Evidence map›Paper›PMID 29121074›Full record

ArticlePloS one2017

Proteome profiling in the aorta and kidney of type 1 diabetic rats.

Moustafa Al Hariri, Mohamad Elmedawar, Rui Zhu, Miran A Jaffa, Jingfu Zhao, Parvin Mirzaei, Adnan Ahmed, Firas Kobeissy, Fuad N Ziyadeh, Yehia Mechref and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

12 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Proteomic Study of Low-Birth-Weight Nephropathy in Rats.International journal of molecular sciences · 2021
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
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

11 authors at 2 institutions in 2 countries.

Moustafa Al HaririDepartment of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of Beirut, Beirut, Lebanon.
Mohamad ElmedawarDepartment of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of Beirut, Beirut, Lebanon.
Rui ZhuDepartment of Chemistry and Biochemistry, Texas Tech University, Memorial Circle & Boston, Lubbock, Texas, United States of America.
Miran A JaffaEpidemiology and Population Health Department, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.
Jingfu ZhaoDepartment of Chemistry and Biochemistry, Texas Tech University, Memorial Circle & Boston, Lubbock, Texas, United States of America.
Parvin MirzaeiDepartment of Chemistry and Biochemistry, Texas Tech University, Memorial Circle & Boston, Lubbock, Texas, United States of America.
Adnan AhmedCenter for Biotechnology & Genomics, Texas Tech University, Canton & Main, Experimental Sciences building, Lubbock, Texas, United States of America.
Firas KobeissyDepartment of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of Beirut, Beirut, Lebanon.
Fuad N ZiyadehDepartment of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of Beirut, Beirut, Lebanon.
Yehia MechrefDepartment of Chemistry and Biochemistry, Texas Tech University, Memorial Circle & Boston, Lubbock, Texas, United States of America.
Ayad A JaffaDepartment of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of Beirut, Beirut, Lebanon.ORCID http://orcid.org/0000-0001-9204-2723
American University of Beirut · LBTexas Tech University · US

Funding

Sensitive and Quantitative MS-bases Glycomic Mapping PlatformR01GM112490 · NIGMS · TEXAS TECH UNIVERSITY · PI MECHREF, YEHIA · 2014 to 2024
$3.2M
NIGMS NIH HHS R01 GM112490
6 · The paper itself

Abstract

Diabetes is associated with a number of metabolic and cardiovascular risk factors that contribute to a high rate of microvascular and macrovascular complications. The risk factors and mechanisms that contribute to the development of micro- and macrovascular disease in diabetes are not fully explained. In this study, we employed mass spectrometric analysis using tandem LC-MS/MS to generate a proteomic profile of protein abundance and post-translational modifications (PTM) in the aorta and kidney of diabetic rats. In addition, systems biology analyses were employed to identify key protein markers that can provide insights into molecular pathways and processes that are differentially regulated in the aorta and kidney of type 1 diabetic rats. Our results indicated that 188 (111 downregulated and 77 upregulated) proteins were significantly identified in the aorta of diabetic rats compared to normal controls. A total of 223 (109 downregulated and 114 upregulated) proteins were significantly identified in the kidney of diabetic rats compared to normal controls. When the protein profiles from the kidney and aorta of diabetic and control rats were analyzed by principal component analysis, a distinct separation of the groups was observed. In addition, diabetes resulted in a significant increase in PTM (oxidation, phosphorylation, and acetylation) of proteins in the kidney and aorta and this effect was partially reversed by insulin treatment. Ingenuity pathway analysis performed on the list of differentially expressed proteins depicted mitochondrial dysfunction, oxidative phosphorylation and acute phase response signaling to be among the altered canonical pathways by diabetes in both tissues. The findings of the present study provide a global proteomics view of markers that highlight the mechanisms and putative processes that modulate renal and vascular injury in diabetes.

Indexed as

ProteomicsAnimalsAortaBlood GlucoseBody WeightChromatography, LiquidDiabetes Mellitus, Type 1Gene Expression Regulation, EnzymologicInsulinKidneyKininogensOxidative StressPeptidyl-Dipeptidase AProtein Processing, Post-TranslationalRatsTandem Mass SpectrometryBlood GlucoseInsulinKininogensPeptidyl-Dipeptidase A

Identifiers

PMID29121074
PMCPMC5679573
OpenAlexW2768052609

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.