Linked Life Data

19018448

Source:http://linkedlifedata.com/resource/pubmed/id/19018448

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
2009-7-14
pubmed:abstractText
In this paper a hypothesis that some special signals ("key-signals" excito-amino acids, beta-amyloid peptides and alpha-synuclein) are not only involved in information handling by the neuronal circuits, but also trigger out substantial structural and/or functional changes in the Central Nervous System (CNS) is introduced. This forces the neuronal circuits to move from one stable state towards a new state, but in doing so these signals became potentially dangerous. Several mechanisms are put in action to protect neurons and glial cells from these potentially harmful signals. However, in agreement with the Red Queen Theory of Ageing (Agnati et al. in Acta Physiol Scand 145:301-309, 1992), it is proposed that during ageing these neuroprotective processes become less effective while, in the meantime, a shortage of brain plasticity occurs together with an increased need of plasticity for repairing the wear and tear of the CNS. The paper presents findings supporting the concept that such key-signals in instances such as ageing may favour neurodegenerative processes in an attempt of maximizing neuronal plasticity.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
1435-1463
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
116
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
953-74
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Common key-signals in learning and neurodegeneration: focus on excito-amino acids, beta-amyloid peptides and alpha-synuclein.
pubmed:affiliation
Department of BioMedical Sciences, University of Modena, Via Campi 287, 41100 Modena, Italy. luigiagnati@tin.it
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't