Evidence map›Paper›PMID 26962295›Full record

ArticleJournal of proteomics & bioinformatics

A Quantitative Proteomic Analysis of Urine from Gamma-Irradiated Non-Human Primates.

Stephanie D Byrum, Marie S Burdine, Lisa Orr, Linley Moreland, Samuel G Mackintosh, Simon Authier, Mylene Pouliot, Martin Hauer-Jensen, Alan J Tackett

Abstract read
In one paragraph

Article in Journal of proteomics & bioinformatics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. 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

9 authors.

Stephanie D ByrumDepartment of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, 4301 West Markham Street, Little Rock, Arkansas 72205, USA.
Marie S BurdineDepartment of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, 4301 West Markham Street, Little Rock, Arkansas 72205, USA.
Lisa OrrDepartment of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, 4301 West Markham Street, Little Rock, Arkansas 72205, USA.
Linley MorelandDepartment of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, 4301 West Markham Street, Little Rock, Arkansas 72205, USA.
Samuel G MackintoshDepartment of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, 4301 West Markham Street, Little Rock, Arkansas 72205, USA.
Simon AuthierCIToxLAB, Laval, Quebec, Canada.
Mylene PouliotCIToxLAB, Laval, Quebec, Canada.
Martin Hauer-JensenDivision of Radiation Health, University of Arkansas for Medical Sciences, 4301 West Markham Street, Little Rock, Arkansas 72205, USA.
Alan J TackettDepartment of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, 4301 West Markham Street, Little Rock, Arkansas 72205, USA.

Funding

Understanding Hesitant AdoptersP20GM103429 · NIGMS · UNIV OF ARKANSAS FOR MED SCIS · PI Lawrence E Cornett, JERRY WARE · 2012 to 2026
$60.9M
Study of the Cell-specific Inflammasome Responses During Defense Against Gram-negative BacteriaP20GM103625 · NIGMS · UNIV OF ARKANSAS FOR MED SCIS · PI SMELTZER, MARK S · 2012 to 2021
$21.5M
The Role o f Tetrahydrobiopterin (BH4) Bioavailability in Radiation-induced Skin InjuryP20GM109005 · NIGMS · UNIV OF ARKANSAS FOR MED SCIS · PI BOERMA, MARJAN · 2015 to 2024
$21.1M
Arkansas Center for Clinical and Translational ResearchUL1TR000039 · NCATS · UNIV OF ARKANSAS FOR MED SCIS · PI BECK, CORNELIA MARIE, JAMES, LAURA P · 2012 to 2014
$10.0M
Using ChAP-MS to Study Macromolecular Chromatin Composition during TranscriptionR01GM106024 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI TACKETT, ALAN, TAVERNA, SEAN D. · 2013 to 2016
$1.2M
Identifying the epigenetic regulation of arsenic exposure - Revision 2R21ES025268 · NIEHS · UNIV OF ARKANSAS FOR MED SCIS · PI TACKETT, ALAN · 2015 to 2017
$487k
Development of MassSQUIRM to Quantitatively Measure Lysine MethylationR33CA173264 · NCI · UNIV OF ARKANSAS FOR MED SCIS · PI TACKETT, ALAN · 2013 to 2015
$430k
NCATS NIH HHS UL1 TR000039NCI NIH HHS R33 CA173264NIEHS NIH HHS R21 ES025268NIGMS NIH HHS P20 GM103429NIGMS NIH HHS P20 GM103625NIGMS NIH HHS P20 GM109005NIGMS NIH HHS R01 GM106024
6 · The paper itself

Abstract

The molecular effects of total body gamma-irradiation exposure are of critical importance as large populations of people could be exposed either by terrorists, nuclear blast, or medical therapy. In this study, we aimed to identify changes in the urine proteome using a non-human primate model system, Rhesus macaque, in order to characterize effects of acute radiation syndrome following whole body irradiation (Co-60) at 6.7 Gy and 7.4 Gy with a twelve day observation period. The urine proteome is potentially a valuable and non-invasive diagnostic for radiation exposure. Using high-resolution mass spectrometry, we identified 2346 proteins in the urine proteome. We show proteins involved in disease, cell adhesion, and metabolic pathway were significantly changed upon exposure to differing levels and durations of radiation exposure. Cell damage increased at a faster rate at 7.4 Gy compared with 6.7 Gy exposures. We report sets of proteins that are putative biomarkers of time- and dose-dependent radiation exposure. The proteomic study presented here is a comprehensive analysis of the urine proteome following radiation exposure.

Indexed as

Acute radiation syndromeBiomarkersQuantitative proteomicRhesus monkeyUrine proteome

Identifiers

PMID26962295
PMCPMC4780756

What OpenQuestion holds

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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.