Publications by authors named "Pei-Yin Chi"

Brain-on-Chip devices, which facilitate on-chip cultures of neurons to simulate brain functions, are receiving tremendous attention from both fundamental and clinical research. Consequently, microsensors are being developed to accomplish real-time monitoring of neurotransmitters, which are the benchmarks for neuron network operation. Among these, electrochemical sensors have emerged as promising candidates for detecting a critical neurotransmitter, dopamine.

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The last 20 years have seen the blooming of microfluidics technologies applied to biological sciences. Microfluidics provides effective tools for biological analysis, allowing the experimentalists to extend their playground to single cells and single molecules, with high throughput and resolution which were inconceivable few decades ago. In particular, microfluidic devices are profoundly changing the conventional way of studying the cell motility and cell migratory dynamics.

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The study of cell behavior in constricted environment is particularly relevant to our understanding of the mechanisms of cell invasion. In this regard, microfluidic systems offer promising platforms as microfabricated fluidic chips provide well-controlled physical, chemical and confined environments to study cell phenotype and behavior. Here, we report a fast and effective manufacturing process of user-friendly microfluidic chips ideally suited for quantitative live cell analysis in combination with immunofluorescence microscopy.

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We combine a micro-fluidic electric-field cell-culture (MEC) chip with structured-illumination nano-profilometry (SINAP) to quantitatively study the variations of cancer cell filopodia under external direct-current electric field (dcEF) stimulations. Because the lateral resolution of SINAP is better than 150 nm in bright-field image modality, filopodia with diameters smaller than 200 nm can be observed clearly without fluorescent labeling. In the MEC chip, a homogeneous EF is generated inside the culture area that simulates the endogenous EF environment.

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