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A mathematical model of the dynamics of prion aggregates with chaperone-mediated fragmentation

Overview of attention for article published in Journal of Mathematical Biology, August 2015
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Title
A mathematical model of the dynamics of prion aggregates with chaperone-mediated fragmentation
Published in
Journal of Mathematical Biology, August 2015
DOI 10.1007/s00285-015-0921-0
Pubmed ID
Authors

Jason K. Davis, Suzanne S. Sindi

Abstract

Prions are proteins most commonly associated with fatal neurodegenerative diseases in mammals but are also responsible for a number of harmless heritable phenotypes in yeast. These states arise when a misfolded form of a protein appears and, rather than be removed by cellular quality control mechanisms, persists. The misfolded prion protein forms aggregates and is capable of converting normally folded protein to the misfolded state through direct interaction between the two forms. The dominant mathematical model for prion aggregate dynamics has been the nucleated polymerization model (NPM) which considers the dynamics of only the normal protein and the aggregates. However, for yeast prions the molecular chaperone Hsp104 is essential for prion propagation. Further, although mammals do not express Hsp104, experimental assays have shown Hsp104 also interacts with mammalian prion aggregates. In this study, we generalize the NPM to account for molecular chaperones and develop what we call the enzyme-limited nucleated polymerization model (ELNPM). We discuss existence, uniqueness and stability of solutions to our model and demonstrate that the NPM represents a quasi-steady-state reduction of our model. We validate the ELNPM by demonstrating agreement with experimental results on the yeast prion [Formula: see text] PSI [Formula: see text] that could not be supported by the NPM. Finally, we demonstrate that, in contrast to the NPM, the ELNPM permits the coexistence of multiple prion strains.

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The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Chile 1 2%
Russia 1 2%
Unknown 44 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 27%
Student > Bachelor 10 21%
Researcher 10 21%
Student > Master 7 15%
Professor 2 4%
Other 3 6%
Unknown 3 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 31%
Biochemistry, Genetics and Molecular Biology 14 29%
Mathematics 5 10%
Neuroscience 2 4%
Engineering 2 4%
Other 6 13%
Unknown 4 8%
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 25 August 2015.
All research outputs
#18,423,683
of 22,824,164 outputs
Outputs from Journal of Mathematical Biology
#445
of 655 outputs
Outputs of similar age
#192,069
of 266,223 outputs
Outputs of similar age from Journal of Mathematical Biology
#5
of 7 outputs
Altmetric has tracked 22,824,164 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 655 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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