Serum apoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC) is a novel stroke biomarker.

BACKGROUND: Apoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC) is a promising stroke biomarker. However, a large study of human serum ASC has not yet to be reported; additionally, the diagnostic value of prehospital concentration and practicality of ASC remains unknown. METHODS: We recruited 774 Chinese stroke patients, including 523 with ischemic stroke (IS) and 251 with hemorrhagic stroke (HS) within 14 days following symptom onset in the emergency department, alongside 481 healthy individuals and 64 cognitive impairment patients as controls. Serum ASC concentrations were determined using automated chemiluminescence immunoassay, exploring the relationship between serum ASC concentration and subtypes, severity, and sampling timepoints of stroke. RESULTS: ASC concentrations were significantly higher in stroke patients compared with all controls (P < 0.001). HS patients had greater ASC concentrations than IS patients (P < 0.05). With increasing ASC concentration, the proportion of severe cases increased. The area under the receiver operating characteristic curve (AUC) for differentiating between healthy individuals and stroke patients in the hyperacute phase was 0.78; this markedly improved (0.90) when considering samples from healthy individuals and patients with subarachnoid hemorrhage (SAH) ≤ 3  h from last-known-well (LKW). CONCLUSIONS: Serum ASC is a valuable biomarker for stroke differentiation and aids in the clinical diagnosis of stroke severity and subtypes.

Dynamic evolutionary characteristics and influence mechanisms of carbon emission intensity in counties of the Yangtze River Delta, China.

Clarifying the intrinsic mechanism of county carbon emission intensity (CEI) is essential for guiding the realization of a low-carbon economy as well as for the strategic goals of carbon peaking and carbon neutrality. However, at present, scholars mostly focus on provincial and city scales, with the identification of influencing factors and spatial effect mechanisms of CEI rarely included in the analysis framework. Herein, with the help of three spatial weight matrices, the spatial autocorrelation, the "F + S" influence factor identification method, and the spatial panel econometric model were used to analyze the evolutionary paths and influencing factors of CEI for 209 counties in the Yangtze River Delta (YRD) from 2007 to 2020. The results show that (1) the CEI of the YRD decreased from 1.998t/104 RMB to 0.858t/104 RMB. Furthermore, the spatial pattern was low in the southeast and high in the northwest, with high-value areas concentrated in municipal districts and resource-based counties. (2) Moran's I spatial autocorrelation index indicated significant spatial clustering of county CEI. (3) Financial science and technology expenditure, industrial structure, share of urban built-up land, and the urban-rural income gap affected the change in CEI and its spatial effect, whereas total imports and exports had a significant negative effect on local CEI. Therefore, to achieve China's "double carbon" goal, it is necessary to consider the five development concepts as the core, strengthen inter-county exchanges and collaboration, as well as promote collaborative management of the ecological environment.

Spatial correlation and coupling between industrial enterprise agglomeration and water pollutant discharge.

Industrial wastewater discharge has become the main cause of water pollution in China. However, the spatial interaction mechanism between industrial structure and water pollution is still unclear. Accordingly, we evaluated and analyzed spatiotemporal changes of the agglomeration pattern of pollution-intensive industrial enterprises and the evolution of the water environmental pollution pattern, as well as the correlation between them. The study results show that the polluting industrial enterprises were located mainly along the Yangtze River and Taihu Lake Basin in southern Jiangsu in 2013 and 2018. However, we observed a spatial trend of pollution transfer to northern Jiangsu. The industrial water pollution discharge presents the distribution pattern of facing rivers, seas, lakes and cities. Papermaking and paper products industry are the leading factors of COD and NH3-N pollution, with explanatory power of 0.3666 and 0.6201 respectively. The spatial positive coupling effect between the concentration degree of polluting enterprises and the intensity of water environment pollution discharge is 94.95% of the region. The spatial agglomeration of polluting industrial enterprises is an important cause of water environment pollution. They promote and couple each other, proving the existence of "Pollution haven" and "Porter hypothesis".

Satellites reveal hotspots of global river extent change.

Rivers are among the most diverse, dynamic, and productive ecosystems on Earth. River flow regimes are constantly changing, but characterizing and understanding such changes have been challenging from a long-term and global perspective. By analyzing water extent variations observed from four-decade Landsat imagery, we here provide a global attribution of the recent changes in river regime to morphological dynamics (e.g., channel shifting and anabranching), expansion induced by new dams, and hydrological signals of widening and narrowing. Morphological dynamics prevailed in ~20% of the global river area. Booming reservoir constructions, mostly skewed in Asia and South America, contributed to ~32% of the river widening. The remaining hydrological signals were characterized by contrasting hotspots, including prominent river widening in alpine and pan-Arctic regions and narrowing in the arid/semi-arid continental interiors, driven by varying trends in climate forcing, cryospheric response to warming, and human water management. Our findings suggest that the recent river extent dynamics diverge based on hydroclimate and socio-economic conditions, and besides reflecting ongoing morphodynamical processes, river extent changes show close connections with external forcings, including climate change and anthropogenic interference.

Examining key impact factors of energy-related carbon emissions in 66 Belt and Road Initiative countries.

Climate change with global warming as the main feature associated with fossil energy use has been recognized as a threat to public health and welfare. Energy-related carbon emission reduction is a more serious challenge for BRI (Belt and Road Initiative) countries with rapid economic development. Examining key impact factors is necessary and helpful. This paper is the first study providing detailed country-by-country analyses aiming to identify the key drivers and inhibitors of energy-related carbon emission in 66 BRI countries with more systematic impact factors. The results show that: (1) Economic development (A), population (Ps), urbanization (Pu), and industrialization (Ss) are the key drivers for 52%, 26%, 11%, and 6% countries of BRI countries. Technological progress (T), energy consumption structure (E), and tertiary industry proportion (St) serve as key inhibitors for 65%, 17%, and 8% countries of BRI countries. (2) Different carbon emission reduction strategies should be formed on different geographical scales. At the international level, carbon emission reduction consensus should be reached and carbon emission reduction targets should be formulated. At the regional level of the Belt and Road Initiative, a carbon emission reduction cooperation fund should be established, and carbon emission reduction technologies and measures should be exchanged and data should be shared to promote the green development of the Belt and Road. At the national level, there should be carbon emission reduction policies reflecting national characteristics. At the local level, there should be specific carbon reduction measures in line with local conditions.

The Preparation of N-Doped Titanium Dioxide Films and Their Degradation of Organic Pollutants.

N-doped TiO2 films supported by glass slides showed superior photocatalytic efficiency compared with naked TiO2 powder due to them being easier to separate and especially being responsive to visible light. The films in this study were prepared via the sol-gel method using TBOT hydrolyzed in an ethanol solution and the nitrogen was provided by cabamide. The N-doped TiO2 coatings were prepared via a dip-coating method on glass substrates (30 × 30 × 2 mm) and then annealed in air at 490 °C for 3 h. The samples were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM) and UV-vis. The doping rate of N ranged from 0.1 to 0.9 (molar ratio), which caused redshifts to a longer wavelength as seen in the UV-vis analysis. The photocatalytic activity was investigated in terms of the degradation of phenol under both UV light and visible light over 4 h. Under UV light, the degradation rate of phenol ranged from 86% to 94% for all the samples because of the sufficient photon energy from the UV light. Meanwhile, under visible light, a peak appeared at the N-doping rate of 0.5, which had a degrading efficiency that reached 79.2%, and the lowest degradation rate was 32.9%. The SEM, XRD and UV-vis experimental results were consistent with each other.

Coordinated Evolution and Influencing Factors of Population and Economy in the Yangtze River Economic Belt.

The degree of population-economy coupling and coordination is an important indicator of a region's balanced development. This study examines the evolution of the population-economy coupling coordination pattern in the Yangtze River Economic Belt spanning from 2000 to 2019. It draws from the economic growth stage and related theories, and employs methods such as geographic concentration, center of gravity analysis, and the coupling coordination model. Accordingly, the population and economy of the Yangtze River Economic Belt form a core-periphery, with a decreasing center toward the periphery, and the east higher than the west. The spatial coupling situation of the population-economic center of gravity yields an inverted U-shaped curve, where their center of gravity separates and then converges, and the difference in regional development expands and then shrinks. Moreover, the population center of gravity lags behind that of the economy. The population-economy coupling and coordination degree shows a decreasing trend after rising fluctuations. Further, the study finds that regional economic development, government role, and market-led capital agglomeration are significant drivers of the population-economy coupling and coordination, with the industrial structural influence being spatially heterogeneous.

A comprehensive data set of physical and human-dimensional attributes for China's lake basins.

Lakes provide water-related ecosystem services that support human life and production. Nevertheless, climate changes and anthropogenic interventions remarkably altered lake and basin hydrology in recent decades, which pose a significant threat to lacustrine ecosystems. Therefore, assessments of lacustrine ecosystems require the spatial and temporal characteristics of key physical and human-dimensional attributes for lakes and lake basins. To facilitate stakeholders obtaining comprehensive data of lake basins in China, we compiled the comprehensive data set for China's lake basins (CODCLAB) mostly from publicly available data sources based on spatial analysis and mathematical statistics methods in this study. The CODCLAB is available in three data formats, including raster layers (Level 1) in "tiff" format, vector shapefiles (Level 2), and attribute tables (Level 3). It covers 767 lakes (>10 km2) in China and their basin extent associating with 34 variables organized into five categories: Hydrology, Topography, Climate, Anthropogenic, and Soils. This unique database will provide basic data for research on the physical processes and socioeconomic activities related to these lakes and their basins in China and expect to feed a broad user community for their application in different areas.

Spatial temporal patterns and driving factors of industrial pollution and structures in the Yangtze River Economic Belt.

The conflict between industrial development and environmental pollution is global. This study quantitatively analyzes the temporal and spatial changes, spatial effects and determinants of industrial pollution discharge in the Yangtze River Economic Belt through two main indicators: wastewater and SO2. Analyze the spatial coupling relationship between industrial agglomeration and pollution emission and the characteristics of industrial structure in different regions. The analysis shows that industrial emissions in the Yangtze River Economic Belt first increased and then decreased during the period 2003-2019. Industrial pollution spread from large to small and medium cities and shifted from downstream to upstream. Moreover, a positive correlation exists between industrial pollution discharge and per capita GDP, secondary industry proportion, population density, and energy use. Meanwhile, scientific and technological progress and environmental regulations are associated with industrial pollution reduction. Since the Yangtze River Economic Belt was still in the industrialization stage and had not yet reached a turning point on the Environmental Kuznets Curve. The "pollution refuge" phenomenon was evident in the Belt, where underdeveloped areas in the central and western regions accommodated portions of highly polluting industries from the eastern areas through "regional competition" and "policy depression." The industrial agglomeration and pollution antagonistic zones were dominated by polluting industries; environmental risks were greatest in these areas. The upstream and downstream of the YREB play the negative and positive environmental externalities of industrial agglomeration, respectively. Thus, differential control measures should be formulated according to different regions, industrial pollutants, and polluting industries to improve environmental quality.

Dual-detection fluorescent immunochromatographic assay for quantitative detection of SARS-CoV-2 spike RBD-ACE2 blocking neutralizing antibody.

The global effort against the COVID-19 pandemic dictates that routine quantitative detection of SARS-CoV-2 neutralizing antibodies is vital for assessing immunity following periodic revaccination against new viral variants. Here, we report a dual-detection fluorescent immunochromatographic assay (DFIA), with a built-in self-calibration process, that enables rapid quantitative detection of neutralizing antibodies that block binding between the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and the angiotensin-converting enzyme 2 (ACE2). Thus, this assay is based on the inhibition of binding between ACE2 and the RBD of the SARS-CoV-2 spike protein by neutralizing antibodies, and the affinity of anti-human immunoglobulins for these neutralizing antibodies. Our self-calibrating DFIA shows improved precision and sensitivity with a wider dynamic linear range, due to the incorporation of a ratiometric algorithm of two-reverse linkage signals responding to an analyte. This was evident by the fact that no positive results (0/14) were observed in verified negative samples, while 22 positives were detected in 23 samples from verified convalescent plasma. A comparative analysis of the ability to detect neutralizing antibodies in 266 clinical serum samples including those from vaccine recipients, indicated that the overall percent agreement between DFIA and the commercial ELISA kit was 90.98%. Thus, the proposed DFIA provides a more reliable and accurate rapid test for detecting SARS-CoV-2 infections and vaccinations in the community. Therefore, the DFIA based strategy for detecting biomarkers, which uses a ratiometric algorithm based on affinity and inhibition reactions, may be applied to improve the performance of immunochromatographic assays.

Analysis of spatio-temporal distribution characteristics and socioeconomic drivers of urban air quality in China.

Having high spatio-temporal resolution data of pollutants is critical to understand environmental pollution patterns and their mechanisms. Our research employs the hourly average concentration data on the air quality index (AQI) and its six component pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) in 336 Chinese cities from 2014 to 2019. We analyze annual, seasonal, monthly, hourly, and spatial variations of different air pollutants and their socioeconomic factors. The results are as follows. (1) Air pollutants' concentration in Chinese cities decreased year by year during 2014-2019. Among the primary pollutants, PM2.5 dominated pollution days, accounting for 38.46%, followed by PM10. Monthly concentration curves of AQI, PM2.5, NO2, SO2, and CO showed a U-shaped trend from January to December, while that of O3 presented an inverted U-shaped unimodal pattern. Regarding daily variation, urban air quality tended to be worse around sunrise compared with sunset. (2) Chinese cities' air quality decreased from north to south and from inland to coastal areas. Recently, air quality has improved, and polluted areas have shrunk. The six pollutant types showed different spatial agglomeration characteristics. (3) Industrial pollution emissions were the main source of urban air pollutants. Energy-intensive industries, dominated by coal combustion, had the greatest impact on SO2 concentration. A "pollution shelter" was established in China because foreign investment introduced more pollution-intensive industries. Thus, China has crossed the Kuznets U-curve inflection point. In addition, population agglomeration contributed the most to PM2.5 concentration, increasing the PM2.5 exposure risk and causing disease, and vehicle exhaust aggravated the pollution of NO2 and CO. The higher China's per capita gross domestic product, the more significant the effect of economic development is on reducing pollutant concentration.

Selenium-Cultured Potamogeton maackianus in the Diet Can Alleviate Oxidative Stress and Immune Suppression in Chinese Mitten Crab (Eriocheir sinensis) Under Copper Exposure.

Selenium (Se) is an essential trace element for aquatic animals. The aquatic plant Potamogeton maackianus is an important natural food of Chinese mitten crab (Eriocheir sinensis). The aim of this study was to determine whether the antioxidant and immune responses of Chinese mitten crab are affected by including Se-cultured P. maackianus in the diet. Three groups of P. maackianus were cultured at levels of 0.02 mg/kg Se, 8.83 mg/kg Se, and 16.92 mg/kg Se, and the plants in these groups were used in experimental diets fed to crabs (dietary Se content of 0.05, 0.43, and 0.82 mg/kg, respectively). Compared with crabs in the 0.05 mg/kg group, those in the 0.82 mg/kg group showed significantly increased specific growth rate, protease and lipase activities, triglyceride and cholesterol contents, and Se content in the hepatopancreas and muscle (P < 0.05); increased activities of glutathione peroxidase, glutathione reductase, and catalase in the antioxidant system; increased transcript levels of MT (encoding metallothionein); and decreased malondialdehyde content (P < 0.05). At the end of the rearing experiment, the crabs in the different groups were exposed to copper (Cu2+) stress for 96 h. All the juvenile crabs in the 0.43 and 0.82 mg/kg groups survived 96 h of Cu2+ stress. Crabs in the 0.82 mg/kg group showed enhanced antioxidant responses under Cu2+ stress, increased transcript levels of MT and LYZ, and increased resistance. Therefore, supplementation of the diet of Chinese mitten crab with increased levels of Se-cultured P. maackianus can reduce oxidative stress under Cu2+ exposure, activate the immune response, and benefit growth.

Spatial distribution and source analysis of heavy metals in soils influenced by industrial enterprise distribution: Case study in Jiangsu Province.

Heavy metal pollution is frequent in China and has received increasing attention globally. This study investigated the influence of Chinese industrialization and urbanization on soil environmental quality. Soil samples from Jiangsu Province were collected, the Cd, Pb, Cr, Cu, Zn, Hg, and As contents were measured, and their spatial variability structure, spatial distribution pattern, and pollution degree were analyzed. The mean values of Hg, Cd, Pb, Cr, Cu, and As were all higher than the background values in Jiangsu Province. Cr and As levels represented moderate pollution, Cu, Zn, Cd, and Pb represented mild pollution, Cr and As represented slight pollution, and Hg was not a pollutant. Spatial distribution patterns were both zonal and concentrated in nature. High concentrations of heavy metals were distributed in developed cities and industrial parks along the Yangtze River. Soil heavy metal pollution showed a decreasing trend from south to north, consistent with the economic gradient. Industrialization had the greatest influence on the spatial heterogeneity of heavy metal pollution. Cr, Cu, Zn, and As were affected by both natural and anthropogenic sources, while Cd and Pb were mainly affected by the latter. Hg was mainly derived from industrial activities such as petrochemical production. There was spatial consistency between industrial enterprise distribution and soil heavy metal pollution with a tendency toward composite pollution accumulated by multiple elements in the soil surrounding industries.

Investigations on pyrolysis of microalgae Diplosphaera sp. MM1 by TG-FTIR and Py-GC/MS: Products and kinetics.

In this work, pyrolysis characteristics and kinetics of microalgae Diplosphaera sp. MM1 cultivated in different mediums were investigated by TG-FTIR and Py-GC/MS. Harvested MM1s biomass varied with the changing in proximate and ultimate analyses presented different weight loss behaviors. The weight loss of MM1s cultivated in dairy and winery wastewater in main pyrolysis region was ~48.4 wt% and ~52.9 wt%, respectively, and both showed secondary weight loss after 570 °C. However, MM1 harvested from BG-11 medium exhibited maximum weight loss of ~63.5 wt% and no secondary weight loss. Further, the activation energies of MM1s harvested from dairy and winery wastewater (176.3 kJ/mol and 130.4 kJ/mol, respectively) were lower than that of BG-11medium (189.4 kJ/mol). The best mechanism function for MM1s pyrolysis was third-order f(α) = (1-α)3. Py-GC/MS results of MM1 cultivated in winery wastewater showed highest contents of C4-C10 and C11-C21 that characterized the carbon level of gasoline and diesel, respectively, which are the major components of bio-oils.

Spatial-Temporal Evolution of PM2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014⁻2017.

PM2.5 is a main source of China's frequent air pollution. Using real-time monitoring of PM2.5 data in 338 Chinese cities during 2014⁻2017, this study employed multi-temporal and multi-spatial scale statistical analysis to reveal the temporal and spatial characteristics of PM2.5 patterns and a spatial econometric model to quantify the socio-economic driving factors of PM2.5 concentration changes. The results are as follows: (1) The annual average value of PM2.5 concentration decreased year by year and the monthly average showed a U-shaped curve from January to December. The daily mean value of PM2.5 concentration had the characteristics of pulse-type fluctuation and the hourly variation presented a bimodal curve. (2) During 2014⁻2017, the overall PM2.5 pollution reduced significantly, but that of more than two-thirds of cities still exceeded the standard value (35 µg/m³) regulated by Chinese government. PM2.5 pollution patterns showed high values in central and eastern Chinese cities and low values in peripheral areas, with the distinction evident along the same line that delineates China's uneven population distribution. (3) Population agglomeration, industrial development, foreign investment, transportation, and pollution emissions contributed to the increase of PM2.5 concentration. Urban population density contributed most significantly while economic development and technological progress reduced PM2.5 concentration. The results also suggest that China in general remains a "pollution shelter" for foreign-funded enterprises.

Modelling intercity accessibility surfaces through different transport modes in the Yangtze River Delta mega-region, China.

The paper presents the data that is related in the research paper entitled "High-speed rail network development and winner and loser cities in megaregions: The case study of Yangtze River Delta, China" (Wang and Duan, in press) [1]. This data article describes the modelling results of spatially continuous accessibility surfaces through transport modes of the highway, conventional rail and high-speed rail networks in the Yangtze River Delta mega-region, China. By using a door-to-door approach to integrate intra- and inter-city travel, the data is stimulated in the geographic information system environment. It is calculated by the datasets of transport networks, land-use types and transport speeds which are mainly collected from the OpenStreetMap and GlobeLand30 and relevant design specifications on transport infrastructures, respectively. The data is stored in raster format and provides high spatial resolution at 100 m. The data can be used as a baseline in the studies of transport economics and planning.

[Familial nasal bottom supernumerary tooth dentigerous cyst: report of 1 case and review of literatures].

Nasal supernumerary teeth and additional dental cyst is a common disease in Department of ENT and Department of Stomatology. In reported diseases, patients with a variety of additional teeth appeared in differ ent parts have varied clinical manifestations. Because of no obvious early symptoms, it is more difficult to diagnose, but CT examination in corresponding site can make it easy to diagnose the maxillary sinus and dentigerous cyst diagnosis. Operation is an effective method to cure the disease. Operation is simple, but the defect and tooth cavity after operation is one unavoidable problem for ENT doctor. In relevant literature it can be seen that the disease has a genetic tendency.

Degradation of landfill leachate using transpiring-wall supercritical water oxidation (SCWO) reactor.

Oxidation of landfill leachate wastewater was studied in a transpiring-wall SCWO reactor, operated under varied temperature and pressure 320-430 °C, 18-30 MPa. Effect of temperature and pressure on COD and BOD removal efficiency was investigated. COD and BOD removal efficiency being 99.23%, 98.06% were achieved at 430 °C, 30 MPa, which increased with temperature and pressure. The modified pseudo first-order rate model was regressed from experimental data, taking into account the induction time (t(ind)) effect. The resulting pre-exponential factor A and activation energy E(a) were 34.86 s(-1) and 32.1 kJ mol(-1), respectively, assuming that the reaction order for feed wastewater (based on COD) and oxidant were first order and zero order, respectively.