μ-2-Amino­terephthalato-κ2 O 1:O 4-bis­[triphenyl­tin(IV)]

The title compound, [Sn2(C6H5)6(C8H5NO4)], contains two triphenyl­tin groups bridged by a 2-amino­terephthalate ligand. The two SnIV centers have similar distorted tetra­hedral coordination geometries. Each SnIV atom is bonded to three phenyl C atoms and one O atom from a carboxyl­ate group. The other O atom of the carboxyl­ate group has a weak inter­action with the Sn atom. The amino group is disordered over two sites, with site-occupancy factors of 0.779 (11) and 0.221 (11). Intra­molecular N—H⋯O hydrogen bonds are observed

Experimental warming causes mismatches in alpine plant-microbe-fauna phenology

Long-term observations have shown that many plants and aboveground animals have changed their phenology patterns due to warmer temperatures over the past decades. However, empirical evidence for phenological shifts in alpine organisms, particularly belowground organisms, is scarce. Here, we investigate how the activities and phenology of plants, soil microbes, and soil fauna will respond to warming in an alpine meadow on the Tibetan Plateau, and whether their potential phenological changes will be synchronized. We experimentally simulate an increase in soil temperature by 2-4 degrees C according to future projections for this region. We find that warming promotes plant growth, soil microbial respiration, and soil fauna feeding by 8%, 57%, and 20%, respectively, but causes dissimilar changes in their phenology during the growing season. Specifically, warming advances soil faunal feeding activity in spring and delays it in autumn, while their peak activity does not change; whereas warming increases the peak activity of plant growth and soil microbial respiration but with only minor shifts in their phenology. Such phenological asynchrony in alpine organisms may alter ecosystem functioning and stability.Phenological shifts driven by climate change are well-studied in plants and aboveground animals, but scarcely in belowground biota. Here, the authors show that soil warming causes phenological mismatches between plants, soil microbes and soil microarthropods in an alpine meadow

An Improved Approach for Text Sentiment Classification Based on a Deep Neural Network via a Sentiment Attention Mechanism

Text sentiment analysis is an important but challenging task. Remarkable success has been achieved along with the wide application of deep learning methods, but deep learning methods dealing with text sentiment classification tasks cannot fully exploit sentiment linguistic knowledge, which hinders the development of text sentiment analysis. In this paper, we propose a sentiment-feature-enhanced deep neural network (SDNN) to address the problem by integrating sentiment linguistic knowledge into a deep neural network via a sentiment attention mechanism. Specifically, first we introduce a novel sentiment attention mechanism to help select the crucial sentiment-word-relevant context words by leveraging the sentiment lexicon in an attention mechanism, which bridges the gap between traditional sentiment linguistic knowledge and current popular deep learning methods. Second, we develop an improved deep neural network to extract sequential correlation information and text local features by combining bidirectional gated recurrent units with a convolutional neural network, which further enhances the ability of comprehensive text representation learning. With this design, the SDNN model can generate a powerful semantic representation of text to improve the performance of text sentiment classification tasks. Extensive experiments were conducted to evaluate the effectiveness of the proposed SDNN model on two real-world datasets with a binary-sentiment-label and a multi-sentiment-label. The experimental results demonstrated that the SDNN achieved substantially better performance than the strong competitors for text sentiment classification tasks

Lexicon-Enhanced Attention Network Based on Text Representation for Sentiment Classification

Text representation learning is an important but challenging issue for various natural language processing tasks. Recently, deep learning-based representation models have achieved great success for sentiment classification. However, these existing models focus on more semantic information rather than sentiment linguistic knowledge, which provides rich sentiment information and plays a key role in sentiment analysis. In this paper, we propose a lexicon-enhanced attention network (LAN) based on text representation to improve the performance of sentiment classification. Specifically, we first propose a lexicon-enhanced attention mechanism by combining the sentiment lexicon with an attention mechanism to incorporate sentiment linguistic knowledge into deep learning methods. Second, we introduce a multi-head attention mechanism in the deep neural network to interactively capture the contextual information from different representation subspaces at different positions. Furthermore, we stack a LAN model to build a hierarchical sentiment classification model for large-scale text. Extensive experiments are conducted to evaluate the effectiveness of the proposed models on four popular real-world sentiment classification datasets at both the sentence level and the document level. The experimental results demonstrate that our proposed models can achieve comparable or better performance than the state-of-the-art methods

Profiling of T cell repertoire in peripheral blood of patients from type 2 diabetes with complication

Abstract Purpose More than 90% of patients with diabetes worldwide are type 2 diabetes (T2D), which is caused by insulin resistance or impaired producing insulin by pancreatic β cells. T2D and its complications, mainly large cardiovascular (LCV) and kidney (Ne) complications, are the major cause of death in diabetes patients. Recently, the dysregulation of peripheral T cell immune homeostasis was found in most T2D patients. However, the characteristics of T-cell receptors (TCR) remain largely unexplored in T2D patients. Patients and methods Here we investigated the TCR repertoire using high-throughput sequencing in peripheral blood collected from T2D patient with (8 LCV and 7 Ne) or without complications. Results Our analysis of TCR repertoires in peripheral blood samples showed that TCR profiles in T2D patients with complications tended to be single and specific compared to controls, according to the characteristics of TCR repertoire in V-J combination number, diversity, principal component analysis (PCA) and differential genes. And we identified some differentially expressed V-J gene segments and amino acid clonotypes, which had the potential to contribute to distinguishing T2D patient with or without complications. As the progression of the disease, we found that the profiling of TCR repertoire was also differential between T2D patients with LVD and Ne complications base on this pilot analysis. Conclusion This study demonstrated the protentional unique property of TCR repertoire in peripheral blood of T2D patient with and without complications, or T2D patients with LVD and Ne complications, which provided the possibility for future improvements in immune-related diagnosis and therapy for T2D complications

Whole-soil-profile warming does not change microbial carbon use efficiency in surface and deep soils.

The paucity of investigations of carbon (C) dynamics through the soil profile with warming makes it challenging to evaluate the terrestrial C feedback to climate change. Soil microbes are important engines driving terrestrial biogeochemical cycles; their carbon use efficiency (CUE), defined as the proportion of metabolized organic C allocated to microbial biomass, is a key regulator controlling the fate of soil C. It has been theorized that microbial CUE should decline with warming; however, empirical evidence for this response is scarce, and data from deeper soils are particularly scarce. Here, based on soil samples from a whole-soil-profile warming experiment (0 to 1 m, +4 °C) and 18O tracing approach, we examined the vertical variation of microbial CUE and its response to ~3.3-y experimental warming in an alpine grassland on the Qinghai-Tibetan Plateau. Microbial CUE decreased with soil depth, a trend that was primarily controlled by soil C availability. However, warming had limited effects on microbial CUE regardless of soil depth. Similarly, warming had no significant effect on soil C availability, as characterized by extractable organic C, enzyme-based lignocellulose index, and lignin phenol-based ratios of vanillyls, syringyls, and cinnamyls. Collectively, our work suggests that short-term warming does not alter microbial CUE in either surface or deep soils, and emphasizes the regulatory role of soil C availability on microbial CUE

Studies on Low Temperature Performance of Rechargeable MH-Ni Batteries

从合金组成及电解液组份研究了ＭＨ－Ｎｉ电池的低温性能，确定了适宜的合金组成和电解液组成。The Dependence of low temperature performance on the alloy composition andelectrolyte component for rechargeable MH-Ni batteries is studied, the suitable composition of alloyand electrofyte are founds.作者联系地址：国营新乡第七五五厂Author's Address: Stated-run Factory No.755 Xinxiang 45306

Severe pneumonia and pathogenic damage in human airway epithelium caused by Coxsackievirus B4

ABSTRACTCoxsackievirus B4 (CVB4) has one of the highest proportions of fatal outcomes of other enterovirus serotypes. However, the pathogenesis of severe respiratory disease caused by CVB4 infection remains unclear. In this study, 3 of 42 (7.2%, GZ-R6, GZ-R7 and GZ-R8) patients with severe pneumonia tested positive for CVB4 infection in southern China. Three full-length genomes of pneumonia-derived CVB4 were sequenced and annotated for the first time, showing their high nucleotide similarity and clustering within genotype V. To analyze the pathogenic damage caused by CVB4 in the lungs, a well-differentiated human airway epithelium (HAE) was established and infected with the pneumonia-derived CVB4 isolate GZ-R6. The outcome was compared with that of a severe hand-foot-mouth disease (HFMD)-derived CVB4 strain GZ-HFM01. Compared with HFMD-derived CVB4, pneumonia-derived CVB4 caused more intense and rapid disruption of HAE polarity, leading to tight-junction barrier disruption, loss of cilia, and airway epithelial cell hypertrophy. More pneumonia-derived CVB4 were released from the basolateral side of the HAE than HFMD-derived CVB4. Of the 18 cytokines tested, only IL-6 and IL-1b secretion significantly increased on bilateral sides of HAE during the early stage of pneumonia-derived CVB4 infection, while multiple cytokine secretions significantly increased in HFMD-derived CVB4-infected HAE. HFMD-derived CVB4 exhibited stronger neurovirulence in the human neuroblastoma cells SH-SY5Y than pneumonia-derived CVB4, which is consistent with the clinical manifestations of patients infected with these two viruses. This study has increased the depth of our knowledge of severe pneumonia infection caused by CVB4 and will benefit its prevention and treatment

Discovery of a subgenotype of human coronavirus NL63 associated with severe lower respiratory tract infection in China, 2018

Human coronavirus NL63 (HCoV-NL63) is primarily associated with common cold in children, elderly and immunocompromised individuals. Outbreaks caused by HCoV-NL63 are rare. Here we report a cluster of HCoV-NL63 cases with severe lower respiratory tract infection that arose in Guangzhou, China, in 2018. Twenty-three hospitalized children were confirmed to be HCoV-NL63 positive, and most of whom were hospitalized with severe pneumonia or acute bronchitis. Whole genomes of HCoV-NL63 were obtained using next-generation sequencing. Phylogenetic and single amino acid polymorphism analyses showed that this outbreak was associated with two subgenotypes (C3 and B) of HCoV-NL63. Half of patients were identified to be related to a new subgenotype C3. One unique amino acid mutation at I507?L in spike protein receptor binding domain (RBD) was detected, which segregated this subgenotype C3 from other known subgenotypes. Pseudotyped virus bearing the I507?L mutation in RBD showed enhanced entry into host cells as compared to the prototype virus. This study proved that HCoV-NL63 was undergoing continuous mutation and has the potential to cause severe lower respiratory disease in humans