Biodegradable copper-iodide clusters modulate mitochondrial function and suppress tumor growth under ultralow-dose X-ray irradiation.

Both copper (Cu2+/+) and iodine (I-) are essential elements in all living organisms. Increasing the intracellular concentrations of Cu or I ions may efficiently inhibit tumor growth. However, efficient delivery of Cu and I ions into tumor cells is still a challenge, as Cu chelation and iodide salts are highly water-soluble and can release in untargeted tissue. Here we report mitochondria-targeted Cu-I cluster nanoparticles using the reaction of Cu+ and I- to form stable bovine serum albumin (BSA) radiation-induced phosphors (Cu-I@BSA). These solve the stability issues of Cu+ and I- ions. Cu-I@BSA exhibit bright radioluminescence, and easily conjugate with the emission-matched photosensitizer and targeting molecule using functional groups on the surface of BSA. Investigations in vitro and in vivo demonstrate that radioluminescence under low-dose X-ray irradiation excites the conjugated photosensitizer to generate singlet oxygen, and combines with the radiosensitization mechanism of the heavy atom of iodine, resulting in efficient tumor inhibition in female mice. Furthermore, our study reveals that BSA protection causes the biodegradable Cu-I clusters to release free Cu and I ions and induce cell death by modulating mitochondrial function, damaging DNA, disrupting the tricarboxylic acid cycle, decreasing ATP generation, amplifying oxidative stress, and boosting the Bcl-2 pathway.

Ginsenoside Rb1 attenuates mouse cerebral ischemia/reperfusion induced neurological impairments through modulation of microglial polarization.

Cerebral ischemia/reperfusion causes high disability, recurrence, and mortality. Ischemic stroke is a powerful stimulus that triggers significant microglia activation. Ginsenoside Rb1 (GS-Rb1) has been demonstrated to have neuroprotective effects in the central nervous system. In this study, the effects of GS-Rb1 against cerebral ischemia/reperfusion were explored. A mouse model of middle cerebral artery occlusion (MCAO) was used to mimic the cerebral ischemia/reperfusion. Mice in MCAO + GS-Rb1 groups received 5, 10, or 20 mg/kg GS-Rb1 through intraperitoneal injection. Modified neurological severity scoring (mNSS) showed neurological function, while the open field test tested the anxiety-like behaviors. Cognitive impairment was evaluated by Morris water maze. Protein levels were evaluated by ELISA and Western blot and mRNA levels were analyzed by qRT-PCR. When compared to the MCAO mice, mice in the MCAO + GS-Rb1 group had significantly lower mNSS scores and less brain water content. GS-Rb1 alleviated both cognitive impairment and anxiety and inhibited microglial activation in the cerebral ischemia/reperfusion model. GS-Rb1 enhanced M2-type microglia polarization while inhibiting M1-type microglia polarization. In summary, we observed that GS-Rb1 had neuro-protective effects in a cerebral ischemia/reperfusion mouse model through regulating the microglia polarization.

Cuproptosis and Cuproptosis-Based Synergistic Therapy for Cancer Treatment.

Copper, as an essential trace nutrient for human, plays a crucial role in numerous cellular activities, and is vital for maintaining homeostasis in organisms. Deviations from normal intracellular copper concentration range can disrupt the cellular homeostasis and lead to cell death. Cell death is the process in which cells lose their vitality and cannot sustain normal metabolism, which has various forms. The recently discovered cuproptosis mechanism differs from the previously recognized forms, which is triggered by intracellular copper accumulation. The discovery of cuproptosis has sparked interest among researchers, and this mechanism has been applied in the treatment of various intractable diseases, including different types of cancer. However, the developed cuproptosis-based therapies have revealed certain limitations, such as low immunostimulatory efficiency, poor tumor targeting, and inhibition by the tumor microenvironment. Therefore, researchers are devoted to combining cuproptosis with existing cancer therapies to develop more effective synergistic cancer therapies. This review summarizes the latest research advancements in the cuproptosis-based therapies for various types of cancer, with a focus on the synergistic cancer therapies. Finally, it provides an outlook on the future development of cuproptosis in anti-tumor therapy.

Measuring the carbon shadow price of agricultural production: a regional-level nonparametric approach.

Climate change poses an urgent threat, necessitating the implementation of measures to actively reduce carbon emissions. The development of effective carbon emission reduction policies requires accurate estimation of the costs involved. In situations where actual prices of commodities are not available in the market, shadow pricing provides a useful method to calculate relative prices between commodities with and without price information. However, most studies focus on the industry, with few contributions on agricultural sector. This paper estimates the shadow price of carbon emissions in the agricultural sector from a provincial perspective, incorporating the impact of livestock into the calculation of carbon emissions and shadow pricing. Our findings indicate that ignoring livestock may overestimate CSP values. On the whole, the level of carbon shadow price is rising, indicating good green development in China's agricultural sector. The two types of convergence results show that there is sigma convergence and beta convergence in the western and central regions, demonstrating a significant improvement in environmental performance.

Cluster-Aware Grid Layout.

Grid visualizations are widely used in many applications to visually explain a set of data and their proximity relationships. However, existing layout methods face difficulties when dealing with the inherent cluster structures within the data. To address this issue, we propose a cluster-aware grid layout method that aims to better preserve cluster structures by simultaneously considering proximity, compactness, and convexity in the optimization process. Our method utilizes a hybrid optimization strategy that consists of two phases. The global phase aims to balance proximity and compactness within each cluster, while the local phase ensures the convexity of cluster shapes. We evaluate the proposed grid layout method through a series of quantitative experiments and two use cases, demonstrating its effectiveness in preserving cluster structures and facilitating analysis tasks.

Cu2+ -Anchored Carbon Nano-Photocatalysts for Visible Water Splitting to Boost Hydrogen Cuproptosis.

Both hydrogen (H2 ) and copper ions (Cu+ ) can be used as anti-cancer treatments. However, the continuous generation of H2 molecules and Cu+ in specific sites of tumors is challenging. Here we anchored Cu2+ on carbon photocatalyst (Cu@CDCN) to allow the continuous generation of H2 and hydrogen peroxide (H2 O2 ) in tumors using the two-electron process of visible water splitting. The photocatalytic process also generated redox-active Cu-carbon centers. Meanwhile, the Cu2+ residues reacted with H2 O2 (the obstacle to the photocatalytic process) to accelerate the two-electron process of water splitting and cuprous ion (Cu+ ) generation, in which the Cu2+ residue promoted a pro-oxidant effect with glutathione through metal-reducing actions. Both H2 and Cu+ induced mitochondrial dysfunction and intracellular redox homeostasis destruction, which enabled hydrogen therapy and cuproptosis to inhibit cancer cell growth and suppress tumor growth. Our research is the first attempt to integrate hydrogen therapy and cuproptosis using metal-enhanced visible solar water splitting in nanomedicine, which may provide a safe and effective cancer treatment.

Evaluating the energy efficiency-enhancing potential of the digital economy: Evidence from China.

Improving energy efficiency can go a long way in helping China address environmental problems it currently faces and help deliver on its pledge of achieving carbon neutrality by 2060. At the same time, innovative production technologies based on digital solutions continue to attract significant attention, owing to their potential to provide environmentally sustainable development opportunities. This study explores whether the digital economy can improve energy efficiency by facilitating input reallocation and promoting better information flows. We rely on a panel of 285 Chinese cities for the period 2010-2019 and a so-called slacks-based efficiency measure incorporating socially undesirable outputs to obtain energy efficiency from the decomposition of a productivity index. Our estimation results demonstrate that the digital economy can promote better energy use efficiency. More specifically, a 1-percentage point increase in the size of the digital economy leads to an average increase of around 14.65 percentage points in energy efficiency. This conclusion still holds under a two-stage least-squares procedure used to mitigate endogeneity. The efficiency-enhancing impact of digitalization is heterogeneous and depends on factors such as resource endowment, city size, and geographical location. Additionally, our results suggest that digital transformation within a particular region has an adverse effect on energy efficiency in that region's neighboring areas due to negative spatial spillover effects. These negative spillovers outweigh the positive direct effect on energy efficiency that can be attributed to a growing digital economy.

Devising evidence-based strategies for progress towards zero-carbon energy at the country level: The by-production approach.

The development of the sustainable energy systems is crucial for economic growth and climate change mitigation. This paper proposes a nonparametric approach based on the by-production technology comprising the economic and environmental sub-technologies. We consider both renewable and fossil energy in the analysis. This approach allows identifying the most relevant energy development strategies at the country level. We examine 42 countries from the OECD, B(R)ICS and ASEAN. The results indicate that most of the countries (23) need to exploit both the energy intensity and carbon factor (energy-mix) effects to ensure sustainable energy development, yet four countries also need to increase the use of the renewable energy in order to secure the economic growth. During 1990-2018, an upward trend for the CO2 emission shadow price is observed for the selected countries which suggests an improving environmental performance. The results of this study provide further guidelines for adopting effective market-oriented policy measures in the energy sector.

How does foreign direct investment improve urban air quality?

Foreign direct investment and environmental pollution have been a prominent topic in China's economic development. Therefore, this paper investigates the relationship between foreign direct investment and environmental pollution, and makes practical policy recommendations to support the harmonious development of economy and environment based on the study findings. In this paper, the spatial econometric approach framework with the spatial weight matrix of the Delaunay method is used to examine the influence of foreign direct investment on the level of urban air quality. It uses air quality index as an indicator to measure air pollution comprehensively. Based on the spatial autocorrelation with the aggregation and radiation effects of foreign direct investment, the results show that the distribution of air pollution has considerable spatial impact in terms of spatial nonequilibrium. Through the empirical analysis, our finding reveals that the increase in GDP, the share of secondary industry, and population growth are the important elements affecting the change in air quality.

Carbon resource reallocation with emission quota in carbon emission trading system.

In this study, a two-stage data envelopment analysis approach is developed to examine resource allocation in a real-world carbon emissions trading system. First, this study focuses on the actual participation process of incorporated units in the trading system, where incorporated units will be allocated with a carbon emission quota. Second, we propose a research structure for the carbon trading process with two stages. The first stage is to identify congestion, and the second stage is to trade among the units. We make a sensitivity analysis by considering restrictive parameters on the initial carbon emission quota. Then, we expand the research with a target-setting model that retains production technology from the previous year to set the target output for the following year. The congestion and the trading amount for each unit could be determined in advance. Furthermore, these results are able to anticipate the trading situation and provide valuable recommendations for the production and trading of the analyzed units. Finally, the proposed approach is applied to analyze 13 cities in Hubei Province to investigate their congestion and trading conditions.

Housing market capitalization of environmental risk: evidence from the Tianjin explosion.

Do environmental risks affect housing prices in the vicinity of industrial plants? Prior studies concentrated on the capitalization effect of infrequent natural disasters instead of industry-related environmental risks caused by production accidents in our everyday lives. In this paper, we first use the 2015 Tianjin explosion in China as an exogenous shock, which led to serious casualties and property damage with nationwide concern, to estimate the effects of environmental risk on housing prices far away from the explosion site. Based on the housing transaction units and chemical plant datasets in Beijing with the difference-in-differences hedonic model, the results indicate that first, housing prices near chemical plants decreased significantly after the explosion and lasted for at least 2 years. Second, the mitigation effects of production and consumption amenities and regional demographic features were examined. The conclusions of this paper provide a policy basis for constantly implementing public sentiment management and safety supervision, balancing industrial and residential land layouts, and improving local amenities and demographics to ensure the stability of the land market.

Evaluating Green Productivity Gains with the Exponential By-Production Technology: an Analysis of the Chinese Industrial Sector.

The conventional convexity assumptions frequently placed on piecewise linear frontiers of production technologies modeled using data envelopment analysis imply non-increasing marginal products. Assuming geometric convexity in the context of the exponential technology represents a more general alternative that imposes no underlying restrictions on the marginal products, while simultaneously reducing the impact of the outlying observations. In this paper, we propose an exponential by-production technology capable of generating the outputs deemed undesirable from the society's point of view. We subsequently rely on this technology to measure environmental productivity. Our empirical illustration uses data from the Chinese industrial sector, which is both a major energy consumer and polluter. By comparing our findings with the results from a conventional production model we demonstrate that our proposed indicator mitigates the impact of outlying observations when gauging the contributions of inputs and outputs to green growth. Our results suggest that the Chinese industrial sector experienced the annual productivity growth rate of around 0.40% during 1999-2016 and that the green productivity was mostly driven by technological progress. We also demonstrate that technological progress has been a bigger contributor to the growth in industrial output in China's east than its inland or western regions.

Internet technology and green productivity in agriculture.

The high-quality development of agriculture requires not only sustainable growth of agricultural productivity but also green agricultural production. Internet technology has played an essential role in agricultural production and marketing in China over the past decades. This paper estimates provincial agricultural green growth in China from 1997 to 2019 and decomposes it into technological progress (TP) and efficiency changes (EC) based on the Luenberger productivity indicator method. Then an econometric model is employed to analyze the impact of the Internet on the growth of agricultural green productivity and each sub-component, and moderating role of farmer education in such effect. The empirical results indicated that annual average growth rate of agricultural green productivity in China is 1.33% from 1997 to 2019, and technological progress dominates its growth. The development of Internet technology has a significant positive impact on agricultural green productivity and its decomposition. Farmer education has strengthened the effect of Internet technology on agricultural green productivity and its decomposition TP and EC.

Capacity utilization and energy-related GHG emission in the European agriculture: A data envelopment analysis approach.

Capacity utilization (CU) measures may show the potential for production growth under improved availability of the (variable and fixed) inputs. However, the environmental constraints should be considered when taking the production decisions. These questions are important in the context of the agricultural sector that needs to ensure food security and sustainability. This paper proposes a novel approach that integrates weak disposability technology with observation-specific abatement factors with input- and output-orientated capacity utilization measures in the short and long run. The case of European Union agricultural sector is analyzed. The results indicate that the multiple output-oriented CU measures considered in the study yield often conflicting results. Italy, Germany and France show the highest levels of the agricultural capacity utilization. At the other end of spectrum, the underdeveloped economies often showed lower values thereof. The inclusion of the energy-related GHG emission in the model generally reduced the performance gaps among the countries considered. Results of the research are important in assessing the possibilities for sustainable agricultural growth and development in the European Union as the CU levels may vary for a certain depending on the inclusion of the environmental pressures in the model.

Energy market integration and renewable energy development: Evidence from the European Union countries.

Based on the panel data of 20 countries in EU during the period of 2007-2019, this paper study the effect of energy market integration (EMI) on renewable energy development (RED). We develop a general equilibrium model to explain how EMI affect the RED and the role of different mechanisms. The empirical results reports that the European EMI increased both the consumption and power generation of renewable energy, which proves a significant positive effect of EMI on the RED. In line with our expectations of theoretical model, our estimates show that the increase of renewable energy consumption is mainly due to the fossil energy cost increased, technology advancement and regional environmental regulation strengthening. And the fossil energy cost is the main driven force which plays a completely mediating role between EMI and RED. Furthermore, we also observe a negative effect of FDI and industry structure on RED.

Impacts of renewable electricity standard and Renewable Energy Certificates on renewable energy investments and carbon emissions.

Accelerating the development of renewable energy is seen as an effective way for achieving the goals of carbon peak and carbon neutrality. The polices of Renewable Electricity Standard (RES) and Renewable Energy Certificates (REC) play increasing and important roles in developing renewable energy. In this paper, we develop an analytical model to analyze the impacts of the interaction of RES and REC polices on the renewable energy investment levels of an electricity generation firm and the carbon emissions. Our analysis reveals several interesting insights. First, we find that the green tags price under REC policy has a non-monotonic effect on the renewable energy investment, which highly depends on the quota (i.e., the required percentage of renewable electricity consumption on total electricity consumption) under the RES policy. Specifically, when the quota in RES policy is set too high, an increase in the green tags price will increase renewable energy investment; otherwise it will reduce the electricity generation firm's incentive to invest in renewable energy. Second, we show that the green tags price also has a non-monotonic effect on the carbon emissions. Specifically, when the quota in RES policy is set small enough, an increase in the green tags price will decrease the carbon emission. However, when the quota in RES policy is high enough, an increase in the green tags price will increase the carbon emission.

Spatiotemporal carbon emissions across the spectrum of Chinese cities: Insights from socioeconomic characteristics and ecological capacity.

In-depth investigation of the spatiotemporal driver patterns of city carbon emissions is vital toward establishing carbon neutrality, as such knowledge would aid policymakers in formulating differentiated emission reduction policies. Through developing a unique carbon emission dataset and applying a spatiotemporal logarithmic mean Divisia index decomposition approach, we explored the spatiotemporal drivers of CO2 emission for diverse cities in China categorized by economic structure and population size during 2002-2018. The results highlighted GDP per capita and industrial structure as the most positive and negative drivers, respectively, with the former overweighing the latter before 2016. Furthermore, the between-group differences of cities categorized using population size were higher than differences within groups, implying evident heterogeneity of carbon emissions. Emission related to within-differences in net primary productivity (NPP) constitutes the largest contributing factor promoting carbon emission in megacities and highly industrialized cities, whereas NPP between-differences in agricultural carbon intensity are predominantly associated with inhibiting emissions in large and highly commercialized cities. We therefore suggest that policymakers should optimize the industrial structure in highly industrialized cities and develop carbon sequestration in cities with high vegetation coverage through fiscal transfer for achieving carbon neutrality.

Does industrial agglomeration affect the regional environment? Evidence from Chinese cities.

This study examines the impact of industrial agglomeration on the regional environment using panel data of 13 prefecture-level cities in the Beijing-Tianjin-Hebei region from 1998 to 2018. The empirical results show a strong spatial autocorrelation and a strong spatial lag and spatial error effect on the environmental pollution level in the Beijing-Tianjin-Hebei region. The results further show that the manufacturing agglomeration significantly aggravates the regional pollution; service agglomeration significantly alleviates the regional environmental pollution; the synergistic agglomeration of manufacturing and service industry has a significant inverted "U" type relationship on the regional environmental pollution. More specifically, the development of synergistic agglomeration intensifies regional environmental pollution at the early stage, and after reaching the inflection point, synergistic agglomeration alleviates regional environmental pollution. The inflection point occurs when the level of synergistic agglomeration is around 2.85. At the same time, there is no significant spillover effect of synergistic agglomeration on neighboring regions after calculating the feedback effect. Study findings provide insights for promoting the strategy of "two-wheel-drive development" and alleviating the contradictory relationship between industrial development and environmental pollution.

The club convergence of green productivity across African countries.

This study investigates economic convergence and sustainable development in Africa. By introducing an aggregate production technology and directional distance function, it examines the productivity growth of 28 African economies from 1990 to 2019. The proposed approach considers all decision-making units (countries) as a whole, and the productivity gains are then estimated under a nonparametric framework. In the empirical analysis, the carbon emissions are included in the Luenberger productivity measurement, called green productivity. The results show that the annual average growth rate of green productivity is 1.51% in African, and different types of club convergence for green productivity indicator and its decomposition are observed during the sample period. The decomposition of the Luenberger indicator shows that green African growth is mainly driven by technological progress, not efficiency change. Furthermore, the overall inefficiency is decomposed into technical and structural effects. The latter measure the potential improvement in terms of resource reallocation. Structural inefficiency is larger than technical inefficiency, suggesting that African countries could improve their economic and environmental performances by optimizing input/output mixes.

Using COVID-19 mortality to select among hospital plant capacity models: An exploratory empirical application to Hubei province.

This contribution defines short- and long-run output- and input-oriented plant capacity measures and evaluates them relative to convex and nonconvex technologies. By applying these different plant capacity concepts, the authors seek to measure the use of existing capacities, as well as the evolution and build-up of extra hospital capacity in the Chinese province of Hubei during the outbreak of the COVID-19 epidemic in early 2020. Furthermore, medical literature has established that mortality rates increase with high capacity utilization rates, an insight that this study leverages to select the most plausible of eight plant capacity concepts. The preliminary results indicate that a relatively new, input-oriented plant capacity concept correlates best with mortality.