Comparisons between Chinese and English metaphorical metal words

Uma quantidade abundante de palavras metafóricas em metal pode ser observada tanto em chinês como em inglês, que são bem desenvolvidos, amplamente utilizados, prontos para comparações. Nós aplicamos a simples análise estatística como nosso método principal para revelar caracteres estruturais e semânticos, referindo-se à coagulação, estrutura interna e propriedade para o primeiro, e através de como os sentidos se espalham, como os significados se concentram e a cor dos significados para o segundo. Através da análise, descobrimos que existem semelhanças surpreendentes em ambas as línguas e as semelhanças superam as diferenças, o que é um sintoma geral em relação a todas as comparações aqui realizadas, revelando, em certa medida, a coletividade cognitiva humana. Mas, em regiões mais específicas, verificam-se diferenças que vão ao encontro da diversidade humana.Abundant amount of Metaphorical Metal Words can be observed in both Chinese and English, which are well-developed and widely used, ready for comparisons. We applied to simple statistic analysis as our main research method in revealing structural and semantic characters, referring to coagulation, internal structure, and property for the former, and through the way senses being scattered in dictionaries, the part bearing metaphorical meanings and the concentration of meanings for the latter. Through analysis, we discover that astonishing similarities exist in both languages and similarities outweigh differences, which is an overall symptom concerning all comparisons held, revealing human cognitive collectiveness to a certain extent. But in more specific regions, differences do appear, reflecting the varieties in mankind.

Autophagy regulates inflammation in intracerebral hemorrhage: Enemy or friend?

Intracerebral hemorrhage (ICH) is the second-largest stroke subtype and has a high mortality and disability rate. Secondary brain injury (SBI) is delayed after ICH. The main contributors to SBI are inflammation, oxidative stress, and excitotoxicity. Harmful substances from blood and hemolysis, such as hemoglobin, thrombin, and iron, induce SBI. When cells suffer stress, a critical protective mechanism called “autophagy” help to maintain the homeostasis of damaged cells, remove harmful substances or damaged organelles, and recycle them. Autophagy plays a critical role in the pathology of ICH, and its function remains controversial. Several lines of evidence demonstrate a pro-survival role for autophagy in ICH by facilitating the removal of damaged proteins and organelles. However, many studies have found that heme and iron can aggravate SBI by enhancing autophagy. Autophagy and inflammation are essential culprits in the progression of brain injury. It is a fascinating hypothesis that autophagy regulates inflammation in ICH-induced SBI. Autophagy could degrade and clear pro-IL-1β and apoptosis-associated speck-like protein containing a CARD (ASC) to antagonize NLRP3-mediated inflammation. In addition, mitophagy can remove endogenous activators of inflammasomes, such as reactive oxygen species (ROS), inflammatory components, and cytokines, in damaged mitochondria. However, many studies support the idea that autophagy activates microglia and aggravates microglial inflammation via the toll-like receptor 4 (TLR4) pathway. In addition, autophagy can promote ICH-induced SBI through inflammasome-dependent NLRP6-mediated inflammation. Moreover, some resident cells in the brain are involved in autophagy in regulating inflammation after ICH. Some compounds or therapeutic targets that regulate inflammation by autophagy may represent promising candidates for the treatment of ICH-induced SBI. In conclusion, the mutual regulation of autophagy and inflammation in ICH is worth exploring. The control of inflammation by autophagy will hopefully prove to be an essential treatment target for ICH

Distinct resting-state effective connectivity of large-scale networks in first-episode and recurrent major depression disorder: evidence from the REST-meta-MDD consortium

IntroductionPrevious studies have shown disrupted effective connectivity in the large-scale brain networks of individuals with major depressive disorder (MDD). However, it is unclear whether these changes differ between first-episode drug-naive MDD (FEDN-MDD) and recurrent MDD (R-MDD).MethodsThis study utilized resting-state fMRI data from 17 sites in the Chinese REST-meta-MDD project, consisting of 839 patients with MDD and 788 normal controls (NCs). All data was preprocessed using a standardized protocol. Then, we performed a granger causality analysis to calculate the effectivity connectivity (EC) within and between brain networks for each participant, and compared the differences between the groups.ResultsOur findings revealed that R-MDD exhibited increased EC in the fronto-parietal network (FPN) and decreased EC in the cerebellum network, while FEDN-MDD demonstrated increased EC from the sensorimotor network (SMN) to the FPN compared with the NCs. Importantly, the two MDD subgroups displayed significant differences in EC within the FPN and between the SMN and visual network. Moreover, the EC from the cingulo-opercular network to the SMN showed a significant negative correlation with the Hamilton Rating Scale for Depression (HAMD) score in the FEDN-MDD group.ConclusionThese findings suggest that first-episode and recurrent MDD have distinct effects on the effective connectivity in large-scale brain networks, which could be potential neural mechanisms underlying their different clinical manifestations

Wildfire CO₂ Emissions in the Conterminous United States from 2015 to 2018 as Estimated by the WRF-Chem Assimilation System from OCO-2 XCO₂ Retrievals

Wildfires are becoming more frequent due to the global climate change. Large amounts of greenhouse gases emitted by wildfires can lead to increases in extreme climate events. Accurately estimating the greenhouse gas carbon dioxide (CO2) emissions from wildfires is important for mitigation of climate change. In this paper, we develop a novel method to estimate wildfire CO2 emissions from the relationship between local CO2 emissions and XCO2 anomalies. Our method uses the WRF-Chem assimilation system from OCO-2 XCO2 retrievals which coupled with Data Assimilation Research Testbed (DART). To validate our results, we conducted three experiments evaluating the wildfire CO2 emissions over the conterminous United States. The four-month average wildfire emissions from July to October in 2015∼2018 were estimated at 4.408 Tg C, 1.784 Tg C, 1.514 Tg C and 2.873 Tg C, respectively. Compared to the average of established inventories CT2019B, FINNv1.5 and GFASv1.2 fire emissions, our estimates fall within one standard deviation, except for 2017 due to lacking of OCO-2 XCO2 retrievals. These results suggest that the regional carbon assimilation system, such as WRF-Chem/DART, using OCO-2 XCO2 retrievals has a great potential for accurately tracking regional wildfire emissions

Analysis of the Clinical Efficacy and Molecular Mechanism of Xuefu Zhuyu Decoction in the Treatment of COPD Based on Meta-Analysis and Network Pharmacology

Background. Chronic obstructive pulmonary disease (COPD) is becoming a major public health burden worldwide. It is urgent to explore more effective and safer treatment strategy for COPD. Notably, Xuefu Zhuyu Decoction (XFZYD) is widely used to treat respiratory system diseases, including COPD, in China. Objective. This study is aimed at comprehensively evaluating the therapeutic effects and molecular mechanism of XFZYD on COPD. Methods. Original clinical studies were searched from eight literature databases. Meta-analysis was conducted using the Review Manager software (version 5.4.1). Network pharmacology and molecular docking experiments were utilized to explore the mechanisms of action of XFZYD. Results. XFZYD significantly enhanced the efficacy of clinical treatment and improved the pulmonary function and hypoventilation of COPD patients. In addition, XFZYD significantly improved the hypercoagulability of COPD patients. The subgroup analysis suggested that XFZYD exhibited therapeutic effects on both stable and acute exacerbation of COPD. XFZYD exerted its therapeutic effects on COPD through multicomponent, multitarget, and multipathway characteristics. The intervention of the PI3K-AKT pathway may be the critical mechanism. Conclusion. The application of XFZYD based on symptomatic relief and supportive treatment is a promising clinical decision. More preclinical and clinical studies are still needed to evaluate the safety and therapeutic effects of long-term use of XFZYD on COPD

A Feasible Community Detection Algorithm for Multilayer Networks

As a more complicated network model, multilayer networks provide a better perspective for describing the multiple interactions among social networks in real life. Different from conventional community detection algorithms, the algorithms for multilayer networks can identify the underlying structures that contain various intralayer and interlayer relationships, which is of significance and remains a challenge. In this paper, aiming at the instability of the label propagation algorithm (LPA), an improved label propagation algorithm based on the SH-index (SH-LPA) is proposed. By analyzing the characteristics and deficiencies of the H-index, the SH-index is presented as an index to evaluate the importance of nodes, and the stability of the SH-LPA algorithm is verified by a series of experiments. Afterward, considering the deficiency of the existing multilayer network aggregation model, we propose an improved multilayer network aggregation model that merges two networks into a weighted single-layer network. Finally, considering the influence of the SH-index and the weight of the edge of the weighted network, a community detection algorithm (MSH-LPA) suitable for multilayer networks is exhibited in terms of the SH-LPA algorithm, and the superiority of the mentioned algorithm is verified by experimental analysis

Exploration of the Potential Targets and Molecular Mechanism of Carthamus tinctorius L. for Liver Fibrosis Based on Network Pharmacology and Molecular Docking Strategy

Carthamus tinctorius L. (Honghua, HH) is an herbal medicine and functional food widely used to treat chronic liver diseases, including liver fibrosis. By using network pharmacology and molecular docking experiments, the present study aims to determine the bioactive components, potential targets, and molecular mechanisms of HH for treating liver fibrosis. The components of HH were screened from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and literature, and the SwissTargetPrediction database was used to predict the treatment targets of HH. Genecards and DisGeNET databases contained targets for liver fibrosis, and the STRING database provided networks of protein–protein interactions. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the Database of Annotation, Visualization and Integrated Discovery. The protein–protein interactive network and drug–component–major target–pathway interactive network were visualized and analyzed by Cytoscape software. Finally, Autodock Vina and Discovery Studio software were used for molecular docking Validation. A total of 23 candidate bioactive compounds with 187 treatment targets of HH were acquired from the databases and literature. A total of 121 overlapping targets between HH and liver fibrosis were found to provide the molecular basis for HH on liver fibrosis. Quercetin, beta carotene, and lignan were identified as key components with targeting to ESR1, PIK3CA, and MTOR. HH is engaged in the intervention of various signaling cascades associated with liver fibrosis, such as PI3K/AKT/mTOR pathway, MAPK pathway, and PPAR pathway. In conclusion, HH treats liver fibrosis through multi-component, multi-target, and multi-pathway mechanisms

Early mapping of winter wheat in Henan province of China using time series of Sentinel-2 data

Accurate mapping of winter wheat in its early stages is crucial for crop growth monitoring and crop yield forecasting. However, early mapping of winter wheat using remotely sensed data is challenging because remote sensing observations can only be used for a part of the growth period. In this study, a framework was proposed for early season mapping of winter wheat using spectral and temporal information of Sentinel-2 images. First, time series of temporal and spectral features were derived using Whittaker smoothing. Subsequently, sensitivities of different parameters (i.e. input features, time interval, and length of time-series data) to early mapping were analyzed. Finally, early maps of winter wheat were generated based on optimal parameters. Results show that the earliest identifiable timing was delayed as the time interval of the time series increased. Winter wheat can be mapped in the early overwintering period (5 months before harvest) with an overall accuracy of 0.91, which is comparable to that of post-season mapping (0.94). In addition, the misclassification in early mapping was caused by uneven sample spatial patterns, natural conditions, and planting management; however, most errors can be gradually amended during the green-up and jointing periods, and the overall accuracy remained stable after the jointing stage. This study demonstrates that it is feasible to implement large-scale early mapping of winter wheat using satellite observations. The proposed approach potentially provides a reference for early mapping of other crop types in agricultural regions worldwide.</p