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Borna disease virus (BoDV-1) is a highly neurotropic RNA virus that causes neurobehavioral disturbances such as abnormal social activities and memory impairment. Although impairments in the neural circuits caused by BoDV-1 infection induce these disturbances, the molecular basis remains unclear. Furthermore, it is unknown whether anti-BoDV-1 treatments can attenuate BoDV-1-mediated transcriptomic changes in neuronal cells. In this study, we investigated the effects of BoDV-1 infection on neuronal differentiation and the transcriptome of differentiated neuronal cells using persistently BoDV-1-infected cells. Although BoDV-1 infection did not have a detectable effect on intracellular neuronal differentiation processes, differentiated neuronal cells exhibited transcriptomic changes in differentiation-related genes. Some of these transcriptomic changes, such as the decrease in the expression of apoptosis-related genes, were recovered by anti-BoDV-1 treatment, while alterations in the expression of other genes remained after treatment. We further demonstrated that a decrease in cell viability induced by differentiation processes in BoDV-1-infected cells can be relieved with anti-BoDV-1 treatment. This study provides fundamental information regarding transcriptomic changes after BoDV-1 infection and the treatment in neuronal cells.

Borna disease virus (BoDV-1) is a highly neurotropic RNA virus that causes neurobehavioral disturbances such as abnormal social activities and memory impairment. Although impairments in the neural circuits caused by BoDV-1 infection induce these disturbances, the molecular basis remains unclear. Furthermore, it is unknown whether anti-BoDV-1 treatments can attenuate BoDV-1-mediated transcriptomic changes in neuronal cells. In this study, we investigated the effects of BoDV-1 infection on neuronal differentiation and the transcriptome of differentiated neuronal cells using persistently BoDV-1-infected cells. Although BoDV-1 infection did not have a detectable effect on intracellular neuronal differentiation processes, differentiated neuronal cells exhibited transcriptomic changes in differentiation-related genes. Some of these transcriptomic changes, such as the decrease in the expression of apoptosis-related genes, were recovered by anti-BoDV-1 treatment, while alterations in the expression of other genes remained after treatment. We further demonstrated that a decrease in cell viability induced by differentiation processes in BoDV-1-infected cells can be relieved with anti-BoDV-1 treatment. This study provides fundamental information regarding transcriptomic changes after BoDV-1 infection and the treatment in neuronal cells.

内容の要約, 広島大学(Hiroshima University), 博士(農学), Doctor of Agriculture, doctoral

Phase recovery from intensity-only measurements forms the heart of coherent imaging techniques and holography. Here we demonstrate that a neural network can learn to perform phase recovery and holographic image reconstruction after appropriate training. This deep learning-based approach provides an entirely new framework to conduct holographic imaging by rapidly eliminating twin-image and self-interference related spatial artifacts. Compared to existing approaches, this neural network based method is significantly faster to compute, and reconstructs improved phase and amplitude images of the objects using only one hologram, i.e., requires less number of measurements in addition to being computationally faster. We validated this method by reconstructing phase and amplitude images of various samples, including blood and Pap smears, and tissue sections. These results are broadly applicable to any phase recovery problem, and highlight that through machine learning challenging problems in imaging science can be overcome, providing new avenues to design powerful computational imaging systems.