Title :
Maximum likelihood factor analysis in malaria cytokines analysis and modelling
Author :
Oliveras-Vergés, Albert
Author_Institution :
Signal Theor. & Commun. Dep., Tech. Univ. of Catalonia - UPC, Barcelona, Spain
Abstract :
A maximum likelihood factor analysis (MLFA) of the dynamics of the human immune system in malaria, based on the observation of a few cytokine in plasma, suggests that an increased overproduction of cytokines: IL-12, IL-6, IFN-gamma, IL-2, and IL-5, over the cytokines: TGF-beta, TNF-alpha, IL-10 and IL-1beta has protective effects against severe malaria and cerebral malaria. According to a simplified model of the human adaptive immunity and the MLFA results, basal levels of cytokine IL-6 may play a key role in the favorable resolution of a malaria infection.
Keywords :
diseases; maximum likelihood estimation; physiological models; proteins; MLFA; cerebral malaria; cytokine IL-6; human adaptive immunity model; human immune system; malaria cytokine modelling; malaria infection; maximum likelihood factor analysis; Covariance matrix; Diseases; Humans; Immune system; Maximum likelihood estimation; Plasma measurements; Protection; Samarium; Signal analysis; Vaccines;
Conference_Titel :
Genomic Signal Processing and Statistics, 2009. GENSIPS 2009. IEEE International Workshop on
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-4761-9
Electronic_ISBN :
978-1-4244-4762-6
DOI :
10.1109/GENSIPS.2009.5174336
