バイオセンサーとバイオエレクトロニクス

Cell-based experiments provide the efficacy of chemicals through the biological function. The authors have described post-synapse model cell-based assay based on qualified analysis for neural drug discoveries. However, in general, cell-based assays often include data fluctuation. This may be a barrier preventing the performance for various practical purposes. In this study, we tried discerning data analysis for clarify the chemical action to the ionotoropic glutamate receptor (GluR), whereby an ion-flux assay of post-synapse model cells is performed and are analyzed based on a chemometrics approach. The dynamic behavior of the GluR of post-synapse model cell was assayed with multivariate data analysis methods namely hierarchical cluster analysis (HCA) and principal component analysis (PCA). By using HCA, we can identify and remove the non-responding samples. By using PCA, the effect of chemicals on the dynamic behavior of ion flux through GluR can be recognized clearly; as either agonist or antagonist. As shown in the results, the GluR-based assay by post-synapse model cell with data analysis methods provide a sodium influx profile which is derived by an agonists or antagonists application. By employing the data analysis methods, PCA and HCA, it is possible to develop a smart cellular biosensing system for qualified analysis.

Recent in vitro studies have highlighted the importance of substrate stiffness in governing a range of cellular functions. Motility of adherent cells, in particular, is found to be regulated by the substrate rigidity. Many cell types exhibit a subtle biphasic migration-velocity response to increasing substrate rigidity, with fast migration occurring at intermediate stiffness and slower migration on very compliant or highly rigid substrates. This study aims at improving the understanding of mechanisms responsible for cell sensitivity to the mechanical stiffness of extracellular environment during migration. We use the "two-spring model" as a mechanistic paradigm for rigidity sensing ability of cells at the scale of a single adhesion site. This will be implemented in a simple physical model of cell motility to elucidate how the local autonomy at the scale of adhesion sites may spatially and temporally regulate the cell motility. The model predicts a bell-shaped dependence between the speed of locomotion and substrate rigidity, similar to the experimental observations. This behavior is demonstrated to be rooted in the different effect of substrate rigidity on the magnitude of anterior and posterior actomyosin contractile forces which leads to the variation of net traction in a biphasic fashion.