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People with minor medical conditions in China tend to prefer healthcare consultation in the emergency department of tertiary hospitals and avoid public sector community health centers (PS-CHC). The reason behind this is the trust deficit in the quality of medical care at PS-CHC. On the other hand, Chinese m-health companies have a surprising number of registered users and daily healthcare queries. However, the lack of physical check-ups causes a lack of trust in the quality of prescribed treatments for m-health users. One such m-health company entered into a joint venture with a local government body. In this joint venture, the doctors from tertiary hospitals can provide healthcare consultation to m-health users at PS-CHC. This study investigates m-health users' intention to use m-health services equipped with PS-CHC, an emerging public-private joint venture in China. We extended the technology acceptance model with government support and trust to predict the adoption of such technology-based public-private joint ventures in a better way. The data were collected from 432 m-health users in Hefei and analyzed using Smart-PLS. All eight direct, but only three mediating relationships were to be found significant. This study has implications for researchers, government healthcare authorities, and m-health service providers. [ABSTRACT FROM AUTHOR]

Skyrise greenery, including green roofs and vertical gardens, has emerged as an indispensable tool for sustainable urban planning with multiple ecological and economic benefits. A bibliometric analysis was used to provide a systematic review of the functions associated with skyrise greenery in urban landscapes. Key research tools, including the "Bibliometrix" R package and "CiteSpace" 6.2 R4, highlight the depth and breadth of the literature covering skyrise greenery. In 2000–2022, a total of 1474 original journal articles were retrieved. Over this period, there was an exponential increase in the number of publications, reflecting both enhanced knowledge and increasing concerns regarding climate change, the urban heat island, and urbanization. Of the total, ~58% of the articles originated from China, followed by the USA, Italy, Australia, and Canada. The research themes, such as urban heat islands, carbon sequestration, hydrology, and air quality, have been identified as the frontier in this fields. Furthermore, researchers from developed countries contributed the most publications to this domain, while developing countries, such as China, play an increasing role in the design and performance evaluation of vertical greenery. Key benefits identified in vertical green systems (e.g., green roofs and walls) include thermal regulation, sustainable water management, air-quality improvement, noise reduction, and biodiversity enhancement. In addition, several potential future research prospectives are highlighted. This review provides a comprehensive insight into exploring the pivotal role of skyrise greenery in shaping sustainable, resilient urban futures, coupled with sustainable urban planning. [ABSTRACT FROM AUTHOR]

China has changed its focus from traditional high-speed economic growth to high-quality economic development (HQED) and the implementation of environmentally friendly practices. This transition can have parallel or unparallel impacts on energy insecurity (EIS). In this regards, HQED, inter Alia, is crucial in mitigating EIS and combating the energy crisis. Our study explores the impact of economic growth (EG) and HQED on EIS using the provincial panel data of China for the period 2011–2017. From the perspective of comparative analysis, the results reveal that HQED reduces EIS while EG increases it. The robustness checks indicate that industrial structure (IS) has a negative impact on EIS, whereas industrial structure upgrading (ISU) and green innovation (GI) have a positive influence. This implies that IS contributes to an increase in EIS, whereas ISU and GI result in a decrease in EIS. In addition, the analysis reveals that digital financial inclusion (DFI) exhibits a significant positive relation with EIS, albeit occasionally a negative but insignificant link. The policy implication is that the government should stimulate policies to promote HQED which reduces the EIS. [ABSTRACT FROM AUTHOR]

Constructing underground reservoirs has emerged as a crucial strategy to address the shortage of fresh water in Rizhao, Shandong Province, China. However, the water quality, microbial community composition, and biogeochemical cycling of nutrients in underground reservoirs compared to raw water remain unknown. To unveil the characteristics of microbial community structures and their nitrogen cycling metabolic potential in coastal underground reservoirs, we utilized a functional gene array (GeoChip 5.0) in conjunction with high-throughput sequencing of 16S rRNA and 18S rRNA genes. Our findings indicate that the water quality in the underground reservoir exhibits a certain degree of eutrophication compared to raw water, with higher concentrations of TN, TP, NO3−N, NO2−-N, and Chl a, but lower concentrations of DO and NH4+-N. The alpha diversity of bacterial and microeukaryotic communities was significantly lower in the underground reservoir. The bacterial community presented a stronger correlation with environmental factors than the microeukaryotic community. Regarding the relative abundance of bacterial communities, Gammaproteobacteria dominated the bacterial community in raw water, while Gammaproteobacteria and Alphaproteobacteria dominated the bacterial community in underground reservoir water. Additionally, the relative abundance of Nitrospirae was noticeably higher in the underground reservoir water. Moreover, we found significantly higher sequence abundance of the archaea Thaumarchaeota in the underground reservoir. Furthermore, our analysis revealed that, except for the amoA functional gene, which significantly increased the metabolic potential of nitrification, the metabolic potential of other microbial nitrogen functional genes was significantly reduced. This reduction may contribute to the lower concentration of NH4+-N in the underground reservoir. This study provides a comprehensive understanding of the microbial community characteristics and their nitrogen cycling metabolic potential in underground reservoirs. It serves as a valuable reference for water source selection, the formulation of water quality assurance measures, and the construction and management of underground reservoirs for subsequent impounding. [ABSTRACT FROM AUTHOR]

Economic development has brought about global greenhouse gas emissions and, thus, global climate change, a common challenge worldwide and urgently needs to be addressed. Accurate carbon price forecasting plays a pivotal role in providing a reasonable basis for carbon pricing and ensuring the healthy development of carbon markets. Therefore, this paper proposes a two-stage interval-valued carbon price combination forecasting model based on bivariate empirical mode decomposition (BEMD) and error correction. In Stage I, the raw carbon price and multiple influencing factors are decomposed into several interval sub-modes by BEMD. Then, we select artificial intelligence-based multiple neural network methods such as IMLP, LSTM, GRU, and CNN to conduct combination forecasting for interval sub-modes. In Stage II, the error generated in Stage I is calculated, and LSTM is used to predict the error; then, the error forecasting result is added to the first stage result to obtain the error-corrected forecasting result. Taking the carbon trading prices of Hubei, Guangdong, and the national carbon market, China, as the research object, the empirical analysis proves that the combination forecasting of interval sub-modes of Stage I outperforms the single forecasting method. In addition, the error correction technique in Stage II can further improve the forecasting accuracy and stability, which is an effective model for interval-valued carbon price forecasting. This study can help policymakers formulate regulatory policies to reduce carbon emissions and help investors avoid risks. [ABSTRACT FROM AUTHOR]

Background: Plants accomplish multiple functions by the interrelationships between functional traits. Clarifying the complex relationships between plant traits would enable us to better understand how plants employ different strategies to adapt to the environment. Although increasing attention is being paid to plant traits, few studies focused on the adaptation to aridity through the relationship among multiple traits. We established plant trait networks (PTNs) to explore the interdependence of sixteen plant traits across drylands. Results: Our results revealed significant differences in PTNs among different plant life-forms and different levels of aridity. Trait relationships for woody plants were weaker, but were more modularized than for herbs. Woody plants were more connected in economic traits, whereas herbs were more connected in structural traits to reduce damage caused by drought. Furthermore, the correlations between traits were tighter with higher edge density in semi-arid than in arid regions, suggesting that resource sharing and trait coordination are more advantageous under low drought conditions. Importantly, our results demonstrated that stem phosphorus concentration (SPC) was a hub trait correlated with other traits across drylands. Conclusions: The results demonstrate that plants exhibited adaptations to the arid environment by adjusting trait modules through alternative strategies. PTNs provide a new insight into understanding the adaptation strategies of plants to drought stress based on the interdependence among plant functional traits. [ABSTRACT FROM AUTHOR]

Purpose: Marriage is an infinite bond between two partners that can be caused to fail by several factors. Economic stress leads to psychological stress and in some cases, marriage dissolution. The current study investigates the impact of economic stress (measured by the unemployment rate and inflation rate) on divorce rates using Chinese province-level panel data from 2010 to 2019. Design/Methodology/Approach: The panel fixed effects (FE) model, panel random effects (RE) model, and fixed effects- Driscoll and Kraay standard errors (DKSE) model were used for empirical analysis. Findings: The research findings support the hypothesized economic stress theory of divorce by Reuben Hill. According to the empirical findings, economic stress indicators such as unemployment and inflation have a positive and significant impact on the divorce rate in China and its regions. Furthermore, urbanization, education and mobile phone variables have a positive relationship with divorce rates except for children's dependency. Contribution to literature: Taking into account both parties' perspectives, this study contributes to the existing literature by looking at economic stress in the context of divorce. We are particularly interested in how economic stress affected the marriage relationship's quality. We investigated the relationship between the unemployment rate, inflation rate and divorce rate in China's 31 provinces for the period 2010-2019. The entire sample is then separated into three sub-samples: Eastern China, Central China and Western China. [ABSTRACT FROM AUTHOR]

Determining response patterns of plant leaf elements to environmental variables would be beneficial in understanding plant adaptive strategies and in predicting ecosystembiogeochemistry processes. Despite the vital role of microelements in life chemistry and ecosystem functioning, little is known about how plant microelement concentrations, especially their bioconcentration factors (BCFs, the ratio of plant to soil concentration of elements), respond to large-scale environmental gradients, such as aridity, soil properties and anthropogenic activities, in drylands. The aim of the present study was to fill this important gap. We determined leaf microelement BCFs by measuring the concentrations of Mn, Fe, Ni, Cu and Zn in soils from 33 sites and leaves of 111 plants from 67 species across the drylands of China. Leaf microelement concentrations were maintained within normal ranges to satisfy the basic requirements of plants, even in nutrient-poor soil. Aridity, soil organic carbon (SOC) and electrical conductivity (EC) had positive effects, while soil pH had a negative effect on leaf microelement concentrations. Except for Fe, aridity affected leaf microelement BCFs negatively and indirectly by increasing soil pH and SOC. Anthropogenic activities and soil clay contents had relatively weak impacts on both leaf microelement concentrations and BCFs. Moreover, leaf microelement concentrations and BCFs shifted with thresholds at 0.89 for aridity and 7.9 and 8.9 for soil pH. Woody plants were positive indicator species and herbaceous plants were mainly negative indicator species of leaf microelement concentrations and BCFs for aridity and soil pH. Our results suggest that increased aridity limits the absorption of microelements by plant leaves and enhances leaf microelement concentrations. The identification of indicator species for the response of plant microelements to aridity and key soil characteristics revealed that woody species in drylands were more tolerant to environmental changes than herbaceous species. [ABSTRACT FROM AUTHOR]

Precise estimation of water temperature plays a key role in environmental impact assessment, aquatic ecosystems' management and water resources planning and management. In the current study, convolutional neural networks (CNN) and long short-term memory (LSTM) network-based deep learning models were examined to estimate daily water temperatures of the Bailong River in China. Two novel optimization algorithms, namely the reptile search algorithm (RSA) and weighted mean of vectors optimizer (INFO), were integrated with both deep learning models to enhance their prediction performance. To evaluate the prediction accuracy of the implemented models, four statistical indicators, i.e., the root mean square errors (RMSE), mean absolute errors, determination coefficient and Nash–Sutcliffe efficiency were utilized on the basis of different input combinations involving air temperature, streamflow, precipitation, sediment flows and day of the year (DOY) parameters. It was found that the LSTM-INFO model with DOY input outperformed the other competing models by considerably reducing the errors of RMSE and MAE in predicting daily water temperature. [ABSTRACT FROM AUTHOR]

Archaea represent a diverse group of microorganisms often associated with extreme environments. However, an integrated understanding of biogeographical patterns of the specialist Haloarchaea and the potential generalist ammonia‐oxidizing archaea (AOA) across large‐scale environmental gradients remains limited. We hypothesize that niche differentiation determines their distinct distributions along environmental gradients. To test the hypothesis, we use a continental‐scale research network including 173 dryland sites across northern China. Our results demonstrate that Haloarchaea and AOA dominate topsoil archaeal communities. As hypothesized, Haloarchaea and AOA show strong niche differentiation associated with two ecosystem types mainly found in China's drylands (i.e. deserts vs. grasslands), and they differ in the degree of habitat specialization. The relative abundance and richness of Haloarchaea are higher in deserts due to specialization to relatively high soil salinity and extreme climates, while those of AOA are greater in grassland soils. Our results further indicate a divergence in ecological processes underlying the segregated distributions of Haloarchaea and AOA. Haloarchaea are governed primarily by environmental‐based processes while the more generalist AOA are assembled mostly via spatial‐based processes. Our findings add to existing knowledge of large‐scale biogeography of topsoil archaea, advancing our predictive understanding on changes in topsoil archaeal communities in a drier world. [ABSTRACT FROM AUTHOR]

This study aims to provide a comprehensive knowledge map of tourism and environmental degradation literature review based on scientific articles published between 1999 and 2020. The study provides an overview of research, influential authors, and journals. The PR China has maintained the lead in academic research with the most contribution in academic research in recent years. Sustainability, the Chinese Academy of Sciences, and Katircioglu are the most productive journal, academic institution, and author in the field of tourism and environmental degradation, respectively. The degree of research contribution among researchers, institutional and national level, has an upward trend in recent years, but the research contribution among author level is higher than the institutional and national level. Furthermore, co-citation analysis suggests that research articles in the field are closely related. "Investigating the influence of tourism on economic growth and carbon emissions: Evidence from panel analysis of the European Union" authored by Lee is the most cited article. Our analysis of abstracts and keywords shows that climate change, ecotourism, carbon emissions, economic growth, and energy consumption are the hot spots of academic literature. We suggest that research collaboration between developed and developing nations should be promoted in creating sustainable tourism reforms. [ABSTRACT FROM AUTHOR]

Since the emergence of COVID-19 pandemic in China in late 2019, scientists are striving hard to explore non-toxic, viable anti-SARS-CoV-2 compounds or medicines. We determined In vitro anti-SARS-CoV-2 activity of oral formulations (syrup and capsule)of an Iodine-complex (Renessans). First, cell cytotoxicity of Renessans on the Vero cells was determined using MTT assay. Afterwards, the antiviral activity of Renessans was determined using viral inhibition assays and TCID50. For this, nontoxic concentrations of the Renessans were used. The results showed that Renessans is nontoxic to the cells up to 50 µg/mL. At 1.5 µg/mL concentration, SARS-CoV-2 production was significantly reduced to 101.43 TCID50 and 101.58 TCID50 for the syrup and capsule, respectively, as compare to virus infected control cells 106.08 TCID50 and we found the dose dependent inhibition of virus replication in the presence of Renessans. Renessans inhibited SARS-CoV-2 with an EC50 value of 0.425 µg/mL and 0.505 µg/mL for syrup and capsule, respectively. Furthermore, there was no virus detected at concentration of 50 µg/mL of Renessans. This study indicates that Renessans, containing iodine, have potential activity against SARS-CoV-2 which needs to be further investigated in human clinical trials. [ABSTRACT FROM AUTHOR]

Abstract The aim of the "One Belt and One Road" (OBOR) project proposed by China is to encourage extension of global value chains, facilitate regional integration and increase efficient resource allocation. In recent times, scientific literature has examined the investment decisions of the OBOR investment and how it will affect the governmental policies, environmental initiatives, and bilateral flow of economic resources. Current study, based on Web of Science database, uses bibliometric methodology to map the research trends in OBOR publications. We contribute in the economic literature in the associated fields of OBOR publications in the following ways: (1) identify the most influential researchers, articles, and academic institutions, (2) mapping the interdisciplinary character of OBOR investments and its bibliometric similarity to adjacent fields, (3) visualize nature and trends of the research field, and (4) synthesizing future research areas. Although OBOR initiative has received considerable traction, but to this date, there is no bibliometric study on this topic. The findings of current study will help policymakers and academics to navigate the OBOR literature, provide a systematic basis for developing the field, and suggest promising future research avenues. [ABSTRACT FROM AUTHOR]

Drylands are expected to be affected by greater global drought variability in the future; consequently, how dryland ecosystems respond to drought events needs urgent attention. In this study, the Normalized Vegetation Index (NDVI) and Standardized Precipitation and Evaporation Index (SPEI) were employed to quantify the resistance of ecosystem productivity to drought events in drylands of northern China between 1982 and 2015. The relationships and temporal trends of resistance and drought characteristics, which included length, severity, and interval, were examined. The temporal trends of resistance responded greatest to those of drought length, and drought length was the most sensitive and had the strongest negative effect with respect to resistance. Resistance decreased with increasing drought length and did not recover with decreasing drought length in hyper-arid regions after 2004, but did recover in arid and semi-arid regions from 2004 and in dry sub-humid regions from 1997. We reason that the regional differences in resistance may result from the seed bank and compensatory effects of plant species under drought events. In particular, this study implies that the ecosystem productivity of hyper-arid regions is the most vulnerable to drought events, and the drought–resistance and drought–recovery interactions are likely to respond abnormally or even shift under ongoing drought change. [ABSTRACT FROM AUTHOR]

Plants need water and energy for their growth and reproduction. However, how water and energy availability influence dryland plant diversity along the aridity gradient in water-limited regions is still lacking. Hence, quantitative analyses were conducted to evaluate the relative importance of water and energy to dryland plant diversity based on 1039 quadrats across 184 sites in China's dryland. The results indicated that water availability and the water–energy interaction were pivotal to plant diversity in the entire dryland and consistent with the predictions of the water–energy dynamic hypothesis. The predominance of water limitation on dryland plant diversity showed a weak trend with decreasing aridity, while the effects of energy on plants were found to be significant in mesic regions. Moreover, the responses of different plant lifeforms to water and energy were found to vary along the aridity gradient. In conclusion, the study will enrich the limited knowledge about the effects of water and energy on plant diversity (overall plants and different lifeforms) in the dryland of China along the aridity gradient. [ABSTRACT FROM AUTHOR]

The study investigates the potential of two new machine learning methods, least-square support vector regression with a gravitational search algorithm (LSSVR-GSA) and the dynamic evolving neural-fuzzy inference system (DENFIS), for modeling reference evapotranspiration (ETo) using limited data. The results of the new methods are compared with the M5 model tree (M5RT) approach. Previous values of temperature data and extraterrestrial radiation information obtained from three stations, in China, are used as inputs to the models. The estimation exactness of the models is measured by three statistics: root mean square error, mean absolute error, and determination coefficient. According to the results, the temperature or extraterrestrial radiation-based LSSVR-GSA models perform superiorly to the DENFIS and M5RT models in terms of estimating monthly ETo. However, in some cases, a slight difference was found between the LSSVR-GSA and DENFIS methods. The results indicate that better prediction accuracy may be obtained using only extraterrestrial radiation information for all three methods. The prediction accuracy of the models is not generally improved by including periodicity information in the inputs. Using optimum air temperature and extraterrestrial radiation inputs together generally does not increase the accuracy of the applied methods in the estimation of monthly ETo. [ABSTRACT FROM AUTHOR]

Encouraging green consumption has become a topic of immense interest in terms of Chinese dual carbon (carbon peaking and carbon neutrality) goals. We used impression and expectation management theories to examine the intermediate mechanism of how consumers' face consciousness formulates green consumption behavior, the mediating effect of green self-efficacy, and the moderating effect of media persuasion. We conducted this study in East China, collected data from 382 green consumers, and utilized hierarchical regression for data analysis. We concluded that (1) both dimensions of face consciousness (i.e., gaining face and avoiding losing face) helped escalate green consumption behavior; 2) consumers with high face consciousness have higher green consumption behavior than those with low face consciousness; (3) media persuasion increases consumers' green consumption behavior; and (4) media persuasion negatively moderates the association between face consciousness and green self-efficacy, which means that media persuasion can reduce consumer green self-efficacy with both dimensions of face consciousness. Therefore, electronic, and social media need to control the frequency and intensity of reporting environment-related negative news. Moreover, the government and enterprises need to stimulate consumers' sense of face, improve their sense of green self-efficacy, and encourage them to adopt green products to achieve dual carbon goals. • Both dimensions of face consciousness (gaining and avoiding losing face) help escalate green consumption behavior. • Consumers with high face awareness have higher green consumption behavior than those with low face awareness. • Electronic and social media need to control the frequency and intensity of reporting environment-related negative news. • The government and enterprises need to stimulate consumers' sense of face to improve green self-efficacy and consumption. [ABSTRACT FROM AUTHOR]

• Leaf iWUE increases but ecosystem WUE decreases with aridity level. • iWUE and ecosystem WUE displayed almost opposite trends in response to abiotic factors. • MAT was the strongest factor in predicting iWUE, whereas the most robust factor in predicting ecosystem WUE was LAI. Water use efficiency (WUE) links carbon and water cycling and has been recognized as important in understanding the carbon-water budget of terrestrial ecosystems. However, there are few studies comparing WUE at leaf and ecosystem levels in response to environmental variables on a global scale. Here, we compare global-scale patterns and the drivers of leaf and ecosystem WUEs and quantify the relative influence of biotic and abiotic factors. Using published world-wide δ13C (carbon stable isotope composition) measurements for 6751 C 3 plant populations from 174 publications, as well as our own measurements of δ13C for 418 C 3 plant populations across drylands in China, and satellite-based datasets of gross primary production and evapotranspiration, we determined global patterns and the drivers of leaf and ecosystem WUEs. Leaf intrinsic WUE (iWUE) and ecosystem WUE displayed almost opposite trends, in response to abiotic factors on a global scale. iWUE was highest in arid regions and lowest in humid regions, whereas ecosystem WUE was lowest in arid regions and highest in humid regions. Phylogeny had a significant effect on iWUE. Mean annual temperature (MAT) was the strongest factor in predicting iWUE, whereas the most robust factor in predicting ecosystem WUE was leaf area index (LAI). The data indicate that the two different responses at the leaf and ecosystem levels must be considered when modeling carbon and water balances in response to climate change. [ABSTRACT FROM AUTHOR]

• Random forest models were employed to estimate plant species richness in drylands. • Plant richness increased from last interglacial and is projected to increase. • Different plant lifeforms exhibit varying sensitivities to climate change. • Herbaceous species respond more rapidly to climate change than woody species. It is commonly believed that climate plays an important role in shaping the patterns of plant species richness. However, it remains unclear how climate may affect plant richness across large spatial scales and also over long-terms, for example across massive arid regions during the Quaternary and into the future. To fill this knowledge gap, we examined the long-term trends in plant species richness across vast drylands in China based on our newly developed climate-species richness models. We first generated optimal random forest models based on the relationships between the current (CUR, 1970–2000) annual, perennial, woody and total species richness and climatic variables. We subsequently hindcasted and forecasted plant species richness in five other periods: last interglacial (LIG, 120,000–140,000 years BP), last glacial maximum (LGM, about 22,000 years BP), mid-Holocene (MH, about 6000 years BP), 2041–2060 (2050), and 2061–2080 (2070). Our results showed that total and herbaceous species richness exhibited similar patterns that were driven by temperature and precipitation. Both groups of species formed a transition zone between arid and semi-arid regions in all periods except LIG. In contrast, woody species richness did not form any transition zone because it was regulated mainly by temperature. Furthermore, the mean richness of herbaceous, woody and all species exhibited gradually increasing trends from LIG to 2070 across drylands in China. On the one hand, herbaceous species were much more sensitive to climate change than woody species. On the other hand, plant species richness in mountain-basin systems and Taklamakan Desert regions were more sensitive to climate change than in meadows and steppes. These results shed new insights into the past and future changes in plant species richness over vast drylands and provide valuable information for future conservation efforts under global warming. [ABSTRACT FROM AUTHOR]

Soil microbes exert critical control over ecosystem functions by regulating organic matter decomposition and nutrient cycling. Diverse methods have been adopted to estimate the soil microbial biomass carbon (C mic) and nitrogen (N mic), largely based on fumigation and respiration or biomarkers, such as phospholipids and ATP. Although soil microbial DNA is also an important biomarker, whether this biomarker can be used to estimate C mic and N mic at a large scale in arid and semi-arid regions that remains unclear. To explore this, the 124 soil samples collected from 28 different vegetation/microhabitat types in diverse ecosystems (i.e., desert, cropland, typical steppe, meadow steppe and forest) across arid and semi-arid regions in northern China; then, the strong linear relationships were developed among soil microbial DNA concentrations with the C mic and N mic contents estimated by the classic chloroform fumigation-extraction (CFE) method. The results showed that the soil microbial DNA concentrations were linearly related to the observed C mic (r = 0.99) and N mic (r = 0.97) across the diverse vegetation types, although soil microbial biomass presented an enormous fluctuation. Moreover, based on the above-mentioned coefficients of the linear relationship, it was further inferred that the mean proportions of carbon and nitrogen elements in DNA were 0.99% and 3.70% for C mic and N mic , respectively, when assuming the G-C base-pair proportion is 50% in double-stranded DNA. In conclusion, the study proved that soil microbial DNA as a powerful indicator may provide convenient and efficient estimates for C mic and N mic in arid and semi-arid systems. Although this method still needs to be further improved and examined at a larger scale, it provides a good addition to the already existing methods to determine microbial biomass. Unlabelled Image [ABSTRACT FROM AUTHOR]

• Adjunct of serological test improves the accuracy in COVID-19 diagnosis after onsets. • Demographic characteristics of patients are analyzed based on severity of COVID-19. • COVID-19 patients are sorted to three subgroups by severity of illness for analysis. • No differences of IgM-IgG concentrations exist among subgroups of COVID-19 patients. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused coronavirus disease 2019 (COVID-19) epidemic in China, December 2019. The clinical features and treatment of COVID-19 patients remain largely elusive. However, accurate detection is required for SARS-CoV-2 infection diagnosis. We aimed to evaluate the antibodies-based test and nucleic acid-based test for SARS-CoV-2-infected patients. We retrospectively studied 133 patients diagnosed with SARS-CoV-2 and admitted to Renmin Hospital of Wuhan University, China, from January 23 to March 1, 2020. Demographic data, clinical records, laboratory tests, and outcomes were collected. Data were accessed by SARS-CoV-2 IgM-IgG antibody test and real-time reverse transcriptase PCR (RT-PCR) detection for SARS-CoV-2 nucleic acid in COVID-19 patients. Of 133 COVID-19 patients, there were 44 moderate cases, 52 severe cases, and 37 critical cases with no differences in gender and age among three subgroups. In RT-PCR detection, the positive rate was 65.9%, 71.2%, and 67.6% in moderate, severe, and critical cases, respectively. Whereas the positive rate of IgM/IgG antibody detection in patients was 79.5%/93.2%, 82.7%/100%, and 73.0%/97.3% in moderate, severe, and critical cases, respectively. Moreover, the IgM and IgG antibodies concentrations were also examined with no differences among three subgroups. The IgM-IgG antibody test exhibited a useful adjunct to RT-PCR detection, and improved the accuracy in COVID-19 diagnosis regardless of the severity of illness, which provides an effective complement to the false-negative results from a nucleic acid test for SARS-CoV-2 infection diagnosis after onsets. [ABSTRACT FROM AUTHOR]

Leaf functional traits (LFTs) of desert plants are responsive, adaptable and highly plastic to their environment. However, the macroscale variation in LFTs and driving factors underlying this variation remain unclear, especially for desert plants. Here, we measured eight LFTs, including leaf carbon concentration (LCC), leaf nitrogen concentration (LNC), leaf phosphorus concentration (LPC), specific leaf area (SLA), leaf dry matter content (LDMC), leaf mass per area (LMA), leaf thickness (LTH) and leaf tissue density (LTD) across 114 sites along environmental gradient in the drylands of China and in Guazhou Common Garden and evaluated the effect of environment and phylogeny on the LFTs. We noted that for all species, the mean values of LCC, LNC, LPC, SLA, LDMC, LMA, LTH and LTD were 384.62 mg g -1 , 19.91 mg g -1 , 1.12 mg g -1 , 79.62 cm 2  g -1 , 0.74 g g -1 , 237.39 g m -2 , 0.38 mm and 0.91 g cm -3 , respectively. LFTs exhibited significant geographical variations and the LNC, LMA and LTH in the plants of Guazhou Common Garden were significantly higher than the field sites in the drylands of China. LDMC and LTD of plants in Guazhou Common Garden were, however, considerably lower than those in the drylands of China. LCC, LPC, LTH and LTD differed significantly among different plant lifeforms, while LNC, SLA, LDMC and LMA didn't show significant variations. We found that the environmental variables explained higher spatial variations (3.6-66.3 %) in LFTs than the phylogeny (1.8-54.2 %). The LCC significantly increased, while LDMC and LTD decreased with increased temperature and reduced precipitation. LPC, LDMC, LMA, and LTD significantly increased, while SLA and LTH decreased with increased aridity. However, leaf elements were not significantly correlated with soil nutrients. The mean annual precipitation was a key factor controlling variations in LFTs at the macroscale in the drylands of China. These findings will provide new insights to better understand the response of LFTs and plants adaptation along environmental gradient in drylands, and will serve as a reference for studying biogeographic patterns of leaf traits., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Relationships between biodiversity and multiple ecosystem functions (that is, ecosystem multifunctionality) are context-dependent. Both plant and soil microbial diversity have been reported to regulate ecosystem multifunctionality, but how their relative importance varies along environmental gradients remains poorly understood. Here, we relate plant and microbial diversity to soil multifunctionality across 130 dryland sites along a 4,000 km aridity gradient in northern China. Our results show a strong positive association between plant species richness and soil multifunctionality in less arid regions, whereas microbial diversity, in particular of fungi, is positively associated with multifunctionality in more arid regions. This shift in the relationships between plant or microbial diversity and soil multifunctionality occur at an aridity level of ∼0.8, the boundary between semiarid and arid climates, which is predicted to advance geographically ∼28% by the end of the current century. Our study highlights that biodiversity loss of plants and soil microorganisms may have especially strong consequences under low and high aridity conditions, respectively, which calls for climate-specific biodiversity conservation strategies to mitigate the effects of aridification., (© 2021. The Author(s).)

This study aims to provide a detailed overview of environmental Kuznets curve hypothesis using bibliometric analysis for the Web of Science (WOS) database. Our analysis provides an overview of research trends, journals and most influential authors. China has contributed the most scientific publications; followed by the USA, Turkey, and Pakistan. Muhammad Shahbaz, Beijing Institute of Technology, and Environmental Science and Pollution Research are the most productive author, research institute, and research journal in EKC publications. Trend analysis of researchers, academic and country-level, reveal that publications in the environmental Kuznets curve have upward trend; also, cocitation analysis indicates that EKC publications are closely related. "Economic growth and income inequality" (1955) by Simon Kuznets is considered to be the basic literature, and "environmental Kuznets curve hypothesis: A Survey" by Dinda (2004) is the most cited research article in the literature. Keywords and abstracts analysis further reveals that carbon emissions, renewable energy, energy consumption, economic growth, and sustainable development are the hot topics in current literature. We propose that joint research projects between industrial and emerging economies will promote research activities.

This study aims to provide a systematic literature review based on bibliometric analysis for scientific articles published between 1999 and 2019 extracted from Clarivate Analytics' Web of Science (WOS) database. The current research project provides an overview of scientific publications, influential authors, and research journals. Our analysis reveals that the USA leads the academic research contribution, whereas China has provided the most research publications in recent years. Environmental and Resource Economics, University of London, and Barcena-Ruiz are the most productive journal, academic institution, and author in the field of environmental taxes, respectively. The degree of research contribution among researchers, institutional and national level, has an upward trend in recent years; however, the research contribution at the author level is higher than the institutional and national level. Furthermore, cocitation analysis suggests that research articles in the dataset are closely related. Pigou's "The economics of welfare" published in 1920, is considered as the basic literature, and the "In defence of degrowth" authored by Giorgis Kallis is the most cited article. Our analysis of abstracts and keywords indicates that climate change, environmental taxes, double dividend, carbon tax, and environmental pollution are the hotspots within academic literature. We suggest that research collaboration between developed and developing nations and further coordination among environmental agencies such as IEA and IPCC will enhance the effectiveness of environmental reforms.

The immune system is not only required for preventing threats exerted by pathogens but also essential for developing immune tolerance to avoid tissue damage. This study identifies a distinct mechanism by which MYSM1 suppresses innate immunity and autoimmunity. The expression of MYSM1 is induced upon DNA virus infection and by intracellular DNA stimulation. MYSM1 subsequently interacts with STING and cleaves STING K63-linked ubiquitination to suppress cGAS-STING signaling. Notably, Mysm1-deficient mice exhibit a hyper-inflammatory response, acute tissue damage, and high mortality upon virus infection. Moreover, in the PBMCs of patients with systemic lupus erythematosus (SLE), MYSM1 production decreases, while type I interferons and pro-inflammatory cytokine expressions increase. Importantly, MYSM1 treatment represses the production of IFNs and pro-inflammatory cytokines in the PBMCs of SLE patients. Thus, MYSM1 is a critical repressor of innate immunity and autoimmunity and is thus a potential therapeutic agent for infectious, inflammatory, and autoimmune diseases., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

The new decade of the 21 st century (2020) started with the emergence of a novel coronavirus known as SARS-CoV-2 that caused an epidemic of coronavirus disease (COVID-19) in Wuhan, China. It is the third highly pathogenic and transmissible coronavirus after severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) emerged in humans. The source of origin, transmission to humans, and mechanisms associated with the pathogenicity of SARS-CoV-2 are not yet clear, however, its resemblance to SARS-CoV and several other bat coronaviruses was recently confirmed through genome sequencing-related studies. The development of therapeutic strategies is necessary in order to prevent further epidemics and cure infections. In this review, we summarize current information about the emergence, origin, diversity, and epidemiology of three pathogenic coronaviruses with a specific focus on the current outbreak in Wuhan, China. Furthermore, we discuss the clinical features and potential therapeutic options that may be effective against SARS-CoV-2., (Copyright © 2020 American Society for Microbiology.)