium.
Ioannis GkantounasULB Center for Diabetes Research, Medical Faculty, Université Libre De Bruxelles, Brussels (ULB) Belgium.
Maikel ColliULB Center for Diabetes Research, Medical Faculty, Université Libre De Bruxelles, Brussels (ULB) Belgium.
Federica FantuzziULB Center for Diabetes Research, Medical Faculty, Université Libre De Bruxelles, Brussels (ULB) Belgium.
Cristina CosentinoULB Center for Diabetes Research, Medical Faculty, Université Libre De Bruxelles, Brussels (ULB) Belgium.
Mariana Igoillo-EsteveULB Center for Diabetes Research, Medical Faculty, Université Libre De Bruxelles, Brussels (ULB) Belgium.
Lorella MarselliDepartment of Clinical and Experimental Medicine, Islet Cell Laboratory, University of Pisa, Pisa, Italy.
Piero MarchettiDepartment of Clinical and Experimental Medicine, Islet Cell Laboratory, University of Pisa, Pisa, Italy.
Miriam CnopULB Center for Diabetes Research, Medical Faculty, Université Libre De Bruxelles, Brussels (ULB) Belgium.
Décio L EizirikULB Center for Diabetes Research, Medical Faculty, Université Libre De Bruxelles, Brussels (ULB) Belgium.
Université Libre de Bruxelles · BEUniversity of Pisa · ITErasmus Hospital · BE

Funding

The Integrated Stress Response in Human Islets During Early T1DU01DK127786 · NIDDK · UNIVERSITY OF CHICAGO · PI EVANS-MOLINA, CARMELLA, MIRMIRA, RAGHAVENDRA G · 2020 to 2025
$7.1M
NIDDK NIH HHS U01 DK127786
6 · The paper itself

Abstract

Exposure of human pancreatic beta cells to pro-inflammatory cytokines or metabolic stressors is used to model events related to type 1 and type 2 diabetes, respectively. Quantitative real-time PCR is commonly used to quantify changes in gene expression. The selection of the most adequate reference gene(s) for gene expression normalization is an important pre-requisite to obtain accurate and reliable results. There are no universally applicable reference genes, and the human beta cell expression of commonly used reference genes can be altered by different stressors. Here we aimed to identify the most stably expressed genes in human beta cells to normalize quantitative real-time PCR gene expression.We used comprehensive RNA-sequencing data from the human pancreatic beta cell line EndoC-βH1, human islets exposed to cytokines or the free fatty acid palmitate in order to identify the most stably expressed genes. Genes were filtered based on their level of significance (adjusted

Indexed as

Insulin-Secreting CellsGenomicsHumansReal-Time Polymerase Chain ReactionReverse Transcriptase Polymerase Chain ReactionReference genes/ beta cells/ diabetes/ RNA-sequencing/ quantitative real-time pcr

Identifiers

PMID34241569
PMCPMC8280887
OpenAlexW3154139735

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.