Microfluidic devices have emerged as a new cell culture tool, which can mimic the structure and physiology of living human organs. However, no standardized culture method for a microfluidic device has yet been established. Here, we describe the effects of various conditions on cell proliferation in a microchannel with a depth smaller than 100 μm. Primary endothelial cell proliferation was suppressed with a decrease in the culture medium volume per cell culture area. Moreover, cell growth was compared with or without medium flow, and the optimum culture condition was determined to be 1 μL/h flow in a 65-μm-deep microchannel. In addition, glucose consumption was greater under fluidic conditions than under static conditions, and the ability of tumor (HeLa) cells to convert glucose into lactate appeared to be higher in a static culture than that in a fluidic culture. Overall, our results will serve as a useful guide for designing a microfluidic cell culture platform in a channel smaller than 100 μm.

In this work, we developed mobile laser-induced fluorescence spectrum (LIFS) lidar based on preliminary experiments on the excitation emission matrix of a water sample and a method for reducing solar background light using the synchronous detection technique. The combination of a UV short-pulse laser (355 nm, 6 ns) for fluorescence excitation with a 10-100 ns short-time synchronous detection using a gated image-intensified multi-channel CCD of the fluorescence made the LIFS lidar operation possible even in daytime. The LIFS lidar with this construction demonstrated the potential of natural river/lake water quality monitoring at the Tenryu River/Lake Suwa. Three main components in the fluorescence data of the water, dissolved organic matter, phycocyanin, and chlorophyll, were extracted by spectral analysis using the standard spectral functions of these components. Their concentrations were estimated by adapting experimentally calibrated data. Results of long-term field observations using our LIFS lidar from 2010 to 2012 show the necessity of simultaneous multi-component detection to understand the natural water environment.

No abstract

No abstract