Indirubin alleviates CCl4-induced liver fibrosis by regulation of TGF-β-mediated signaling pathways

Objective(s): Liver fibrosis is a common liver disease caused by chronic liver damage. However, there are currently no approved drugs available to treat it. Therefore, the therapeutic effect of indirubin on liver fibrosis was evaluated. This study investigated the protective effect and related molecular mechanism of indirubin against CCl4-induced liver fibrosis in mice.Materials and Methods: We first detected the effect of indirubin on liver fibrosis in mice (n=8 per group, 32 mice total) by ELISA, HE, and Masson staining. Subsequently, the proliferation of activated HSCs was detected by MTT and EdU. Finally, the changes of related proteins and signaling pathways in mice treated with indirubin were investigated by qRT-PCR and Western blot. One-way ANOVA or two-tailed student’s t-test was used for comparison between groups.Results: Firstly, we found that indirubin (25 mg/kg) therapy could attenuate liver injury and significantly down-regulate α-SMA (P=0.0038) and collagen 1 (P=0.0057) in the liver using CCl4-induced liver fibrosis in mice. Secondly, we showed that indirubin (25 μM) could significantly inhibit hepatic stellate cell (HSC) trans-differentiation into myofibroblasts and proliferation (P=0.0063) in HSC-T6 cells treated by TGF-β. Finally, we showed that indirubin could greatly reduce the protein levels of p-Smad2/3, p38, p-ERK, and p-JNK in vivo and in vitro.Conclusion: Our results suggested that indirubin alleviated liver fibrosis and HSC activation mainly through TGF-β-mediated signaling pathways in vivo and in vitro. In conclusion, our data showed that indirubin could be a promising clinical therapeutic drug for the prevention and treatment of liver fibrosis

Relative impacts of global changes and regional watershed changes on the inorganic carbon balance of the Chesapeake Bay

The Chesapeake Bay is a large coastal-plain estuary that has experienced considerable anthropogenic changeover the past century. At the regional scale, land-use change has doubled the nutrient input from rivers and led to an increase in riverine carbon and alkalinity. The bay has also experienced global changes, including the rise of atmospheric temperature and CO2. Here we seek to understand the relative impact of these changes on the inorganic carbon balance of the bay between the early 1900s and the early 2000s. We use a linked land–estuarine–ocean modeling system that includes both inorganic and organic carbon and nitrogen cycling. Sensitivity experiments are performed to isolate the effect of changes in (1) atmospheric CO2, (2) temperature,(3) riverine nitrogen loading and (4) riverine carbon and alkalinity loading. Specifically, we find that over the past century global changes have increased ingassing by roughly the same amount (∼30 Gg-C yr−1) as has the increased riverine loadings. While the former is due primarily to increases in atmospheric CO2, the latter results from increased net ecosystem production that enhances ingassing. Interestingly, these increases in ingassing are partially mitigated by increase temperatures and increased riverine carbon and alkalinity in-puts, both of which enhance outgassing. Overall, the bay has evolved over the century to take up more atmospheric CO2 and produce more organic carbon. These results suggest that over the past century, changes in riverine nutrient loads have played an important role in altering coastal carbon budgets, but that ongoing global changes have also substantially affected coastal carbonate chemistry

Impacts of Multiple Environmental Changes on Long‐Term Nitrogen Loading From the Chesapeake Bay Watershed

Excessive nutrient inputs from land, particularly nitrogen (N), have been found to increase the occurrence of hypoxia and harmful algal blooms in coastal ecosystems. To identify the main contributors of increased N loading and evaluate the efficacy of water pollution control policies, it is essential to quantify and attribute the long‐term changes in riverine N export. Here, we use a state‐of‐the‐art terrestrial–aquatic interface model to examine how multiple environmental factors may have affected N export from the Chesapeake Bay watershed since 1900. These factors include changes in climate, carbon dioxide, land use, and N inputs (i.e., atmospheric N deposition, animal manure, synthetic N fertilizer use, and wastewater discharge). Our results estimated that ammonium (NH4+) and nitrate (NO3−) export increased substantially (66% for NH4+ and 123% for NO3−) from the 1900s to the 1990s and then declined (32% for NH4+ and 14% for NO3−) since 2000. The temporal trend of dissolved organic nitrogen (DON) export paralleled that of dissolved inorganic N, while particulate organic nitrogen export was relatively constant during 1900–2015. Precipitation was the primary driver of interannual variability in N export to the Bay. Wastewater discharge explained most of the long‐term change in riverine NH4+ and DON fluxes from 1900 to 2015. The changes in atmospheric deposition, wastewater, and synthetic fertilizer were responsible for the trend of riverine NO3−. In light of our model‐based attribution analysis, terrestrial non‐point source nutrient management will play an important role in achieving water quality goals

Impacts of Multiple Environmental Changes on Long‐Term Nitrogen Loading From the Chesapeake Bay Watershed

Excessive nutrient inputs from land, particularly nitrogen (N), have been found to increase the occurrence of hypoxia and harmful algal blooms in coastal ecosystems. To identify the main contributors of increased N loading and evaluate the efficacy of water pollution control policies, it is essential to quantify and attribute the long‐term changes in riverine N export. Here, we use a state‐of‐the‐art terrestrial–aquatic interface model to examine how multiple environmental factors may have affected N export from the Chesapeake Bay watershed since 1900. These factors include changes in climate, carbon dioxide, land use, and N inputs (i.e., atmospheric N deposition, animal manure, synthetic N fertilizer use, and wastewater discharge). Our results estimated that ammonium (NH4+) and nitrate (NO3−) export increased substantially (66% for NH4+ and 123% for NO3−) from the 1900s to the 1990s and then declined (32% for NH4+ and 14% for NO3−) since 2000. The temporal trend of dissolved organic nitrogen (DON) export paralleled that of dissolved inorganic N, while particulate organic nitrogen export was relatively constant during 1900–2015. Precipitation was the primary driver of interannual variability in N export to the Bay. Wastewater discharge explained most of the long‐term change in riverine NH4+ and DON fluxes from 1900 to 2015. The changes in atmospheric deposition, wastewater, and synthetic fertilizer were responsible for the trend of riverine NO3−. In light of our model‐based attribution analysis, terrestrial non‐point source nutrient management will play an important role in achieving water quality goals

Cellular Internalization-Induced Aggregation of Porous Silicon Nanoparticles for Ultrasound Imaging and Protein-Mediated Protection of Stem Cells

Nanotechnology employs multifunctional engineered materials in the nanoscale range that provides many opportunities for translational stem cell research and therapy. Here, a cell-penetrating peptide (virus-1 transactivator of transcription)-conjugated, porous silicon nanoparticle (TPSi NP) loaded with the Wnt3a protein to increase both the cell survival rate and the delivery precision of stem cell transplantation via a combinational theranostic strategy is presented. The TPSi NP with a pore size of 10.7 nm and inorganic framework enables high-efficiency loading of Wnt3a, prolongs Wnt3a release, and increases antioxidative stress activity in the labeled mesenchymal stem cells (MSCs), which are highly beneficial properties for cell protection in stem cell therapy for myocardial infarction. It is confirmed that the intracellular aggregation of TPSi NPs can highly amplify the acoustic scattering of the labeled MSCs, resulting in a 2.3-fold increase in the ultrasound (US) signal compared with that of unlabeled MSCs. The translational potential of the designed nanoagent for real-time US imaging-guided stem cell transplantation is confirmed via intramyocardial injection of labeled MSCs in a nude mouse model. It is proposed that the intracellular aggregation of protein drug-loaded TPSi NPs could be a simple but robust strategy for improving the therapeutic effect of stem cell therapy.Peer reviewe

Estuarine Dissolved Organic Carbon Flux From Space: With Application to Chesapeake and Delaware Bays

This study uses a neural network model trained with in situ data, combined with satellite data and hydrodynamic model products, to compute the daily estuarine export of dissolved organic carbon (DOC) at the mouths of Chesapeake Bay (CB) and Delaware Bay (DB) from 2007 to 2011. Both bays show large flux variability with highest fluxes in spring and lowest in fall as well as interannual flux variability (0.18 and 0.27 Tg C/year in 2008 and 2010 for CB; 0.04 and 0.09 Tg C/year in 2008 and 2011 for DB). Based on previous estimates of total organic carbon (TOCexp) exported by all Mid‐Atlantic Bight estuaries (1.2 Tg C/year), the DOC export (CB + DB) of 0.3 Tg C/year estimated here corresponds to 25% of the TOCexp. Spatial and temporal covariations of velocity and DOC concentration provide contributions to the flux, with larger spatial influence. Differences in the discharge of fresh water into the bays (74 billion m3/year for CB and 21 billion m3/year for DB) and their geomorphologies are major drivers of the differences in DOC fluxes for these two systems. Terrestrial DOC inputs are similar to the export of DOC at the bay mouths at annual and longer time scales but diverge significantly at shorter time scales (days to months). Future efforts will expand to the Mid‐Atlantic Bight and Gulf of Maine, and its major rivers and estuaries, in combination with coupled terrestrial‐estuarine‐ocean biogeochemical models that include effects of climate change, such as warming and CO2 increase

Ocean Circulation Causes Strong Variability in the Mid-Atlantic Bight Nitrogen Budget

Understanding of nitrogen cycling on continental shelves, a critical component of global nutrient cycling, is hampered by limited observations compared to the strong variability on a wide range of time and space scales. Numerical models have the potential to partially alleviate this issue by filling spatiotemporal data gaps and hence resolving annual area-integrated nutrient fluxes. In this study, a three-dimensional biogeochemical-circulation model was implemented to simulate the Mid-Atlantic Bight (MAB) nitrogen budget. Model results demonstrate that, on average, MAB net community production (NCP) was positive (+0.27 Tg N/year), indicating net autotrophy. Interannual variability in NCP was strong, with annual values ranging between 0.19 and 0.41 Tg N/year. Along-shelf and across-shelf horizontal transport fluxes were the other dominant terms in the nitrogen budget and were primarily responsible for this NCP variability. The along-shelf current transported nitrogen from the north (0.65 Tg N/year) into the MAB, supplementing the nitrogen entering from terrestrial inputs (0.27 Tg N/year). However, NCP was highest in the year when total water volume transport and inorganic nitrogen input was strongest across the continental slope in the southern MAB, rather than when terrestrial inputs were greatest. Interannual variability of NCP appears to be linked to changes in the positions of the Gulf Stream and Slope Water Gyre. Overall, the strong spatiotemporal variability of the nitrogen fluxes highlights the importance of observations throughout all seasons and multiple years in order to accurately resolve the current status and future changes of the MAB nitrogen budget

Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning

Code summarization generates brief natural language description given a source code snippet, while code retrieval fetches relevant source code given a natural language query. Since both tasks aim to model the association between natural language and programming language, recent studies have combined these two tasks to improve their performance. However, researchers have yet been able to effectively leverage the intrinsic connection between the two tasks as they train these tasks in a separate or pipeline manner, which means their performance can not be well balanced. In this paper, we propose a novel end-to-end model for the two tasks by introducing an additional code generation task. More specifically, we explicitly exploit the probabilistic correlation between code summarization and code generation with dual learning, and utilize the two encoders for code summarization and code generation to train the code retrieval task via multi-task learning. We have carried out extensive experiments on an existing dataset of SQL and Python, and results show that our model can significantly improve the results of the code retrieval task over the-state-of-art models, as well as achieve competitive performance in terms of BLEU score for the code summarization task.Comment: Published at The Web Conference (WWW) 2020, full pape

The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom : 1990-2017

Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27 C UK). We integrate recent emission inventory data, ecosystem process-based model results and inverse modeling estimates over the period 1990-2017. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported to the UN climate convention UNFCCC secretariat in 2019. For uncertainties, we used for NGHGIs the standard deviation obtained by varying parameters of inventory calculations, reported by the member states (MSs) following the recommendations of the IPCC Guidelines. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model-specific uncertainties when reported. In comparing NGHGIs with other approaches, a key source of bias is the activities included, e.g., anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011-2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 TgCH(4) yr (-1) (EDGAR v5.0) and 19.0 TgCH(4) yr(-1) (GAINS), consistent with the NGHGI estimates of 18.9 +/- 1.7 TgCH(4) yr(-1). The estimates of TD total inversions give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher-resolution atmospheric transport models give a mean emission of 28.8 TgCH(4) yr(-1). Coarser-resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 TgCH(4) yr(-1)) and surface network (24.4 TgCH(4) yr (-1)). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions, and geological sources together account for the gap between NGHGIs and inversions and account for 5.2 TgCH(4) yr(-1). For N2O emissions, over the 2011-2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 TgN(2)Oyr(-1), respectively, agreeing with the NGHGI data (0.9 0.6 TgN(2)Oyr(-1)). Over the same period, the average of the three total TD global and regional inversions was 1.3 +/- 0.4 and 1.3 +/- 0.1 TgN(2)Oyr(-1), respectively. The TD and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at the EU CUK scale and at the national scale.Peer reviewe