Abstract
To assess the effect of surface topography on cell attachment, central nervous system (astroglial cells) cells were grown on surfaces patterned with two different types of texture. Reactive ion etching (RIE) was used to induce nanometer-scale roughness in silicon wafers. In a subsequent wet etch, photo-patterned resist protected selected areas of the surface, resulting in a pattern of modified and unmodified texture. Scanning electron microscopy (SEM) showed that the RIE-roughened "primary" surface consists of randomly positioned columnar structures (diameter ≈50 nm, height ≈250 nm). The wet-etched "secondary" surfaces had shorter and more sparsely distributed projections, controlled to a degree by wet etch duration. Confocal microscopy and SEM demonstrated that transformed astroglial (LRM55) cells preferred secondary surfaces. The morphology of cells on secondary surfaces depended on wet etch duration. with brief wet etch, cells hade stellate or mounded morphology and were not closely adherent to the surface. With long wet etch, cells had an epithelial-like morphology and were closely adherent to substrates. Under all conditions, cells discriminated between primary and secondary surfaces. In contrast to LRM55 cells, astrocytes in primary cell culture preferred primary surfaces. Thus changes in surface topography produce cell-specific selectivity and change cell attachment characteristics.
Original language | English (US) |
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Pages (from-to) | 41-52 |
Number of pages | 12 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 2978 |
DOIs | |
State | Published - 1997 |
Event | Micro- and Nanofabricated Electro-Optical Mechanical Systems for Biomedical and Environmental Applications - San Jose, CA, United States Duration: Feb 10 1997 → Feb 10 1997 |
Keywords
- Astrocytes
- Cell attachment
- Reactive ion etching
- Silicon
- Surface topography
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering