Gut microbiota are reported to be associated with many diseases, including cancers. Several bacterial taxa have been shown to be associated with cancer development or response to treatment. However, longitudinal microbiota alterations during the development of cancers are relatively unexplored. To better understand how microbiota changes, we profiled the gut microbiota composition from prostate cancer-bearing mice and control mice at five different time points. Distinct gut microbiota differences were found between cancer-bearing mice and control mice. Akkermansiaceae was found to be significantly higher in the first three weeks in cancer-bearing mice, which implies its role in the early stage of cancer colonization. We also found that Bifidobacteriaceae and Enterococcaceae were more abundant in the second and last sampling week, respectively. The increments of Akkermansiaceae, Bifidobacteriaceae and Enterococcaceae were previously found to be associated with responses to immunotherapy, which suggests links between these bacteria families and cancers. Additionally, our function analysis showed that the bacterial taxa carrying steroid biosynthesis and butirosin and neomycin biosynthesis were increased, whereas those carrying naphthalene degradation decreased in cancer-bearing mice. Our work identified the bacteria taxa altered during prostate cancer progression and provided a resource of longitudinal microbiota profiles during cancer development in a mouse model.

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to enable zero net-energy consumption and optimal power management for future homes or buildings, the dc electric distribution systems (dc nano-grid) finds feasibility and simplicity for integrating multi-type renewable energy sources. However, integrating all the sources and loads in a simple, reliable and smart way is still challenging. This paper introduces a 380V emulator testbed of 10kW, and then proposes a distributed droop control method to integrate all source converters. Control functions in components level and system level will be defined and discussed, and energy storage management and its control law in dc nano-grid is proposed. System level energy management control strategies in a day/24 hours are examined and discussed with considerations of residential load demand profile, local renewable energy source profile and schedules of electricity rate. System level static experiments within 24h are given for verification purposes.

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