Safeguarding China's long-term sustainability against systemic disruptors.

China's long-term sustainability faces socioeconomic and environmental uncertainties. We identify five key systemic risk drivers, called disruptors, which could push China into a polycrisis: pandemic disease, ageing and shrinking population, deglobalization, climate change, and biodiversity loss. Using an integrated simulation model, we quantify the effects of these disruptors on the country's long-term sustainability framed by 17 Sustainable Development Goals (SDGs). Here we show that ageing and shrinking population, and climate change would be the two most influential disruptors on China's long-term sustainability. The compound effects of all disruptors could result in up to 2.1 and 7.0 points decline in the China's SDG score by 2030 and 2050, compared to the baseline with no disruptors and no additional sustainability policies. However, an integrated policy portfolio involving investment in education, healthcare, energy transition, water-use efficiency, ecological conservation and restoration could promote resilience against the compound effects and significantly improve China's long-term sustainability.

Historical construction, quantitative source identification and risk assessment of heavy metals contamination in sediments from the Pearl River Estuary, South China.

Historical reconstruction of heavy metals (HMs) contamination in sediments is a key for understanding the effects of anthropogenic stresses on water bodies and predicting the variation trends of environmental state. In this work, eighteen sediment cores from the Pearl River Estuary (PRE) were collected to determine concentrations and geochemical fractions of HMs. Then, their potential sources and the relative contributions during different time periods were quantitatively identified by integrating lead-210 (210Pb) radioisotope dating technique into positive matrix factorisation (PMF) method. Pollution levels and potential ecological risks (PERs) caused by HMs were accurately assessed by enrichment factors (EF) based on establishment of their geochemical baselines (GCBs) and multiparameter evaluation index (MPE). HMs concentrations generally showed a particle size- and organic matter-dependent distribution pattern. During the period of 1958-1978, HMs concentrations remained at low levels with agricultural activities and natural processes being identified as the predominant sources and averagely contributing >60%. Since the reform and opening-up in 1978, industrial and traffic factors become the primary anthropogenic sources of HMs (such as Cu, Zn, Cd, Pb, Cr, and Ni), averagely increasing from 22.1% to 28.1% and from 11.6% to 23.4%, respectively. Conversely, the contributions of agricultural and natural factors decreased from 37.0% to 28.5% and from 29.3% to 20.0%, respectively. Subsequently, implementation of environmental preservation policies was mainly responsible for the declining trend of HMs after 2010. Little enrichment of sediment Cu, Zn, Pb, Cr and Ni with EFs (0.15-1.43) was found in the PRE, whereas EFs of Cd (1.16-2.70) demonstrated a slight to moderate enrichment. MPE indices of Cu (50.7-252), Pb (52.0-147), Zn (35.5-130), Ni (19.6-71.5), Cr (14.2-68.8) and Cd (0-9.90) highlighted their potential ecological hazards due to their non-residual fractions and anthropogenic sources.

Government's public panic emergency capacity assessment and response strategies under sudden epidemics: A fuzzy Petri net-based approach.

In the post-epidemic era, public panic has emerged as a highly significant secondary disaster, necessitating an urgent enhancement of emergency management capabilities by governments at all levels. In order to ensure a robust assessment of the government's ability to manage public panic, it is crucial to effectively address the influence of uncertain and ambiguous factors associated with such scenarios. This paper proposes a governmental public panic emergency management capability assessment method based on fuzzy Petri nets. By analyzing the factors influencing public panic across the four evolutionary stages, namely gestation, outbreak, diffusion, and fading, we establish a hierarchical evaluation index system for assessing emergency management capabilities. Additionally, we develop a range of multi-scenario emergency management strategies. To address the challenges posed by uncertainty, randomness, fuzziness, and insufficient statistical data within the assessment index system, we introduce fuzzy Petri nets and fuzzy reasoning rules to evaluate the emergency management capability of the assessment system and derive the optimal emergency management strategy. According to example simulations, the effectiveness and practicality of models and rules constructed using fuzzy Petri nets are demonstrated, highlighting their superiority over traditional assessment methods. This comprehensive approach equips the government with a versatile toolkit for effectively managing public panic emergencies.

Genome assembly of autotetraploid Actinidia arguta highlights adaptive evolution and enables dissection of important economic traits.

Actinidia arguta, the most widely distributed Actinidia species and the second cultivated species in the genus, can be distinguished from the currently cultivated Actinidia chinensis on the basis of its small and smooth fruit, rapid softening, and excellent cold tolerance. Adaptive evolution of tetraploid Actinidia species and the genetic basis of their important agronomic traits are still unclear. Here, we generated a chromosome-scale genome assembly of an autotetraploid male A. arguta accession. The genome assembly was 2.77 Gb in length with a contig N50 of 9.97 Mb and was anchored onto 116 pseudo-chromosomes. Resequencing and clustering of 101 geographically representative accessions showed that they could be divided into two geographic groups, Southern and Northern, which first diverged 12.9 million years ago. A. arguta underwent two prominent expansions and one demographic bottleneck from the mid-Pleistocene climate transition to the late Pleistocene. Population genomics studies using paleoclimate data enabled us to discern the evolution of the species' adaptation to different historical environments. Three genes (AaCEL1, AaPME1, and AaDOF1) related to flesh softening were identified by multi-omics analysis, and their ability to accelerate flesh softening was verified through transient expression assays. A set of genes that characteristically regulate sexual dimorphism located on the sex chromosome (Chr3) or autosomal chromosomes showed biased expression during stamen or carpel development. This chromosome-level assembly of the autotetraploid A. arguta genome and the genes related to important agronomic traits will facilitate future functional genomics research and improvement of A. arguta.

Cost-effectiveness of latent tuberculosis infection testing and treatment with 6-week regimen among key population in rural communities in China: a decision analysis study.

PURPOSE: Several model studies suggested the implementation of latent tuberculosis infection (LTBI) testing and treatment could greatly reduce the incidence of tuberculosis (TB) and achieve the 2035 target of the "End TB" Strategy in China. The present study aimed to evaluate the cost-effectiveness of LTBI testing and TB preventive treatment among key population (≥ 50 years old) susceptible to TB at community level in China. METHODS: A Markov model was developed to investigate the cost-effectiveness of LTBI testing using interferon gamma release assay (IGRA) and subsequent treatment with 6-month daily isoniazid regimen (6H) (as a standard regimen for comparison) or 6-week twice-weekly rifapentine and isoniazid regimen (6-week H2P2) in a cohort of 10,000 adults with an average initial age of 50 years. RESULTS: In the base-case analysis, LTBI testing and treatment with 6H was dominated (i.e., more expensive with a lower quality-adjusted life year (QALY)) by LTBI testing and treatment with 6-week H2P2. LTBI testing and treatment with 6-week H2P2 was more effective than no intervention at a cost of $20,943.81 per QALY gained, which was below the willingness-to-pay (WTP) threshold of $24,211.84 per QALY gained in China. The one-way sensitivity analysis showed the change of LTBI prevalence was the parameter that most influenced the results of the incremental cost-effectiveness ratios (ICERs). CONCLUSION: As estimated by a Markov model, LTBI testing and treatment with 6-week H2P2 was cost-saving compared with LTBI testing and treatment with 6H, and it was considered to be a cost-effective option for TB control in rural China.

Overview of Health-Monitoring Technology for Long-Distance Transportation Pipeline and Progress in DAS Technology Application.

There are various health issues associated with the different stages of long-distance pipeline transportation. These issues pose potential risks to environmental pollution, resource waste, and the safety of human life and property. It is essential to have real-time knowledge of the overall health status of pipelines throughout their entire lifecycle. This article investigates various health-monitoring technologies for long-distance pipelines, providing references for addressing potential safety issues that may arise during long-term transportation. This review summarizes the factors and characteristics that affect pipeline health from the perspective of pipeline structure health. It introduces the principles of major pipeline health-monitoring technologies and their respective advantages and disadvantages. The review also focuses on the application of Distributed Acoustic Sensing (DAS) technology, specifically time and space continuous monitoring technology, in the field of pipeline structure health monitoring. This paper discusses the process of commercialization development of DAS technology, the main research progress in the experimental field, and the open research issues. DAS technology has broad application prospects in the field of long-distance transportation pipeline health monitoring.

An accurate, efficient, and economical identification technology for black twig borer based on species-specific cytochrome C oxidase subunit I PCR assay.

Xylosandrus compactus (Eichhoff) (Coleoptera: Curculionidae, Scolytinae) is a worldwide invasive species that causes huge economic loss and environmental damage in many countries. Traditional morphological characteristics make it hard to identify scolytines due to their tiny size. Besides, the intercepted insect samples are incomplete, and the limitation of insect (larvae and pupae) morphology makes morphological identification more difficult. The majority of the damage is caused by adults and fungi that serve as nutrition for their larvae. They destroy plant trunks, branches, and twigs, affecting plant transport tissues in both weak and healthy plants. An accurate, efficient, and economical molecular identification technique for X. compactus not restricted by professional taxonomic knowledge is necessary. In the present study, a molecular identification tool based on the mitochondrial DNA gene, cytochrome C oxidase subunit I (COI) was developed. A species-specific COI (SS-COI) PCR assay was designed to identify X. compactus regardless of the developmental stage. Twelve scolytines commonly found in eastern China, namely Xylosandrus compactus, X. crassiusculus, X. discolor, X. germanus, X. borealis, X. amputates, X. eupatorii, X. mancus, Xyleborinus saxesenii, Euwallacea interjectus, E. fornicatus, and Acanthotomicus suncei, were included in the study. Additionally, specimens of X. compactus from 17 different areas in China, as well as a specimen collected from the United Stated, were also analyzed. Results demonstrated the accuracy and high efficiency of the assay, regardless of the developmental stage or the type of specimen. These features provide a good application prospect for fundamental departments and can be used to prevent the harmful consequences of the spread of X. compactus.

Using the H2O Automatic Machine Learning Algorithms to Identify Predictors of Web-Based Medical Record Nonuse Among Patients in a Data-Rich Environment: Mixed Methods Study.

BACKGROUND: With the advent of electronic storage of medical records and the internet, patients can access web-based medical records. This has facilitated doctor-patient communication and built trust between them. However, many patients avoid using web-based medical records despite their greater availability and readability. OBJECTIVE: On the basis of demographic and individual behavioral characteristics, this study explores the predictors of web-based medical record nonuse among patients. METHODS: Data were collected from the National Cancer Institute 2019 to 2020 Health Information National Trends Survey. First, based on the data-rich environment, the chi-square test (categorical variables) and 2-tailed t tests (continuous variables) were performed on the response variables and the variables in the questionnaire. According to the test results, the variables were initially screened, and those that passed the test were selected for subsequent analysis. Second, participants were excluded from the study if any of the initially screened variables were missing. Third, the data obtained were modeled using 5 machine learning algorithms, namely, logistic regression, automatic generalized linear model, automatic random forest, automatic deep neural network, and automatic gradient boosting machine, to identify and investigate factors affecting web-based medical record nonuse. The aforementioned automatic machine learning algorithms were based on the R interface (R Foundation for Statistical Computing) of the H2O (H2O.ai) scalable machine learning platform. Finally, 5-fold cross-validation was adopted for 80% of the data set, which was used as the training data to determine hyperparameters of 5 algorithms, and 20% of the data set was used as the test data for model comparison. RESULTS: Among the 9072 respondents, 5409 (59.62%) had no experience using web-based medical records. Using the 5 algorithms, 29 variables were identified as crucial predictors of nonuse of web-based medical records. These 29 variables comprised 6 (21%) sociodemographic variables (age, BMI, race, marital status, education, and income) and 23 (79%) variables related to individual lifestyles and behavioral habits (such as electronic and internet use, individuals' health status and their level of health concern, etc). H2O's automatic machine learning methods have a high model accuracy. On the basis of the performance of the validation data set, the optimal model was the automatic random forest with the highest area under the curve in the validation set (88.52%) and the test set (82.87%). CONCLUSIONS: When monitoring web-based medical record use trends, research should focus on social factors such as age, education, BMI, and marital status, as well as personal lifestyle and behavioral habits, including smoking, use of electronic devices and the internet, patients' personal health status, and their level of health concern. The use of electronic medical records can be targeted to specific patient groups, allowing more people to benefit from their usefulness.

Spatial and Temporal Variations and Risk Assessment of Heavy Metal Fractions in Sediments of the Pearl River Estuary, Southern China.

Sequential extraction was used to study the mobility and ecological risk of chemical fractions of six heavy metals in sediments collected from the Pearl River Delta (PRE) in China. Results revealed that residual fractions (F4) were the dominant forms for Cr and Ni in surface sediments, indicating that they were primarily stable in nature and had low bioavailability and ecotoxicity. Cd had a high environmental risk owing to its higher availability in acid-soluble fraction (F1), whereas Pb occurred predominantly in the reducible fraction (F2) in surface sediments. The profile variations of bioavailable fractions were generally consistent with socioeconomic development in the Pearl River Delta (PRD). A decreasing trend after 2006 suggested a reduction in heavy metal bioavailable fractions owing to the removal of heavy polluting industries and the effective control of sewage discharge. The risk assessment code suggested that the high mobility of Cd posed an extremely high risk and a threat to the aquatic environment.

Quantitative assessment of zonal trabecular volumetric bone mineral density in middle-aged and elderly women using quantitative computed tomography.

Background: To explore the feasibility of the 9 zonal trabecular volumetric bone mineral density (trabecular vBMD) method in the first lumbar vertebral body (L1) and to assess the zonal trabecular vBMD distribution of L1 in women aged 50-80 years. Methods: A total of 578 women patients underwent a quantitative computed tomography (CT) scan of the L1 vertebra, and these patients were categorized into 3 age subgroups with 10-year intervals. L1 was segmented into 9 zones, based on which, L1 was then divided into 6 regions [i.e., vBMD-anterior (vBMD-A), vBMD-medial (vBMD-M), and vBMD-posterior (vBMD-P) from the ventral to the dorsal side, vBMD-upper (vBMD-U), vBMD-medial (vBMD-M'), and vBMD-lower (vBMD-L) from the head to the foot]. Independent samples t-test, intraclass correlation coefficient (ICC), and one-way analysis of variance (ANOVA) were used for statistical analyses. Results: There were no significant differences of the 9 zonal vBMDs measured by the 2 analysts (P≥0.638), and ICCs were all greater than or equal to 0.990. There was significant difference of global vBMD among the 3 age groups (P<0.001), and so as to the 9 zonal vBMDs among the 3 age groups (P<0.001). Age was negatively correlated with global vBMD and the 9 zonal vBMDs (P<0.001). There were significant differences among vBMD-A, vBMD-M, and vBMD-P (P<0.001), and vBMD-A and vBMD-M were both lower than vBMD-P. There were significant differences among vBMD-U, vBMD-M', and vBMD-L (P<0.001), and vBMD-U and vBMD-L were both lower than vBMD-M'. Conclusions: The 9 zonal trabecular vBMD method of L1 is stable and feasible, and the 9 zonal trabecular vBMD method may quantitatively explain osteoporotic vertebral deformity from the perspective of vBMD in middle-aged and elderly women.

Study on the Impact of Collaborative Agglomeration of Manufacturing and Producer Services on PM2.5 Pollution: Evidence from Urban Agglomerations in the Middle Reaches of the Yangtze River in China.

In this paper, using panel data of 28 cities in the middle reaches of the Yangtze River from 2003 to 2020 as the research sample, we built a dynamic spatial Durbin model based on the STIRPAT (stochastic impacts by regression on population, affluence, and technology) model and conducted an empirical study on the impact of the coordinated agglomeration of manufacturing and producer services on particulate matter (PM) 2.5 pollution. The results show a significant positive spatial spillover effect of PM2.5 pollution in the middle reaches of the Yangtze River. The coordinated agglomeration of manufacturing and producer services in the urban agglomerations there is conducive to reducing PM2.5 pollution. Similar to the inverted-U curve of the classic environmental Kuznets curve hypothesis, there is a significant inverted-U curve relationship between PM2.5 pollution and economic growth in urban agglomerations in the middle reaches of the Yangtze River. The proportion of coal consumption, the proportion of secondary industry, and the urbanization level are significantly and positively correlated with PM2.5 pollution in urban agglomerations in this area. Technological innovation, environmental regulation, and annual average humidity play an important role in addressing the PM2.5 pollution and spatial spillover effect. Industrial structure and technological innovation are the main ways for the coordinated agglomeration of manufacturing and producer services to affect PM2.5. The research conclusion can be of great practical significance to optimize the regional industrial layout, control PM2.5 pollution, and establish a sustainable development policy system in the middle reaches of the Yangtze River in China.

Decomposition analysis of health inequalities between the urban and rural oldest-old populations in China: Evidence from a national survey.

The number of Chinese oldest-old (aged 80+) is growing rapidly and some studies have shown that the health status is unequal among older persons in different regions. However, to the best of our knowledge, no study to date has analyzed health inequalities among the oldest-old in urban and rural areas in China. This study therefore aimed to examine the correlation between health inequalities among the oldest-old in urban and rural areas of China. From the 8th wave of the Chinese Longitudinal Health Longevity Survey (CLHLS), we selected 8124 oldest-old participants who met the requirements of the study. Chi-square tests were used to analyze the distribution characteristics of indicators and a logistic model was performed to determine the factors associated with different self-rated health (SRH). The Fairlie model was adopted to decompose the causes and related contributions to health inequality. Our results found that of the Chinese oldest-old, 46.57% were in good health. Urban residents reported significantly better SRH than rural residents (50.17% vs. 45.13%). Variables associated with good and poor SRH had different distribution characteristics. The logistic model suggested that marital status, alcohol consumption, and annual income were important factors underlying the SRH differences. Our decomposition analysis indicated that 76.64% of the SRH differences were caused by observational factors, and validated that the difference in SRH between urban and rural areas was significantly (P<0.05) associated with exercise status (45.44%), annual income (37.64%), social activity status (3.75%), age (-5.27%), and alcohol consumption (-2.66%). Therefore, socioeconomic status and individual lifestyle status were the main factors underlying the health inequality between urban and rural Chinese oldest-old.

Heavy metals in paired samples of hair and nails in China: occurrence, sources and health risk assessment.

The occurrence of heavy metals including chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd) and lead (Pb) was investigated in paired samples of hair and nails collected from 121 volunteers in 16 cities, China. Results showed that the mean concentrations of Zn, Cu, As, Pb, Cr, Ni and Cd were 205, 18.0, 7.79, 6.18, 3.54, 2.02, 0.533 µg g-1 in hair and 103, 8.09, 0.760, 7.27, 6.07, 8.81, 0.485 µg g-1 in nails, respectively. The concentrations of Zn, Ni, Cr, Cd and Pb were positively correlated in paired samples of hair and nails, whereas a negative correlation was found for Cu and As between hair and nails. Higher concentrations of heavy metals were found in northern China than southern China. The multivariate analysis of variance revealed that dwelling environment was the dominant factor influencing the levels of Cd in hair (p < 0.05), while age was the dominant factor influencing the levels of Cr in nails (p < 0.05). Moreover, industrial pollution and smoking were also the important factors leading to the accumulation of heavy metals in human body. Principal component analysis (PCA) showed that industrial pollution and decoration material immersion were the main factors for the high concentrations of Cr and Ni in hair, accounting for 62.9% of the total variation; As in hair was dominantly related to groundwater pollution. The concentrations of heavy metals were within the recommended ranges in nails from this study. However, the mean levels of Cr, Ni and As in hair exceeded their recommended reference values, indicating potential health risks from heavy metals for residents in China.

Is air pollution detrimental to regional innovation? An empirical heterogeneity test based on Chinese cities.

Nowadays, innovation seems to be the inevitable choice to achieve stable economic growth. However, the negative impact of air pollution on health and economy makes air pollution an important factor in regional innovation, which deserves our discussion. The overall regional innovation level from 2014 to 2019 has an upward trend, while the overall air pollution has a downward trend during the period, which provides foundation for our research. Based on the data of 285 prefecture-level cities in China from 2014 to 2019, this paper uses the fixed effect and mediation model to verify the impact and mechanism of air pollution on regional innovation. The results show that the increase in air pollution, measured by the air quality index, significantly inhibits regional innovation. Air pollution has significant funds crowding-out effect and human capital loss effect, thereby decreasing the regional innovation level, which means innovation funds and researchers play a conductive role between air pollution and regional innovation. In heterogeneity analysis, it is found that the detrimental effect of air pollution on regional innovation is significant in eastern and central China, in large- and medium-sized cities, and in cities with poor or general air quality. It indicates that developed and large-scale regions should pay more attention to air pollution control. For polluted regions, more emphasis and endeavors are needed to address air pollution problems. Besides, the inhibitory effect is more severe on incremental innovation rather than on radical innovation, which deserves the attention of enterprises engaged in incremental innovation. Therefore, we propose that targeted environmental policies and effective measures should be developed to improve air quality in the long run. Moreover, policymakers could provide strong support for innovation grants, talent subsidies, and rewards and encourage clean technological innovation through short-term trade-offs between heavily polluting and low polluting enterprises.

The "Pollution Halo" Effect of FDI: Evidence from the Chinese Sichuan-Chongqing Urban Agglomeration.

In this paper, panel data from nineteen key cities in the Sichuan-Chongqing urban agglomeration from 2003 to 2016 were used as the study sample. Using the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model, the effect of foreign direct investment (FDI) on particulate matter (PM2.5) pollution and its action mechanism in the Sichuan-Chongqing urban agglomeration were considered for both socioeconomic and natural factors. The results showed that the "pollution halo" hypothesis of FDI in the Sichuan-Chongqing urban agglomeration has been supported. There are significant positive spatial spillover effects of PM2.5 pollution in this urban agglomeration, and the introduction of FDI is conducive to alleviating PM2.5 pollution in the urban agglomeration. Similar to the "inverted U" curve proposed by the environmental Kuznets curve (EKC) hypothesis, there was a significant "inverted U" curve relationship between PM2.5 pollution and economic growth in the Sichuan-Chongqing urban agglomeration. However, there was a significant "U"-type curve relationship between the urbanization degree and the PM2.5 concentration, which indicates that the current urbanization mode may aggravate the pollution degree of PM2.5 in the urban agglomeration in the long term. Furthermore, the two natural factors of annual average temperature and annual precipitation play an important role in PM2.5 pollution and spatial spillover effect in the Sichuan-Chongqing urban agglomeration. Economic development and rationalization of the industrial structure are the main ways by which FDI affects PM2.5 pollution in the urban agglomeration. The research conclusions of this study can be of great practical significance to optimize the regional industrial layout, control PM2.5 pollution, and establish a sustainable development policy system in the Sichuan-Chongqing urban agglomeration.

Decoupling environmental impact from economic growth to achieve Sustainable Development Goals in China.

Developing countries, such as China, have achieved unprecedented success in a single Sustainable Development Goal (SDG), which usually leads to trade-offs between the three pillars of sustainability, and even destroys sustainability. Quantifying the degrees of coupling among the pillars is essential to support policymakers' systematic actions to minimize trade-offs and maximize co-benefits between the pillars, and simultaneously achieve all SDGs. However, assessing the degrees of coupling among the pillars for the full SDGs is lacking. Here, we evaluate the progress of the pillars towards the SDGs and quantify the degrees of coupling among them at both national and sub-national levels in China from 2000 to 2015. The results indicate that the degrees of coupling among the pillars were almost constant while the degrees of coupling between the pillars and economic growth declined over time. The degrees of coupling between environmental impact and economic growth accounted for 52%-83% of the SDGs' progress. Reducing the degrees of coupling helps achieve simultaneously economic growth and environmental protection. The higher the degrees of coupling, the lower progress. This trend was universal among all provinces (sub-national level) regardless of their development levels. Our study highlights not only the necessity to track the degrees of coupling among the pillars, but also decoupling environmental impact from economic growth to achieve the SDGs.

A Risk Assessment Tool for Identifying Osteoporosis in Older Women with Type 2 Diabetes Mellitus.

PURPOSE: To develop a simple and clinically useful assessment tool for osteoporosis in older women with type 2 diabetes mellitus (T2DM). METHODS: A total of 601 women over 60 years of age with T2DM were enrolled in this study. The levels of serum sex hormones and bone metabolism markers were compared between the osteoporosis and non-osteoporosis groups. The least absolute shrinkage and selection operator regularization (LASSO) model was applied to generate a risk assessment tool. The risk score formula was evaluated using receiver operating characteristic analysis and the relationship between the risk score and the bone mineral density (BMD) and T-value were investigated. RESULTS: Serum sex hormone-binding globulin (SHBG), cross-linked C-telopeptide of type 1 collagen (CTX), and osteocalcin (OC) were significantly higher in the osteoporosis group. After adjustment for age and body mass index (BMI), SHBG was found to be correlated with the T-value or BMD. Then, a risk score was specifically generated with age, BMI, SHBG, and CTX using the LASSO model. The risk score was significantly negatively correlated with the T-value and BMD of the lumbar spine, femoral neck, and total hip (all P<0.05). CONCLUSION: A risk score using age, BMI, SHBG, and CTX performs well for identifying osteoporosis in older women with T2DM.

China's industrial green total-factor energy efficiency and its influencing factors: a spatial econometric analysis.

The sustainable development of China's economy is bottlenecked by resource shortage and environmental pollution. As the leading resource consumer and pollutant source, the industrial sector needs to improve its energy efficiency. This paper establishes a super epsilon-based measure (Super-EBM) model with bad outputs like environmental cost and evaluates the industrial green total-factor energy efficiencies (IGTFEEs) of 30 provinces in China during 2000-2017. Unlike previous research, the main contribution of this paper is to choose four environmental pollutants as bad outputs (industrial carbon dioxide, industrial sulfur dioxide, industrial chemical oxygen demand, industrial solid waste). By contrast, the previous studies mostly only take one environmental pollutant as bad output, i.e., the bad outputs are not fully measured. Then, the spatiotemporal dynamics and spatial correlations of the IGTFEEs were analyzed, and the influencing factors of IGTFEE were examined empirically with a spatial econometric model. Finally, this paper adopts generalized method of moments (GMM) to solve the endogenous problem, trying to assure the robustness of estimation results. The results show significant provincial differences in IGTFEE. Most eastern coastal provinces achieved satisfactory IGTFEEs, while most inland provinces had undesirable IGTFEEs. Eastern region achieved the highest IGTFEE, followed by central region; western region had the lowest IGTFEE. The IGTFEE improved over time in some provinces while worsened greatly in some provinces. The IGTFEE in most provinces need to be further improved. Global Moran's I values indicate that the provincial IGTFEEs were clustered in space, rather than randomly distributed. Local indication of spatial association (LISA) map reflects significant local spatial clustering of provincial IGTFEEs. In addition, IGTFEE is significantly promoted by industrial structure, technological innovation, human capital, opening-up, and energy structure yet significantly suppressed by ownership structure and environmental regulation. Considering the endogeneity, GMM results show that the estimation results of the model were robust. Specific policy recommendations include vigorously developing high-tech industries, deepening state-owned enterprises reform, diverting more funds to research and development, cultivating versatile talents, introducing environmentally-friendly foreign capital, accelerating the implementation of clean energy development strategy, and widening the fund channels of pollution control investment.

Preinvasion Assessment of Exotic Bark Beetle-Vectored Fungi to Detect Tree-Killing Pathogens.

Exotic diseases and pests of trees have caused continental-scale disturbances in forest ecosystems and industries, and their invasions are considered largely unpredictable. We tested the concept of preinvasion assessment of not yet invasive organisms, which enables empirical risk assessment of potential invasion and impact. Our example assesses fungi associated with Old World bark and ambrosia beetles and their potential to impact North American trees. We selected 55 Asian and European scolytine beetle species using host use, economic, and regulatory criteria. We isolated 111 of their most consistent fungal associates and tested their effect on four important southeastern American pine and oak species. Our test dataset found no highly virulent pathogens that should be classified as an imminent threat. Twenty-two fungal species were minor pathogens, which may require context-dependent response for their vectors at North American borders, while most of the tested fungi displayed no significant impact. Our results are significant in three ways; they ease the concerns over multiple overseas fungus vectors suspected of heightened potential risk, they provide a basis for the focus on the prevention of introduction and establishment of species that may be of consequence, and they demonstrate that preinvasion assessment, if scaled up, can support practical risk assessment of exotic pathogens.

Voxel-Wise Analysis of Structural and Functional MRI for Lateralization of Handedness in College Students.

The brain structural and functional basis of lateralization in handedness is largely unclear. This study aimed to explore this issue by using voxel-mirrored homotopic connectivity (VMHC) measured by resting-state functional MRI (R-fMRI) and gray matter asymmetry index (AI) by high-resolution anatomical images. A total of 50 healthy subjects were included, among them were 13 left-handers, 24 right-handers, and 13 mixed-handers. Structural and R-fMRI data of all subjects were collected. There were significant differences in VMHC among the three groups in lateral temporal-occipital, orbitofrontal, and primary hand motor regions. Meanwhile, there were significant differences in AI that existed in medial prefrontal, superior frontal, and superior temporal regions. Besides, the correlation analysis showed that the closer the handedness score to the extreme of the left-handedness (LH), the stronger the interhemispheric functional connectivity, as well as more leftward gray matter. In general, left/mixed-handedness (MH) showed stronger functional homotopy in the transmodal association regions that depend on the integrity of the corpus callosum, but more variable in primary sensorimotor cortices. Furthermore, the group differences in VMHC largely align with that in AI. We located the specific regions for LH/MH from the perspective of structural specification and functional integration, suggesting the plasticity of hand movement and different patterns of emotional processing.