Cerebral cortical astrocyte responses to polyamide nanofibrillar scaffolds versus poly-L-lysine (PLL)-functionalized planar glass, unfunctionalized planar Aclar coverslips, and PLL-functionalized planar Aclar surfaces were investigated by atomic force microscopy and immunocytochemistry. The physical properties of the cell culture environments were evaluated using contact angle and surface roughness measurements and compared. Astrocyte morphological responses, including filopodia, lamellipodia, and stress fiber formation, and stellation were imaged using atomic force microscopy and phalloidin staining for F-actin. Activation of the corresponding Rho GTPase regulators was investigated using immunolabeling with Cdc42, Rac1, and RhoA. Astrocytes cultured on the nanofibrillar scaffolds showed a unique response that included stellation, cell-cell interactions by stellate processes, and evidence of depression of RhoA. The results support the hypothesis that the extracellular environment can trigger preferential activation of members of the Rho GTPase family, with demonstrable morphological consequences for cerebral cortical astrocytes.
Nanofibrillar scaffold properties were shown to reduce immunoreactivity responses while poly-L-lysine-functionalized Aclar® (Ted Pella Inc., CA, USA) properties were shown to induce responses reminiscent of glial scar formation. The comparison study indicated that directive cues may differ in wound-healing versus quiescent situations.
The wireless communication system was investigated by novel methods, which produce an optimized data link, especially the software-based methods. Software-Defined Radio (SDR) is a common method for developing and implementing wireless communication protocols. In this paper, SDR and artificial intelligence (AI) are used to design a self-management communication system with variable node locations. Three affected parameters for the wireless signal are considered: channel frequency, bandwidth, and modulation type. On one hand, SDR collects and analyzes the signal components while on the other hand, AI processes the situation in real-time sequence after detecting unwanted data during the monitoring stage. The decision was integrated into the system by AI with respect to the instantaneous data read then passed to the communication nodes to take its correct location. The connectivity ratio and coverage area are optimized nearly double by the proposed method, which means the variable node location, according to the peak time, increases the attached subscriber by a while ratio
A new cell shape index is defined for use with atomic force microscopy height images of cell cultures. The new cell shape index reveals quantitative cell spreading information not included in a conventional cell shape index. A supervised learning-based cell segmentation algorithm was implemented by texture feature extraction and a multi-layer neural network classifier. The texture feature sets for four different culture surfaces were determined from the gray level co-occurrence matrix and local statistics texture models using two feature selection algorithms and by considering computational cost. The quantitative morphometry of quiescent-like and reactive-like cerebral cortical astrocytes cultured on four different culture environments was investigated using the new and conventional cell shape index. Inclusion of cell spreading with stellation information through use of the new cell shape index was shown to change biomedical conclusions derived from conventional cell shape analysis based on stellation alone. The new CSI results showed that the quantitative astrocyte spreading and stellation behavior was induced by both the underlying substrate and the immunoreactivity of the astrocytes. V C 2015 International Society for Advancement of Cytometry Key terms cell spreading; stellation; immunoreactivity; texture-based cell segmentation; floating feature selection; cell-material interactions A cell shape index (CSI) is a dimensionless quantitative measure of cell morphology acquired from images. Cells have different morphologies depending on their type in vivo, e.g., astrocytes have a stellate morphology in the central nervous system (CNS) for interactions with neurons and capillaries (1), while endothelial cells in heart arteries have an elongated morphology with actin and microtubule fibers aligned parallel to the direction of blood flow (2). In vitro, cells also adopt distinctive morphologies that approximately recapitulate their in vivo counterparts and that can be influenced by a controlled environment. Quantitative cell morphology investigations have recently been used to explore the potentially significant directive impact of environments for healthy or pathological cellular outcomes (3-7).A conventional CSI in widespread use is the ratio of perimeter squared to the cell projection area (1):where P is cell perimeter and A is cell projection area. This equation describes stellation as a cell's departure from a circular projection since:
A diagnostic approach is developed and implemented that provides clear feature definition in atomic force microscopy (AFM) images of neural cells on nanofibrillar tissue scaffolds. Because the cellular edges and processes are on the same order as the background nanofibers, this imaging situation presents a feature definition problem. The diagnostic approach is based on analysis of discrete Fourier transforms of standard AFM section measurements. The diagnostic conclusion that the combination of dynamic range enhancement with low-frequency component suppression enhances feature definition is shown to be correct and to lead to clear-featured images that could change previously held assumptions about the cell-cell interactions present. Clear feature definition of cells on scaffolds extends the usefulness of AFM imaging for use in regenerative medicine.
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