Open AccessNoise in multiple sclerosis: unwanted and necessary
Author(s) -
Bordi Isabella,
Ricigliano Vito A. G.,
Umeton Renato,
Ristori Giovanni,
Grassi Francesca,
Crisanti Andrea,
Sutera Alfonso,
Salvetti Marco
Publication year - 2014
Publication title -
annals of clinical and translational neurology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.824
H-Index - 42
ISSN - 2328-9503
DOI - 10.1002/acn3.72
Subject(s) - nondeterministic algorithm , multiple sclerosis , disease , noise (video) , scale (ratio) , computer science , neuroscience , computational biology , medicine , data science , bioinformatics , cognitive science , artificial intelligence , biology , theoretical computer science , psychology , immunology , physics , pathology , quantum mechanics , image (mathematics)
As our knowledge about the etiology of multiple sclerosis ( MS ) increases, deterministic paradigms appear insufficient to describe the pathogenesis of the disease, and the impression is that stochastic phenomena (i.e. random events not necessarily resulting in disease in all individuals) may contribute to the development of MS . However, sources and mechanisms of stochastic behavior have not been investigated and there is no proposed framework to incorporate nondeterministic processes into disease biology. In this report, we will first describe analogies between physics of nonlinear systems and cell biology, showing how small‐scale random perturbations can impact on large‐scale phenomena, including cell function. We will then review growing and solid evidence showing that stochastic gene expression (or gene expression “noise”) can be a driver of phenotypic variation. Moreover, we will describe new methods that open unprecedented opportunities for the study of such phenomena in patients and the impact of this information on our understanding of MS course and therapy.