Sex differences in the tumor promoting effects of tobacco smoke in a cRaf transgenic lung cancer disease model.

Tobacco smoke (TS) is the leading cause for lung cancer (LC), and female smokers are at a greater risk for LC. Yet, the underlying causes are unknown. We performed whole genome scans in TS exposed wild type and histologically characterized tumor lesions of cRaf transgenic mice. We constructed miRNA-gene and transcription factor-miRNA/gene regulatory networks and determined sex-specific gene regulations by evaluating hormone receptor activities. We validated the findings from TS exposed cRaf mice in a large cohort of smoking and never-smoking LC patients. When compared to males, TS prompted a sevenfold increase in tumor multiplicity in cRaf females. Genome-wide scans of tumor lesions identified 161 and 53 genes and miRNAs, which code for EGFR/MAPK signaling, cell proliferation, oncomirs and oncogenes, and 50% of DEGs code for immune response and tumor evasion. Outstandingly, in transgenic males, TS elicited upregulation of 20 tumor suppressors, some of which are the targets of the androgen and estrogen receptor. Conversely, in females, 18 tumor suppressors were downregulated, and five were specifically repressed by the estrogen receptor. We found TS to perturb the circadian clock in a sex-specific manner and identified a female-specific regulatory loop that consisted of the estrogen receptor, miR-22-3p and circadian genes to support LC growth. Finally, we confirmed sex-dependent tumor promoting effects of TS in a large cohort of LC patients. Our study highlights the sex-dependent genomic responses to TS and the interplay of circadian clock genes and hormone receptors in the regulation of oncogenes and oncomirs in LC growth.

Impact of digital finance on energy-based carbon intensity: Evidence from mediating effects perspective.

This research measures energy-based carbon intensity based on energy consumption of 30 Chinese provinces and investigates the impact of digital finance. First, the baseline results were examined through panel data model. Second, we reveal the "black box" system of digital finance and energy-based carbon intensity through mediating effects model. Third, by employed panel quantile regression model, we examine the heterogeneity of the effects of various factors under different carbon intensity quantile. The main quantitative results are as follows: (1) Digital finance shows significant sustainable effect, and its growth of 1% will reduce the carbon intensity by about 0.092%. (2) The intermediary effects of technological innovation and energy structure are -0.0663 and 0.007, respectively, accounting for 41.88% and 19.36% of the total effects. Both are significant transmission mechanisms. (3) When the carbon intensity in >0.9 quantile, digital finance shows a positive coefficient. On the contrary, the coefficient at <0.75 quantile is negative and its absolute value increases with the decrease of quantile. It shows that with the reduction of carbon intensity, the positive impact of digital finance gradually increases. (4) In the eastern, central and western regions, a 1% increase in digital finance will reduce the carbon intensity by 0.147%, 0.096% and 0.089% respectively. This research provides a reference for regional governments to use digital finance tools to promote sustainable development.

Inhibition of visfatin alleviates sepsis-induced intestinal damage by inhibiting Hippo signaling pathway.

BACKGROUND: The aim of this study is to investigate role of Visfatin, one of the pro-inflammatory adipokines, in sepsis-induced intestinal injury and to clarify the potential mechanism. METHODS: C57BL/6 mice underwent cecal ligation and puncture (CLP) surgery to establish sepsis model in vivo. Intestinal epithelial cells were stimulated with LPS to mimic sepsis-induced intestinal injury in vitro. FK866 (the inhibitor of Visfatin) with or without XMU-MP-1 (the inhibitor of Hippo signaling) was applied for treatment. The expression levels of Visfatin, NF-κB and Hippo signaling pathways-related proteins were detected by western blot or immunohistochemistry. The intestinal cell apoptosis and intestinal injury were investigated by TUNEL staining and H&E staining, respectively. ELISA was used to determine the production of inflammatory cytokines. RESULTS: The expression of Visfatin increased in CLP mice. FK866 reduced intestinal pathological injury, inflammatory cytokines production, and intestinal cell apoptosis in sepsis mice. Meanwhile, FK866 affected NF-κB and Hippo signaling pathways. Additionally, the effects of FK866 on inflammatory response, apoptosis, Hippo signaling and NF-κB signaling were partly abolished by XMU-MP-1, the inhibitor of Hippo signaling. In vitro experiments also revealed that FK866 exhibited a protective role against LPS-induced inflammatory response and apoptosis in intestinal cells, as well as regulating NF-κB and Hippo signaling, whereas addition of XMU-MP-1 weakened the protective effects of FK866. CONCLUSION: In short, this study demonstrated that inhibition of Visfatin might alleviate sepsis-induced intestinal injury through Hippo signaling pathway, supporting a further research on Visfatin as a therapeutic target.

Overexpression of novel lncRNA NLIPMT inhibits metastasis by reducing phosphorylated glycogen synthase kinase 3ß in breast cancer.

Long noncoding RNAs (lncRNAs) are considered as regulators of gene expression in cancers. However, cancer profiling has little focused on noncoding genes. Here, we reported that RP11-115N4.1 (here renamed novel lncRNA inhibiting proliferation and metastasis [NLIPMT]) was downregulated in breast cancer tissues. Ectopic expression of NLIPMT inhibited mammary cell proliferation, motility in vitro. Moreover, lnc-NLIPMT reduced the growth of implanted MDA-MB-231 cells in vivo. Mechanistically, glycogen synthase kinase 3ß (GSK3ß) was identified as an effector protein regulated by lnc-NLIPMT. Inhibition of GSK3ß activity restored NLIPMT-induced inhibition of proliferation and motility in breast cancer cells. These data reveal that lnc-NLIPMT functions as a driver of breast cancer progression and might serve as a potential target for antimetastatic therapies.

UBN2 promotes tumor progression via the Ras/MAPK pathway and predicts poor prognosis in colorectal cancer.

BACKGROUND: Ubinuclein-2 (UBN2) is a nuclear protein that interacts with many transcription factors. The molecular role and mechanism of UBN2 in the development and progression of cancers, including colorectal cancer (CRC), is not well understood. The current study explored the role of UBN2 in the development and progression CRC. METHODS: Oncomine network and The Cancer Genome Atlas (TCGA) database were downloaded and Gene Set Enrichment Analysis (GSEA) was performed to compare the UBN2's expression between normal and tumor tissues, as well as the potential correlation of UBN2 expression with signaling pathways. Immunohistochemistry (IHC), qRT-PCR and Western blotting were performed to determine the expression of UBN2 in CRC tissues or cell lines. In vitro proliferation and invasion assays, and orthotopic mouse metastatic model were used to analyze the effect of UBN2 on the development and progression of CRC. RESULTS: The analysis of UBN2 expression using Oncomine network showed that UBN2 was upregulated in CRC tissues compared to matched adjacent normal intestinal epithelial tissues. IHC, qRT-PCR and Western blotting confirmed that UBN2 expression is higher in CRC tissues compared with matched adjacent normal intestinal epithelial tissues. In addition, analyses of TCGA data revealed that high UBN2 expression was associated with advanced stages of lymph node metastasis, distant metastasis, and short survival time in CRC patients. IHC showed that high UBN2 expression is correlated with advanced stages of CRC. Moreover, UBN2 is highly expressed in the liver metastatic lesions. Furthermore, knockdown of UBN2 inhibited the growth, invasiveness and metastasis of CRC cells via regulation of the Ras/MAPK signaling pathway. CONCLUSION: The current study demonstrates that UBN2 promotes tumor progression in CRC. UBN2 may be used as a promising biomarker for predicting the prognosis of CRC patients.

Effect of Endometrial Stem Cell-derived Cytokine Cocktail on a Mouse Model of Myocardial Reperfusion Injury.

Objective To study the effect of endometrial stem cells (EnSCs) derived cytokine cocktail (EdCC) on myocardial ischemic reperfusion injury (I/R) in a mouse model. Methods EdCC was concentrated from the culture medium of EnSCs with Millipore ultra-filtration technology and was administrated to a myocardial I/R mouse models through tail vein injection. The infarct area was determined by TTC/Evans Blue staining. The apoptotic cells were counted by TUNEL assay and the protein level of cleaved caspase 3 was evaluated by Western blotting. Results The EdCC extraction efficiency was (222.4±29.3) Μg/10(6) cells in every 24 h,but the protein gradually degraded under-80 ℃ storage. As compared with I/R group,100 Μg fresh EdCC decreased infarct area (P=0.001),reduced apoptotic nuclei in the infarct border (P=0.019),and inhibited cleaved caspase 3 expression (P=0.002). Increasing EdCC dosage did not further reduce the infarct area. The myocardial protective effect of EdCC diminished after 90 days' storage under-80 ℃. Conclusion EdCC reduces myocardial I/R injury through protecting cardiomyocytes from apoptosis within 30 days storage under-80 ℃.

The impact of smart city construction (SCC) on pollution emissions (PE): evidence from China.

Based on panel data from 210 prefecture-level cities in China from 2003 to 2021, this study employs the Time-Varying Differences-in-Differences (Time-Varying DID) approach to systematically examine the impact of smart city construction on pollution emissions and its underlying mechanisms. Additionally, the Propensity Score Matching-Differences-in-Differences method is employed for further validation. The research findings indicate that Smart City Construction (SCC) significantly reduces urban Volume of Sewage Discharge (VSD), sulfur dioxide emissions (SO2), and Emissions of Fumes and Dust (EFD), thereby mitigating pollution emissions (PE) and enhancing environmental quality. Mechanism analysis reveals that SCC achieves these effects through scale effects, structural effects, and technological effects. City heterogeneity analysis shows that provincial capital cities exhibit a stronger suppression effect on pollution emissions compared to non-provincial capital cities. Moreover, cities with lower levels of education attainment demonstrate a stronger ability to curb pollution emissions, while larger cities exhibit a more pronounced impact on mitigating pollution emissions. The marginal contributions of this study mainly consist of three aspects: Firstly, it enriches the literature on environmental impact factors by assessing, for the first time, the influence of SCC on PE. Secondly, a comprehensive approach is employed, integrating VSD, EFD, SO2 data, and economic and pollution data at the city level. Time-Varying DID is used to evaluate the policy effects of SCC. Finally, the study analyzes the impact mechanisms of SCC policy on environmental emissions from various perspectives.

Impact of Environmental Protection Tax on carbon intensity in China.

In the context of increasingly severe global climate change, finding effective carbon emission reduction strategies has become key to mitigating climate change. Environmental Protection Tax (EPT), as a widely recognized method, effectively promotes climate change mitigation by encouraging emission reduction behaviors and promoting the application of clean technologies. Based on data from 282 cities in China, this paper takes the official implementation of the EPT in 2018 as the policy impact and the cities with increased tax rates for air taxable pollutants as the treatment group and uses DID model to systematically demonstrate the relationship between the implementation of the EPT and carbon intensity (CI) and further explores the possible pollutant emissions and green innovation mediating effects. The findings show that (1) the implementation of EPT can effectively reduce CI by about 4.75%, and this conclusion still holds after considering the robustness of variable selection bias, elimination of other normal effects, policy setting time bias, and self-selection bias. (2) The implementation of EPT can reduce CI by reducing pollutant emissions and improving the level of green innovation. (3) There is obvious regional heterogeneity in the carbon reduction effect of EPT, and the implementation of EPT has a more significant effect on CI in medium-tax areas, low environmental concern areas, general cities, and eastern regions. This paper not only provides a new analytical perspective for systematically understanding the carbon emission reduction effect of EPT but also provides policy insights for promoting regional green transformation and advancing carbon peak carbon neutralization.

The impact of foreign direct investment on green innovation efficiency: Evidence from Chinese provinces.

Improving green innovation efficiency (GIE) is the key to achieve high-quality economic development in China, and the introduction of foreign direct investment (FDI) has become an important path choice to promote the GIE. Based on the data of 30 provinces in China, this paper explores the linear and nonlinear effects of FDI on GIE from both quantity and quality perspectives, and further analyzes the mediating role of environmental regulation level. The results show that: (1) From 2011 to 2020, the GIE of all provinces in China generally shows an upward trend. (2) The quantity and quality of FDI have a significant positive impact on the improvement of GIE in China's provinces, and this impact has regional heterogeneity. (3) The quantity and quality of FDI can promote the improvement of GIE in China through the level of environmental regulation (ER). (4) With the level of knowledge accumulation and GIE as the threshold variables, the quantity and quality of FDI have a single threshold effect on the GIE of China's provinces. The conclusions of this study provide some policy implications for local governments to make full use of FDI to perform green innovation activities.

The carbon emission reduction effect of China's national high-tech industrial development zones.

The double carbon goal is a wide and profound economic and social systematic change. It is also crucial to China's sustainable development. How to promote emission reduction, the National High-Tech Industrial Development Zones(NHTDZs) policy is the key to addressing this problem. Based on urban data from 2003 to 2019 from China, this paper uses the multi-time point asymptotic difference method to explore the impact of the NHTDZs establishment on carbon emissions. The establishment of NHTDZs reduces CO2 emissions, which remains valid through robustness tests. The mechanism analysis demonstrated that the construction of NHTDZs reduces CO2 emissions by increasing innovation levels, increasing research expenditures and emphasizing human capital. Further analysis shown that geographic location, initial resource endowment, population size, and level of green finance development are difference in different cities. This provides guidance promoting the development of NHTDZs and future layout.

The carbon emission reduction effect of green fiscal policy: a quasi-natural experiment.

Carbon emission reduction is crucial for mitigating global climate change, and green fiscal policies, through providing economic incentives and reallocating resources, are key means to achieve carbon reduction targets. This paper uses data covering 248 cities from 2003 to 2019 and applies a multi-period difference-in-differences model (DID) to thoroughly assess the impact of energy conservation and emission reduction (ECER) fiscal policies on enhancing carbon emission (CE1) reduction and carbon efficiency (CE2). It further analyzes the mediating role of Green Innovation (GI), exploring how it strengthens the impact of ECER policies. We find that: (1) ECER policies significantly promote the improvement of carbon reduction and CE2, a conclusion that remains robust after excluding the impacts of concurrent policy influences, sample selection biases, outliers, and other random factors. (2) ECER policies enhance CE1 reduction and CE2 in pilot cities by promoting green innovation, and this conclusion is confirmed by Sobel Z tests. (3) The effects of ECER policies on CE1 reduction and the improvement of CE2 are more pronounced in higher-level cities, the eastern regions and non-resource cities. This research provides policy makers with suggestions, highlighting that incentivizing green innovation through green fiscal policies is an effective path to achieving carbon reduction goals.

Fintech's role in carbon emission efficiency: dynamic spatial analysis.

Against the backdrop of digitization and global warming, fintech plays a crucial role in accelerating the growth of green finance, driving innovation in the financial industry, and catalyzing the low-carbon transformation of economic activities. This paper utilizes city panel data from 2007 to 2019 to examine the direct impact of fintech on carbon emission efficiency (CEE), the transmission channels of green technological innovation and green finance, and the spatial spillover effects, using dynamic panel models, mediation effect models, and dynamic spatial Durbin models (SDM). The study finds that: (i) Fintech significantly improves CEE, and this conclusion remains robust after accounting for potential endogeneity issues and conducting robustness tests. (ii) Mechanism analysis reveals that green finance and green technological innovation are the primary channels through which fintech influences CEE. (iii) Results from the dynamic SDM model indicate that fintech has a significant positive spatial spillover effect on CEE, with the long-term spillover effect being smaller than the short-term spillover effect. (iv) Heterogeneity analysis reveals that fintech's improvement effect on CEE is mainly evident in eastern regions, emerging first-tier and first-tier cities, and non-resource-based cities. Our research provides new insights for policymakers on achieving China's dual-carbon goals through the promotion of fintech development, green finance, and green technological innovation. It also aids in the coordinated development of fintech among cities and the formulation of differentiated policies, providing a theoretical foundation and empirical support for future research.

Evaluation the impact of electricity consumption on China's air pollution at the provincial level.

As the world's largest electricity-consuming country, China faces the challenge of energy conservation and environmental pollution. Therefore, it is imperative that China takes decisive action to address these issues. Based on the panel data of 30 provinces (cities, districts) in China from 2011 to 2020, we use the entropy method to measure the air pollution index in different provinces, construct two fixed effects models, panel quantile model, and spatial Durbin model to empirically analyze the impact of electricity consumption on air pollution in China's provincial regions. The experimental results show that: (1) Electricity consumption has a significant positive impact on the provincial air pollution index in China and the higher the index is, the more serious the air pollution is. When the electricity consumption increases 1%, the air pollution index will increase of by 0.0649% as accompanied. (2) Through comparison of different times, we found that the degree of increase in air pollution index caused by electricity consumption would be reduced due to the improvement of environmental protection efforts. From the perspective of different geographical locations, the electricity consumption in the southeast side of the "Hu Line" has exacerbated the impact on air pollution index. (3) According to the panel quantile regression results, the marginal effect of electricity consumption on air pollution is positive. With the increase of quantiles, the impact of electricity consumption on air pollution is increasing. (4) Spatial effect analysis shows that electricity consumption has a significant positive spatial spillover effect on air pollution index. The increase in electricity consumption not only increases the air pollution index in the local region, but also leads to an increase in the air pollution index in surrounding areas. These findings contribute to the governance of air pollution and the promotion of sustainable economic, environmental and energy development.

The impact of digital economy on environmental pollution: Evidence from 267 cities in China.

Environmental pollution has become a pressing global issue, severely threatening human health and ecosystems. As an emerging driver of economic development in countries worldwide, the digital economy (DE) has the potential to enhance resource utilization efficiency and promote the development of clean technologies, thereby reducing environmental pollution. Based on the panel data of 267 cities in China from 2012 to 2021, the spatial econometric model is used to test the impact of DE on environmental pollution. The mediating effect model is used to explore the transmission mechanism of DE affecting environmental pollution. The panel threshold model is used to examine the threshold effect of marketization. The results are as follows: (1) DE can significantly reduce environmental pollution. The conclusion is still valid after conducting robustness tests such as selecting historical data as instrumental variables and the "Broadband China" pilot as a quasi-natural experiment. (2) From the perspective of transmission mechanism, DE can reduce environmental pollution through green technology innovation and industrial structure upgrading. (3) From the perspective of spatial spillover effect, DE can reduce the environmental pollution level of surrounding cities. (4) From the perspective of threshold effect, DE has obvious market-oriented single threshold effect on environmental pollution. When the marketization level crosses the threshold of 11.6611, the emission reduction effect of DE is significant. (5) From the perspective of heterogeneity, DE has a heterogeneous impact on environmental pollution in cities with different geographic locations, resource endowments and administrative level. Regarding geographical heterogeneity, DE can effectively reduce environmental pollution in eastern and central regions, but has no significant impact on environmental pollution in western regions. Regarding the heterogeneity of resource endowment, compared to non-resource-based cities, resource-based cities suffer more from the negative effects of DE on their environment. Regarding the heterogeneity of administrative levels, compared with non-central cities, the DE of central cities has a greater emission reduction effect. Based on empirical results, this paper proposes strategic recommendations in areas such as enhancing the application of DE in emission reduction, upgrading industrial structures, promoting green technology innovation, and improving the level of marketization. This study not only enriches the research of DE and environmental pollution, but also provides a reference for the formulation of environmental pollution control policies.

Sex disparities in non-small cell lung cancer: mechanistic insights from a cRaf transgenic disease model.

BACKGROUND: Women are at greater risk of developing non-small cell lung cancer (NSCLC), yet the underlying causes remain unclear. METHODS: We performed whole genome scans in lung tumours of cRaf transgenic mice and identified miRNA, transcription factor and hormone receptor dependent gene regulations. We confirmed hormone receptors by immunohistochemistry and constructed regulatory gene networks by considering experimentally validated miRNA-gene and transcription factor-miRNA/gene targets. Bioinformatics, genomic foot-printing and gene enrichment analysis established sex-specific circuits of lung tumour growth. Translational research involved a large cohort of NSCLC patients. We evaluated commonalities in sex-specific NSCLC gene regulations between mice and humans and determined their prognostic value in Kaplan-Meier survival statistics and COX proportional hazard regression analysis. FINDINGS: Overexpression of the cRaf kinase elicited an extraordinary 8-fold increase in tumour growth among females, and nearly 70% of the 112 differentially expressed genes (DEGs) were female specific. We identified oncogenes, oncomirs, tumour suppressors, cell cycle regulators and MAPK/EGFR signalling molecules, which prompted sex-based differences in NSCLC, and we deciphered a regulatory gene-network, which protected males from accelerated tumour growth. Strikingly, 41% of DEGs are targets of hormone receptors, and the majority (85%) are oestrogen receptor (ER) dependent. We confirmed the role of ER in a large cohort of NSCLC patients and validated 40% of DEGs induced by cRaf in clinical tumour samples. INTERPRETATION: We report the molecular wiring that prompted sex disparities in tumour growth. This allowed us to propose the development of molecular targeted therapies by jointly blocking ER, CDK1 and arginase 2 in NSCLC. FUNDING: We gratefully acknowledge the financial support of the Lower Saxony Ministry of Culture and Sciences and Volkswagen Foundation, Germany to JB (25A.5-7251-99-3/00) and of the Chinese Scholarship Council to SZ (202008080022). This publication is funded by the Deutsche Forschungsgemeinschaft (DFG) as part of the "Open Access Publikationskosten" program.

The efficiency of China's freshwater fishery breeding: nonparametric data envelopment analysis based on interprovincial data.

Studying the economic efficiency of freshwater fishery breeding is of great significance to the sustainable utilization of freshwater fishery resources. Based on the nonparametric research method, this study combines the super-SBM data envelopment analysis (DEA) model with the global Malmquist index (GMI) to evaluate the total factor productivity of freshwater fishery breeding (FTFP) of China from 2004 to 2019, so as to reflect the economic efficiency of freshwater fishery breeding in China. The empirical results show that (1) in general, FTFP has reached the effective level in China with a fluctuating trend in time, but it lacks a breakthrough value. (2) In China, FTFP shows significant differences in space, and its spatial development pattern has gradually evolved from "high in the south and low in the north" to "high in the north and low in the south." (3) The change of FTFP in China mainly depends on technological progress, while the change of scale efficiency and pure efficiency has no significant impact on it. (4) When environmental factors are taken into account, the FTFP value will decrease as a whole. Therefore, it is very important to optimize the structure of freshwater fishery breeding and strengthen the construction of aquatic science and technology system.

The impact of industrial collaborative agglomeration on total factor carbon emission efficiency in China.

Improving total factor carbon emission efficiency (TCE) is the key to achieving carbon emission reduction targets while ensuring economic growth. In this paper, the global Malmquist index based on the SBM model is used to measure TCE of 283 cities in China from 2011 to 2019. On this basis, this paper uses the spatial econometric model and intermediary effect model to empirically analyze the impact of industrial co-agglomeration on TCE and its transmission mechanism. Furthermore, considering the differences in geographical location and resource endowment among regions, this paper analyzes the heterogeneous effect of industrial collaboration agglomeration on TCE in different regions and cities. The results show that: (1) Industrial co-agglomeration can improve TCE, and its main transmission channel is technological innovation. (2) Industrial co-agglomeration has a positive spatial spillover effect. Industrial co-agglomeration in one region can improve the TCE in the surrounding regions. (3) Industrial co-agglomeration of cities with different geographic locations and resource endowments has a heterogeneous effect on TCE. Regarding geographical heterogeneity, the industrial co-agglomeration in the eastern region has the greatest promoting effect on TCE, followed by the central region. However, the impact of industrial co-agglomeration in the western region on TCE is not significant. Regarding resource endowment heterogeneity, the industrial co-agglomeration in non-resource-based cities has a greater promoting effect on TCE than that in resource-based cities.

Impact of urban innovation ability on industrial pollution governance in Chinese cities: taking the Yangtze River Economic Belt as an example.

This paper uses spatial measurement method, by selecting panel data from a total of 106 cities in 11 provinces and municipalities in the Yangtze River Economic Belt from 2006 to 2018, to conduct an empirical study on the impact mechanism of urban innovation ability on industrial pollution governance. The results show that there is a significant negative correlation between urban innovation ability and the degree of industrial pollution, and cities in the Yangtze River Economic Belt have a significant spatial connection. Specifically, this paper finds that urban innovation ability can have a positive impact on urban industrial pollution governance through industrial selection, production technology innovation, pollution discharge technology innovation, and environmental pollution treatment, which will help cities reduce industrial pollution; The industrial pollution governance level of individual cities is not only affected by the innovation ability of the city, but also by the innovation spillover of the surrounding cities. Area surrounded by cities with high urban innovation ability will benefit from the spillover of the surrounding cities. The industrial pollution governance level of individual cities is not only affected by the innovation ability of the city, but also by the innovation spillover of the surrounding cities. Areas surrounded by cities with high urban innovation ability will benefit from the spillover of the surrounding cities, thus improving the industrial pollution control and regional ecological environment. Based on this, this paper proposes relevant policy recommendations for urban industrial pollution governance from the perspective of improving urban innovation ability.

Industrial green total factor productivity based on an MML index in the Yangtze River Economic Belt.

The environmental problems caused by industrial development in the Yangtze River Economic Belt in China have become a bottleneck for urban economic development. Therefore, the measurement of the green efficiency of the urban industry in the Yangtze River Economic Belt can provide a reasonable basis for future industrial green development paths. Based on the DEA model, this study measures the industrial green total factor productivity of 108 cities in the YREB by combining the meta-frontier infrastructure framework and the Malmquist-Luenberger index. The results indicate the following: (1) The industrial green total factor productivity of cities in the Yangtze River Economic Belt declined at first and then increased from 2009 to 2016. The overall performance indicated that the structures of the technological efficiency change index and technological change index were unreasonable. The industrial green total factor productivity of midstream cities is the highest, and the difference between cities is influenced by economic development level, industrial base, transportation convenience, labor quality, and the government's emphasis on green development of industrialization. (2) Different regions have different decomposition efficiency to promote the improvement of ITFP. Considering regional heterogeneity, the industrial green total factor productivity in the middle and lower reaches of the region relies on the advantages of technical efficiency, whereas the upper reaches rely on the improvement of management efficiency. (3) The technology gap in the upper and lower reaches is small, and in the middle reaches is relatively large. Thus, according to the above empirical results, this study finally presents some policy suggestions for industrial green development in different cities of the Yangtze River Economic Belt.

Measurement of green total factor productivity on Chinese pig breeding: from the perspective of regional differences.

China has a vast territory and abundant resources, and there are significant differences in the development of pig breeding in different regions. Chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) produced in the process of pig breeding will affect China's environmental quality. In view of this, based on the Minimum Distance to Weak efficient frontier model, this paper constructs Metafrontier-Malmquist-Luenberger (MML) index considering negative output under the common frontier to comprehensively evaluate the green total factor productivity of Chinese pig breeding (GTCP). This has guiding significance for improving China's pork production and reducing pollution emissions. The results manifest that (1) no matter under the common frontier or the group frontier, GTCP presents large temporal and spatial differentiation characteristics. Compared with the central region and the western region, the eastern region has obvious advantages in GTCP. (2) GTCP has shown an upward trend as a whole, which is mainly due to the technical progress. (3) Compared with small-scale and medium-sized GTCP, large-scale GTCP has apparent superiorities. Based on the above outcomes, this paper finally raises policy recommendations for improving GTCP: (1) give full play to the advantages of pig breeding in different regions, (2) increase the research and introduction of pig breeding clean technology and improve the application efficiency, and (3) give full play to the scale effect and vigorously develop large-scale pig breeding.