Linked Life Data

15817855

Source:http://linkedlifedata.com/resource/pubmed/id/15817855

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2005-4-8
pubmed:abstractText
We previously derived a whole-body resting energy expenditure (REE) prediction model by using organ and tissue mass measured by magnetic resonance imaging combined with assumed stable, specific resting metabolic rates of individual organs and tissues. Although the model predicted REE well in young persons, it overpredicted REE by approximately 11% in elderly adults. This overprediction may occur because of a decline in the fraction of organs and tissues as cell mass with aging.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
AIM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0002-9165
pubmed:author
pubmed:issnType
Print
pubmed:volume
81
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
799-806
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
A cellular-level approach to predicting resting energy expenditure across the adult years.
pubmed:affiliation
Obesity Research Center, St Luke's-Roosevelt Hospital, Columbia University College of Physicians and Surgeons, New York, USA. zw28@columbia.edu
pubmed:publicationType
Journal Article, Clinical Trial, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't