Evidence map›Paper›PMID 22396763›Full record

ArticlePloS one2012

Function-based discovery of significant transcriptional temporal patterns in insulin stimulated muscle cells.

Barbara Di Camillo, Brian A Irving, Jill Schimke, Tiziana Sanavia, Gianna Toffolo, Claudio Cobelli, K Sreekumaran Nair

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Human and mouse muscle transcriptomic analyses identify insulin receptor mRNA downregulation in hyperinsulinemia-associated insulin resistance.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2022
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia.Proceedings of the National Academy of Sciences of the United States of America · 2013
    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

7 authors at 2 institutions in 2 countries.

Barbara Di CamilloInformation Engineering Department, University of Padova, Padova, Italy.
Brian A Irving
Jill Schimke
Tiziana Sanavia
Gianna Toffolo
Claudio Cobelli
K Sreekumaran Nair
University of Padua · ITMayo Clinic · US

Funding

IN VIVO REGULATION OF PROTEIN TURNOVER BY HORMONESR01DK041973 · NIDDK · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI NAIR, K SREEKUMARAN · 1989 to 2014
$7.3M
NCRR NIH HHS KL2 RR084151NIDDK NIH HHS R01 DK041973NIDDK NIH HHS R01 DK 41973
6 · The paper itself

Abstract

backgroundInsulin action on protein synthesis (translation of transcripts) and post-translational modifications, especially of those involving the reversible modifications such as phosphorylation of various signaling proteins, are extensively studied but insulin effect on transcription of genes, especially of transcriptional temporal patterns remains to be fully defined. METHODOLOGY/PRINCIPAL

findingsTo identify significant transcriptional temporal patterns we utilized primary differentiated rat skeletal muscle myotubes which were treated with insulin and samples were collected every 20 min for 8 hours. Pooled samples at every hour were analyzed by gene array approach to measure transcript levels. The patterns of transcript levels were analyzed based on a novel method that integrates selection, clustering, and functional annotation to find the main temporal patterns associated to functional groups of differentially expressed genes. 326 genes were found to be differentially expressed in response to in vitro insulin administration in skeletal muscle myotubes. Approximately 20% of the genes that were differentially expressed were identified as belonging to the insulin signaling pathway. Characteristic transcriptional temporal patterns include: (a) a slow and gradual decrease in gene expression, (b) a gradual increase in gene expression reaching a peak at about 5 hours and then reaching a plateau or an initial decrease and other different variable pattern of increase in gene expression over time. CONCLUSION/SIGNIFICANCE: The new method allows identifying characteristic dynamic responses to insulin stimulus, common to a number of genes and associated to the same functional group. The results demonstrate that insulin treatment elicited different clusters of gene transcript profile supporting a temporal regulation of gene expression by insulin in skeletal muscle cells.

Indexed as

Transcription, GeneticCluster AnalysisComputer SimulationGene Expression ProfilingGene Expression RegulationGlucoseHumansImage Processing, Computer-AssistedInsulinModels, StatisticalMuscle CellsMusclesMuscle, SkeletalMyoblastsOligonucleotide Array Sequence AnalysisPhosphorylationGlucoseInsulin

Identifiers

PMID22396763
PMCPMC3291562
OpenAlexW2020564997

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.