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Abstract Quantum chemical (QC) property prediction is crucial for computational materials and drug design, but relies on expensive electronic structure calculations like density functional theory (DFT). Recent deep learning methods accelerate this process using 1D SMILES or 2D graphs as inputs but struggle to achieve high accuracy as most QC properties depend on refined 3D molecular equilibrium conformations. We introduce Uni-Mol+, a deep learning approach that leverages 3D conformations for accurate QC property prediction. Uni-Mol+ first generates a raw 3D conformation using RDKit then iteratively refines it towards DFT equilibrium conformation using neural networks, which is finally used to predict the QC properties. To effectively learn this conformation update process, we introduce a two-track Transformer model backbone and a novel training approach. Our benchmarking results demonstrate that the proposed Uni-Mol+ significantly improves the accuracy of QC property prediction in various datasets.

Abstract Simulating electronic behavior in materials and devices with realistic large system sizes remains a formidable task within the ab initio framework due to its computational intensity. Here we show DeePTB, an efficient deep learning-based tight-binding approach with ab initio accuracy to address this issue. By training on structural data and corresponding ab initio eigenvalues, the DeePTB model can efficiently predict tight-binding Hamiltonians for unseen structures, enabling efficient simulations of large-size systems under external perturbations such as finite temperatures and strain. This capability is vital for semiconductor band gap engineering and materials design. When combined with molecular dynamics, DeePTB facilitates efficient and accurate finite-temperature simulations of both atomic and electronic behavior simultaneously. This is demonstrated by computing the temperature-dependent electronic properties of a gallium phosphide system with 106 atoms. The availability of DeePTB bridges the gap between accuracy and scalability in electronic simulations, potentially advancing materials science and related fields by enabling large-scale electronic structure calculations.

In order to study the effect of temperature effect on CO2 injection and gas extraction in deep coal seams, a fluid-solid-thermal coupling model for CO2-injection enhanced coal seam extraction was established based on the basic theory of coal deformation characteristics and gas seepage characteristics, which also considered non-isothermal adsorption, binary gas competitive adsorption, gas seepage and diffusion, heat transfer and heat convection. The influence of temperature effect on coal reservoir parameters and gas production evolution law is investigated. The results show that the shrinkage of coal matrix caused by coal bed temperature decrease promotes CH4 desorption, and the fluid-solid coupling model ignoring temperature effect will underestimate gas production. When the initial permeability is 3.95×10−17 m2 and the CO2 injection pressure is 8 MPa, for the deep coal body buried 1 400 m in the No. 3 coal seam in Hancheng Mining area, compared with the fluid-solid-thermal coupling model considering the temperature effect (319.5 K), the gas extraction time of 3 650 days is higher than that of the fluid-solid coupling model. The average gas pressure of coal seam decreased by 0.69%, the permeability of A point increased by 11.02%, the gas production rate increased by 13.51%, and the cumulative gas production increased by 13.76%.

In order to explore the influence of thermal effect and strain on gas drainage, a fluid solid thermal coupling model considering coal deformation, gas adsorption and thermal effect was established to simulate the influence of thermal effect and strain on gas drainage. The results show that the gas production rate is 11.48% higher and the gas production rate is 11.45% higher when the thermal effect is considered than when the thermal effect is not considered. The stronger the thermal effect, the greater the permeability, and the higher the gas production. This shows that the influence of thermal effect on gas drainage cannot be ignored; the influence of different strains on gas extraction is different, adsorption strain > temperature strain > pressure strain.

Abstract Background Community-acquired pneumonia (CAP) is a common and serious condition that can be caused by a variety of pathogens. However, much remains unknown about how these pathogens interact with the lower respiratory commensals, and whether any correlation exists between the dysbiosis of the lower respiratory microbiota and disease severity and prognosis. Methods We conducted a retrospective cohort study to investigate the composition and dynamics of sputum microbiota in patients diagnosed with CAP. In total, 917 sputum specimens were collected consecutively from 350 CAP inpatients enrolled in six hospitals following admission. The V3-V4 region of the 16 S rRNA gene was then sequenced. Results The sputum microbiota in 71% of the samples were predominately composed of respiratory commensals. Conversely, 15% of the samples demonstrated dominance by five opportunistic pathogens. Additionally, 5% of the samples exhibited sterility, resembling the composition of negative controls. Compared to non-severe CAP patients, severe cases exhibited a more disrupted sputum microbiota, characterized by the highly dominant presence of potential pathogens, greater deviation from a healthy state, more significant alterations during hospitalization, and sparser bacterial interactions. The sputum microbiota on admission demonstrated a moderate prediction of disease severity (AUC = 0.74). Furthermore, different pathogenic infections were associated with specific microbiota alterations. Acinetobacter and Pseudomonas were more abundant in influenza A infections, with Acinetobacter was also enriched in Klebsiella pneumoniae infections. Conclusion Collectively, our study demonstrated that pneumonia may not consistently correlate with severe dysbiosis of the respiratory microbiota. Instead, the degree of microbiota dysbiosis was correlated with disease severity in CAP patients.

Abstract Machine learning-assisted modeling of the inter-atomic potential energy surface (PES) is revolutionizing the field of molecular simulation. With the accumulation of high-quality electronic structure data, a model that can be pretrained on all available data and finetuned on downstream tasks with a small additional effort would bring the field to a new stage. Here we propose DPA-1, a Deep Potential model with a gated attention mechanism, which is highly effective for representing the conformation and chemical spaces of atomic systems and learning the PES. We tested DPA-1 on a number of systems and observed superior performance compared with existing benchmarks. When pretrained on large-scale datasets containing 56 elements, DPA-1 can be successfully applied to various downstream tasks with a great improvement of sample efficiency. Surprisingly, for different elements, the learned type embedding parameters form a s p i r a l in the latent space and have a natural correspondence with their positions on the periodic table, showing interesting interpretability of the pretrained DPA-1 model.

The technology of CO2-enhanced coalbed methane (CO2-ECBM) can reduce greenhouse gas emissions, and has the function of clean energy production and environmental protection. In order to study the drainage and production laws of CH4 production by CO2 injection in water-bearing coal seams under gas-water two-phase flow conditions, as well as the effects of different initial water saturation and CO2 injection conditions on CH4 production, CO2 storage, and reservoir permeability. A coupled fluid-solid-thermal model for competitive adsorption, temperature changes, coal deformation, and water transport was constructed. The high accuracy of the model was demonstrated by comparing with the field data, existing experiments and numerical solutions of existing model, and the advantages of the model were specified. CO2-ECBM numerical simulation were subsequently carried out using COMSOL. The results shown that, CO2 injection can enhance the rate and amount of CH4 production, which indicated the feasibility of CO2 injection to increase production. With the continuous CO2 injection, the CH4 concentration in the reservoir decreased, the CO2 concentration increased, the temperature near the gas injection well increased, the temperature near the production well decreased and the temperature from the gas injection well to the production well slowly decreased. Water phase relative permeability gradually decreased and gas phase relative permeability gradually increased during gas injection and extraction period. Due to the combined effect of effective stress and matrix shrinkage/expansion, the reservoir permeability exhibited a trend of “decrease-increase-decrease”. The higher the initial water saturation of the coal seam, the lower the CH4 production and the lower the permeability decrease. The maximum decrease in cumulative CH4 production was 15.19%. Ignoring the impact of water in coal seams can overestimate CH4 production, and the impact of coal seam water should be considered in numerical simulation. The higher the CO2 injection temperature and pressure, the greater the CH4 production and the greater the permeability decrease. The cumulative CH4 production increased by 13.27% and 39.77%, and permeability decreased by 20.4% and 46.14%, respectively. Increasing the CO2 injection temperature and pressure was conducive to increase CH4 production.

Abstract Gas separation is crucial for industrial production and environmental protection, with metal-organic frameworks (MOFs) offering a promising solution due to their tunable structural properties and chemical compositions. Traditional simulation approaches, such as molecular dynamics, are complex and computationally demanding. Although feature engineering-based machine learning methods perform better, they are susceptible to overfitting because of limited labeled data. Furthermore, these methods are typically designed for single tasks, such as predicting gas adsorption capacity under specific conditions, which restricts the utilization of comprehensive datasets including all adsorption capacities. To address these challenges, we propose Uni-MOF, an innovative framework for large-scale, three-dimensional MOF representation learning, designed for multi-purpose gas prediction. Specifically, Uni-MOF serves as a versatile gas adsorption estimator for MOF materials, employing pure three-dimensional representations learned from over 631,000 collected MOF and COF structures. Our experimental results show that Uni-MOF can automatically extract structural representations and predict adsorption capacities under various operating conditions using a single model. For simulated data, Uni-MOF exhibits remarkably high predictive accuracy across all datasets. Additionally, the values predicted by Uni-MOF correspond with the outcomes of adsorption experiments. Furthermore, Uni-MOF demonstrates considerable potential for broad applicability in predicting a wide array of other properties.

In computer-aided drug discovery, accurately determining the structure and properties of drug-like molecules is of utmost importance. This necessitates the use of precise and efficient electronic structure methods. Here, we developed two deep learning-based density functional methods, namely DeePHF and DeePKS, specifically tailored for drug-like molecules. Notably, DeePKS incorporates self-consistency into its framework. With a limited dataset labelled at the CCSD(T)/def2-TZVP level, both models have been able to achieve chemical accuracy in calculating molecular energies and have demonstrated excellent transferability. We anticipate that further advancements in this field will lead to the development of high-quality density functional methods designed specifically for drug discovery purposes. This research showcases the capabilities of deep learning approaches in simplifying the construction complexity associated with traditional DFT methods.

Abstract The constant emergence of SARS-CoV-2 variants continues to impair the efficacy of existing neutralizing antibodies, especially XBB.1.5 and EG.5, which showed exceptional immune evasion properties. Here, we identify a highly conserved neutralizing epitope targeted by a broad-spectrum neutralizing antibody BA7535, which demonstrates high neutralization potency against not only previous variants, such as Alpha, Beta, Gamma, Delta and Omicron BA.1-BA.5, but also more recently emerged Omicron subvariants, including BF.7, CH.1.1, XBB.1, XBB.1.5, XBB.1.9.1, EG.5. Structural analysis of the Omicron Spike trimer with BA7535-Fab using cryo-EM indicates that BA7535 recognizes a highly conserved cryptic receptor-binding domain (RBD) epitope, avoiding most of the mutational hot spots in RBD. Furthermore, structural simulation based on the interaction of BA7535-Fab/RBD complexes dissects the broadly neutralizing effect of BA7535 against latest variants. Therapeutic and prophylactic treatment with BA7535 alone or in combination with BA7208 protected female mice from the circulating Omicron BA.5 and XBB.1 variant infection, suggesting the highly conserved neutralizing epitope serves as a potential target for developing highly potent therapeutic antibodies and vaccines.

Purpose: Chronic wounds that are difficult to heal pose a major challenge for clinicians and researchers. Currently, common treatment methods focus on isolating the wound from the outside world, relying on the tissue at the wound site to grow and heal unaided. Umbilical cord mesenchymal stem cell (MSC) exosomes can promote wound healing by enhancing new blood vessel growth at the wound site. Valproic acid (VPA) reduces the inflammatory response and acts on macrophages to accelerate wound closure. In this study, VPA was loaded into umbilical cord MSC exosomes to form a drug carrier exosome (VPA-EXO) with the aim of investigating the effect of VPA-EXO on wound healing. Methods: This study first isolated and obtained umbilical cord MSC exosomes, then added VPA to the exosomes and explored the ability of VPA-EXO to promote the proliferation and migration of human skin fibroblasts (HSFs) and human umbilical vein endothelial cells (HUVECs), as well as the ability to promote the angiogenesis of HUVECs, by using scratch, Transwell, and angiogenesis assays. An in vitro cell model was established and treated with VPA-EXO, and the expression levels of inflammation and pro-angiogenesis-related proteins and genes were examined using Western blot and qRT-PCR. The therapeutic effect of VPA-EXO on promoting wound healing in a whole skin wound model was investigated using image analysis of the wound site, H&E staining, and immunohistochemical staining experiments in a mouse wound model. Results: The in vitro model showed that VPA-EXO effectively promoted the proliferation and migration of human skin fibroblast cells and human umbilical vein endothelial cells; significantly inhibited the expression of MMP-9, IL-1β, IL-8, TNF-α, and PG-E2; and promoted the expression of vascular endothelial growth factors. In the mouse wound model, VPA-EXO reduced inflammation at the wound site, accelerated wound healing, and significantly increased the collagen content of tissue at the wound site. Conclusions: As a complex with dual efficacy in simultaneously promoting tissue regeneration and inhibiting inflammation, VPA-EXO has potential applications in tissue wound healing and vascular regeneration. In future studies, we will further investigate the mechanism of action and application scenarios of drug-loaded exosome complexes in different types of wound healing and vascular regeneration.

The COVID-19 pandemic has left a profound impact on higher education, prompting the need to assess its effects and provide guidance for future pandemics or disasters. While previous research has often focused on individual courses and short-term consequences, there is a limited understanding of the broader college experience. This study conducts a comparative analysis of graduate performance throughout different phases of the COVID-19 pandemic, utilizing a Graduate Learning Experience questionnaire with a five-point Likert scale. Scores for graduate attribute items were collected and compared across three distinct phases: pre-pandemic, pandemic era, and post-pandemic. The results reveal significant shifts in the student learning experience during these timeframes, with notable differences between on-campus and off-campus learners concerning their learning environments. The study also examines the reasons behind these variations, particularly among students living in on-campus hostels versus those off-campus. Additionally, it assesses the university’s response to the pandemic’s adverse effects and evaluates the effectiveness of these response measures. These findings offer valuable insights into the factors influencing graduate attributes in the context of online learning, with a specific focus on Hong Kong. They also provide policy recommendations for shaping the future of higher education in the aftermath of pandemics or disasters. Furthermore, these results can serve as a guiding framework for addressing similar challenges in other regions dealing with post-disaster recovery.

The scale of the cosmetic market is increasing every day. There are many safety risks to cosmetics, but they benefit people at the same time. The skin can become red, swollen, itchy, chronically toxic, and senescent due to the misuse of cosmetics, triggering skin injuries, with contact dermatitis being the most common. Therefore, there is an urgent need for a system that can scientifically and rationally detect the composition and perform a toxicological assessment of cosmetic products. Traditional detection methods rely on instrumentation and method selection, which are less sensitive and more complex to perform. Engineered skin tissue has emerged with the advent of tissue engineering technology as an emerging bioengineering technology. The ideal engineered skin tissue is the basis for building good in vitro structures and physiological functions in this field. This review introduces the existing cosmetic testing and toxicological evaluation methods, the current development status, and the types and characteristics of engineered skin tissue. The application of engineered skin tissue in the field of cosmetic composition detection and toxicological evaluation, as well as the different types of tissue engineering scaffold materials and three-dimensional (3D) organoid preparation approaches, is highlighted in this review to provide methods and ideas for constructing the next engineered skin tissue for cosmetic raw material component analysis and toxicological evaluation.

Abstract Background Previous studies have investigated the association between cardiometabolic risk factors and cardiovascular disease (CVD), but evidence of the attributable burden of individual and combined cardiometabolic risk factors for CVD and mortality is limited. We aimed to investigate and quantify the associations and population attributable fraction (PAF) of cardiometabolic risk factors on CVD and all-cause mortality, and calculate the loss of CVD-free years and years of life lost in relation to the presence of cardiometabolic risk factors. Methods Twenty-two thousand five hundred ninety-six participants aged ≥ 35 without CVD at baseline were included between October 2012 and December 2015. The outcomes were the composite of fatal and nonfatal CVD events and all-cause mortality, which were followed up in 2018 and 2019 and ascertained by hospital records and death certificates. Cox regression was applied to evaluate the association of individual and combined cardiometabolic risk factors (including hypertension, diabetes and high low-density lipoprotein cholesterol (LDL-C)) with CVD risk and all-cause mortality. We also described the PAF for CVD and reductions in CVD-free years and life expectancy associated with different combination of cardiometabolic conditions. Results During the 4.92 years of follow-up, we detected 991 CVD events and 1126 deaths. Hazard ratio were 1.59 (95% confidential interval (CI) 1.37–1.85), 1.82 (95%CI 1.49–2.24) and 2.97 (95%CI 1.85–4.75) for CVD and 1.38 (95%CI 1.20–1.58), 1.66 (95%CI 1.37–2.02) and 2.97 (95%CI 1.88–4.69) for all-cause mortality, respectively, in participants with one, two or three cardiometabolic risk factors compared with participants without diabetes, hypertension, and high LDL-C. 21.48% of CVD and 15.38% of all-cause mortality were attributable to the combined effect of diabetes and hypertension. Participants aged between 40 and 60 years old, with three cardiometabolic disorders, had approximately 4.3-year reductions life expectancy compared with participants without any abnormalities of cardiometabolic disorders. Conclusions Cardiometabolic risk factors were associated with a multiplicative risk of CVD incidence and all-cause mortality, highlighting the importance of comprehensive management for hypertension, diabetes and dyslipidemia in the prevention of CVD.

Accurate positioning is the necessary basis for autonomous underwater vehicles (AUV) to perform safe navigation in underwater tasks, such as port environment monitoring, target search, and seabed exploration. The position estimates of underwater navigation systems usually suffer from an error accumulation problem, which makes the AUVs difficult use to perform long-term and accurate underwater tasks. Underwater simultaneous localization and mapping (SLAM) approaches based on multibeam-bathymetric data have attracted much attention for being able to obtain error-bounded position estimates. Two problems limit the use of multibeam bathymetric SLAM in many scenarios. The first is that the loop closures only occur in the AUV path intersection areas. The second is that the data association is prone to failure in areas with gentle topographic changes. To overcome these problems, a joint graph-based underwater SLAM approach that fuses bathymetric and magnetic-beacon measurements is proposed in this paper. In the front-end, a robust dual-stage bathymetric data-association method is used to first detect loop closures on the multibeam bathymetric data. Then, a magnetic-beacon-detection method using Euler-deconvolution and optimization algorithms is designed to localize the magnetic beacons using a magnetic measurement sequence on the path. The loop closures obtained from both bathymetric and magnetic-beacon observations are fused to build a joint-factor graph. In the back-end, a diagnosis method is introduced to identify the potential false factors in the graph, thus improving the robustness of the joint SLAM system to outliers in the measurement data. Experiments based on field bathymetric datasets are performed to test the performance of the proposed approach. Compared with classic bathymetric SLAM algorithms, the proposed algorithm can improve the data-association accuracy by 50%, and the average positioning error after optimization converges to less than 10 m.

Abstract Background Air pollution is a growing public health concern of global significance. Till date, few studies have explored the associations between air pollutants and cardiac imaging phenotypes. In this study, we aim to explore the association of ambient air pollution and abnormal left ventricular diastolic function (ALVDF) among a large-scale free-living population. Methods The participants were from a national representative large-scale cross-sectional study, i.e., the China Hypertension Survey (CHS), 2012–15. After exclusion, 25,983 participants from 14 provinces and 30 districts in China were included for the final analysis. The annual average ambient PM2.5, PM10 and NO2 concentrations were obtained from the chemical data assimilation system (ChemDAS). The clinical evaluation of left ventricular function was conducted in the survey field which was based on echocardiography. Grading diastolic dysfunction was based on Recommendations for the evaluation of left ventricular diastolic function by echocardiography (2009). Results The mean age of 25,983 participants was 56.8 years, 46.5% were male, and the crude prevalence of GradeI-III ALVDF were 48.1%, 1.6% and 1.1%, respectively. The ORs (95% CI) for ALVDF in the fully adjusted model were 1.31 (1.11–1.56), 1.11 (1.01–1.21) and 1.18 (0.90–1.54) for an increase of 10 μg/m3 of PM2.5, PM10 and NO2, respectively. And for different grades of ALVDF, elevated concentration of PM2.5 and PM10 exposures significantly increased the risk of gradeIinstead of gradeII ~ III ALVDF. There was a positive linear and “J” shape concentration–response association between annual average ambient PM2.5 and NO2 and the ALVDF risk assessed by the restricted cubic spline. The exposure level of most participants to PM10 was less than 130 μg/m3, and the risk of ALVDF increased significantly with the concentration rise. Conclusions This large-scale nationwide population study demonstrated a significantly positive association between ambient PM2.5, PM10 and NO2 with ALVDF, especially for mild ALVDF. The functional abnormality may partially explain the enhanced cardiovascular morbidity and mortality associated with air pollution, which highlights the importance of appropriate interventions to reduce ambient air pollution in China.

Abstract Background A workplace-based primary prevention intervention be an effective approach to reducing the incidence of hypertension (HTN). However, few studies to date have addressed the effect among the Chinese working population. We assessed the effect of a workplace-based multicomponent prevention interventions program for cardiovascular disease on reducing the occurrence of HTN through encouraging employees to adopt a healthy lifestyle. Methods In this post hoc analysis of cluster randomized controlled study, 60 workplaces across 20 urban regions in China were randomized to either the intervention group (n = 40) or control group (n = 20). All employees in each workplace were asked to complete a baseline survey after randomization for obtaining sociodemographic information, health status, lifestyle, etc. Employees in the intervention group were given a 2-year workplace-based primary prevention intervention program for improving their cardiovascular health, including (1) cardiovascular health education, (2) a reasonable diet, (3) tobacco cessation, (4) physical environment promotion, (5) physical activity, (6) stress management, and (7) health screening. The primary outcome was the incidence of HTN, and the secondary outcomes were improvements of blood pressure (BP) levels and lifestyle factors from baseline to 24 months. A mix effect model was used to assess the intervention effect at the end of the intervention in the two groups. Results Overall, 24,396 participants (18,170 in the intervention group and 6,226 in the control group) were included (mean [standard deviation] age, 39.3 [9.1] years; 14,727 men [60.4%]). After 24 months of the intervention, the incidence of HTN was 8.0% in the intervention groups and 9.6% in the control groups [relative risk (RR) = 0.66, 95% CI, 0.58 ~ 0.76, P

Abstract Formamidine lead triiodide (FAPbI3) perovskites have attracted increasing interest for photovoltaics attributed to the optimal bandgap, high thermal stability, and the record power conversion efficiency (PCE). However, the materials still face several key challenges, such as phase transition, lattice defects, and ion migration. Therefore, external ions (e.g., cesium ions (Cs+)) are usually introduced to promote the crystallization and enhance the phase stability. Nevertheless, the doping of Cs+ into the A‐site easily leads to lattice compressive strain and the formation of pinholes. Herein, trioctylphosphine oxide (TOPO) is introduced into the precursor to provide tensile strain outside the perovskite lattice through intermolecular forces. The special strain compensation strategy further improves the crystallization of perovskite and inhibits the ion migration. Moreover, the TOPO molecule significantly passivates grain boundaries and undercoordinated Pb2+ defects via the forming of P═O─Pb bond. As a result, the target solar cell devices with the synergistic effect of Cs+ and TOPO additives have achieved a significantly improved PCE of 22.71% and a high open‐circuit voltage of 1.16 V (voltage deficit of 0.36 V), with superior stability under light exposure, heat, or humidity conditions.

Reducing transportation-related carbon dioxide (CO2) emissions in China poses significant challenges due to the sector’s growth potential and variations among provinces and transportation modes. This study utilizes the bottom-up approach and the Logarithmic Mean Divisia Index (LMDI) decomposition method to calculate transportation CO2 emissions and explores the temporal-spatial differences across Chinese provinces. The results reveal that national transportation CO2 emissions increased by 50.14% from 2010 to 2019, and emissions from private cars present the fastest growth among all transportation modes by 254% over the decade. Spatially, higher emissions are found in eastern provinces, and neighboring provinces notably distinguish from each other in terms of the emission proportion of different modes and the factor analysis from LMDI. Regarding the heterogeneity of the spatial emission characteristics, a cluster-based evaluation method is proposed for the 31 provinces according to the emission structure and the LMDI decomposition. Four clusters are derived, each featuring varied emission distribution and driving factors. Correspondingly, policy recommendations are proposed to address the characteristics of each cluster, such as controlling car ownership, promoting integrated transport modes, improving fuel economy, and electrifying urban transportation services. The cluster-based analysis method can provide more specific suggestions to province targeting its emission characteristics rather than its location, which is one of the major contributions of this study.

Herein, the NiFe2O4/CeO2 composite photocatalysts were successfully synthesized via a facile one-pot hydrothermal method. We found that the one-pot synthesized composite photocatalysts exhibited better photocatalytic degradation performance than sole photocatalyst or conventional hand ground composite photocatalyst under visible light irradiation, and the degradation efficiency of methylene blue for the one-pot photocatalyst with 10% CeO2 reached 82% in 10 h. The enhanced photocatalytic degradation performance can be explained by the improved adsorption and charge transfer of the reaction site induced by the CeO2 phase. This study can guide the development of alternative photocatalyst for photocatalytic degradation of wastewater.

One-part geopolymer is a single-component, easy-to-use geopolymer material that offers simplified and cost-effective production processes for eco-friendly building materials. This study aimed to optimize the thermal and mechanical properties of one-part geopolymer for geothermal energy applications by incorporating both silicon carbide (SiC) sand and SiC powder. Various mix designs of one-part geopolymer composites were investigated, and their flexural and compressive strength were analysed. Thermal conductivity was measured using a novel home-made test set-up. Results showed that the compressive strength of one-part geopolymer composite can be as high as 83 MPa under ambient curing condition. The relationship between flexural and compressive strength was also studied, with the PCA code providing the best fitting precision. Furthermore, the thermal conductivity of one-part geopolymer composite was significantly increased with the combined application of SiC powder and SiC particles. These findings suggest that geopolymer composites with SiC materials are suitable for geothermal energy applications.

Introduction: Although physical activity (PA) has multiple health benefits, the inhaled dose of fine particulate matter (PM2.5) during PA may increase. The trade-off between harmful effects of PM2.5 exposure and protective effects of PA remain unclear. Our study aims to examine the joint effects of PA and PM2.5 exposure on blood pressure (BP) in Chinese adults. Methods: A total of 203,108 adults aged ≥ 18 years from the China Hypertension Survey study (2012–2015) were included. Individual-level PA was assessed as minutes of metabolic equivalent tasks per week (MET-min/week). The average weekly PM2.5 exposures were estimated by using a spatial resolution of 10 km, integrating multiple data sources, including monitoring values, satellite measurements and model simulations. BP was measured with a professional portable BP monitor. Generalized linear regressions were used to estimate joint associations and to further explore two-dimensional nonlinear associations. Results: The median PA and 4-week PM2.5 average exposures were 3213.0 MET-min/week and 47.8 μg/m3, respectively. PA was negatively associated with BP, while PM2.5 exposure was positively with BP. The associations between PA and systolic BP were significantly modified by PM2.5 exposure (P interaction < 0.001). Compared with inactive participants under low PM2.5 exposure, those with highest level of PA under low PM2.5 exposure had a 0.90 (95 % CI: 0.53, 1.26) mmHg decrease in systolic BP, whereas they had a 0.48 (95 % CI: 0.07, 0.89) mmHg increase under high PM2.5 exposure. When PM2.5 exposure was approximately > 25 μg/m3, the joint exposure to total PA and PM2.5 was associated with an increase in systolic BP. Conclusions: The benefits of PA on BP were counteracted by high PM2.5 levels.

Abstract Histone modifications play critical roles in regulating gene expression and present dynamic changes during early embryo development. However, how they are reprogrammed during human prenatal germline development has not yet been elucidated. Here, we map the genome-wide profiles of three key histone modifications in human primordial germ cells (hPGCs) from weeks 8 to 23 of gestation for the first time by performing ULI-NChIP-seq. Notably, H3K4me3 exhibits a canonical promoter-enriched pattern, though with relatively lower enrichment, and is positively correlated with gene expression in globally hypomethylated hPGCs. In addition, H3K27me3 presents very low enrichment but plays an important role in not only dynamically governing specific bivalent promoters but also impeding complete X chromosome reactivation in female hPGCs. Given the activation effects of both global DNA demethylation and H3K4me3 signals, repressive H3K9me3 and H3K27me3 marks are jointly responsible for the paradoxical regulation of demethylation-resistant regions in hPGCs. Collectively, our results provide a unique roadmap of three core histone modifications during hPGC development, which helps to elucidate the architecture of germ cell reprogramming in an extremely hypomethylated DNA environment.

Abstract Background Metabolic syndrome (MetS) is characterized by a cluster of signs of metabolic disturbance and has caused a huge burden on the health system. The study aims to explore the prevalence and characteristics of MetS defined by different criteria in the Chinese population. Methods Using the data of the China Hypertension Survey (CHS), a nationally representative cross-sectional study from October 2012 to December 2015, a total of 28,717 participants aged 35 years and above were included in the analysis. The MetS definitions of the International Diabetes Federation (IDF), the updated US National Cholesterol Education Program Adult Treatment Panel III (the revised ATP III), and the Joint Committee for Developing Chinese Guidelines (JCDCG) on Prevention and Treatment of Dyslipidemia in Adults were used. Multivariable logistic regression was used to identify factors associated with MetS. Results The prevalence of MetS diagnosed according to the definitions of IDF, the revised ATP III, and JCCDS was 26.4%, 32.3%, and 21.5%, respectively. The MetS prevalence in men was lower than in women by IDF definition (22.2% vs. 30.3%) and by the revised ATP III definition (29.2% vs. 35.4%), but the opposite was true by JCDCG (24.4%vs 18.5%) definition. The consistency between the three definitions for men and the revised ATP III definition and IDF definition for women was relatively good, with kappa values ranging from 0.77 to 0.89, but the consistency between the JCDCG definition and IDF definition (kappa = 0.58) and revised ATP III definition (kappa = 0.58) was poor. Multivariable logistic regression showed that although the impact and correlation intensity varied with gender and definition, area, age, education, smoking, alcohol use, and family history of cardiovascular disease were factors related to MetS. Conclusions The prevalence and characteristics of the MetS vary with the definition used in the Chinese population. The three MetS definitions are more consistent in men but relatively poor in women. On the other hand, even if estimated according to the definition of the lowest prevalence, MetS is common in China.

Abstract We report on an extensive study of the viscosity of liquid water at near-ambient conditions, performed within the Green-Kubo theory of linear response and equilibrium ab initio molecular dynamics (AIMD), based on density-functional theory (DFT). In order to cope with the long simulation times necessary to achieve an acceptable statistical accuracy, our ab initio approach is enhanced with deep-neural-network potentials (NNP). This approach is first validated against AIMD results, obtained by using the Perdew–Burke–Ernzerhof (PBE) exchange-correlation functional and paying careful attention to crucial, yet often overlooked, aspects of the statistical data analysis. Then, we train a second NNP to a dataset generated from the Strongly Constrained and Appropriately Normed (SCAN) functional. Once the error resulting from the imperfect prediction of the melting line is offset by referring the simulated temperature to the theoretical melting one, our SCAN predictions of the shear viscosity of water are in very good agreement with experiments.

Abstract This study intended to compare the prevalence of hypertension in adolescents aged 15–17 years in China according to different criteria defined by various guidelines. We included 28 715 adolescents aged 15–17 years from the China Hypertension Survey study (CHS) 2012–2015, and the 2017 American Association of Pediatrics (AAP) Clinical Practice Guideline and 2018 Chinese guidelines for children and adults were used to define hypertension. The prevalence of hypertension among Chinese adolescents aged 15–17 years was 24.4% according to the 2018 Chinese guidelines for children; the corresponding values were 18.6% according to the 2017 AAP Guidelines, and 3.5% according to 2018 Chinese guidelines for adults. The age‐specific prevalence of hypertension in the age of 15, 16, and 17 years in the same population was 26.2%, 24.4%, and 23.3% according to 2018 Chinese guidelines for children; 18.8%, 17.9%, and 19.2% as per the 2017 AAP Guidelines; 3.4%, 3.4%, and 3.6% as per the 2018 Chinese guidelines for adults. A highest prevalence of hypertension was observed according to 2018 Chinese guidelines for children than the other two guidelines. Compared with the 2018 Chinese guidelines for children, a higher 95th percentile BP (systolic and diastolic) was also observed in the present study in each gender‐age‐height‐specific group. And the height, which was key factor to influence blood pressure, was similar between adolescents aged 15–17 and adults, and a paralleled result was seen in the present study. Therefore, the 2018 Chinese guidelines for adults may also be appropriate for adolescents aged 15–17 years.

In the context of the relentless evolution of network and communication technologies, the need for enhanced communication content and quality continues to escalate. Addressing the demands of data collection from the abundance of terminals within Internet of Things (IoT) scenarios, this paper presents an advanced approach to multi-Unmanned Aerial Vehicle (UAV) data collection and path planning tailored for extensive terminal accessibility. This paper focuses on optimizing the complex interplay between task completion time and task volume equilibrium. To this end, a novel strategy is devised that integrates sensor area partitioning and flight trajectory planning for multiple UAVs, forming an optimization framework geared towards minimizing task completion duration. The core idea of this work involves designing an innovative k-means algorithm capable of balancing data quantities within each cluster, thereby achieving balanced sensor node partitioning based on data volume. Then, the UAV flight trajectory paths are discretely modeled, and a grouped, improved genetic algorithm is used to solve the Multiple Traveling Salesman Problem (MTSP). The algorithm introduces a 2-opt optimization operator to improve the computational efficiency of the genetic algorithm. Empirical validation through comprehensive simulations clearly underscores the efficacy of the proposed approach. In particular, the method demonstrates a remarkable capacity to rectify the historical issue of diverse task volumes among multiple UAVs, all the while significantly reducing task completion times. Moreover, its convergence rate substantially outperforms that of the conventional genetic algorithm, attesting to its computational efficiency. This paper contributes an innovative and efficient paradigm to improve the problem of data collection from IoT terminals through the use of multiple UAVs. As a result, it not only augments the efficiency and balance of task distribution but also showcases the potential of tailored algorithm solutions for realizing optimal outcomes in complex engineering scenarios.

Abstract Large scale atomistic simulations provide direct access to important materials phenomena not easily accessible to experiments or quantum mechanics-based calculation approaches. Accurate and efficient interatomic potentials are the key enabler, but their development remains a challenge for complex materials and/or complex phenomena. Machine learning potentials, such as the Deep Potential (DP) approach, provide robust means to produce general purpose interatomic potentials. Here, we provide a methodology for specialising machine learning potentials for high fidelity simulations of complex phenomena, where general potentials do not suffice. As an example, we specialise a general purpose DP method to describe the mechanical response of two allotropes of titanium (in addition to other defect, thermodynamic and structural properties). The resulting DP correctly captures the structures, energies, elastic constants and γ-lines of Ti in both the HCP and BCC structures, as well as properties such as dislocation core structures, vacancy formation energies, phase transition temperatures, and thermal expansion. The DP thus enables direct atomistic modelling of plastic and fracture behaviour of Ti. The approach to specialising DP interatomic potential, DPspecX, for accurate reproduction of properties of interest “X”, is general and extensible to other systems and properties.

ObjectiveBlue sky has been considered to boost outdoor physical activity and social interaction, ameliorate work pressure and life stress, and enhance people's sense of happiness. However, the direct association between blue sky exposure and cardiovascular disease (CVD) still lacks epidemiological evidence. In this study, we aimed to quantify their relationship via a nationwide prospective cohort in China.MethodWe extracted the baseline data from the China Hypertension Survey (CHS), by enrolling 22,702 participants aged ≥ 35 years without self-reported medical history of CVD from 14 provinces of China between 2012 and 2015 and followed up from 2018 to 2019. A blue day was marked out with no rain, low cloud cover ≤ climatological mean at each station, and visibility at 2 pm ≥ 21.52 km. We calculated the number of blue days at baseline survey year to evaluate the chronic individual blue day exposure. Cox proportional hazards models were employed to calculate the multivariable-adjusted hazard ratio (HR). We implemented subgroup analyses as well to identify potential effect modifications.ResultsA total of 1,096, 993, and 597 incident cases of all-cause mortality, fatal or nonfatal CVD, and stroke occurred during a median follow-up around 5 years, respectively. A 10-day increase in annual blue day exposure was associated with a 3% (95% confidence interval [CI]: 1–6%) and 7% (95% CI: 5–10%) decreased risk of fatal or nonfatal CVD and stroke, respectively. Compared with those exposed to the worst tertile of blue days at baseline, subjects who exposed to the best tertile had a 32% (95% CI: 19–43%) and 43% (95% CI: 29–55%) lower likelihood of developing fatal or nonfatal CVD and stroke, respectively. Negative consistent exposure–response relationships were generally observed between them in the restricted cubic spline model. In the stratified analyses, the cardioprotective effects of blue sky were stronger for females, rural residents, and individuals residing in heavily contaminated areas.ConclusionThis study indicates that blue sky may serve as an independent environmental protective factor against CVD, and informs future policies on fighting air pollution and protecting the blue sky in China.

BackgroundAt present, the association between age at menarche and menopause, reproductive lifespan, and cardiovascular disease (CVD) risk among Chinese postmenopausal women is not clear, and some related researches are contradictory.MethodsA total of 6,198 Chinese postmenopausal women with a mean age of 63.6 years were enrolled at baseline in 2012–2015 and followed up for 5 years. A standardized questionnaire was used to collect relevant information by well-trained interviewers. Physical examination of the participants was performed by trained medical staff. CVD events were observed during follow-up. Cox proportional hazards models were used to estimate hazard ratios between reproductive characteristics and CVD events.ResultsAge at menarche was positively associated with CVD events (HR, 1.106; 95%CI, 1.047–1.167). There was a negative association between age at menopause and CVD risk in postmenopausal women with comorbidity (HR, 0.952; 95%CI, 0.909–0.996). Reproductive lifespan was negatively associated with CVD events (HR, 0.938; 95%CI, 0.880–0.999). The CVD risk increased by 10.6% for every 1-year increase in age at menarche. The CVD risk reduced by 6.2% for every 1-year increase in age at menopause in women with comorbidity. The CVD risk reduced by 3.8% for every 1-year increase in reproductive lifespan.ConclusionsBased on the large prospective study with a nationally representative sample, Chinese postmenopausal women with late age at menarche and shorter reproductive lifespan have higher risk of CVD events.

Abstract This study explored the association between age at menarche and the risk of hypertension in Chinese women. A total of 234 867 women aged ≥18 years from the China Hypertension Survey were included in this study. Participants were required to complete a standard questionnaire. Blood pressure and physical examination of the participants were performed by trained medical staff. Spearman correlation analysis was used to explore the correlation between age at menarche and other individual characteristics. Logistic regression was used to estimate the odds ratios for hypertension by age in years at menarche. The average age at menarche in Chinese women was 14.8 years. Women who were older at menarche were more likely to have a higher body mass index, larger waist circumference, smoke, and have a primary education (p

Abstract Background The epidemiology of valvular heart disease (VHD) has changed markedly over the last 50 years worldwide, and the prevalence and features of VHD in China are unknown. The objective of this study was to investigate the current status and etiology of VHD in China. Methods We used a cross-sectional national survey with stratified multistage random sampling from the general Chinese population to estimate the VHD burden. Data on demographic characteristics, medical history, physical examination, blood tests, and potential etiology were collected. Echocardiography was used to detect VHD. Results The national survey enrolled 34,994 people aged 35 years or older across China. Overall, 31,499 people were included in the final analysis, and 1309 participants were diagnosed with VHD. The weighted prevalence was 3.8%, with an estimated 25 million patients in China. The prevalence of VHD increased with age and was higher in participants with hypertension or chronic kidney disease than in their counterparts. Among participants with VHD, 55.1% were rheumatic and 21.3% were degenerative. The proportion of rheumatic decreased with age, and the proportion of degenerative rose with age. However, the prevalence of rheumatic disease was still higher in the elderly population than in the younger population. Logistic regression revealed that age and hypertension were correlated with VHD. Conclusions In China, rheumatic heart disease was still the major cause of the VHD, with a significant increase in degenerative heart disease. Age and hypertension are important and easily identifiable markers of VHD.

BackgroundThe association between reproductive lifespan and risk of hypertension among postmenopausal women is unclear.MethodsA total of 94,141 postmenopausal women with a mean age of 64.8 years from the China Hypertension Survey were enrolled at baseline from 2012 to 2015. A standardized questionnaire was used to collect relevant information by well-trained interviewers. Blood pressure and physical examination of the participants were performed by trained medical staff. Logistic regression was used to estimate the odds ratios for hypertension by years of reproductive lifespan.ResultsThe average years of reproductive lifespan in Chinese women was 34.0 years. Women who were longer in reproductive lifespan were more likely to have older age at recruitment, higher body mass index, larger waist circumference, lower mean systolic blood pressure, and higher mean diastolic blood pressure (p < 0.05). After adjustments, odds ratios (95% confidence interval) for hypertension were 1.035 (0.988–1.085), 1.007 (0.966–1.048), 1.000 (reference), 0.932 (0.899–0.967), and 0.953 (0.909–0.997) for those with reproductive lifespan at ≤ 28, 29–31, 32–34 (reference), 35–37, and ≥ 38 years, respectively, with a significantly inverse association was seen in those with reproductive lifespan at 35–37 and ≥ 38 years. The overall risk of hypertension declined with the increase in reproductive lifespan, and the risk of hypertension was reduced by 1.1% for every 1-year increase in the reproductive lifespan (odds ratio, 0.989; 95% confidence interval, 0985–0.994) per year. The negative association between reproductive lifespan and hypertension was evident among age at recruitment groups, body mass index categories, and education levels, with the strongest association among women aged ≥ 70 years. Positive associations between reproductive lifespan and risk of hypertension were evident among women aged < 60 years, and this association was stronger among current alcohol drinkers.ConclusionBased on the large nationally representative sample, Chinese postmenopausal women with a shorter reproductive lifespan have a higher risk of hypertension.

A combined preparation of SO2 and recovery of solid products was investigated as a hazard-free method to use coke as a reducer to treat electrolytic manganese residue (EMR) at high temperature. In this study, the response surface prediction and thermodynamic analysis of the high-temperature calcination of EMR were evaluated. In addition, the effects of mole ratio of EMR to coke and temperature on the gas–solid phase and the feasibility of calcined solid products as cement raw materials were also studied. The results showed that the release of sulfur from EMR mainly depends on the mole ratio of EMR to coke and temperature. The best condition for preparing SO2 was EMR calcined for 60 min at 1000 °C and the molar ratio of C:CaSO4 = 0.78:1. At this time, the volume fraction of SO2 reached 7.6%, which meets the requirements for preparing sulfuric acid with SO2. Under this condition, the sulfur in desulfurization manganese residue (DMR) was reduced to 0.38%, and DMR was used as cement raw material to prepare cement. The cement prepared by adding 10% DMR meets the national standard GB175. The method realized the recovery of sulfur in EMR and calcined solid products and promoted the resource utilization of EMR.

With the acceleration of 5G global commercial deployment process,various emerging immersive network applications represented by holographic communication have put forward significant requirements and tests on the structure and capability of the existing network architecture.The wide application of holographic communication services in many fields was introduced,and the current situation was analyzed that 5G network can not meet the rapid development needs of holographic immersion applications.The performance requirements of holographic communication applications in bandwidth,delay,computing power,synchronization,quality of service,reliability,security and other aspects of the future network performance were analyzed.The application scenarios and key technologies of holographic communication were summarized.Through the investigation and analysis of the possible evolution routes of the future network,the direction of the future network evolution and development was pointed out.

PurposeThe National Essential Public Health Services Package (NEPHSP), a set of community-based hypertension management programs, was launched by the Chinese government in 2009. However, the data are limited for the comprehensive evaluation of NEPHSP on hypertension management. This study was to estimate the effect of NEPHSP on hypertension control nationwide in China.MethodsData were from China Hypertension Survey (CHS). The participants (n = 119,412) aged ≥35 years with hypertension were included in the analysis. Further, a subset of 64,188 diagnosed hypertensive patients were analyzed to evaluate the effect of NEPHSP by comparing the ones covered and not covered by NEPHSP. Blood pressure (BP) was measured by trained staff using a validated digital portable monitor in local communities or clinics.ResultsAmong adults aged ≥35 years with hypertension, the coverage of NEPHSP was 25.6% and increased with age. The coverage was significantly higher in women than in men (P < 0.001). Among the 64, 188 diagnosed hypertensive patients, compared to the control group (not covered by NEPHSP), the mean systolic and diastolic BPs were 2 mmHg and 1.6 mmHg lower in NEPHSP group, respectively. The rate of treatment for hypertension was significantly higher in NEPHSP group than the control group (93.0% vs. 81.4%, P < 0.001), and the rate of BP control was also significantly higher in NEPHSP group than the control group (35.9% vs. 29.6%, P < 0.001). Furthermore, similar trends were found in rural and urban, as well as in men and women.ConclusionsOur results showed that NEPHSP is effective in improving hypertension treatment and control in hypertensive patients in China. However, the coverage of NEPHSP was still low.

BackgroundFormation and rupture of abdominal aortic aneurysm (AAA) is fatal, and the pathological processes and molecular mechanisms underlying its formation and development are unclear. Perivascular adipose tissue (PVAT) has attracted extensive attention as a newly defined secretory organ, and we aim to explore the potential association between PVAT and AAA.MethodsWe analyzed gene expression and clinical data of 30 PVAT around AAA and 30 PVAT around normal abdominal aorta (NAA). The diagnostic markers and immune cell infiltration of PVAT were further investigated by WGCNA, CIBERSORT, PPI, and multiple machine learning algorisms (including LASSO, RF, and SVM). Subsequently, eight-week-old C57BL/6 male mice (n = 10) were used to construct AAA models, and aorta samples were collected for molecular validation. Meanwhile, fifty-five peripheral venous blood samples from patients (AAA vs. normal: 40:15) in our hospital were used as an inhouse cohort to validate the diagnostic markers by qRT-PCR. The diagnostic efficacy of biomarkers was assessed by receiver operating characteristic (ROC) curve, area under the ROC (AUC), and concordance index (C-index).ResultsA total of 75 genes in the Grey60 module were identified by WGCNA. To select the genes most associated with PVAT in the grey60 module, three algorithms (including LASSO, RF, and SVM) and PPI were applied. EGR1 and KLF4 were identified as diagnostic markers of PVAT, with high accurate AUCs of 0.916, 0.926, and 0.948 (combined two markers). Additionally, the two biomarkers also displayed accurate diagnostic efficacy in the mice and inhouse cohorts, with AUCs and C-indexes all >0.8. Compared with the NAA group, PVAT around AAA was more abundant in multiple immune cell infiltration. Ultimately, the immune-related analysis revealed that EGR1 and KLF4 were associated with mast cells, T cells, and plasma cells.ConclusionEGR1 and KLF4 were diagnostic markers of PVAT around AAA and associated with multiple immune cells.

Previous studies have documented the associations between short-term diurnal temperature range (DTR) exposure and cardiovascular disease (CVD) via time-series analyses. However, the long-term impacts of DTR through a population-based prospective cohort have not been elucidated thoroughly. This study aimed to quantify the longitudinal association of DTR exposure with all-cause mortality and CVD in a nationwide prospective cohort and, by extension, project future DTR changes across China under climate change. We included 22,702 adults (median age 56.1 years, 53.7% women) free of CVD at baseline from a nationwide cross-sectional study in China during 2012–2015, and examined three health outcomes during a follow-up survey in 2018–2019. We estimated the chronic DTR exposure as baseline annual mean daily maximum minus minimum temperature. The Cox proportional hazards regression was adopted to assess the multivariable-adjusted hazard ratio and its corresponding 95% confidence interval (95% CI). We employed 31 downscaled global climate models under two shared socioeconomic pathways for future projection. During the median follow-up period of ~5 years, 1096 subjects died due to all causes while 993 and 597 individuals developed fatal or nonfatal CVD and fatal or nonfatal stroke, respectively. The cumulative incidence rates of all-cause mortality, CVD, and stroke were 10.49, 9.45, and 5.64 per 1000 person-years, respectively. In the fully adjusted models, the risks for all-cause mortality, CVD, and stroke would increase by 13% (95% CI: 8–18%), 12% (95% CI: 7–18%), and 9% (95% CI: 2–16%) per 1 °C increment in DTR, respectively. Moreover, linear positive associations for the concentration–response curves between DTR and mortality and CVD were observed. We also found significantly greater DTR-related mortality risks among rural residents than their urban counterparts. The DTR changes featured a dipole pattern across China under a warming climate. The southern (northern) China would experience increased (decreased) DTR exposure by the end of 21st century. The present study indicates that chronic DTR exposure can exert long-term impacts on mortality and CVD risks, which may inform future public health policies on DTR-related susceptible population and regions.

Metabolic syndrome (MetS) is associated with cardiovascular risk, and there are various definitions, but which is most predictive of future cardiovascular disease (CVD) in the Chinese population is still unclear. MetS was defined with the revised ATP III (Third Adult Treatment Panel Report), International Diabetes Federation (IDF), and the Joint Committee for Developing Chinese Guidelines (JCDCG) definitions. Cox regression was used to estimate the hazard risk of cardiovascular disease among 20,888 participants using the Chinese Hypertension Survey (CHS) data. Sensitivity, specificity, and receiver operating characteristic (ROC) curve distance were used to test the ability of three MetS criteria to identify CVD. During an average follow-up of 4.89 years of 20,888 participants, 925 CVD events occurred (stroke, 560; coronary heart disease, 275; and other cardiovascular events, 119). The revised ATP III criteria identified the most individuals with MetS and had the highest prevalence of MetS. In addition, MetS was associated with a high risk of CVD in both men and women, according to three criteria. The highest diagnostic specificity was for IDF in men and JCDCG in women. The revised ATP III criteria had the highest sensitivity and shortest ROC curve distance in both men and women. Although the MetS definitions, including the revised ATP III, IDF, and JCDCG, are all related to the increased risks of CVD, overall, the revised ATP III performs best and is the most recommended for the Chinese population.

Docosahexaenoic acid (DHA) shows different anti-cancer effects on breast cancer (BC) cell proliferation and progression; however, the underlying molecular mechanism yet still is blanketed in mystery. Herein, we aimed to reveal whether the inhibitory effects of DHA on BC proliferation and migration are exerted, at least in part, through promoting the expression of miR-99a and targeting mTOR signaling. DHA lessened the BC cell viability in a time- and concentration-dependent manner. Besides, DHA-treatment significantly suppressed the proliferation and migration, while promoted BC cell apoptosis by regulating Bax and Bcl-2. We also demonstrated that DHA activated caspase-3/7 in MDA-MB-231 BCE cells. Also, we determined that miR-99a was upregulated in DHA-treated cells and mTOR was a direct and functional target of this miRNA, verified by the ability of anti-miR-99a to rescue the suppressive effects of DHA on mTOR expression in BC cells. Furthermore, DHA was shown to inhibit the mTOR-HIF-1α-VEGF signaling via regulating miR-99a in BC cells. DHA treatment caused a significant dose-dependent reduction of VEGF secretion from BC cells. When miR-99a was knocked down, DHA did not inhibit the BC proliferation and migration. We concluded that the anti-cancer effects of DHA can be attributed to the up-regulation of miR-99a that ipso facto inhibit the mTOR-HIF-1α-VEGF axis in BC cells. It is thought that DHA treatment might be considered as a promising supplement for BC therapy.

IntroductionCircular RNAs (CircRNAs), an emerging non-coding RNA, have been demonstrated to be involved in tumorigenesis, metastasis, and cancer progression, and could represent novel potential biomarkers for diagnosing oral squamous cell carcinoma (OSCC). However, no meta-analysis has investigated the diagnostic role of circRNAs in OSCC. Hence, to investigate whether circRNAs could serve as specific biomarkers for OSCC, the present systematic review and meta-analysis evaluated the diagnostic efficiency of circRNAs in patients with OSCC.Materials and MethodsA thorough search of online databases (Pubmed, Web of Science, Embase, and the Cochrane Library) was conducted to collect relevant studies up to March 30th, 2021. All eligible studies were case-control studies. The quality of each study was evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. STATA (version 15.1) and Review Manager (version 5.4) were employed to conduct the meta-analysis, and the PRISMA statement was adopted in this study.ResultsA total of 16 studies were included in the meta-analysis, with five studies on upregulated circRNAs, and 11 on downregulated circRNAs. The enrolled studies that met our eligibility criteria all derived from China. The pooled sensitivity (SEN), specificity (SPE), diagnostic odds ratio (DOR), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and the area under receiver operating characteristics curve (AUC) with the 95% confidence intervals (95% CIs) were 0.74 (0.69–0.79), 0.79 (0.73–0.84), 10.74 (7.81–14.77), 3.50 (2.78–4.45), 0.33 (0.27–0.39) and 0.83 (0.79–0.86), respectively. The subgroup analysis demonstrated that serum, plasma, and saliva specimens had a better diagnostic performance than tissue samples, with a high value of sensitivity, specificity, DOR, and AUC values. The results also showed that the subgroups of upregulated circRNAs and a sample size of ≥100 manifested higher specificity, DOR, and AUC for cancer detection than downregulated circRNAs and a sample size of < 100.ConclusionsA strong association was demonstrated between the dysregulated expression of circRNAs and the diagnosis of OSCC. Hence, circRNAs have the potential to function as promising biomarkers and therapeutic targets for OSCC.Systematic Review RegistrationPROSPERO, number CRD42021256857.

Emerging evidence suggests that circular RNAs (circRNAs) are linked to the development and progression of human cancers. Nevertheless, their contribution to breast cancer (BC) is still largely unknown. In the current study, we screened and identified a novel circRNA, circ-UBE2D2, which was highly expressed in BC cell lines and tissues and was closely related to aggressive clinical features and dismal prognosis. Small interfering RNA (siRNA)–mediated circ-UBE2D2 silencing notably inhibited the proliferation, migration and invasion of BC cells, whereas circ-UBE2D2 overexpression displayed opposite effects. Mechanistically, circ-UBE2D2 was able to simultaneously function as molecular sponges of miR-1236 and miR-1287 to regulate the expression of their respective target genes. Moreover, circ-UBE2D2–induced tumor-promoting effects could be effectively blocked by miR-1236 or miR-1287 in BC cells. More importantly, therapeutic delivery of cholesterol-conjugated si-circ-UBE2D2 oligonucleotides significantly delayed tumor growth in vivo. Overall, our findings indicate that circ-UBE2D2 plays an essential oncogenic role in BC, and targeting circ-UBE2D2 may be a feasible treatment for BC patients.

In this paper, we propose junction conditions for discontinuities due to local perturbation, diverging, merging, and multi-in-multi-out junctions. Traffic flows on junctions can be described by a system of coupled Hamilton-Jacobi equations. At their connection points, it is necessary to propose appropriate junction conditions to close the system. Then, we provide an effective numerical method to compute approximate solutions to these Hamilton-Jacobi equations on junctions. The numerical boundary conditions to close the Hamilton-Jacobi system are also proposed. Numerical tests demonstrate the effectiveness of both the proposed junction conditions and the numerical method.

Background Although numerous studies have been published evaluating the positive or negative effects of altitude on cardiovascular disease, many of them are conflicting. Methods and Results Data come from 2 cross‐sectional surveys using a similar method in China; and a total of 34 215 residents, aged ≥35 years, were eligible and recruited in the study. Left ventricular diastolic dysfunction (LVDD), according to the 2009 American Society of Echocardiography guidelines, was defined and evaluated. Altitude was divided into low (

Objective: Heparinization is applied to prevent ischemic complications in the endovascular treatment of intracranial aneurysms, but there is no unified heparinization scheme. Diffusion-weighted imaging (DWI) can be used to evaluate ischemia after endovascular therapy for intracranial aneurysms. The goal of this study is to apply DWI to evaluate the effects of different heparinization schemes on intracranial aneurysms treated with endovascular therapy.Methods: We retrospectively reviewed 141 patients with 149 aneurysms treated with endovascular interventions from July 2019 to April 2020 at our center, including 96 aneurysms treated with local heparinization and 53 aneurysms treated with systemic heparinization. We collected the basic information of the patients, including age, sex, comorbidities, and aneurysm characteristics, and associated treatment data. New ischemic lesions detected by DWI were categorized belonging to four types. Multivariate logistic regression was used to compare the effects of different heparinization schemes on intracranial aneurysms treated with endovascular therapy.Results: There were no significant differences in age, sex, hypertension, diabetes, and aneurysm size or location between the two groups. The incidence and distribution types of DWI abnormalities in the local heparinization groups and systemic heparinization groups were not significantly different (P > 0.05). There was a correlation between the laser engraving stent and postoperative DWI abnormalities (P < 0.003). Multivariate logistic regression analysis showed that the laser engraving stent was significantly correlated with postoperative DWI abnormalities (odds ratio, 4.71; 95% CI: 1.51–14.58; P = 0.007).Conclusion: Compared with systemic heparinization, local heparinization does not increase the incidence of DWI abnormalities after endovascular treatment, and its application in this group of patients is safe and effective.

COVID-19 affects aviation around the world. China’s civil aviation almost recovered to its pre-epidemic levels in the domestic market, but there are still local outbreaks that affect air traffic. This paper proposes measuring the impact of local outbreaks of COVID-19 by the machine learning method and the synthetic control method as a counterfactual control group to measure such an impact. In this study, we use the LightGBM algorithm to construct a counterfactual control group and transform the prediction problem from time series to the fitting problem at the spatial level. We find that machine learning methods can measure such an impact more accurately. We take local outbreaks in Beijing and Dalian as examples, and our measure of their impacts shows that the impact of an outbreak on intercity air traffic can be divided into lag, decline, stable, and recovery periods, and will last for a long period (more than 40 days) unless there are external stimuli, such as legal holidays. The outbreaks reduced the number of passengers in the cities by 90%. Finally, we show the impact on the air traffic network, and find that when a local outbreak happens in a big city, tourist cities or small stations will be greatly affected.

Predicting crystal structure has been a challenging problem in physics and materials science for a long time. A reliable energy calculation engine combined with an efficient global search algorithm, such as particle swarm optimization algorithm or genetic algorithm, is needed to conduct crystal structure prediction. In recent years, machine learning-based interatomic potential energy surface models have been proposed, potentially allowing us to perform crystal structure prediction for systems with the accuracy of density functional theory (DFT) and the speed of empirical force fields. In this paper, we employ a previously developed Deep Potential model to predict the intermetallic compound of the aluminum–magnesium system, and find six meta-stable phases with negative or nearly zero formation energy. In particular, Mg12Al8 shows excellent ductility and Mg5Al27 has a high Young's modulus. Based on our benchmark results, we propose a relatively robust structure screening criterion that selects potentially stable structures from the Deep Potential-based convex hull and performs DFT refinement. By using this criterion, the computational cost needed to construct the convex hull with ab initio accuracy can be dramatically reduced.

Triple-negative breast cancer (TNBC) is one of the most aggressive cancer types with high recurrence, metastasis, and drug resistance. Recent studies report that long noncoding RNAs (lncRNAs)-mediated competing endogenous RNAs (ceRNA) play an important role in tumorigenesis and drug resistance of TNBC. Although elevated lncRNA DLX6 antisense RNA 1 (DLX6-AS1) has been observed to promote carcinogenesis in various cancers, the role in TNBC remained unclear. In this study, expression levels of DLX6-AS1 were increased in TNBC tissues and cell lines when compared with normal tissues or breast fibroblast cells which were determined by quantitative real-time PCR (RT-qPCR). Then, CCK-8 assay, cell colony formation assay and western blot were performed in CAL-51 cells transfected with siRNAs of DLX6-AS1 or MDA-MB-231 cells transfected with DLX6-AS1 over expression plasmids. Knock down of DLX6-AS1 inhibited cell proliferation, epithelial-mesenchymal transition (EMT), decreased expression levels of BCL2 apoptosis regulator (Bcl-2), Snail family transcriptional repressor 1 (Snail) as well as N-cadherin and decreased expression levels of cleaved caspase-3, γ-catenin as well as E-cadherin, while up regulation of DLX6-AS1 had the opposite effect. Besides, knockdown of DLX6-AS1 in CAL-51 cells or up regulation of DLX6-AS1 in MDA-MB-231 cells also decreased or increased cisplatin resistance of those cells analyzed by MTT assay. Moreover, by using dual luciferase reporter assay, RNA immunoprecipitation and RNA pull down assay, a ceRNA which was consisted by lncRNA DLX6-AS1, microRNA-199b-5p (miR-199b-5p) and paxillin (PXN) was identified. And DLX6-AS1 function through miR-199b-5p/PXN in TNBC cells. Finally, results of xenograft experiments using nude mice showed that DLX6-AS1 regulated cell proliferation, EMT and cisplatin resistance by miR-199b-5p/PXN axis in vivo. In brief, DLX6-AS1 promoted cell proliferation, EMT, and cisplatin resistance through miR-199b-5p/PXN signaling in TNBC in vitro and in vivo.

Genetic risk loci for tuberculosis (TB) have so far been identified in African and Russian populations. Here, the authors perform a three-stage GWAS for TB in Han Chinese populations and find two risk loci near ESRRB and TGM6 and further demonstrate that tgm6 protects mice from Mtb infection.