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iTRAQ-Based Quantitative Proteomic Analysis of the Potentiated and Dormant Antler Stem Cells

Overview of attention for article published in International Journal of Molecular Sciences, October 2016
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Article details
Title
iTRAQ-Based Quantitative Proteomic Analysis of the Potentiated and Dormant Antler Stem Cells
Published in
International Journal of Molecular Sciences, October 2016
DOI 10.3390/ijms17111778
Pubmed ID
Authors
Abstract

As the only known organ that can completely regenerate in mammals, deer antler is of real significance in the field of regenerative medicine. Recent studies have shown that the regenerative capacity of the antlers comes from the pedicle periosteum and the cells resident in the periosteum possess the attributes of stem cells. Currently, the molecular mechanism of antler regeneration remains unclear. In the present study, we compared the potentiated and dormant antler stem cells using isobaric tags for the relative and absolute quantification (iTRAQ) labeling of the peptides, coupled with two-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS) to compare the proteome profiles. Proteins were identified by searching against the NCBI nr database and our own Cervine transcriptome database, and bioinformatics analysis was conducted to identify the differentially expressed proteins. Based on this searching strategy, we identified 169 differentially expressed proteins in total, consisting of 70 up- and 99 down-regulated in the potentiated vs. dormant antler stem cells. Reliability of the iTRAQ was confirmed via quantitative real-time polymerase chain reaction (qRT-PCR) to measure the expression of selected genes. We identified transduction pathways through the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, such as HIF-1 and PI3K-AKT signaling pathways that play important roles in regulating the regeneration of antlers. In summary, the initiation stage of antler regeneration, a process from dormant to potentiated states in antler stem cells, is regulated by multiple proteins and complicated signal networks.

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The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 4 27%
Researcher 2 13%
Other 1 7%
Student > Master 1 7%
Professor > Associate Professor 1 7%
Other 0 0%
Unknown 6 40%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 27%
Agricultural and Biological Sciences 4 27%
Medicine and Dentistry 1 7%
Unknown 6 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 March 2017.
All research outputs
#22,694,404
of 27,782,313 outputs
Outputs from International Journal of Molecular Sciences
#35,311
of 48,351 outputs
Outputs of similar age
#242,783
of 314,764 outputs
Outputs of similar age from International Journal of Molecular Sciences
#250
of 377 outputs
Altmetric has tracked 27,782,313 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 48,351 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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