Weather and climate models are challenged by uncertainties and biases in simulating Southern Ocean (SO) radiative fluxes that trace to a poor understanding of cloud, aerosol, precipitation and radiative processes, and their interactions. Projects between 2016 and 2018 used in-situ probes, radar, lidar and other instruments to make comprehensive measurements of thermodynamics, surface radiation, cloud, precipitation, aerosol, cloud condensation nuclei (CCN) and ice nucleating particles over the SO cold waters, and in ubiquitous liquid and mixed-phase cloudsnucleating particles over the SO cold waters, and in ubiquitous liquid and mixed-phase clouds common to this pristine environment. Data including soundings were collected from the NSF/NCAR G-V aircraft flying north-south gradients south of Tasmania, at Macquarie Island, and on the RV Investigator and RSV Aurora Australis. Synergistically these data characterize boundary layer and free troposphere environmental properties, and represent the most comprehensive data of this type available south of the oceanic polar front, in the cold sector of SO cyclones, and across seasons.Results show a largely pristine environments with numerous small and few large aerosols above cloud, suggesting new particle formation and limited long-range transport from continents, high variability in CCN and cloud droplet concentrations, and ubiquitous supercooled water in thin, multi-layered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of confirmed low clouds were responsible for radiation biases. The combination of models and observations is examining how aerosols and meteorology couple to control SO water and energy budgets.

The information regarding the effect of hepatitis B virus (HBV) infection on gut microbiota and the relationship between gut microbiota dysbiosis and hepatitis B virus-induced chronic liver disease (HBVCLD) is limited. In this study, we aimed at characterizing the gut microbiota composition in the three different stages of hepatitis B virus-induced chronic liver disease patients and healthy individuals. Faecal samples and clinical data were collected from HBVCLD patients and healthy individuals.The 16S rDNA gene amplification products were sequenced. Bioinformatic analysis including alpha diversity and PICRUSt was performed. A total of 19 phyla, 43 classes, 72 orders, 126 families and 225 genera were detected. The beta-diversity showed a separate clustering of healthy controls and HBVCLD patients covering chronic hepatitis (CHB), liver cirrhosis (LC) and hepatocellular carcinoma (HCC); and gut microbiota of healthy controls was more consistent, whereas those of CHB, LC and HCC varied substantially. The abundance of Firmicutes was lower, and Bacteroidetes was higher in patients with CHB, LC and HCC than in healthy controls. Predicted metagenomics of microbial communities showed an increase in glycan biosynthesis and metabolism-related genes and lipid metabolism-related genes in HBVCLD than in healthy individuals. Our study suggested that HBVCLD is associated with gut dysbiosis, with characteristics including, a gain in potential bacteria and a loss in potential beneficial bacteria or genes. Further study of CHB, LC and HCC based on microbiota may provide a novel insight into the pathogenesis of HBVCLD as well as a novel treatment strategy. K E Y W O R D S16S rDNA, dysbiosis, Gut Microbiota, hepatitis B virus, progression

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In situ observations of cloud properties made by airborne probes play a critical role in ice cloud research through their role in process studies, parameterization development, and evaluation of simulations and remote sensing retrievals. To determine how cloud properties vary with environmental conditions, in situ data collected during different field projects processed by different groups must be used. However, because of the diverse algorithms and codes that are used to process measurements, it can be challenging to compare the results. Therefore it is vital to understand both the limitations of specific probes and uncertainties introduced by processing algorithms. Since there is currently no universally accepted framework regarding how in situ measurements should be processed, there is a need for a general reference that describes the most commonly applied algorithms along with their strengths and weaknesses. Methods used to process data from bulk water probes, single-particle light-scattering spectrometers and cloud-imaging probes are reviewed herein, with emphasis on measurements of the ice phase. Particular attention is paid to how uncertainties, caveats, and assumptions in processing algorithms affect derived products since there is currently no consensus on the optimal way of analyzing data. Recommendations for improving the analysis and interpretation of in situ data include the following: establishment of a common reference library of individual processing algorithms, better documentation of assumptions used in these algorithms, development and maintenance of sustainable community software for processing in situ observations, and more studies that compare different algorithms with the same benchmark datasets.