About: Machine learning approach identifies new pathways associated with demyelination in a viral model of multiple sclerosis

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About: Machine learning approach identifies new pathways associated with demyelination in a viral model of multiple sclerosis Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Machine learning approach identifies new pathways associated with demyelination in a viral model of multiple sclerosis
Creator	Ulrich, Reiner Baumgärtner, Wolfgang Deschl, Ulrich Kalkuhl, Arno
Source	PMC
abstract	Theiler’s murine encephalomyelitis is an experimentally virus-induced inflammatory demyelinating disease of the spinal cord, displaying clinical and pathological similarities to chronic progressive multiple sclerosis. The aim of this study was to identify pathways associated with chronic demyelination using an assumption-free combined microarray and immunohistology approach. Movement control as determined by rotarod assay significantly worsened in Theiler’s murine encephalomyelitis -virus-infected SJL/J mice from 42 to 196 days after infection (dpi). In the spinal cords, inflammatory changes were detected 14 to 196 dpi, and demyelination progressively increased from 42 to 196 dpi. Microarray analysis revealed 1001 differentially expressed genes over the study period. The dominating changes as revealed by k-means and functional annotation clustering included up-regulations related to intrathecal antibody production and antigen processing and presentation via major histocompatibility class II molecules. A random forest machine learning algorithm revealed that down-regulated lipid and cholesterol biosynthesis, differentially expressed neurite morphogenesis and up-regulated toll-like receptor-4-induced pathways were intimately associated with demyelination as measured by immunohistology. Conclusively, although transcriptional changes were dominated by the adaptive immune response, the main pathways associated with demyelination included up-regulation of toll-like receptor 4 and down-regulation of cholesterol biosynthesis. Cholesterol biosynthesis is a rate limiting step of myelination and its down-regulation is suggested to be involved in chronic demyelination by an inhibition of remyelination.
has issue date	2009-01-14(xsd:dateTime)
bibo:doi	10.1111/j.1582-4934.2008.00646.x
bibo:pmid	19183246
has license	no-cc
sha1sum (hex)	7051169cee12dbca19764986a24af534e60c3ab4
schema:url	https://doi.org/10.1111/j.1582-4934.2008.00646.x
resource representing a document's title	Machine learning approach identifies new pathways associated with demyelination in a viral model of multiple sclerosis
has PubMed Central identifier	PMC3837619
has PubMed identifier	19183246
schema:publication	J Cell Mol Med
resource representing a document's body	covid:7051169cee12dbca19764986a24af534e60c3ab4#body_text
is schema:about of	named entity 'IMMUNOHISTOLOGY' named entity 'VIRAL' named entity 'frequently' named entity 'production' named entity 'missing' named entity 'human' named entity 'multiple sclerosis' named entity 'machine learning' named entity 'spinal cord' named entity 'AMOUNTS' named entity 'INDUCTION' named entity 'AXONAL INJURY' named entity 'MULTIPLE SCLEROSIS' named entity 'RELAPSES' named entity 'YEARS' named entity 'DISEASE' named entity 'COMPLEX' named entity 'INFLAMMATORY PROCESS' named entity 'DETERIORATION' named entity 'MILLION' named entity 'THESE' named entity 'LATER' named entity '2.5' named entity 'RIGHT' named entity 'ASSOCIATED WITH' named entity 'REVEALED' named entity 'REMYELINATION' named entity 'RATE' named entity 'INFLAMED' named entity 'MASSIVE' named entity 'TRAPPED' named entity 'RESPONSIBLE' named entity 'HUMAN DISEASE' named entity 'SPINAL CORD' named entity 'PATHOLOGICAL' named entity 'DIFFUSE AXONAL INJURY' named entity 'PROGRESSIVE' named entity 'SEVERITY' named entity 'CORTICAL' named entity 'ANTIINFLAMMATORY' named entity 'MAJOR' named entity 'MAJORITY' named entity 'RELAPSING' named entity 'VARYING' named entity 'MISSING' named entity 'ASSOCIATED WITH' named entity 'TOLL-LIKE RECEPTOR 4' named entity 'RANDOM FOREST' named entity 'MURINE ENCEPHALOMYELITIS' named entity 'NEW' named entity 'MACHINE LEARNING ALGORITHM' named entity 'LESION' named entity 'CLINICAL' named entity 'PROGRESSIVE MS' named entity '80%' named entity 'KEYWORDS' named entity 'MICROARRAY' named entity '27S' named entity 'CHOLESTEROL' named entity 'MULTIPLE SCLEROSIS' named entity 'COMPARISON' named entity 'BASED' named entity 'CENTRAL NERVOUS SYSTEM' named entity 'PHASE' named entity 'LIKELY' named entity 'PATIENTS' named entity 'TO PREVENT' named entity 'REFLECT' named entity 'IMMUNOMODULATORY' named entity 'MODEL OF' named entity 'APPROACH' named entity 'FREQUENTLY' named entity 'MECHANISMS' named entity 'FINDINGS' named entity 'AVAILABLE' named entity 'INTRATHECAL' named entity 'AFFECTING' named entity 'DIFFUSE'

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