The role of human cytochrome P450 2E1 in liver inflammation and fibrosis.

Cytochrome P450 2E1 (CYP2E1) plays an important role in alcohol and toxin metabolism by catalyzing the conversion of substrates into more polar metabolites and producing reactive oxygen species. Reactive oxygen species-induced oxidative stress promotes hepatocyte injury and death, which in turn induces inflammation, activation of hepatic stellate cells, and liver fibrosis. Here, we analyzed mice expressing only the human CYP2E1 gene (hCYP2E1) to determine differences in hCYP2E1 versus endogenous mouse Cyp2e1 function with different liver injuries. After intragastric alcohol feeding, CYP2E1 expression was induced in both hCYP2E1 and wild-type (Wt) mice. hCYP2E1 mice had greater inflammation, fibrosis, and lipid peroxidation but less hepatic steatosis. In addition, hCYP2E1 mice demonstrated increased expression of fibrogenic and proinflammatory genes but decreased expression of de novo lipogenic genes compared to Wt mice. Lipidomics of free fatty acid, triacylglycerol, diacylglycerol, and cholesterol ester species and proinflammatory prostaglandins support these conclusions. Carbon tetrachloride-induced injury suppressed expression of both mouse and human CYP2E1, but again hCYP2E1 mice exhibited greater hepatic stellate cell activation and fibrosis than Wt controls with comparable expression of proinflammatory genes. By contrast, 14-day bile duct ligation induced comparable cholestatic injury and fibrosis in both genotypes. Conclusion: Alcohol-induced liver fibrosis but not hepatic steatosis is more severe in the hCYP2E1 mouse than in the Wt mouse, demonstrating the use of this model to provide insight into the pathogenesis of alcoholic liver disease. (Hepatology Communications 2017;1:1043-1057)

ESarDet: An Efficient SAR Ship Detection Method Based on Context Information and Large Effective Receptive Field

Ship detection using synthetic aperture radar (SAR) has been extensively utilized in both the military and civilian fields. On account of complex backgrounds, large scale variations, small-scale targets, and other challenges, it is difficult for current SAR ship detection methods to strike a balance between detection accuracy and computation efficiency. To overcome those challenges, ESarDet, an efficient SAR ship detection method based on contextual information and a large effective receptive field (ERF), is proposed. We introduce the anchor-free object detection method YOLOX-tiny as a baseline model and make several improvements to it. First, CAA-Net, which has a large ERF, is proposed to better merge the contextual and semantic information of ships in SAR images to improve ship detection, particularly for small-scale ships with complex backgrounds. Further, to prevent the loss of semantic information regarding ship targets in SAR images, we redesign a new spatial pyramid pooling network, namely A2SPPF. Finally, in consideration of the challenge posed by the large variation in ship scale in SAR images, we design a novel convolution block, called A2CSPlayer, to enhance the fusion of feature maps from different scales. Extensive experiments are conducted on three publicly available SAR ship datasets, DSSDD, SSDD, and HRSID, to validate the effectiveness of the proposed ESarDet. The experimental results demonstrate that ESarDet has distinct advantages over current state-of-the-art (SOTA) detectors in terms of detection accuracy, generalization capability, computational complexity, and detection speed

Short-Term Effects of Bio-Organic Fertilizer on Soil Fertility and Bacterial Community Composition in Tea Plantation Soils

Overuse of chemical fertilizers to maintain tea production has caused many adverse effects in tea plantations and largely hampers the sustainable development of the tea industry. Applying bio-organic fertilizer (BOF) to achieve the goal of sustainable agriculture has become popular because of its advantages, such as its pollution-free nature, considerable amount of beneficial microbes and soil-friendly organic materials. However, the effects of BOF application on tea plantation soil remain an open question. Herein, we carried out a 3-year pot experiment with four treatments, including control without fertilization (CK), 100% chemical fertilizer (CF), 50% chemical fertilizer +50% BOF (CFOF) and 100% BOF (OF), to explore the effects of BOF application on soil fertility and bacterial community in tea plantations. The results showed that BOF application could increase soil fertility in both bulk and rhizosphere soils and improve the biomass of tea leaves. In addition, the nutrient level change caused by BOF application significantly changed bacterial community diversity and composition and accounted for 74.91% of the community variation. CFOF and OF treatments significantly increased the bacterial Chao1 and Shannon indices compared to CF treatment (p < 0.05). Moreover, bacterial community composition was dominated by Betaproteobacteria (46.88%), Acidobacteria (11.29%), Alphaproteobacteria (9.69%) and Gammaproteobacteria (9.59%). BOF application increased the relative abundance of Alphaproteobacteria, Acidobacteria, Deltaproteobacteria and planctomycetes and decreased the relative abundance of Betaproteobacteria (p < 0.05). Furthermore, bacterial function prediction revealed that BOF application improved the N and C cycling processes and enhanced the co-occurrence network complexity in the bulk soils. Bacterial community functions and co-occurrence networks in the rhizosphere did not show similar results, indicating that rhizosphere bacterial communities were more affected by the rhizosphere effect than BOF application. All these findings verified our hypothesis that applying BOF in tea plantations could increase the biomass of tea plants by improving soil fertility and influencing the soil bacterial function groups. In summary, we suggested that BOF application could be a promising way to achieve the sustainable development of the tea industry

Short-Term Effects of Bio-Organic Fertilizer on Soil Fertility and Bacterial Community Composition in Tea Plantation Soils

Overuse of chemical fertilizers to maintain tea production has caused many adverse effects in tea plantations and largely hampers the sustainable development of the tea industry. Applying bio-organic fertilizer (BOF) to achieve the goal of sustainable agriculture has become popular because of its advantages, such as its pollution-free nature, considerable amount of beneficial microbes and soil-friendly organic materials. However, the effects of BOF application on tea plantation soil remain an open question. Herein, we carried out a 3-year pot experiment with four treatments, including control without fertilization (CK), 100% chemical fertilizer (CF), 50% chemical fertilizer +50% BOF (CFOF) and 100% BOF (OF), to explore the effects of BOF application on soil fertility and bacterial community in tea plantations. The results showed that BOF application could increase soil fertility in both bulk and rhizosphere soils and improve the biomass of tea leaves. In addition, the nutrient level change caused by BOF application significantly changed bacterial community diversity and composition and accounted for 74.91% of the community variation. CFOF and OF treatments significantly increased the bacterial Chao1 and Shannon indices compared to CF treatment (p Betaproteobacteria (46.88%), Acidobacteria (11.29%), Alphaproteobacteria (9.69%) and Gammaproteobacteria (9.59%). BOF application increased the relative abundance of Alphaproteobacteria, Acidobacteria, Deltaproteobacteria and planctomycetes and decreased the relative abundance of Betaproteobacteria (p < 0.05). Furthermore, bacterial function prediction revealed that BOF application improved the N and C cycling processes and enhanced the co-occurrence network complexity in the bulk soils. Bacterial community functions and co-occurrence networks in the rhizosphere did not show similar results, indicating that rhizosphere bacterial communities were more affected by the rhizosphere effect than BOF application. All these findings verified our hypothesis that applying BOF in tea plantations could increase the biomass of tea plants by improving soil fertility and influencing the soil bacterial function groups. In summary, we suggested that BOF application could be a promising way to achieve the sustainable development of the tea industry

The warming winter accelerated methane emissions during subsequent rice growing season from paddy fields

Global temperature is projected to increase, which impacts the ecological process in northern mid- and high-latitude ecosystems, but the winter temperature change in ecosystems is among the least understood. Rice paddy represents a significant contributor to global anthropogenic CH _4 emissions and has a strong climate forcing feedback; however, the legacy effects of warming winter on CH _4 emissions in the subsequent growing season remain uncertain. Here, we conducted field and incubation experiments to determine the effects of winter soil temperature changes on CH _4 emissions in the subsequent growing season. First, in the 3 year field experiment, we continuously measured CH _4 emissions from the rice cropping system. The winter soil temperature and its variation showed significant differences over the 3 years. In the warming-winter year, the rice paddy accumulated less NH _4 ^+ –N and more dissolved organic carbon (DOC) in the soil during winter, resulting in high CH _4 emissions. Second, we incubated the paddy soils without flooding at three temperatures (5 °C, 15 °C, and 25 °C) for 4 weeks to simulate warming winter, and subsequently incubated at same temperature (25 °C) under submerged conditions for 4 weeks to simulate growing season. The result was consistent with field experiment, increased soil temperature significantly increased soil DOC content and decreased NH _4 ^+ –N content in ‘winter season’. The CH _4 emissions in the subsequent ‘growing season’ increased by 190% and 468% when previous incubation temperature increased 10 °C and 20 °C. We showed strong and clear links between warming winter and CH _4 emissions in the subsequent growing season for the first time, suggesting that CH _4 related processes respond not only to warming during the growing season but also in the previous winter. Our findings indicate that nonuniform global warming causes a disproportionate increase in climate forcing feedback to emit more CH _4

Error changes with the iteration number of NMF on networks without node attitudes.

<p>Error changes with the iteration number of NMF on networks without node attitudes.</p

The AUC scores of NMF-LP algorithm with different values of <i>i</i>.

<p>The AUC scores of NMF-LP algorithm with different values of <i>i</i>.</p

Notations and their meanings.

<p>Notations and their meanings.</p