Search results for " in vitro models"
showing 3 items of 3 documents
Engineering approaches in siRNA delivery.
2017
siRNAs are very potent drug molecules, able to silence genes involved in pathologies development. siRNAs have virtually an unlimited therapeutic potential, particularly for the treatment of inflammatory diseases. However, their use in clinical practice is limited because of their unfavorable properties to interact and not to degrade in physiological environments. In particular they are large macromolecules, negatively charged, which undergo rapid degradation by plasmatic enzymes, are subject to fast renal clearance/hepatic sequestration, and can hardly cross cellular membranes. These aspects seriously impair siRNAs as therapeutics. As in all the other fields of science, siRNAs management ca…
Neuronal and BBB damage induced by sera from patients with secondary progressive multiple sclerosis.
2009
An important component of the pathogenic process of multiple sclerosis (MS) is the blood-brain barrier (BBB) damage. We recently set an in vitro model of BBB, based on a three-cell-type co-culture system, in which rat neurons and astrocytes synergistically induce brain capillary endothelial cells to form a monolayer with permeability properties resembling those of the physiological BBB. Herein we report that the serum from patients with secondary progressive multiple sclerosis (SPMS) has a damaging effect on isolated neurons. This finding suggests that neuronal damaging in MS could be a primary event and not only secondary to myelin damage, as generally assumed. SPMS serum affects the perme…
Testing chemical carcinogenicity by using a transcriptomics HepaRG-based model?
2014
The EU FP6 project carcinoGENOMICS explored the combination of toxicogenomics and in vitro cell culture models for identifying organotypical genotoxic- and non-genotoxic carcinogen- specific gene signatures. Here the performance of its gene classifier, derived from exposure of metabolically competent human HepaRG cells to prototypical non-carcinogens (10 compounds) and hepatocarcinogens (20 compounds), is reported. Analysis of the data at the gene and the pathway level by using independent biostatistical approaches showed a distinct separation of genotoxic from non-genotoxic hepatocarcinogens and non-carcinogens (up to 88 % correct prediction). The most characteristic pathway responding to …