Tele-connection of embodied carbon emissions from industries in China's trade: A complex network analysis.

Regions can meet their development demands through trade, with the attendant environmental costs being shifted to other regions, and carbon emissions emitted from different industries could be transferred over long distances through the increasingly diversified trade network. However, it remains unclear how regional trade leads to the tele-connection and transfer of embodied carbon emissions form industries, and what is the structure and characteristics of the transfer. Thus, multiregional input‒output models and complex network analysis are employed to reveal the tele-connection of carbon emissions from industries in China. The results show that embodied carbon emissions from trade increased by 869.47 million tons during in five years, with North China being the largest outflow area, while the coastal regions being the inflow areas. Moreover, the secondary industry is the highest source of embodied carbon emissions, accounting for 96.68 % of the volume, and the transfer of carbon emissions mainly occurs in North and East China. In carbon emissions networks, North China holds a controlling position, as analysed by degree and strength. The first 23.3%-30% of nodes carry about 62.6%-72.4% of the entire carbon emissions flow, and the network conforms to scale-free features. Centrality further reveals that northern and coastal areas occupy core positions, with interregional carbon flows dominating the critical pathways in the network. The number of clusters evolved from three to four communities during 2012-2017 in the network, demonstrating that the carbon flow network is developing towards multipolarity and modularity. This study underscores the urgency of mitigating carbon emissions in industrial trade by identifying key nodes and cluster structures in emission networks.

Employing graph attention networks to decode psycho-metabolic interactions in Schizophrenia.

Schizophrenia is a severe mental disorder characterized by intricate and underexplored interactions between psychological symptoms and metabolic health, presenting challenges in understanding the disease mechanisms and designing effective treatment strategies. To delve deeply into the complex interactions between mental and metabolic health in patients with schizophrenia, this study constructed a psycho-metabolic interaction network and optimized the Graph Attention Network (GAT). This approach reveals complex data patterns that traditional statistical analyses fail to capture. The results show that weight management and medication management play a central role in the interplay between psychiatric disorders and metabolic health. Furthermore, additional analysis revealed significant correlations between the history of psychiatric symptoms and physical health indicators, as well as the key roles of biochemical markers(e.g., triglycerides and low-density lipoprotein cholesterol), which have not been sufficiently emphasized in previous studies. This highlights the importance of medication management approaches, weight management, psychological treatment, and biomarker monitoring in comprehensive treatment and underscores the significance of the biopsychosocial model. This study is the first to utilize a GNN to explore the interactions between schizophrenia symptoms and metabolic features, providing new insights into understanding psychiatric disorders and guiding the development of more comprehensive treatment strategies for schizophrenia.

Discovering different acupoint combinations of manual or electro-acupuncture to treat chemotherapy-induced nausea and vomiting based on the complex networks analysis.

OBJECTIVES: The aim of this research was to find the acupoint combinations of manual and electro-acupuncture to treat chemotherapy-induced nausea and vomiting via the complex networks analysis. METHODS: We conducted searches using PubMed, ScienceDirect, MEDLINE, Ovid, spring, Wiley, EMBASE, the Chinese biomedicine database, VIP information network, and China National Knowledge Infrastructure from the establishment of the databases to the August, 2023. Information about titles, journals, interventions, and main acupoints was extracted using the self-established "acupoint for prevention CINV data base" powered by EpiData. According to the level of literature evidence and sample size, the clinical trials and weights of the outcome indicators including nausea/vomiting efficiency were combined. After identifying articles, literature processing and complex network analysis were conducted. The degree distribution of each node, the probability distribution of node degree, the node clustering coefficient, and the distance matrix are calculated by software. RESULTS: Of the 4001 screened publications, 489 were eligible after careful selection. Our result showed the acupoints ST36 and PC6 were the most common combination acupoints in both electro and manual acupuncture. In terms of efficiency, ST36, PC6, and CV12 are significantly effective acupoints for manual acupuncture, and the PC6 and ST36 are effective acupoint for electro-acupuncture. CONCLUSIONS: We found that the near-far collocation method has been commonly used for different types of acupuncture treatment in CINV. Zhongwan, Shangwan, and Liangmen have been mainly used as local acupoints, while Neiguan, Hegu, Quchi, Zusanli, Gongsun, TaiChong, and Neiguan have been mainly used as distal acupoints. From the effect analysis, acupuncture treatment of nausea manual acupuncture effect is better; acupuncture treatment of vomiting or electro-acupuncture effect is better.

Evolution of global value-added trade networks and response to risk transmission.

To enhance the international division of labor of developing countries and scientifically respond to the risks and conflicts in the network system, it is important to examine the evolutionary characteristics of the global value-added trade network, simulate the impact of risk shocks, and propose corresponding measures. Based on UNCTAD-Eora value-added trade data, this paper measured and evaluated the evolution characteristics of the global value-added trade network from 2003 to 2018 using the social network analysis and value-added decomposition methods. Then we analyze the impact of risk shocks on the evolution of the trade network using the bootstrap percolation model, building global trade networks and proposing countermeasures. The results show that the global value-added trade network has formed a complex structure and structurally stable distribution pattern, with Germany, China, and the U.S. as the core and the most crucial supports. Among which, China's core position is mainly due to the rapid rise in its export center status. The trade benefits of the three core countries are both competitive and complementary along the "One Belt and One Road". Furthermore, simulations of bootstrap percolation model reveals that the adoption of trade protection policies (caused by poor institutional quality) by different countries will spread and diffuse non-linearly in the network, and the impacts triggered by low-centered countries are comparatively more widespread. By improving defense capabilities and changing the network structure, the "cascading" impacts of trade policy uncertainty can be reduced.

Identifying interactions among air pollutant emissions on diabetes prevalence in Northeast China using a complex network.

BACKGROUND: Low air quality related to ambient air pollution is the largest environmental risk to health worldwide. Interactions between air pollution emissions may affect associations between air pollution exposure and chronic diseases. Therefore, this study aimed to quantify interactions among air pollution emissions and assess their effects on the association between air pollution and diabetes. METHODS: After constructing long-term emission networks for six air pollutants based on data collected from routine monitoring stations in Northeast China, a mutual information network was used to quantify interactions among air pollution emissions. Multiple linear regression analysis was then used to explore the influence of emission interactions on the association between air pollution exposure and the prevalence of diabetes based on data reported from the Northeast Natural Cohort Study in China. RESULTS: Complex network analysis detected three major emission sources in Northeast China located in Shenyang and Changchun. The effects of particulate matter (PM2.5 and PM10) and ground-level ozone (O3) emissions were limited to certain communities but could spread to other communities through emissions in Inner Mongolia. Emissions of sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) significantly influenced other communities. These results indicated that air pollutants in different geographic areas can interact directly or indirectly. Adjusting for interactions between emissions changed associations between air pollution emissions and diabetes prevalence, especially for PM2.5, NO2, and CO. CONCLUSIONS: Complex network analysis is suitable for quantifying interactions among air pollution emissions and suggests that the effects of PM2.5 and NO2 emissions on health outcomes may have been overestimated in previous population studies while those of CO may have been underestimated. Further studies examining associations between air pollution and chronic diseases should consider controlling for the effects of interactions among pollution emissions.

Carbon neutrality along the global value chain: an international embedded carbon network analysis.

Using the value-added method in the global input-output framework, embedded carbon transfers between economies are measured. Then, the international embedded carbon network (IECN) models are constructed and analyzed to reveal the real pattern of the IECN. Influential factors of the IECN are further explored with Quadratic Assignment Procedure (QAP). The main findings are as follows: first, the IECN has the characteristics of small world and scale-free. Developed economies led by the USA have high centrality indicators and always occupy the core position in the network; the network position of China and India has risen significantly with different network characteristics. Second, the subgroup relationships of the carbon network implied by international trade are becoming more and more complex and diverse, economies' participation in the global carbon chain is gradually increasing, and the number of edge nodes are decreasing. Third, the results of QAP analysis show that in addition to the negative impact of geographical distance on embedded carbon transfers between economies, inter-country trade agreement relations, differences in industrial structure, energy intensity, environmental regulation, economic size, and population size have a positive impact on embedded carbon transfers between economies. These findings can provide important practice implications for the global carbon neutrality.

Population Atlas Analysis of Emerging Brain Structural Connections in the Human Fetus.

BACKGROUND: A lack of in utero imaging data hampers our understanding of the connections in the human fetal brain. Generalizing observations from postmortem subjects and premature newborns is inaccurate due to technical and biological differences. PURPOSE: To evaluate changes in fetal brain structural connectivity between 23 and 35 weeks postconceptional age using a spatiotemporal atlas of diffusion tensor imaging (DTI). STUDY TYPE: Retrospective. POPULATION: Publicly available diffusion atlases, based on 60 healthy women (age 18-45 years) with normal prenatal care, from 23 and 35 weeks of gestation. FIELD STRENGTH/SEQUENCE: 3.0 Tesla/DTI acquired with diffusion-weighted echo planar imaging (EPI). ASSESSMENT: We performed whole-brain fiber tractography from DTI images. The cortical plate of each diffusion atlas was segmented and parcellated into 78 regions derived from the Edinburgh Neonatal Atlas (ENA33). Connectivity matrices were computed, representing normalized fiber connections between nodes. We examined the relationship between global efficiency (GE), local efficiency (LE), small-worldness (SW), nodal efficiency (NE), and betweenness centrality (BC) with gestational age (GA) and with laterality. STATISTICAL TESTS: Linear regression was used to analyze changes in GE, LE, NE, and BC throughout gestation, and to assess changes in laterality. The t-tests were used to assess SW. P-values were corrected using Holm-Bonferroni method. A corrected P-value <0.05 was considered statistically significant. RESULTS: Network analysis revealed a significant weekly increase in GE (5.83%/week, 95% CI 4.32-7.37), LE (5.43%/week, 95% CI 3.63-7.25), and presence of SW across GA. No significant hemisphere differences were found in GE (P = 0.971) or LE (P = 0.458). Increasing GA was significantly associated with increasing NE in 41 nodes, increasing BC in 3 nodes, and decreasing BC in 2 nodes. DATA CONCLUSION: Extensive network development and refinement occur in the second and third trimesters, marked by a rapid increase in global integration and local segregation. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Decoupling evolution of economic activity and carbon transfer in China: A multi-level analysis from network perspective.

Economic activities among multiple regions are always accompanied by carbon transfers. Analyzing coupling characteristics of economic activities and carbon transfer linkages based on the supply-demand relationships, can further reveal the networked structures of the multiregional interactions and common development trend of various industries, shedding light on carbon emission governance and high-quality development. This study advances novel coupling network models at the regional and industrial levels, and empirically analyzes the coupling characteristics in China based on the input-output data in 2012, 2015, and 2017. The findings reveal a noticeable decoupling process of economic activities and carbon transfers, but with distinct characteristics at the regional and industrial levels. The widening differences in coupling among provinces indicate increasing regional disparities. The decoupling process at the industrial level is primarily driven by the decreased connectivity in networked carbon transfers, instead of economic activities, reflecting the significant variations of industries' low-carbon development. The carbon decoupling process is notably more pronounced in supply-demand chains associated with export as the final use, compared to those linked with capital formation and final consumption. Analysis of coupling characteristics and the identification of decoupling evolution process enhance our understanding of the relationship between economic activities and carbon transfer, and may provide valuable insights for prioritizing actions and achieving efficient carbon emission reduction.

Tracing global N2O emission mitigation strategies through trade networks.

Nitrous oxide (N2O) is the third most potent greenhouse gas (GHG) and the most important ozone depleting substance. But how global N2O emissions are connected through the interwoven trade network remains unclear. This paper attempts to specifically trace anthropogenic N2O emissions via global trade networks using a multi-regional input-output model and a complex network model. Nearly one quarter of global N2O emissions can be linked to products traded internationally in 2014. The top 20 economies contribute to about 70% of the total embodied N2O emission flows. In terms of the trade embodied emissions classified by sources, cropland-, livestock-, chemistry-, and other industries-related embodied N2O emissions account for 41.9%, 31.2%, 19.9%, and 7.0%, respectively. Clustering structure of the global N2O flow network is revealed by the regional integration of 5 trading communities. Hub economies such as mainland China and the USA are collectors and distributors, and some emerging countries, such as Mexico, Brazil, India, and Russia, also exhibit dominance in different kinds of networks. This study selects the cattle sector to further verify that low production-side emission intensities and trade cooperation can lead to N2O emission reduction. In view of the impact of trade networks on global N2O emissions, achieving N2O emission reduction calls for vigorous international cooperation.

[Regularities of acupoint compatibility and application characteristics of methods of needling and moxibustion in the treatment of ankle sprain based on complex network analysis].

OBJECTIVE: To analyze the compatibility regularities of acupoints and the application characteristics of needling-moxibustionmethods in the treatment of ankle sprain by using complex network technology, so as to provide the basis and treatment ideas. METHODS: The clinical research articles on acupuncture treatment of ankle joint sprain published from November 2011 to November 2021 were retrieved from databases of CNKI, Wanfang Data knowledge service platform, VIP information Chinese journal service platform and PubMed by using key words of "acupuncture""moxibustion" "acupuncture and moxibustion" "ankle injury" "ankle sprain" "injured ankle" and "syndesmotic injuries". After screening these articles according to our inclusion and exclusion criteria, a database of acupuncture treatment of ankle sprain was established. Then, analysis on the occurrence frequency of acupoints and their related meridians, and methods of needling manipulation, and the association rule analysis (quantitative analysis) about the closeness between acupoints, and the degree of support and confidence coefficient were conducted for acquiring the acupoint combinations with higher correlation in the compatibility using Apriori algorithm after modeling (with IBM SPSS Modeler18.0 software). Gephi 0.9.2 software was used to make complex network analysis, for which "k-core hierarchical analysis" and "community analysis" were used as the methods to analyze the network structure of acupoints, and the confidence value was used as the index to measure the importance of acupoints. RESULTS: A total of 201 articles meeting the criteria were collected, including 196 articles in Chinese and 5 in English. A total of 236 acupuncture prescriptions were extracted, involving 61 acupoints, with a total frequency of occurrence being 846. The top 10 acupoints were Ashi point, Kunlun (BL60), Jiexi (ST41), Qiuxu (GB40), Shenmai (BL62), Yanglingquan (GB34), Taixi (KI3), Zhaohai (KI6), Xuanzhong (GB39) and Shangqiu (SP5), with the occurrence frequency being 109, 79, 70, 68, 63, 59, 53, 52, 37 and 34, respectively. The results of descriptive analysis showed that the top 5 meridians were Gallbladder Meridian of Foot-shaoyang, Bladder Meridian of Foot-taiyang, Kidney Meridian of Foot-shaoyin, Stomach Meridian of Foot-yangming and Spleen Meridian of Foot-taiyin, with the frequency being 181, 153, 116, 105 and 53, respectively. Complex network analysis displayed that after "k-core hierarchical analysis" and "Community division", two communities were reserved, mainly involving 15 core acupoints such as Ahshi point, GB40, ST14, BL62, GB34, KI6, BL60, KI3, GB39, Zusanli (ST36), SP5; Taichong (LR3), Zulinqi (GB41), Sanyinjiao (SP6) and Rangu (KI2). The results of association rule analysis showed that the most relevant acupoint combination is "BL60-ST41" (support degree 34.83％), followed by "BL60-KI3" (support degree 26.37%), reflecting the principle of selection of local acupoint for ankle sprain. The therapeutic methods are filiform needle acupuncture, and the reducing technique and uniform reinforcing and reducing manipulation are the most commonly used approaches, but the reinforcing method is rarely used. CONCLUSION: In the treatment of ankle sprain, local acupoints and Ashi points are mainly used, in combination with reducing or uniform reinforcing and reducing manipulations, as well as the method of needling and moxibustion, which provides a good reference for clinical practice.

Global transfer of salinization on irrigated land: Complex network and endogenous structure.

Increasing globalization intensifies land redistribution via global supply chains. Interregional trade not only transfers embodied land but also displaces the negative environmental impact of land degradation from one region to another. This study sheds light on land degradation transfer by focusing on salinization directly whereas previous studies have extensively assessed the land resource embodied in trade. To analyze the relationships among economies under interwoven embodied flows, this study integrates complex network analysis and input-output method to observe the endogenous structure of the transfer system. By focusing on irrigated land with higher crop yields than dryland farming, we make policy recommendations on food safety and proper irrigation. The results of the quantitative analysis show that the total amount of saline and sodic irrigated land embodied in global final demand are 260978.23 and 424291.05 square kilometers respectively. Salt-affected area of irrigated land is imported by not only developed countries but also large developing countries such as Mainland China and India. Exports of embodied salt-affected land in Pakistan, Afghanistan, and Turkmenistan are pressing issues, accounting for nearly 60% of total exports from net exporters worldwide. It is also demonstrated that embodied transfer network has a basic community structure of three groups due to regional preference in agricultural products trade.

External supply risk of agricultural products trade along the Belt and Road under the background of COVID-19.

Agricultural product trade along the Belt and Road (B&R) is an important part of the international food security system, the vulnerabilities of which have been highlighted by the recent COVID-19 pandemic. Based on the complex network analysis, this study analyzes the characteristics of agricultural products trade network along the B&R. It also combines the effects of COVID-19 with the import trade volume of agricultural products in countries along the B&R to build a risk supply model of agricultural products. The results show that: (1) In 2021, the spatial correlation structure of agricultural products trade along the B&R became increasingly sparse, and the network connectivity and density also decreased. (2) The network showed obvious scale-free distribution characteristics and obvious heterogeneity. Five communities emerged under the influence of the core node countries, but the formation of community in 2021 had obvious geopolitical characteristics. (3) Under the influence of the COVID-19 epidemic, the number of countries with medium-risk and high-risk level along the route facing external dependence risk (REDI), import concentration risk (RHHI) and COVID-19 epidemic risk (RRICI) increased in 2021, and the number of countries with extremely low-risk level decreased. (4) The dominant risk type of external supply of agricultural products along the route changed from compound risk type in 2019 to epidemic risk in 2021. Hence, the results can be expected to prevent external risk impact from reducing excessive concentration of agricultural products trade and excessive dependence on the external market.

Assessing Functional Brain Network Dynamics in Dyslexia from fNIRS Data.

Developmental dyslexia is characterized by a deficit of phonological awareness whose origin is related to atypical neural processing of speech streams. This can lead to differences in the neural networks that encode audio information for dyslexics. In this work, we investigate whether such differences exist using functional near-infrared spectroscopy (fNIRS) and complex network analysis. We have explored functional brain networks derived from low-level auditory processing of nonspeech stimuli related to speech units such as stress, syllables or phonemes of skilled and dyslexic seven-year-old readers. A complex network analysis was performed to examine the properties of functional brain networks and their temporal evolution. We characterized aspects of brain connectivity such as functional segregation, functional integration or small-worldness. These properties are used as features to extract differential patterns in controls and dyslexic subjects. The results corroborate the presence of discrepancies in the topological organizations of functional brain networks and their dynamics that differentiate between control and dyslexic subjects, reaching an Area Under ROC Curve (AUC) up to 0.89 in classification experiments.

Health-Related Quality of Life Among Chinese Pregnant Women in the Third Trimester Based on Theory of Unpleasant Symptoms: A Complex Network Analysis.

Health-related quality of life (HRQOL) is the result of complex interactions between many different factors. But few studies to date have explored the structure of HRQOL. This study aimed to investigate the complex inter-relationship between HRQOL and influencing factors using network analysis. In all, 624 Chinese pregnant women in third trimester were recruited through recruiting sampling. We used regularized network analysis to create a complex network. The relationship with mother-in-law was the most central node followed by relationship with partner. We found the comorbidity of anxiety and depressive symptoms using network analysis. Physical- and mental-related quality of life were a "bridge node" connecting psychological factors with physiologic factors. The present network analysis highlights the strong link between relationship with mother-in-law or partner and HRQOL, which is also a unique phenomenon under Chinese culture. This analysis provides key variables for future intervention or improvement of pregnant women' HRQOL.

The Mental Lexicon Features of the Hakka-Mandarin Dialect Bilingual.

The current study investigated the mental lexicon features of the Hakka-Mandarin dialect bilingual from two perspectives: the structural features of lexicons and the relations between lexicons. Experiment one used a semantic fluency task and complex-network analysis to observe the structural features of lexicons. Experiment two used a cross-language long-term repetition priming paradigm to explore the relations between lexicons, with three sub-experiments focusing on conceptual representation, lexical representation, and their relations, respectively. The results from experiment one showed that the dialect bilingual lexicons were small-world in nature, and the D2 (Mandarin) lexicon was better organized than the D1 (Hakka) lexicon. Experiment two found that D1 and D2 might have partially shared conceptual representations, separate lexical form representations, and partially shared lemma representations. Based on the findings, we tentatively proposed a two-layer activation model to simulate the lexicon features of dialect bilingual speakers.

Road networks structure analysis: A preliminary network science-based approach.

Road network studies attracted unprecedented and overwhelming interest in recent years due to the clear relationship between human existence and city evolution. Current studies cover many aspects of a road network, for example, road feature extraction from video/image data, road map generalisation, traffic simulation, optimisation of optimal route finding problems, and traffic state prediction. However, analysing road networks as a complex graph is a field to explore. This study presents comparative studies on the Porto, in Portugal, road network sections, mainly of Matosinhos, Paranhos, and Maia municipalities, regarding degree distributions, clustering coefficients, centrality measures, connected components, k-nearest neighbours, and shortest paths. Further insights into the networks took into account the community structures, page rank, and small-world analysis. The results show that the information exchange efficiency of Matosinhos is 0.8, which is 10 and 12.8% more significant than that of the Maia and Paranhos networks, respectively. Other findings stated are: (1) the studied road networks are very accessible and densely linked; (2) they are small-world in nature, with an average length of the shortest pathways between any two roads of 29.17 units, which as found in the scenario of the Maia road network; and (3) the most critical intersections of the studied network are 'Avenida da Boavista, 4100-119 Porto (latitude: 41.157944, longitude: - 8.629105)', and 'Autoestrada do Norte, Porto (latitude: 41.1687869, longitude: - 8.6400656)', based on the analysis of centrality measures.

The spatiotemporal patterns and network characteristics of emissions embodied in the international trade of livestock products.

Livestock production is greenhouse gas (GHG) emission intensive, and thus the increasing international trade of livestock products in recent decades has resulted in increased embodied emissions. Considering the varying emission intensity in production in different countries and the expected further increase in livestock product trade in the future, it becomes crucial to understand the spatial and temporal dynamics of such embodied GHG emissions for climate change mitigation in the livestock sector. In this study, we aimed to address such gaps and analyzed the spatiotemporal patterns and network characteristics of GHG emissions embodied in the international trade of seven major categories of livestock products among 228 world economies during 1986-2017. The results showed that the total volume of GHG emissions embodied in livestock product trade reached 92.0 MT in 2017, accounting for 2.6% of the total emissions from livestock production. Sheep meat has replaced cattle meat as the major contributor to embodied emissions. In 2017, the largest flows of embodied emissions were within Europe, followed by the flows from Oceania to Asia. The fluxes in intra-upper middle and intra-high-income economies accounted for most of the total embodied emissions. Although the global average emission intensity of livestock production declined in these four decades, the trade flows from high to low emission intensity economies increased, especially for cattle and sheep meat. This resulted in an overall increase of contribution from the global livestock trade in GHG emissions from the global livestock sector. Therefore, effective measures and policies must be designed from both consumption and production perspectives to ensure proper accounting of these embodied emissions and maximize the reduction potential for a sustainable food system transition.

[Material basis and molecular mechanism of Angelicae Sinensis Radix in activating blood:based on computer-aided drug design].

Angelicae Sinensis Radix excels in activating blood, but the scientific mechanism has not been systematically analyzed, thus limiting the development of the medicinal. This study employed the computer-aided drug design methods, such as structural similarity-based target reverse prediction, complex network analysis, molecular docking, binding free energy calculation, cluster analysis, and ADMET(absorption, distribution, metabolism, excretion, toxicity) calculation, and enzyme activity assay in vitro, to explore the components and mechanism of Angelicae Sinensis Radix in activating blood. Target reverse prediction and complex network analysis yielded 40 potential anticoagulant targets of the medicinal. Gene Ontology(GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis indicated that the targets mainly acted on the complement and coagulation cascade signaling pathway to exert the anticoagulant function. Among them, the key enzymes thrombin(THR) and coagulation factor Xa(FXa) in coagulation cascade and thrombosis were the drug targets for thromboembolic diseases. At the same time, molecular docking and cluster analysis showed that the medicinal had high selectivity for FXa. According to binding free energy score, 8 potential active components were selected for enzyme activity assay in vitro. The results demonstrated that 8 components inhibited THR and FXa, and the inhibition was stronger on FXa than on THR. The pharmacophore model of 8 active compounds was constructed, which suggested that the components had the common pharmacophore AAHH. The ADMET calculation result indicated that they had good pharmacokinetic properties and were safe. Based on target reverse prediction, complex network analysis, molecular docking and binding free energy calculation, anticoagulant activity in vitro, spatial binding conformation of molecules and targets, pharmacophore model construction, and ADMET calculation, this study preliminarily clarified the material basis and molecular mechanism of Angelicae Sinensis Radix in activating blood from the perspective of big data, and calculated the pharmacology and toxicology parameters of the active components. Our study, for the first time, revealed that the medicinal had obvious selectivity and pertinence for different coagulation proteins, reflecting the unique effect of different Chinese medicinals and the biological basis. Therefore, this study can provide clues for precision application of Angelicae Sinensis Radix and the development of the blood-activating components with modern technology.

Cold Chain Food and COVID-19 Transmission Risk: From the Perspective of Consumption and Trade.

Since the outbreak of the coronavirus disease 2019 (COVID-19), political and academic circles have focused significant attention on stopping the chain of COVID-19 transmission. In particular outbreaks related to cold chain food (CCF) have been reported, and there remains a possibility that CCF can be a carrier. Based on CCF consumption and trade matrix data, here, the "source" of COVID-19 transmission through CCF was analyzed using a complex network analysis method, informing the construction of a risk assessment model reflecting internal and external transmission dynamics. The model included the COVID-19 risk index, CCF consumption level, urbanization level, CCF trade quantity, and others. The risk level of COVID-19 transmission by CCF and the dominant risk types were analyzed at national and global scales as well as at the community level. The results were as follows. (1) The global CCF trade network is typically dominated by six core countries in six main communities, such as Indonesia, Argentina, Ukraine, Netherlands, and the USA. These locations are one of the highest sources of risk for COVID-19 transmission. (2) The risk of COVID-19 transmission by CCF in specific trade communities is higher than the global average, with the Netherlands-Germany community being at the highest level. There are eight European countries (i.e., Netherlands, Germany, Belgium, France, Spain, Britain, Italy, and Poland) and three American countries (namely the USA, Mexico, and Brazil) facing a very high level of COVID-19 transmission risk by CCF. (3) Of the countries, 62% are dominated by internal diffusion and 23% by external input risk. The countries with high comprehensive transmission risk mainly experience risks from external inputs. This study provides methods for tracing the source of virus transmission and provides a policy reference for preventing the chain of COVID-19 transmission by CCF and maintaining the security of the global food supply chain.

[Analysis on rules of acupoint compatibility and application characteristics in acupuncture treatment of migraine based on complex network technique].

OBJECTIVE: To analyze the compatible rules of acupoints in the treatment of migraine with acupuncture and moxibustion based on complex network technique so as to provide a reference for composing best acupoint recipes. METHODS: Clinical papers about acupuncture treatment of migraine published from January of 2010 to October of 2020 were searched from Chinese and English databases including CNKI, Wanfang, VIP and Pubmed by using keywords of acupuncture, moxibustion and migraine. According to our inclusive and exclusive criteria, the collected papers were screened out to set up a database. The SPSS Modeler 18.0 software was used to analyze the association rules of acupoints, and the Gephi 0.9.2 software was used to conduct a complex network analysis about the compatibility rules of acupoints and their application characteristics of moxibustion and needling methods in the treatment of migraine. RESULTS: In the end, 572 articles meeting the conclusive criteria were selected, and a total of 1 091 acupoint prescriptions for the treatment of migraine were extracted, including 230 acupoints with a total appea-rance frequency of 7 902. Those acupoints most frequently used were mainly attributed to the Gallbladder Meridian, with Fengchi (GB20) being the highest in the cumulative frequency. The association rule analysis showed that the highest supporting degree acupoints was GB20-Taiyang(EX-HN5). The highest levels of confidence were EX-HN5-Touwei(ST8), GB20-Baihui(GV20), and GB20-ST8. The analysis of complex network topology showed that a total of 17 acupoints including GB20, EX-HN5, Shuaigu(GB8), Taichong(LR3), GV20, Ashi point, etc. were the core node acupoints for acupuncture treatment of migraine. CONCLUSION: In the treatment of migraine, the acupoints selected are mainly distributed in the head region. When the specific acupoints chosen, the five Shu acupoints, Yuan (source) acupoints and the confluent acupoints of eight meridians are frequently used. In terms of composing acupoint recipes, the acupoints in the local and distant part of the body are often used in combination. These outcomes may have a certain guiding significance for clinical treatment of migraine.