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Arterial Stiffening Provides Sufficient Explanation for Primary Hypertension

Overview of attention for article published in PLoS Computational Biology, May 2014
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Title
Arterial Stiffening Provides Sufficient Explanation for Primary Hypertension
Published in
PLoS Computational Biology, May 2014
DOI 10.1371/journal.pcbi.1003634
Pubmed ID
Authors

Klas H. Pettersen, Scott M. Bugenhagen, Javaid Nauman, Daniel A. Beard, Stig W. Omholt

Abstract

Hypertension is one of the most common age-related chronic disorders, and by predisposing individuals for heart failure, stroke, and kidney disease, it is a major source of morbidity and mortality. Its etiology remains enigmatic despite intense research efforts over many decades. By use of empirically well-constrained computer models describing the coupled function of the baroreceptor reflex and mechanics of the circulatory system, we demonstrate quantitatively that arterial stiffening seems sufficient to explain age-related emergence of hypertension. Specifically, the empirically observed chronic changes in pulse pressure with age and the impaired capacity of hypertensive individuals to regulate short-term changes in blood pressure arise as emergent properties of the integrated system. The results are consistent with available experimental data from chemical and surgical manipulation of the cardio-vascular system. In contrast to widely held opinions, the results suggest that primary hypertension can be attributed to a mechanogenic etiology without challenging current conceptions of renal and sympathetic nervous system function.

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Geographical breakdown

Country Count As %
United Kingdom 2 3%
Spain 1 1%
United States 1 1%
Unknown 69 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 21%
Student > Ph. D. Student 13 18%
Student > Master 12 16%
Other 7 10%
Student > Doctoral Student 6 8%
Other 8 11%
Unknown 12 16%
Readers by discipline Count As %
Medicine and Dentistry 14 19%
Agricultural and Biological Sciences 14 19%
Engineering 11 15%
Biochemistry, Genetics and Molecular Biology 7 10%
Computer Science 6 8%
Other 9 12%
Unknown 12 16%