The uptake of nanoparticles (NPs) into biological cells with rigid cell walls is poorly understood. Interestingly, the authors demonstrated that positively charged polystyrene NPs were taken into yeast cells in the physiological saline. However, the polystyrene NPs are not suitable for carrier NPs due to their low biodegradability. In this study, we evaluated the uptake of biodegradable poly(lactic-co-glycolic) acids (PLGA) NPs into the yeast cells. As a result, PLGA NPs were taken into yeast cells regardless of their surface potentials. The yeast cells were alive after the uptake of negatively charged NPs, whereas the cell viability for the positively charged NPs was low. In addition, the experiments using endocytosis inhibitors suggested that the uptake of PLGA NPs was different from the conventional endocytosis. These experimental results strongly suggested that the negatively charged PLGA NPs are suitable for the delivery of useful substances to eukaryotic cells with cell walls.

This paper presents a new iterative algorithm to solve linear inverse problem for static light scattering (SLS) particle size distribution measurement.

The problem is written by Mv = w, where v is a particle size distribution (unknown), w is intensities of the scattered light of particles (known), and M is a kernel matrix based on Mie scattering theorem.

This study was made to propose new iterative algorithm which copes both high peak detection and robustness to measure mixture sample, especially narrow or monodisperse distribution mixture sample (picket fences).

First, we introduced two known algorithms. Then we propose new algorithm which was united of the two algorithms with mixture coefficient C_m. After that, we evaluated the optimal C_m and the capability of new algorithm by simulation which contained 6 peaks picket fences sample. Finally, we discussed the superiority of the algorithm especially robustness for complex particle size distributions.

Although the rapid installation of renewable energy and the restart of nuclear power plants have been and will be progressed, thermal power generation is still important power generation method. Thermal power generation burns a fossil fuel such as oil, gas and coal. Among them, the powder technology is required for the operation and development of coal-fired power generation system. Recently, numerical simulation technique for the equipment in a coal-fired power plant have been developed and applied to various equipment in a plant. In this review paper, the examples of application of numerical simulation to the existing and developing coal-fired power plant are introduced.