Numerical Air Quality Forecast over Eastern China: Development, Uncertainty and Future

Air pollution is severely focused due to its distinct effect on climate change and adverse effect on human health, ecological system, etc. Eastern China is one of the most polluted areas in the world and many actions were taken to reduce air pollution. Numerical forecast of air quality was proved to be one of the effective ways to help to deal with air pollution. This chapter will present the development, uncertainty and thinking about the future of the numerical air quality forecast emphasized in eastern China region. Brief history of numerical air quality modeling including that of Shanghai Meteorological Service (SMS) was reviewed. The operational regional atmospheric environmental modeling system for eastern China (RAEMS) and its performance on forecasting the major air pollutants over eastern China region was introduced. Uncertainty was analyzed meanwhile challenges and actions to be done in the future were suggested to provide better service of numerical air quality forecast

A Study on the Radiosensitivity of Radiation-Induced Lung Injury at the Acute Phase Based on Single-Cell Transcriptomics

Background and AimsRadiation-induced lung injury (RILI) is the most common complication associated with chest tumors, such as lung and breast cancers, after radiotherapy; however, the pathogenic mechanisms are unclear. Single-cell RNA sequencing has laid the foundation for studying RILI at the cellular microenvironmental level. This study focused on changes during the acute pneumonitis stage of RILI at the cellular microenvironmental level and investigated the interactions between different cell types.MethodsAn acute RILI model in mice and a single-cell transcriptional library were established. Intercellular communication networks were constructed to study the heterogeneity and intercellular interactions among different cell types.ResultsA single-cell transcriptome map was established in a mouse model of acute lung injury. In total, 18,500 single-cell transcripts were generated, and 10 major cell types were identified. The heterogeneity and radiosensitivity of each cell type or subtype in the lung tissues during the acute stage were revealed. It was found that immune cells had higher radiosensitivity than stromal cells. Immune cells were highly heterogeneous in terms of radiosensitivity, while some immune cells had the characteristics of radiation resistance. Two groups of radiation-induced Cd8+Mki67+ T cells and Cd4+Cxcr6+ helper T cells were identified. The presence of these cells was verified using immunofluorescence. The ligand-receptor interactions were analyzed by constructing intercellular communication networks. These explained the origins of the cells and revealed that they had been recruited from endothelial cells to the inflammatory site.ConclusionsThis study revealed the heterogeneity of in vivo radiosensitivity of different cell types in the lung at the initial stage post irradiatio

A comprehensive review of circRNA: from purification and identification to disease marker potential

Circular RNA (circRNA) is an endogenous noncoding RNA with a covalently closed cyclic structure. Based on their components, circRNAs are divided into exonic circRNAs, intronic circRNAs, and exon-intron circRNAs. CircRNAs have well-conserved sequences and often have high stability due to their resistance to exonucleases. Depending on their sequence, circRNAs are involved in different biological functions, including microRNA sponge activity, modulation of alternative splicing or transcription, interaction with RNA-binding proteins, and rolling translation, and are a derivative of pseudogenes. CircRNAs are involved in the development of a variety of pathological conditions, such as cardiovascular diseases, diabetes, neurological diseases, and cancer. Emerging evidence has shown that circRNAs are likely to be new potential clinical diagnostic markers or treatments for many diseases. Here we describe circRNA research methods and biological functions, and discuss the potential relationship between circRNAs and disease progression

2-Deoxyglucose alleviates migraine-related behaviors by modulating microglial inflammatory factors in experimental model of migraine

BackgroundTargeting metabolic pathways has emerged as a new migraine treatment strategy as researchers realize the critical role metabolism plays in migraine. Activated inflammatory cells undergo metabolic reprogramming and rely on glycolysis to function. The objective of this study was to investigate the glycolysis changes in the experimental model of migraine and the effect of glycolysis inhibitor 2-Deoxy-D-glucose (2-DG) in the pathophysiology of migraine.MethodsWe used a rat model of migraine that triggered migraine attacks by applying inflammatory soup (IS) to the dura and examined changes in glycolysis. 2-DG was used to inhibit glycolysis, and the effects of 2-DG on mechanical ectopic pain, microglial cell activation, calcitonin gene-related peptides (CGRP), c-Fos, and inflammatory factors induced by inflammatory soup were observed. LPS stimulated BV2 cells to establish a model in vitro to observe the effects of 2-DG on brain-derived neurotrophic factor (BDNF) after microglia activation.ResultsIn the experimental model of migraine, key enzymes involved in glycolysis such as phosphofructokinase platelet (PFKP), hexokinase (HK2), hypoxia inducible factor-1α (HIF-1α), lactate dehydrogenase (LDH) and pyruvate kinase (PKM2) were expressed in the medullary dorsal horn. While the expression of electronic respiratory transport chain complex IV (COXIV) decreased. There were no significant changes in glucose 6-phosphate dehydrogenase (G6PD), a key enzyme in the pentose phosphate pathway. The glycolysis inhibitor 2-DG alleviated migraine-like symptoms in an experimental model of migraine, reduced the release of proinflammatory cytokines caused by microglia activation, and decreased the expression of CGRP and c-Fos. Further experiments in vitro demonstrated that glycolysis inhibition can reduce the release of Iba-1/proBDNF/BDNF and inhibit the activation of microglia.ConclusionThe migraine rat model showed enhanced glycolysis. This study suggests that glycolytic inhibitor 2-DG is an effective strategy for alleviating migraine-like symptoms. Glycolysis inhibition may be a new target for migraine treatment

Light-Reinforced Key Intermediate for Anticoking To Boost Highly Durable Methane Dry Reforming over Single Atom Ni Active Sites on CeO₂.

Dry reforming of methane (DRM) has been investigated for more than a century; the paramount stumbling block in its industrial application is the inevitable sintering of catalysts and excessive carbon emissions at high temperatures. However, the low-temperature DRM process still suffered from poor reactivity and severe catalyst deactivation from coking. Herein, we proposed a concept that highly durable DRM could be achieved at low temperatures via fabricating the active site integration with light irradiation. The active sites with Ni-O coordination (NiSA/CeO2) and Ni-Ni coordination (NiNP/CeO2) on CeO2, respectively, were successfully constructed to obtain two targeted reaction paths that produced the key intermediate (CH3O*) for anticoking during DRM. In particular, the operando diffuse reflectance infrared Fourier transform spectroscopy coupling with steady-state isotopic transient kinetic analysis (operando DRIFTS-SSITKA) was utilized and successfully tracked the anticoking paths during the DRM process. It was found that the path from CH3* to CH3O* over NiSA/CeO2 was the key path for anticoking. Furthermore, the targeted reaction path from CH3* to CH3O* was reinforced by light irradiation during the DRM process. Hence, the NiSA/CeO2 catalyst exhibits excellent stability with negligible carbon deposition for 230 h under thermo-photo catalytic DRM at a low temperature of 472 °C, while NiNP/CeO2 shows apparent coke deposition behavior after 0.5 h in solely thermal-driven DRM. The findings are vital as they provide critical insights into the simultaneous achievement of low-temperature and anticoking DRM process through distinguishing and directionally regulating the key intermediate species

C1-C2 alkyl aminiums in urban aerosols: Insights from ambient and fuel combustion emission measurements in the Yangtze River Delta region of China

We measured low molar-mass alkyl aminiums (methylaminium, dimethylaminium, ethylaminium and diethylaminium) in urban aerosols in the Yangtze River Delta region of eastern China in August 2014 and from November 2015 to May 2016. After examining artifact formation on sample filters, methylaminium, dimethylaminium and ethylaminium concentrations were quantified. The three C1-C2 aminiums exhibited a unimodal size distribution that maximized between 0.56 and 1.0 μm. Their concentrations in PM2.5 were 5.7 ± 3.2 ng m−3, 7.9 ± 5.4 ng m−3 and 20.3 ± 16.6 ng m−3, respectively, with higher concentrations during the daytime and in warm seasons. On new particle growth days, amine uptake to particles larger than 56 nm was barely enhanced. The molar ratios of individual aminium/NH4+ in PM2.5 were on the order of 10−4 and 10−3. Aminiums were thus far less to out-compete ammonium (NH4+) in neutralizing acidic species in particle sizes down to 56 nm. Abundant nitrate (NO3−/SO42− molar ratio = ∼3) and its correlation to methylaminium and ethylaminium implied that nitrate might be more important aminium salt than sulfate in urban aerosols of this area. Direct measurement of particle-phase amine emission from coal and biomass burning showed that coal burning is an important atmospheric amine source, considering coal burning is top-ranked particulate matter source in China

Expression Profiling and Proteomic Analysis of JIN Chinese Herbal Formula in Lung Carcinoma H460 Xenografts

Many traditional Chinese medicine (TCM) formulae have been used in cancer therapy. The JIN formula is an ancient herbal formula recorded in the classic TCM book Jin Kui Yao Lue (Golden Chamber). The JIN formula significantly delayed the growth of subcutaneous human H460 xenografted tumors in vivo compared with the growth of mock controls. Gene array analysis of signal transduction in cancer showed that the JIN formula acted on multiple targets such as the mitogen-activated protein kinase, hedgehog, and Wnt signaling pathways. The coformula treatment of JIN and diamminedichloroplatinum (DDP) affected the stress/heat shock pathway. Proteomic analysis showed 36 and 84 differentially expressed proteins between the mock and DDP groups and between the mock and JIN groups, respectively. GoMiner analysis revealed that the differentially expressed proteins between the JIN and mock groups were enriched during cellular metabolic processes, and so forth. The ones between the DDP and mock groups were enriched during protein-DNA complex assembly, and so forth. Most downregulated proteins in the JIN group were heat shock proteins (HSPs) such as HSP90AA1 and HSPA1B, which could be used as markers to monitor responses to the JIN formula therapy. The mechanism of action of the JIN formula on HSP proteins warrants further investigation

A Comparative Analysis of 3D Printers and Printing Materials for Art Designers in China

In China, the group composed of art designers is becoming one of the biggest communities using 3D printing technology for their work. By analysis of 3D printing related technology, performance and cost performance factors of commonly used 3D printers and printing materials, this thesis aims to provide them with some unique references and suggestions for their selecting and purchasing 3D printers and printing materials. The research method used in this thesis includes the method of literature induction, the method of comparative analysis and the questionnaire method. In addition, the writer's experience and awareness obtained from the personal practical training are also fully demonstrated in the research of the thesis. Based on the status analysis of 3D printing in China, the writer chooses the Chinese art designers as the object to assert the importance of 3D printing to their design work. The writer divides all art design fields into 14 different specialties according to the departments set in China’s most authoritative universities and then analyzes the professional characteristics of each specialty’s work to find out their unique requirements and key concerns for art designers from each specialty when selecting and using 3D printers and materials. Through the analysis of the advantages and disadvantages in performance such as printing accuracy, printing speed, printable materials and printing volume of the 3D printers as well as the colors, tensile strength and flexibility of the materials mostly found in Chinese market with good reputation, the author offers some recommendations for art designers from different professions in their selection and purchase of 3D printers and materials. This thesis can also be valuable for manufacturers to design and build new professional 3D printers and printing materials for art designers in the future

Using Trajectory Clusters to Define the Most Relevant Features for Transient Stability Prediction Based on Machine Learning Method

To achieve rapid real-time transient stability prediction, a power system transient stability prediction method based on the extraction of the post-fault trajectory cluster features of generators is proposed. This approach is conducted using data-mining techniques and support vector machine (SVM) models. First, the post-fault rotor angles and generator terminal voltage magnitudes are considered as the input vectors. Second, we construct a high-confidence dataset by extracting the 27 trajectory cluster features obtained from the chosen databases. Then, by applying a filter–wrapper algorithm for feature selection, we obtain the final feature set composed of the eight most relevant features for transient stability prediction, called the global trajectory clusters feature subset (GTCFS), which are validated by receiver operating characteristic (ROC) analysis. Comprehensive simulations are conducted on a New England 39-bus system under various operating conditions, load levels and topologies, and the transient stability predicting capability of the SVM model based on the GTCFS is extensively tested. The experimental results show that the selected GTCFS features improve the prediction accuracy with high computational efficiency. The proposed method has distinct advantages for transient stability prediction when faced with incomplete Wide Area Measurement System (WAMS) information, unknown operating conditions and unknown topologies and significantly improves the robustness of the transient stability prediction system