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Abstract This study provides a comprehensive analysis of the dynamic evolution of complexity and synchrony between the carbon market and the new energy market from 2019 to 2023, employing multiscale sample entropy and cross‐sample entropy methods. The study shows that, both in the long term and short term, the complexity of the new energy market consistently exceeds that of the carbon market. Additionally, the carbon and new energy markets exhibit higher synchronization on smaller scales. As the time scale increases, interactions between the carbon and new energy markets become more complex and diverse. According to these findings, it is recommended that policymakers improve the transparency of the new energy market, optimize the operational mechanisms of the carbon market, and ensure that carbon reduction strategies and new energy policies are mutually coordinated. This holds significant importance for both carbon reduction targets and the development of new energy.

The addition of Ca could enhance the ignition point of magnesium alloys but impairing their workability, so it is essential to study the hot deformation behavior of new Ca-containing ignition resistance magnesium alloys. The hot deformation behavior of a new ignition resistance Mg–6Zn-0.6Zr-1.2Ca alloy was investigated by compression experiment in the temperature range of 240 °C–360 °C, strain rates of 10−3 s−1-1 s−1 and height reduction of 10%–60%. The true stress-strain curves show that flow stress decreases as the deformation temperature increases or the strain rate decreases. Microstructure analysis shows that higher temperatures and lower strain rates are favorable for DRX, while higher strain rates promote the fragmentation of the Ca2Mg6Zn3 phase. Meanwhile, the existence of Ca2Mg6Zn3 phase make the DRX process be dominated by the particle-induced subgrain nucleation mechanism. By superposition of the power dissipation map and the instability map, a hot processing map of true strain of 0.6 is generated. According to analyses on the processing map and microstructure evolution, the instability of processing map can be attributed to the greater dislocation motion resistances, insufficient DRX, and Ca2Mg6Zn3 phase with low-melting point. Conversely, the optimal processing parameters for the alloy were determined as 280–360 °C/0.001–0.01 s−1 in safe zone with a high η above 0.3, which can be due to the apparent DRX and good deformation coordination.

ABSTRACT: The earlobes of chickens exhibit a range of colors, but there has been relatively little research on the formation of structural blue earlobes. Previous results showed that the structural color earlobes were related to the interplay between melanin and collagen in light reflection. To investigate the metabolic differences in these earlobe colors, we conducted nontargeted liquid chromatograph mass spectrometer (LC-MS) for metabolomic sequencing on structural blue (Green and Blue groups) and nonstructural color (Black group) earlobes tissue of Jiangshan black-bone chickens. The content detection in earlobe tissues of different groups shows that there were significant differences in melanin and collagen content between the Black and Green group. The metabolome identified a total of 6,102 mass spectroscopic peaks and ultimately identified 919 annotated metabolites. Variable importance in the projection (VIP) analysis identified the common differential expressed metabolites (DMs) “Tyr Thr Ala Glu” among the 3 groups. By combining those DMs with differentially expressed genes (DEGs) in our previous transcriptome data from the same sample, and associated with KEGG pathway analysis, multiple pathways related to melanogenesis and collagen metabolism were enriched across the 3 groups. By analyzing the metabolites and genes in these pathways, as well as the interaction network diagram of DEGs, we identified some key genes, Wnt Family Member 6 (WNT6), Transcription Factor 7 (TCF7), Proopiomelanocortin (POMC) and Calcium/Calmodulin Dependent Protein Kinase II Alpha (CAMK2A), and some key DMs like DG (11M3/9M5/0:0) and gentisic acid. The differential gene expression and metabolic levels affect the production of melanin and collagen, leading to differences in the content in melanin and the thickness of the collagen layer between earlobe colors, while the thickness of the collagen layer could affect light scattering, ultimately resulting in different colored earlobes in Jiangshan black-bone chickens.

Abstract Understanding lanthanide coordination chemistry can help develop new ligands for more efficient separation of lanthanides for critical materials needs. The Cambridge Structural Database (CSD) contains tens of thousands of single crystal structures of lanthanide complexes that can serve as a training ground for both fundamental chemical insights and future machine learning and generative artificial intelligence models. This work aims to understand the currently available structures of lanthanide complexes in CSD by analyzing the coordination shell, donor types, and ligand types, from the perspective of rare-earth element (REE) separations. We obtain four sets of lanthanide complexes from CSD: Subset 1, all Ln-containing complexes (49472 structures); Subset 2, mononuclear Ln complexes (27858 structures); Subset 3, mononuclear Ln complexes without cyclopentadienyl ligands (Cp) (26156 structures); Subset 4, Ln complexes with at least one 1,10-phenanthroline (phen) or its derivative as a coordinating ligand (2226 structures). The subsequent analysis of lanthanide complexes in these subsets examines the trends in coordination numbers and first shell distances as well as identifies and characterizes the ligands and donor groups. In addition, examples of Ln-complexes with commercially available complexants and phen-based ligands are interrogated in detail. This systematic investigation lays the groundwork for future data-driven ligand designs for REE separations based on the structural insights into the lanthanide coordination chemistry.

Dissolved oxygen (DO) is a vital water quality index influencing biological processes in aquatic environments. Accurate modeling of DO levels is crucial for maintaining ecosystem health and managing freshwater resources. To this end, the present study contributes a Bayesian-optimized explainable machine learning (ML) model to reveal DO dynamics and predict DO concentrations. Three ML models, support vector regression (SVR), regression tree (RT), and boosting ensemble, coupled with Bayesian optimization (BO), are employed to estimate DO levels in the Mississippi River. It is concluded that the BO-SVR model outperforms others, achieving a coefficient of determination (CD) of 0.97 and minimal error metrics (root mean square error = 0.395 mg/L, mean absolute error = 0.303 mg/L). Shapley Additive Explanation (SHAP) analysis identifies temperature, discharge, and gage height as the most dominant factors affecting DO levels. Sensitivity analysis confirms the robustness of the models under varying input conditions. With perturbations from 5% to 30%, the temperature sensitivity ranges from 1.0% to 6.1%, discharge from 0.9% to 5.2%, and gage height from 0.8% to 5.0%. Although the models experience reduced accuracy with extended prediction horizons, they still achieve satisfactory results (CD > 0.75) for forecasting periods of up to 30 days. The established models also exhibit higher accuracy than many prior approaches. This study highlights the potential of BO-optimized explainable ML models for reliable DO forecasting, offering valuable insights for water resource management.

The mammalian gastrointestinal tract is a stage for dynamic inter-kingdom interactions among bacteria, fungi, viruses, and protozoa, which collectively shape the gut micro-ecology and influence host physiology. Despite being a modest fraction, the fungal community, also referred to as mycobiota, represents a critical component of the gut microbiota. Emerging evidence suggests that fungi act as early colonizers of the intestine, exerting a lasting influence on gut development. Meanwhile, the composition of the mycobiota is influenced by multiple factors, with diet, nutrition, drug use (e.g., antimicrobials), and physical condition standing as primary drivers. During its establishment, the mycobiota forms both antagonistic and synergistic relationships with bacterial communities within the host. For instance, intestinal fungi can inhibit bacterial colonization by producing alcohol, while certain bacterial pathogens exploit fungal iron carriers to enhance their growth. However, the regulatory mechanisms governing these complex interactions remain poorly understood. In this review, we first introduce the methodologies for studying the microbiota, then address the significance of the mycobiota in the mammalian intestine, especially during weaning when all ‘primary drivers’ change, and, finally, discuss interactions between fungi and bacteria under various influencing factors. Our review aims to shed light on the complex inter-kingdom dynamics between fungi and bacteria in gut homeostasis and provide insights into how they can be better understood and managed to improve host health and disease outcomes.

Abstract Cancer cells develop multiple strategies to evade T cell-mediated killing. On one hand, cancer cells may preferentially rely on certain amino acids for rapid growth and metastasis. On the other hand, sufficient nutrient availability and uptake are necessary for mounting an effective T cell anti-tumor response in the tumor microenvironment (TME). Here we demonstrate that tumor cells outcompete T cells for cystine uptake due to high Slc7a11 expression. This competition induces T-cell exhaustion and ferroptosis, characterized by diminished memory formation and cytokine secretion, increased PD-1 and TIM-3 expression, as well as intracellular oxidative stress and lipid-peroxide accumulation. Importantly, either Slc7a11 deletion in tumor cells or intratumoral cystine supplementation improves T cell anti-tumor immunity. Mechanistically, cystine deprivation in T cells disrupts glutathione synthesis, but promotes CD36 mediated lipid uptake due to dysregulated cystine/glutamate exchange. Moreover, enforced expression of glutamate-cysteine ligase catalytic subunit (Gclc) promotes glutathione synthesis and prevents CD36 upregulation, thus boosting T cell anti-tumor immunity. Our findings reveal cystine as an intracellular metabolic checkpoint that orchestrates T-cell survival and differentiation, and highlight Gclc as a potential therapeutic target for enhancing T cell anti-tumor function.

Abstract In the livestock production system, the evolution of porcine gut microecology is consistent with the idea of “The Hygiene Hypothesis” in humans. I.e., improved hygiene conditions, reduced exposure to environmental microorganisms in early life, and frequent use of antimicrobial drugs drive immune dysregulation. Meanwhile, the overuse of antibiotics as feed additives for infectious disease prevention and animal growth induces antimicrobial resistance genes in pathogens and spreads related environmental pollutants. It justifies our attempt to review alternatives to antibiotics that can support optimal growth and improve the immunophysiological state of pigs. In the current review, we first described porcine mucosal immunity, followed by discussions of gut microbiota dynamics during the critical weaning period and the impacts brought by antibiotics usage. Evidence of in-feed additives with immuno-modulatory properties highlighting probiotics, prebiotics, and phytobiotics and their cellular and molecular networking are summarized and reviewed. It may provide insights into the immune regulatory mechanisms of antibiotic alternatives and open new avenues for health management in pig production.

The escalating human pressures on natural ecosystems necessitate urgent and effective conservation strategies to safeguard biodiversity and ecosystem functions. This review explored current techniques for mapping human pressure, with a particular focus on their application in nature conservation, especially within protected areas (PAs). Specifically, we analyzed the impacts of seven major types of human pressures on nature conservation within PAs. Additionally, we discussed four key methods for mapping human pressure, including land use intensity, human footprint, digital human footprint, and other proxies, examining their distinct characteristics and respective advantages and disadvantages. Additionally, our research explored the application of human pressure mapping for nature conservation, assessing its suitability for conservation applications and delineating directions for future work. These insights contributed to better support nature conservation and the management of PAs.

Wetlands play a vital role in regulating the global carbon cycle, providing biodiversity, and reducing flood risks. These functions maintain ecological balance and ensure human well-being. Timely, accurate monitoring of wetlands is essential, not only for conservation efforts, but also for achieving Sustainable Development Goals (SDGs). In this study, we combined Sentinel-1/2 images, terrain data, and field observation data collected in 2020 to better understand wetland distribution. A total of 22 feature variables were extracted from multi-source data, including spectral bands, spectral indices (especially red edge indices), terrain features, and radar features. To avoid high correlations between variables and reduce data redundancy, we selected a subset of features based on recursive feature elimination (RFE) and Pearson correlation analysis methods. We adopted the random forest (RF) method to construct six wetland delineation schemes and incorporated multiple types of characteristic variables. These variables were based on remote sensing image pixels and objects. Combining red-edge features, terrain data, and radar data significantly improved the accuracy of land cover information extracted in low-mountain and hilly areas. Moreover, the accuracy of object-oriented schemes surpassed that of pixel-level methods when applied to wetland classification. Among the three pixel-based schemes, the addition of terrain and radar data increased the overall classification accuracy by 7.26%. In the object-based schemes, the inclusion of radar and terrain data improved classification accuracy by 4.34%. The object-based classification method achieved the best results for swamps, water bodies, and built-up land, with relative accuracies of 96.00%, 90.91%, and 96.67%, respectively. Even higher accuracies were observed in the pixel-based schemes for marshes, forests, and bare land, with relative accuracies of 98.67%, 97.53%, and 80.00%, respectively. This study’s methodology can provide valuable reference information for wetland data extraction research and can be applied to a wide range of future research studies.

Developing effective strategies to prevent diarrhea and associated-gut disorders in mammals has gained great significance. Owing to the many health benefits provided by the commensal microbiota of the intestinal tract, such as against environmental perturbation, we explored the host phenotype-associated microbes and their probiotic potential. Based on the observations that the chronic heat stress-exposed weaned piglets present as heat stress-susceptible (HS-SUS) or heat stress-resistant (HS-RES) individuals, we confirmed the phenotypic difference between the two on growth performance (P

Abstract Background Congenital muscular torticollis (CMT) is a common musculoskeletal disease affecting infants and young children. If CMT is not treated correctly and timely, it can lead to limited head and neck movements, head and neck deviation, and abnormal posture. In order to improve patients' symptoms and alleviate the negative impact of the disease on their lives, we are committed to exploring the treatment of CMT. Methods The general clinical and ultrasonographic data of 2599 children with CMT who received standardized treatment at Shenzhen Children’s Hospital from 2004 to 2020 were retrospectively reviewed. According to given treatment, children with CMT were divided into the physiotherapy group, physiotherapy combined with glucocorticoid treatment group, and surgical treatment group. We divided children with CMT into local mass, uniform thickening, and atrophy according to ultrasound features. General clinical information, treatment, and ultrasound examination data in each group were compared. Additionally, electronic medical records of 2344 patients admitted due to CMT in 17 tertiary children’s hospitals of China’s Futang Research Center of Pediatric Development (FRCPD) from 2015 to 2019 were retrospectively analyzed. Data on sex, age, year of admission and discharge, and treatment costs during hospitalization were extracted from the first medical record pages according to the ICD codes. The data were assessed for normality using the Kolmogorov–Smirnov test. Depending on the data distribution, they were analyzed using parametric tests, such as the t-test, or non-parametric tests. Qualitative data are expressed as percentages (%) and analyzed using the chi-square or Fisher’s exact probability test, with α = 0.05 as the test level. P

Marginal lands, such as those with saline soils, have potential as alternative resources for cultivating dedicated biomass crops used in the production of renewable energy and chemicals. Optimum utilization of marginal lands can not only alleviate the competition for arable land use with primary food crops, but also contribute to bioenergy products and soil improvement. Miscanthus sacchariflorus and M. lutarioriparius are prominent perennial plants suitable for sustainable bioenergy production in saline soils. However, their responses to salt stress remain largely unexplored. In this study, we utilized 318 genotypes of M. sacchariflorus and M. lutarioriparius to assess their salt tolerance levels under 150 mM NaCl using 14 traits, and subsequently established a mini-core elite collection for salt tolerance. Our results revealed substantial variation in salt tolerance among the evaluated genotypes. Salt-tolerant genotypes exhibited significantly lower Na+ content, and K+ content was positively correlated with Na+ content. Interestingly, a few genotypes with higher Na+ levels in shoots showed improved shoot growth characteristics. This observation suggests that M. sacchariflorus and M. lutarioriparius adapt to salt stress by regulating ion homeostasis, primarily through enhanced K+ uptake, shoot Na+ exclusion, and Na+ sequestration in shoot vacuoles. To evaluate salt tolerance comprehensively, we developed an assessment value (D value) based on the membership function values of the 14 traits. We identified three highly salt-tolerant, 50 salt-tolerant, 127 moderately salt-tolerant, 117 salt-sensitive, and 21 highly salt-sensitive genotypes at the seedling stage by employing the D value. A mathematical evaluation model for salt tolerance was established for M. sacchariflorus and M. lutarioriparius at the seedling stage. Notably, the mini-core collection containing 64 genotypes developed using the Core Hunter algorithm effectively represented the overall variability of the entire collection. This mini-core collection serves as a valuable gene pool for future in-depth investigations of salt tolerance mechanisms in Miscanthus.

Protected areas (PAs) are crucial for supporting biodiversity and ecosystem services, but human pressure increasing within PAs, which remain poorly understood, will undermine this. Here, we used the human modification model to map the comprehensive human pressure for China and analyze its changes in nature reserves (NRs, the primary category of PAs in China) during 2000–2020. We found that human pressure within NRs showed decreasing trends with fluctuations, far lower than the whole country. But in eastern and northeastern China, human pressure within NRs has been increasing since 2000. NRs in China can be classified into the national, provincial, prefectural, and county levels, and an individual NR can be further classified into strictly protected core zones, buffer zones allowing limited human use, and experimental zones that examine different land uses. The stricter the management level of the NRs, the lower the human pressure. Our results show substantial progress in China's NRs management, but existing conservation actions are not enough for conservation targets. Strictly conservation areas must be expanded to promote conservation planning and complimented by multi-coordinated regional policy for biodiversity conservation.

High-velocity aerated flow is a common phenomenon in spillways. Its accurate modelling is challenging, mainly due to the lack of realistic physics in the conventional two-phase models. To this end, this study establishes a population balance model (PBM) approach to account for the evolutionary process of air bubbles. The air-water flow in a stepped chute is examined. The model performance is evaluated by statistical metrics: correlation coefficient (CC), root mean squared error (RMSE), and mean absolute error (MAE). Compared with conventional models, the PBM generates improved air-water predictions. However, the flow parameters are still underestimated, particularly in areas with intense air-water interactions. For further development, an error-corrected PBM (EPBM) is proposed by incorporating machine learning (ML) techniques into the PBM. Compared with the PBM, the EPBM leads to a mean augmentation in velocity prediction by 19.8% for the CC, 73.0% for the RMSE, and 77.1% for the MAE. The gains in air concentration estimation are 2.0%, 67.6% and 73.5%, respectively. The EPBM generates the most accurate results, with 99.6% and 89.6% of the velocity and air concentration predictions within a 20% relative error range. The main contributions are establishing a PBM for air-water flows and developing an error-corrected PBM using ML.

Protected areas are widely recognized as crucial for biodiversity conservation and ecosystem service maintenance. In recent decades, countries worldwide have made great progress in expanding the scope of protected areas. However, the evaluation of conservation effectiveness is insufficient due to limited resource inputs. In this study, we assessed the nature reserves’ effectiveness in conserving biodiversity and ecosystem services for the Three-river Source of the Tibetan Plateau in China over the past 20 years at multiple scales. Our findings revealed substantial improvements in biodiversity value, habitat quality, water retention carbon storage, and a slight decline in soil retention. Furthermore, implementing conservation measures within the nature reserves has resulted in better ecological conditions than areas outside. In terms of the different protection zones within the nature reserves, the core areas showed the highest improvement in ecological conditions, followed by the buffer areas and experimental areas. These results indicate a positive influence of ecological projects on conservation objectives. Additionally, the study indicated the effectiveness of more stringent conservation management. Limiting human activities and taking measures to protect soil retention in the Three-river nature reserves is urgent.

Suspended sediment load (SSL) is essential to river and dam engineering. Due to the complexity and stochastic nature of sedimentation, SSL prediction is a challenging task and conventional methods often fail to generate accurate results. Aiming to provide an improved estimation, this paper contributes to a new forecasting framework by integrating the seasonal adjustment (SA) and Bayesian optimization (BOP) into a machine learning (ML) model (denoted as BMS). The SA is used for de-seasonalisation and trend extraction; the BOP is to optimize the ML architecture. The BMS is evaluated using the daily SSL records from the Yangtze River. Its performance is appraised by statistical criteria of Nash-Sutcliffe efficiency (NSE), correlation coefficient (CC), root mean squared error (RMSE) and mean absolute error (MAE). With the de-noising and hyper-parameter tuning modules, the BMS effectively heightens the accuracy of the standard ML models. The most significant improvement occurs in the Boosting model, with its augments in NSE and CC by 4.3% and 1.6%, and reductions in RMSE and MAE by 24.9% and 24.2%. The BMS gains by comparison even under flood conditions, where it remarkably reduces the errors of the constituent models by up to 47.9% for RMSE and 48.3% for MAE.

Abstract Purpose To investigate the factors influencing and long-term effects of manual myotomy (MM) occurring during physiotherapy for congenital muscular torticollis (CMT). Methods We retrospectively collected the clinical data of children with CMT receiving physiotherapy between 2008 and 2018. The children were divided into manual myotomy (MM) and non-manual myotomy (NMM) groups according to whether MM occurred during treatment. We assessed physiotherapy outcomes in children with CMT using craniofacial asymmetry parameters and the Cheng–Tang rating score. By measuring the ear-eye distance, ear-nose distance, eye-mouth distance, ear-mouth distance, half-head circumference, and half-head top at two sides to evaluate craniofacial asymmetry. Based on the Cheng–Tang assessment criteria, we recorded the range of rotation, range of lateral flexion, the status of the contracted muscle, the hardness of the mass, the extent of head tilting during activities and sleeping, the status of daily activities, face size, type of head shape, cranial changes, and subjective head tilting to assess the effectiveness of treatment. Clinical data and outcome indicators (craniofacial asymmetry parameters and Cheng–Tang rating score) were compared. Results The MM group had a significantly higher total Cheng–Tang rating score than the NMM group (P

IntroductionPublic–private partnership (PPP) older adult care project is an effective means to solve the dilemma of the aging population in China's rural areas, but there are some problems in the operation process, such as a low participation rate and poor service quality, resulting in the needs of rural older adult groups not being met.MethodsTo alleviate the pressure of the aging population in rural areas, this study establishes an evolutionary game model for the PPP older adult care project, then defines the interests of local government, the private sector, and rural older adult residents, based on which it discusses the strategic choices of the three parties in the evolutionary process, and finally analyzes the influencing factors of the strategic choices of the game parties through simulation.ResultsThe results suggest that whether the private sector chooses to actively participate in the project will be influenced by the willingness of local government and rural older adult residents to participate in the project. Local government could play the role of supervisor through reward and punishment mechanisms. Whether older rural residents choose to participate in the project depends on the number of benefits they would receive.DiscussionBased on these findings, local governments should clarify the responsibilities of relevant stakeholders, adopt a regulatory strategy combining subsidies and penalties, improve the participation efficiency of rural older adult residents, promote the effective operation of PPP older adult care projects, and improve the quality of rural older adult care services in the new era.

Nowadays, economic development and ecological environment protection are difficult to synergize, which poses a challenge to global sustainable development. This paper uses the Tapio decoupling model to evaluate the decoupling between ecological footprint and economic growth, and uses the Logarithmic Mean Divisia Index (LMDI) decomposition methods to identify the driving factors of decoupling at national and provincial levels. There are four driving factors: industrial structural, technological innovation, economic development, and population size. It is found that: (1) The ecological footprint of 28 provinces show an upward trend, with an average increase of 40.26%. Among them, the ecological footprint of three provinces in the northwest region increased by more than 100%, and there is an urgent need to reduce natural resource consumption and ensure resource sustainability; (2) The number of provinces with good decoupling show a change of first declining and then rising. Moreover, the spatial distribution characteristics of the decoupling state are obvious, with the northeastern region in negative decoupling; and (3) Technological innovation plays a positive and leading role in decoupling, with a contribution rate of 0.5402. However, economic development inhibits decoupling, with a contribution rate of 0.3829. According to the results, this paper suggests countermeasures and approaches to promote the decoupling of ecological footprint and economic growth, and establishes three key regional concerns. It provides a basis for further analysis of environmental governance in China. Not only that, the regulatory measures and methods proposed in this study will also help promote the decoupling process of other developing countries in the world.

Background: The SYNTAX score (SS) is useful for predicting clinical outcomes in patients undergoing percutaneous coronary intervention (PCI). The clinical SYNTAX score (CSS), developed by combining clinical parameters with the SS, enhances the risk model’s ability to predict clinical outcomes. However, prior research has not yet evaluated the prognostic capacity of CSS in patients with complex coronary artery disease (CAD) and chronic renal insufficiency (CRI) who are undergoing PCI. We aimed to demonstrate the prognostic potential of CSS in assessing long-term adverse events in this high-risk patient cohort. Methods: A total of 962 patients with left main and/or three-vessel CAD and CRI were enrolled in the study spanning from January 2014 to September 2017. The CSS was calculated by multiplying the SS by the modified age, creatinine, and left ventricular ejection fraction (ACEF) score (age/ejection fraction + 1 for each 10 mL of creatinine clearance

Abstract Background Fractures are the most common type of unintentional injury in children, with traumatic upper limb fractures accounting for approximately 80% of all childhood fractures. Many epidemiological investigations of upper limb fractures in children have been conducted, but with the development of society, the patterns of childhood fractures may have changed. This study aimed to analyze the epidemiology and economic cost factors of upper limb fractures in Chinese children. Methods We retrospectively reviewed children with upper limb fractures or old upper limb fractures hospitalized between December 1, 2015, and December 31, 2019, in 22 tertiary children’s hospitals, under China’s Futang Research Center of Pediatric Development. We used the ICD10 codes on the front sheet of their medical records to identify cases and extracted data on age, sex, injury cause, fracture site, treatment, the year of admission and discharge, visiting time, and various costs during hospitalization from the medical record. Results A total of 32,439 children (21,478 boys and 10,961 girls) were identified, of whom 32,080 had fresh fractures and 359 had old fractures. The peak age was 3–6 years in both sexes. A total of 4788 were infants, 14,320 were preschoolers, 10,499 were in of primary school age, and 2832 were adolescent. Fractures were most frequent in autumn (August to October). Admissions peaked at 0 o’clock. Among the 32,080 children with fresh upper limb fractures, the most common fracture site was the distal humerus, with a total of 20,090 fracture events including 13,134 humeral supracondylar fractures and 4914 lateral humeral condyle fractures. The most common cause of injuries was falling over. The most common joint dislocation accompanying upper limb fractures occurred in the elbow, involving 254 cases. Surgery was performed in 31,274 children, and 806 did not receive surgery. Among those with clear operative records, 10,962 children were treated with open reduction and 18,066 with closed reduction. The number of cases was largest in the East China region (Anhui Province, Shandong Province, Jiangsu Province, Zhejiang Province, and Fujian Province), with 12,065 cases overall. Among the 359 children with old fractures, 118 were admitted with a diagnosis of “old humerus fracture,” accounting for the highest proportion; 244 underwent surgical open reduction, 16.16% of whom had osteotomy. For the children with fresh fractures, the average total hospital cost was 10,994 yuan, and the highest average total hospital cost was 14,053 yuan, for humeral shaft fractures. For the children with old fractures, the average total hospital cost was 15,151 yuan, and the highest average total hospital cost was 20,698 yuan, for old ulna fractures. Cost of materials was the principle factor affecting total hospital cost, followed by surgery and anesthesia costs, both in children with fresh fractures and those with old fractures. Significant differences were observed in all hospital costs (P

Establishing an artificial grassland is a common measure employed to restore heavily degraded alpine grasslands for regional sustainability. The Three-River Headwaters Region in China has significant areas of black-soil-type grassland which is typified by heavy degradation; nearly 35% of the grassland regions in the Three-River Headwaters Region has degraded into this type. There are different plant community types of black-soil-type grasslands, however, it is not clear which restoration measures should be adopted for different kinds of black-soil-type grasslands. Here, we investigate the plant community characteristics and soil physicochemical properties of artificial grasslands, two types of black-soil-type grasslands, and native undegraded grassland in the Three-River Headwaters Region, then analyzed the direct and indirect interactions between the plant and soil properties by partial least squares path models (PLS-PM). Our results revealed that establishing artificial grassland significantly increased aboveground biomass and plant community coverage, and also decreased plant species richness and diversity and soil water content, soil organic carbon and total nitrogen in the 0-10 cm soil layer as compared with black-soil-type grasslands. Plant community diversity had a positive effect on plant community productivity, soil nutrient, and soil water content in native undegraded grassland. These results suggest that more management interventions are needed after establishing an artificial grassland, such as reducing dominant species in two types of black-soil-type grasslands, water regulation in the A. frigida-dominated meadow, diversifying plant species (i.e., Gramineae and sedges), and fertilizer addition.

Abstract Purpose To explore and analyze the causes and related influencing factors of pediatric fractures, and provide theoretical basis for reducing the incidence and adverse effects of pediatric fractures. Methods This study retrospectively analyzed the epidemiological characteristics of fractures in pediatric aged ≤18 years old who were admitted to the our hospital between July 2015 and February 2020. Results A total of 10,486 pediatric patients were included in the study, of whom 6961 (66.38%) were boys, and 3525 (33.62%) were girls. For the fracture incidence, age group of the 3-6 years reached the peak. 5584 (60.76%) children were operated upon within 12 h after admission. The top three types of fractures were the distal humerus (3843 sites, 27.49%), distal ulna (1740 sites, 12.44%), and distal radius (1587 sites, 11.35%). The top three causes of injury were falls (7106 cases, 82.10%), car accidents (650 cases, 65.72%), and clipping (465 cases, 5.37%). Fractures predominantly occurred between July and November (4664 cases, 48.87%) and on Saturdays and Sundays (3172 cases, 33.24%). The highest number of hospital visits occurred between 20:00 and 00:00 (4339 cases, 45.46%). Conclusion For pediatric fractures, we should take appropriate and effective preventive measures to reduce the incidence of children’s fractures according to the distribution characteristics of age, gender, cause of injury, and fracture site.

A spillway discharging a high-speed flow is susceptible to cavitation damages. As a countermeasure, an aerator is often used to artificially entrain air into the flow. Its air demand is of relevance to cavitation reduction and requires accurate estimations. The main contribution of this study is to establish an embedded multi-gene genetic programming (EMGGP) model for improved prediction of air demand. It is an MGGP-based framework coupled with the gene expression programming acting as a pre-processing technique for input determination and the Pareto front serving as a post-processing measure for solution optimization. Experimental data from a spillway aerator are used to develop and validate the proposed technique. Its performance is statistically evaluated by the coefficient of determination (CD), Nash–Sutcliffe coefficient (NSC), root-mean-square error (RMSE) and mean absolute error (MAE). Satisfactory predictions are yielded with CD = 0.95, NSC = 0.94, RMSE = 0.17 m3/s and MAE = 0.12 m3/s. Compared with the best empirical formula, the EMGGP approach enhances the fitness (CD and NSC) by 23% and reduces the errors (RMSE and MAE) by 48%. It also exhibits higher prediction accuracy and a simpler expressional form than the genetic programming solution. This study provides a procedure for the establishment of parameter relationships for similar hydraulic issues. HIGHLIGHTS An embedded multi-gene genetic programming is developed.; An explicit and simple correlation is proposed for air demand estimation.; Existing empirical models are assessed and recalibrated.; The proposed model improves the prediction accuracy significantly.;

Abstract Background Unintentional injury is one of the top three causes of death for infants. However, the epidemiological studies of skeletal trauma and skull fractures in infants younger than 1 year were poorly understood in China. Therefore, our study aimed to examine accidental and emergency attendance in infants under 1 year. It also tried to determine the prevalence and severity of accident types in infants. Methods A retrospective analysis was performed on the demographic characteristics of infants younger than 1 year with skeletal trauma and skull fractures who visited the Shenzhen Children’s Hospital from January 1, 2016 to December 31, 2019. Age, gender, fracture site and type, mechanism of injury, length of visit, length of hospital stay, hospitalization cost, and treatment methods were analyzed. Results A total number of 675 fractures in 664 infants were included, the median age was 187days (IQR,90-273days), including 394 males and 270 females. The top three fracture sites were the skull (430 sites, 63.70 %), long bones of the limbs (168 sites, 24.89 %), and clavicle (53 sites, 7.85 %). The top three causes of injury were locomotion injuries (256 cases, 38.55 %), falls or trips from low height (from beds, tables, chairs, etc.) (130 cases, 19.58 %), and birth injuries (97 cases, 14.61 %). The greatest amount of fractures occurred in children 1–28 days of life (d) reached a top of 101 cases, followed by 331–365 days, accounting for 15.21 and 10.24 %, respectively. The number of fractures reached a trough of 29 cases in the 29-60d group (4.37 %). And increased again to 65 cases in the 151-180d group (9.79 %). The proportion remained relatively constant at 9 % in the 181-210d group (9.19 %) and 211-240d group (9.64 %). The interval between injury and visiting our hospital was ≤ 72 h in 554 cases. Conclusions Special attention should be given to the demographic characteristics of fractures in infants under 1 year of age, and appropriate outreach should be implemented. For example, health education should be provided to aid in the prevention especially for frequently occurring locomotion injuries, and prompt access to specialist medical care should be recommended for skull fractures, which are prone to delayed treatment. In addition, multidisciplinary collaboration should be implemented in trauma care, while also promoting the establishment of trauma centers in specialist children’s hospitals with a stronger capacity to treat pediatric trauma, and a regional system for pediatric trauma treatment.

BackgroundPhenotype information in electronic health records (EHRs) is mainly recorded in unstructured free text, which cannot be directly used for clinical research. EHR-based deep-phenotyping methods can structure phenotype information in EHRs with high fidelity, making it the focus of medical informatics. However, developing a deep-phenotyping method for non-English EHRs (ie, Chinese EHRs) is challenging. Although numerous EHR resources exist in China, fine-grained annotation data that are suitable for developing deep-phenotyping methods are limited. It is challenging to develop a deep-phenotyping method for Chinese EHRs in such a low-resource scenario. ObjectiveIn this study, we aimed to develop a deep-phenotyping method with good generalization ability for Chinese EHRs based on limited fine-grained annotation data. MethodsThe core of the methodology was to identify linguistic patterns of phenotype descriptions in Chinese EHRs with a sequence motif discovery tool and perform deep phenotyping of Chinese EHRs by recognizing linguistic patterns in free text. Specifically, 1000 Chinese EHRs were manually annotated based on a fine-grained information model, PhenoSSU (Semantic Structured Unit of Phenotypes). The annotation data set was randomly divided into a training set (n=700, 70%) and a testing set (n=300, 30%). The process for mining linguistic patterns was divided into three steps. First, free text in the training set was encoded as single-letter sequences (P: phenotype, A: attribute). Second, a biological sequence analysis tool—MEME (Multiple Expectation Maximums for Motif Elicitation)—was used to identify motifs in the single-letter sequences. Finally, the identified motifs were reduced to a series of regular expressions representing linguistic patterns of PhenoSSU instances in Chinese EHRs. Based on the discovered linguistic patterns, we developed a deep-phenotyping method for Chinese EHRs, including a deep learning–based method for named entity recognition and a pattern recognition–based method for attribute prediction. ResultsIn total, 51 sequence motifs with statistical significance were mined from 700 Chinese EHRs in the training set and were combined into six regular expressions. It was found that these six regular expressions could be learned from a mean of 134 (SD 9.7) annotated EHRs in the training set. The deep-phenotyping algorithm for Chinese EHRs could recognize PhenoSSU instances with an overall accuracy of 0.844 on the test set. For the subtask of entity recognition, the algorithm achieved an F1 score of 0.898 with the Bidirectional Encoder Representations from Transformers–bidirectional long short-term memory and conditional random field model; for the subtask of attribute prediction, the algorithm achieved a weighted accuracy of 0.940 with the linguistic pattern–based method. ConclusionsWe developed a simple but effective strategy to perform deep phenotyping of Chinese EHRs with limited fine-grained annotation data. Our work will promote the second use of Chinese EHRs and give inspiration to other non–English-speaking countries.

Exploring the complex relationship between ecological restoration and economic development is valuable for decision makers to formulate policy for sustainable development. The large-scale environmental restoration program—Grain for Green—was mainly implemented in the Loess Plateau of China to improve the soil retention service. However, whether this world-famous program affects local economic development has not been fully explored. In this study, using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and spatializing the gross domestic product (GDP) based on the remotely sensed nightlight data, we explored the tradeoff between environment (i.e., soil retention service) and economy (i.e., GDP) for the Loess Plateau in a spatially explicit way. We found that the soil retention service increased prominently over the past 40 years, especially after implementing the Grain for Green project. Meanwhile, the GDP increased about nine-fold over the past four decades from 4.52 to 40.29 × 107 USD. A win–win situation of soil retention and economic development was achieved in the Loess Plateau of China, particularly in the loess gully and loess hilly gully regions of the Loess Plateau. The win–win situation of soil retention and economic development was as a result of the Grain for Green program, the optimization of industrial structure, and the increase in non-agriculture employment. Compared with previous studies, more spatial information was available for the Loess Plateau in this study, which is more valuable to policymakers.

In order to improve the thickness uniformity of the electroformed metal layer and components, a new electroforming technique is proposed—wire-anode scanning electroforming (WAS-EF). WAS-EF uses an ultrafine inert anode so that the interelectrode voltage/current is superimposed upon a very narrow ribbon-shaped area at the cathode, thus ensuring better localization of the electric field. The anode of WAS-EF is in constant motion, which reduces the effect of the current edge effect. The stirring paddle of WAS-EF can affect the fluid flow in the microstructure, and improve the mass transfer effect inside the structure. The simulation results show that, when the depth-to-width ratio decreases from 1 to 0.23, the depth of fluid flow in the microstructure can increase from 30% to 100%. Experimental results show that. Compared with the traditional electroforming method, the single metal feature and arrayed metal components prepared by WAS-EF are respectively improved by 15.5% and 11.4%.

ObjectiveThe purpose of this study was to predict elevated TSH levels by developing an effective machine learning model based on large-scale physical examination results.MethodsSubjects who underwent general physical examinations from January 2015 to December 2019 were enrolled in this study. A total of 21 clinical parameters were analyzed, including six demographic parameters (sex, age, etc.) and 15 laboratory parameters (thyroid peroxidase antibody (TPO-Ab), thyroglobulin antibody (TG-Ab), etc.). The risk factors for elevated TSH levels in the univariate and multivariate Logistic analyses were used to construct machine learning models. Four machine learning models were trained to predict the outcome of elevated TSH levels one year/two years after patient enrollment, including decision tree (DT), linear regression (LR), eXtreme Gradient boosting (XGBoost), and support vector machine (SVM). Feature importance was calculated in the machine learning models to show which parameter plays a vital role in predicting elevated TSH levels.ResultsA total of 12,735 individuals were enrolled in this study. Univariate and multivariate Logistic regression analyses showed that elevated TSH levels were significantly correlated with gender, FT3/FT4, total cholesterol (TC), TPO-Ab, Tg-Ab, creatinine (Cr), and triglycerides (TG). Among the four machine learning models, XGBoost performed best in the one-year task of predicting elevated TSH levels (AUC (0.87(+/- 0.03))). The most critical feature in this model was FT3/FT4, followed by TPO-Ab and other clinical parameters. In the two-year task of predicting TSH levels, none of the four models performed well.ConclusionsIn this study, we trained an effective XGBoost model for predicting elevated TSH levels one year after patient enrollment. The measurement of FT3 and FT4 could provide an early warning of elevated TSH levels to prevent relative thyroid diseases.

The existed synthesis methods for producing high microhardness nanostructured metal materials (NMMs) are usually at the cost of reducing the tensile strength and introducing heterogeneous elements, thus making forming ultrahigh strength ultrapure NMMs significantly challengeable. We unprecedentedly produced ultrapure (99.9997%) nickel deposits simultaneously with an ultrahigh strength and mirror-like surfaces as well as an appreciably high ductility by using our proposed ultrafine anode scanning electrodeposition (UAS-ECD). Distinctively, the UAS-ECD is a speed-dependent localized scanning electrodeposition rather than a commonly-used current-dependent electrodeposition. Therefore, the UAS-ECD can create NMMs at extremely high local current densities and with no additives. This makes it achievable to generate ultrahigh strength ultrapure NMMs with microhardness of 656 HV and tensile strength of 664 MPa (fracture elongation, 8.5%), which are respectively 29% and 30% higher than those reported in the literature. Further surprisingly, the samples’ tensile strength has only an approximately 1% reduction after being annealed. This is attributed to minimum impurities introduction and evenly distributed ultrafine grains formed. In addition, UAS-ECD is able to produce grain-varying deposits just by adjusting the anode’s scanning speed, conveniently achieving 65 wt%-95 wt% nano-& micro-sized grains composite NMMs. This work provides a novel strategy for synthesizing ultrahigh strength ultrapure NMMs.

Global aging is getting worse, especially in China, a country with a large population. It is urgently needed to plan the site of new urban elderly care facilities for an aging society. Based on point of interest data and machine learning algorithms, we established a site selection model of urban elderly care facilities for Wuhan in China and selected potential optimal sites for new urban elderly care facilities. We found that 2059 of the 31,390 grids with a resolution of 500 m × 500 m of Wuhan are priority layout grids for new urban elderly care facilities. A total of 635 priority grids were further selected based on the agglomeration degree of the aging population in each street. They are mainly distributed in the areas with a concentrated aging population within the Second Ring Road around the urban centers. Additionally, some outer suburban streets with a relatively high aging degree also require immediate facility construction. The point of interest data and machine learning algorithms to select the location of urban elderly care facilities can optimize their overall configuration and avoid the subjectivity of site selection to some degree, provide empirical support for how to achieve a good configuration of “population–facilities” in space, and continuously improve the science of the spatial allocation of elderly care facilities.

A pooled fishway is an artificial structure to improve the river flow connectivity and facilitate fish migration. Its conventional layout is characterized by straight weirs and suffers from limited passage rate. To improve its flow behaviors, an alternative design, featuring a V-shaped weir arrangement, is devised. CFD simulations are performed to examine its effects on the flow conditions. The governing geometrical parameters include weir angling, height, and spacing. Depending on weir arm angle, the flow is directed towards either the channel’s central part or the sidewalls, leading to both across- and along-channel differences in flow velocity and turbulent kinetic energy. This offers conducive zones for multiple fish species with distinct swimming preferences. For a given location in a pool, the cross-sectional velocity exhibits a cosine-type variation; a relationship is established to predict the maximum longitudinal velocity. The pressure distribution exhibits a similar pattern, with high-pressure areas residing upstream of the weir. A power law describes the relationship between the energy dissipation rate and unit discharge with an exponent at approximately 2/3. With an increase in either weir spacing or height, the energy dissipation rate declines. A change in weir angle shows however a negligible influence on it.

The scientific estimation of carbon budgets induced by land use and land cover change (LUCC) can improve the accuracy of carbon budget estimates for terrestrial ecosystems and deepen our understanding of the future carbon sink potential of these ecosystems. Previous studies have typically selected one of many LUCC-induced carbon budget methods and overlooked the differences in the results between the different methods. Taking Henan Province, China, as a case study, we used the IPCC method, the bookkeeping model, and the inventory method to estimate LUCC-induced carbon budgets and compared the differences in these methods. The results showed that LUCC in Henan Province was categorized as a carbon sink from 1980 to 2015 based on the IPCC method and the inventory method. However, the estimates were significantly different, and the total estimates of the IPCC method were 40% less than those of the inventory method. At the regional ecogeographical scale, the two methods were not consistent in assessing the carbon source/sink of LUCC. The bookkeeping model categorized LUCC as a carbon source in Henan Province for the same period, and the carbon storage change trend opposed those of the other two methods. The failure of the IPCC method and the bookkeeping model to include the dynamic changes in carbon density caused by climate and land use management led to the great differences between the three methods. The inventory method is recommended to estimate the carbon budget caused by LUCC for regions where carbon density varies greatly over time. Both the IPCC method and the bookkeeping model may have great uncertainty in estimating changes in LUCC-induced carbon stocks and should be used with caution.

The internal trade-off of land space is caused by the competition of land use for multiple functions, such as agricultural production, economic development and ecological protection. In response to this common problem, this study uses a positive and negative assignment method and a more refined evaluation scale to analyze the spatial and temporal variation characteristics and synergy/trade-off relationship of production–living–ecological space in the Sino-Vietnamese border area from 2000 to 2020. The results show that: (1) There was great regional diversity in the evolution characteristics of the Sino-Vietnamese border. Production space (PS) and living space (LS) presented prominent expansion, and ecological space (ES) was shrinking. (2) From 2000 to 2020, the degree of synergy between PS and LS has increased gradually. The trade-off relationship between PS and ES has shown different fluctuation intensities. The synergy/trade-off relationship between LS and ES has changed, and its trade-off intensity has continuously increased. (3) On the spatial scale, the PS and LS trade-off areas are mostly distributed in the central and western regions with higher altitudes, and the spatial pattern of the synergy zone is expanding. The synergy and trade-off relationship between PS and ES are relatively stable over time. The area of the trade-off between LS and ES has expanded gradually. In conclusion, the synergy/trade-off relationship between the PLES functions has strong consistency with regional economic and social development, which can serve as a scientific basis for the healthy and sustainable development of land space.

Salt-sensitive hypertension is closely related to inflammation, but the mechanism is barely known. Transmembrane member 16A (TMEM16A) is the Ca2+-activated chloride channel in epithelial cells, smooth muscle cells, and sensory neurons. It can promote inflammatory responses by increasing proinflammatory cytokine release. Here, we identified a positive role of TMEM16A in vascular inflammation. The expression of TMEM16A was increased in high-salt-stimulated vascular smooth muscle cells (VSMCs), whereas inhibiting TMEM16A or silencing TMEM16A with small interfering RNA (siRNA) can abolish this effect in vitro or in vivo. Transcriptome analysis of VSMCs revealed some differential downstream genes of TMEM16A related to inflammation, such as endothelial cell-specific molecule 1 (ESM1) and CXC chemokine ligand 16 (CXCL16). Overexpression of TMEM16A in VSMCs was accompanied by high levels of ESM1, CXCL16, intercellular adhesion molecule-1 (ICAM-1), and vascular adhesion molecule-1 (VCAM-1). We treated VSMCs cultured with high salt and arctigenin (ARC), T16Ainh-A01 (T16), and TMEM16A siRNA (siTMEM16A), leading to greatly decreased ESM1, CXCL16, VCAM-1, and ICAM-1. Beyond that, silencing ESM1, the expression of VCAM-1 and ICAM-1, and CXCL16 was attenuated. In conclusion, our results outlined a signaling scheme that increased TMEM16 protein upregulated ESM1, which possibly activated the CXCL16 pathway and increased VCAM-1 and ICAM-1 expression, which drives VSMC inflammation. Beyond that, arctigenin, as a natural inhibitor of TMEM16A, can reduce the systolic blood pressure (SBP) of salt-sensitive hypertension mice and alleviate vascular inflammation.

Hepatocellular carcinoma (HCC) accounts for 70–85% of liver cancer, and about 85% of HCC are hepatitis B virus-related (HBV-HCC) in China. Transarterial chemoembolization (TACE) combined with traditional Chinese medicine (TCM) has been reported as an effective treatment. Potential biomarkers to stratify patients who may benefit from this treatment are needed. In this study, we aimed to evaluate whether circulating cell-free mitochondrial DNA (ccf-mtDNA) content was associated with the outcome of HCC patients, especially of those who received the combination treatment of TACE and TCM. Univariate and multivariate Cox analyses were conducted to evaluate the association between ccf-mtDNA content and the overall survival of HBV-HCC patients. Kaplan–Meier analysis was used to compare the survival differences between patients with low and high ccf-mtDNA content. In a hospital-based cohort with 141 HBV-HCC patients, there was no statistically significant association between the ccf-mtDNA content and the overall survival of HBV-HCC patients in the univariate analysis, but a borderline significant association was found in the multivariate analyses. In a subcohort of 50 HBV-HCC patients who received TACE and TCM treatment, high ccfDNA content conferred an increased death risk with a hazard ratio of 4.01 (95% confidence interval: 1.25–12.84, p = 0.019) in the multivariate analysis. Kaplan–Meier survival analysis also showed that patients with high ccf-mtDNA content had unfavorable survival (log rank p = 0.097). Our findings suggest that ccf-mtDNA content is a potential non-invasive prognostic biomarker in HCC patients receiving TACE and TCM treatment.

The optimization of energy control strategy is one of the key technologies of plug-in hybrid vehicles (PHEVs) to improve the capabilities of energy saving and emission reduction. In order to improve fuel economy of PHEV, adaptive equivalent minimum fuel consumption strategy (A-ECMS) is proposed. Firstly, optimization methods of different energy control strategies are analyzed, and the Pontryagin’s Minimum Principle (PMP) and the equivalent fuel consumption theory are selected to optimize energy control strategy of the PHEV. Secondly, the configuration of PHEV and research objectives of the power control system are determined. Thirdly, the energy control problem is analyzed by the PMP theory, and the improvement measures for the energy control problem are put forward by the equivalent minimum fuel consumption strategy (ECMS). Fourthly, after analyzing the relationship between the equivalent factor and reference SOC, adaptive equivalent minimum fuel consumption strategy (A-ECMS) model is established by MATLAB/Simulink. Finally, combined with Cruise software, the PHEV simulation model is simulated, and the simulation results are analyzed. The results show that compared with the CD/CS energy control strategy, the A-ECMS energy control strategy reduced the 100 km fuel consumption of the vehicle by 7% under three times WLTC driving condition.

BackgroundPhenotypes characterize the clinical manifestations of diseases and provide important information for diagnosis. Therefore, the construction of phenotype knowledge graphs for diseases is valuable to the development of artificial intelligence in medicine. However, phenotype knowledge graphs in current knowledge bases such as WikiData and DBpedia are coarse-grained knowledge graphs because they only consider the core concepts of phenotypes while neglecting the details (attributes) associated with these phenotypes. ObjectiveTo characterize the details of disease phenotypes for clinical guidelines, we proposed a fine-grained semantic information model named PhenoSSU (semantic structured unit of phenotypes). MethodsPhenoSSU is an “entity-attribute-value” model by its very nature, and it aims to capture the full semantic information underlying phenotype descriptions with a series of attributes and values. A total of 193 clinical guidelines for infectious diseases from Wikipedia were selected as the study corpus, and 12 attributes from SNOMED-CT were introduced into the PhenoSSU model based on the co-occurrences of phenotype concepts and attribute values. The expressive power of the PhenoSSU model was evaluated by analyzing whether PhenoSSU instances could capture the full semantics underlying the descriptions of the corresponding phenotypes. To automatically construct fine-grained phenotype knowledge graphs, a hybrid strategy that first recognized phenotype concepts with the MetaMap tool and then predicted the attribute values of phenotypes with machine learning classifiers was developed. ResultsFine-grained phenotype knowledge graphs of 193 infectious diseases were manually constructed with the BRAT annotation tool. A total of 4020 PhenoSSU instances were annotated in these knowledge graphs, and 3757 of them (89.5%) were found to be able to capture the full semantics underlying the descriptions of the corresponding phenotypes listed in clinical guidelines. By comparison, other information models, such as the clinical element model and the HL7 fast health care interoperability resource model, could only capture the full semantics underlying 48.4% (2034/4020) and 21.8% (914/4020) of the descriptions of phenotypes listed in clinical guidelines, respectively. The hybrid strategy achieved an F1-score of 0.732 for the subtask of phenotype concept recognition and an average weighted accuracy of 0.776 for the subtask of attribute value prediction. ConclusionsPhenoSSU is an effective information model for the precise representation of phenotype knowledge for clinical guidelines, and machine learning can be used to improve the efficiency of constructing PhenoSSU-based knowledge graphs. Our work will potentially shift the focus of medical knowledge engineering from a coarse-grained level to a more fine-grained level.

Identifying the driving forces and mechanisms underlying vegetation change is critical to globally adapting to future climate change. However, this topic remains unclear for ecosystems within the Headwater Source Region of Brahmaputra and Indus (HSRBI), southwestern Tibetan Plateau. In this study, vegetation changes, in terms of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), were detected for breakpoints for the period of 2000–2017 by segment regression analysis. The effects of 14 potential environmental variables on vegetation dynamics were estimated and quantified via random forest modelling. Our results showed that monotonic increases (MI) and abrupt increases (AI) in NDVI accounted for 39.87% and 22.55% of vegetation change, respectively. In contrast, monotonic decreases (MD) and abrupt decreases (AD) only accounted for 19.38% and 7.65% of vegetation change, respectively. Our findings also confirmed that climate change was the most crucial driver of vegetation change in the HSRBI, and human disturbance was responsible for abrupt changes in vegetation. The primary MI pattern was affected by distance to the replenishment water source, which contributed to 21.36% of vegetation change. The distance to lakes was an essential factor associated with vegetation greening. AI was mainly affected by the interaction between human disturbance and climate change, which contributed to 27.12% and 26.89% of vegetation changes, respectively. Distance to residential areas was the most significant factor that linked the human disturbance to abrupt vegetation changes. AD and MD were inclined to be affected by the variation in climate variables. Finally, this study will help to identify multidimensional mechanisms of vegetation change and aid ecosystem stability in the headwater zones.

Global historical land use datasets have been widely used in global or regional environmental change studies. Historical pasture data are essential components of these spatially explicit global datasets, and their uncertainties have not been well evaluated. Using the livestock-based historical pasture dataset for the Tibetan Plateau (TP), we evaluated the uncertainties of these representative global historical land use datasets in pasture reconstruction for the TP over the past 300 years in terms of pasture area estimation and spatial pattern mapping. We found that only the Sustainability and the Global Environment (SAGE) dataset can roughly reflect the temporal and spatial characteristics of historical pasture changes on the TP. The History Database of the Global Environment (HYDE) version 3.2 and the Pongratz Julia (PJ) datasets overestimated pasture area for the TP dramatically, with a maximum area ratio of about 221% and 291%, respectively, and the Kaplan and Krumhardt 2010 (KK10) dataset underestimated pasture area for the TP dramatically, with a minimum area ratio of only 9%. As for the spatial pattern, all these global datasets overestimated the spatial scope of grazing activities obviously. The KK10 dataset unreasonably allocated pasture to forest areas in southeastern Tibet because only climate and soil factors were considered in assessing land suitability for grazing. Using population to estimate pasture area and only using natural factors to allocate pasture area into grids is unsuitable for the TP historical pasture reconstruction. In the future, more information directly related to grazing activities, e.g., the number of livestock and its spatial distribution, and social-cultural factors, including technology and diet, should be used for area estimation and spatial pattern mapping to improve the accuracy of pasture data in these global datasets.

The management effectiveness of protected areas plays a key role in biodiversity and ecosystem services conservation. We evaluated the effectiveness of Qilian Mountain Nature Reserve (QMNR) in reducing human footprint (HF). Four dominant human activity factors, including population density, land use, road distribution, and night light, were incorporated for HF mapping. Comparisons of the HF value between inside and outside QMNR and its four functional zones were conducted. The results show that both the HF inside and outside of QMNR were increasing, but the difference between them was increasing, indicating partial management effectiveness. The north part of the central reserve has a good effect in reducing human impacts, while the effectiveness was poor at both ends of the reserve. The HF value of the most strictly managed core and buffer zones increased by 10.50 and 6.68%, respectively, for 2010–2020. The QMNR was effective in controlling population density and land use, but ineffective in reducing road construction, mining, and construction of hydropower facilities.

Abstract Background Aberrant DNA methylations are significantly associated with esophageal squamous cell carcinoma (ESCC). In this study, we aimed to investigate the DNA methylation-driven genes in ESCC by integrative bioinformatics analysis. Methods Data of DNA methylation and transcriptome profiling were downloaded from TCGA database. DNA methylation-driven genes were obtained by methylmix R package. David database and ConsensusPathDB were used to perform gene ontology (GO) analysis and pathway analysis, respectively. Survival R package was used to analyze overall survival analysis of methylation-driven genes. Results Totally 26 DNA methylation-driven genes were identified by the methylmix, which were enriched in molecular function of DNA binding and transcription factor activity. Then, ABCD1, SLC5A10, SPIN3, ZNF69, and ZNF608 were recognized as significant independent prognostic biomarkers from 26 methylation-driven genes. Additionally, a further integrative survival analysis, which combined methylation and gene expression data, was identified that ABCD1, CCDC8, FBXO17 were significantly associated with patients’ survival. Also, multiple aberrant methylation sites were found to be correlated with gene expression. Conclusion In summary, we studied the DNA methylation-driven genes in ESCC by bioinformatics analysis, offering better understand of molecular mechanisms of ESCC and providing potential biomarkers precision treatment and prognosis detection.

Abstract Visceral pleural invasion (VPI) has been identified as an adverse prognostic factor for non‐small cell lung cancer (NSCLC). Accurate nodal staging for NSCLC correlates with improved survival, but it is unclear whether tumors with VPI require a more extensive lymph nodes (LNs) dissection to optimize survival. We aimed to evaluate the impact of VPI status on the optimal extent of LNs dissection in stage I NSCLC, using the Surveillance, Epidemiology, and End Results (SEER) database. We identified 9297 surgically treated T1‐2aN0M0 NSCLC patients with at least one examined LNs. Propensity score matching was conducted to balance the baseline clinicopathologic characteristics between the VPI group and non‐VPI group. Log‐rank tests along with Cox proportional hazards regression methods were performed to evaluate the impact of extent of LNs dissection on survival. VPI was correlated with a significant worse survival, but there was no significant difference in survival rate between PL1 and PL2. Patients who underwent sublobectomy had slightly decreased survival than those who underwent lobectomy. Pathologic LNs examination was significantly correlated with survival. Examination of 7‐8 LNs and 14‐16 LNs conferred the lowest hazard ratio for T1‐sized/non‐VPI tumors (stage IA) and T1‐sized/VPI tumors (stage IB), respectively. The optimal extent of LNs dissection varied by VPI status, with T1‐sized/VPI tumors (stage IB) requiring a more extensive LNs dissection than T1‐sized/non‐VPI tumors (stage IA). These results might provide guidelines for surgical procedure in early stage NSCLC.

The ecological security of the Tibetan Plateau is vital for sustainable development. In recent years, biodiversity loss and ecosystem degradation caused by industrial and mining activities have attracted wide attention. However, a synthesis assessment of the impacts of industrial and mining land (IML) on the ecosystem is currently lacking. In this study, based on the land cover data and normalized differential vegetation index, we used the landscape ecological index, Theil-Sen trend analysis and equivalent value factors method to evaluate the change in IML and its ecosystem impact on the TP. The results demonstrated that the area of IML expanded by 3.3 times (228.56%) during 1990–2020, and reached 968.95 km² in 2020. Within this area, the newly added, stable, and reduced areas were 842.71, 126.26, and 168.65 km², respectively. Simultaneously, IML expansion made the landscape more fragmented during 1990–2020. The number of patches, splitting index, and landscape shape index in 2020 increased by 3.59-, 2.70-, and 1.90-fold compared to those in 1990, respectively. Furthermore, the difference in the vegetation change between the IML and its 10 km buffer zone was significant. About 77.34% of the vegetation in the IML area showed a trend of decrease, while about 76.51% of the vegetation in the buffer zone of IML showed a trend of increase. In addition, the expansion of IML also reduced the total ecological services value by USD 6969.31 million (0.66%) from 1990 to 2020. However, the lowered value was USD 8649.50 million (0.82%) in the newly added IML. This study highlights the rapid expansion of IML and reveals the ecosystem structure, ecosystem quality, and ecosystem service impact on the TP, which helps guide ecosystem protection and the sustainable development of mining.

Protected areas play significant roles in protecting biodiversity by mitigating human activities. As an indicator for human activities, the human footprint (HF) can be used to assess the effectiveness of protected areas. We developed a HF dataset for the Sanjiangyuan region in China after localizing the global HF model. Then we used it to assess the effectiveness of Sanjiangyuan nature reserve (SNR) in mitigating human pressures. Our results suggest that the HF value for the Sanjiangyuan region was generally low from 1995 to 2015, with a fluctuating increasing trend. The SNR is partially effective in mitigating human pressures. For 2005–2010, the HF values decreased both within and outside the reserve with more decreases for the outside. For the three functional zones of the SNR, our results show that the HF values decreased during 2005–2010 for all of them, with the largest decrease in the experimental area, and increased during 2010–2015, with the lowest increase in the core areas. The results we obtained are consistent with ecological indicator-based assessments. It is a challenge for the government to balance conservation and development in establishing Sanjiangyuan National Park.

The Mt. Qomolangma (Everest) National Nature Preserve (QNNP) is among the highest natural reserves in the world. Monitoring the spatiotemporal changes in the vegetation in this complex vertical ecosystem can provide references for decision makers to formulate and adapt strategies. Vegetation growth in the reserve and the factors driving it remains unclear, especially in the last decade. This study uses the normalized difference vegetation index (NDVI) in a linear regression model and the Breaks for Additive Seasonal and Trend (BFAST) algorithm to detect the spatiotemporal patterns of the variations in vegetation in the reserve since 2000. To identify the factors driving the variations in the NDVI, the partial correlation coefficient and multiple linear regression were used to quantify the impact of climatic factors, and the effects of time lag and time accumulation were also considered. We then calculated the NDVI variations in different zones of the reserve to examine the impact of conservation on the vegetation. The results show that in the past 19 years, the NDVI in the QNNP has exhibited a greening trend (slope = 0.0008/yr, p < 0.05), where the points reflecting the transition from browning to greening (17.61%) had a much higher ratio than those reflecting the transition from greening to browning (1.72%). Shift points were detected in 2010, following which the NDVI tendencies of all the vegetation types and the entire preserve increased. Considering the effects of time lag and time accumulation, climatic factors can explain 44.04% of the variation in vegetation. No climatic variable recorded a change around 2010. Considering the human impact, we found that vegetation in the core zone and the buffer zone had generally grown better than the vegetation in the test zone in terms of the tendency of growth, the rate of change, and the proportions of different types of variations and shifts. A policy-induced reduction in livestock after 2010 might explain the changes in vegetation in the QNNP.

The mechanisms underlying the oncogenesis and progression of lung adenocarcinoma (LUAD) are currently unclear. The discovery of competitive endogenous RNA (ceRNA) regulatory networks has provided a new direction for the treatment and prognosis of patients with LUAD. However, the mechanism of action of ceRNA in LUAD remains elusive. In the present study, differentially expressed mRNAs, microRNAs (miRs) and long non-coding RNAs from the cancer genome atlas database were screened. CeRNAs for LUAD were then identified using online prediction software. Among the ceRNAs identified, family with sequence similarity 83 member A (FAM83A), miR-34c-5p, KCNQ1OT1 and FLJ26245 were observed to be significantly associated with the overall survival of patients with LUAD. Of note, FAM83A has potential significance in drug resistance, and may present a candidate biomarker for the prognosis and treatment of patients with LUAD.

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