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Fusarium head blight (FHB), mainly caused by the fungal pathogen Fusarium graminearum, is one of the most destructive wheat diseases. Besides directly affecting the yield, the mycotoxin residing in the kernel greatly threatens the health of humans and livestock. Xinong 979 (XN979) is a widely cultivated wheat elite with high yield and FHB resistance. However, its resistance mechanism remains unclear. In this study, we studied the expression of genes involved in plant defense in XN979 by comparative transcriptomics. We found that the FHB resistance in XN979 consists of two lines of defense. The first line of defense, which is constitutive, is knitted via the enhanced basal expression of lignin and jasmonic acid (JA) biosynthesis genes. The second line of defense, which is induced upon F. graminearum infection, is contributed by the limited suppression of photosynthesis and the struggle of biotic stress-responding genes. Meanwhile, the effective defense in XN979 leads to an inhibition of fungal gene expression, especially in the early infection stage. The formation of the FHB resistance in XN979 may coincide with the breeding strategies, such as selecting high grain yield and lodging resistance traits. This study will facilitate our understanding of wheat–F. graminearum interaction and is insightful for breeding FHB-resistant wheat.

Abstract As people increased emphasis on health problems, various wearable electronic devices are developed for sport‐related activity monitoring. However, these reported sensors must be tightly attached on the body to record the photonic, electronic even chemical changes during exercise. Poor user experience hinders the rapid application of wearable sensors. Here, an all‐printed perovskite photodetector for achieving non‐contact sports motion monitoring is developed. 1D MAPbBr3 arrays are printed with uniform orientation and strict crystallization via the droplet‐manipulation printing strategy. Under the guidance of microarrays on the template, the perovskite‐loaded droplet can be self‐shaped into the linear confined liquid space for the next crystallization. 1D perovskite photodetectors with high responsivity (R, MAX: 198 A W−1) and detectivity (D*, MAX: 6.64 × 1013 Jones) can be utilized to detect changes in the ambient light intensity under the body during the push‐up movement, achieving non‐contact real‐time monitoring of motions. The average accuracy of printed photodetectors to classify the collected push‐up signals reaches 97.40%. This strategy provides a reference for further improving the sensing performance of wearable sensors, which also extends the application of sports monitoring.

Abstract Ubiquitination, catalyzed usually by a three-enzyme cascade (E1, E2, E3), regulates various eukaryotic cellular processes. E3 ligases are the most critical components of this catalytic cascade, determining both substrate specificity and polyubiquitination linkage specificity. Here, we reveal the mechanism of a naturally occurring E3-independent ubiquitination reaction of a unique human E2 enzyme UBE2E1 by solving the structure of UBE2E1 in complex with substrate SETDB1-derived peptide. Guided by this peptide sequence-dependent ubiquitination mechanism, we developed an E3-free enzymatic strategy SUE1 (sequence-dependent ubiquitination using UBE2E1) to efficiently generate ubiquitinated proteins with customized ubiquitinated sites, ubiquitin chain linkages and lengths. Notably, this strategy can also be used to generate site-specific branched ubiquitin chains or even NEDD8-modified proteins. Our work not only deepens the understanding of how an E3-free substrate ubiquitination reaction occurs in human cells, but also provides a practical approach for obtaining ubiquitinated proteins to dissect the biochemical functions of ubiquitination.

Helminths produce calreticulin (CRT) to immunomodulate the host immune system as a survival strategy. However, the structure of helminth-derived CRT and the structural basis of the immune evasion process remains unclarified. Previous study found that the tissue-dwelling helminth Trichinella spiralis produces calreticulin (TsCRT), which binds C1q to inhibit activation of the complement classical pathway. Here, we used x-ray crystallography to resolve the structure of truncated TsCRT (TsCRTΔ), the first structure of helminth-derived CRT. TsCRTΔ was observed to share the same binding region on C1q with IgG based on the structure and molecular docking, which explains the inhibitory effect of TsCRT on C1q-IgG–initiated classical complement activation. Based on the key residues in TsCRTΔ involved in the binding activity to C1q, a 24 amino acid peptide called PTsCRT was constructed that displayed strong C1q-binding activity and inhibited C1q-IgG–initiated classical complement activation. This study is the first to elucidate the structural basis of the role of TsCRT in immune evasion, providing an approach to develop helminth-derived bifunctional peptides as vaccine target to prevent parasite infections or as a therapeutic agent to treat complement-related autoimmune diseases.

Multi-directional forging is an effective plastic deformation method for polycrystalline grain refinement, and the degree of refinement is closely related to the number of forging passes. However, the relationship between the degree of refinement and the number of forging passes is almost ambiguous. Focusing on the forging passes, the grain refinement and dislocation nucleation mechanisms were revealed by combining the free energy variation and the strain field distribution using the dual-mode phase-field crystal model in our work. The results show that the nucleated dislocations within the grain can divide the grain into many finer grains under continuous stress. The nucleation mechanism of dislocation mainly includes two forms: grain boundary emission dislocation and atomic misalignment near the twin boundary. The strain field distribution reveals the mechanism of dislocation annihilation. The grain refinement effect of triple pass stress loading is the best, being 59 %, 18 %, and 43 % higher than that of the one forging pass, two forging passes, and four forging passes stress loading respectively. Moreover, the cause of the above phenomenon was further revealed by atomic analysis. This study reveals the response rule of forging passes to fine grain strengthening and gives feedback to guide the actual production experiment.

Abstract Toll-like receptors (TLRs) are a class of proteins that play critical roles in recognizing pathogens and initiating innate immune responses. TASL, a recently identified innate immune adaptor protein for endolysosomal TLR7/8/9 signaling, is recruited by the lysosomal proton-coupled amino-acid transporter SLC15A4, and then activates IRF5, which in turn triggers the transcription of type I interferons and cytokines. Here, we report three cryo-electron microscopy (cryo-EM) structures of human SLC15A4 in the apo monomeric and dimeric state and as a TASL-bound complex. The apo forms are in an outward-facing conformation, with the dimeric form showing an extensive interface involving four cholesterol molecules. The structure of the TASL-bound complex reveals an unprecedented interaction mode with solute carriers. During the recruitment of TASL, SLC15A4 undergoes a conformational change from an outward-facing, lysosomal lumen-exposed state to an inward-facing state to form a binding pocket, allowing the N-terminal helix of TASL to be inserted into. Our findings provide insights into the molecular basis of regulatory switch involving a human solute carrier and offers an important framework for structure-guided drug discovery targeting SLC15A4-TASL-related human autoimmune diseases.

Abstract The Viridiplantae comprise two main clades, the Chlorophyta (including a diverse array of marine and freshwater green algae) and the Streptophyta (consisting of the freshwater charophytes and the land plants). Lineages sister to core Chlorophyta, informally refer to as prasinophytes, form a grade of mainly planktonic green algae. Recently, one of these lineages, Prasinodermophyta, which is previously grouped with prasinophytes, has been identified as the sister lineage to both Chlorophyta and Streptophyta. Resolving the deep relationships among green plants is crucial for understanding the historical impact of green algal diversity on marine ecology and geochemistry, but has been proven difficult given the ancient timing of the diversification events. Through extensive taxon and gene sampling, we conduct large-scale phylogenomic analyses to resolve deep relationships and reveal the Prasinodermophyta as the lineage sister to Chlorophyta, raising questions about the necessity of classifying the Prasinodermophyta as a distinct phylum. We unveil that incomplete lineage sorting is the main cause of discordance regarding the placement of Prasinodermophyta. Molecular dating analyses suggest that crown-group green plants and crown-group Prasinodermophyta date back to the Paleoproterozoic-Mesoproterozoic. Our study establishes a plausible link between oxygen levels in the Paleoproterozoic-Mesoproterozoic and the origin of Viridiplantae.

Abstract Background Stroke is a common and frequently-occurring disease in older people. It has the characteristics of high morbidity, high mortality, high recurrence rate and high disability rate. Most stroke risk studies are based on pathophysiology, however psychosocial factors such as diet quality are often understudied. The aim of this study was to assess stroke risk in urban community residents in Tianjin and investigate the factors that affect the dietary quality of older stroke high-risk populations. Methods Using a cross-sectional, multicenter study, recruit people aged 60 to 80 in Tianjin. Dietary intake data were obtained through a validated food frequency questionnaire, which were used to calculate Alternate Healthy Eating Index-2010 (AHEI-2010) and to analyze its association with sociodemographic characteristics, stroke risk factors and health marker variables. Results A total of 1068 participants from 4 community health service centers in Tianjin were recruited, including 300 low-risk individuals and 768 high-risk individuals. Compared with the low-risk group (62.75 ± 3.59), the AHEI-2010 mean score of the high-risk group (56.83 ± 6.54) was significantly lower. The top three most common risk factors among participants were dyslipidemia (80.3%), hypertension (60.6%), and physical inactivity (58.2%). Multiple logistic regression showed that diet quality was independently and significantly associated with stroke risk (OR = 0.765; 95%CI: 0.690–0.848, p

The significance of environmental considerations has been highlighted by the substantial impact of plant pests on ecosystems. Addressing the urgent demand for sophisticated pest management solutions in arboreal environments, this study leverages advanced deep learning technologies to accurately detect and classify common tree pests, such as “mole cricket”, “aphids”, and “Therioaphis maculata (Buckton)”. Through comparative analysis with the baseline model ResNet-18 model, this research not only enhances the SE-RegNetY and SE-RegNet models but also introduces innovative frameworks, including GCT-Inception-ResNet-V3, SE-Inception-ResNet-V3, and SE-Inception-RegNetY-V3 models. Notably, the GCT-Inception-ResNet-V3 model demonstrates exceptional performance, achieving a remarkable average overall accuracy of 94.59%, average kappa coefficient of 91.90%, average mAcc of 94.60%, and average mIoU of 89.80%. These results signify substantial progress over conventional methods, outperforming the baseline model’s results by margins of 9.1%, nearly 13.7%, 9.1%, and almost 15% in overall accuracy, kappa coefficient, mAcc, and mIoU, respectively. This study signifies a considerable step forward in blending sustainable agricultural practices with environmental conservation, setting new benchmarks in agricultural pest management. By enhancing the accuracy of pest identification and classification in agriculture, it lays the groundwork for more sustainable and eco-friendly pest control approaches, offering valuable contributions to the future of agricultural protection.

Lineament is a unique geological structure. The study of Lunar lineament structure has great significance on understanding its history and evolution of Lunar surface. However, the existing geographic feature extraction methods are not suitable for the extraction of Lunar lineament structure. In this paper, a new lineament extraction method is proposed based on improved-UNet++ and YOLOv5. Firstly, new lineament dataset is created containing lineaments structure based on CCD data from LROC. At same time the residual blocks are replaced with the VGG blocks in the down sample part of the UNet++ with adding the attention block between each layer. Secondly, the improved-UNet++ and YOLO networks are trained to execute the object detection and semantic segmentation of lineament structure respectively. Finally, a polygon-match strategy is proposed to combine the results of object detection and semantic segmentation. The experiment result indicate that this new method has relatively better and more stable performance compared with current mainstream networks and the original UNet++ network in the instance segmentation of lineament structure. Additionally, the polygon-match strategy is able to perform preciser edge detail in the instance segmentation of lineament structure result.

As the depth of mines continues to increase, the problems of high temperature and potential heat damage become more prominent. In this study, the characteristics of natural and industrial heat sources in mines were reviewed, and then mainstream heat hazard governance technologies and corresponding utilization methods were discussed and compared. The first category of technologies comprises the optimization of ventilation systems, the insulation of roc heat, and artificial refrigeration. These cooling approaches are limited because the heat resources cannot be recovered. The second category is the utilization of waste industrial heat in mines, including the use of waste heat from the air compressors, drainage water, and foul airflow, but the current applications of these approaches have limited effectiveness in cooling the underground space. The third category is the application of geo-structures to recover natural heat in mines. Based on the principles of the chiller/heat pump cycle and the characteristics of heat sources and sinks in mines, the potential and constraints of each technology were discussed and summarized. This study provides a scientific reference for the selection of suitable heat governance and utilization technologies.

Fractured rock mass is extensively distributed in Karst topography regions, and its geological environment is different from that of the quaternary strata. In this study, the influences on geological environment induced by the construction and operation of a large-scale borehole group of ground source heat pumps are analyzed by a thermo-hydro-mechanical (THM) coupling numerical model. It was found that groundwater is redirected as the boreholes can function as channels to the surface, and the flow velocity in the upstream of borehole group is higher than those downstream. This change in groundwater flow enhances heat transfer in the upstream boreholes but may disturb the original groundwater system and impact the local geological environment. Heat accumulation is more likely to occur downstream. The geo-stress concentration appears in the borehole area, mainly due to exaction and increasing with the depth. On the fracture plane, tensile stress and maximum shear stress simultaneously occur on the upstream of boreholes, inducing the possibility of fracturing or the expansion of existing fractures. There is a slight uplift displacement on the surface after the construction of boreholes. The correlations of the above THM phenomena are discussed and analyzed. From the modeling results, it is suggested that the consolidation of backfills can minimize the environmental disturbances in terms of groundwater redirection, thermal accumulation, occurrence of tensile stress, and possible fracturing. This study provides support for the assessment of impacts on geological environments resulting from shallow geothermal development and layout optimization of ground heat exchangers in engineering practices.

The Tongde Graphite Deposit in Panzhihua is located in the accretionary zone on the western margin of the Yangtze plate. In this paper, the whole rock geochemical analysis, C isotope determination and Re-Os isotope dating of the ore in Tongde graphite mining area are carried out, the original rock of the ore is restored, and the metallogenic environment is discussed. Research shows that the ore SiO2 is 55.65~61.68%, SiO2/Al2O3 ratio is 4.59~5.42, and Ni/Co ratio is 6.23~12.88. It is rich in Ba, Rb, Sr and other large ion lithophile elements and Nb, Zr, Hf, Th, U and other high field strength elements. Total rare earth elements of ore ΣREE is 149.13×10-6～195.37×10-6, with weak Ce negative anomaly and Eu negative anomaly, representing the anoxic marine sedimentary environment. The Carbon isotope δ13CV-PDB in ore is -25.0‰~-23.5‰, which is within the range of biogenic organic carbon, indicating that the ore-forming carbon mainly comes from organic matter. The Re-Os isotopic age of graphite is 983 ± 72 Ma (MSWD=1.7), belonging to the early Neoproterozoic, earlier than the intrusion age of magmatic rocks around Tongde. The content of re is between 27.66×10-9～79.81×10-9, the contents of ordinary Os and 187Os are 0.52 ×10-9～2.16×10-9, 0.28 × 10-9～0.83×10-9,respectively ,it is significantly enriched relative to the abundance of Re and Os in the crust. The 187re/188os ratio is 122.9~350.5, and the initial Os isotope ratio 187Os/188Os=0.31±0.21. Combined with the field geological survey, the original rock of ore and ore bearing mica quartz schist in Tongde area is restored, and it is concluded that the original rock is sedimentary rock.

This is the first investigation on the micromorphology and kinetics evolution of Cr-rich α′ precipitates under Cr composition, irradiation and dislocation with the three-dimensional phase-field simulation. The statistical results of volume fraction, particle number density, and average particle size under different Cr composition are consistent with the APT results. The particle density and volume fraction of α′ precipitates increase with the increase of Cr composition (>9 at.%), while the mean radius decreases. Fitting the free energy curve to analyze the driving force and resistance of α′ precipitates. It is found that α′ precipitates preferentially nucleate in the dislocation core region due to the drive of dislocation elastic energy, while the nucleation in the dislocation free region is driven by chemical free energy. Growth of α′ precipitates is driven by chemical free energy and interface energy. The particle size distribution of 3dpa shows that the particle size distribution of α′ precipitates becomes more uniform with the increase of dislocation density. The strengthening model calculated from the simulation results shows that the Cr component has a great influence on the strengthening, and the total strength increases slightly with the increase of dislocation density.

Inorganic arsenic (iAs) contamination in drinking water is a global public health problem, and exposure to iAs is a known risk factor for bladder cancer. Perturbation of urinary microbiome and metabolome induced by iAs exposure may have a more direct effect on the development of bladder cancer. The aim of this study was to determine the impact of iAs exposure on urinary microbiome and metabolome, and to identify microbiota and metabolic signatures that are associated with iAs-induced bladder lesions. We evaluated and quantified the pathological changes of bladder, and performed 16S rDNA sequencing and mass spectrometry-based metabolomics profiling on urine samples from rats exposed to low (30 mg/L NaAsO2) or high (100 mg/L NaAsO2) iAs from early life (in utero and childhood) to puberty. Our results showed that iAs induced pathological bladder lesions, and more severe effects were noticed in the high-iAs group and male rats. Furthermore, six and seven featured urinary bacteria genera were identified in female and male offspring rats, respectively. Several characteristic urinary metabolites, including Menadione, Pilocarpine, N-Acetylornithine, Prostaglandin B1, Deoxyinosine, Biopterin, and 1-Methyluric acid, were identified significantly higher in the high-iAs groups. In addition, the correlation analysis demonstrated that the differential bacteria genera were highly correlated with the featured urinary metabolites. Collectively, these results suggest that exposure to iAs in early life not only causes bladder lesions, but also perturbs urinary microbiome composition and associated metabolic profiles, which shows a strong correlation. Those differential urinary genera and metabolites may contribute to bladder lesions, suggesting a potential for development of urinary biomarkers for iAs-induced bladder cancer.

Abstract Objectives To investigate the relationship between diffusion tensor imaging (DTI) indicators and cerebral small vessel disease (CSVD) with depressive states, and to explore the underlying mechanisms of white matter damage in CSVD with depression. Method A total of 115 elderly subjects were consecutively recruited from the neurology clinic, including 36 CSVD patients with depressive state (CSVD+D), 34 CSVD patients without depressive state (CSVD-D), and 45 controls. A detailed neuropsychological assessment and multimodal magnetic resonance imaging (MRI) were performed. Based on tract-based spatial statistics (TBSS) analysis and structural network analysis, differences between groups were compared, including white matter fiber indicators (fractional anisotropy and mean diffusivity) and structural brain network indicators (global efficiency, local efficiency and network strength), in order to explore the differences and correlations of DTI parameters among the three groups. Results There were no significant differences in terms of CSVD burden scores and conventional imaging findings between the CSVD-D and CSVD+D groups. Group differences were found in DTI indicators (p

Co-contamination of arsenic and fluoride is widely distributed in groundwater. However, little is known about the interactively influence of arsenic and fluoride, especially the combined mechanism in cardiotoxicity. Cellular and animal models exposure to arsenic and fluoride were established to assess the oxidative stress and autophagy mechanism of cardiotoxic damage using the factorial design, a widely used statistical method for assessing two factor interventions. In vivo, combined exposure to high arsenic (50 mg/L) and high fluoride (100 mg/L) induced myocardial injury. The damage is accompanied by accumulation of myocardial enzyme, mitochondrial disorder, and excessive oxidative stress. Further experiment identified that arsenic and fluoride induced the accumulation of autophagosome and increased expression level of autophagy related genes during the cardiotoxicity process. These findings were further demonstrated through the in vitro model of arsenic and fluoride-treated the H9c2 cells. Additionally, combined of arsenic-fluoride exposure possesses the interactively influence on oxidative stress and autophagy, contributing to the myocardial cell toxicity. In conclusion, our data suggest that oxidative stress and autophagy are involved in the process of cardiotoxic injury, and that these indicators showed interaction effect in response to the combined exposure of arsenic and fluoride.

Wetlands, situated at the vital intersection of terrestrial and aquatic ecosystems, are pivotal in preserving global biodiversity and maintaining environmental equilibrium. The escalating trend of global urbanization necessitates the utilization of high-resolution satellite imagery for accurate wetland delineation, which is essential for establishing efficacious conservation strategies. This study focuses on the wetlands of Macau, characterized by distinctive coastal and urban features. A noteworthy enhancement in this study is the integration of the Coordinate Attention mechanism with the RegNet model, forming the CA-RegNet. This combined model demonstrates superior performance, outdoing previous Macau wetlands segmentation studies that used ResNet, evidenced by an approximate rise of 2.7% in overall accuracy (OA), 4.0% in the Kappa coefficient, 1.9% in the mAcc, and 0.5% in the mIoU. Visual evaluations of the segmentation results reinforce the competence of the CA-RegNet model in precisely demarcating coastal wetlands and Saiwan Lake, thereby overcoming the former constraints of ResNet and underscoring the robustness and innovation of this study.

Volcanism is an important geological evolutionary process on the Moon. The study of lunar volcanic features is of great significance and value to understanding the geological evolution of the Moon better. Lunar domes are one of the essential volcanic features of the Moon. However, the existing lunar dome detection methods are still traditional manual or semiautomatic identification approaches that require extensive prior knowledge and have a complex identification process. Therefore, this paper proposes an automatic detection method based on improved YOLOv7 for lunar dome detection. First, a new lunar dome dataset was created by digital elevation model (DEM) data, and the effective squeeze and excitation (ESE) attention mechanism module was added to the backbone and neck sections to reduce information loss in the feature map and enhance network expressiveness. Then, a new SPPCSPC-RFE module was proposed by adding the receptive field enhancement (RFE) module into the neck section, which can adapt to dome feature maps of different shapes and sizes. Finally, the bounding box regression loss function complete IOU (CIOU) was replaced by wise IOU (WIOU). The WIOU loss function improved the model’s performance for the dome detection effect. Furthermore, this study combined several data enhancement strategies to improve the robustness of the network. To evaluate the performance of the proposed model, we conducted several experiments using the dome dataset developed in this study. The experimental results indicate that the improved method outperforms related methods with a mean average precision (mAP@0.5) value of 88.7%, precision (P) value of 85.6%, and recall (R) value of 86.4%. This study provides an effective solution for lunar dome detection.

Deep learning technology has achieved breakthrough research results in the fields of medical computer vision and image processing. Generative adversarial networks (GANs) have demonstrated a capacity for image generation and expression ability. This paper proposes a new method called MWG-UNet (multiple tasking Wasserstein generative adversarial network U-shape network) as a lung field and heart segmentation model, which takes advantages of the attention mechanism to enhance the segmentation accuracy of the generator so as to improve the performance. In particular, the Dice similarity, precision, and F1 score of the proposed method outperform other models, reaching 95.28%, 96.41%, and 95.90%, respectively, and the specificity surpasses the sub-optimal models by 0.28%, 0.90%, 0.24%, and 0.90%. However, the value of the IoU is inferior to the optimal model by 0.69%. The results show the proposed method has considerable ability in lung field segmentation. Our multi-organ segmentation results for the heart achieve Dice similarity and IoU values of 71.16% and 74.56%. The segmentation results on lung fields achieve Dice similarity and IoU values of 85.18% and 81.36%.

Graph convolutional networks (GCNs) are neural network frameworks for machine learning on graphs. They can simultaneously perform end-to-end learning on the attribute information and the structure information of graph data. However, most existing GCNs inevitably encounter the limitations of non-robustness and low classification accuracy when labeled nodes are scarce. To address the two issues, the deep graph convolutional generative adversarial network (DGCGAN), a model combining GCN and deep convolutional generative adversarial networks (DCGAN), is proposed in this paper. First, the graph data is mapped to a highly nonlinear space by using the topology and attribute information of the graph for symmetric normalized Laplacian transform. Then, through the feature-structured enhanced module, the node features are expanded into regular structured data, such as images and sequences, which are input to DGCGAN as positive samples, thus expanding the sample capacity. In addition, the feature-enhanced (FE) module is adopted to enhance the typicality and discriminability of node features, and to obtain richer and more representative features, which is helpful for facilitating accurate classification. Finally, additional constraints are added to the network model by introducing DCGAN, thus enhancing the robustness of the model. Through extensive empirical studies on several standard benchmarks, we find that DGCGAN outperforms state-of-the-art baselines on semi-supervised node classification and remote sensing image classification.

The grain-boundary dislocation arrangement and decomposition during constant-volume deformation of a nanoscale bi-crystal system in fcc-structured materials were studied by using the two-mode phase-field crystal (2PFC) method. The effects of different grain boundary misorientations (GBMs) and tensile deformation directions on the dislocation arrangement and decomposition are analyzed. In three different symmetrical tilt grain boundaries evaluated by PFC, the atomic density profile of grain boundaries changed periodically at equilibrium. The initial grain boundary dislocation arrangement of the three samples is almost the same when tensile deformation is applied to the samples in the x- or y- direction, and all are symmetrically arranged in a “bowknot ”structure. The stress at the grain boundary is concentrated with the increase of strain, and dislocation decomposition can effectively reduce the stress concentration. The time steps of dislocation decomposition at grain boundaries decreases with increasing strain rate. This work facilitates the application of PFC in the analysis of grain-boundary mechanics in an extended range of materials.

To assess the impact of the relative displacement between machines and subjects, the machine angle and the fine-tuning of the subject posture on the segmentation accuracy of chest X-rays, this paper proposes a Position and Direction Network (PDNet) for chest X-rays with different angles and positions that provides more comprehensive information for cardiac image diagnosis and guided surgery. The implementation of PDnet was as follows: First, the extended database image was sent to a traditional segmentation network for training to prove that the network does not have linear invariant characteristics. Then, we evaluated the performance of the mask in the middle layers of the network and added a weight mask that identifies the position and direction of the object in the middle layer, thus improving the accuracy of segmenting targets at different positions and angles. Finally, the active-shape model (ASM) was used to postprocess the network segmentation results, allowing the model to be effectively applied to 2014 × 2014 or higher definition chest X-rays. The experimental comparison of LinkNet, ResNet, U-Net, and DeepLap networks before and after the improvement shows that its segmentation accuracy (MIoU) are 5%, 6%, 20%, and 13% better. Their differences of losses are 11.24%, 21.96%, 18.53%, and 13.43% and F-scores also show the improved networks are more stable.

We consider SAR-optical image matching problems, where correspondences are acquired from a pair of SAR and optical images. Recent methods for such a problem typically simplify the SAR-optical image matching to the SAR-SAR or optical-optical image matchings using supervised-image-synthesis methods. However, training supervised-image-synthesis needs plenty of aligned SAR-optical image pairs while gathering sufficient amounts of aligned multi-modal image pairs is challenging in remote sensing. In this work, we investigate the applicability of unsupervised-image-synthesis for SAR-optical image matching such that the unaligned SAR-optical images could be used. To this end, we apply feature matching loss to a well known unsupervised-image-synthesis method, i.e., CycleGAN, to enforce the feature matching consistency. Moreover, we develop a shared-matching-strategy to improve the results of SAR-optical image matching further. Qualitative comparisons against CycleGAN, StarGAN, and DualGAN demonstrate the superiority of our approach. Quantitative results show that, compared with CycleGAN, StarGAN, and DualGAN, our method obtains at least 2.6 times more qualified SAR-optical matchings.

Rad5 is a hub connecting three replication stress tolerance pathways. Here, the authors present the 3.3 Å crystal structure of a N-terminal truncated K.lactis Rad5 construct that reveals the spatial arrangement of the HIRAN, Snf2 and RING domains and structure-guided in vitro and in vivo experiments reveal multiple activities of the yeast Rad5 HIRAN domain among them a role in binding PCNA and supporting its ubiquitination.

Synthetic Aperture Radar and optical (SAR-optical) image matching is a technique of finding correspondences between SAR and optical images. SAR-optical image matching can be simplified to single-mode image matching through image synthesis. However, the existing SAR-optical image synthesis methods are unable to provide qualified images for SAR-optical image matching. In this work, we present a K-means Clustering Guide Generative Adversarial Networks (KCG-GAN) to improve the image quality of synthesizing by constraining spatial information synthesis. KCG-GAN uses k-means segmentations as one of the image generator's inputs and introduces feature matching loss, segmentation loss, and L1 loss to the objective function. Meanwhile, to provide repeatable k-means segmentations, we develop a straightforward 1D k-means algorithm. We compare KCG-GAN with a leading image synthesis method-pix2pixHD. Qualitative results illustrate that KCG-GAN preserves more spatial structures than pix2pixHD. Quantitative results show that, compared with pix2pixHD, images synthesized by KCG-GAN are more similar to original optical images, and SAR-optical image matching based on KCG-GAN obtains at most 3.15 times more qualified matchings. Robustness tests demonstrate that SAR-optical image matching based on KCG-GAN is robust to rotation and scale changing. We also test three SIFT-like algorithms on matching original SAR-optical image pairs and matching KCG-GAN synthesized optical-optical image pairs. Experimental results show that our KCG-GAN significantly improves the performances of the three algorithms on SAR-optical image matching.

In recent years, Graph Convolutional Networks (GCNs) have been increasingly and widely used in graph data representation and semi-supervised learning. GCNs can reveal and dig deep into irregular data with spatial topological structure. However, in the task of node classification, most models will be over-smoothing (indistinguishable representations of nodes in different classes) after stacking multilayer GCNs. To alleviate the issue of over-smoothing, we propose a novel Discriminable Squeeze and Excitation Graph Convolutional Network (D-SEGCN) based on the attention mechanism of features for semi-supervised node classification. In the proposed D-SEGCN model, Squeeze and Excitation (SE) module is fused to the Graph Convolutional Networks to form SEGCN, which can selectively enhance significant features and realize the adaptive calibration of feature dimensions, thus enhancing node features. Then, the feature representation is obtained through a hierarchical structure, it is put into a discriminable capsule layer which can judge the similarities between the node features to obtain new feature. Finally, the feature representation and new feature are fused to obtain the final feature to strengthen the discriminability of nodes. Furthermore, we demonstrate that D-SEGCN significantly outperforms the state-of-the-art methods on three citation networks datasets.

Abstract Introduction Only two studies investigated the associations between peak width of skeletonized mean diffusivity (PSMD) and age‐related cognitive alterations, whereas none of the studies investigated the association with vascular risk factors. Methods We evaluated 801 stroke‐ and dementia‐free elderlies with baseline and 3‐year follow‐up assessments. Regression analyses were used to assess the association between age‐related cognitive functions and PSMD. Simple mediation models were used to study the mediation effect of PSMD between vascular risk factors and age‐related cognitive outcomes. Results PSMD was negatively associated with processing speed at baseline and negatively associated with processing and memory scores at 3‐year follow‐up. The association between vascular risk factors and age‐related cognition was mediated by PSMD, as well as other diffusion tensor imaging markers. Discussion PSMD is preferred over other diffusion tensor imaging markers as it is sensitive to age‐related cognitive alterations and calculation is fully automated. PSMD is proposed as a research tool to monitor age‐related cognitive alterations.

While numerous studies have shown that fluoride or arsenic exposure may damage the reproductive system, there are few reports of co-exposure to fluoride and arsenic. In addition, the literature on autophagy and intestinal flora composition in reproductive toxicity studies of co-exposure to fluoride and arsenic is insufficient. In this study, we developed a rat model of fluoride and arsenic exposure via drinking water from pre-pregnancy to 90 days postnatal. Sprague-Dawley rats were randomly divided into sterile water control group, fluoride group (100 mg/L NaF), arsenic group (50 mg/L NaAsO2) and combined exposure group (100 mg/L NaF+50 mg/L NaAsO2). Our results showed that fluoride and arsenic exposure caused a reduction in testicular weight and significant pathological damage to tissue. We found that the levels of follicle-stimulating hormone, luteinizing hormone, and testosterone were reduced to varying degrees. Meanwhile experiments showed that fluoride and arsenic exposure can modulate autophagic flux, causing increased levels of Beclin1 and LC3 expression and decreased p62 expression. Analogously, by performing 16S sequencing of rat feces, we found 24 enterobacterial genera that differed significantly among the groups. Furthermore, the flora associated with testicular injury were identified by correlation analysis of hormonal indices and autophagy alterations with intestinal flora composition at the genus level, respectively. In summary, our study shows that fluoride and arsenic co-exposure alters autophagic flux in the testis, causes testicular injury, and reveals an association between altered intestinal flora composition and testicular injury.

Purpose: Stroke-associated infection (SAI) is associated with adverse outcomes in patients with acute ischemic stroke (AIS). In this study, we aimed to evaluate the association between neutrophil percentage-to-albumin ratio (NPAR) and SAI occurrence in patients with AIS.Methods: We retrospectively analyzed all AIS patients who were admitted to the Neurology ward of The Second Hospital of Tianjin Medical University from November 2018 to October 2020. The relationship between NPAR and SAI was analyzed by multivariable analysis. The receiver operating characteristic (ROC) curve was used to compare the predicted value of albumin, neutrophil percentage, neutrophil-to-lymphocyte ratio (NLR), and NPAR.Results: We included 379 AIS patients out of which 51 (13.5%) developed SAI. The NPAR was independently associated with increased risk of SAI adjusting for confounders [adjusted odds ratio (aOR) = 10.52; 95% confidence interval (CI), 3.33–33.28; P

The regulation of mitochondrial function, which is dominated by oxidative phosphorylation (OXPHOs), is important in fluoride induced cardiovascular disease. Based on the previous study of fluoride-induced mitochondrial structure and membrane potential abnormalities, this study integrated ITRAQ protein quantification and RNA-Seq methods to analyze the sequencing data of rat myocardial tissue under fluoride exposure (0, 30, 60 and 90 mg/L). A total of 22 differentially expressed genes associated with the OXPHOs pathway were screened by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) co-enrichment analysis, and were localizated by Interaction Network and calculated inter-genes and inter-omics correlations by Pearson correlation. In general, fluoride exposure can down-regulate genes related OXPHOs, particularly affecting the assembly of the complex I including Ndufa10, resulting in abnormal mitochondrial ATP synthesis and reduced myocardial energy supply. Most importantly, this study shows that the enriched information from the proteomics can explain the change process of energy production, but the specific molecules involved in energy supply cannot be obtained via transcriptomics information alone. Based on the results of transcriptional and protein analysis, our findings contribute to an innovative understanding of the pathways and molecular changes of myocardial injury induced by fluorosis.

Background: This study aims to explore the features of gait disorders with cerebral small vessel disease (CSVD), and results from magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI) were analyzed. Methods: The 139 patients with CSVD were divided into two groups by the Tinetti scale scores: the gait disorder (GD) group with a score

Abstract Starches of four legume varieties grown in China were evaluated for composition, granule structure, turbidity, swelling power, solubility, and thermal and pasting properties. The similar granule shapes, surface fissures, polarized crosses, inner structure characteristics, and granule sizes could be observed among all legume varieties through a variety of microscopy techniques such as light microscopy, scanning electron microscopy, and confocal laser scanning microscopy. Amylose contents were in the range of 30.61%–33.55%. All of the starch varieties showed C‐type X‐ray pattern, but exhibited different relative crystallinity percentage. Significant differences were observed among starch varieties in swelling power, solubility, and light transmittance. Thermal analysis and pasting profile of legume starches showed that all the varieties’ differences are probably due to variation in amylose content. The thermal and pasting parameters of starches were evaluated using differential scanning calorimeter and Rapid Visco‐Analyser, respectively, and significant differences were observed in individual pasting and thermal parameters. The present study can be used for identifying differences between legume varieties for starch structural and physicochemical characteristics and could provide guidance to possible industries for their end use.

An exploration of dislocation microstructure evolution with different misorientation angles was performed using phase field crystal method (PFC). The microcosmic evolution process of grain boundaries under external stress, as well as the corresponding energy curve and stress–strain curve, are analyzed. The relationship between the misorientation angle and the dislocations emission frequency is discussed. Three forms of dislocations reaction on the evolution process of 6° and 10° are analyzed in detail, which are respectively type I semi-annihilation, type II semi-annihilationand full-annihilation. Among them, the nature of type I semi-annihilation is a combination of dislocation and a single edge dislocation reaction with a single edge dislocation left. The essence of type II semi-annihilation is a pair of dislocation and the other pair of dislocation reaction leaving two edge dislocations. The essence of full-annihilation is that two pairs of dislocations or single edge dislocations with opposite Burger vectors react with each other and the distortion area disappears. When the misorientation angle is 10°, the dislocation reaction and the dislocation motion ability of the system are stronger than 6°. The peak of the energy curve is related to the number of dislocation proliferations in the evolution process. An emission frequency and average density of dislocations of 10° is greater than 6°. The causes of plastic deformation are revealed to a certain extent by stress–strain curves.

Background and Aims: Internet Gaming Disorder (IGD), which is an underlying symptom classified as a behavioral addiction disorder, has many related social problems that have garnered the bulk of attention in recent research. However, its psychological/behavioral mechanism is still unclear. The purpose of the current study was to explore the relationship between IGD and impulsivity which is regulated by behavioral inhibition and activation among different age groups.Methods: A total of 1,525 students completed Young's Internet Addiction Test (IAT), Online Game Addiction Questionnaire, the Behavioral Inhibition System/Behavioral Activation System (BIS/BAS) scales, and the Barratt Impulsiveness Scale-11 (BIS-11).Results: (1) The prevalence of IGD in different ages students was 10.3%. (2) BIS, BAS-Fun seeking (BAS-F), and BIS-11 scores indicated that there were significant differences between IGD and non-IGD individuals. (3) BIS showed significant differences in different grades (i.e., between undergraduates and middle school students with IGD; F = 3.10, p < 0.05). (4) The IAT scores demonstrated a significant positive correlation with BIS scores (r = 0.375, p < 0.05) among undergraduates with IGD; IAT scores of high school students with IGD were negatively correlated with BAS-Reward (BAS-R) (r = −0.28, p < 0.05).5)BIS and BIS-11 together could explain 14.9% variance of IGD among the college group; BAS-R and BAS-F together could explain 16.7% variance of IGD among the high school group (p < 0.05).Conclusions: The relationships between IGD and BIS, BAS-F, BAS-D, BIS-11 scores differed due to the age group of individuals tested.

Many “hot spot” geographic areas across the world with drinking water co-contaminated with inorganic arsenic (iAs) and fluoride (F-), two of the most common natural contaminants in drinking water. Both iAs and F- are known neurotoxins and affect neurodevelopment of children. However, very few studies have investigated the neurodevelopmental effects of concurrent exposure to iAs and F-, which could potentially pose a greater risk than iAs or F- exposure alone. Further, perturbations of gut microbiota, which plays a regulatory role in neurodevelopment, resulting from iAs and F- exposure has been reported in numerous studies. There is lacking of information regarding to the relationship among concurrent iAs and F- exposure, microbiome disruption, and neurodevelopmental impacts. To fill these gaps, we treated offspring rats to iAs (50 mg/L NaAsO2) and F- (100 mg/L NaF), alone or combined from early life (in utero and childhood) to puberty. We applied Morris water maze test to assess spatial learning and memory of these rats and generated gut microbiome profiles using 16S rRNA gene sequencing. We showed that concurrent iAs and F- exposure caused more prominent neurodevelopmental effects in rats than either iAs or F- exposure alone. Moreover, Unsupervised Principal Coordinates Analysis (PCoA) and Linear Discriminant Analysis Effect Size (LEfSe) analysis of gut microbiome sequencing results separated concurrent exposure group from others, indicating a more sophisticated change of gut microbial communities occurred under the concurrent exposure condition. Further, a correlation analysis between indices of the water maze test and microbial composition at the genus level identified featured genera that were clearly associated with neurobehavioral performance of rats. 75% (9 out of 12) genera, which had a remarkable difference in relative abundance between the control and combined iAs and F- exposure groups, showed significantly strong correlations (r = 0.70–0.90) with the water maze performance indicators. Collectively, these results suggest that concurrent iAs and F- exposure led to more prominent effects on neurodevelopment and gut microbiome composition structures in rats, and the strong correlation between them indicates a high potential for the development of novel microbiome-based biomarkers of iAs and/or F- associated neurodevelopmental deficits.

Medical image segmentation is a classic challenging problem. The segmentation of parts of interest in cardiac medical images is a basic task for cardiac image diagnosis and guided surgery. The effectiveness of cardiac segmentation directly affects subsequent medical applications. Generative adversarial networks have achieved outstanding success in image segmentation compared with classic neural networks by solving the oversegmentation problem. Cardiac X-ray images are prone to weak edges, artifacts, etc. This paper proposes an adaptive generative adversarial network for cardiac segmentation to improve the segmentation rate of X-ray images by generative adversarial networks. The adaptive generative adversarial network consists of three parts: a feature extractor, a discriminator and a selector. In this method, multiple generators are trained in the feature extractor. The discriminator scores the features of different dimensions. The selector selects the appropriate features and adjusts the network for the next iteration. With the help of the discriminator, this method uses multinetwork joint feature extraction to achieve network adaptivity. This method allows features of multiple dimensions to be combined to perform joint training of the network to enhance its generalization ability. The results of cardiac segmentation experiments on X-ray chest radiographs show that this method has higher segmentation accuracy and less overfitting than other methods. In addition, the proposed network is more stable.

In astronomy, physics, climate modeling, geoscience, planetary science, and many other disciplines, the mass of data often comes from spherical sampling. Therefore, establishing an efficient and distortion-free representation of spherical data is essential. This paper introduces a novel spherical (global) coordinate system that is free of singularity. Contrary to classical coordinates, such as Cartesian or spherical polar systems, the proposed coordinate system is naturally defined on the spherical surface. The basic idea of this coordinate system originated from the classical planar barycentric coordinates that describe the positions of points on a plane concerning the vertices of a given planar triangle; analogously, spherical area coordinates (SACs) describe the positions of points on a sphere concerning the vertices of a given spherical triangle. In particular, the global coordinate system is obtained by decomposing the globe into several identical triangular regions, constructing local coordinates for each region, and then combining them. Once the SACs have been established, the coordinate isolines form a new class of global grid systems. This kind of grid system has some useful properties: the grid cells exhaustively cover the globe without overlapping and have the same shape, and the grid system has a congruent hierarchical structure and simple relationship with traditional coordinates. These beneficial characteristics are suitable for organizing, representing, and analyzing spatial data.

A video tracking method based on spatial constrained coding (SCC) is proposed in this study. To characterise local image structure information, the dense scale‐invariant feature transform (SIFT) descriptor is extracted for each pixel in the image. The proposed tracking method uses SCC model which adopts a new constrained strategy – weighted code, which is achieved by considering the sum of the weighted codes based on grey values of neighbouring pixels and distances between them. The proposed model is able to obtain robust code of corresponding pixels in the frames of complex scenes by taking spatial information into account, which enhances the stability of coding and makes the tracker more robust for object tracking. Twelve challenging sequences involving partial or full occlusion, large pose variation and drastic illumination change are chosen to test the proposed method. The experimental results show the proposed method performs excellent in comparison with other previously proposed trackers.

This study proposes a new method to track the moving object based on undecimated scattering transform (UST). The UST removes the down‐sampling operation from the traditional scattering transform to produce a complete representation. Based on the UST, the structural information of object can be captured, which is a highly discriminative representation and facilitates the tracker to distinguish the object from background. The update parameter of tracking model is adaptively adjusted by the correlation coefficient. Occlusion identification is achieved by using a new cascaded model, which can correctly find occlusion and avoid the drift. Experimental results demonstrate that the proposed method is able to track the object accurately and reliably in realistic videos where the appearance and motion change drastically over time.

Many bacteria are known to regulate their cooperative activities and physiological processes through a mechanism called quorum sensing (QS), in which bacterial cells communicate with each other by releasing, sensing and responding to small diffusible signal molecules. The ability of bacteria to communicate and behave as a group for social interactions like a multi-cellular organism has provided significant benefits to bacteria in host colonization, formation of biofilms, defense against competitors, and adaptation to changing environments. Importantly, many QS-controlled activities have been involved in the virulence and pathogenic potential of bacteria. Therefore, understanding the molecular details of quorum sensing mechanisms and their controlled social activities may open a new avenue for controlling bacterial infections.

The presynaptic active zone is a dynamic structure that orchestrates regulated release of neurotransmitters. Developmental and aging processes, and changes in neuronal network activity can all modulate the number, size and composition of active zone and thereby synaptic efficacy. However, very little is known about the mechanism that controls the structural stability of active zone. By studying a model synapse, the Drosophila neuromuscular junction, our recent work shed light on how two scaffolding proteins at the active zone regulate active zone stability by promoting a localized dephosphorylation event at the nerve terminal. Here we discuss the major insights from our findings and their implications for future research.