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Analyzing rock mass seepage using the discrete fracture network (DFN) flow model poses challenges when dealing with complex fracture networks. This paper presents a novel DFN flow model that incorporates the actual connections of large-scale fractures. Notably, this model efficiently manages over 20,000 fractures without necessitating adjustments to the DFN geometry. All geometric analyses, such as identifying connected fractures, dividing the two-dimensional domain into closed loops, triangulating arbitrary loops, and refining triangular elements, are fully automated. The analysis processes are comprehensively introduced, and core algorithms, along with their pseudo-codes, are outlined and explained to assist readers in their programming endeavors. The accuracy of geometric analyses is validated through topological graphs representing the connection relationships between fractures. In practical application, the proposed model is employed to assess the water-sealing effectiveness of an underground storage cavern project. The analysis results indicate that the existing design scheme can effectively prevent the stored oil from leaking in the presence of both dense and sparse fractures. Furthermore, following extensive modification and optimization, the scale and precision of model computation suggest that the proposed model and developed codes can meet the requirements of engineering applications.

Abstract Background Study objectives included the development of a practical nomogram for predicting live birth following frozen-thawed embryo transfers in ovulatory women. Methods Totally, 2884 patients with regular menstrual cycles in our center were retrospectively enrolled. In an 8:2 ratio, we randomly assigned patients to training and validation cohorts. Then we identified risk factors by multivariate logistic regression and constructed nomogram. Finally, receiver operating characteristic curve analysis, calibration curve and decision curve analysis were performed to assess the calibration and discriminative ability of the nomogram. Results We identified five variables which were related to live birth, including age, anti-Müllerian hormone (AMH), protocol of frozen-thawed embryo transfer (FET), stage of embryos and amount of high-quality embryos. We then constructed nomograms that predict the probabilities of live birth by using those five parameters. Receiver operating characteristic curve analysis (ROC) showed that the area under the curve (AUC) for live birth was 0.666 (95% CI: 0.644–0.688) in the training cohort. The AUC in the subsequent validation cohorts was 0.669 (95% CI, 0.625–0.713). The clinical practicability of this nomogram was demonstrated through calibration curve analysis and decision curve analysis. Conclusions Our nomogram provides a visual and simple tool in predicting live birth in ovulatory women who received FET. It could also provide advice and guidance for physicians and patients on decision-making during the FET procedure.

Building change detection (BCD) aims to identify new or disappeared buildings from bitemporal images. However, the varied scales and appearances of buildings, along with the challenge of pseudochange interference from complex backgrounds, make it difficult to accurately extract complete changes. To address these challenges in BCD, a U-shaped hybrid Siamese network combining a convolutional neural network and a vision transformer (CNN-ViT) with learnable mask guidance, called U-Conformer, is designed. First a new hybrid architecture of U-Conformer is proposed. The architecture integrates the strengths of CNNs and ViTs to establish a robust, multiscale heterogeneous representation that aids in detecting buildings of various sizes. Second, a learnable mask guidance module is specifically designed for U-Conformer, focusing the multiscale heterogeneous representation on extracting relevant scale changes while progressively suppressing pseudochanges. Furthermore, for the U-Conformer architecture, a mask information joint class-balanced loss function that combines the binary cross-entropy loss function and the dice loss function is devised, significantly mitigating the issue of class imbalance. Experimental results on three publicly available change detection datasets, LEVIR-CD, WHU-CD, and GZ-CD, demonstrate that U-Conformer surpasses previous methods, achieving F1 scores of 91.5%, 94.6%, and 86.7%, as well as IoU scores of 84.3%, 89.7%, and 76.5% on the LEVIR-CD, WHU-CD, and GZ-CD datasets, respectively.

With the development of information and cloud technology, the dynamic demand for OTN service is gradually increasing.As a next generation OTN switching technology, OSU needs to provide network and cloud services for high-quality enterprise leased lines and boutique home broadband services.The OSU-based OTN needs to be able to provide integrated services and automated service provisioning through end-to-end management and control capabilities to support one-hop service into the cloud.Firstly, the background, technical characteristics, and standardization progress of OSU technology were introduced.Then, a service-aware control framework for OSU-OTN was proposed to meet the demand for efficient bearer of government and enterprise leased lines.Finally, an experimental validation of the end-to-end management and control capability of the access OSU-OTN controller system was carried out.

Background: Gestational diabetes mellitus (GDM) is a serious complication of pregnancy that is characterized by high blood sugar levels that occur due to insulin resistance and dysfunction in glucose metabolism during pregnancy. It usually develops in the second or third trimester of pregnancy and affects about 7 % of all pregnancies worldwide. In this experimental study, we scrutinized the GDM protective effect of soy isolate protein against streptozotocin (STZ) induced GDM in rats and explore the underlying mechanism. Material and methods: Sprague-Dawley (SD) rats were used in this experimental study. A 55 mg/kg intraperitoneal injection of streptozotocin (STZ) was administered to induce diabetes in female rats, followed by oral administration of soy isolate protein for 18 days. Body weight, glucose levels, and insulin were measured at different time intervals (0, 9, and 18 days). Lipid profiles, antioxidant levels, inflammatory cytokines, apoptosis parameters, and mRNA expression were also assessed. Pancreatic and liver tissues were collected for histopathological examination during the experimental study. Results: Soy isolate protein significantly (P

Abstract A cataclastic rock mass is a poor type of engineering geological rock mass. The determination of the shear failure characteristics and shear strengths of cataclastic rock masses can provide key basis for the design and construction of infrastructure. Physical model samples of a sandstone cataclastic rock mass were first produced by a combination of three-dimensional (3D) printing technology and manual pouring. Shear tests were conducted with respect to the shear stresses parallel to the trace line plane and perpendicular to the trace line plane of the cataclastic rock mass model. Based on an extensive analysis of the shear failure characteristic, shear stress evolution characteristic curve and shear strength. When the shear stress was parallel to the trace line plane, and when the rock block that was cut and confined by the trace line exhibited a significant tip, the end stress concentration effect of the cataclastic rock mass was more significant during the shear process with the anisotropy of the rock block increased. In addition, the shapes of the rock blocks that were confined and cut by the joints were the main influencing factors of the strength of the cataclastic rock mass. When the shear stress was perpendicular to the trace line plane, the structure of the rock wall was the main influencing factor of the deformation and failure process of the shear failure plane and the shear strength. The physical and mechanical properties of the shear failure plane of the cataclastic rock mass were found to be closely related to the joint–rock wall system characteristics of the cataclastic rock mass. Therefore, when determining the shear strength of cataclastic rock mass, the shape and combination form of the rock block, shear direction, and structural failure characteristics of the rock wall should be comprehensively considered during the shear process.

Abstract Understanding the shear strength degradation mechanism of a rock mass joint surface under cyclic shear load and determining a corresponding analytical model is an important foundation for accurately evaluating the safety of rock mass engineering under seismic loads. It is worth noting that, to date, there has been a dearth of studies on the strength characteristics of joint surfaces that consider the number of loading cycles, normal load, and initial undulant angle of the structural plane. In this study, focused on the behaviour of sandstone, the particle flow code (PFC) modelling framework was used to simulate a joint surface cyclic shear test considering first- and second-order undulations. Based on the experimental results, the comprehensive effects of the number of cyclic shear cycles, the normal stress, first- and second-order undulation and the dilatancy angle on shear stress during cyclic shear were analysed. Formulas for the joint surface shear basic friction angle and dilatancy angle under cyclic shear were proposed, and a method for calculating the joint surface peak shear strength under cyclic shear considering the deterioration of the dilatancy angle and basic friction angle was established. The peak shear strength of a sample after five cycles of shearing was calculated using the proposed formula and compared with the results of numerical simulations, the Barton method, and the Homand method. The results showed that the calculated values have good consistency with the results of the numerical simulations, demonstrating the effectiveness and accuracy of the proposed formula. However, under a low normal stress, there could be errors in estimating the cyclic shear strength of the joint surface.

Abstract Accurately determining the shear strength of structural planes is crucial for evaluating the stability of rock masses. The shear test using the sawtooth structural plane usually captures the main influencing factors of its shear characteristics. In this study, the two-dimensional particle flow code (PFC2D) numerical simulation method was used to conduct shear tests on the sawtooth structural planes of rock masses with undulant angles of 10°, 20°, and 30°, respectively. With the increase in normal stress and the undulant angle, the shear failure of the structural planes was found to no longer be pure slip failure or shear failure but accompanied by a compression-induced fracture phenomenon. Based on the analysis of the shear test results, a peak shear strength model considering different undulant angles and normal stresses was proposed, and the hyperbolic function post-peak shear strength model was improved. The peak shear strength obtained from the physical direct shear tests was compared with those calculated using the proposed model, Parton model, and Shen model. The calculation error under low and high normal stress of the proposed method was found to be within an acceptable range. Additionally, when calculating the peak shear strength of a structural plane under high normal stress, applying the calculation method proposed in this study is a better option than applying the other models. Furthermore, although the variation trend of the post-peak shear strength was similar to that of the experimental results, the values obtained using the hyperbolic variation model were too large. The variation trend of the post-peak shear strength obtained using the improved function was essentially consistent with the experimental results, and the calculated values were close to the experimental results. The systematic research on the shear strength calculation model of rock mass structural planes contributes to the theoretical research of rock mass mechanics, and this study can act as a guide for landslide prediction and control projects.

Abstract When a rock mass shears along a joint surface, the shear resistance is affected by joint surface undulations and friction between the contact regions. During an earthquake, the seismic load causes dynamic deterioration of the joint surface mechanical properties, mostly reflected as follows. (1) The peak shear strength of the joint surface decreases with an increase in the shear rate. (2) Under a seismic load cyclic shear, the undulant angle α k decreases. (3) Under a dynamic load, the friction coefficient of the joint surface is reduced. By studying the cyclic shear test of the joint surface, the strength deterioration effect of the joint surface under cyclic shearing is first analysed, and the equations of the dilatation angle and the basic friction angle of the joint surface under the cyclic shearing load are proposed. Then, starting with the effect of cyclic shear deterioration on the joint surface in the rock mass and the reduction in the dynamic friction coefficient between sliding rock blocks caused by relative velocity, an equation for calculating the shear strength of a rock mass joint surface under cyclic shear loading is recommended. Through two case calculations, the shear strength obtained using the proposed method is compared with the experimental results. The results show that the model proposed in this study is in good agreement with the experimental results and can also be used to calculate the structural surface shear strength of the asperity-rich sample. However, when the calculation equation is used to estimate the cyclic shear strength of the joint surface where the sum of the initial undulation angle and the basic friction angle is greater than 70°, there may be some errors in the calculation results.

The mechanism of seismic-induced bedding rock landslide is distinct from that of slope instability/landslide in normal gravity conditions; their failure modes are mainly characterized by vibration deterioration effect of rock mass structural plane due to a seismic loading, which has a significant effect on the stability of the bedding rock landslide. Several advanced methods have been proposed to assess earthquake-induced bedding rock landslide. However, the quantitative evaluation of the vibration deterioration effect of structural plane, along with its application in the dynamic stability analysis of bedding rock slopes, remains a challenging topic that requires further study. In this study, on the basic of the analysis of the cyclic shear condition and the cyclic shear test of the structural plane, the expressions to calculate the dilatancy angle and basic friction angle of structural plane under cyclic shear loading are studied. A deterioration formula for structural plane shear strength is proposed, which fully considers the deterioration effect during cyclic shear. Furthermore, a new calculating method of the seismic-induced permanent displacement of the bedding rock landslide, which introduces the deterioration effect of the structural plane, is developed. A case study was used to compare the permanent displacement calculated with the proposed method with those obtained using the Newmark and Qi methods, which demonstrates the effectiveness and applicability of the proposed method.

Abstract Background This study aims to examine the cross-sectional association between serum total bilirubin (STB) and type 2 diabetes (T2D) risk in the general population, and whether obesity could moderate this association. Methods We used data from the 1999–2018 National Health and Nutrition Examination Surveys (NHANES), including a total of 38,641 US adult participants who were 18 years or older. The STB was classified as the low, moderate, and high groups according to tertiles. Results We found that participants with lower STB had a significantly higher risk of T2D than those with moderate (OR = 0.81; 95% CI 0.74, 0.89; P

Objectives: To assess the association of road traffic noise exposure with Type 2 Diabetes (T2D) risk, and to explore the potential moderation effect of obesity.Methods: A total of 305,969 participants from the UK Biobank Cohort - an open access cohort of 500,000 participants recruited in the United Kingdom (UK) between 2006 and 2010 - were included in the study. A Cox proportional hazard model was fitted to assess the association between road traffic noise exposure and T2D.Results: A total of 19,303 participants were diagnosed with T2D during the 11.9-year median follow-up period. For every 10 dB increase in road traffic noise, there was a 4% increase in T2D risk (HR = 1.04, 95%CI: 1.01, 1.07). Besides, a significant positive interaction was observed between obesity and road traffic noise (P interaction

Abstract Clock genes not only regulate the circadian rhythm of physiological activities but also participate in the pathogenesis of many diseases. Previous studies have documented the abnormal expression of clock genes in epilepsy. However, the molecular mechanism of brain and muscle Arnt-like protein 1 (Bmal1), one of the core clock genes, in the epileptogenesis and seizures of temporal lobe epilepsy (TLE) remain unclear. We first investigated the levels of Bmal1 and other clock proteins in the hippocampus of subjects with epilepsy to define the function of Bmal1. The levels of Bmal1 were decreased during the latent and chronic phases in the experimental group compared with those in the control group. Knockout of Bmal1 in hippocampal dentate gyrus (DG) neurons of Bmal1flox/flox mice by Synapsin 1 (Syn1) promoter AAV (adeno-associated virus) lowered the threshold of seizures induced by pilocarpine administration. High-throughput sequencing analysis showed that PCDH19 (protocadherin 19), a gene associated with epilepsy, was regulated by Bmal1. PCDH19 expression was also decreased in the hippocampus of epileptic mice. Furthermore, the higher levels of Bmal1 and PCDH19 were detected in patients with no hippocampal sclerosis (no HS) than in patients with HS International League Against Epilepsy (ILAE) type I and III. Altogether, these data suggest that decreased expression of clock gene Bmal1 may participate in epileptogenesis and seizures via PCDH19 in TLE.

Change detection is a critical task in remote sensing Earth observation for identifying changes in the Earth’s surface in multi-temporal image pairs. However, due to the time-consuming nature of image collection, labor-intensive pixel-level labeling with the rare occurrence of building changes, and the limitation of the observation location, it is difficult to build a large, class-balanced, and diverse building change detection dataset, which can result in insufficient changed sample pairs for training change detection models, thus degrading their performance. Thus, in this article, given that data scarcity and the class-imbalance issue lead to the insufficient training of building change detection models, a novel multi-temporal sample pair generation method, namely, Image-level Sample Pair Generation (ISPG), is proposed to improve the change detection performance through dataset expansion, which can generate more valid multi-temporal sample pairs to overcome the limitation of the small amount of change information and class-imbalance issue in existing datasets. To achieve this, a Label Translation GAN (LT-GAN) was designed to generate complete remote sensing images with diverse building changes and background pseudo-changes without any of the complex blending steps used in previous works. To obtain more detailed features in image pair generation for building change detection, especially the surrounding context of the buildings, we designed multi-scale adversarial loss (MAL) and feature matching loss (FML) to supervise and improve the quality of the generated bitemporal remote sensing image pairs. On the other hand, we also consider that the distribution of generated buildings should follow the pattern of human-built structures. The proposed approach was evaluated on two building change detection datasets (LEVIR-CD and WHU-CD), and the results proved that the proposed method can achieve state-of-the-art (SOTA) performance, even if using plain models for change detection. In addition, the proposed approach to change detection image pair generation is a plug-and-play solution that can be used to improve the performance of any change detection model.

A plate-type Al/Fe–Cr alloy/Al-clad substrate was used to prepare a sandwich-structured plate-type anodic alumina catalyst by anodization, post-modification treatment, and metal loading. The as-prepared plate-type catalyst was utilized in the design of a catalytic plate reactor for a methane steam reforming reaction, and a 3D model was developed to simulate the performance of tube-type and box-type reformers. The experimental results of the preparation of the clad materials showed that the hydrothermal treatment and subsequent high-temperature calcination transformed the amorphous skeletal alumina in the conventional anodic alumina layer into γ-alumina, and significantly increased its specific surface area. Simulation results showed that the temperature difference between the channel wall and the center of the gas phase of the thin-walled catalyst was only 30% of that of the particulate catalyst, indicating the potential advantages of the catalytic plate reactor in terms of heat transfer and energy saving. When the length-to-diameter ratio (or length-to-width ratio) of the reaction channel is small and the channel height is large, insufficient transverse mass transfer and backmixing are two major factors affecting reformer performance. For the tube-type channels, a length-to-diameter ratio of 10~35, and a diameter of 5~20 represent favorable choices. In contrast, for the box-type channel, the length-to-width ratio and the height should be set to 2~4 and 2~5 mm, respectively. Additionally, for box-type channels, the number of gas inlet ports has a significant effect on the reformer performance, and the distribution state provided by two inlet ports is close to the ideal distribution state.

Development of very-high-resolution (VHR) remote sensing imaging platforms have resulted in a requirement for developing refined land cover classification maps for various applications. Therefore, aiming at exploring the accurate boundary and complex interior texture retrieval in VHR optical remote sensing images, a novel detail injection network (DI-Net) is proposed in this article, which is composed of three aspects. First, the decoupling refinement module embedded with a multiscale representation is designed to improve the feature extraction capabilities that precede the encoding-to-decoding process. Second, we pay attention to the hard examples of boundary and complex interior texture in land cover classification and design two detail injection attention modules to solve the feature inactivation phenomenon in gradually convolutional encoding-to-decoding process. Third, a specific stage grading loss is proposed to adaptively regulate the structural-level weights of the encoding and decoding stages, which facilitates the details retrieval and produce refined land cover classification results. Finally, various datasets [incl. International Society for Photogrammetry and Remote Sensing (ISPRS) and Gaofen Image Dataset (GID)] are employed to demonstrate that the proposed DI-Net achieves better performance than state-of-the-art methods. DI-Net provides more accurate boundaries and more consistent interior textures, and it achieves 86.86% PA and 68.37% mIoU on ISPRS dataset as well as 77.04% PA and 64.38% mIoU on GID dataset, respectively.

With the rapid development of global trade, the turnover of shipping containers has increased rapidly. How to use port resources reasonably and efficiently has become one of the main challenges that ports need to deal with when planning for the future. In order to develop scientific and efficient berth plans to improve operational efficiency and service level, this paper proposes a hybrid prediction model based on Principal Component Analysis (PCA) and Extreme Learning Machine (ELM) optimized by Improved Particle Swarm Optimization (IPSO), namely, the PCA-IPSO-ELM model. After assessing the uncertain factors influencing the operation time of the container ship at berth, this work reduces the dimensionality of the investigational data by the PCA method. Aiming to solve easy premature convergence of the traditional particle swarm algorithm, this paper introduces an improved particle swarm optimization algorithm via dynamic adjustment of nonlinear parameters. This improved particle swarm algorithm is mainly used to optimize the weights and thresholds of the extreme learning machine. Thus, a PCA-IPSO-ELM model which aims to forecast the operation time of a container ship at berth, is constructed. Using the historical operation data of the Tianjin Port Container Shipping Company as the prediction sample, this PCA-IPSO-ELM model is compared and assessed with traditional models. The results show that compared with other models, the PCA-IPSO-ELM prediction model has the characteristics of high prediction accuracy, fast running rate and strong stability, and it has a higher coefficient of determination and a better fitting degree.

Purpose: To report complications after epilepsy surgery, grade the severity of complications, investigate risk factors, and develop a nomogram for risk prediction of complications.Methods: Patients with epilepsy surgery performed by a single surgeon at a single center between October 1, 2003 and April 30, 2019 were retrospectively analyzed. Study outcomes included severity grading of complications occurring during the 3-month period after surgery, risk factors, and a prediction model of these complications. Multivariable logistic regression analysis was used to calculate odds ratio and 95% confidence interval to identify risk factors.Results: In total, 2,026 surgical procedures were eligible. There were 380 patients with mild complications, 23 with moderate complications, and 82 with severe complications. Being male (odds ratio 1.29, 95% confidence interval 1.02–1.64), age at surgery (>40 years: 2.58, 1.55–4.31; ≤ 40: 2.25, 1.39–3.65; ≤ 30: 1.83, 1.18–2.84; ≤ 20: 1.71, 1.11–2.63), intracranial hemorrhage in infancy (2.28, 1.14–4.57), serial number of surgery ( ≤ 1,000: 1.41, 1.01–1.97; ≤ 1,500: 1.63, 1.18–2.25), type of surgical procedure (extratemporal resections: 2.04, 1.55–2.70; extratemporal plus temporal resections: 2.56, 1.80–3.65), surgery duration (>6 h: 1.94, 1.25–3.00; ≤ 6: 1.92, 1.39–2.65), and acute postoperative seizure (1.44, 1.06–1.97) were independent risk factors of complications. A nomogram including age at surgery, type of surgical procedure, and surgery duration was developed to predict the probability of complications.Conclusions: Although epilepsy surgery has a potential adverse effect on the patients, most complications are mild and severe complications are few. Risk factors should be considered during the perioperative period. Patients with the above risk factors should be closely monitored to identify and treat complications timely. The prediction model is very useful for surgeons to improve postoperative management.

BackgroundIt has been shown that circular RNAs (circRNAs) play a vital role in the progression of glioma. Recently, hsa_circ_0001836 was found to be upregulated in glioma tissues, but the role of hsa_circ_0001836 in glioma remains unclear.MethodsEdU staining and flow cytometry assays were used to measure the viability and death of glioma cells. In addition, scanning electron microscopy (SEM) was used to observe the morphology of cells undergoing cell death.ResultsHsa_circ_0001836 expression was upregulated in U251MG and SHG-44 cells. In addition, hsa_circ_0001836 knockdown significantly reduced the viability and proliferation of U251MG and SHG-44 cells. Moreover, hsa_circ_0001836 knockdown markedly induced the pyroptosis of U251MG and SHG-44 cells, evidenced by the increased expressions of NLRP1, cleaved caspase 1 and GSDMD-N. Meanwhile, methylation specific PCR (MSP) results indicated that hsa_circ_0001836 knockdown epigenetically increased NLRP1 expression via mediating DNA demethylation of NLRP1 promoter region. Furthermore, downregulation of hsa_circ_0001836 notably induced pyroptosis and inhibited tumor growth in a mouse xenograft model of glioma.ConclusionCollectively, hsa_circ_0001836 knockdown could induce pyroptosis cell death in glioma cells in vitro and in vivo via epigenetically upregulating NLRP1 expression. These findings suggested that hsa_circ_0001836 may serve as a potential therapeutic target for the treatment of glioma.

Secoisolariciresinol diglucoside (SDG) is the main component of flax lignans. Current studies have reported a positive effect of SDG on obesity and metabolic diseases. SDG has strong blood fat- and blood sugar-lowering, anti-inflammatory, and antioxidant effects and prevents heart disease and other chronic diseases. In this study, we explored the effects of SDG on Western diet-induced obesity and lipid metabolic disorder. Supplementing Western diet-induced obese mice with 40 mg kg1 d1, SDG for 12 weeks significantly reduced body and tissue weights. Increased adiponectin levels and decreased serum leptin and resistin levels were observed in obese mice orally administered SDG. Proliferation of adipose tissue was observed by hematoxylin and eosin staining, and cell size was quantitatively analyzed. As a result, SDG inhibited the proliferation of adipose tissue. In addition, SDG suppressed the mRNA expression of lipid synthetic genes and upregulated the mRNA expression of lipolytic genes. Overall, these results indicate that SDG inhibits obesity induced by a Western diet and regulates adipose tissue metabolic disorder. These results provide a theoretical basis for further study on the regulation of obesity and lipid metabolic disorder caused by SDG.

Building extraction using very high resolution (VHR) optical remote sensing imagery is an essential interpretation task that impacts human life. However, buildings in different environments exhibit various scales, complicated spatial distributions, and different imaging conditions. Additionally, with the spatial resolution of images increasing, there are diverse interior details and redundant context information present in building and background areas. Thus, the above-mentioned situations would create large intra-class variances and poor inter-class discrimination, leading to uncertain feature descriptions for building extraction, which would result in over- or under-extraction phenomena. In this article, a novel hierarchical disentangling network with an encoder–decoder architecture called HDNet is proposed to consider both the stable and uncertain feature description in a convolution neural network (CNN). Next, a hierarchical disentangling strategy is set up to individually generate strong and weak semantic zones using a newly designed feature disentangling module (FDM). Here, the strong and weak semantic zones set up the stable and uncertain description individually to determine a more stable semantic main body and uncertain semantic boundary of buildings. Next, a dual-stream semantic feature description is built to gradually integrate strong and weak semantic zones by the designed component feature fusion module (CFFM), which is able to generate a powerful semantic description for more complete and refined building extraction. Finally, extensive experiments are carried out on three published datasets (i.e., WHU satellite, WHU aerial, and INRIA), and the comparison results show that the proposed HDNet outperforms other state-of-the-art (SOTA) methods.

Summary: Gene expression levels vary across developmental stage, cell type, and region in the brain. Genomic variants also contribute to the variation in expression, and some neuropsychiatric disorder loci may exert their effects through this mechanism. To investigate these relationships, we present BrainVar, a unique resource of paired whole-genome and bulk tissue RNA sequencing from the dorsolateral prefrontal cortex of 176 individuals across prenatal and postnatal development. Here we identify common variants that alter gene expression (expression quantitative trait loci [eQTLs]) constantly across development or predominantly during prenatal or postnatal stages. Both “constant” and “temporal-predominant” eQTLs are enriched for loci associated with neuropsychiatric traits and disorders and colocalize with specific variants. Expression levels of more than 12,000 genes rise or fall in a concerted late-fetal transition, with the transitional genes enriched for cell-type-specific genes and neuropsychiatric risk loci, underscoring the importance of cataloging developmental trajectories in understanding cortical physiology and pathology. : Werling et al. analyze gene expression across the span of human cerebral cortical development and profile the trajectories of individual genes, coordinated groups of genes, and their relationships to disorders. Integration of genetic variation identifies quantitative trait loci that implicate specific genes in loci associated with neuropsychiatric traits and disorders. Keywords: dorsolateral prefrontal cortex, DLPFC, fetal transition, BrainVar, PsychENCODE, prenatal eQTL, RHEBL1, mTOR, LOC101926933 RP11-298I3.1 AL132780.1 ENSG00000257285

Abstract Brain hypometabolism is a common epilepsy-related finding in both patients and animal models. Fluorodeoxyglucose positron emission tomography studies have shown that recurrent seizures lead to reduced glucose metabolism in certain brain regions, but no studies have definitively determined whether this induces epileptogenesis. There is evidence that acid-sensing ion channel 2a (ASIC2a) affects epilepsy susceptibility. Transcription factor CP2 (TFCP2) regulates ASIC2a expression. We report that suppressed TFCP2 expression and elevated ASIC2a expression were associated with glucose hypometabolism in the hippocampi of humans with epilepsy and of rat epilepsy model brains. In cultured PC12 cells, we determined that glucose deficiency led to TFCP2 downregulating ASIC2a. Moreover, electrophysiological recordings from cultured rat hippocampal slices showed that ASIC2a overexpression resulted in more action potentials in CA1 pyramidal neurons and increased seizure susceptibility. Our findings suggest that hippocampal glucose hypometabolism elevates ASIC2a expression by suppressing TFCP2 expression, which further enhances the intrinsic excitability of CA1 pyramidal neurons and increases seizure susceptibility in patients with temporal lobe epilepsy.

Summary: We previously established the contribution of de novo damaging sequence variants to Tourette disorder (TD) through whole-exome sequencing of 511 trios. Here, we sequence an additional 291 TD trios and analyze the combined set of 802 trios. We observe an overrepresentation of de novo damaging variants in simplex, but not multiplex, families; we identify a high-confidence TD risk gene, CELSR3 (cadherin EGF LAG seven-pass G-type receptor 3); we find that the genes mutated in TD patients are enriched for those related to cell polarity, suggesting a common pathway underlying pathobiology; and we confirm a statistically significant excess of de novo copy number variants in TD. Finally, we identify significant overlap of de novo sequence variants between TD and obsessive-compulsive disorder and de novo copy number variants between TD and autism spectrum disorder, consistent with shared genetic risk. : Wang et al. expand their earlier exome-sequencing work in TD, adding 291 trios and conducting combined analyses suggesting de novo variants carry more risk in individuals with unaffected parents, establishing de novo structural variants as risk factors, identifying CELSR3 as a risk gene, and implicating cell polarity in pathogenesis. Keywords: Tourette disorder, simplex, multiplex, de novo variants, copy number variants, whole exome sequencing, microarray genotyping, gene discovery, cell polarity, TIC Genetics

The RNA synthesis of porcine reproductive and respiratory syndrome virus (PRRSV), a positive-strand RNA virus, is compartmentalized in virus-induced double-membrane vesicles where viral proteins and some cellular proteins assemble into replication and transcription complexes (RTCs). The viral replicase proteins are the major components of the RTCs but the physical associations among these non-structural proteins (nsps) remain elusive. In this study, we investigated the potential interactions between PRRSV nsps by yeast two-hybrid (Y2H), bimolecular fluorescence complementation (BiFC) and pull-down assays. Our analyses revealed a complex network of interactions involving most of PRRSV nsps. Among them, nsp9 and nsp12 were identified as the hubs of the nsp interactome; transmembrane proteins nsp2 and nsp5 both interacted with nsp3, indicating that the three membrane-bound proteins might bind together to form the scaffold to support the association of RTCs with the intracellular membrane. The PRRSV nsp interactions identified in this study may provide valuable clues for future researches on the RTC formation and function.

The significance of maternal cholesterol transporting to the fetus under normal as well as pathological circumstances is less understood. The objective of this study was to observe the effects of maternal hypercholesterolemia on placental cholesterol transportation. Human full-time placenta, maternal and venous cord blood were sampled at delivery from the pregnant women with serum total cholesterol (TC) concentrations at third trimester higher than 7.25 mM (n = 19) and the pregnant women with normal TC concentrations (n = 19). Serum lipids and expression of genes related to cholesterol transportation were measured by western blot or real-time PCR. The results indicated that serum TC, high density lipoprotein cholesterol (HDL-C), and low density lipoprotein cholesterol (LDL-C) levels were significantly increased, in pregnancies, but decreased in cord blood in hypercholesterolemic group compared to the matched control group. All the subjects were no-drinking, non-smoker, and gestational disease free. The mRNA expression of lipoprotein receptors, including LDLR and VLDLR were significantly increased, while the protein expression of PCSK9 was significantly increased in hypercholesterolemic placenta. In conclusion, maternal hypercholesterolemia might decrease the transportation of cholesterol from mother to fetus because of the high levels of PCSK9 protein expression.

Summary: Whole-exome sequencing (WES) studies have demonstrated the contribution of de novo loss-of-function single-nucleotide variants (SNVs) to autism spectrum disorder (ASD). However, challenges in the reliable detection of de novo insertions and deletions (indels) have limited inclusion of these variants in prior analyses. By applying a robust indel detection method to WES data from 787 ASD families (2,963 individuals), we demonstrate that de novo frameshift indels contribute to ASD risk (OR = 1.6; 95% CI = 1.0–2.7; p = 0.03), are more common in female probands (p = 0.02), are enriched among genes encoding FMRP targets (p = 6 × 10−9), and arise predominantly on the paternal chromosome (p < 0.001). On the basis of mutation rates in probands versus unaffected siblings, we conclude that de novo frameshift indels contribute to risk in approximately 3% of individuals with ASD. Finally, by observing clustering of mutations in unrelated probands, we uncover two ASD-associated genes: KMT2E (MLL5), a chromatin regulator, and RIMS1, a regulator of synaptic vesicle release. : Insertions and deletions (indels) have proven especially difficult to detect in exome sequencing data. Dong et al. now identify indels in exome data for 787 autism spectrum disorder (ASD) families. They demonstrate association between de novo indels that alter the reading frame and ASD. Furthermore, by observing clustering of indels in unrelated probands, they uncover two additional ASD-associated genes: KMT2E (MLL5), a chromatin regulator, and RIMS1, a regulator of synaptic vesicle release.

Water body extraction is a hot research topic in remote sensing applications. Using panchromatic optical remote sensing images to extract water bodies is a challenging task, because these images have one level of gray information, variable imaging conditions, and complex scene information. Refined water body extraction from optical panchromatic images often experiences serious under- or over- segmentation problems. In this paper, for producing refined water body extraction results from optical panchromatic images, we propose a fusion feature multi-scale pooling for Markov modeling method. Markov modeling includes two aspects: label field initialization and feature field establishment. These two aspects are jointly created by the fusion feature multi-scale pooling process, and this process is proposed to enhance the feature difference between water bodies and land cover. Then, the greedy algorithm in the iteration conditional method is used to extract refined water bodies according to the rebuilt Markov initial label and feature fields. Finally, to prove the effectiveness of proposed method, extensive experiments were used with collected 2.5m SPOT 5 and 1m GF-2 optical panchromatic images and evaluation indexes (precision, recall, overall accuracy, kappa coefficient and boundary detection ratios) to demonstrate that our proposed method can produce more refined water body extraction results than the state-of-the-art methods. The global and local refined indexes are improved by about 7% and 10%, respectively.

For exploring the mechanical properties and behaviors of new materials, a novel in situ nanoscratch device compatible with commercial microscope has been developed. The developed device with specific dimensions of 178 mm × 165 mm × 78 mm includes the coarse positioning module, the precise feed module, the measurement module, and the control module. Integrating the servo motor, worm and gears, ball screw, flexure hinge, and piezoelectric actuator, the device can realize macroscopical coarse positioning motion and precise feed motion. A novel arrangement of load sensor and indenter with no middle chain is used to reduce the measurement error. Closed-loop control system is established to guarantee the accuracy of load and displacement control. Mechanical properties of the developed device have been proved by calibrating the load sensor, finite element analysis of flexure hinge, and verifying the output performance. The in situ nanoscratch test has been conducted on the single crystal copper. The captured images and finite element analysis prove the feasibility and accuracy of the developed device.

The paper introduced a mathematical model of three-phase PWM rectifier, analyzed principle of fixed switching frequency control strategy,built control structure of PWM rectifier based on inner current loop and outer voltage loop the simulated the fixed switching frequency control strategy by use of Matlab. The simulation waves of voltage at DC side and current of AC side proved the finxed swithing frequency control strategy is feasible.Meanwhile,it analyzed influence of setting key parameters of PWM rectifier on harmonic content of input current at AC side,and gave a comparatively reasonable parameter of filter inductor.

In view of the problem that diode rectifying circuit ca't realize bidirectional flow of energy, the paper proposed a design scheme of energy feedback VSR. On the basis of topology of main circuit and mathematical model of three-phase VSR, it analyzed control principle of the energy feedback VSR in details, and introduced implementation of improved SVPWM algorithm. At last it built simulation model in Matlab/Simulink. The simulation result showed that the VSR has good stability and quick dynamic response speed and realizes bidirectional flow of energy.

Nucleosome occupancy results in complex sequence variation rate heterogeneity by either increasing mutation rate or inhibiting DNA repair in yeast, fish, and human. H2A.Z nucleosome is extensively involved in gene transcription activation and regulation. To test whether H2A.Z nucleosome has the similar impact on sequence variability in the Drosophila genome, we profiled the H2A.Z nucleosome occupancy and sequence variation rate at gene ends and splicing sites. Consistent with previous studies, H2A.Z nucleosome positioning helps to demarcate the borders of exons. Nucleosome occupancy is anticorrelated with sequence divergence rate in the regions flanking transcription start sites and splicing sites. However, there is no rate heterogeneity between the linker DNA and H2A.Z nucleosomal DNA regardless of nucleosome occupancy, fuzziness, positioning in promoter, coding, and intergenic regions, young or old genes. But the rate at intergenic nucleosomes and the flanking linker regions is higher than that at the genic counterparts. Further analyses found that the high sequence divergence rate in the promoter regions that are usually nucleosome depleted regions may be likely resulted from the high mutation rate in the enriched tandem repeats. Interestingly, within nucleosomes spanning splicing sites, sequence variability of nucleosomal DNA significantly increases from the end within exons to the other end protruding into introns. The relaxed functional constraint in introns contributes to the high rate of nucleosomal DNA residing in introns while the strict functional constraint in exons maintains the low rate of nucleosomal DNA residing in exons. Taken together, H2A.Z nucleosome occupancy has no effect on sequence variability of Drosophila genome, which is likely determined by local sequence composition and the concomitant selection pressure.

BackgroundLong QT syndrome 3 (LQT3) is caused by SCN5A mutations. Late sodium current (late I Na) inhibitors are current-specific to treat patients with LQT3, but the mechanisms underlying mexiletine (MEX) -sensitive (N1325S and R1623Q) and -insensitive (M1652R) mutations remains to be elucidated.MethodsLQT3 patients with causative mutations were treated with oral MEX following i.v. lidocaine. Whole-cell patch-clamp techniques and molecular remodeling were used to determine the mechanisms underlying the sensitivity to MEX.ResultsIntravenous administration of lidocaine followed by MEX orally in LQT patients with N1325S and R1623Q sodium channel mutation shortened QTc interval, abolished arrhythmias, and completely normalized the ECG. In HEK293 cells, the steady-state inactivation curves of the M1652R channels were rightward shifted by 5.6 mV relative to the WT channel. In contrast, the R1623Q mutation caused a leftward shift of the steady-state inactivation curve by 15.2 mV compared with WT channel, and N1325S mutation did not affect steady-state inactivation (n = 5-13, P < 0.05). The extent of the window current was expanded in all three mutant channels compared with WT. All three mutations increased late I Na with the greatest amplitude in the M1652R channel (n = 9-15, P < 0.05). MEX caused a hyperpolarizing shift of the steady-state inactivation and delayed the recovery of all three mutant channels. Furthermore, it suppressed late I Na in N1325S and R1623Q to a greater extent compared to that of M1652R mutant channel. Mutations altered the sensitivity of Nav1.5 to MEX through allosteric mechanisms by changing the conformation of Nav1.5 to become more or less favorable for MEX binding. Late I Na inhibitors suppressed late I Na in N1325S and R1623Q to a greater extent than that in the M1652R mutation (n = 4-7, P < 0.05).ConclusionThe N1325S, R1623Q, and M1652R mutations are associated with a variable augmentation of late I Na, which was reversed by MEX. M1652R mutation changes the conformation of Nav1.5 that disrupt the inactivation of channel affecting MEX binding, corresponding to the poor response to MEX. The lidocaine test, molecular modeling, and drugs screening in cells expressing mutant channels are useful for predicting the effectiveness of late I Na inhibitors.

There is evidence that transcription factor (TF) encoding genes, which temporally control development in multiple cell types, can have tens of enhancers that regulate their expression. The NR2F1 TF developmentally promotes caudal and ventral cortical regional fates. Here, we epigenomically compared the activity of Nr2f1's enhancers during mouse cortical development with their activity in a transgenic assay. We identified at least six that are likely to be important in prenatal cortical development, with three harboring de novo mutants identified in ASD individuals. We chose to study the function of two of the most robust enhancers by deleting them singly or together. We found that they have distinct and overlapping functions in driving Nr2f1's regional and laminar expression in the developing cortex. Thus, these two enhancers, probably in combination with the others that we defined epigenetically, precisely tune Nr2f1's regional, cell type, and temporal expression during corticogenesis. [ABSTRACT FROM AUTHOR]