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Abstract Understanding and measuring the link between vegetation greenness and urbanization is crucial for public health and sustainable development. However, previous methods may oversimplify urbanization indicators and fail to adequately reflect changes in their relationships. To address this, we introduced a comprehensive urbanization vegetation coordination index (CUVCI) on the basis of comprehensive urbanization and a compound annual growth rate and applied this index to the Yellow River Basin in China. We examined the spatiotemporal evolution of the NDVI, comprehensive urbanization level (CUL), and CUVCI from 2000 to 2019 and explored potential driving factors. The results indicate that: (1) from 2000 to 2019, 87.8% of the areas in the Yellow River Basin demonstrated a trend of vegetation growth, with growth levels highest in the midstream regions, followed by the upstream and downstream areas. (2) The CULs of most cities in the basin have shown an increasing trend, with the CUL levels in the middle and downstream cities being significantly higher than those in the upstream cities. (3) CUVCI from 2000 to 2019 was characterized mainly by general coordination (57.4%) and minor conflict (18.5%), with minor-conflict cities located primarily in the middle and lower basin. The coordinating relationships in most cities show signs of improvement. (4) While natural environmental factors such as precipitation, temperature, and relief have a significant impact on CUVCI, scientific researchers can promote the coordinated development of vegetation greenness and urbanization. Our findings suggest that cities in the basin are experiencing economic prosperity and increased greenery. However, strong- and minor-conflict cities should prioritize cultivating and attracting scientific research talent and learning from coordinated provincial capital cities.

As a type of environmental footprint, the concept of virtual land captures the indirect land use embedded in our consumption and trade activities. Utilising the environmentally-extended multi-regional input–output model (EEMRIO) and Kaleidoscope diagram, we visualise for the first time the interprovincial flow of virtual urban land in China. It unveils the intricate urban network connections and the telecoupled interactions between human activities and land use amidst China's rapid urbanisation phase. The results indicate that the eastern region of China emerges as the primary net beneficiary of virtual urban land, whereas the western region stands as the principal net contributor. The local urban land in 65% of the provinces suffices for their own consumption demands. However, provinces like Zhejiang, Henan, and Jiangsu rely heavily on inter-provincial urban land to fulfil their consumption requirements. Inter-regional trade plays a pivotal role in facilitating the flow of land resources, significantly easing the strain between human demands and land availability in the developed coastal provinces of eastern China. Yet, it imposes additional ecological pressure on the more ecologically vulnerable areas in the west. The insights from this research are poised to offer valuable guidance for the Chinese government in harmonising urban development strategies, industrial distribution and the allocation of construction land on a national scale.

Abstract Spatial inequality erodes social cohesion and political stability, impacting global sustainable development and human well-being. This study examines spatial inequality in China across economic, social, environmental, infrastructural, and innovation dimensions, exploring how these inequalities evolve with economic development. Drawing on the Sustainable Development Goals and Chinese planning goals, we selected 13 indicators pertinent to human well-being. We employed the population-weighted coefficient of variation, Gini coefficient, and Moran’s I to assess spatial inequalities and analyzed their relationship with economic growth. The findings reveal that China currently exhibits the highest spatial inequality in innovation and the lowest in the social dimension. Since 1990, most indicators have trended towards decreasing spatial inequality, except for unemployment rates and carbon emissions, which have increased. The economic and innovation gap between the eastern coastal regions and the central and western regions has widened, whereas disparities in housing, healthcare, roads, and digitalization have narrowed. China’s experience demonstrates that Williamson’s inverted U-shaped hypothesis extends beyond the economic domain to encompass education, healthcare, infrastructure, and digitalization, providing policy insights for addressing regional inequalities in China in the post-pandemic era.

Water resources are fundamental for sustaining natural ecosystems and human activities, playing a critical role in the sustainable development of the regional environment. Under the dual pressures of human activities and climate change, however, the stress on water resources has become increasingly evident, emerging as one of the greatest global risks for the next decade. In this study, by applying the water stress index, Lorenz curve, and Theil index, we explored the spatiotemporal patterns and inequality distribution characteristics of water resource stress across two scales: catchment and basin. Additionally, we used partial least squares regression to identify the key factors influencing water resource stress. The results indicated significant regional variations in water stress across China during 2002 to 2020. At the catchment scale, areas with a water stress index greater than 0.4 were distributed in the eastern, northeastern and northwestern regions. While at the basin scale, a north–south pattern emerged with lower stress in the south and higher stress in the north. The Haihe and Huaihe river basins exhibited the highest water stress. The Lorenz curve deviated significantly from the line of absolute equality, indicating a high degree of inequality in regional water resource stress. The Theil index increased from 1.26 to 1.50, showing a slight upward trend in inequality. Analysis of the driving factors revealed that the Yellow River Basin was primarily influenced by GDP and population, the Songhua River Basin was affected by population and urban land use, and the Southwest River Basin is driven mainly by vegetation cover. Overall, precipitation was the most critical driver affecting water stress, predominantly exerting a negative influence. This study provides a theoretical basis for alleviating regional water stress and offers valuable insights for the scientific planning and management of water resources.

Abstract Background Traditional Chinese medicine (TCM) has been found widespread application in neoplasm treatment, yielding promising therapeutic candidates. Previous studies have revealed the anti-cancer properties of Brevilin A, a naturally occurring sesquiterpene lactone derived from Centipeda minima (L.) A.Br. (C. minima), a TCM herb, specifically against lung cancer. However, the underlying mechanisms of its effects remain elusive. This study employs network pharmacology and experimental analyses to unravel the molecular mechanisms of Brevilin A in lung cancer. Methods The Batman-TCM, Swiss Target Prediction, Pharmmapper, SuperPred, and BindingDB databases were screened to identify Brevilin A targets. Lung cancer-related targets were sourced from GEO, Genecards, OMIM, TTD, and Drugbank databases. Utilizing Cytoscape software, a protein-protein interaction (PPI) network was established. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene set enrichment analysis (GSEA), and gene-pathway correlation analysis were conducted using R software. To validate network pharmacology results, molecular docking, molecular dynamics simulations, and in vitro experiments were performed. Results We identified 599 Brevilin A-associated targets and 3864 lung cancer-related targets, with 155 overlapping genes considered as candidate targets for Brevilin A against lung cancer. The PPI network highlighted STAT3, TNF, HIF1A, PTEN, ESR1, and MTOR as potential therapeutic targets. GO and KEGG analyses revealed 2893 enriched GO terms and 157 enriched KEGG pathways, including the PI3K-Akt signaling pathway, FoxO signaling pathway, and HIF-1 signaling pathway. GSEA demonstrated a close association between hub genes and lung cancer. Gene-pathway correlation analysis indicated significant associations between hub genes and the cellular response to hypoxia pathway. Molecular docking and dynamics simulations confirmed Brevilin A’s interaction with PTEN and HIF1A, respectively. In vitro experiments demonstrated Brevilin A-induced dose- and time-dependent cell death in A549 cells. Notably, Brevilin A treatment significantly reduced HIF-1α mRNA expression while increasing PTEN mRNA levels. Conclusions This study demonstrates that Brevilin A exerts anti-cancer effects in treating lung cancer through a multi-target and multi-pathway manner, with the HIF pathway potentially being involved. These results lay a theoretical foundation for the prospective clinical application of Brevilin A.

Regional inequality significantly influences sustainable development and human well-being. In China, there exists pronounced regional disparities in economic and digital advancements; however, scant research delves into the interplay between them. By analyzing the economic development and digitalization gaps at regional and city levels in China, extending the original Cobb-Douglas production function, this study aims to evaluate the impact of digitalization on China’s regional inequality using seemingly unrelated regression. The results indicate a greater emphasis on digital inequality compared to economic disparity, with variable coefficients of 0.59 for GDP per capita and 0.92 for the digitalization index over the past four years. However, GDP per capita demonstrates higher spatial concentration than digitalization. Notably, both disparities have shown a gradual reduction in recent years. The southeastern region of the Hu Huanyong Line exhibits superior levels and rates of economic and digital advancement in contrast to the northwestern region. While digitalization propels economic growth, it yields a nuanced impact on achieving balanced regional development, encompassing both positive and negative facets. Our study highlights that the marginal utility of advancing digitalization is more pronounced in less developed regions, but only if the government invests in the digital infrastructure and education in these areas. This study’s methodology can be utilized for subsequent research, and our findings hold the potential to the government’s regional investment and policy-making.

The rapid increase in population and economy, coupled with accelerated urbanization, is placing immense pressure on the water–energy–food (WEF) system. In this context, the water–energy–food nexus framework has emerged, recognizing the interdependencies and interactions among water, energy, and food systems, with the aim of optimizing resource management through cross-sectoral collaboration to promote sustainable development. Understanding the spatio-temporal differentiation patterns of the WEF nexus and elucidating the driving mechanisms behind changes in their coupling relationships is essential. This knowledge is crucial for ensuring the security of each subsystem and enhancing the overall sustainability of interconnected systems through coordinated efforts. To address these challenges, this study first established evaluation indicators for water, energy, and food security to quantify their levels and spatio-temporal dynamics. Subsequently, the degrees of coupling coordination within the WEF nexus were calculated. Finally, the WEF nexus’s spatial correlations were analyzed by using a spatial autocorrelation model. Spatial econometric models then identified key factors affecting its coordination. The results revealed significant spatial heterogeneity in water, energy, and food security across mainland China’s provinces. From 2002 to 2022, water security improved substantially in 87% of the provinces, while energy security began to improve in the eastern regions following a phase of high consumption. Food security saw significant enhancements, particularly in Inner Mongolia and the northeastern provinces. The overall coupling coordination of the WEF nexus improved across 30 provinces, progressing toward primary coordination. However, Henan and Anhui provinces experienced fluctuations in WEF nexus coordination. Spatial correlation analysis showed upward trends and increased clustering in WEF nexus coordination. Factors such as economic development and population positively influenced coordination, while economic agglomeration, education, and effective irrigation area had negative effects. This study elucidates the complex interconnections and key influencing factors within the WEF nexus, providing a reference framework and practical recommendations for equitable resource management.

Cotton is an important agricultural crop and strategic resource. China is currently the country with the largest global cotton production and consumption, but few studies have systematically analyzed the dynamic relationship between factor price change (FPC) and cotton production pattern evolution (CPPE). Based on provincial panel data from the main cotton planting areas from 1985 to 2021, this paper used spatial econometric models to empirically analyze the impact of FPC including labor price, production material cost, and mechanical cost on CPPE from the perspective of mechanical substitution difficulty. The findings are that (1) FPC significantly affected CPPE, specifically the rise of labor price induced the demand for mechanical substitution, resulting in a significant cotton agglomeration effect; (2) spatial econometric analysis found that FPC had a significant spatial spillover effect on CPPE in adjacent regions; and (3) the transfer analysis found that higher mechanical substitution difficulty exerted an inhibitory effect on cotton planting, leading to a gradual shift of the main cotton planting areas from the Yangtze River Basin and Yellow River Basin with high labor prices to the Northwest Inland region with lower labor prices. Updating the production technology and improving the efficiency of cotton specialization are effective strategies. The results are valuable for policy making related to the development of China’s cotton industry.

Approximately 35 % of Chinese cities are situated in mountainous areas, where rapid urban expansion on slopes has led to the degradation of urban ecosystem health, marked by the loss of natural landscapes, diminished resilience, and reduced ecosystem services. However, the impact of vertical urban growth on ecosystem health, especially in terms of temporal dynamics, distribution, and underlying mechanisms, remains poorly understood. Chongqing, a typical mountainous metropolis, was selected to investigate these impacts over the past two decades. By integrating the slope spectrum (SS), climbing index (CI) of built-up land, and ecosystem health index (EHI), we explored how urban expansion has affected the EHI. Additionally, we developed a method for identifying the expansion advantage slope range (EASR), which can track dynamic slope-climbing urban expansion. Our findings revealed that the built-up land expansion in Chongqing was primarily concentrated in the central areas of the western region. From 2000 to 2010, this expansion occurred primarily in urban built-up areas and shifted to other built-up areas between 2010 and 2020. Although the Climbing Index was −0.11, the EASR results indicated an increasingly significant slope-climbing trend, with slopes of built-up land increasing from [1.17, 8.25] to [1.42, 8.48]. Notably, when expansion occurs on slopes exceeding 12°, the decline in the EHI becomes significantly more pronounced, with the impact coefficient rising from 0.201 to 0.447. This study reveals the fundamental relationship between slope-climbing urban expansion and ecosystems, providing valuable insights for urban planning and sustainable development in mountainous regions.

Abstract As the Earth's Third Pole and the Asian water tower, the Qinghai‐Tibet Plateau (QTP) plays a key role in global climate regulation and biodiversity maintenance. Living in harmony with nature is vital for local and global sustainable development. Current research on the conflicted or coordinated relationship between humans and nature on the QTP at a fine spatial scale remains limited. To fill the gap, we developed the human activity intensity index (HAI) and eco‐environmental quality index (EQI) at 1‐km resolution and proposed a four‐quadrant diagram approach to explore the dynamics between them. The results show a coordinated development on the QTP as the HAI and EQI both increased from 2000 to 2020, and the ratio of coordinated areas to conflicted areas was 5:1. High HAI areas were mainly in big cities such as Xining, Lhasa, Haidong, Xigaze, and along traffic lines. The significant conflicted areas were mainly outside the Lhasa metropolitan, south of the Hengduan Mountains, and along some new roads, and reduced by 8% between 2000–2010 and 2010–2020. The area of high HAI but low EQI was the smallest proportion, mainly in southern Qinghai Lake, southern Brahlung Zangbo River, Gobi oases, and western transport lines, but it implies the highest risk of ecosystem degradation. This research expands the fundamental methodology to address complex human‐natural relationships and provides implications for the sustainable development of fragile ecosystems.

Non-optimal temperatures significantly influence public health. However, the role of socio-economic factors in modulating health risks associated with non-optimal temperatures varies geographically and among different populations. Thus, the meteorological, air quality, health data, and socio-economic indicators were obtained from 23 districts in North and 48 districts in East China, respectively. Employing a two-stage meta-analysis, the exposure-response relationship was constructed for temperature against mortality from non-accidental causes, cardiovascular and cerebrovascular diseases, and respiratory illnesses. Furthermore, a non-linear spline regression was applied to assess the impact of socio-economic indicators on the exposure-response relationship and predicted future risks under various Shared Socioeconomic Pathways. The results revealed that the influence of socio-economic factors on the exposure-response curve showed heterogeneity in East China and North China. In North China, the shape of the exposure-response curve changed greatly under different socio-economic levels, while it remained similar in East China. In East China, the relative risk of heat and cold exposure was reduced in regions with high GDP, high levels of public finance, good medical services, and a low proportion of the elderly population. Specifically, the risk of non-accidental deaths due to heat shows a nearly linear negative correlation with per capita GDP in East China, with a decrease of the relative risk by 0.075 for every 10 thousand yuan increase in per capita GDP. Future projections indicate that population aging plays a decisive role in shaping the exposure-response curves. Although economic growth can reduce the risk of heat-related mortality, the combined effect of population aging and economic increase results in steeper exposure-response curves in both hot and cold temperature ranges in the future. In conclusion, although spatial variations in relative risk changes still exist, enhancing the adaptive capacity of populations can mitigate health risks associated with future climate change.

The relationship between stakeholders and the environment influences sustainable development and human wellbeing. To illustrate the multi-stakeholder perceptions of environmental pollution in China, we interpreted a feedback loop in the perception-behavior-environment nexus from the perspective of the coupled human-environment system, measured the differences of environmental perceptions among five stakeholders (the public, government, media, companies, and scientists) and regions (including 31 provinces, autonomous regions, and municipalities in China, with exceptions of Taiwan of China, Hong Kong of China, and Macao of China due to a lack of data) using big data, and made a comparison between the perceptions and the actual pollution situation. The results showed that the five stakeholders exhibited similar perceptions of environmental pollution at the national scale, with air pollution being of most concern, followed by water pollution and soil pollution. There were significant spatial differences in environmental perceptions. All stakeholders in the developed regions in eastern China paid relatively high attention to environmental issues, while those in the northwestern regions paid much less attention. There existed a mutual influence and interaction among the different stakeholders. More attention should be paid to air pollution in Xinjiang Uygur Autonomous Region and Ningxia Hui Autonomous Region, water pollution in Hainan Province, Inner Mongolia Autonomous Region, Heilongjiang Province, and Jilin Province, and soil pollution in Hainan Province, Fujian Province, and Jilin Province. This paper provides a research paradigm on multi-stakeholder environmental perceptions based on big data, and the results provide a background reference for regional environmental governance.

Understanding the relationship between urbanization and vegetation is essential for sustainable urban development. Over the last few decades, China has experienced rapid and dramatic urbanization along with impressive land transformations. However, the dynamic relationship between urban expansion and vegetation cover lacks enough understanding. We proposed an urbanization-vegetation cover coordination index (UVCI) by combining the physical boundaries of cities at 10-year intervals and the 250 m vegetation index, and measured the conflict or coordination relationships between urbanization and vegetation cover for 338 cities in China from 1990 to 2018. The results show that China has experienced a process of rapid, large-scale, but uneven urban expansion over the past 30 years, with urban areas expanding by approximately 556 %. Urbanization has made China’s urban areas less green, yet vegetation cover changes vary between newly developed and older urban areas. There is a substantial tendency for vegetation degradation in the newly urbanized areas, whereas vegetation cover has generally improved in the older urban areas. The vegetation in non-urban areas has been showing a noticeable greening trend after 2010, with NDVI maintaining an annual growth rate of 0.89 %. The relationship between urbanization and urban vegetation cover in China is becoming increasingly coordinated. The proportion of conflict cities decreased from 93 % in 1990–2000 to 15 % in 2010–2018. The spatial heterogeneity of the UVCI is apparent, with northern Chinese cities having achieved a largely coordinated urban-vegetation relationship, while most southern cities still face challenges. The methodology of this study can be used as a reference for subsequent research, and the findings can help shape government policies that will support green and sustainable urban development in China.

The sustainability of coupled human and natural systems (CHANS), linked to several of the United Nation’s Sustainable Development Goals, affects both global sustainable development and human wellbeing. However, few studies have explored the relationship between the whole human system and the natural system from the perspective of supply and demand. Based on ecosystem service concept and Maslow’s hierarchy of needs, we constructed an ecosystem services supply index (ESSI) and a human demand index (HMDI) and then analyzed the spatial mismatch of the ESSI and HMDI in 338 prefecture cities in China. We propose a supply-demand balance index inspired by the doughnut theory and demonstrate the conflicts and synergies between ecosystems and human systems. Our results show that the ESSI decreased from 2000 to 2010, but remained almost unchanged from 2010 to 2020. The low ESSI values were mainly distributed over the North China Plain, the Yangtze River Delta, and the Sichuan Basin. The HMDI increased from 2000 to 2020, but the rate of increase has slowed since 2010. The high HMDI values were mainly distributed over the east coast of China, Inner Mongolia, and part of Xinjiang province. From 2000 to 2020, the cities with spatial mismatches of the ESSI and HMDI showed a significant increase and spatial agglomeration. The sustainability of most regions showed a decreasing trend, and the higher the value of the supply-demand balance index, the faster the speed of decrease. Overall, there were more regions in a state of conflict between the natural ecosystem and humans than in a synergistic state, although this number has decreased since 2010. Urban agglomerations and western regions should receive more attention for their ecological health. This study provides a new methodology to assess the sustainability of CHANS that could be applied to other locations. Our findings could support the Chinese government in regional ecosystem governance and territorial space planning.

Abstract Since spring 2020, the human world seems to be exceptionally silent due to mobility reduction caused by the COVID-19 pandemic. To better measure the real-time decline of human mobility and changes in socio-economic activities in a timely manner, we constructed a silent index (SI) based on Google’s mobility data. We systematically investigated the relations between SI, new COVID-19 cases, government policy, and the level of economic development. Results showed a drastic impact of the COVID-19 pandemic on increasing SI. The impact of COVID-19 on human mobility varied significantly by country and place. Bi-directional dynamic relationships between SI and the new COVID-19 cases were detected, with a lagging period of one to two weeks. The travel restriction and social policies could immediately affect SI in one week; however, could not effectively sustain in the long run. SI may reflect the disturbing impact of disasters or catastrophic events on the activities related to the global or national economy. Underdeveloped countries are more affected by the COVID-19 pandemic.

The Tibetan Plateau (TP) is undergoing rapid urbanization. To improve urban sustainability and construct ecological security barriers, it is essential to quantify the spatial patterns of urbanization level on the TP, but the existing studies on the topic have been limited by the lack of socioeconomic data. This study aims to quantify the urbanization level on the TP in 2018 with Luojia1-01 (LJ1-01) high-resolution nighttime light (NTL) data. Specifically, the compounded night light index is used to quantify spatial patterns of urbanization level at multiple scales. The results showed that the TP had a low overall urbanization level with a large internal difference. The urbanization level in the northeast, southeast and south of the TP was relatively high, forming three hotspots centered in Xining City, Lhasa City and Shangri-La City, while the urbanization level in the central and western regions was relatively low. The analysis of influencing factors, based on the random forest model, showed that transportation and topography were the main factors affecting the TP's spatial patterns of urbanization level. The comparison analysis with socioeconomic statistics and traditional NTL data showed that LJ1-01 NTL data can be used to more effectively quantify the urbanization level since it is more advantageous for reflecting the spatial extent of urban land and describing the spatial structure of socioeconomic activities within urban areas. These advantages are attributed to the high spatial resolution of the data, appropriate imaging time and unaffected by saturation phenomena. Thus, the proposed LJ1-01 NTL-based urbanization level measurement method has the potential for wide applications around the world, especially in less-developed regions lacking statistical data. Using this method, we refined the measurement of the TP's urbanization level in 2018 for multiple scales including the region, basin, prefecture and county levels, which provides basic information for the further urban sustainability research on the TP.

The emergence and enduring diffusion of COVID-19 has had a dramatic impact on cities worldwide. The scientific aim of this study was to introduce geospatial thinking to research related to infectious diseases, while the practical aim was to explore the impact on population movements and urban linkages in the longer term following a pandemic outbreak. Therefore, this study took 366 cities in China as the research subjects while exploring the relationship between urban contact and the outbreak of the pandemic from both national and regional perspectives using social network analysis (SNA), Pearson correlation analysis and multi-scale geographically weighted regression (MGWR) modeling. The results revealed that the number of COVID-19 infections in China fluctuated with strain variation over the study period; the urban contact network exhibited a significant trend of recovery. The pandemic had a hindering effect on national urban contact, and this effect weakened progressively. Meanwhile, the effect exhibited significant spatial heterogeneity, with a weakening effect in the eastern region ≈ northeast region > central region > western region, indicating a decreasing phenomenon from coastal to inland areas. Moreover, the four major economic regions in China featured border barrier effects, whereby urban contact networks constituted by cross-regional flows were more sensitive to the development of the pandemic. The geostatistical approach adopted in this study related to infectious disease and urban linkages can be used in other regions, and its findings provide a reference for China and other countries around the world to respond to major public health events.

Abstract Food security is closely related to individual livelihood and social stability, and assessing the state of food security is essential for making agricultural policies. Nonetheless multi‐scale assessment of national food security state with explicit consideration of availability and access remains to be resolved. In this study, a spatially explicit crop model was used to simulate the production of major crops in China (i.e., wheat, maize, rice, and soybeans). Food production (as simulated by the crop model) and GDP per capita relative to the global average were then used to develop food security indicators to evaluate China's food security levels on grid, provincial, and economic zone scales. The Getis–Ord method was further applied to analyze the spatial aggregation of food security and food insecurity provinces. Results show that food security situation improved in mainland China during 1990–2015, attributed largely to the enhanced purchasing power. On the grid scale, changes in food security state went through two stages: Before 2000, the regions in the eastern part of the Hu Line were food security, while the regions in the western part were food insecurity; after 2000, the state of food security greatly improved from insecurity to security in Northwest China, and the areas of the highest security level considerably increased in eastern China. On the provincial scale, food security state in most provinces improved or almost unchanged over time. Exception was found in coastal provinces, with food security state was greatly affected by urbanization. Food security hot spots were primarily detected in central China, while cold spots were detected in Xinjiang, Qinghai, and Tibet. On the economic zone scale, food security areas in the eastern part decreased during 1990–2010 but increased thereafter, while food security areas in the other three economic zones increased from 1990 to 2015. To ensure food security, China should maintain the arable land areas, improve the quality of farmlands, mobilize farming enthusiasm, and advance agricultural marketization.

Urbanization is one of the most consequential human activities on earth. The contradictions between urbanization and the eco-environment are particularly prominent in urban agglomerations with high industrial concentrations. Based on the Environmental Kuznets Curve (EKC) theory, we propose the hypothesis of the Urbanization-EKC (UEKC), which states that in the process of urbanization, eco-environmental quality first deteriorates and then improves, following a “U” trend. Taking 19 Chinese urban agglomerations as empirical cases, this paper analyzed the multi-dimensional coupling curves between urbanization and the eco-environment. The results show that the coupling curves between urbanization and the eco-environment are heterogeneous, as a result of differences among urban agglomerations and various eco-environmental indicators. In five mega-urban agglomerations, we found that the coupled curve of urbanization and eco-environmental quality index (EQI) is a compound function containing logarithm and quadratic terms, following the “U” curve shape of “quick down, slow up”; the turning point of EQI improvement was found at an urbanization rate of 47%. The empirical results validate that the UEKC hypothesis is tenable for developed urban agglomerations. This study provides a methodological reference for researching the evolutionary relationship between urbanization and the eco-environment and provides decision support for a more harmonious development of humans and nature in China's urban agglomerations.

The development zone (DZ) is a typical representative of China's regional economic development model. By comparing the development pattern of DZs in China from 2005 to 2017, we find that there was strong imbalance in 2005, but this trend decreased in 2017, mainly due to the rapid increase in the number of DZs in the central and western regions. Moreover, there is a significant correlation between the spatial pattern of the DZs and economic development. But compared with the spatial pattern of economic development, DZs have dispersed more strongly from 2005 to 2017. Indeed, the rapid dispersion of DZs has not fundamentally changed the imbalanced pattern of China's economic development from 2005 to 2017.

Monitoring human activities in border areas is challenging due to the complex geographical environment and diverse people. China has the longest terrestrial boundary and the highest number of neighboring countries in the world. In this study, a human activity intensity index (HAI) was proposed based on land cover, population density, and satellite-based nighttime light for a long-term macroscopic study. The HAI was calculated at 1 km resolution within the 50 km buffer zone of China’s land boundary on each side in 1992, 2000, 2010, and 2020, respectively. Results show that human activity is low in about 90% of the study area. Overall, the HAI on the Chinese side is higher than that on the neighboring side, and the intensity of land use on the Chinese side has increased significantly from 1992 to 2020. Among China’s neighbors, India has the highest HAI with the fastest growth. With the changes in the HAI between China and its neighboring countries, four regional evolution patterns are found in the study area: Sino-Russian HAI decline; Sino-Kazakhstan HAI unilateral growth; Indian HAI continuous growth; China and Indochina HAI synchronized growth. Hotspot analysis reveals three spatial evolution patterns, which are unilateral expansion, bilateral expansion, and cross-border fusion. Both the “border effect” and “agglomeration effect” exist in border areas. The HAI changes in border areas not only impact the eco-environment but also affect geopolitics and geoeconomics. The HAI can be used as an instrument for decision-making and cooperation between China and neighboring countries in such areas as ecological protection, border security, and border trade.

Based on socioeconomic statistical data, transport data, and network big data, the urban connection index (UCI) was constructed in terms of industry, transportation, information, and innovation, and the high-quality development index (HDI) was established from five aspects: innovation, coordination, green development, openness, and sharing. Taking Lanzhou-Xining urban agglomeration as a case, the urban connection intensity and high-quality development level were measured to analyze the relationship between them. From 2012 to 2018, the UCI and HDI of each city showed different degrees of growth. Note that there exist significant regional differences, with Lanzhou and Xining having the largest difference. The biggest gap among cities lies in the innovative connection intensity. Moreover, urban external connections are closely related to high-quality development, especially innovation and green development. For every 1% increase in industrial and transport connection, the HDI will increase by 0.317% and 0.159%, respectively. This study provides a methodological reference for measuring urban connectivity and provides decision support for high-quality development in China and other countries.

The outbreak of COVID-19 exposed the shortage of medical resources and the imbalance between cities in China. To better reveal this inequality, this study uses cartograms and half-violin plots to visualize the hospital beds per 10,000 people, medical personnel per 10,000 people and number of 3A hospitals in China. We find that China has made remarkable progress in the primary healthcare system; however, there is still a significant imbalance in the distribution of medical resources, especially the high-quality part. There is a two- to three-fold gap in primary medical care resources between diverse cities, and high-quality medical resources are highly concentrated in cities with high administrative rank and influence.

Objective: Axillary lymph node dissection (ALND) may be unnecessary in 20%–60% of breast cancer patients with sentinel lymph node (NSLN) metastasis. The aim of the present study was to review the medical records of Chinese patients with early-stage breast cancer and positive NSLN metastasis to identify clinicopathological characteristics as risk factors for non-NSLN metastasis.Methods: The medical records of 2008 early-stage breast cancer patients who received intraoperative sentinel lymph node biopsy (SLNB) between 2006 and 2016 were retrospectively reviewed. These patients were clinically and radiologically lymph node-negative and had no prior history of receiving neoadjuvant chemotherapy or endocrinotherapy. The clinicopathological characteristics of patients with positive NSLN metastasis who underwent ALND were investigated.Results: In the present study, 296 patients with positive NSLN metastases underwent ALND. Positive non-NSLN metastases were confirmed in 95 patients (32.1%). On univariate analysis, ≥ 3 positive NSLN metastases (P P = 0.023), and lymphovascular invasion (P = 0.04) were associated with non-NSLN metastasis (P Conclusions: The number of positive NSLNs, NSLN macrometastases, and lymphovascular invasion were correlated with non-SLN metastasis. The number of positive SLNs was an independent predictor for non-NSLN metastasis. When 2 or 3 risk factors were present in one patient, the probability of non-NSLN was higher than that in the American College of Surgeons Oncology Group Z0011 trial (27.3%); thus, avoiding ALND should be considered carefully.

Since the beginning of 2020, the COVID-19 epidemic has dramatically influenced the human socioeconomic system. If we conceive of the city as a complex organism with a metabolism, then the daily flows of people, materials, and information into and out of a city can be regarded as its metabolism. To evaluate the real-time impact of COVID-19 on a city’s economy and society, we construct a health index of cities (HIC) using human mobility big data from Baidu and analyze the temporal and spatial changes of the HIC in China. The results show that both internal and intercity population movements have been significantly affected by the COVID-19 epidemic, and the decline in both was more than 50% at some points. The intercity movement is more affected than the intracity movement, and the impact is more sustained. Compared with the same period before the outbreak, the HIC in China decreased by 28.6% from January 20 to April 21, 2020. The deterioration rate of the HIC was faster than the growth rate of COVID-19 cases, but the improvement in the HIC was much slower than the decline in COVID-19 cases. Although the HIC is highly correlated with COVID-19 in both the spatial and temporal dimensions, the effect of the epidemic on the HIC varied across regions. The HIC fell more significantly in provincial capitals, such as Beijing, Shanghai, Guangzhou, and Zhengzhou, and in urban agglomerations, and these cities’ HICs were lower with a longer-lasting reduction. This study can serve as a frame of reference for studying the real-time impact of the epidemic, helping cities’ policymakers to quickly assess its socioeconomic impact. By extension, this index can be applied to other countries and other public health emergencies.

Abstract Background Breast cancer is the most common cancer among women worldwide. Here, we report the prevalence of BRCA1/2 mutations in patients with high‐risk breast cancer from Inner Mongolia and Jilin, China, which was a part of a nationwide project on the detection of BRCA1/2 mutations in Chinese patients with hereditary breast cancer. Methods According to the criteria, index patients from a total of 245 independent families were initially recruited. All 49 exons of BRCA1 and BRCA2 and adjacent noncoding regions were screened for mutations based on next‐generation sequencing from collected saliva. Results We detected 17 BRCA1/2 variants in 18 of 216 (8.3%) index patients with high‐risk breast cancer. Among these, seven mutations were novel, including four BRCA1 mutations (c.123_124delCAinsAT, c.5093_5096delCTAA, c.5396‐2A>G, and c.2054delinsGAAGAGTAACAAGTAAGAAGAGTAACAAGAAG), and three BRCA2 mutations (c.304A>T, c.7552_7553insT, and c.9548_9549insA). The BRCA1/2 variants were identified in 14% (8/57) of the patients with triple‐negative breast cancer and in 6.3% (10/159) of the patients with non‐triple‐negative breast cancer. There was no significant difference between the two groups (p = 0.07). A higher frequency for BRCA1 mutations was observed in patients with triple‐negative breast cancer than in those with non‐triple‐negative breast cancer (12.3% vs. 2.5%, p = 0.004). The frequencies of the BRCA2 mutations were not significantly different between patients with triple‐negative breast cancer and those with non‐triple‐negative breast cancer (1.8% vs. 3.8%, p = 0.46). Conclusion We found that patients with triple‐negative breast cancer had a higher frequency of BRCA1 mutations than those with non‐triple‐negative breast cancer. In this study, no significant associations between the BRCA1/2 mutation status and age, family history of breast cancer, ovarian cancer, pancreatic cancer and prostate cancer, number of primary lesions, tumor size, or lymph node metastasis were observed.

The Tibetan Plateau (TP) is an important area that affects global sustainable development. Quantifying spatiotemporal patterns of urbanization is crucial for maintaining the sustainability on the TP. This study took Xining City, the largest city on the TP, as an example to understand the urban expansion in this region in the past 50 years. We combined the high-resolution spy satellite data and China’s long-term urban land dataset (CULD) to quantify the urban expansion of Xining City. The object-oriented random forest classification was performed to extract urban land from spy satellite data in 1969, and the inter-annual correction was used to combine urban land information from 1969 to 2017. We found that the proposed approach can accurately quantify the urban expansion of Xining City over the past half century with an overall accuracy of 91% and a kappa coefficient of 0.86. Such high accuracy benefits from the fine resolution of spy satellite data and the consistency of CULD. We also found that Xining City experienced accelerated and fragmented urban sprawl to higher altitude areas, as a result of socioeconomic development and topographical limitations. The acceleration of urban expansion was more obvious, and the urban landscape fragmentation was more serious at high altitude areas. Such urban expansion encroached on cropland and grassland, and caused increased risks of landslides and other geological disasters. Therefore, Xining City urgently needs to promote the development of compact cities to control urban sprawl at higher altitude areas and provide a reference for improving urban sustainability across the TP. In this study, we analyzed the urban expansion of Xining city from 1969 to 2017, and provided a reliable way to understand the long-term spatiotemporal urbanization based on remote sensing, which has the potential for wide applications. In addition, the extracted urban information can help to improve the urban sustainability of Xining City and the entire TP.

To study the impact of future climatic changes on hydrology in the Kaidu River Basin in the Tianshan Mountains, two sets of future climatic data were used to force a well-calibrated hydrologic model: one is bias-corrected regional climate model (RCM) outputs for RCP4.5 and RCP8.5 future emission scenarios, and the other is simple climate change (SCC) with absolute temperature change of −1~6°C and relative precipitation change of −20%~60%. Results show the following: (1) temperature is likely to increase by 2.2°C and 4.6°C by the end of the 21st century under RCP4.5 and RCP8.5, respectively, while precipitation will increase by 2%~24%, with a significant rise in the dry season and small change in the wet season; (2) flow will change by −1%~20%, while evapotranspiration will increase by 2%~24%; (3) flow increases almost linearly with precipitation, while its response to temperature depends on the magnitude of temperature change and flow decrease is significant when temperature increase is greater than 2°C; (4) similar results were obtained for simulations with RCM outputs and with SCC for mild climate change conditions, while results were significantly different for intense climate change conditions.