Evidence map›Paper›PMID 27906902›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2016

Comparison of Transcriptome Between Type 2 Diabetes Mellitus and Impaired Fasting Glucose.

Ying Cui, Wen Chen, Jinfeng Chi, Lei Wang

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 30% 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, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Association Between Diabetes Mellitus and Outcomes of Patients with Sepsis: A Meta-Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2017
    Pooled it
  2. Article
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  4. Review
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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

4 authors at 2 institutions in 1 country.

Ying CuiDepartment of Endocrinology, Jinan Central Hospital Affiliated to Shandong University, Jinan, Shandong, China (mainland)
Wen ChenDepartment of Neurology, Jinan Central Hospital Affiliated to Shandong University, Jinan, Shandong, China (mainland)
Jinfeng ChiDepartment of Endocrinology, Jinan Central Hospital Affiliated to Shandong University, Jinan, Shandong, China (mainland)
Lei WangDepartment of Cardiology, Jinan Central Hospital Affiliated to Shandong University, Jinan, Shandong, China (mainland)
Jinan Central Hospital · CNShandong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND The aim of this study was to compare the transcriptome between impaired fasting glucose (IFG) and type 2 diabetes mellitus (T2DM), and further research their molecular mechanisms. MATERIAL AND METHODS The original microarray GSE21321, including miRNA and mRNA expression profiles, was downloaded from the GEO database. Data preprocessing was processed by limma package, and differentially expressed genes (DGs) and miRNA (DMs) were screened. Then, the regulatory relationships among miRNA, TF, and genes were screened and the regulatory network was constructed. Finally, DAVID was used for KEGG enrichment analysis. RESULTS There were 11 upregulated IFG-related DMs and five upregulated T2DM-related DMs. Three of the DMs overlapped. In addition, there were eight downregulated IFG-related DMs and two downregulated T2DM-related DMs. Only one downregulated DM overlapped. Similarly, there were 264 upregulated IFG-related DGs and 331 upregulated T2DM-related DGs; and 196 overlapping genes were obtained. In addition, there were 400 downregulated IFG-related DMs and 568 downregulated T2DM-related DMs. A total of 326 downregulated DMs were overlapped. The overlapped DGs were enriched in various pathways, including hematopoietic cell lineage, Fc gamma R-mediated phagocytosis, and MAPK signaling pathway. TAF1 (upregulated gene) and MAFK (downregulated gene) were hub nodes both in IFG- and T2DM-related miRNA-TF-gene regulatory network. In addition, miRNAs, including hsa-miR-29a, hsa-miR-192, and hsa-miR-144, were upregulated hub nodes in the two regulatory networks. CONCLUSIONS Genes including TAF1 and MAFK, and miRNAs including hsa-miR-29a, hsa-miR-192, and hsa-miR-144 might be potential target genes and important miRNAs for IFG and T2DM.

Indexed as

AdultAgedBlood GlucoseCase-Control StudiesDiabetes Mellitus, Type 2FastingGene Expression ProfilingGene Expression RegulationGlucoseHistone AcetyltransferasesHumansMafK Transcription FactorMaleMAP Kinase Signaling SystemMicroRNAsMiddle AgedBlood GlucoseGlucoseHistone AcetyltransferasesMAFK protein, humanMafK Transcription FactorMicroRNAsTATA-binding protein associated factor 250 kDaTATA-Binding Protein Associated FactorsTranscription Factor TFIID

Identifiers

PMID27906902
PMCPMC5147684
OpenAlexW2558418642

What Socratic 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 Socratic graph.