Linked Life Data

15038983

Source:http://linkedlifedata.com/resource/pubmed/id/15038983

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2004-3-24
pubmed:abstractText
A key issue for the study of tuberculosis is to understand why individuals infected with Mycobacterium tuberculosis (Mtb) experience different clinical outcomes. To better understand the dynamics of Mtb infection and immunity, we have previously developed a temporal mathematical model that qualitatively and quantitatively characterizes the cellular and cytokine control network during infection. In this work we extend that model to a two compartmental model to capture the important processes of cellular activation and priming that occur between the lung and the nearest draining lymph node. We are able to reproduce typical disease progression scenarios including primary infection, latency or clearance. Then we use the model to predict key processes determining these different disease trajectories (i.e. identify bifurcation parameters), suggesting directions for further basic science study and potential new treatment strategies.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0022-5193
pubmed:author
pubmed:issnType
Print
pubmed:day
21
pubmed:volume
227
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
463-86
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
The human immune response to Mycobacterium tuberculosis in lung and lymph node.
pubmed:affiliation
Department of Microbiology and Immunology, University of Michigan Medical School, 6730 Medical Science Building II, Ann Arbor, MI 48109-0620, USA. simeonem@umich.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't