Network-Based Driving Force of National Economic Development: A Social Capital Perspective.

Network science has been widely applied in theoretical and empirical studies of global value chain (GVC), and many related articles have emerged, forming many more mature and complete analytical frameworks. Among them, the GVC accounting method based on complex network theory is different from the mainstream economics in both research angle and content. In this paper, we build up global industrial value chain network (GIVCN) models based on World Input-Output Database, introduce the theoretical framework of Social Capital, and define the network-based indicators with economic meanings. Second, we follow the econometric framework to analyze the hypothesis and test whether it is true. Finally, we study how the three types of capital constituted by these indicators interact with each other, and discuss their impact on the social capital (economic development level, i.e., GDP). The results prove that the structural capital (industrial status) has a positive impact on the social capital; the relational capital (industrial correlation) has a positive impact on both social capital and structural capital; the cognitive capital (industrial structure) has a small impact on the social capital, structural capital, and relational capital.

Analyzing the Co-Competition Mechanism of High-Tech Park from the Perspective of Complex Socioeconomic Network.

The fusion of "innovation theory" and "ecology" gave birth to a large number of studies on "innovation ecology", which mainly studies how to build an industrial ecological chain at the regional level, focusing on self-evolution, achieving ecological balance, and enabling the regional economy to take the path of sustainable innovation. This type of research borrows a lot of concepts from ecology and very vividly describes the competition and cooperation relationships formed by various agents in the innovation system, laying a good foundation for qualitative analysis of the inherent dynamics of innovation development. However, many studies focus on the analogous description of ecosystems and economic systems, lacking scientifically and rigorously quantitative empirical research as support. This paper uses network-based indicators such as degree, cluster coefficient, and betweenness centrality to measure the function and position of high-tech enterprises in the Z-Park of a business environment. In this way, we clarify the socioeconomic meaning of the topological structure of the regional innovation system. On this basis, it provides theoretical references for regional innovation development and sustainable development policy formulation.

Nestedness-Based Measurement of Evolutionarily Stable Equilibrium of Global Production System.

A nested structure is a structural feature that is conducive to system stability formed by the coevolution of biological species in mutualistic ecosystems The coopetition relationship and value flow between industrial sectors in the global value chain are similar to the mutualistic ecosystem in nature. That is, the global economic system is always changing to form one dynamic equilibrium after another. In this paper, a nestedness-based analytical framework is used to define the generalist and specialist sectors for the purpose of analyzing the changes in the global supply pattern. We study why the global economic system can reach a stable equilibrium, what the role of different sectors play in the steady status, and how to enhance the stability of the global economic system. In detail, the domestic trade network, export trade network and import trade network of each country are extracted. Then, an econometric model is designed to analyze how the microstructure of the production system affects a country's macroeconomic performance.

Structural Characteristics and Evolutionary Drivers of Global Virtual Water Trade Networks: A Stochastic Actor-Oriented Model for 2000-2015.

The globalization of trade has caused tremendous pressure on water resources globally, and a virtual water trade provides a new perspective on global freshwater sharing and water sustainability. No study has yet explored the structural characteristics and drivers of the evolution of global virtual water trade networks from a network structure evolution perspective. This paper aims to fill this critical gap by developing a research framework to explore how endogenous network structures and external factors have influenced the evolution of virtual water trade networks. We constructed virtual water trade networks for 62 countries worldwide from 2000 to 2015 and used an innovative combination of multi-regional input-output data and stochastic actor-oriented models for analytical purposes. Our results support the theoretical hypothesis of ecologically unequal exchange and trade drivers, arguing that virtual water flows from less developed countries to developed countries under global free trade and that unequal trade patterns lead to excessive consumption of virtual water in less developed countries. The results partially support the theoretical content of water endowment and traditional gravity models, finding that trade networks are expanding to farther and larger markets, confirming that national water scarcity levels do not impact the evolution of virtual water trade networks. Finally, we point out that meritocratic links, path dependence, reciprocity, and transmissive links have extreme explanatory power for the evolutionary development of virtual water networks.

Measurement and simulation of the relatively competitive advantages and weaknesses between economies based on bipartite graph theory.

The input-output table is very comprehensive and detailed in describing the national economic systems with abundant economic relationships, which contain supply and demand information among various industrial sectors. The complex network, a theory, and method for measuring the structure of a complex system can depict the structural characteristics of the internal structure of the researched object by measuring the structural indicators of the social and economic systems, revealing the complex relationships between the inner hierarchies and the external economic functions. In this paper, functions of industrial sectors on the global value chain are to be distinguished with bipartite graph theory, and inter-sector competitive relationships are to be extracted through resource allocation process. Furthermore, quantitative analysis indices will be proposed under the perspective of a complex network, which will be used to bring about simulations on the variation tendencies of economies' status in different situations of commercial intercourses. Finally, a new econophysics analytical framework of international trade is to be established.

Analysis of inter-country input-output table based on citation network: How to measure the competition and collaboration between industrial sectors on the global value chain.

The input-output table is comprehensive and detailed in describing the national economic system with complex economic relationships, which embodies information of supply and demand among industrial sectors. This paper aims to scale the degree of competition/collaboration on the global value chain from the perspective of econophysics. Global Industrial Strongest Relevant Network models were established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output tables and then transformed into Global Industrial Resource Competition Network/Global Industrial Production Collaboration Network models embodying the competitive/collaborative relationships based on bibliographic coupling/co-citation approach. Three indicators well suited for these two kinds of weighted and non-directed networks with self-loops were introduced, including unit weight for competitive/collaborative power, disparity in the weight for competitive/collaborative amplitude and weighted clustering coefficient for competitive/collaborative intensity. Finally, these models and indicators were further applied to empirically analyze the function of sectors in the latest World Input-Output Database, to reveal inter-sector competitive/collaborative status during the economic globalization.

Quercitrin attenuates osteoporosis in ovariectomized rats by regulating mitogen-activated protein kinase (MAPK) signaling pathways.

MAPK signaling pathways are crucial in regulating osteogenesis, a genetic disorder affecting the bones. Quercitrin, a type of flavonoid, is widely distributed in nature and involved in many pharmacological activities. But its osteoprotective functions and mechanism in osteoporosis are far from being understood clearly. In this paper, the MAPK upregulation was observed in the ovariectomy-induced bone loss. Quercitrin was found to downregulate MAPK signaling pathways and prevent the ovariectomy-induced deterioration of bone mineral density (BMD), trabecular microstructure, and bone mechanical characteristics. In this study, quercitrin was seen to prevent the progression of the postmenopausal osteoporosis among the rats, which may be mediated by the downregulated MAPK signaling pathways.

Can intravenous steroid administration reduce postoperative pain scores following total knee arthroplasty?: A meta-analysis.

BACKGROUND: The purpose of this systematic review and meta-analysis of randomized controlled trials (RCTs) was to evaluate whether intravenous steroids would result in reduced acute pain and postoperative nausea and vomiting (PONV) among patients undergoing total knee arthroplasty (TKA). METHODS: Electronic databases, including PubMed, Embase, Web of Science, and the Cochrane Library, were searched to identify articles published from database inception to July 2016. RCTs that compared the effects of intravenous steroids with the effects of placebo among patients undergoing TKA were included in this meta-analysis. The primary outcomes were visual analogue scale (VAS) scores after 12, 24, and 48 hours of rest and PONV incidence. The secondary outcomes were blood glucose levels and incidence of infection. We calculated the risk ratio (RR) with its corresponding 95% confidence interval (CI) for dichotomous outcomes and the mean difference (MD) with its corresponding 95% CI for continuous outcomes. RESULTS: Seven clinical trials involving 434 patients were included in the final meta-analysis. The pooled results indicated that intravenous steroids were associated with decreased VAS scores after 24 hours (MD = -10.21, 95%CI = -18.80 to -1.63, P = .020) and 48 hours (MD = -2.60, 95%CI = -4.70 to -0.50, P = .015) of rest. Moreover, intravenous steroids were also associated with decreased risk of nausea (RR = 0.58, 95% CI 0.44-0.77, P = .000) and vomiting (RR = 0.46, 95% CI = 0.24-0.88, P = .019). However, intravenous steroids were also associated with increased blood glucose levels. No significant difference in the risk of infection was identified between the 2 groups. CONCLUSION: Intravenous steroids may be associated with decreased pain intensity and decreased risk of nausea and vomiting during the early period following TKA. However, evidence supporting its use is limited by the low quality of and variations in dosing regimens between the included RCTs. Thus, more high-quality RCTs are needed to identify the optimal drug administration intervals for maximal pain control.

Spreading Effect in Industrial Complex Network Based on Revised Structural Holes Theory.

This paper analyzed the spreading effect of industrial sectors with complex network model under perspective of econophysics. Input-output analysis, as an important research tool, focuses more on static analysis. However, the fundamental aim of industry analysis is to figure out how interaction between different industries makes impacts on economic development, which turns out to be a dynamic process. Thus, industrial complex network based on input-output tables from WIOD is proposed to be a bridge connecting accurate static quantitative analysis and comparable dynamic one. With application of revised structural holes theory, flow betweenness and random walk centrality were respectively chosen to evaluate industrial sectors' long-term and short-term spreading effect process in this paper. It shows that industries with higher flow betweenness or random walk centrality would bring about more intensive industrial spreading effect to the industrial chains they stands in, because value stream transmission of industrial sectors depends on how many products or services it can get from the other ones, and they are regarded as brokers with bigger information superiority and more intermediate interests.

Therapeutic potential of Oroxylin A in rheumatoid arthritis.

Excessive inflammation contributes greatly to the pathogenesis and development of rheumatoid arthritis (RA). Oroxylin A (OA) is a natural anti-inflammatory flavonoid compound. In this study, we investigated the effects of OA on collagen-induced arthritis (CIA) and human RA fibroblast-like synoviocytes (FLS). CIA was induced in DBA/1 mice and mice were intraperitoneally treated with OA (10mg/kg) for 10days. Arthritis severity was evaluated every day and the histopathologic examination of joints was done. Serum levels of anti-collagen II antibodies (anti-CII Abs) and cytokines were determined by ELISA. Frequency of regulatory T cells (Tregs) and Th17 cells in draining inguinal lymph nodes (ILN) was quantified by flow cytometry. FLS from patients with active RA were treated with varying doses of oroxylin A, followed by stimulation with tumor necrosis factor (TNF)-α (10ng/mL). The production of cytokines was measured by ELISA. Signal transduction proteins were examined by western blot. OA significantly diminished the arthritis and histological damage. Serum anti-CII Abs, IL-1ß, IL-6, TNFα, and IL-17 were significantly diminished by OA treatment. Analysis of CD4+T cell populations in OA-treated mice showed an increase in Tregs and reduction in Th17 cells in the ILN. In vitro, OA decreased the secretion of IL-1ß and IL-6 from TNFα-stimulated RA FLS in a dose-dependent manner. TNFα-induced p38 MAPK, ERK1/2 and NF-κB signaling pathways were suppressed by OA. Our results indicate that OA exerts an anti-inflammatory activity and may have therapeutic potential for human RA.

Microinjection of calcitonin in midbrain periaqueductal gray attenuates hyperalgesia in a chronic constriction injury rat model.

OBJECTIVES: As heat, pain is one of the most common clinical symptoms. Generally, calcitonin (CT) is prescribed as an analgesic agent for the treatment of pain, especially for the pain caused by osteoporosis or primary and metastatic bone tumor. However, the detailed mechanism remains unknown. MATERIALS AND METHODS: In this study, chronic constriction injury (CCI) rat model was created, and hot plate test and von frey filaments test were employed to evaluate thermal withdrawal latency (TWL) and mechanical withdrawal threshold (MWT), respectively. Immunohistochemistry staining and western blot analyses were used to assess the distribution and expression of calcitonin receptor (CT-R) in the midbrain periaqueductal gray (PAG), which was a pivotal site in the modulatory system for the endogenous pain. RESULTS: The TWL and MWT before the surgery (19.6±1.19 sec) were significantly longer than that at day 2 (12.5±1.60 sec), and day 14 (7.75±0.89 sec) (P< 0.01; P< 0.01), respectively. The TWL and MWT at day 14 were significantly increased compared to that at day 7 after microinjection of salmon calcitonin (sCT) with different doses. Interestingly, the expression of CT-R was up-regulated in neuropathic pain. Furthermore, the expression of CT-R was significantly up-regulated and algesia was remarkably relieved when CT was microinjected into PAG. CONCLUSION: These results suggested that an increased CT-R might be associated with hyperalgesia in CCI rat, and CT had a potent antinociceptive effect by the up-regulation of CT-R in the PAG. Thus, it might provide a potential approach for the treatment of bone pain.