Back to Search
Start Over
Networks of neuroblastoma cells on porous silicon substrates reveal a small world topology.
- Source :
-
Integrative biology : quantitative biosciences from nano to macro [Integr Biol (Camb)] 2015 Feb; Vol. 7 (2), pp. 184-97. - Publication Year :
- 2015
-
Abstract
- The human brain is a tightly interweaving network of neural cells where the complexity of the network is given by the large number of its constituents and its architecture. The topological structure of neurons in the brain translates into its increased computational capabilities, low energy consumption, and nondeterministic functions, which differentiate human behavior from artificial computational schemes. In this manuscript, we fabricated porous silicon chips with a small pore size ranging from 8 to 75 nm and large fractal dimensions up to Df ∼ 2.8. In culturing neuroblastoma N2A cells on the described substrates, we found that those cells adhere more firmly to and proliferate on the porous surfaces compared to the conventional nominally flat silicon substrates, which were used as controls. More importantly, we observed that N2A cells on the porous substrates create highly clustered, small world topology patterns. We conjecture that neurons with a similar architecture may elaborate information more efficiently than in random or regular grids. Moreover, we hypothesize that systems of neurons on nano-scale geometry evolve in time to form networks in which the propagation of information is maximized.
- Subjects :
- Cell Adhesion
Cell Line, Tumor
Cell Proliferation
Humans
Microscopy, Atomic Force
Microscopy, Electron, Scanning
Nanostructures chemistry
Nanostructures ultrastructure
Nanotechnology
Nerve Net physiology
Neuroblastoma pathology
Neurons cytology
Neurons physiology
Porosity
Silicon
Surface Properties
Models, Neurological
Nerve Net cytology
Subjects
Details
- Language :
- English
- ISSN :
- 1757-9708
- Volume :
- 7
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Integrative biology : quantitative biosciences from nano to macro
- Publication Type :
- Academic Journal
- Accession number :
- 25515929
- Full Text :
- https://doi.org/10.1039/c4ib00216d