| 1. |
- Durso, M., et al.
(författare)
-
Biomimetic graphene for enhanced interaction with the external membrane of astrocytes
- 2018
-
Ingår i: Journal of Materials Chemistry B. - : Royal Society of Chemistry (RSC). - 2050-7518 .- 2050-750X. ; 6:33, s. 5335-5342
-
Tidskriftsartikel (refereegranskat)abstract
- Graphene and graphene substrates display huge potential as material interfaces for devices and biomedical tools targeting the modulation or recovery of brain functionality. However, to be considered reliable neural interfaces, graphene-derived substrates should properly interact with astrocytes, favoring their growth and avoiding adverse gliotic reactions. Indeed, astrocytes are the most abundant cells in the human brain and they have a crucial physiological role to maintain its homeostasis and modulate synaptic transmission. In this work, we describe a new strategy based on the chemical modification of graphene oxide (GO) with a synthetic phospholipid (PL) to improve interaction of GO with brain astroglial cells. The PL moieties were grafted on GO sheets through polymeric brushes obtained by atom-transfer radical-polymerization (ATRP) between acryloyl-modified PL and GO nanosheets modified with a bromide initiator. The adhesion of primary rat cortical astrocytes on GO-PL substrates increased by about three times with respect to that on glass substrates coated with standard adhesion agents (i.e. poly-d-lysine, PDL) as well as with respect to that on non-functionalized GO. Moreover, we show that astrocytes seeded on GO-PL did not display significant gliotic reactivity, indicating that the material interface did not cause a detrimental inflammatory reaction when interacting with astroglial cells. Our results indicate that the reported biomimetic approach could be applied to neural prosthesis to improve cell colonization and avoid glial scar formation in brain implants. Additionally, improved adhesion could be extremely relevant in devices targeting neural cell sensing/modulation of physiological activity.
|
|
| 2. |
|
|
| 3. |
|
|
| 4. |
|
|
| 5. |
|
|
| 6. |
|
|
| 7. |
|
|
| 8. |
|
|
| 9. |
|
|
| 10. |
- Benfenati, E., et al.
(författare)
-
A large comparison of integrated SAR/QSAR models of the Ames test for mutagenicity($)
- 2018
-
Ingår i: SAR and QSAR in environmental research (Print). - : Taylor & Francis. - 1062-936X .- 1029-046X. ; 29:8, s. 591-611
-
Tidskriftsartikel (refereegranskat)abstract
- Results from the Ames test are the first outcome considered to assess the possible mutagenicity of substances. Many QSAR models and structural alerts are available to predict this endpoint. From a regulatory point of view, the recommendation from international authorities is to consider the predictions of more than one model and to combine results in order to develop conclusions about the mutagenicity risk posed by chemicals. However, the results of those models are often conflicting, and the existing inconsistency in the predictions requires intelligent strategies to integrate them. In our study, we evaluated different strategies for combining results of models for Ames mutagenicity, starting from a set of 10 diverse individual models, each built on a dataset of around 6000 compounds. The novelty of our study is that we collected a much larger set of about 18,000 compounds and used the new data to build a family of integrated models. These integrations used probabilistic approaches, decision theory, machine learning, and voting strategies in the integration scheme. Results are discussed considering balanced or conservative perspectives, regarding the possible uses for different purposes, including screening of large collection of substances for prioritization.
|
|
