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Molecular network analysis of phosphotyrosine and lipid metabolism in hepatic PTP1b deletion mice

Overview of attention for article published in Integrative Biology, May 2013
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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6 X users

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46 Mendeley
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Title
Molecular network analysis of phosphotyrosine and lipid metabolism in hepatic PTP1b deletion mice
Published in
Integrative Biology, May 2013
DOI 10.1039/c3ib40013a
Pubmed ID
Authors

Emily R. Miraldi, Hadar Sharfi, Randall H. Friedline, Hannah Johnson, Tejia Zhang, Ken S. Lau, Hwi Jin Ko, Timothy G. Curran, Kevin M. Haigis, Michael B. Yaffe, Richard Bonneau, Douglas A. Lauffenburger, Barbara B. Kahn, Jason K. Kim, Benjamin G. Neel, Alan Saghatelian, Forest M. White

Abstract

Metabolic syndrome describes a set of obesity-related disorders that increase diabetes, cardiovascular, and mortality risk. Studies of liver-specific protein-tyrosine phosphatase 1b (PTP1b) deletion mice (L-PTP1b(-/-)) suggest that hepatic PTP1b inhibition would mitigate metabolic-syndrome through amelioration of hepatic insulin resistance, endoplasmic-reticulum stress, and whole-body lipid metabolism. However, the altered molecular-network states underlying these phenotypes are poorly understood. We used mass spectrometry to quantify protein-phosphotyrosine network changes in L-PTP1b(-/-) mouse livers relative to control mice on normal and high-fat diets. We applied a phosphosite-set-enrichment analysis to identify known and novel pathways exhibiting PTP1b- and diet-dependent phosphotyrosine regulation. Detection of a PTP1b-dependent, but functionally uncharacterized, set of phosphosites on lipid-metabolic proteins motivated global lipidomic analyses that revealed altered polyunsaturated-fatty-acid (PUFA) and triglyceride metabolism in L-PTP1b(-/-) mice. To connect phosphosites and lipid measurements in a unified model, we developed a multivariate-regression framework, which accounts for measurement noise and systematically missing proteomics data. This analysis resulted in quantitative models that predict roles for phosphoproteins involved in oxidation-reduction in altered PUFA and triglyceride metabolism.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hungary 1 2%
Unknown 45 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 26%
Student > Ph. D. Student 8 17%
Other 4 9%
Student > Bachelor 3 7%
Student > Postgraduate 3 7%
Other 10 22%
Unknown 6 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 43%
Biochemistry, Genetics and Molecular Biology 9 20%
Medicine and Dentistry 3 7%
Environmental Science 1 2%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Other 5 11%
Unknown 7 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 21 May 2013.
All research outputs
#7,301,979
of 25,374,647 outputs
Outputs from Integrative Biology
#199
of 692 outputs
Outputs of similar age
#59,398
of 208,744 outputs
Outputs of similar age from Integrative Biology
#6
of 16 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 692 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 71% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 208,744 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.