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Accurate assessment of the size and distribution of carbon dioxide (CO 2) sources and sinks is important for efforts to understand the carbon cycle and support policy decisions regarding climate mitigation actions. Satellite retrievals of the column-averaged dry-air mole fractions of CO 2 (XCO 2) have been widely used to infer spatial and temporal variations in carbon fluxes through atmospheric inversion techniques. In this study, we present a global spatially resolved terrestrial and ocean carbon flux dataset for 2015–2022. The dataset was generated by the Global ObservatioN-based system for monitoring Greenhouse GAses (GONGGA) atmospheric inversion system through the assimilation of Orbiting Carbon Observatory-2 (OCO-2) XCO 2 retrievals. We describe the carbon budget, interannual variability, and seasonal cycle for the global scale and a set of TransCom regions. The 8-year mean net biosphere exchange and ocean carbon fluxes were - 2.22 ± 0.75 and - 2.32 ± 0.18 Pg C yr -1 , absorbing approximately 23 % and 24 % of contemporary fossil fuel CO 2 emissions, respectively. The annual mean global atmospheric CO 2 growth rate was 5.17 ± 0.68 Pg C yr -1 , which is consistent with the National Oceanic and Atmospheric Administration (NOAA) measurement (5.24 ± 0.59 Pg C yr -1). Europe has the largest terrestrial sink among the 11 TransCom land regions, followed by Boreal Asia and Temperate Asia. The dataset was evaluated by comparing posterior CO 2 simulations with Total Carbon Column Observing Network (TCCON) retrievals as well as Observation Package (ObsPack) surface flask observations and aircraft observations. Compared with CO 2 simulations using the unoptimized fluxes, the bias and root mean square error (RMSE) in posterior CO 2 simulations were largely reduced across the full range of locations, confirming that the GONGGA system improves the estimates of spatial and temporal variations in carbon fluxes by assimilating OCO-2 XCO 2 data. This dataset will improve the broader understanding of global carbon cycle dynamics and their response to climate change. The dataset can be accessed at 10.5281/zenodo.8368846 (Jin et al., 2023a). [ABSTRACT FROM AUTHOR]

The probiotic Limosilactobacillus reuteri DSM 17938 produces anti-inflammatory effects in scurfy (SF) mice, a model characterized by immune dysregulation, polyendocrinopathy, enteropathy, and X-linked inheritance (called IPEX syndrome in humans), caused by regulatory T cell (Treg) deficiency and is due to a Foxp3 gene mutation. Considering the pivotal role of lipids in autoimmune inflammatory processes, we investigated alterations in the relative abundance of lipid profiles in SF mice (± treatment with DSM 17938) compared to normal WT mice. We also examined the correlation between plasma lipids and gut microbiota and circulating inflammatory markers. We noted a significant upregulation of plasma lipids associated with autoimmune disease in SF mice, many of which were downregulated by DSM 17938. The upregulated lipids in SF mice demonstrated a significant correlation with gut bacteria known to be implicated in the pathogenesis of various autoimmune diseases. Chronic hepatitis in SF livers responded to DSM 17938 treatment with a reduction in hepatic inflammation. Altered gene expression associated with lipid metabolism and the positive correlation between lipids and inflammatory cytokines together suggest that autoimmunity leads to dyslipidemia with impaired fatty acid oxidation in SF mice. Probiotics are presumed to contribute to the reduction of lipids by reducing inflammatory pathways. [ABSTRACT FROM AUTHOR]

Viruses are implicated in autoimmune destruction of pancreatic islet [beta] cells, which results in insulin deficiency and type 1 diabetes (T1D).sup.1-4. Certain enteroviruses can infect [beta] cells in vitro.sup.5, have been detected in the pancreatic islets of patients with T1D.sup.6 and have shown an association with T1D in meta-analyses.sup.4. However, establishing consistency in findings across studies has proven difficult. Obstacles to convincingly linking RNA viruses to islet autoimmunity may be attributed to rapid viral mutation rates, the cyclical periodicity of viruses.sup.7 and the selection of variants with altered pathogenicity and ability to spread in populations. [beta] cells strongly express cell-surface coxsackie and adenovirus receptor (CXADR) genes, which can facilitate enterovirus infection.sup.8. Studies of human pancreata and cultured islets have shown significant variation in enteroviral virulence to [beta] cells between serotypes and within the same serotype.sup.9,10. In this large-scale study of known eukaryotic DNA and RNA viruses in stools from children, we evaluated fecally shed viruses in relation to islet autoimmunity and T1D. This study showed that prolonged enterovirus B rather than independent, short-duration enterovirus B infections may be involved in the development of islet autoimmunity, but not T1D, in some young children. Furthermore, we found that fewer early-life human mastadenovirus C infections, as well as CXADR rs6517774, independently correlated with islet autoimmunity. Analysis of known viruses in stool samples from young children with high genetic risk for type 1 diabetes shows that sustained enterovirus B (EV-B) infections, rather than independent, short-duration EV-B infections, might be involved in the development of islet autoimmunity, but not type 1 diabetes., Author(s): Kendra Vehik [sup.1] , Kristian F. Lynch [sup.1] , Matthew C. Wong [sup.2] , Xiangjun Tian [sup.2] , Matthew C. Ross [sup.2] , Richard A. Gibbs [sup.3] , Nadim [...]

In this study, a forecasting model was developed based on the COAWST and atmospheric 3D EnVar module to investigate the effects of assimilation of the sounding and COSMIC–2 data on the forecasting of the revised atmospheric refraction. Three groups of 72 h forecasting tests, with assimilation of different data obtained for a period of one month, were constructed over the Yellow Sea. The results revealed that the bias of the revised atmospheric refraction was the lowest if both the sounding and COSMIC–2 data were assimilated. As a result of the assimilation of the hybrid data, the mean bias reduced by 6.09–6.28% within an altitude of 10 km, and the greatest reduction occurred below the altitude of 3000 m. In contrast, the test that assimilated only the sounding data led to an increase in bias at several levels. This increased bias was corrected after the introduction of the COSMIC–2 data, with the mean correction of 1.6 M within the middle and lower troposphere. During the typhoon period, the improvements in the assimilation were more significant than usual. The improved forecasts of the revised atmospheric refraction were mainly due to the moisture changes within the middle and lower troposphere, while the changes in the upper troposphere were influenced by multiple factors. [ABSTRACT FROM AUTHOR]