Search Results (769)

The sustainable transformation of resource-based cities (RBCs) is a critical global challenge. The digital economy is emerging as a potential catalyst for this transition, but the precise mechanisms and spatial dynamics underlying its influence on urban resilience remain underexplored. This study addresses this gap by investigating how the digital economy impacts RBC’s resilience, with a focus on both internal mechanisms and cross-regional spatial effects. Fixed effects, mediation, exploratory spatial data analysis (ESDA) and spatial Durbin model (SDM) are used to examine the complex relationships observed in this context. The results reveal the following: (1) While the digital economy in Chinese RBCs demonstrated a stable upward trajectory, urban resilience, although it exhibited a general increase, remained fragile. (2) The digital economy significantly enhanced urban resilience (coefficient = 0.117, p < 0.05), in which context the most pronounced effects pertained to the social and economic resilience subsystems. (3) Green technological innovation (GTI) served as the core intermediary pathway (a × b = 0.017, p < 0.01). Industrial structure rationalization also served as a mediator. (4) The digital economy and urban resilience exhibited positive spatial autocorrelation (significant direct effects 0.032, p < 0.05), and the advancement of the digital economy in a focal city can enhance both the urban resilience of that city itself and that of neighboring cities indirectly. Full article

Background: Land use change fundamentally alters soil microbial communities and biochemical processes, yet the integrated effects on rhizosphere microbiome–metabolome networks remained poorly understood. Objective: This study investigated land uses as forest, grassland and intermediary edge shape the rhizosphere biochemical networks of naturally grown Barbarea vulgaris. Methods: Rhizosphere soils of Barbarea vulgaris were analysed for microbial community structure abundance, and metabolomic profile applying phospholipid fatty acid (PLFA) profiling and mass spectrometric untargeted metabolomics (GC–MS/MS and MALDI–TOF/TOF MS). These were coupled with co–inertia analysis to assess microbiome–metabolome interactions. Results: Microbial community analysis revealed significant effects of land use on bacterial community structure (G+/G−, p < 0.001). Untargeted metabolomics identified 248 metabolites, of which 161 were mapped to KEGG pathways. Amino acids and derivatives (21.1%) followed by organic acids (16.8%) were the most representative among identified metabolites. Pathway enrichment analysis revealed coordinated reprogramming of central carbon and nitrogen metabolism across land use gradients, particularly in the amino acid metabolism, TCA cycle, and glycolysis/gluconeogenesis pathways. Microbiome–metabolome coupling analysis revealed distinct correlation patterns between microbial phenotypes and metabolite classes, with forest environments showing the strongest biochemical network integration (RV = 0.91). Edge habitats presented intermediate signatures, supporting their role as transitional zones with unique biochemical properties. Conclusions: The environmental context fundamentally shapes rhizosphere biochemical network organization through coordinated shifts in bacterial community structure and metabolic pathway activity. These habitat-specific metabolic signatures suggest that land use change triggers adaptive biochemical responses that may influence plant performance and ecosystem functioning across environmental gradients. Full article

In order to alleviate the constraints of global warming and sustainable development, digitalization has made significant contributions to promoting agricultural carbon reduction through resources, technology, and platforms. Under this situation, China insists on developing agricultural scale management. However, what impact will scale management in agricultural digital emission reduction have on mechanisms and pathways? Based on three rounds of follow-up surveys conducted by the Digital Countryside Research Institute of Nanjing Agricultural University in Jiangsu Province from 2022 to 2024, in this study a total of 258 valid questionnaires on the rice and wheat industry were collected. Methods such as member checking and audit trail were employed to ensure data reliability and validity. Using econometric approaches including Tobit, mediation, and moderation models, this study quantified the Scale Management Level (SML), examined the mechanism pathways of digital emission reduction in a scaled environment, further demonstrated the impact of scale management on digital emission reduction, and verified the mediating and moderating effects of internal and external scale management. We found that: (1) In scale and carbon reduction, the SBM-DEA model calculates that the scale of agricultural land in Jiangsu showed an “inverted S” trend with SML and an “inverted W” trend with the overall agricultural green production efficiency (AGPE), and the highest agricultural green production efficiency is 0.814 in the moderate scale range of 20–36.667 hm². (2) In digitalization and carbon reduction, the Tobit regression model results indicate that Network Platform Empowerment (NPE) significantly promotes carbon reduction (p < 1%), but its squared terms exhibit an inverted U-shaped relationship with agricultural green production efficiency (p < 1%), and SML is significant at the 5% level. From a local regression perspective, the strength of SML’s impact on the three core variables is: NPE > DRE > DTE. (3) Adding scale in agricultural digital emission reduction, the intermediary mechanism results showed that the significant intensity (p < 5%) of the mediating role of Agricultural Mechanization Level (AML) is NPE > DTE > DRE, and that of the Employment of Labor (EOL) is DRE > NPE > DTE. (4) Adding scale in agricultural digital emission reduction, the regulatory effect results showed that the Organized Management Level (OML) and Social Service System (SSS) significantly positively regulate the inhibitory effect of DRE and DTE on AGPE. Finally, we suggest controlling the scale of land management reasonably and developing moderate agricultural scale management according to local conditions, enhancing the digital literacy and agricultural machinery training of scale entities while encouraging the improvement of organizational level and social service innovation, and reasonably reducing labor and mechanization inputs in order to standardize the digital emission reduction effect of agriculture under the background of scale. Full article

Against the backdrop of rapid population aging and a high prevalence of cognitive impairment in China, identifying modifiable environmental risk factors is a public health priority. Although environmental noise is widely recognized as a significant stressor, its effects on cognitive health remain underexplored within the Chinese context. Drawing on balanced panel data from three waves of the China Health and Retirement Longitudinal Study (CHARLS), we examined 3459 individuals aged 45 and above to assess the association between noise pollution and cognitive function using a two-way fixed-effects model. Additionally, we employed a chained mediation approach to investigate whether sleep disturbances and depressive symptoms serve as intermediary mechanisms. The findings indicated a significant inverse relationship: each unit increase in the noise pollution index corresponded to a 0.41-point reduction in overall cognitive scores. These results were robust across various noise exposure measures. Sensitivity analyses using alternative noise metrics also supported this finding. Sleep duration and depression were identified as significant mediators in the relationship between noise pollution and cognitive decline. This longitudinal analysis offers compelling evidence that environmental noise constitutes a substantial risk factor for declining cognitive function in middle-aged and older adults in China. Full article

Green transformation is becoming key for corporate sustainability in the context of global carbon neutrality goals and China’s “dual carbon” strategy (peak carbon emissions and carbon neutrality). Digital transformation, particularly supply chain digitization, plays a significant role in green transformation. Corporations could improve environmental performance through appropriate resource allocation. Much academic and practical attention is drawn to this area to motivate corporate green transformation. This research proposes to explore the incentive effect of supply chain digitization on corporate green transformation and analyze the mediation mechanism of carbon information disclosure and the regulatory effect of external investor supervision. The study samples Chinese A-share listed firms between 2012 and 2024, constructs a moderated mediation effect model, and arrives at the following conclusions: (1) The digitization of the supply chain significantly stimulates the green transformation of public firms, indicating that digital technology promotes the green development of enterprises through optimizing supply chain management and improving environmental governance efficiency; (2) Carbon information disclosure plays a partial intermediary role between supply chain digitization and corporate green transformation, that is, supply chain digitization enhances the quality of carbon information disclosure and further strengthens the willingness and ability of enterprises to undergo green transformation; (3) The positive regulatory effect of external supervision on carbon information disclosure by investors indicates that external regulatory pressure can enhance the transmission effect of carbon information disclosure on corporate green transformation; (4) Heterogeneity analysis shows that supply chain digitization has a more significant incentive effect on green transformation for manufacturing firms, state-owned enterprises, and high-polluting enterprises, indicating that industry attributes, property rights, and environmental regulation intensity affect the effectiveness of digital green transformation. Full article

The growth-promoting roles of IGF-1 (Insulin-like Growth Factor 1) and the inflammation-modulating cytokine TNF-α (Tumor Necrosis Factor-alpha) have been substantially deciphered in various pathological conditions. Also, their biphasic roles in modulating cellular inflammation have been reported. While their independent signaling pathways are sufficiently explored, recent studies have identified that their combined or costimulatory effects uniquely contribute to the regulation of different disease states. Such costimulatory effects appear to confer divergent and at times opposite effects on certain cellular processes. We and others in the literature have previously demonstrated that TNF-α and IGF-1 would independently induce the expression of SOCS3 (Suppressor of Cytokine Signaling-3, a tumor suppressor protein). However, their combined presence has been found to prevent SOCS3 expression. The cause of this divergent opposite effect remained unclear. Here, we provide structural evidence on the interactions between the receptors for TNF-α and IGF-1, and the expression patterns of intermediary proteins which play a prominent role in SOCS3 expression. Our analysis here presents new evidence which demonstrates that TNFR1 (Tumor Necrosis Factor Receptor-1) has the potential to form hybrid receptors with IGF1R (Insulin-like Growth Factor-1 Receptor). Formation of these hybrid receptors may preclude the intracellular signaling that leads to the inhibition of SOCS3. Additionally, we also identified a unique binding site on TNFR1, where SOCS3 by binding to this region is hypothesized to prevent the export of TNFR1 to cell surface. This could be one of negative feedback regulation mechanisms of SOCS3 associated with preventing inflammatory signaling. Our results described here delineate molecular mediators which could cause inhibition of SOCS3 when both TNF-α and IGF-1 induce their costimulatory effects. Full article

Background: Colorectal cancer (CRC) is significantly associated with multiple metabolic diseases, with plasma metabolites potentially mediating this relationship. This large-scale metabolomics study aims to (1) quantify the genetic correlations and causal effects between 10 metabolic disease-related phenotypes and CRC risk; (2) identify the plasma metabolites mediating these effects; and (3) explore downstream regulatory genes and druggable targets. Methods: Using linkage disequilibrium score regression and two-sample Mendelian randomization, we assessed the causal relationships between each metabolic trait and CRC. A total of 1091 plasma metabolites and 309 metabolite ratios were identified and analyzed for mediating effects by a two-step MR approach. Colocalization analyses evaluated shared genetic loci. The findings were validated in the UK Biobank for metabolite-trait associations. The expression of candidate genes was explored using data from TCGA, GTEx, and GEO. A FADS1-centered protein–protein interaction (PPI) network was constructed via STRING. Results: BMI, waist circumference, basal metabolic rate, insulin resistance and metabolic syndrome exhibited both genetic correlation and causal effects on CRC. Five plasma metabolites—mannonate, the glucose/mannose ratio, plasma free asparagine, 1-linolenoyl-2-linolenoyl-GPC (18:2/18:3), and the mannose/trans-4-hydroxyproline ratio—were identified as shared central mediators. A colocalization analysis showed rs174546 linked CRC and 1-linolenoyl-2-linoleoyl-GPC. Validation in the UK Biobank confirmed the associations between phosphatidylcholine (the lipid class of this metabolite), adiposity measures, and CRC risk. An integrative analysis of TCGA, GTEx, and GEO revealed consistent upregulation of FADS1/2/3 and FEN1 in CRC, with high FADS1 expression predicting a poorer prognosis and showing the distinct cell-type expression in adipose and colon tissue. The PPI network mapping uncovered nine FADS1 interacting proteins targeted by supplements such as α-linolenic acid and eicosapentaenoic acid. Conclusions: This study systematically reveals, for the first time, the shared intermediary plasma metabolites and their regulatory genes in the causal pathway from metabolic diseases to CRC. These findings provide candidate targets for subsequent functional validation and biomarker development. Full article

In the context of global climate change, achieving a green and low-carbon economic transition is essential for sustainable development. This study constructs a model using data from 30 provinces collected between 2006 and 2020 to investigate how green finance influences China’s carbon productivity and the transmission mechanism mediated by factor-biased technological progress. The findings reveal the following: (1) The Moran’s index test for carbon productivity across Chinese provinces demonstrates significant spatial clustering. (2) Green finance exhibits substantial spillover effects on carbon productivity in surrounding regions. (3) Capital-biased and energy-biased technological progress significantly mediate the relationship between green finance and carbon productivity, indicating that green finance enhances carbon productivity by optimizing the allocation of capital, labor, and energy factors. (4) Regional heterogeneity analysis indicates that capital-technology-biased and energy-factor-technology-biased approaches can significantly enhance carbon productivity in Central and Northeastern China. Notably, energy-factor innovation delivers far greater environmental efficiency gains in these regions than in Eastern and Western China. Full article

Aging is characterized by a progressive decline in physiological function that impairs performance and increases vulnerability to disease and mortality. Delaying this deterioration is key to promoting healthy aging. Age-associated functional decline is closely linked to alterations in intermediary metabolism, including disrupted lipid metabolism and impaired mitochondrial function. Counteracting these metabolic changes, particularly those affecting basal metabolic rate and energy utilization, may be a feasible strategy to extend healthspan. The Renin-Angiotensin System (RAS), which controls blood pressure through Angiotensin II, an octapeptide hormone generated from Angiotensin I by Angiotensin-Converting Enzyme (ACE), has been identified as a potential target for aging therapies. ACE inhibitors, such as the commonly prescribed vasodilator lisinopril, have been shown to exert beneficial effects on healthspan. Disentangling their systemic effects from direct cellular actions on intermediary metabolism is challenging in humans but can be pursued in model organisms. Drosophila melanogaster expresses two ortholog of mammalian ACE, Ance and Acer, which have diverged to acquire different functions. Since fundamental cellular processes are evolutionarily conserved and flies have an open circulatory system, Drosophila provides a versatile model for translational studies on ACE inhibition and aging. Recent studies in Drosophila reveal sex-, age-, and genetic background-specific effects of lisinopril on metabolic rates and aging-related organismal phenotypes. Integrating preclinical findings from Drosophila with clinical studies will be essential to define the therapeutic potential of RAS inhibition in extending lifespan and delaying aging. Full article

Environmental protection tax is levied based on various types of emitted pollutants and has a significant impact on the green behaviors and ESG (environmental, social, and corporate governance) performance of enterprises. This article explores the green effect and the impact of environmental protection tax on the green behavior of listed companies with in-depth empirical analysis based on the data of industrial enterprises listed on the A-shares from 2018 to 2022 in China. Research has found that the implementation of environmental protection tax has played a significant driving role in improving the overall performance level of corporate ESG, and this tax system has formed a driving force mechanism for enterprises to increase investment in green innovation and effectively improve their comprehensive ESG performance. Green innovation plays a significant intermediary role between environmental protection tax and corporate ESG performance. It is suggested that regions should adjust the applicable amount of environmental protection tax, increase green innovation, and standardize pollution control and emission reduction regulations. Full article

Background: Compared to other high-income countries, US women face higher maternal and infant mortality rates. Methods: This study used structural equation modeling (SEM) to examine cross-sectional, county-level associations between structural and intermediary social determinants of health (SDOHs) and maternal and infant mortalities, based on the World Health Organization’s Commission on Social Determinants of Health framework. Results: Our findings suggest maternal mortality may be linked to increased food insecurity, food assistance, distance to obstetric care, and decreased walkability and marriage rates. Our modeling also points toward a connection between infant mortality and increased food insecurity, food assistance, Black race, mental distress, and decreased walkability, education, and income. SEM revealed significant direct and indirect effects of these SDOHs. Notably, food insecurity and walkability had direct associations with both maternal and infant mortality in both SEM models. Conclusions: The findings underscore the need for policy, practice, and research efforts to address key SDOHs and reduce mortality disparities in the US. Full article

This paper addresses the lack of hedging effectiveness that yellow corn 1-month futures of the Chicago Mercantile Exchange (CME) offer for cross-hedging the price of Mexican white corn. For this purpose, the authors tested 1013 combinations (portfolios) of the ten most traded futures on the CME and the New York Mercantile Exchange (NYMEX). The results suggest that using a 51.6741% corn and a 48.3259% wheat portfolio mimics the white corn price with a hedging effectiveness of 0.6180. To test the practical use of such a portfolio, the authors backtested its use from 1 January 2000 to 9 February 2025 as a balancing short position for sale of white corn at t + 1. By using the corn–wheat portfolio, the simulated seller (farmer or intermediary) would have earned MXN 5.7664 per kilo traded. The results in this paper provide the first solution to the Mexican white corn cross-hedging problem with a futures portfolio. This hedge can be used as the balancing (short) position for the strike or minimum buy price that the Mexican Government or a financial institution could offer to farmers and intermediaries to enhance food security. Full article

As a key component of new infrastructure, smart logistics is becoming an essential driver for reducing foreign trade costs and risks and promoting the sustainable development of foreign trade. Using panel data from 286 prefecture level and above cities from 2014 to 2023, this article attempts to refine the measurement of smart logistics level from provincial to municipal levels, construct a two-way fixed effect model and a mediation effect model, and deeply explore the inherent relationship between smart logistics, industrial structure upgrading, and sustainable development of foreign trade. The results reveal that: (1) smart logistics significantly promotes the sustainable development of foreign trade. (2) Rationalization and advancement of industrial structure play an intermediary role between the two. (3) Market integration has a positive moderating effect on the path of “smart logistics—industrial structure rationalization”, but the moderating effect is not significant in other paths. It has been confirmed that there is a “siphon effect” in the advantageous regions. (4) Heterogeneity analysis shows that the effect of smart logistics on foreign trade promotion is more significant in the central and inland regions. This study provides a theoretical basis and practical inspiration for optimizing regional smart logistics layout and deepening industrial structure adjustment. Full article

The integration of blockchain technology into healthcare offers a robust solution to challenges in secure data sharing, privacy protection, and operational efficiency. Effective exchange of sensitive patient information among hospitals, clinics, insurers, and researchers is essential for better outcomes and medical advancements. Traditional centralized systems often suffer from data breaches, inefficiency, and poor interoperability. This paper presents a blockchain-based secure data-sharing framework tailored for healthcare, addressing these limitations. The framework employs a hybrid blockchain model, combining private and public blockchains: the private chain ensures fast transactions and controlled access, while the public chain fosters transparency and trust. Advanced cryptographic methods—such as asymmetric encryption, hashing, and digital signatures—safeguard patient data and maintain integrity throughout the datalifecycle. Smart contracts automate processes like consent management, access control, and auditing, ensuring dynamic permission enforcement without intermediaries. Role-based access control (RBAC) further limits access to authorized entities, enhancing privacy. To tackle interoperability, standardized data formats and protocols enable smooth communication across diverse healthcare systems. Large files, such as medical images, are stored off-chain, with only essential metadata and logs on the blockchain. This approach optimizes performance, scalability, and suitability for large-scale healthcare deployments. Full article

Amplifying corporate environmental investments is a pivotal strategy for achieving the “carbon peak and carbon neutral” objectives of China’s green development initiative. The digital transformation has the potential to generate new quality productive forces by leveraging data, thereby promoting green technology innovation, enhancing technology efficiency, and leveraging the impact of resource reallocation. Consequently, this transition enables enterprises to transition from a “passive compliance” model to a “proactive enhancement” model, thereby achieving a significant quality leap forward in their environmental investment. The present study utilises a sample of Chinese A-share companies from 2011 to 2023 to innovatively construct a multifaceted data model to quantitatively analyse the impact of digital transformation on corporate environmental investment. This analysis incorporates the intermediary effects of enhanced new quality productive forces, the intermediary effects of data application, and the threshold effects of environmental uncertainty, as well as the non-linear effects of industry, property rights, regional differences, policy, and the intensity of production factors. The study’s findings are as follows: (1) Digital transformation significantly promotes corporate environmental investment, and this conclusion is robust. (2) The new quality productive forces have a positive intermediary effect on corporate environmental investment during digital transformation. (3) The application of big data has been demonstrated to moderate the intermediary effects of “digital transformation-new quality productive forces-enterprise environmental investment.” (4) The impact of environmental uncertainty on corporate environmental investment during the digital transformation process is characterised by a “barrier effect,” exhibiting a “border effect” that is non-linear in nature. (5) In the context of the lightweight pollution industry, non-state-owned enterprises, the eastern region, and the implementation of environmental policies, the efficacy of digital transformation in enhancing corporate environmental investment is particularly pronounced. In light of the aforementioned, the present study puts forth four specific recommendations, offering invaluable insights for the contemporary Chinese enterprise to navigate the process of transformation and achieve sustainable, high-quality growth. Full article