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Ceramic particles reinforced magnesium matrix composites (CMMCs) have attracted widespread attention and investigation due to their excellent comprehensive performances. However, limited research on additive manufacturing of CMMCs has been performed. In this work, the SiC/AZ31 composites were fabricated by wire-arc directed energy deposition (WA-DED) based on the synchronous feeding strategy of powder and wire. The defects, SiC particle distribution, microstructure and mechanical properties of the prepared WA-DED SiC/AZ31 composites were studied. The results indicated that SiC particles with the content range of 0.3–1.7 wt% have been successfully added into the single-channel monolayer AZ31 matrix by adjusting the turret speed (TS) and the argon gas flow rate (AGFR) flowing through the powder feeder. The mathematical model is established to predict the introduced SiC particle content by correlating the relationship between SiC particle content and process parameters (TS and AGFR) of the powder feeder. The transformation from columnar to equiaxed grains occurs after adding SiC particles, more precipitated phases are formed after introducing more SiC particles. Compared to the AZ31 matrix, the WA-DED SiC/AZ31 composites exhibit the highest yield strength of 92.8 MPa and tensile strength of 213.3 MPa on the premise of almost no loss of elongation, and the maximum improvement efficiency of tensile strength reaches 56%, which is mainly ascribed to refinement strengthening, while thermal mismatch strengthening, Orowan strengthening and load-bearing strengthening play a booster action.

Low Pt utilization and intense carbon corrosion of cathode catalysts is a crucial issue for high‐efficiency proton exchange membrane fuel cells due to the highly demanded long‐term durability and less acquisition/application cost. Herein, structurally tunable graphitized mesoporous carbon (GMC) is obtained by direct high‐temperature pyrolysis and in situ‐controlled mesopore formation; the structure‐optimized GMC1300‐1800 exhibits a mesopore size of 7.54 nm and enhanced corrosion resistance. Functionalized GMC1300‐1800 is loaded with small‐sized Pt nanoparticles (NPs) (1.5 nm) uniformly by impregnation method to obtain Pt/GMC1300‐1800 and form an “internal platinum structure” to avoid sulfonic acid groups poisoning as well as ensure O2/proton accessibility. Hence, the electrochemically active surface area (ECSA) of Pt/GMC1300‐1800 reaches 106.1 m2 g−1Pt, while mass activity and specific activity at 0.9 V are 2.1 and 1.4 times those of commercial Pt/C, respectively. Notably, the ECSA decay is less than 17% for both 30 000 cycles’ accelerated durability tests (ADTs) of Pt attenuation and carbon attenuation. Accordingly, the optimized mesoporous structure of GMC1300‐1800 significantly decreases the coverage of sulfonic acid groups on Pt NPs, leading to the highest peak power density in the single‐cell test. Density functional theory calculations demonstrate the synergistic effect between graphitization and mesoporosity on enhancing the accessibility and durability of the catalysts.

Abstract Probiotics hold promise as a potential therapy for colorectal cancer (CRC), but encounter obstacles related to tumor specificity, drug penetration, and dosage adjustability. In this study, genetic circuits based on the E. coli Nissle 1917 (EcN) chassis were developed to sense indicators of tumor microenvironment and control the expression of therapeutic payloads. Integration of XOR gate amplify gene switch into EcN biosensors resulted in a 1.8-2.3-fold increase in signal output, as confirmed by mathematical model fitting. Co-culturing programmable EcNs with CRC cells demonstrated a significant reduction in cellular viability ranging from 30% to 50%. This approach was further validated in a mouse subcutaneous tumor model, revealing 47%-52% inhibition of tumor growth upon administration of therapeutic strains. Additionally, in a mouse tumorigenesis model induced by AOM and DSS, the use of synthetic bacterial consortium (SynCon) equipped with multiple sensing modules led to approximately 1.2-fold increased colon length and 2.4-fold decreased polyp count. Gut microbiota analysis suggested that SynCon maintained the abundance of butyrate-producing bacteria Lactobacillaceae NK4A136, whereas reducing the level of gut inflammation-related bacteria Bacteroides. Taken together, engineered EcNs confer the advantage of specific recognition of CRC, while SynCon serves to augment the synergistic effect of this approach.

This study explores the causes of coal bursts in the Xinzhou Kiln Mine, identifying key factors such as residual pillars, hard coal seams and/or roofs, stress concentration due to complex geological structures, and the stress distribution characteristics of the primary rock. A significant finding is that hydraulic cutting not only diminishes and redistributes the stress concentration region inside the coal seam but also mitigates the burst potential of the coal-rock mass, fundamentally reducing the likelihood of coal bursts. By taking Face No. 8937 in Xinzhou Kiln Mine as the test object, a coal burst prevention test was performed using hydraulic cutting. In combination with theoretical analysis and numerical simulation, the mechanism of hydraulic cutting for preventing coal burst was discussed, and reasonable cutting parameters were established. Onsite monitoring revealed that hydraulic cutting disrupts the integrity of the coal-rock mass, releases internal stress, and increases its water content, thereby weakening its burst tendency. Additionally, the deformation and fracturing of the cutting slots and the closure of boreholes shifted the stress concentration from the coal seam to deeper areas and to the two ribs. Post-cutting observations showed a significant reduction in both the frequency and impact energy of coal bursts; there was also a noticeable increase in the convergence of the roadway in the cutting area compared to non-cutting areas. Furthermore, displacement of the roof and floor increased by 78.9 % and that of the two ribs increased by 47.4 % after cutting, preventing the coal-rock mass from accumulating high stress. In conclusion, hydraulic cutting is a promising method for effectively preventing coal bursts and enhancing the safety of mining operations.

Abstract Background People with hypertension have a higher risk of developing Parkinson’s disease (PD), epidemiological evidence suggests that multiple antihypertensives may affect the occurrence and development of PD with inconsistent results. With multisource data, we sought to determine whether specific antihypertensive classes elevated or reduced the risk for PD. Methods We used a mixed methods approach that combines 4 methodologies. First, we conducted a disproportionality analysis using the reports causing adverse events in the US Food and Drug Administration Adverse Events Reporting System (FAERS) to explore the effect of different classes of antihypertensive medications on the risk of PD; based on the findings from FAERS, a meta-analysis and a UK Biobank cohort analysis were used to further assess the association of drug use with PD; finally, we employed Mendelian randomization (MR) analysis to validate the causal relationship between the drug target and the occurrence of PD. Results In the disproportionality analysis using the FAERS (N = 187,266), nonselective beta-adrenoceptor blockers (NBBs) were demonstrated to have a significant association with PD (reporting odds ratio (ROR) = 3.13; 95% CI 2.33–4.22). In the meta-analysis of 12 studies with 12,183,809 participants, PD risk was elevated in NBBs (RR, 1.64; 95% CI, 1.19–2.09) when stratified by subtypes of BBs. Among the 105,763 participants included in the cohort analysis using data from the UK Biobank, individuals who used NBBs had a significantly increased risk of PD compared to nonusers (HR, 1.47; 95% CI 1.04–2.06). The MR analysis revealed a significant association between higher expression of the β2 adrenergic receptor (ADRB2) gene, a drug target blocked by NBBs, and a reduced risk of PD (OR, 0.85; 95% CI 0.73–0.99). Conclusions Our comprehensive study indicated that regular NBB use is associated with an increased risk of PD. In light of the detrimental effects of NBBs on PD, some people should choose alternative antihypertensive treatments.

Abstract The inhibitor of apoptosis protein survivin has a critical regulatory role in carcinogenesis and treatment tolerance in colorectal cancer (CRC). However, the targeted drugs for survivin protein are extremely limited. In the present research, we discovered that Tanshinone IIA (Tan IIA) played a dual regulatory role in inhibiting tumorigenesis and reversing 5-Fu tolerance via modulating the expression and phosphorylation of survivin in CRC cells. Mechanistically, Tan IIA suppressed the Akt/WEE1/CDK1 signaling pathway, which led to the downregulation of survivin Thr34 phosphorylation and destruction of the interaction between USP1 and survivin to promote survivin ubiquitination and degradation. Furthermore, Tan IIA significantly facilitated chemoresistant CRC cells to 5-Fu sensitivity. These results revealed that Tan IIA possessed a strong antitumor activity against CRC cells and could act as an up-and-coming agent for treating CRC and overcoming chemotherapy resistance.

The measurement of the target azimuth angle using forward-looking radar (FLR) is widely applied in unmanned systems, such as obstacle avoidance and tracking applications. This paper proposes a semi-supervised support vector regression (SVR) method to solve the problem of small sample learning of the target angle with FLR. This method utilizes function approximation to solve the problem of estimating the target angle. First, SVR is used to construct the function mapping relationship between the echo and the target angle in beamspace. Next, by adding manifold constraints to the loss function, supervised learning is extended to semi-supervised learning, aiming to improve the small sample adaptation ability. This framework supports updating the angle estimating function with continuously increasing unlabeled samples during the FLR scanning process. The numerical simulation results show that the new technology has better performance than model-based methods and fully supervised methods, especially under limited conditions such as signal-to-noise ratio and number of training samples.

Deep cryogenic aging (DCA) is a newly developed heat treatment technique for additive-manufactured metallic materials to reduce residual stress and improve their mechanical properties. In this study, AlSi10Mg alloy samples fabricated by selective laser melting were deep-cryogenic-treated at −160 °C and subsequently aged at 160 °C. Phase and microstructural analyses were conducted using X-ray diffraction, optical microscopy, scanning electron microscopy, and transmission electron microscopy, while the mechanical properties were evaluated through microhardness and tensile testing at room temperature. The results indicated that the DCA treatment did not have an effect on the morphology of the melt pools. However, it facilitated the formation of atomic clusters and nanoscale Si and β′ phases, as well as accelerating the coarsening of grains and the ripening of the eutectic Si phase. After DCA treatment, the mass fraction of the Si phase experienced an increase from 4.4% to 7.2%. Concurrently, the volume fraction of the precipitated secondary phases elevated to 5.1%. The microhardness was enhanced to 147 HV, and the ultimate tensile strength and yield strength achieved 495 MPa and 345 MPa, respectively, with an elongation of 7.5%. In comparison to the as-built specimen, the microhardness, ultimate tensile strength, and yield strength increased by 11.4%, 3.1%, and 19.0%, respectively. The improvement in mechanical properties is primarily attributed to the Orowan strengthening mechanism induced by the secondary phases.

The microstructure characteristics of TiAl alloy prepared by laser-directed energy deposition (L-DED) are coarse columnar grains parallel to the building direction, which results in serious mechanical properties and anisotropy and limits its application. In the present study, TiB2 can be used as an effective grain refiner due to the extremely high Q value (growth inhibition factor; the larger the Q value of an alloying element, the stronger its grain refinement effect.) of B. With TiB2 addition, TiAl alloys prepared by laser-directed energy deposition with the microstructure of full equiaxed grains were obtained, and the grain size was significantly reduced by about 30% with 0.45 wt.% TiB2. This value has been further increased to 45% when adding 0.9 wt.% TiB2. Moreover, the γm phase was nearly eliminated and the width of (α2 + γ) lamellar was significantly decreased, which has positive effects on mechanical properties. Meanwhile, TiB2 precipitates uniformly distribute in the matrix, as a reinforced particle to increase the hardness and compressive strength of the alloys. The microhardness of the TiAl alloy increased with the increasing content of TiB2. The addition of TiB2 improved the room and high-temperature compressive properties of TiAl alloy while slightly increasing its ductility. These findings have important guiding significance for expanding the application of TiAl alloys.

Colorectal cancer (CRC) is a serious global health concern, and researchers have been investigating different strategies to prevent, treat, or support conventional therapies for CRC. This review article comprehensively covers CRC therapy involving wild-type bacteria, including probiotics and oncolytic bacteria as well as genetically modified bacteria. Given the close relationship between CRC and the gut microbiota, it is crucial to compile and present a comprehensive overview of bacterial therapies used in the context of colorectal cancer. It is evident that the use of native and engineered probiotics for colorectal cancer therapy necessitates research focused on enhancing the therapeutic properties of probiotic strains.. Genetically engineered probiotics might be designed to produce particular molecules or to target cancer cells more effectively and cure CRC patients.

Joint radar-communication waveform design has been the focus of intensive research in recent years. The integrated waveform based on a collocated antenna can simultaneously detect targets and communicate with multiple users in different directions. However, integrated waveforms possess poor anti-jamming properties and lack secure communication abilities, which limits their capacity to address the jamming and eavesdropping behaviors that generate at various ranges in the same beam direction. In this study, a novel joint radar-communication waveform design method based on a distributed aperture is proposed to control waveform distributions in the three-dimensional space. First, the waveform synthesis constraint is established to synthesize the desired radar and communication waveforms in designated directions. Second, the constant modulus constraint is added to each sub-aperture, following which an integrated waveform optimization model is established based on the minimum transmission power. Finally, the alternating projection algorithm is used to iteratively solve the nonconvex optimization problem. Simulation results demonstrate that the proposed method synthesizes desired waveforms at target positions and realizes three-dimensional spatial waveform manipulation.

The magnesium matrix composites (MMCs) formed by introducing reinforcements to magnesium alloys overcome the limitations of the mechanical properties to a certain extent, presenting unique and excellent properties that any component does not have, such as high specific stiffness and specific strength, good dimensional stability, outstanding shock absorption performance, excellent electromagnetic shielding and hydrogen storage characteristics, etc. As an emerging manufacturing technology, additive manufacturing (AM) is based on the design of three-dimensional (3D) data model to obtain 3D objects through layer-by-layer processing, which possesses the advantages of short manufacturing cycle, high material utilization rate, high degree of design freedom, excellent mechanical properties and the ability to fabricate complex structural components. Combining the high stiffness and high strength properties of MMCs and the technical advantages of AM forming complex structural parts with high performance, the prepared AM MMCs have huge potential advantages and broad application prospects in new high-tech industries such as automobile, aerospace, consumer electronics and biomedicine, etc. This paper reviews the research progress in the field of AM MMCs, mainly introduces the main AM technologies, including selective laser melting (SLM), electron beam selective melting (EBSM), laser engineered net shaping (LENS) and wire and arc additive manufacturing (WAAM). The formation mechanism and control methods of the typical defects including balling effect, porosity, poor fusion, loss of alloy elements and cracks produced during AM are discussed. The main challenges of AM MMCs are proposed from the aspects of composition design and the preparation of powder raw material. The relationship between the microstructure and mechanical properties, corrosion performance and biocompatibility of AM MMCs are elaborated in detail. The application potential of AM MMCs in various fields at present and in the future is introduced. Finally, the development direction and urgent problems to be solved in the AM MMCs are prospected.

In the process of acquiring 3D point cloud data, due to environmental interference or unstable scanning equipment, the acquired data often have noisy points. Recently, with the development of neural networks for point clouds, great progress has been made in deep learning-based point cloud denoising. However, most of the existing methods adopt a pointnet-like structure to predict point offsets. Simple pooling operation loses much important information, such as local neighborhood information, and global information. The loss of information makes the algorithm ineffective when dealing with some complex cases. In order to solve the above problems, we propose a self-attention-based point cloud denoising network architecture, through the Transformer structure, to establish long-range dependencies of the points. In addition, we propose a local information embedding module to fast select meaningful points and serve as the input of the Transformer. We also consider the correlation between channels of point cloud features and further introduce a channel attention module. Extensive experiments prove that our method outperforms existing methods, and maintains a high running speed.

The tree shrew (Tupaia belangeri) is currently placed in the order Scandentia. Owing to their unique characteristics, such as small body size, high brain-to-body mass ratio, short reproductive cycle and life span, and low maintenance costs in laboratory conditions, tree shrews have been proposed as alternative experimental animals to primates in biomedical research. In this study, we determined the complete mitochondrial genome of the subspecies Tupaia belangeri yaoshanensis (T.b. yaoshanensis). The mitochondrial DNA (mtDNA) is 16,777 bp long and contains 13 protein-coding genes (PCGs), two ribosomal RNA genes (12S and 16S), and 22 transfer RNA (tRNA) genes. The base composition of the mitogenome was A (32.28%), T (26.82%), G (14.79%), and C (26.11%). For the 13 PCGs, 1405 variable sites were found between T.b. yaoshanensis and T.b. chinensis (JN800724), of which 916 were synonymous and 489 were nonsynonymous. The frequency of mutations significantly varied among the different genes, with the highest value in the mt-NAD5 gene of tree shrews. Phylogenetic analysis based on the amino acid sequences of 13 PCGs revealed a closer relationship between the species of Scandentia and Lagomorpha. To the best of our knowledge, this is the first study to report the complete mitochondrial genome sequence of T.b. yaoshanensis.

TC4 particles reinforced AZ31 composite was successfully prepared by innovatively using simultaneous feeding method of powder and wire in wire-arc directed energy deposition (WA-DED). The results indicated that TC4 particles are expected to be evenly distributed in the AZ31 matrix and the introduced TC4 particle content of 9%−33.43 wt% can be acquired by adjusting the turret speed (TS) of powder feeder. The coarse columnar grains in the AZ31 transforms into the equiaxed grains after adding TC4 particles. A large number of acicular/flake Mg-Al phase and partial granular Al-Mn phase are formed around TC4 particles. The excellent tensile properties with yield strength of 85.6 MPa, ultimate tensile strength of 195 MPa and tensile elongation of 7.1% are obtained at the TS of 5 rpm, the corresponding maximum improvement efficiency reaches up to 42.6%. The improved strength mainly derives from grain refinement strengthening and thermal mismatch strengthening.

Abstract Accurate precipitation prediction can help decision makers judge the trend of climate change and formulate more effective measures, and prevent flood and drought disasters. In this paper, we propose a short‐term regional precipitation prediction model based on wind‐improved spatiotemporal convolutional network. Among them, the improved graph convolution network integrates the effects of wind direction and geographic location at past moments to capture the spatial dependence, whilst the gated recurrent unit captures the temporal dependence by learning the dynamic changes of data. The spatio‐temporal memory flow module and attention module are added to capture spatial deformation and temporal variation more accurately, thereby better matching the physical properties of precipitation. The proposed model achieves better prediction results on real data sets. Experiments show that our method is better at extracting the spatio‐temporal information of precipitation data and capturing its time dependence and spatial correlation.

Taking an oxygen-rich side-blown lead melting furnace made by a company as the research object, the three-dimensional design software Solidworks was used to construct a model at an equal scale, and established a physical model which is in line with the actual system. Based on the determination of the physical properties of the slag phase and metal phase in the furnace, the VOF multiphase flow model and standard turbulence model in FLUENT were used to simulate the gas–liquid multiphase flow. By adjusting the different inclination angles of the spray gun, we analyzed the distribution changes of key indicators, such as the flow field, average turbulent kinetic energy and gas content in the furnace. At the same time, it was found that the turbulent kinetic energy in the middle of the furnace was large, which could strengthen the winding effect of the material and the best arrangement. The gas content of the upper part of the oxygen gun was high, and the gas content in the middle of the furnace was higher than that in the wall area on both sides and showed a gradual downward trend. If the inclination angle of the spray gun is too small, the agitation of the lower melting area is not strong enough, On the contrary, if the inclination angle is too large, the local flow rate of the sedimentation area increases and the gas content is low. The optimal tilt angle of the spray gun is between 10° and 15°.

Aims: Current idiopathic pulmonary fibrosis (IPF) therapies usually show a poor outcome or treatment efficacy. The search for new risk factors has significant implications in preventing, delaying, and treating IPF. The association between obesity and the risk of IPF is not clear. This study aimed to investigate the role of different obesity types in IPF risk, which provides the possibility of weight loss as a new approach for IPF prevention.Methods: We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal effect of obesity on IPF risk. We collected summary data of genetically determined obesity-related traits, including body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) from large-scale consortia (the sample size ranging from 232,101 to 681,275), and genetic association with IPF from one of the largest meta-analyses including 2,668 cases. A total of 35–469 single nucleotide polymorphisms were selected as instrumental variables for obesity-related traits. We further performed multivariable MR to estimate the independent effect of BMI and WC on the risk of IPF.Results: Increased BMI and WC were associated with higher risk of IPF [odds ratio (OR) = 1.51, 95% confidence interval (CI) (1.22–1.87), p = 1.27 × 10–4, and OR = 1.71, 95% CI (1.08–2.72), p = 2.33 × 10–2, respectively]. Similar results for the BMI and WC were obtained in the replicated analysis. Subsequently, only the result for BMI survived following the multiple testing correction and showed good consistency with the weighted median estimator. Sensitivity analyses indicated that there was no heterogeneity or horizontal pleiotropy for MR estimations. Further multivariable MR suggested that the BMI showed the same direction and similar magnitude with that in the univariable MR analysis. There was little evidence to support the causal role of WHR on the risk of IPF in this study.Conclusion: Genetically determined BMI demonstrates a causal risk for IPF, which offers a novel insight into probing potential mechanisms. Meanwhile, these results also suggest that weight loss may be beneficial to IPF prevention.

Abstract Background Lung adenocarcinoma is metastatic cancer with a high mortality rate. Circular RNAs (circRNAs) are a type of noncoding RNA and play a vital role in cancer progression. However, the expression and function of circRNAs in lung adenocarcinoma are still mostly unknown. Methods In this study, we screened the differential expression of circRNAs in human bronchial epithelial cells (HBE) and A549 human lung adenocarcinoma cell line (A549) by human circRNA microarray and RT-qPCR. The role of overexpressed circRNA_104889 in A549 cell proliferation, apoptosis, migration, and invasion was studied extensively. Intracellular localization of circRNA_104889 was visualized by FISH assay. MiRNA sponging, ERK1/2 signaling, and caspase-3 expression were analyzed in siRNA-mediated circRNA_104889 knockdowned A549 cells. Results CircRNA microarray showed overexpression of circRNA_104889 (> 13-fold) in A459 cells compared to HBE. This finding was further corroborated by the RT-qPCR result. CircRNA_104889 was mainly localized in the cytoplasm of A549 cells. The knockdown of circRNA_104889 in A549 cells by si-RNA mediated RNA interference did not affect cell proliferation and apoptosis but significantly inhibited cell migration and invasion in vitro. Furthermore, knockdown of circRNA_104889 led to an increase of miR4458 expression. Overexpression of miR4458 inhibited A549 cell migration. Both the knockdown of circRNA_104889 and overexpression of miR4458 inhibited the caspase-3 expression and ERK1/2 phosphorylation in A549 cells. Conclusions CircRNA_104889 promotes lung adenocarcinoma cell migration and invasion by sponging miR4458 and targeting ERK1/2 signaling and caspase-3 expression.

BackgroundObstructive sleep apnea (OSA) and atrial fibrillation (AF) are epidemiologically correlated, but the causal relationship between them remains elusive. We aimed to explore the causal relationships between OSA and AF.MethodUsing both the Finnish biobank and publicly available genome-wide association study data (GWAS), we conducted a two-sample Mendelian randomization (MR) analysis to estimate the causal effect of OSA on AF, both in the primary analysis and replicated analysis. The inverse variance weighted MR was selected as the main method. To further test the independent causal effect of OSA on AF, we also performed multivariable MR (MVMR), adjusting for body mass index (BMI), hypertension, and coronary artery disease (CAD), respectively.ResultsIn the primary analysis, OSA was significantly associated with the increased risk of AF (OR 1.21, 95% CI 1.11–1.32) and the replicated analysis showed consistent results (OR 1.17, 95% CI 1.05–1.30). Besides, there was no heterogeneity and horizontal pleiotropy observed both in the primary and replicated analysis. Further multivariable MR suggested that the causal relationships between OSA and AF exist independently of BMI and CAD. The MVMR result after the adjustment for hypertension is similar in magnitude and direction to the univariable MR. But it did not support a causal relationship between OSA and AF.ConclusionOur study found that genetically driven OSA causally promotes AF. This causal relationship sheds new light on taking effective measures to prevent and treat OSA to reduce the risk of AF.

Background: Observational studies have revealed the association between some inflammatory cytokines and the occurrence of ischemic stroke, but the causal relationships remain unclear.Methods: We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal effects of thirty inflammatory cytokines and the risk of ischemic stroke. For exposure data, we collected genetic variants associated with inflammatory cytokines as instrumental variables (IVs) from a genome-wide association study (GWAS) meta-analysis from Finland (sample size up to 8,293). For the outcome data, we collected summary data of ischemic stroke from a large-scale GWAS meta-analysis involved 17 studies (34,217 cases and 406,111 controls). We further performed a series of sensitivity analyses as validation of primary MR results.Results: According to the primary MR estimations and further sensitivity analyses, we established one robust association after Bonferroni correction: the odds ratio (95% CI) per unit change in genetically increased IL-4 was 0.84 (0.89–0.95) for ischemic stroke. The chemokine MCP3 showed a nominally significant association with ischemic stroke risk (OR: 0.93, 95% CI: 0.88–0.99, unadjusted p < 0.05). There was no evidence of a causal effect of other inflammatory cytokines and the risk of ischemic stroke.Conclusions: Our study suggested that genetically increased IL-4 levels showed a protective effect on the risk of ischemic stroke, which provides important new insights into the potential therapeutic target for preventing ischemic stroke.

Abstract Background Emerging evidence has shown that dysregulated expression of long noncoding RNAs (lncRNAs) is implicated in liver hepatocellular carcinoma (HCC). However, the role and molecular mechanism of differentially expressed lncRNAs in HCC has not been fully explained. Methods The expression profiles of lncRNAs in HCC samples were derived from microarrays analysis or downloaded from The Cancer Genome Atlas (TCGA), and their correlation with prognosis and clinical characteristics were further analyzed. Silencing of lncRNA ZFPM2-AS1 was conducted to assess the effect of ZFPM2-AS1 in vitro. The miRcode and Target Scan databases were used to determine the lncRNA-miRNA-mRNA interactions. The biological functions were demonstrated by luciferase reporter assay, western blotting, PCR and rescue experiments. Results The expression level of lncRNA ZFPM2-AS1 was significantly higher in HCC tissues than in adjacent normal tissues, and higher ZFPM2-AS1 was remarkably related to poor survival. Functionally, silencing of lncRNA ZFPM2-AS1 inhibited cell proliferation, migration, invasion and promoted cell apoptosis in vitro. Bioinformatics analysis based on the miRcode and TargetScan databases showed that lncRNA ZFPM2-AS1 regulated GDF10 expression by competitively binding to miR-139. miR-139 and downregulated GDF10 reversed cell phenotypes caused by lncRNA ZFPM2-AS1 by rescue analysis. Conclusions ZFPM2-AS1, an upregulated lncRNA in HCC, was associated with malignant tumor phenotypes and worse patient survival. ZFPM2-AS1 regulated the progression of HCC by acting as a competing endogenous RNA (ceRNA) to competitively bind to miR-139 and regulate GDF10 expression. Our study provides new insight into the posttranscriptional regulation mechanism of lncRNA ZFPM2-AS1 and suggests that ZFPM2-AS1/miR-139/GDF10 may act as a potential therapeutic target and prognostic biomarker for HCC.

Background: Insulin resistance (IR) is closely associated with the pathogenesis of type 2 diabetes mellitus (T2DM). However, remission of insulin sensitivity after bariatric surgery in patients with T2DM and a body mass index (BMI) of 27.5–32.5 kg/m2 has not been fully elucidated.Methods: Thirty-six T2DM patients with a BMI of 27.5–32.5 kg/m2 were prospectively consecutively recruited for laparoscopic Roux-en-Y gastric bypass (LRYGB) or laparoscopic sleeve gastrectomy (LSG). Hyperinsulinemic euglycemic clamp, oral glucose tolerance test (OGTT), and other indicators were tested at baseline and 6 months postoperative. Glucose disposal rate (GDR), time to reach euglycemia, homeostatic model assessment of IR, quantitative insulin sensitivity check index (QUICKI), triglyceride glucose (TyG) index, 30-min insulinogenic index (IGI30), and disposition index (DI) were calculated at baseline and 6 months after surgery. The criterion for remission in T2DM patients was the achievement of the triple composite endpoint.Results: Anthropometric and glucolipid metabolism parameters significantly improved following surgery. The GDR increased significantly from baseline to 6 months after LRYGB (from 4.28 ± 1.70 mg/kg/min to 8.47 ± 1.89 mg/kg/min, p < 0.0001) and LSG (from 3.18 ± 1.36 mg/kg/min to 7.09 ± 1.69 mg/kg/min, p < 0.001). The TyG index decreased after surgery (RYGB group, from 9.93 ± 1.03 to 8.60 ± 0.43, p < 0.0001; LSG group, from 10.04 ± 0.79 to 8.72 ± 0.65, p = 0.0002). There was a significant reduction in the IGI30 (RYGB group, from 2.04 ± 2.12 to 0.83 ± 0.47, p = 0.005; LSG group, from 2.12 ± 1.73 to 0.92 ± 0.66, p = 0.001). The mean DI significantly increased from 1.14 ± 1.35 to 7.11 ± 4.93 in the RYGB group (p = 0.0001) and from 1.25 ± 1.78 to 5.60 ± 4.58 in the LSG group (p = 0.003). Compared with baseline, HOMR-IR, QUICKI, area under the curve-C-peptide release test (AUC-CRT), and AUC-OGTT were significantly changed at 6 months postoperative. Overall, 52.63% of patients in the LRYGB group versus 29.41% of patients in the LSG group achieved the triple composite endpoint.Conclusion: Both LRYGB and LSG effectively induced remission of IR in patients with T2DM and a BMI of 27.5–32.5 kg/m2.

Alcohol abuse increases the risk of acute liver injury. Escherichia coli Nissle 1917(EcN) has been comprehensively demonstrated as a safe oral probiotic. In this study, we genetically modified EcN expressing alcohol dehydrogenase gene, acetaldehyde dehydrogenase gene, NAD synthase gene, and NADH oxidase gene. Applied strains in the mouse experiment showed a 54.44% reduction in serum ethanol. EcN-treated mice also exhibited lower liver AST, ALT, MDA, TG, T-CHO, TNF-α, IL-1β and increased SOD and GSH levels versus untreated ones, indicating restored liver function alongside depressed oxidative stress, lipid peroxidation, and inflammation. Consistently, aberrant gene expression correlating with alcohol metabolism and injured liver induced by alcoholic food were restored following EcN inoculation. The efficacy EcN conferred was accompanied by the restoration of gut microbiota homeostasis. In conclusion, the engineered EcN has been shown to detoxify ethanol metabolites in liver disease models and which may be attributed to intestinal recovery.

BackgroundSmoking was strongly associated with breast cancer in previous studies. Whether smoking promotes breast cancer through DNA methylation remains unknown.MethodsTwo-sample Mendelian randomization (MR) analyses were conducted to assess the causal effect of smoking-related DNA methylation on breast cancer risk. We used 436 smoking-related CpG sites extracted from 846 middle-aged women in the ARIES project as exposure data. We collected summary data of breast cancer from one of the largest meta-analyses, including 69,501 cases for ER+ breast cancer and 21,468 cases for ER− breast cancer. A total of 485 single-nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs) for smoking-related DNA methylation. We further performed an MR Steiger test to estimate the likely direction of causal estimate between DNA methylation and breast cancer. We also conducted colocalization analysis to evaluate whether smoking-related CpG sites shared a common genetic causal SNP with breast cancer in a given region.ResultsWe established four significant associations after multiple testing correction: the CpG sites of cg2583948 [OR = 0.94, 95% CI (0.91–0.97)], cg0760265 [OR = 1.07, 95% CI (1.03–1.11)], cg0420946 [OR = 0.95, 95% CI (0.93–0.98)], and cg2037583 [OR =1.09, 95% CI (1.04–1.15)] were associated with the risk of ER+ breast cancer. All the four smoking-related CpG sites had a larger variance than that in ER+ breast cancer (all p < 1.83 × 10−11) in the MR Steiger test. Further colocalization analysis showed that there was strong evidence (based on PPH4 > 0.8) supporting a common genetic causal SNP between the CpG site of cg2583948 [with IMP3 expression (PPH4 = 0.958)] and ER+ breast cancer. There were no causal associations between smoking-related DNA methylation and ER− breast cancer.ConclusionsThese findings highlight potential targets for the prevention of ER+ breast cancer. Tissue-specific epigenetic data are required to confirm these results.

Increasing attention is being paid to the clean and efficient mining and utilization of coal resources. Lignite is a major component of coal; however, its high moisture and volatile contents and low calorific value cause it to have low mining and utilization efficiencies. During the dehydration, upgrading and in-situ heat injection or underground coal gasification of lignite, its pore structure plays an important role in the pyrolysis and product transfer processes. Therefore, it is necessary to systematically study the high-temperature pore structure of lignite. The evolution of pore fissures in gas-pyrolyzed lignite was studied by nuclear magnetic resonance combined with a gas heating reactor and test device. We found that the total connectivity, porosity and permeability of lignite increased between temperatures of 25 °C and 250 °C, then decreased at 350 °C and increased again at 450 °C. At 450 °C, the porosity, effective porosity and permeability of lignite were 18.32%, 30.22% and 856.98 md, respectively. The evolution in the pore structure parameters of lignite with temperature was observed to determine the changes in seepage channels that occur during the processes of lignite mining and utilization.

The energy crisis and environmental issues are becoming more severe due to the long-term consumption of fossil fuels. Therefore, novel energy-conversion devices with high energy density and environmental friendliness are expected to provide reliable alternatives to traditional fossil-based energy systems. However, because of the inevitable use of costly precious metals as the electrode catalysts for such devices, their popularization is seriously hindered. Transition metal nitrides (TMNs) exhibit similar surface and adsorption properties to noble metals because the atomic distance between metal atoms increases and the d-band center of metal atoms downshifts after nitrogen atoms enter the metal lattice. TMNs have become one of the best electrode materials to replace noble metal-based electrocatalysts in next-generation energy-storage and energy-conversion devices. In this review, the recent developments in the electrocatalytic application of TMNs are covered. First, we discuss the structure and activity origin of TMNs and introduce the common synthesis methods for the preparation of TMNs. Subsequently, we illustrate the applications of mono-metallic TMNs and multi-metallic TMNs in oxygen-reduction reaction, oxygen-evolution reaction, and bifunctional oxygen reduction and evolution reactions. Finally, we summarize the challenges of TMNs encountered at the present stage, and expect their future development.

Mid-term load forecasting (MTLF) of power supply unit (PSU) is an essential part of refined distribution network planning. By analyzing a large amount of historical data accumulated in electric automation systems, accurate MTLF result can be obtained with the help of big-data and parallel computing technology. In this paper, a dynamic bayes network (DBN)-based MTLF model is proposed to forecast the peak power load of next year of each PSU. In the first stage, we improve the accuracy of MTLF model by using dynamic radius DBSCAN algorithm to determine the optimal state division. In the second stage, to improve the computation efficiency, the calculations of multiple probability matrixes and the modified forward algorithm are implemented on an apache spark-based parallel computing platform. The experiment results indicate that the parallel processing of DBN-based MTLF model has superior performance in accuracy, efficiency, and versatility.

It is well known that underground in situ pyrolysis technology for oil shale production is a promising field. In the in situ modification mining process, the permeability property of a shale matrix has a great effect on the transport capacity of pyrolytic products. For oil shale undergoing pyrolysis, the changes of internal structure (fracture and pore space) have a considerable influence on the permeability network which further affects the migration of hydrocarbon products. In this study, based on an oil shale retorting experiment performed under different temperatures (20 °C, 100 °C, 200 °C, 300 °C, 325 °C, 350 °C, 375 °C, 400 °C, 425 °C, 450 °C, 475 °C, 500 °C, 525 °C, 550 °C, 575 °C, 600 °C), an investigation on the distribution characteristics of the fractures was conducted using micro-CT technology. Meanwhile, mercury injection porosimetry was used to characterize the pore structure of the oil shale samples under different temperatures. Finally, a fracture-pore dual medium model was constructed to calculate the percolation probability to quantitatively describe the permeability variation of oil shale with temperature. The test results indicated that the higher the temperature, the larger were the pore spaces. The increase in pore volume due to pyrolysis temperatures mainly affected the pores ranging from 10 nm to 100 nm and occurred in the specific temperature range (400 °C to 425 °C). Additionally, CT images show that the fracture morphology varied with increasing temperature and the number and length of fractures at different temperatures were in great accordance with the fractal law statistically. On the other hand, simulation of the percolation probabilities discovered that in a single pore media model over the whole range of tested temperatures they were too low to exceed the threshold. In contrast, in the dual medium model, the theoretical threshold of 31.16% was exceeded when the temperature reached 350 °C. Moreover, the results demonstrated that fractures dominated the seepage channel and had more significant effects on the permeability of oil shale. What has been done in this study will provide some guidance for the in situ fluidization mining of oil shale.

Multidimensional sleep trait, which is related to circadian rhythms closely, affects some cancers predominantly, while the relationship between sleep and lung cancer is rarely illustrated. We aimed to investigate whether sleep is causally associated with risk of lung cancer, through a two-sample Mendelian randomization study. The main analysis used publicly available GWAS summary data from two large consortia (UK Biobank and International Lung Cancer Consortium). Two-sample Mendelian randomization (MR) analysis was used to examine whether chronotype, getting up in the morning, sleep duration, nap during the day, or sleeplessness was causally associated with the risk of lung cancer. Additionally, multivariate MR analysis was also conducted to estimate the direct effects between sleep traits and lung cancer risks independent of smoking status including pack years of smoking or current tobacco smoking. There was no evidence of causal association between chronotype, getting up in the morning, or nap during the day and lung cancer. Sleeplessness was associated with higher risk of lung adenocarcinoma (odds ratio 5.75, 95% confidence intervals 2.12-15.65), while sleep duration played a protective role in lung cancer (0.46, 0.26-0.83). In multivariate MR analysis, sleeplessness and sleep duration remained to have similar results. In conclusion, we found robust evidence for effect of sleeplessness on lung adenocarcinoma risk and inconsistent evidence for a protective effect of sleep duration on lung cancer risk.

Acid mine drainage (AMD) is a hazardous by-product of coal mining, which may intensify the creep deformation of cemented gangue backfill (CGB) in solid backfill mining. In this study, the long-term stability and creep property of CGB soaked in AMD were quantitatively measured by experimental and theoretical analysis. The uniaxial compressive strength, elastic modulus, and mass of CGB soaked in AMD, with pH of 5.56 and soaking time of 30 to 360 days, were tested. The change trend of compressive strength, elasticity modulus, and mass first increased, then decreased, and finally ended at 94.37%, 96.68%, and 98.00%, respectively. The respective creep processes of CGB soaked in AMD and untreated CGB were similar, initial creep stage lasted only for a short time, and no creep deformation occurred in the steady creep stage. Moreover, the long-term strength of CGB soaked in AMD was 98.6% of the untreated CGB. The creep law of the CGB soaked in AMD was accurately fitted by using the Kelvin model. The theoretical analysis revealed that the final creep deformation of the CGB column soaked in AMD was only 4.4 mm. The results of this paper show the possibility of using CGB in AMD-accumulating goaf.

Icing/snowing/frosting is ubiquitous in nature and industrial processes, and the accretion of ice mostly leads to catastrophic consequences. The existing understanding of icing is still limited, particularly for aircraft icing, where direct observation of the freezing dynamics is inaccessible. In this work, we investigate experimentally the impact and freezing of a water drop onto the supercooled substrate at extremely low vapor pressure, to mimic an aircraft passing through clouds at a relatively high altitude, engendering icing upon collisions with pendant drops. Special attention is focused on the ice coverage induced by an impinging drop, from the perimeter pointing outward along the radial direction. We observed two freezing regimes: (I) spread-recoil-freeze at the substrate temperature of Ts = −15.4 ± 0.2 °C and (II) spread (incomplete)-freeze at the substrate temperature of Ts = −22.1 ± 0.2 °C. The ice coverage is approximately one order of magnitude larger than the frozen drop itself, and counterintuitively, larger supercooling yields smaller ice coverage in the range of interest. We attribute the variation of ice coverage to the kinetics of vapor diffusion in the two regimes. This fundamental understanding benefits the design of new anti-icing technologies for aircraft.

Spontaneous combustion of coal is one of the major hazards threatening production safety during longwall mining. Mining-induced voids, which provide passages for air leakage, are the key factor triggering spontaneous combustion of coal in longwall goafs. In this study, a comprehensive method, which combined pressure balance, grouting injection, and filling fissures, was proposed to prevent spontaneous combustion of coal in longwall goafs with complex air leakage. Field engineering practice was carried out in Sitai Coal Mine in China. The results demonstrated that with the application of the proposed method, in the working face, the concentration of CO was decreased from 31ppm to 0 and the air leakage quantity was decreased from 261 to below 80 m3min-1. The gas samples analysis from the gob areas also indicated that concentrations of O2 and CO were successively decreased, indicating that the risk of spontaneous combustion of coal in goafs was eliminated. The above mentioned analysis indicates that, the method proposed in this study is useful and efficient. Successful application of this technology could provide reference for the treatment of other coal mines.

With the explosive demand for wireless communications, users are always experiencing poor quality-of-services. Spectrum auction is a promising approach to allocate spectrum resources in wireless networks. Most of the previous works ignored social characteristics of users in wireless networks which influence the allocation of spectrum resources. In this article, we study the spectrum auction problem in a femtocell network and jointly exploit the social reciprocity of users for optimizing the allocation of spectrum resources. We propose an auction incentive framework combined with social reciprocity in the femtocell network. Such a matter is formulated as an integer programming optimization problem, and a modified quantum genetic algorithm is developed to solve the optimization problem. Besides we propose a payment rule satisfying truthfulness and individual rationality properties. Simulation results show that our algorithm can achieve the optimal solution to the optimization problem.

The vortex electromagnetic (EM) wave with orbital angular momentum (OAM) brings a new degree of freedom for synthetic aperture radar (SAR) imaging, although to date, its application to multi-input multi-output (MIMO) SAR has not yet been widely reported. In this paper, an orbital angular momentum (OAM)-based MIMO-SAR system is proposed. The rotational Doppler Effect (RDE) of vortex EM waves offers a novel scheme for an OAM-based MIMO-SAR system. By transmitting the rotational vortex EM waves, echoes of different OAM modes can be discriminated by a bandpass filter in the range-Doppler domain. The performance of the proposed scheme is independent of the time-variant channel responses, and the wider beam width of the vortex EM waves delivers, for the same antenna aperture size, better performance in terms of swath width and azimuth resolution, in contrast to the plane EM waves. Moreover, the spatial diversity of vortex EM waves shows great potential to enhance the MIMO-SAR system applications, which involve high-resolution wide-swath remote sensing, 3-D imaging, and radar-communication integration. The proposed scheme is verified by proof-of-concept experiments. This work presents a new application of vortex EM waves, which facilitates the development of new-generation and forthcoming SAR systems.

In this work, a methodology for characterizing reservoir pore pressure and permeability during underbalanced drilling of horizontal wells was presented. The methodology utilizes a transient multiphase wellbore flow model that is extended with a transient well influx analytical model during underbalanced drilling of horizontal wells. The effects of the density behavior of drilling fluid and wellbore heat transfer are considered in our wellbore flow model. Based on Kneissl’s methodology, an improved method with a different testing procedure was used to estimate the reservoir pore pressure by introducing fluctuations in the bottom hole pressure. To acquire timely basic data for reservoir characterization, a dedicated fully automated control real-time data monitoring system was established. The methodology is applied to a realistic case, and the results indicate that the estimated reservoir pore pressure and permeability fit well to the truth values from well test after drilling. The results also show that the real-time data monitoring system is operational and can provide accurate and complete data set in real time for reservoir characterization. The methodology can handle reservoir characterization during underbalanced drilling of horizontal wells.

With the rapid development and integration of biomedicine and information technology,massive amounts of imaging data,patient report data,electronic health records,and omics data have been accumulated rapidly in healthcare.These data are cha-racterized by complexity,heterogeneity and high dimensionality.Deep learning has the ability of complex function simulation and automatic feature learning,which can provide efficient technical support for research in medical diagnosis and drug development.Currently,deep learning has been extremely successful in medical imaging and further more,some medical imaging diagnostic systems based on deep learning have achieved performance that is even comparable to that of relevant experts.Due to the progress of natural language processing technology,deep learning has also made remarkable progress in the use of non-image data tasks.This paper first briefly describes the development of deep learning in healthcare.Subsequently,the application of deep learning model in healthcare is statistically analyzed,and some available datasets are sorted out.In addition,this paper also introduces the research progress of deep learning in medical diagnosis and treatment processes such as disease diagnosis and health monitoring,and its research progress in protein structure prediction and drug discovery.Finally,key challenges of deep learning in healthcare applications such as data quality,interpretability,privacy security and practical application limitations are discussed.It also discusses feasible solutions or approaches to these challenges.