Apolipoprotein E is a prognostic factor for pancreatic cancer and associates with immune infiltration.

BACKGROUND: The expression level of apolipoprotein E (APOE) in pancreatic ductal adenocarcinoma (PDAC) and its effect on the prognosis of PDAC patients are not clear. The effect of APOE on the immune status of patients with PDAC has not been elucidated. METHODS: We obtained pancreatic cancer data from the TCGA and GETx databases. Patients with PDAC who underwent pancreatic surgery at the Second Affiliated Hospital of Jiaxing University between 2012 and 2021 were included. Clinical pathological data were recorded, plasma APOE levels were measured, and tissue samples were collected. A tissue microarray was generated using the collected tissue samples. APOE and CD4 staining was performed to determine immunoreactive scores (IRSs). The expression of APOE in the plasma and tumour tissues of pancreatic cancer patients was analysed and compared. The correlations between plasma APOE levels, tissue APOE levels and clinicopathological characteristics were analysed. Survival prognosis was analysed using Kaplan-Meier survival analysis and Cox multivariate regression analysis. The correlations between APOE expression levels and immune biomarkers and immune cells were further analysed. Single-cell analysis of APOE distribution in various cells was performed on the TISCH website. RESULTS: APOE was highly expressed in the tumour tissue of pancreatic cancer patients, and high plasma APOE levels were associated with poor prognosis. Females, patients with high-grade disease and patients with pancreatic head carcinoma had high plasma APOE levels. High APOE expression in tumour tissues was associated with good prognosis. Mononuclear macrophages in the pancreatic cancer microenvironment primarily expressed APOE. APOE levels positively correlated with immune biomarkers, such as CD8A, PDCD1, GZMA, CXCL10, and CXCL9, in the tumour microenvironment. APOE promoted CD4 + T cell or dendritic cell infiltration in the tumour microenvironment. CONCLUSIONS: APOE may affect the occurrence and development of pancreatic cancer by regulating the infiltration of immune cells in the tumour microenvironment.

Does the local government multi-objective competition intensify the transfer of polluting industries in the Yangtze River Economic Belt?

Exploring the effect of local government multi-objective competition on the transfer of polluting industries is of great practical significance for promoting the high-quality development in the Yangtze River Economic Belt. This paper adopted the extended shift-share analysis method to measure the scale of inter-provincial transfer of polluting industries in the Yangtze River Economic Belt from 2008 to 2020. Considering local governments' economic, innovation, talent and environmental protection competition, the paper examined the effects of local government multi-objective competition on the transfer of polluting industries in the region, and tested its spatial spillover effects. The results showed that: 1. Different competitions had different effects on the transfer of polluting industries. Economic competition intensified the transfer of polluting industries, while talent, innovation, and environmental protection competition all restrained it, among which environmental protection competition had the strongest restraining effect. 2. Compared with the transfer of polluting industries, the direction of economic competition and environmental protection competition on the transfer of industries did not change, but the degree of influence was reduced, talent competition instead promoted industrial transfer of the research region to some extent. 3. From the basin level, government competition in the upstream region more obviously intensified the transfer of polluting industries; while from the economic scale level, the restraining effect of government competition in the developed region on the transfer of polluting industries was much stronger. 4. Both innovation and environmental protection competition had positive spatial spillover effects. Therefore, it is necessary to optimize the promotion and assessment mechanism of local officials, adopt differentiated competitive constraint mechanisms in accordance with local conditions, guide local governments to transform their development concepts, promote the sharing and common use of technological innovations, and promote the orderly transfer of industries in the Yangtze River Economic Belt.

Alleviation of D-gal-induced senile liver injury by Rg3, a signature component of red ginseng.

To investigate the mechanism by which ginsenoside Rg3 regulates oxidative stress (OS) and inflammation through NF/KB pathway to delay mouse liver injury. This work randomized Balbc mice as four groups: Normal, D-gal, Rg3-L, Rg3-H. Paraffin-embedded liver tissue sections were prepared, later, BAX/BCL-2 protein expression was observed by HE, Sirius red, TUNEL and immunofluorescence to detect apoptotic injury and α-SMA/TGF-ß protein expression to detect fibrosis, and liver inflammation-related protein NF-KB was detected. HE and TUNEL staining showed that Rg3 reduced necrotic cells and fibrosis in liver-injured mice, Rg3 increased anti-inflammatory cytokine IL-18 and reduced TNF-α, IL-1ß and IL-6 expression. Conclusion: Ginsenoside Rg3 can effectively antagonize D-gal's role in mouse liver injury, and its mechanism may be associated with regulating inflammatory pathway by Rg.

Booster or Killer? Research on Undertaking Transferred Industries and Residents' Well-Being Improvements.

Inter-regional industrial transfers would change the economic, societal, and ecological environment of the undertaking area profoundly. Some experts have recognized the ecological and environmental problems caused by industrial transfers. However, there are few studies on whether undertaking an industrial transfer will ultimately improve the well-being of residents. There is a strong application value for exploring this issue under the domestic cycle in China. This paper uses the shift-share analysis method to measure China's inter-provincial industrial transfer from 2004 to 2019. According to the subjective and objective indicators, the article measures the level of residents' well-being. A spatial econometric model is used to empirically test the impact of undertaking transferred industries on residents' well-being and its mechanism. The results show that: 1. There is a significant spatial positive correlation between the well-being of residents at the national level. The empirical results also indicated significant spatial correlations at the level of the three major economic belts in the east, central, west, and northeast; 2. From the perspective of China as a whole, the inter-regional industrial transfer improved the well-being of the residents significantly, but the indirect negative effect reduced the total effect; 3. From the regional perspective, undertaking a transferred industry could significantly improve the well-being of residents in the central and eastern regions. However, in the northeast and western regions, it showed a serious negative effect. We should enhance the orderly transfer of industries deeply, considering the ecological and environmental capacities of the undertaking area fully and strictly limiting the inter-regional transfer of polluting industries. Only in this way could the government improve the well-being of residents in the industrial transfer-out areas and undertake areas effectively.

Can green bonds empower green technology innovation of enterprises?

Green bonds, a new green financial instrument, encourage enterprises to achieve high-quality development through green technology innovation. However, a lack of research is currently being conducted into the effect of green bond issuance in China. Can green bonds effectively empower enterprises to green innovation? What is the underlying mechanism? In the context of carbon-neutral strategies, it is significant to answer these questions scientifically. This paper uses a quasi-natural experiment of the launch of the green bond market in China in 2016 to conduct empirical studies based on the panel data of 1 558 non-financial Chinese-listed enterprises from 2015 to 2020 with the multi-period difference-in-difference model. The results show that ① issuing green bonds can significantly empower enterprises' green technology innovation. The empowering effect is mainly for green utility patents rather than green invention patents. This result remains after dynamic heterogeneity analysis, placebo test, and other tests. In addition, the effect has a lag. ② Heterogeneity tests show that this empowerment effect varies across enterprises with different property rights, industries, and regions. ③ In terms of the mechanism of action, green bonds can enhance enterprises' ability to innovate green technology by increasing the proportion of long-term loans and improving their debt structure. This paper broadens the relevant literature on the economic consequences of green bonds and the influencing factors of enterprises' green technology innovation and provides policy suggestions for further improving the analysis of green bonds.

Environmental Regulation Promotes Eco-Efficiency through Industrial Transfer: Evidence from the Yangtze River Economic Belt in China.

How does environmental regulation affect ecological efficiency? What is the role of industrial transfer in the mechanism of action? Relations and interactions between the three determine economic quality when ecological performance is concerned. Empirical studies in this paper are based on samples from the Yangtze River economic belt in China, which contributes nearly half of China's GDP. By measuring environmental regulation, industrial transfer, and ecological efficiency, data and indexes are prepared for investigating the driving mechanism of environmental regulation and illustrating of the role of industrial transfer. By applying the Markov process to model industrial transfer between regions, the dynamic of transfer is simulated and facilitates further study on the effects of industrial transfer. Finally, this paper concludes that by targeting on the improvement of ecological efficiency, environmental regulation releases its utility through industrial transfer. The highlights include three aspects. Theoretically, it illustrates the driving mechanism of improving the eco-efficiency by environmental regulation. Technically, it pioneers a methodology for describing the regional industrial transfer by modeling it with a Markov process. Practically, the conclusion supplies insights into the inherent law of sustainable development for policy makers.

Will green finance promote green development: based on the threshold effect of R&D investment.

Deeply understanding the driving effect of green finance on green development is of great significance to promote economic transformation and realize the long-term green development. This paper uses the entropy method and undesirable-SE-SBM model to measure provincial green finance and green development efficiency respectively from 2008 to 2018. And based on the above, the panel threshold model is constructed to discuss the nonlinear relationship between green finance and green development efficiency from the first empirical verification. The results show that ① the impact of green finance on green development has a significant single threshold effect, only when R&D investment crosses 2.810 can green finance significantly promote green development efficiency, and before that, it will suppress green development efficiency. ②At present, a few provinces in China have crossed the threshold value of R&D investment, only including Beijing, Tianjin, and Shanghai, while the R&D investment of Jiangsu, Zhejiang, Shandong, and Guangdong gradually approaches the threshold value. Therefore, improving the construction of the green financial system, correctly guiding the direction of green capital investment, and strengthening the supervision of environmental information disclosure are important.

MFDroid: A Stacking Ensemble Learning Framework for Android Malware Detection.

As Android is a popular a mobile operating system, Android malware is on the rise, which poses a great threat to user privacy and security. Considering the poor detection effects of the single feature selection algorithm and the low detection efficiency of traditional machine learning methods, we propose an Android malware detection framework based on stacking ensemble learning-MFDroid-to identify Android malware. In this paper, we used seven feature selection algorithms to select permissions, API calls, and opcodes, and then merged the results of each feature selection algorithm to obtain a new feature set. Subsequently, we used this to train the base learner, and set the logical regression as a meta-classifier, to learn the implicit information from the output of base learners and obtain the classification results. After the evaluation, the F1-score of MFDroid reached 96.0%. Finally, we analyzed each type of feature to identify the differences between malicious and benign applications. At the end of this paper, we present some general conclusions. In recent years, malicious applications and benign applications have been similar in terms of permission requests. In other words, the model of training, only with permission, can no longer effectively or efficiently distinguish malicious applications from benign applications.

Does the new-type urbanization construction improve the efficiency of agricultural green water utilization in the Yangtze River Economic Belt?

It is very important to control agricultural water pollution and promote agricultural water saving, for high-quality development of Yangtze River Economic Belt (YREB). The efficiency of agricultural green water utilization (EAGWU) needs financial and technical support from the new-type urbanization, which also change agricultural production mode and resource utilization level. This paper introduces non-point source water pollution into the output, adopts the super efficiency-slack model (SE-SBM) to measure the EAGWU, and uses difference generalized method of moments (DIF-GMM) to examine how new-type urbanization affects EAGWU from its four core characteristics. The results of EAGWU show that the overall efficiency value has been increasing rapidly in the research period, while the eastern provinces performed better and the central provinces performed worse. On the other hand, the overall difference in EAGWU first diverged and then shrunk, while economically developed provinces has been converging all the time. The results of driving factor estimation show that population urbanization has a significantly positive effect on EAGWU, with the rural labor force transfer and agricultural land circulation. Economic urbanization and urban-rural integration have negative effects, with the widening gap of absolute income and the compressed space of agricultural development. The EAGWU lag phase has a positive effect, because of the ratchet or cumulative effect, while equilibrium-urbanization has an insignificant effect. The conclusions will provide preferable recommendations for decision-making of green and water-saving development in agriculture.

Study on the Spatial Differentiation of Public Health Service Capabilities of European Union under the Background of the COVID-19 Crisis.

Access to public health services is a cause that benefits the people and concerns the vital interests of the people. Everyone has access to basic health care services. The continuous improvement in people's health is an important indicator of the improvement in people's quality of life. This paper selects data from the European Union (EU) on aspects of public health expenditure, medical care resources, and government emergency coordination capacity from the period 2008 to 2017. Principal component analysis and factor analysis are used to measure their public health service capacity scores and conduct a comparative analysis. On this basis, the TOBIT model is adopted to explore the driving factors that lead to the spatial differentiation of public health service capabilities, and to combine it with the data of the COVID-19 epidemic as of 8 August 2020 from the official announcements of the World Health Organization and governments for further thinking. The results indicate that the public health service capacity of countries in the EU is showing a gradual increase. The capacity in Western Europe is, in turn, higher than that of Northern Europe, Southern Europe and Eastern Europe. In addition, the overall capacity in Western Europe is relatively high, but it is not balanced and stable, while Northern Europe has remained stable and balanced at a high level. Population density, degree of opening up, education level, economic development level, technological innovation level, and degree of aging have a positive effect on public health service capabilities. The level of urbanization has a negative effect on it. However, in countries with strong public health service capabilities, the epidemic of COVID-19 is more severe. The emergence of this paradox may be related to the detection capabilities of countries, the high probability of spreading thCOVID-19 epidemic, the inefficient implementation of government policy, the integrated system of the EU and the adverse selection of youth. This paper aims to improve the ability of the EU to respond to public health emergencies, improve the utilization of medical and health resources, and better protect people's health from the perspective of public health service capacity.

A Study on The Driving Factors and Spatial Spillover of Carbon Emission Intensity in The Yangtze River Economic Belt under Double Control Action.

It is greatly important to promote low-carbon green transformations in China, for implementing the emission reduction commitments and global climate governance. However, understanding the spatial spillover effects of carbon emissions will help the government achieve this goal. This paper selects the carbon-emission intensity panel data of 11 provinces in the Yangtze River Economic Belt from 2004 to 2016. Then, this paper uses the Global Moran's I to explore the spatial distribution characteristics and spatial correlation of carbon emission intensity. Furthermore, this paper constructs a spatial econometric model to empirically test the driving path and spillover effects of relevant factors. The results show that there is a significant positive correlation with the provincial carbon intensity in the Yangtze River Economic Belt, but this trend is weakening. The provinces of Jiangsu, Zhejiang, and Shanghai are High-High agglomerations, while the provinces of Yunnan and Guizhou are Low-Low agglomerations. Economic development, technological innovation, and foreign direct investion (FDI) have positive effects on the reduction of carbon emissions, while industrialization has a negative effect on it. There is also a significant positive spatial spillover effect of the industrialization level and technological innovation level. The spatial spillover effects of FDI and economic development on carbon emission intensity fail to pass a significance test. Therefore, it is necessary to promote cross-regional low-carbon development, accelerate the R&D of energy-saving and emission-reduction technologies, actively enhance the transformation and upgrade industrial structures, and optimize the opening up of the region and the patterns of industrial transfer.