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Prenatal Factors Contribute to the Emergence of Kwashiorkor or Marasmus in Severe Undernutrition: Evidence for the Predictive Adaptation Model

Overview of attention for article published in PLOS ONE, April 2012
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Title
Prenatal Factors Contribute to the Emergence of Kwashiorkor or Marasmus in Severe Undernutrition: Evidence for the Predictive Adaptation Model
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0035907
Pubmed ID
Authors

Terrence E. Forrester, Asha V. Badaloo, Michael S. Boyne, Clive Osmond, Debbie Thompson, Curtis Green, Carolyn Taylor-Bryan, Alan Barnett, Suzanne Soares-Wynter, Mark A. Hanson, Alan S. Beedle, Peter D. Gluckman

Abstract

Severe acute malnutrition in childhood manifests as oedematous (kwashiorkor, marasmic kwashiorkor) and non-oedematous (marasmus) syndromes with very different prognoses. Kwashiorkor differs from marasmus in the patterns of protein, amino acid and lipid metabolism when patients are acutely ill as well as after rehabilitation to ideal weight for height. Metabolic patterns among marasmic patients define them as metabolically thrifty, while kwashiorkor patients function as metabolically profligate. Such differences might underlie syndromic presentation and prognosis. However, no fundamental explanation exists for these differences in metabolism, nor clinical pictures, given similar exposures to undernutrition. We hypothesized that different developmental trajectories underlie these clinical-metabolic phenotypes: if so this would be strong evidence in support of predictive adaptation model of developmental plasticity.

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Mendeley readers

The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 <1%
Canada 1 <1%
Unknown 118 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 22%
Student > Bachelor 15 13%
Researcher 13 11%
Other 10 8%
Student > Ph. D. Student 10 8%
Other 18 15%
Unknown 28 23%
Readers by discipline Count As %
Medicine and Dentistry 40 33%
Agricultural and Biological Sciences 14 12%
Nursing and Health Professions 11 9%
Social Sciences 6 5%
Biochemistry, Genetics and Molecular Biology 5 4%
Other 15 13%
Unknown 29 24%