https://www.selleckchem.com/products/mepazine-hydrochloride.html Protein dynamics in the synaptic bouton are still not well understood, despite many quantitative studies of synaptic structure and function. The complexity of the synaptic environment makes investigations of presynaptic protein mobility challenging. Here, we present an in vitro approach to create a minimalist model of the synaptic environment by patterning synaptic vesicles (SVs) on glass coverslips. We employed fluorescence correlation spectroscopy (FCS) to measure the mobility of monomeric enhanced green fluorescent protein (mEGFP)-tagged proteins in the presence of the vesicle patterns. We observed that the mobility of all eleven measured proteins is strongly reduced in the presence of the SVs, suggesting that they all bind to the SVs. The mobility observed in these conditions is within the range of corresponding measurements in synapses of living cells. Overall, our simple, but robust, approach should enable numerous future studies of organelle-protein interactions in general.Microfossils are a powerful tool in earth sciences, and they have been widely used for the determination of geological age and in paleoenvironmental studies. However, the identification of fossil species requires considerable time and labor by experts with extensive knowledge and experience. In this study, we successfully automated the acquisition of microfossil data using an artificial intelligence system that employs a computer-controlled microscope and deep learning methods. The system was used to calculate changes in the relative abundance (%) of Cycladophora davisiana, a siliceous microfossil species (Radiolaria) that is widely used as a stratigraphic tool in studies on Pleistocene sediments in the Southern Ocean. The estimates obtained using this system were consistent with the results obtained by a human expert ( less then  ± 3.2%). In terms of efficiency, the developed system was capable of performing the classificatio