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Osteopetrosis is an inherited metabolic disease, characterized by increased bone density and narrow marrow cavity. Patients with severe osteopetrosis exhibit abnormal bone brittleness, anemia, and infection complications, which commonly cause death within the first decade of life. Pathologically, osteopetrosis impairs not only the skeletal system, but also the hemopoietic and immune systems during development, while the underlying osteoimmunological mechanisms remain unclear. Osteoclastic mutations are regarded as the major causes of osteopetrosis, while osteoclast non-autonomous theories have been proposed in recent years with unclear underlying mechanisms. Retinoic acid (RA), the metabolite of Vitamin A, is an essential requirement for skeletal and hematopoietic development, through the activation of retinoic acid signaling. RA can relieve osteopetrosis symptoms in some animal models, while its effect on bone health is still controversial and the underlying mechanisms remain unclear. In this study, we constructed an osteoblast-specific inhibitory retinoic acid signaling mouse model and surprisingly found it mimicked the symptoms of osteopetrosis found in clinical cases: dwarfism, increased imperfectly-formed trabecular bone deposition with a reduced marrow cavity, thin cortical bone with a brittle skeleton, and hematopoietic and immune dysfunction. Micro-CT, the three-point bending test, and histological analysis drew a landscape of poor bone quality. Single-cell RNA sequencing (scRNA-seq) of the femur and RNA-seq of osteoblasts uncovered an atlas of pathological skeletal metabolism dysfunction in the mutant mice showing that osteogenesis was impaired in a cell-autonomous manner and osteoclastogenesis was impaired via osteoblast-osteoclast crosstalk. Moreover, scRNA-seq of bone marrow and flow cytometry of peripheral blood, spleen, and bone marrow uncovered pathology in the hematopoietic and immune systems in the mutant mice, mimicking human osteopetrosis. Results showed that hematopoietic progenitors and B lymphocyte differentiation were affected and the osteoblast-dominated cell crosstalk was impaired, which may result from transcriptional impairment of the ligands Pdgfd and Sema4d. In summary, we uncovered previously unreported pathogenesis of osteopetrosis-like disorder in mice with skeletal, hematopoietic, and immune system dysfunction, which was induced by the inhibition of retinoic acid signaling in osteoblasts, and sheds new insights into a potential treatment for osteopetrosis. [ABSTRACT FROM AUTHOR]

Titanium alloys are mostly used in high temperature and high pressure, which requires its high mechanical properties and corrosion resistance. As a good surface modification technology, arc surface cladding has been applied in various fields. In this study, the gas tungsten arc welding was used to clad titanium alloy and the nitrogen gas with different contents were added in the shielding gas. During the cladding process, the TiN strengthening phase was formed in the cladding layer. The effects of different nitrogen flow rates on the microstructure and properties of the cladding layer were studied. The scanning electron microscope (SEM) and the x-ray diffractometer (XRD) were used to observe microstructure and identify the formed phases. The mechanical properties and corrosion properties were studied by Vickers hardness and electrochemical experiments. The results show that after adding nitrogen, the grain size becomes smaller and the hardness increases from 247 to 363 HV. The formation of TiN also improves the pitting corrosion resistance of the cladding layer. The corrosion resistance of the cladding layer was the best when the nitrogen flow rate was 0.4 L/min. Therefore, adding suitable nitrogen gas in the titanium alloy arc cladding process can significantly improve the performance of the cladding layer. [ABSTRACT FROM AUTHOR]

Currently, the predominant method for indirectly obtaining cattle weight data involves establishing the correlation between cattle liveweight and measurable parameters, and subsequently calculating the liveweight of cattle using specific formulas. However, the factors considered in these methods are not comprehensive, which can easily lead to biased weight estimates. Additionally, deep learning-based cattle weight estimation methods typically rely on predicting weight from limited measurable parameters or images, limiting the potential for improved performance. In this study, we propose a novel cattle liveweight estimation algorithm based on composite image/height/length data and spatial and channel attention convolution network (SCA-ConvNet). By combining measurable parameters and images on the channel dimension, our algorithm is able to provide a more comprehensive set of learnable information. Furthermore, the incorporation of channel attention and spatial attention branches in the SCA-ConvNet enhances the network's ability to extract valuable information from the composite data. Through multi-task prediction and loss calculation, our algorithm is able to fully leverage the diverse information available in the channels during training. The experimental results demonstrate that our proposed algorithm outperforms widely used methods including multiple linear regression, Xception, and ConvNeXt in terms of mean-absolute-error, root-mean-square-error, and mean-absolute-percentage-error for cattle liveweight estimation. [ABSTRACT FROM AUTHOR]

Direct sequence spread spectrum (DSSS) communications are highly significant in military and civilian wireless communications because of its ability to resist narrowband interference, multipath interference and high security. However, under low signal-to-noise ratio (SNR), the detection of DSSS signals becomes very difficult under non-cooperative communication. Therefore, in order to improve the detection performance of DSSS signals in fading channels with low SNR, a DSSS signal detection method based on an eigenvalues local binary patterns residual network (EL-ResNet) is proposed with an unknown spread spectrum sequence. Firstly, according to the characteristics of DSSS signals, the eigenvalues of the sample covariance matrix of the DSSS signals are used to construct the signal eigenvalue histograms. This method uses the strong contrast of eigenvalue energy and gradient change to enlarge the discrimination of images with or without DSSS signals. Then, EL-ResNet is built to distinguish between eigenvalue histograms with or without DSSS signals. The local binary patterns (LBPs) are introduced to constrain the loss function of the network, increasing the differentiation of the two types of eigenvalue histograms, and improving the DSSS signal detection performance of the network. Finally, the experimental results show that the performance of the DSSS signal detection method based on EL-ResNet is larger than fast Fourier transform (FFT), FFT-deep neural network (FFT-DNN), covariance matrix-convolutional neural network (CM-CNN) detection methods. [ABSTRACT FROM AUTHOR]

Objective: To investigate the risk factors for delayed postoperative bleeding after endoscopic submucosal dissection (ESD) in patients with gastric precancerous lesions and to construct a risk prediction model. Methods: This retrospective analysis included clinical data from patients with gastric precancerous lesions who underwent ESD at Wuhan University People's Hospital between November 2016 and June 2022. An XGBoost model was built to predict delayed bleeding after ESD using risk factors identified by univariable and multivariate logistic regression analysis. The model was evaluated using receiver operating characteristic curves (ROC), and SHapely Additive exPlanations (SHAP) analysis was used to interpret the model. Results: Seven factors were statistically associated with delayed postoperative bleeding in gastric precancerous lesions after ESD: age, low-grade intraepithelial neoplasia, hypertension, lesion size ≥ 40 mm, operative time ≥ 120 min, female, and nonuse of hemoclips. A risk prediction model was established. In the training cohort, the model achieved an AUC of 0.97 (0.96–0.98), a sensitivity of 0.90, a specificity of 0.94, and an F1 score of 0.91. In the validation cohort, the AUC was 0.94(0.90–0.98), with a sensitivity of 0.85, a specificity of 0.89, and an F1 score of 0.85. In the test cohort, the AUC was 0.94 (0.89–0.99), the sensitivity was 0.80, the specificity was 0.92, and the F1 score was 0.84, indicating strong predictive capability. Conclusion: In this study, an XGBoost prediction model for assessing the risk of delayed postoperative bleeding after ESD in patients with gastric precancerous lesions was developed and validated. This model can be applied in clinical practice to effectively predict the risk of post-ESD bleeding for individual patients. [ABSTRACT FROM AUTHOR]

Adipose progenitor cells (APCs) are heterogeneous stromal cells and help to maintain metabolic homeostasis. However, the influence of obesity on human APC heterogeneity and the role of APC subpopulations on regulating glucose homeostasis remain unknown. Here, we find that APCs in human visceral adipose tissue contain four subsets. The composition and functionality of APCs are altered in patients with type 2 diabetes (T2D). CD9+CD55low APCs are the subset which is significantly increased in T2D patients. Transplantation of these cells from T2D patients into adipose tissue causes glycemic disturbance. Mechanistically, CD9+CD55low APCs promote T2D development through producing bioactive proteins to form a detrimental niche, leading to upregulation of adipocyte lipolysis. Depletion of pathogenic APCs by inducing intracellular diphtheria toxin A expression or using a hunter-killer peptide improves obesity-related glycemic disturbance. Collectively, our data provide deeper insights in human APC functionality and highlights APCs as a potential therapeutic target to combat T2D. All mice utilized in this study are male. Adipose tissue harbors functionally distinct progenitor cell subsets. Using scRNAseq and functional assays, we disclose a pathogenic adipose progenitor subset, which impairs glycose homeostasis through the construction of a detrimental niche. [ABSTRACT FROM AUTHOR]

The impact of interfacial charge on catalytic performance of supported-metal-cluster (SMC) heterostructures remains unclear, hindering efforts to develop high-performance SMC catalysts. Herein we systematically investigated interfacial charge effects of SMCs using a model system of graphene-supported gold-nanoclusters (AuNCs/rGO) for azo hydrogenation. Three types of SMCs with different interfacial charges were synthesized by anchoring electropositive 2-aminoethanethiol (CSH), amphoteric cysteine (Cys), and electronegative 3-mercaptopropionic-acid (MPA) onto AuNCs/rGO, respectively. All three SMCs exhibited high and selective catalytic activity to azo-hydrogenation in four representative azo dyes. The catalytic activity of Cys@AuNCs/rGO was lower than that of CSH@AuNCs/rGO but higher than that of MPA@AuNCs/rGO. However, the cyclic stability of Cys@AuNCs/rGO was inferior to that of both CSH@AuNCs/rGO and MPA@AuNCs/rGO. Further mechanistic studies revealed that amino ligands modified CSH@AuNCs and Cys@AuNCs agglomerated into large-size gold nanoparticles on rGO surface during catalytic reaction under NaBH4 action, leading to reduced efficiency and cyclic stability. Conversely, non-amino ligand modified MPA@AuNCs only partially detached from rGO surface without agglomeration, resulting in better cyclic stability. Protection of amino groups in ligands such as modifying -NH3+ group in Cys into imine to form N-isobutyryl-L-cysteine (NIBC) substantially improved the cyclic stability while maintaining the high activity in the NIBC@AuNCs/rGO catalyst system. Our work provides an approach for developing a highly-active and stable SMC heterostructure catalyst via manipulating interfacial charges in SMC. [ABSTRACT FROM AUTHOR]

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Purpose: Donor-derived infection (DDI) has become an important factor affecting the prognosis of lung transplantation patients. The risks versus benefits of using donor organs infected with multidrug-resistant organisms (MDRO), especially carbapenem-resistant organisms (CRO), are frequently debated. Traditional microbial culture and antimicrobial susceptibility testing at present fail to meet the needs of quick CRO determination for donor lungs before acquisition. In this study, we explored a novel screening method by using Xpert® Carba-R assay for CRO in donor lungs in a real-time manner to reduce CRO-associated DDI mortality. Methods: This study was registered on chictr.org.cn (ChiCTR2100053687) on November 2021. In the Xpert Carba-R screening group, donor lungs were screened for CRO infection by the Xpert Carba-R test on bronchoalveolar fluid (BALF) before acquisition. If the result was negative, donor lung acquisition and subsequent lung transplantation were performed. In the thirty-five potential donors, nine (25.71%) with positive Xpert Carba-R results in BALF were declined for lung transplantation. Twenty-six recipients and the matching CRO-negative donor lungs (74.29%) were included in the Xpert Carba-R screening group. In the control group, nineteen recipients underwent lung transplants without Xpert Carba-R screening. The incidence and mortality of CRO-associated DDI were collected and contrasted between the two groups. Results: Multivariate analysis showed that CRO-related death due to DDI within 60 days was significantly lower in the Xpert Carba-R screening group than that in the control group (OR = 0.05, 95% CI 0.003–0.74, p = 0.03). Conclusion: Real-time CRO screening of donor lungs before transplantation at the point of care by the Xpert Carba-R helps clinicians formulate lung transplantation strategies quickly and reduces the risk of subsequent CRO infection improving the prognosis of lung transplantation. [ABSTRACT FROM AUTHOR]

Protein arginine methyltransferase 9 (PRMT9) is a recently identified member of the PRMT family, yet its biological function remains largely unknown. Here, by characterizing an intellectual disability associated PRMT9 mutation (G189R) and establishing a Prmt9 conditional knockout (cKO) mouse model, we uncover an important function of PRMT9 in neuronal development. The G189R mutation abolishes PRMT9 methyltransferase activity and reduces its protein stability. Knockout of Prmt9 in hippocampal neurons causes alternative splicing of ~1900 genes, which likely accounts for the aberrant synapse development and impaired learning and memory in the Prmt9 cKO mice. Mechanistically, we discover a methylation-sensitive protein–RNA interaction between the arginine 508 (R508) of the splicing factor 3B subunit 2 (SF3B2), the site that is exclusively methylated by PRMT9, and the pre-mRNA anchoring site, a cis-regulatory element that is critical for RNA splicing. Additionally, using human and mouse cell lines, as well as an SF3B2 arginine methylation-deficient mouse model, we provide strong evidence that SF3B2 is the primary methylation substrate of PRMT9, thus highlighting the conserved function of the PRMT9/SF3B2 axis in regulating pre-mRNA splicing. Mutations in protein arginine methyltransferase 9 (PRMT9) are linked to intellectual disability. Here, the authors show that mutant PRMT9 fails to methylate its primary substrate SF3B2, causing aberrant RNA splicing and abnormal synapse development. [ABSTRACT FROM AUTHOR]

Objective: This study evaluated vocal fold leukoplakia using i-scan combined with laryngovideostroboscopy for risk assessment prediction. Methods: A total of 141 patients with 218 lesions were enrolled in this study. Morphological characteristics of leukoplakia, assessment of the vascular pattern using i-scan, and vocal fold vibratory function were analyzed. Results: The number of patients with no, mild, moderate, severe dysplasia, and invasive carcinoma were 68, 40, 17, 46 and 47, respectively. The sensitivity of morphological characteristic, vascular pattern, vibratory function and predictive model were 77.4%, 72%, 69.9%, and 82.8%, respectively. Receiver operating characteristic curve analysis of morphological characteristic, vascular pattern, vibratory function and predictive model were 0.771, 0.824, 0.769, and 0.923, respectively. The results of logistic regression analysis showed that rough morphological types, perpendicular vascular pattern, severe decrease and absence of mucosal waves increased the risk of malignancy (OR = 5.531, 4.973, and 16.992, respectively; P < 0.001). Conclusions: I-scan combined with laryngovideostroboscopy can improve the differential diagnosis of low-risk and high-risk vocal fold leukoplakia. [ABSTRACT FROM AUTHOR]

Finger vein recognition is an important biometric method, and its performance is easily affected by noise. The widely used Denoising Convolutional Neural Network (DnCNN) and Fast and Flexible Denoising Network (FFDNet) tend to have smoother images after denoising, and fail to fully retain information such as vein image edges and textures. To this end, a finger vein denoising net based on gradient-oriented residual structure and Local Binary Patterns (LBP) texture loss constraints, referred to as LGR-Net is proposed. First, a gradient direction operator is introduced in the residual structure to avoid the loss of gradient direction information in the denoised vein image. Second, the local features such as the texture of the shallow layer of the image are fused with the semantic information of the deep layer through the layer-skip connection, so as to preserve the semantic and local information of the denoised vein image as much as possible. Finally, an LBP loss term is added to the loss function to enhance the recovery ability of vein texture. The simulation experiments were carried out on the laboratory dust and stripe fingervein data sets. The results show that the proposed algorithm has better visual effect, Peak Signal-to-Noise Ratio (PSNR), and recognition performance, compared with the traditional Block-Matching and 3D filtering BM3D denoising algorithm, DnCNN algorithm, FFDNet algorithm and RDUNet algorithm. [ABSTRACT FROM AUTHOR]

Background: The course of disease after microvascular decompression (MVD) in patients with hemifacial spasm (HFS) is variable. The purpose of this study was to develop and validate a nomogram to predict the probability of delayed cure after microvascular decompression in patients with hemifacial spasms based on clinical multivariate factors. Methods: A retrospective data collection was performed on 290 patients with HFS undergoing MVD at our center from January 2017 to January 2022. The patients were randomly assigned to the training cohort (n = 232) and validation cohort (n = 58) at a ratio of 8:2. Retrospective analysis was performed of information on clinical, radiological, and intraoperative findings and clinical outcomes. Univariate and multivariate analyses were performed in the training cohort, and a nomogram was constructed using a stepwise logistic regression approach. The receiver operating characteristic (ROC) was calculated to evaluate the reliability of the nomogram model. Decision curve analysis (DCA) was used to assess the clinical application value of the nomogram model. Results: In the training cohorts, 73 patients (73/232) had a delayed cure. In the validation cohorts, 18 patients (18/58) had a delayed cure. We developed a novel nomogram model to predict the risk of delayed cure after MVD in HFS patients based on the presence of vertebral artery compression, venous compression, absence of LSR, degree of facial nerve indentation, degree of neurovascular compression, and internal auditory canal vascular looThe area under the curve (AUC) of the nomogram model was 0.9483 in the training cohort and 0.9382 in the validation cohort. The calibration curve showed good correspondence between the predicted and actual probabilities in the training and validation groups. The decision curve showed that the nomogram model had good performance in clinical applications. Conclusions: We developed and validated a preoperative and intraoperative multivariate factors nomogram to predict the possibility of delayed cure after MVD in HFS patients, which may help clinicians in the comprehensive management of HFS. [ABSTRACT FROM AUTHOR]

Surgery plays a crucial role in the treatment of patients with chronic pulmonary aspergillosis (CPA). However, there is currently limited information available regarding the use of uniportal thoracoscopy (Uni-VATS) in CPA patients. To address this gap, we conducted a retrospective analysis of surgical procedures performed at a single center, aiming to demonstrate the feasibility and safety of Uni-VATS for patients with CPA. We collected basic information and surgical data from patients who underwent surgery for CPA at our hospital between January 2018 and June 2022. All patients received voriconazole antifungal medication for 3–6 months post-surgery and were monitored for a minimum of 6 months. A total of 110 patients, comprising 59 cases in the traditional open chest incision group and 51 cases in the Uni-VATS group, met the inclusion criteria. Among those who underwent surgery, 70% were male (77/110). The median age (IQR) of all enrolled patients was 55 (46–62) years. There were no statistically significant differences in general information, such as age, sex, comorbidities, BMI, FEV1, FVC, clinical symptoms, location of the disease, and duration of voriconazole antifungal medication, between the OS group and the Uni-VATS group (p > 0.05). The postoperative complication rates were 40.7% (24/59) for the traditional open chest incision group and 17.6% (9/51) for the Uni-VATS group. Through univariate analysis, we identified sex and operative approach as risk factors for postoperative complications. Multivariate logistic analysis confirmed that male and OS procedures were the independent risk factors for postoperative complications. There were statistically significant differences in operative time, intraoperative blood loss volume, postoperative drainage volume, pain scores, postoperative drainage tube removal time, postoperative hospital stay time between the OS group and the Uni-VATS group (p < 0.05). Uni-VATS is a feasible and safe surgical procedure for patients with CPA, and we recommend it as a preferred option for selected patients with CPA. [ABSTRACT FROM AUTHOR]

Febrile seizures (FS) are the most prevalent type of seizures in children. Existing predictive models for FS exhibit limited predictive ability. To build a better-performing predictive model, a retrospective analysis study was conducted on febrile children who visited the Children's Hospital of Shanghai from July 2020 to March 2021. These children were divided into training set (n = 1453), internal validation set (n = 623) and external validation set (n = 778). The variables included demographic data and complete blood counts (CBCs). The least absolute shrinkage and selection operator (LASSO) method was used to select the predictors of FS. Multivariate logistic regression analysis was used to develop a predictive model. The coefficients derived from the multivariate logistic regression were used to construct a nomogram that predicts the probability of FS. The calibration plot, area under the receiver operating characteristic curve (AUC), and decision curve analysis (DCA) were used to evaluate model performance. Results showed that the AUC of the predictive model in the training set was 0.884 (95% CI 0.861 to 0.908, p < 0.001) and C-statistic of the nomogram was 0.884. The AUC of internal validation set was 0.883 (95% CI 0.844 to 0.922, p < 0.001), and the AUC of external validation set was 0.858 (95% CI 0.820 to 0.896, p < 0.001). In conclusion, the FS predictive model constructed based on CBCs in this study exhibits good predictive ability and has clinical application value. [ABSTRACT FROM AUTHOR]

The riparian zone ecosystems have greater energy flow and elemental cycling than adjacent terrestrial and aquatic ecosystems. Mineralization and nitrification are important initiating processes in the nitrogen cycle, but their distribution and activity under different environmental conditions in the riparian zone and the driving mechanisms are still not clear. We investigated the effects of environmental and microbial factors on mineralization and nitrification activities by analyzing the community of alkaline (apr) and neutral (npr) metallopeptidase, ammonia-oxidizing archaea (AOA), and bacteria (AOB) in soils and sediments under different land-use types in the riparian zone of Miyun Reservoir, as well as measuring potential nitrogen mineralization and ammonia oxidation rates (AOR). The results showed that the mineralization and nitrification activities of soils were greater than those of sediments. AOA and AOB dominate the ammonia oxidation activity of soil and sediment, respectively. NH4+ content was a key factor influencing the ecological niche differentiation between AOA and AOB. The high carbon and nitrogen content of the woodland significantly increased mineralization and nitrification activity. Microbial communities were significantly clustered in the woodland. The land-use type, not the flooding condition, determined the distribution of microbial community structure. The diversity of npr was significantly correlated with potential N mineralization rates, while the transcript abundance of AOA was significantly correlated with ammonia oxidation rates. Our study suggests that environmental changes regulate the distribution and activity of mineralization and nitrification processes in the reservoir riparian zone by affecting the transcript abundance, diversity and community structure of the microbial functional genes. [ABSTRACT FROM AUTHOR]

Cr-Co-Mo-Ni high-hardness steel is widely used in critical mechanical transmission components. It has the difficult-to-cut characteristic because of its high hardness and high strength. In the cutting process, the machining cutting force is large, the tool is worn quickly, and the machining accuracy is poorly maintained. It has become one of the crux of restricting the improvement of quality and production efficiency of innovative products. In order to solve the above problems, this paper carried out research on the electrochemical machining process to achieve high-quality and efficient machining of high-hardness gear steel splines. Firstly, the process characteristics of ECM of internal spline are analyzed. The electrochemical field model is established by the multi-physical field coupling simulation platform, and the effects of the main electrolytic process parameters on the forming accuracy were numerically simulated and analyzed. Meanwhile, the three-dimensional simulation model of electrolyte flow field in the inner cavity of the electrolytic fixture is established, and the influence of electrolyte flow direction and electrolyte back pressure on the flow field distribution is explored. The platform of electrochemical machining system is set up. An experimental study on electrochemical machining of involute internal splines is carried out to further optimize the electrochemical machining process parameters. The test results showed that the electrolysis accuracy and efficiency of the 41-tooth involute spline workpiece are optimized when the electrolyte is 8% NaNO3, the back pressure of the electrolyte is 0.2 MPa, the feed speed is 1.8 mm/min, and the processing voltage is 16.0 V. The machining accuracy of the method proposed in this paper meets the actual requirements of actual gear application. Compared with the traditional slotting process, the machining efficiency is improved by 62.5%, the tool wear is reduced, and the machining accuracy retention is improved. It has important application value for advanced machining technology of high-performance materials. [ABSTRACT FROM AUTHOR]

Finger vein recognition technology has been widely used in various identity authentication scenarios due to its convenience, fast recognition speed, and high security. However, there is an inevitable problem that seriously affects its recognition, which is the change of finger poses, such as shift and rotation during the image acquisition process. Therefore, how to extract finger vein features that are more robust to finger pose changes is a more concerned issue. We analyze the multi-pose finger vein images in practical application scenarios, and find the fact that the global vein features of the same finger are quite different while the local features are highly similar. In most existing finger vein recognition algorithms based on convolutional neural network (CNN), only global finger vein features are extracted by global average pooling (GAP), which fails to take full account of the above fact. In this paper, we proposed a finger vein feature extraction network fusing global and local features (FGL-Net) and its lightweight network KD-FGL-MobileNet, which effectively improves finger vein recognition performance in different finger poses. Firstly, FGL-Net consists of two parts, the backbone network based on the designed ResBlock with Mish is used to extract the high-level semantic features of finger veins, and then the global and local feature extraction module with three independent branches are designed to fully learn the global and local finger vein features at different granularities, and finally all the features of the three branches are fused into a fusion feature with greater robustness to pose change for recognition. To improve the generalization ability of the network, the CurricularFace loss is added to train FGL-Net with the cross-entropy loss. Such design not only aggregates homologous features and separates heterologous features, but also mines finger vein image samples under special poses online for intensive training. Secondly, according to the characteristics of the finger veins, we design a lightweight residual block based on fast receptive field (SE-FrfResBlock) to build a more lightweight FGL-MobileNet. A knowledge distillation loss and a feature map loss are added to FGL-MobileNet to address the generalization performance degradation of FGL-MobileNet, and we named it KD-FGL-MobileNet. On FV-USM, FV-Normal and FV-Specical datasets, compared with VGG-Net and InceptionResnet, the Top1 ranking of FGL-Net are improved by 2.38%, 8.26%, 13.42% and 0.00%, 1.17%, 9.95%, and the recognition rate are improved by 9.42%, 18.59%, 28.33% and 0.72%, 7.12%, 20.88%. On FV-Specical datasets, compared with MobileNetv3, FGL-MobileNet, the recognition rate and Top1 ranking of KD-FGL-MobileNet are improved by 24.12% ,6.19% and 12.46%, 3.78%. The above results show that the proposed FGL-Net effectively improves the recognition performance of finger vein images in different poses, and KD-FGL-MobileNe requires less storage space while remaining basically consistent with the performance of FGL-Net. [ABSTRACT FROM AUTHOR]

Introduction: The symptom of constipation has been confirmed as an early diagnose criteria for Parkinson's disease (PD). Furthermore, evidences suggest that pathogenesis of PD initiates in gut, rather than brain. If so, identifying biomarkers for constipation in PD might have potentials to assist early diagnosis and initial treatment. Method: We first identified that microRNA 29c (miR-29c) was dysregulated both in PD and constipation patients through bioinformatics analysis. Then, serological analysis of the expression of miR-29c in 67 PD patients with constipation (PD–C), 51 PD patients without constipation (PD-NC), and 50 healthy controls (HC) was carried out by qPCR. Demographic and clinical features were also compared. Patients in PD–C group were further classified into two groups: those with prodromal stage constipation (PD–C-Pro) (n = 36) and those with clinical stage constipation (PD–C-Clinic) (n = 31), to explore their different characteristics. Results: The levels of miR-29c in PD–C group were higher than that in PD-NC group, both higher than HC group. PD–C-Pro group's miR-29c levels were statistically higher compared with PD–C-Clinic group's. What is more, PD–C group had higher scores of MDS-UPDRS-I, NMSS, NMSS3, NMSS4, NMSS6, NMSS9, SCOPA-AUT, HAMD, HAMA, RBDSQ, CSS, and PACQOL compared with PD-NC party. Relative to the PD–C-Clinic, patients in PD–C-Pro group had higher MDS-UPDRS-I, NMSS, NMSS3, HAMD, and HAMA scores, and were more likely to have RBD. Conclusion: Our results indicated that miR-29c seems to be an underlying cause for developing constipation in patients with PD and PD–C identifies a group of patients with more severe non-motor impairment, prominent neuropsychiatric disorders, and possible RBD conversion as well as a substandard quality of life. We further confirmed that there is a close relationship between symptoms representing the same pathological origin, especially constipation and RBD. [ABSTRACT FROM AUTHOR]

A Gram-stain-negative, rod-shaped, non-flagellated, pale-yellow bacterium, designated GHJ8T, was isolated from the rhizosphere soil of Ulmus pumila L., Shanxi Province, China. Growth occurred at 20–37 °C (optimum, 28 °C), pH 6.0–11.0 (optimum, pH 8.0), and 0–1% NaCl (optimum, 0%). Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain GHJ8T was related to members of the genus Luteolibacter, and close to Luteolibacter flavescens GKXT (98.5%), Luteolibacter luteus G-1-1-1T (97.3%), Luteolibacter arcticus MC 3726T (97.2%), and Luteolibacter marinus NBU1238T (96.0%). The genome size of strain GHJ8T was 6.2 Mbp, with a G + C content of 62.5%. Genomic mining revealed that the strain contained antibiotic resistance genes and secondary metabolic gene clusters, indicating that it had adaptation mechanisms to environmental stress. Comparative genomic analyses clearly separated strain GHJ8T from the recognized species of the genus Luteolibacter based on average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values below the thresholds for species delineation. The major cellular fatty acids were iso-C14:0 (30.8%), C16:1ω9c (23.0%), C16:0 (17.3%), and C14:0 (13.4%). The quinone system was composed of the major menaquinones MK-8, MK-9, and MK-10, and the principal polar lipids were diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, an unidentified aminophospholipid, an unidentified glycolipid, two unidentified phospholipids, and three unidentified lipids. Based on its phenotypic and genotypic properties and phylogenetic inference, strain GHJ8T is a novel species of the genus Luteolibacter, for which the name Luteolibacter rhizosphaerae sp. nov. is proposed. The type strain is GHJ8T (= GDMCC 1.2160T = KCTC 82452T = JCM 34400T). [ABSTRACT FROM AUTHOR]

Aims: The objective of this study was to develop and validate an easy-to-use risk score (APRS) to predict which patients with acute pancreatitis (AP) will need intensive care unit (ICU) treatment within 48 h post-hospitalization on the basis of the ubiquitously available clinical records. Methods: Patients with acute pancreatitis were retrospectively included from three independent institutions (RM cohort, 5280; TJ cohort, 262; SN cohort, 196), with 56 candidate variables collected within 48 h post-hospitalization. The RM cohort was randomly divided into a training set (N = 4220) and a test set (N = 1060). The most predictive features were extracted by LASSO from the RM cohort and entered into multivariate analysis. APRS was constructed using the coefficients of the statistically significant variables weighted by the multivariable logistic regression model. The APRS was validated by RM, TJ, and SN cohorts. The C-statistic was employed to evaluate the APRS's discrimination. DeLong test was used to compare area under the receiver operating characteristic curve (AUC) differences. Results: A total of 5738 patients with AP were enrolled. Eleven variables were selected by LASSO and entered into multivariate analysis. APRS was inferred using the above five factors (pleural effusion, ALT/AST, ALB/GLB, urea, and glucose) weighted by their regression coefficients in the multivariable logistic regression model. The C-statistics of APRS were 0.905 (95% CI 0.82–0.98) and 0.889 (95% CI 0.81–0.96) in RM and TJ validation. An online APRS web-based calculator was constructed to assist the clinician to earlier assess the clinical outcomes of patients with AP. Conclusion: APRS could effectively stratify patients with AP into high and low risk of ICU admission within 48 h post-hospitalization, offering clinical value in directing management and personalize therapeutic selection for patients with AP. [ABSTRACT FROM AUTHOR]

Despite extensive researches on the motion of polymer chains on lipid membranes, the effect of membrane fluctuations on polymer chain dynamics remains poorly understood. Here we report single molecule tracking experiments that allow for comparable measurements of polymer chain diffusion dynamics on nanotubular and planar phospholipid membranes. We observe a super-diffusion behavior and no apparent chain-length-dependent mobility of polymer chains on nanotubular membranes, while a Brownian motion and apparent chain-length-dependent mobility of polymer chains on planar membranes. We suggest the super-diffusion nature of polymer chains may be due to the thermal-fluctuations of lipid nanotubes, which can be described from a statistical thermodynamic phenomenon coupling of polymer chain dynamics and surface thermal fluctuations. We suggest that the existence of surface environment fluctuations should influence the dynamics of the adsorbed polymer chains. This study provides previously uncharacterized insights into polymer diffusion dynamics on thermal-fluctuating flexible surfaces, which is essential to understanding the effect of environment fluctuations on polymer chain behaviors. [ABSTRACT FROM AUTHOR]

Multi-view stereo (MVS) methods based on deep learning have developed rapidly in recent years, but inaccuracies in reconstruction due to the general effect of feature extraction and poor correlation between cost volumes are still present, opening possibilities for improvement in reconstruction accuracy and completeness. We therefore develop a hierarchical MVS network model with cost volume separation and fusion to mitigate these problems. First, to obtain a more complete and accurate feature information from the input images, a U-shape feature extraction module was designed that outputs feature information simultaneously according to a hierarchical structure composed of three different scales. Then, to enhance the learning ability of the network structure for features, we introduced attention mechanisms to the extracted features that focus on and learn the highlighted features. Finally, in the cost volume regularization stage, a cost volume separation and fusion module was designed in the structure of a hierarchical cascade. This module separates the information within the small-scale cost volume, passes it to the lower level cost volume for fusion, and performs a coarse-to-fine depth map estimation. This model results in substantial improvements in reconstruction accuracy and completeness. The results of extensive experiments on the DTU dataset show that our method performs better than Cascade-MVSNet by about 10.2% in accuracy error (acc.), 7.6% in completeness error (comp.), and 9.0% in overall error (overall), with similar performance in the reconstruction completeness, showing the validity of our module. [ABSTRACT FROM AUTHOR]

Dry eye disease (DED) is a common disease associated with disorder of tear secretion. Research on risk factors for DED, such as depression, arthritis, thyroid disease, stroke and diabetes, is important to facilitate its diagnosis and prognosis. We created a dataset on risk factors for DED (DrDED) with public access that can provide up-to-date and validated data acquired from systematically searched and screened, high-quality studies. The established DrDED contained 119 studies published between 2000 and 2022. The range of the study sample size was from 43 to 4,871,504. The study types were, as follows: cross-sectional (n = 92), retrospective cohort (n = 9), prospective cohort (n = 10), and case-control (n = 8) studies. Data from eligible studies were collected and presented for the present study, including the publication information, study characteristics, definition and prevalence of the disease, and risk factors for DED, together with the strength of association. With the publication of new relevant studies, the DrDED will be updated, and the data will be made accessible to the users. Design Type(s) Dataset creation objective Measurement Type(s) Patient outcome • scientific publication • risk factors • dry eye disease Technology Type(s) Digital curation • documenting • meta-analysis Factor Type(s) Depression • arthritis • thyroid disease • stroke disease • diabetes Sample Characteristic(s) Homo sapiens • dry eye disease • global [ABSTRACT FROM AUTHOR]

Group 2 innate lymphoid cells (ILC2s) play important tissue resident roles in anti-parasite immunity, allergic immune response, tissue homeostasis, and tumor immunity. ILC2s are considered tissue resident cells with little proliferation at steady state. Recent studies have shown that a subset of small intestinal ILC2s could leave their residing tissues, circulate and migrate to different organs, including lung, liver, mesenteric LN and spleen, upon activation. However, it remains unknown whether other ILC populations with migratory behavior exist. In this study, we find two major colon ILC2 populations with potential to migrate to the lung in response to IL-25 stimulation. One subset expresses IL-17A and resembles inflammatory ILC2s (iILC2s) but lacks CD27 expression, whereas the other expresses CD27 but not IL-17A. In addition, the IL-17A+ ILC2s express lower levels of CD127, CD25, and ST2 than CD27+ ILC2s, which express higher levels of IL-5 and IL-13. Surprisingly, we found that both colon ILC2 populations still maintained their colonic features of preferential expression of IL-17A and CD27, IL-5/IL-13, respectively. Together, our study identifies two migratory colon ILC2 subsets with unique surface markers and cytokine profiles which are critical in regulating lung and colon immunity and homeostasis. [ABSTRACT FROM AUTHOR]

Lower-grade glioma (LGG) is a common primary brain tumor with a highly heterogeneous clinical presentation, and its prognosis cannot be accurately predicted by current histopathology. It has been found that mitochondria play an important role in hypoxia, angiogenesis, and energy metabolism in glioma, and mitochondrial function may have an important impact on LGG prognosis. The goal of this study was to develop a novel prognostic model based on Mitochondrial-related genes (MRGs). We first analyzed the somatic alterations profiles of MRGs in patients with LGG and found that somatic alterations were common in LGG and correlated with prognosis. Using RNA-seq data from TCGA and CGGA, 12 prognosis-related MRGs were identified to construct a mitochondrial activation score (MiAS) model by combining univariate regression and LASSO regression analysis. The model and nomogram were evaluated using the area under the ROC curve with AUC = 0.910. The model was closely correlated with the clinical characteristics of LGG patients and performed well in predicting the prognosis of LGG patients with significantly shorter overall survival (OS) time in the high-MiAS group. GSVA and GSEA results showed that oxidative stress, pro-cancer, and immune-related pathways were significantly enriched in the high-MiAS group. CIBERSORT results showed that MiAS was significantly associated with immune cell infiltration in LGG. Macrophage M1 and follicular helper T cells had increased infiltration in the high-MiAS group. TIDE predicted a better immunotherapy outcome in patients in the low-MiAS group. Finally, using data from the CTRPv2 and GDSC2 datasets to assess chemotherapy response in LGG, it was predicted that the chemotherapeutic agents AZD6482, MG-132, and PLX-4720 might be potential agents for patients in the high-MiAS group of LGG. In addition, we performed in vitro experiments and found that knockdown of OCIAD2 expression reduced the abilities of glioma cells to proliferate, migrate, and invade. In contrast, overexpression of OCIAD2 enhanced these abilities of glioma cells. This study found that MRGs were correlated with LGG patient prognosis, which is expected to provide new treatment strategies for LGG patients with different MiAS. [ABSTRACT FROM AUTHOR]

Functionalized superwetting materials that are able to deal with the contamination problems of industrial and domestic oily wastewater are urgently demanded in the field of oil–water separation. In this work, we fabricated superhydrophobic absorbent with excellent electrothermal conversion performance through the liquid-phase reduction and hierarchically assemble methods. The adhesive layer of poly-dopamine (PDA), Cu/carbon microspheres composites (Cu/CMSs) and the fluoride-free hydrophobic reagents were successively assembled on the absorbent cotton to obtain the intelligent absorbent with excellent superhydrophobicity (WCA = 154°), satisfactory oil–water separation efficiency (> 98.3%) and high oil absorption capacity (12–20 g/g). Surprisingly, this intelligent absorbent displayed an excellent electrothermal conversion capacity, which provided the basis for the collection of high-viscosity oil and the low-melting solid oil. On the basis of the excellent electrothermal conversion performance, it also could be utilized as a filter to effectively realize the continuous separation process of high-viscosity crude oil/water mixture under low-voltage conditions. Therefore, this intelligent absorbent possesses broad application prospects in high-viscosity oil–water separation, oily wastewater treatment, oil spill cleaning, crude oil extraction, petrochemicals and other fields. [ABSTRACT FROM AUTHOR]

Deep learning (DL) has indeed emerged as a powerful tool for rapidly and accurately predicting materials properties from big data, such as the design of current commercial Li-ion batteries. However, its practical utility for multivalent metal-ion batteries (MIBs), the most promising future solution of large-scale energy storage, is limited due to scarce MIB data availability and poor DL model interpretability. Here, we develop an interpretable DL model as an effective and accurate method for learning electrode voltages of multivalent MIBs (divalent magnesium, calcium, zinc, and trivalent aluminum) at small dataset limits (150–500). Using the experimental results as validation, our model is much more accurate than machine-learning models, which usually are better than DL in the small dataset regime. Besides the high accuracy, our feature-engineering-free DL model is explainable, which automatically extracts the atom covalent radius as the most important feature for the voltage learning by visualizing vectors from the layers of the neural network. The presented model potentially accelerates the design and optimization of multivalent MIB materials with fewer data and less domain-knowledge restriction and is implemented into a publicly available online tool kit in http://batteries.2dmatpedia.org/ for the battery community. [ABSTRACT FROM AUTHOR]

Traditional inpainting methods obtain poor performance for finger vein images with blurred texture. In this paper, a finger vein image inpainting method using Neighbor Binary-Wasserstein Generative Adversarial Networks (NB-WGAN) is proposed. Firstly, the proposed algorithm uses texture loss, reconstruction loss, and adversarial loss to constrain the network, which protects the texture in the inpainting process. Secondly, the proposed NB-WGAN is designed with a coarse-to-precise generator network and a discriminator network composed of two Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN-GP). The cascade of a coarse generator network and a precise generator network based on Poisson fusion can obtain richer information and get natural boundary connection. The discriminator consists of a global WGAN-GP and a local WGAN-GP, which enforces consistency between the entire image and the repaired area. Thirdly, a training dataset is designed by analyzing the locations and sizes of the damaged finger vein images in practical applications (i.e., physical oil dirt, physical finger molting, etc). Experimental results show that the performance of the proposed algorithm is better than traditional inpainting methods including Curvature Driven Diffusions algorithm without texture constraints, a traditional inpainting algorithm with Gabor texture constraints, and a WGAN inpainting algorithm based on attention mechanism without texture constraints. [ABSTRACT FROM AUTHOR]

A Gram-stain-negative, cocci-to-oval-shaped bacterial strain, designated XZZS9T, was isolated from the rhizosphere soil of Pinus sylvestris var. mongolica and characterized taxonomically using a polyphasic approach. Growth occurred at 20–35 °C (optimum, 28 °C), pH 6.0–11.0 (optimum, pH 7.0), and in 0–1% NaCl (optimum, 0%). Phylogenetic analysis based on 16S rRNA gene sequencing indicated that strain XZZS9T was related to members of the genus Roseococcus, with the highest sequence identity to Roseococcus microcysteis NIBR12T (96.9%). The major cellular fatty acids (> 5% of the total) were C18:1ω7c and C19:0 cyclo ω8c. The major isoprenoid quinone was Q-9 and the polar lipid profile contained diphosphatidylglycerol, phosphatidylglycerol, phosphatidylcholine, phosphatidylethanolamine, an unidentified glycophospholipid, and an unidentified phospholipid. Genome sequencing revealed that had a genome size of 4.79 Mbp with a G + C content of 69.5%. Comparative genomic analyses clearly separated strain XZZS9T from the known species of the genus Roseococcus based on average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values below the thresholds for species delineation. Genome annotations did not find pufL and pufM genes in strain XZZS9T, suggesting a possible lack of photosynthetic reaction. Based on genotypic and phenotypic characteristics, strain XZZS9T represents a novel species of the genus Roseococcus, for which we propose the name Roseococcus pinisoli sp. nov. The type strain is XZZS9T (= KCTC 82435T = JCM 34402T = GDMCC 1.2158T). [ABSTRACT FROM AUTHOR]

Beyond a function in hemostasis and thrombosis, platelets can regulate innate and adaptive immune responses. Hyperactive platelets are frequently associated with multiple human autoimmune diseases, yet their pathogenic functions in these diseases have not been fully established. Emerging studies show an essential function of the phosphatase and tensin homolog (PTEN) in maintenance of immune homeostasis. Here, we show that mice with platelet-specific deletion of Pten, develop age-related lymphoproliferative diseases and humoral autoimmunity not seen in wildtype animals. Platelet-specific Pten-deficient mice have aberrant T cell activation, excessive T follicular helper (Tfh) cell responses and accumulation of platelet aggregates in lymph nodes. Transferred Pten-deficient platelets are able to infiltrate into the peripheral lymphoid tissues and form more aggregates. Moreover, Pten-deficient platelets are hyperactive and overproduce multiple Tfh-promoting cytokines via activation of the PDK1/mTORC2-AKT-SNAP23 pathway. Pten-deficient platelets show enhanced interaction with CD4+ T cells and promote conversion of CD4+ T cells into Tfh cells. Our results implicate PTEN in platelet-mediated immune homeostasis, and provide evidence that hyperactive platelets function as an important mediator in autoimmune diseases using mouse models. Platelets have been shown to alter immune cell function but it is not clear if this includes autoimmunity. Here the authors show that phosphatase and tensin homolog (PTEN) deficient platelets promote autoimmunity in mouse models through excessive activation of TFH cells and systemic autoimmune pathology. [ABSTRACT FROM AUTHOR]

This paper experimentally examines variations in the macroscopic properties of concrete under the interaction of early-age temperature and salt ion corrosion and investigates the microscopic mechanism of these variations from the perspective of pore structure and microcracks. The results show a prominent initial defect compaction stage of the compressive stress–strain curves of the specimens under the interaction of two factors, an increase in the number of pores and a high degree of crack development. Accordingly, the peak strength, secant elastic modulus and porosity of the specimens are greatly affected by the interaction between early-age temperature and salt ion corrosion, as reflected by the obvious deterioration trend. Based on a theoretical analysis, the concept of the initial defect strain ratio is proposed, the relationship between the total deformation and two indicators (initial defect deformation and matrix deformation) is clarified, and a constitutive model that reflects the initial defect compaction characteristics is established. [ABSTRACT FROM AUTHOR]

Intervertebral disc disease (IDD) is a primary cause of low back pain, affecting 5% of individuals. Previous study have shown that dual-specificity (Thr/Tyr) phosphatase 1 (DUSP1) regulates p38 MAPK activity and DUSP1 level is regulated by ubiquitination. As an E3 ubiquitin-protein ligase, UBR3 has been shown to regulate a variety of biological processes through ubiquitination. However, the role of UBR3/DUSP1/p38 in IDD remains to be elucidated. In the current study, we found that UBR3 was significantly increased in the nucleus pulposus tissues of IDD patients and was correlated with IDD severity. Silencing UBR3 promoted the growth, inhibited apoptosis, and inhibited inflammation in primary NPCs. Mechanism study suggested that UBR3 exerted its effects through p38. Co-immunoprecipitation assay indicated that UBR3 promoted DUSP1 ubiquitination. Overexpression of DUSP1 reversed the effect of UBR3 overexpression. Our data also supported that UBR3 was positively correlated with p-p38, but negatively correlated with DUSP1 in IDD. In summary, UBR3 promotes inflammation and apoptosis via inhibiting the p38 signaling pathway by DUSP1 ubiquitination in the NPCs of IDD patients. These findings highlight the importance of UBR3/DUSP1/p38 signaling pathway in IDD and provide new insights for the prevention and treatment of IDD. [ABSTRACT FROM AUTHOR]

Using high-throughput first-principles calculations to search for layered van der Waals materials with the largest piezoelectric stress coefficients, we discover NbOI2 to be the one among 2940 monolayers screened. The piezoelectric performance of NbOI2 is independent of thickness, and its electromechanical coupling factor of near unity is a hallmark of optimal interconversion between electrical and mechanical energy. Laser scanning vibrometer studies on bulk and few-layer NbOI2 crystals verify their huge piezoelectric responses, which exceed internal references such as In2Se3 and CuInP2S6. Furthermore, we provide insights into the atomic origins of anti-correlated piezoelectric and ferroelectric responses in NbOX2 (X = Cl, Br, I), based on bond covalency and structural distortions in these materials. Our discovery that NbOI2 has the largest piezoelectric stress coefficients among 2D materials calls for the development of NbOI2-based flexible nanoscale piezoelectric devices. The recent thrust toward flexible nanoscale devices creates a need for two-dimensional piezoelectric materials. Here, the authors find large piezoelectric response in NbOI2 flakes ranging from 4 nm to the bulk. [ABSTRACT FROM AUTHOR]

Strain XMGL2T, isolated from rhizosphere soil of Quercus mongolica in China, was characterized using a polyphasic taxonomic approach. Cells were Gram-negative, aerobic, non-spore-forming, and rod-shaped. Growth occurred at 20–37 °C (optimum, 28 °C), pH 5.0–10.0 (optimum, pH 6.0), and with 0–1% NaCl (optimum, 1%). Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain XMGL2T was related to members of the genus Sphingomonas and had the highest 16S rRNA gene sequence identity to Sphingomonas oleivorans FW-11 T (96.4%). The average nucleotide identity and digital DNA–DNA hybridization values between strain XMGL2T and the closely related taxa Sphingomonas oleivorans FW-11 T and Sphingomonas fennica K101T were 75.3/19.8% and 75.8/20.2%, respectively. The major cellular fatty acids were C18:1ω7c, C14:0 2-OH, and C16:0. The major isoprenoid quinone was Q-10 and the polar lipid profile contained diphosphatidylglycerol, phosphatidylglycerol, phosphatidylcholine, phosphatidylethanolamine, phosphatidyldimethylethanolamine, phosphatidylmonomethylethanolamine, an unidentified glycophospholipid and an unidentified phospholipid. The genomic DNA G + C content was 67.9%. Based on the phenotypic and genotypic properties and phylogenetic inference, strain XMGL2T represents a novel species of the genus Sphingomonas, for which the name Sphingomonas quercus sp. nov. is proposed. The type strain is XMGL2T (= JCM 34441 T = GDMCC 1.2153 T). [ABSTRACT FROM AUTHOR]

Aim: This study investigated the effects of sodium-glucose cotransporter 2 (SGLT2) inhibitors on renal outcomes in Asian patients with type 2 diabetes mellitus (T2DM). Materials and methods: We searched Medline, EMBASE, and the Cochrane Library to identify randomized controlled trials published up to April 2020 that compared SGLT2 inhibitors with placebo or active comparator and reported any renal outcomes in Asian patients with T2DM. Random effects models and inverse variance weighting were used to calculate relative risks with 95% confidence intervals (CIs). Results: We included 14 studies, totaling 3792 patients, in the analysis. In the short term, SGLT2 inhibitors significantly slowed estimated glomerular filtration rate (eGFR) decline (MD: 0.80; 95% CI: 0.66 to 0.94; p < 0.00001) and reduced Scr levels (SMD: − 0.17; 95% CI: − 0.23 to − 0.10; p < 0.00001) as compared with the control groups. The SGLT2 inhibitor group also had an advantage over the control group in lowering uric acid (UA) (SMD: − 1.2; 95% CI: − 1.30 to − 1.11; p < 0.00001). There was no significant difference in urinary albumin creatinine ratio (UACR) reduction between the SGLT2 inhibitor and control groups (MD: − 8.87; 95% CI: − 19.80 to 2.06; p = 0.11). However, dapagliflozin does appear to reduce albuminuria (p = 0.005). Lastly, SGLT2 inhibitors increased the incidence of adverse events (AEs) related to renal function (OR: 1.90; 95% CI: 1.24 to 2.91; p = 0.003), but did not increase the incidence of renal impairment (OR: 0.85; 95% CI: 0.40 to 1.81; p = 0.68). Conclusion: The use of SGLT2 inhibitors in Asian patients with T2DM can help delay the decline of eGFR and reduce Scr and UA. Although SGLT2 inhibitors have no overall advantage in reducing albuminuria, dapagliflozin does appear to reduce albuminuria, and while they may increase the occurrence of AEs related to renal function, they do not increase the incidence of renal impairment. [ABSTRACT FROM AUTHOR]

Recognition and expression of emotion are key factors to the success of multi-turn conversations. Emotion recognition that can help model the relationship between query and response is used to be employed in single-turn conversation models. However, little work focuses on infusing the emotional factor in multi-turn conversation generation so far. To alleviate these problems, we propose Multi-turn Emotional Conversation Model (MECM) by using multi-task learning, which improves the ability to represent emotions in multi-turn conversations. MECM is based on hierarchical latent variable model, that utilizes context hidden to sharing the common information. Besides it also contains an emotion classifier to help the model recognize the emotion in the conversation, and a conversation generator to maintain consistency of content and transformation of emotion. Experimental results show that our model significantly improves the quality of responses in terms of diversity and empathy, and keeps better performance on semantic similarity compared with baseline methods. [ABSTRACT FROM AUTHOR]

Valleytronic properties of monolayer transition metal dichalcogenides have attracted extensive attention owing to its intriguing fundamental physics and potential application for future electronics. Here, we investigate the spin-valley coupling and valley polarization of monolayer chromium dichalcogenides induced by the magnetic proximity effect using first-principle calculations. It is found that monolayer CrX2 (X = S, Se, and Te) have inherent spin-valley coupling and a sizable Zeeman-type spin splitting near the maximum of valance band. The valley-contrasting characteristics are further clarified by the Berry curvature, which induces a novel spin/valley Hall effect. Finally, CrSe2/MnO2 heterostructure is proposed to introduce valley polarization via a magnetic proximity effect. A primitive valley splitting of 31 meV is induced at the maximum of valance band, corresponding to a Zeeman field of 185 T. More interestingly, the valley splitting could be effectively enhanced over a wide range by an electric field or out-of-plane strain. [ABSTRACT FROM AUTHOR]

Therapeutic blockade of the immune checkpoint proteins programmed cell death protein 1 (PD-1) and cytotoxic T lymphocyte antigen 4 (CTLA4) has transformed cancer treatment. However, the overall response rate to these treatments is low, suggesting that immune checkpoint activation is not the only mechanism leading to dysfunctional anti-tumour immunity. Here we show that butyrophilin-like protein 2 (BTNL2) is a potent suppressor of the anti-tumour immune response. Antibody-mediated blockade of BTNL2 attenuates tumour progression in multiple in vivo murine tumour models, resulting in prolonged survival of tumour-bearing mice. Mechanistically, BTNL2 interacts with local γδ T cell populations to promote IL-17A production in the tumour microenvironment. Inhibition of BTNL2 reduces the number of tumour-infiltrating IL-17A-producing γδ T cells and myeloid-derived suppressor cells, while facilitating cytotoxic CD8+ T cell accumulation. Furthermore, we find high BTNL2 expression in several human tumour samples from highly prevalent cancer types, which negatively correlates with overall patient survival. Thus, our results suggest that BTNL2 is a negative regulator of anti-tumour immunity and a potential target for cancer immunotherapy. Cancer cells producing ligands for the immune checkpoint molecules PD-1 and CTLA-4 is an important mechanism of tumour immune resistance. Here authors show that BTNL2 expression on cancer cells generates a dysfunctional tumour immune microenvironment via promoting IL-17A-producing γδ T cells. [ABSTRACT FROM AUTHOR]

Strain XQZ8T, isolated from the rhizosphere soil of a Populus popularis plant in China, was characterized using a polyphasic taxonomic approach. Cells were Gram-negative, aerobic, non-spore-forming, and rod-shaped. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain XQZ8T was related to members of the genus Rhizobium and had the highest 16S rRNA gene sequence similarity to Rhizobium smilacinae PTYR-5T (96.6%). The average nucleotide identity and digital DNA–DNA hybridization value between strain XQZ8T and R. smilacinae PTYR-5T were 77.5% and 21.4%, respectively. TYGS whole-genome-based taxonomic and multi-locus sequence analyses of three concatenated housekeeping genes (atpD–recA–glnII) further indicated that strain XQZ8T was a new member of the genus Rhizobium. The major cellular fatty acids included summed feature 8 (C18:1ω7c/C18:1ω6c), summed feature 2 (C12:0 aldehyde/unknown 10.928), C16:0, and C19:0 cyclo ω8c. The major respiratory quinones were Q-9 and Q-10. The polar lipids were phosphatidylglycerol, phosphatidylcholine, phosphatidylethanolamine, phosphatidyldimethylethanolamine, phosphatidylmonomethylethanolamine, an unidentified glycophospholipid, and three unidentified lipids. The genomic DNA G + C content of the strain was 60.1 mol%. Based on the phylogenetic, phenotypic, and genotypic characteristics, strain XQZ8T represents a novel species of the genus Rhizobium, for which the name Rhizobium populisoli sp. nov. is proposed. The type strain is XQZ8T (= JCM 34442T = GDMCC 1.2201T). [ABSTRACT FROM AUTHOR]

Finger vein recognition is very important in the identity authentication, but its performance is affected significantly by noise. The widely used Conditional Generative Adversarial Nets (CGAN) de-noising algorithm without accurate texture constraints is easy to damage the texture features of the image. In this paper, we propose a finger vein de-noising algorithm based on Custom Sample-Texture Conditional Generative Adversarial Nets (CS-TCGAN). The proposed algorithm effectively protects the texture features while removing noise. Firstly, the proposed algorithm uses texture loss, adversarial loss, and content loss as constraints, which lead to a better de-noising performance on finger vein image with blurred texture.Secondly, in order to avoid the checkerboard artifacts effect caused by up-sampling in de-convolution process which results in the loss of the vein information, the dimension preserving structure is adopted in the generator network to minimize this problem. Lastly, the noise distribution of finger vein images obtained in the practical application has been investigated to generate the training dataset for obtaining a de-noising model with better generalization. Specifically, the training dataset has been established by combining Poisson noise, salt/pepper noise, Gaussian noise, and speckle noise. The experimental results illustrate that the performance of the proposed algorithm is better than the traditional filtering de-noising approaches and the widely used CGAN de-noising algorithms. [ABSTRACT FROM AUTHOR]

Detailed analysis the disparity and reduction potential of clinker emission factors at the provincial level is important for regional reduction policies. Using the surveyed data from 185 new suspension and pre-heater (NSP) process lines and 69 shaft kiln lines, this study firstly analyzed the disparity in emission factors based on production process, production scale, and regional distribution in 2015. We found that the emission factor of the shaft kiln process (898.24 kg/t) is higher than that of the NSP process (858.59 kg/t), and that small-scale production lines have higher emission factors than large-scale lines both for the two process. China's clinker emission factors increase from the eastern to the western regions. Then, we estimated the reduction potential of structural adjustment, raw material substitution, and energy saving and fuel substitution in regional emission factors by 2030. The result shows that emission factors of the surveyed provinces will decrease by 101.41–174.60 kg/t compared to the values in 2015, which mainly contributes by energy saving and fuel substitution (65.98%), and raw material substitution (25.72%). And structural adjustment contributes only a small part reduction for most investigated provinces. The national average emission factor is estimated to be 715.33 kg/t in 2030, which indicates a reduction of 16.65%. These results can provide valuable feedback to government officials on the effectiveness of existing measures and also serve as a reference for future decisions on emission reduction polices. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 outbreak has been declared by World Health Organization as a worldwide pandemic. However, there are many unknowns about the antigen-specific T-cell-mediated immune responses to SARS-CoV-2 infection. Here, we present both single-cell TCR-seq and RNA-seq to analyze the dynamics of TCR repertoire and immune metabolic functions of blood T cells collected from recently discharged COVID-19 patients. We found that while the diversity of TCR repertoire was increased in discharged patients, it returned to basal level ~1 week after becoming virus-free. The dynamics of T cell repertoire correlated with a profound shift of gene signatures from antiviral response to metabolism adaptation. We also demonstrated that the top expanded T cell clones (~10% of total T cells) display the key anti-viral features in CD8+ T cells, confirming a critical role of antigen-specific T cells in fighting against SARS-CoV-2. Our work provides a basis for further analysis of adaptive immunity in COVID-19 patients, and also has implications in developing a T-cell-based vaccine for SARS-CoV-2. [ABSTRACT FROM AUTHOR]