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The continuous decrease of low-slope cropland resources caused by construction land crowding poses huge threat to regional sustainable development and food security. Slope spectrum analysis of topographic and geomorphic features is considered as a digital terrain analysis method which reflects the macro-topographic features by using micro-topographic factors. However, pieces of studies have extended the concept of slope spectrum in the field of geoscience to construction land to explore its expansion law, while research on the slope trend of cropland from that perspective remains rare. To address the gap, in virtue of spatial analysis and geographically weighted regression (GWR) model, the cropland use change in the Yangtze River Basin (YRB) from 2000 to 2020 was analyzed and the driving factors were explored from the perspective of slope spectrum. Results showed that the slope spectrum curves of cropland area-frequency in the YRB showed a first upward then a downward trend. The change curve of the slope spectrum of cropland in each province (municipality) exhibited various distribution patterns. Quantitative analysis of morphological parameters of cropland slope spectrum revealed that the further down the YRB, the stronger the flattening characteristics, the more obvious the concentration. The province experienced the greatest downhill cropland climbing (CLC) was Shannxi, while province experienced the highest uphill CLC was Zhejiang. The most common cropland use change type in the YRB was horizontal expansion type. The factors affecting average cropland climbing index (ACCI) were quite stable in different periods, while population density (POP) changed from negative to positive during the study period. This research is of practical significance for the rational utilization of cropland at the watershed scale. [ABSTRACT FROM AUTHOR]

China has entered a critical stage of urbanization transition but still faces unbalanced regional development and uncoordinated urban–rural integration. Studying the regional differences in spatial determinants of land urbanization (LU) is crucial to achieving coordinated regional development of urbanization. However, the spatial determinants of LU remain unclear, especially in terms of their regional differences. Therefore, this study introduced dynamic distribution and spatial analysis to measure regional differences in spatial determinants of LU in China. During 1990–2020, the imbalance of LU in China was constantly decreasing, and the differences in LU among different regions were also decreasing. LU in China had significant spatial dependence and spatial spillover effects, and the trend of group development was gradually becoming obvious. LU in eastern region was more affected by natural factors than in central and western regions, while central and western regions were more affected by socioeconomic factors than in eastern region. This study can provide a scientific reference for understanding the spatial disequilibrium of LU and promoting the regional implementation of LU coordinated development. [ABSTRACT FROM AUTHOR]

Cultivated land fragmentation (CLF) has severely affected China's agricultural production efficiency, large-scale operations, agricultural modernization, and food security. Exploring the spatiotemporal evolution patterns and driving forces of CLF is crucial for agricultural modernization. However, the driving forces of CLF in different agricultural regions in China still need to be clarified. In this study, CLF was measured in 2000, 2010, and 2020 based on remote sensing data with landscape pattern metrics, and the driving forces of spatial differentiation were detected based on a geographical detector model. The overall cultivated land area has slightly declined during the study period while the CLF has intensified. CLF showed significant spatial autocorrelation, with CLF increased-cultivated land decreased (2000 to 2010) and CLF decreased-cultivated land decreased (2010 to 2020). The contribution rate of land use intensity on CLF was the highest among all agricultural regions, excluding the Qinghai Tibet Plateau. In contrast, the contribution rates of other factors significantly varied across agricultural regions. These findings provide scientific support in formulating policies to conserve cultivated land for sustainable use of agricultural resources and CLF management in China. [ABSTRACT FROM AUTHOR]

Burgeoning urbanization is a defining challenge for global carbon emissions mitigation in the coming decades. In this context, achieving low-carbon urbanization remains an urgent issue that demands prompt solutions. The coupling and decoupling relationships between urbanization and carbon emissions play an important role in the coordination of urbanization development and carbon emissions reduction, which has rarely been explored in existing studies, especially in China at the county level. To address this gap, the coupling and decoupling relationship between the urbanization level (UL) and carbon emissions density (CED) was explored using an improved coupling degree model and the Tapio decoupling method in China at the county level from 2000 to 2020. The results showed that the UL and CED of China both exhibited increasing trends, and the spatial distribution was quite similar, with the UL increasing from 0.018 in 2000 to 0.028 in 2020 and the CED increasing from 95.163 ton/km2 in 2000 to 295.746 ton/km2 in 2020. The spatial distribution of hotspots in the UL change differed with time, whereas that in the CED change was relatively stable. However, both of them were concentrated in eastern China. The coupling degrees of the UL and CED in China were 0.348, 0.355, 0.369, 0.370, and 0.338 in 2000, 2005, 2010, 2015, and 2020, respectively, with the moderately unbalanced type (>35%) being dominant at the county level and mainly scattered in eastern China. The changes in the spatial distribution patterns of the 10 subcategories were quite limited, with the systematically balanced type being dominant (89%). The decoupling types of the UL and CED during 2000–2005, 2005–2010, and 2010–2015 were weak decoupling, while those in 2015–2020 were expansive negative decoupling. At the county level, the most significant transition occurred between expansive negative decoupling, strong decoupling, and strong negative decoupling. The proportion of strong decoupling type counties peaked in 2015–2020 (70.86%), whereas that of the strong negative decoupling type counties remained high (17.55%), scattering the country. These findings can advance policy enlightenment of low-carbon urbanization and green development for China against the backdrop of "30·60 dual carbon" goal. [ABSTRACT FROM AUTHOR]

Globally, land-based urbanization had far-reaching impacts on ecosystem health. Determining the spatial relationship between land urbanization and ecosystem health is important for sustainable socioeconomic development and ecological protection. However, existing studies lack research on these relationships in basin regions, which may limit the implementation of effective basin ecological management measures. Based on multi-source data, this study analyzed the spatiotemporal patterns and spatial correlations of land urbanization rate (LUR) and ecosystem health index (EHI) in the Yangtze River basin (YRB) with a series of spatial analysis methods. The results showed that EHI in the YRB decreased by 0.024 during 2000–2020, with a decreasing range of 3.133 %, while LUR increased by 0.216, with an increasing range of 54.135 %. LUR has a significant negative spatial correlation with EHI, with high EHI and high LUR (9.814% in 2020) and high EHI and low LUR (12.397% in 2020) being the main types of agglomeration. The global regression results showed that LUR significantly negatively affected EHI. At the local scale, the LUR positively affected the EHI in the mountainous region, while the opposite was confirmed in the plain region. This study can provide scientific reference for the development of sustainable urban land control measures and basin ecological management measures. [ABSTRACT FROM AUTHOR]

Under the framework of ecological civilisation, the formulation of territorial spatial planning (TSP) and improvement of spatial governance systems are of great practical significance. Since the founding of the People's Republic of China, land-use planning (LUP) has experienced profound changes, and tremendous research efforts have been made in that field. However, systematic studies on LUP history are scarce. To bridge the existing gap, this study traced back to the emergence of LUP, described its practice stages, and analysed the evolution of its classification system and methods. Further, the three rounds of general LUP practice and the current TSP over the past 40 years of the reform and opening-up have been discussed. The evolution of LUP was found to be closely related to economic development and could be broadly divided into four stages. The development of land-use classification in China has been slow and can be divided into five stages according to the evolution of the land classification system and important historical events. The development of LUP methods can be divided into two stages, before and after 1978. Since the economic reform, China has successively conducted three rounds of general LUP under different institutional and policy backgrounds. Future development should aim to innovate the theories and methods of TSP with Chinese characteristics and promote the study of village planning and the construction of TSP systems to achieve rural revitalisation and ecological civilisation. [ABSTRACT FROM AUTHOR]

Ecosystem health in the Yangtze River basin (YRB) shows significant regional differences. Analysis of regional differences and drivers of ecosystem health in YRB is of practical significance for sustainable basin ecological management. However, existing studies lack research on regional differences and driving forces of ecosystem health, especially in big basin regions. Based on multi-source data, this study adopted spatial statistics and distribution dynamics models to quantitatively analyze the regional differences of ecosystem health in the YRB during 2000–2020 and employed the spatial panel model to reveal the driving forces of ecosystem health in the YRB. The ecosystem health index of the upper, middle, and lower reaches of YRB and the entire basin in 2020 was 0.753, 0.781, 0.637, and 0.742, respectively, while they all decreased during 2000–2020. Regional differences in YRB ecosystem health increased during 2000–2020. From the perspective of dynamic evolution, low-level and high-level ecosystem health units evolved to high-level, while medium-high-level ecosystem health units evolved to low-level. High-high (accounting for 30.372% in 2020) and low-low (accounting for 13.533% in 2020) were the main cluster types. Regression result showed that urbanization was the main reason for ecosystem health deterioration. The findings can provide enlightenment to further understand the regional differences of ecosystem health in YRB and provide theoretical reference for the coordinated management of ecosystem at macro-level and the differential regulation of local ecosystem at micro-level in the basin region. [ABSTRACT FROM AUTHOR]

Since the 21st century, crisis events have been frequent and normalized globally, and improving resilience has become the key for the tourism industry to cope with various uncertainty risks. To reveal the reality of the economic resilience of tourism in China, this study employed the autoregressive integrated moving average model (ARIMA) to construct a counterfactual function and integrated with the peaks-over-threshold (POT) model and geographical detector model to evaluate the spatiotemporal evolution and influencing factors of the economic resilience of tourism in China from the resistance and recoverability perspective, with a view to providing a reference for consolidating the resilience of the economic system of tourism in China and promoting the sustainable development of its tourism economy. The results showed that the economic resilience of tourism in China can be divided into four types—robust, self-reliant, laissez-faire, and fragile—based on a baseline resistance of −0.361 and recoverability of 0.342. Under different contraction–recovery cycles, the resistance and recoverability of China's tourism economy have been progressively improved, transforming from the centralized model to the discrete model, from a fragile to a self-reliant type. The type of economic resilience of tourism in China exhibited a clustered contiguous development trend, with obvious zonal distribution characteristics and self-reliant tourism economic resilience areas dominating, but most areas have not yet formed stable economic resilience in their tourism sector. The ecological environment quality, government management ability, and technological innovation level were the main factors affecting the economic resilience of tourism in China. The interactions between different influencing factors were more significant in strengthening the tourism economic resilience. [ABSTRACT FROM AUTHOR]

The spatial relationships between traffic accessibility and supply and demand (S&D) of ecosystem services (ESs) are essential for the formulation of ecological compensation policies and ESs regulation. In this study, an ESs matrix and coupling analysis method were used to assess ESs S&D based on land-use data for 2000, 2010, and 2020, and spatial regression models were used to analyze the correlated impacts of traffic accessibility. The results showed that the ESs supply and balance index in the middle reaches of the Yangtze River urban agglomeration (MRYRUA) continuously decreased, while the demand index increased from 2000 to 2020. The Gini coefficients of these indices continued to increase but did not exceed the warning value (0.4). The coupling degree of ESs S&D continued to increase, and its spatial distribution patterns were similar to that of the ESs demand index, with significantly higher values in the plains than in the montane areas, contrasting with those of the ESs supply index. The results of global bivariate Moran's I analysis showed a significant spatial dependence between traffic accessibility and the degree of coupling between ESs S&D; the spatial regression results showed that an increase in traffic accessibility promoted the coupling degree. The present results provide a new perspective on the relationship between traffic accessibility and the coupling degree of ESs S&D, representing a case study for similar future research in other regions, and a reference for policy creation based on the matching between ESs S&D in the MRYRUA. [ABSTRACT FROM AUTHOR]

Considering the current global goal of carbon neutrality, the relationship between cultivated land intensive use (CLIU) and carbon emission efficiency (CEE) should be explored to address the global climate crisis and move toward a low-carbon future. However, previous work in this has been conducted at provincial/regional scales and few have identified the spatial correlation between CLIU and CEE at the scale of large river basins. Therefore, this study explored the spatiotemporal characteristics of CLIU, cultivated land carbon emissions (CLCE), and CEE, as well as the spatial correlation between CLIU and CEE in the Yellow River Basin (YRB), China. A comprehensive evaluation model, the Intergovernmental Panel on Climate Change (IPCC) coefficient methodology, existing data envelopment analysis model, and bivariate spatial autocorrelation models were used to analyze statistical data from 2005 to 2017. We found that the overall CLIU and CLCE values in the YRB exhibited a continuous increase; the average carbon emission total efficiency and carbon emission scale efficiency first decreased and then increased, and the average carbon emission pure technical efficiency gradually decreased. Areas of high CLCE were concentrated in eastern areas of the YRB, whereas those of high CLIU, carbon emission total efficiency, carbon emission scale efficiency, and carbon emission pure technical efficiency predominantly appeared in the eastern areas, followed by central and western areas of the YRB. Spatial analysis revealed a significant spatial dependence of CLIU on CEE. From a global perspective, the spatial correlations between CLIU and CEE changed from positive to negative with time. Moreover, the aggregation degree between CLIU and CEE gradually decreases with time, while the dispersion degree increases with time, and the spatial correlation gradually weakens. The local spatial autocorrelation further demonstrates that the number of high–low and low–high clusters between CLIU and CEE gradually increases over time, while the number of high–high and low–low clusters gradually decreased over time. Collectively, these findings can help policymakers formulate feasible low-carbon and efficient CLIU policies to promote win–win cooperation among regions. [ABSTRACT FROM AUTHOR]

Objectives: To expand the genotypes and phenotypes of sodium voltage-gated channel alpha subunit 1 (SCN1A)-related epilepsy. Methods: We retrospectively collected the clinical and genetic information of 22 epilepsy patients (10 males, 12 females; mean: 9.2 ± 3.9 years; 3.9–20.3 years) carrying 22 variants of SCN1A. SCN1A mutations were identified by next-generation sequencing. Results: Twenty-two variants were identified, among which 12 have not yet been reported. The median age at seizure onset was 6 months. Sixteen patients were diagnosed with Dravet syndrome (DS), two with genetic epilepsy with febrile seizures plus [one evolved into benign epilepsy with centrotemporal spikes (BECTS)], one with focal epilepsy, one with atypical childhood epilepsy with centrotemporal spikes (ABECTS) and two with unclassified epilepsy. Fourteen patients showed a global developmental delay/intellectual disability (GDD/ID). Slow background activities were observed in one patient and epileptiform discharges were observed in 11 patients during the interictal phase. Significance: This study enriches the genotypes and phenotypes of SCN1A-related epilepsy. The clinical characteristics of patients with 12 previously unreported variants were described. [ABSTRACT FROM AUTHOR]

Aim and objective: S100B has been found abundantly expressed in microglia during cerebral ischemia. However, S100B effects on phenotype changes and migration of microglia are unclear.Methods: Real-time PCR of S100B, M1 and M2 markers were tested to characterize phenotypic changes in microglia in mice middle cerebral artery occlusion (MCAO) model. Migration assay and additional mechanism studies were performed to elucidate the role of NF-κB in S100B-mediated microglia M1/M2 phenotype change and migration. Finally, S100B treatment on MCAO models was performed to show the in vivo evidence.Results: S100B was identified as an induced gene with its pattern in accordance with M1 markers in mice MCAO model. That S100B was promoted by M1 stimuli whereas inhibited by M2 stimuli further confirmed S100B a M1 marker. Moreover, S100B promotes microglia M1 polarization with enhanced migration ability and inhibits M2 polarization. Additionally, NF-κB is essential in S100B control in microglia M1/M2 polarization and migration. Furthermore, S100B aggravated cerebral ischemia in murine MCAO model and exacerbated the microglia M1 polarization and migration.Conclusions: Our findings demonstrate that S100B promotes microglia M1 polarization to aggravate cerebral ischemia, and provide a better understanding on the therapeutic effects of S100B and/or its antagonist/neutralization antibody in stroke. [ABSTRACT FROM AUTHOR]

Background: Early and accurate prediction of outcome in acute stroke is important. The aim of this prospective study was to explore the correlation between serum triiodothyronine level and prognosis in acute ischemic stroke patients.Methods: A prospective observational study which included 359 consecutive patients with acute ischemic stroke from December 2014 to November 2015 was interrogated. Serum triiodothyronine (T3) concentrations were measured on admission to understand their value in predicting functional outcome within 90 d using multivariable models adjusted for confounding factors. Receiver operating characteristic (ROC) curves were calculated to define the best cut-off value of triiodothyronine to predict outcome. The accuracy of the test was assessed measuring the area under the ROC curve (AUROC).Results: Triiodothyronine was significantly decreased in patients with an unfavorable functional outcome as compared to patients with a favorable functional outcome within 90 d (p= 0.01). Binary logistic regression analyses revealed that lower triiodothyronine concentrations on admission were associated with a risk for poor outcomes (OR 0.05, 95% CI 0.01–0.25;p< 0.01). In addition, in ROC curve analysis, triiodothyronine may improve the National Institutes of Health Stroke Scale (NIHSS) score in predicting functional outcome. The combined model AUROC was 0.84 for 30 d and 0.91 for 90 d, which were both significantly higher than the AUROCs of original NIHSS (0.83 and 0.87), triiodothyronine (0.64 and 0.69) and age (0.57 and 0.68) (allp< 0.05).Conclusions: Low serum triiodothyronine levels can be a predictive marker of short-term outcome after ischemic stroke. A combined model (triiodothyronine, age and NIHSS score) can add significant additional predictive information to the clinical score of the NIHSS. [ABSTRACT FROM AUTHOR]

Sound ecosystems are a precondition for the sustainable survival and development of human society. However, ecological deterioration caused by socioeconomic activities can result in increasing pressure on ecosystems. Exploration of the spatial interaction between ecosystem and economic development under the background of high-quality and green development is, therefore, necessary. In this study, we analyzed the spatial interaction between the ecosystem services value (ESV) and economic development with the economic and ecological coupling index method based on high-resolution remote-sensing land-use data and socioeconomic statistical data in Hunan Province from 2000 to 2018. The results revealed that the ESV provided by the ecosystems in Hunan Province decreased by US$1256.166 million from 2000 to 2018. The areas with high ESV per unit area were distributed in the mountainous areas, while the areas with low ESV per unit area were distributed in the major cities and their surroundings. The bivariate spatial autocorrelation analysis showed that the ESV had significant spatial dependence on the economic development. In addition, the coupling analysis documented that the relationship between the ESV and economic density was mostly in the low conflict and potential crisis states. These results provide important guidance for the coordinated development of the regional economy and ecosystem conservation. [ABSTRACT FROM AUTHOR]