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Abstract Background Clear cell renal cell carcinoma (ccRCC) arises from the renal parenchymal epithelium and is the predominant malignant entity of renal cancer, exhibiting increasing incidence and mortality rates over time. SEC14-like 3 (SEC14L3) has emerged as a compelling target for cancer intervention; nevertheless, the precise clinical implications and molecular underpinnings of SEC14L3 in ccRCC remain elusive. Methods By leveraging clinical data and data from the TCGA-ccRCC and GEO datasets, we investigated the association between SEC14L3 expression levels and overall survival rates in ccRCC patients. The biological role and mechanism of SEC14L3 in ccRCC were investigated via in vivo and in vitro experiments. Moreover, siRNA-SEC14L3@PDA@MUC12 nanoparticles (SSPM-NPs) were synthesized and assessed for their therapeutic potential against SEC14L3 through in vivo and in vitro assays. Results Our investigation revealed upregulated SEC14L3 expression in ccRCC tissues, and exogenous downregulation of SEC14L3 robustly suppressed the malignant traits of ccRCC cells. Mechanistically, knocking down SEC14L3 facilitated the ubiquitination-mediated degradation of ribosomal protein S3 (RPS3) and augmented IκBα accumulation in ccRCC. This concerted action thwarted the nuclear translocation of P65, thereby abrogating the activation of the nuclear factor kappa B (NFκB) signaling pathway and impeding ccRCC cell proliferation and metastasis. Furthermore, diminished SEC14L3 levels exerted a suppressive effect on NFKB1 expression within the NFκB signaling cascade. NFKB1 functions as a transcriptional regulator capable of binding to the SEC14L3 enhancer and promoter, thereby promoting SEC14L3 expression. Consequently, the inhibition of SEC14L3 expression was further potentiated, thus forming a positive feedback loop. Additionally, we observed that downregulation of SEC14L3 significantly increased the sensitivity of ccRCC cells to sunitinib. The evaluation of SSPM-NPs nanotherapy highlighted its effectiveness in combination with sunitinib for inhibiting ccRCC growth. Conclusion Our findings not only underscore the promise of SEC14L3 as a therapeutic target but also unveil an SEC14L3/RPS3/NFκB positive feedback loop that curtails ccRCC progression. Modulating SEC14L3 expression to engage this positive feedback loop might herald novel avenues for ccRCC treatment.

Abstract Objective Our aim was to comprehensively investigate the relationship between blood volatile organic compounds (VOCs) and kidney stone prevalence for U.S. adults. Methods In this cross-sectional study, 10,052 participants from the 2007–2020 National Health and Nutrition Examination Survey (NHANES) were included. Multivariate logistic regression model was employed to investigate the association between 9 blood VOCs and kidney stones. We explored the dose–response relationship between blood VOCs and kidney stones using restricted cubic spline (RCS) analysis. Additionally, weighted quantile sum (WQS) regression model was performed to assess the overall association of 9 blood VOCs with kidney stones. Finally, subgroup analyses were conducted to identify the findings in different populations at high prevalence. Results Logistic regression analysis and dose–response risk curves revealed that blood benzene (aOR = 1.308, 95% CI: 1.118–1.530, P = 0.001), blood ethylbenzene (aOR = 1.280, 95% CI: 1.054–1.554, P = 0.013), blood m-/p-xylene (aOR = 1.187, 95% CI: 1.008–1.398, P = 0.040), blood 2,5-dimethylfuran (aOR = 1.319, 95% CI: 1.135–1.533, P

Abstract Early screening methods for the thyroid gland include palpation and imaging. Although palpation is relatively simple, its effectiveness in detecting early clinical signs of the thyroid gland may be limited, especially in children, due to the shorter thyroid growth time. Therefore, this constitutes a crucial foundational work. However, accurately determining the location and size of the thyroid gland in children is a challenging task. Accuracy depends on the experience of the ultrasound operator in current clinical practice, leading to subjective results. Even among experts, there is poor agreement on thyroid identification. In addition, the effective use of ultrasound machines also relies on the experience of the ultrasound operator in current clinical practice. In order to extract sufficient texture information from pediatric thyroid ultrasound images while reducing the computational complexity and number of parameters, this paper designs a novel U-Net-based network called DC-Contrast U-Net, which aims to achieve better segmentation performance with lower complexity in medical image segmentation. The results show that compared with other U-Net-related segmentation models, the proposed DC-Contrast U-Net model achieves higher segmentation accuracy while improving the inference speed, making it a promising candidate for deployment in medical edge devices in clinical applications in the future.

Abstract Multiferroic materials have been intensively pursued to achieve the mutual control of electric and magnetic properties. The breakthrough progress in 2D magnets and ferroelectrics encourages the exploration of low-dimensional multiferroics, which holds the promise of understanding inscrutable magnetoelectric coupling and inventing advanced spintronic devices. However, confirming ferroelectricity with optical techniques is challenging in 2D materials, particularly in conjunction with antiferromagnetic orders in single- and few-layer multiferroics. Here, we report the discovery of 2D vdW multiferroic with out-of-plane ferroelectric polarization in trilayer NiI2 device, as revealed by scanning reflective magnetic circular dichroism microscopy and ferroelectric hysteresis loops. The evolution between ferroelectric and antiferroelectric phases has been unambiguously observed. Moreover, the magnetoelectric interaction is directly probed by magnetic control of the multiferroic domain switching. This work opens up opportunities for exploring multiferroic orders and multiferroic physics at the limit of single or few atomic layers, and for creating advanced magnetoelectronic devices.

Abstract The central nervous system has been implicated in the age-induced reduction in adipose tissue lipolysis. However, the underlying mechanisms remain unclear. Here, we show the expression of SLC7A14 is reduced in proopiomelanocortin (POMC) neurons of aged mice. Overexpression of SLC7A14 in POMC neurons alleviates the aging-reduced lipolysis, whereas SLC7A14 deletion mimics the age-induced lipolysis impairment. Metabolomics analysis reveals that POMC SLC7A14 increased taurochenodeoxycholic acid (TCDCA) content, which mediates the SLC7A14 knockout- or age-induced WAT lipolysis impairment. Furthermore, SLC7A14-increased TCDCA content is dependent on intestinal apical sodium-dependent bile acid transporter (ASBT), which is regulated by intestinal sympathetic afferent nerves. Finally, SLC7A14 regulates the intestinal sympathetic afferent nerves by inhibiting mTORC1 signaling through inhibiting TSC1 phosphorylation. Collectively, our study suggests the function for central SLC7A14 and an upstream mechanism for the mTORC1 signaling pathway. Moreover, our data provides insights into the brain–gut–adipose tissue crosstalk in age-induced lipolysis impairment.

Abstract High-quality standard views in two-dimensional echocardiography are essential for accurate cardiovascular disease diagnosis and treatment decisions. However, the quality of echocardiographic images is highly dependent on the practitioner’s experience. Ensuring timely quality control of echocardiographic images in the clinical setting remains a significant challenge. In this study, we aimed to propose new quality assessment criteria and develop a multi-task deep learning model for real-time multi-view classification and image quality assessment (six standard views and “others”). A total of 170,311 echocardiographic images collected between 2015 and 2022 were utilized to develop and evaluate the model. On the test set, the model achieved an overall classification accuracy of 97.8% (95%CI 97.7–98.0) and a mean absolute error of 6.54 (95%CI 6.43–6.66). A single-frame inference time of 2.8 ms was achieved, meeting real-time requirements. We also analyzed pre-stored images from three distinct groups of echocardiographers (junior, senior, and expert) to evaluate the clinical feasibility of the model. Our multi-task model can provide objective, reproducible, and clinically significant view quality assessment results for echocardiographic images, potentially optimizing the clinical image acquisition process and improving AI-assisted diagnosis accuracy.

Addressing peripheral nerve defects remains a significant challenge in regenerative neurobiology. Autografts emerged as the gold-standard management, however, are hindered by limited availability and potential neuroma formation. Numerous recent studies report the potential of wireless electronic system for nerve defects repair. Unfortunately, few has met clinical needs for inadequate electrode precision, poor nerve entrapment and insufficient bioactivity of the matrix material. Herein, we present an advanced wireless electrical nerve stimulator, based on water-responsive self-curling silk membrane with excellent bioabsorbable and biocompatible properties. We constructed a unique bilayer structure with an oriented pre-stretched inner layer and a general silk membrane as outer layer. After wetting, the simultaneous contraction of inner layer and expansion of outer layer achieved controllable super-contraction from 2D flat surface to 3D structural reconfiguration. It enables shape-adaptive wrapping to cover around nerves, overcomes the technical obstacle of preparing electrodes on the inner wall of the conduit, and prevents electrode breakage caused by material expansion in water. The use of fork capacitor-like metal interface increases the contact points between the metal and the regenerating nerve, solving the challenge of inefficient and rough electrical stimulation methods in the past. Newly developed electronic stimulator is effective in restoring 10 mm rat sciatic nerve defects comparable to autologous grafts. The underlying mechanism involves that electric stimulation enhances anterograde mitochondrial transport to match energy demands. This newly introduced device thereby demonstrated the potential as a viable and efficacious alternative to autografts for enhancing peripheral nerve repair and functional recovery.

Abstract Among the many adverse geological disasters, the surge water disaster in karst areas causes the greatest loss to underground engineering construction, so it is necessary to carry out relevant research on the management of surge water disaster in karst pipelines. This study presents the creation of an oily epoxy resin magnetic convergence grouting material (OEMS) specifically developed to prevent water infiltration in pipelines. A self-designed visual karst pipeline grouting simulation system was used to conduct an experimental study on the diffusion and plugging behavior of magnetic slurry grouting. A model was constructed to simulate the migration of a magnetic slurry in water inrush circumstances. The model is based on the theory of slurry diffusion and the concept of magnetic adsorption. The results suggest that:(i) The best performance in grouting sealing is achieved when the ratio of new OEMS epoxy resin A liquid to B liquid is 2:1, and the blending ratio of flyash and Fe3O4 powder falls between 25 and 55%. (ii) The primary and secondary correlations among the parameters that affect the rate of change in flow rate, plugging pressure, and slurry retention rate are as follows: Hydrodynamic velocity has the greatest correlation, followed by plugging length, Fe3O4 power ratio, and flyash mixture ratio. (iii) The validity of the model is verified by comparing empirical observations with calculated theoretical values.

Abstract This paper seeks to draw a research agenda for unveiling the underlying bottlenecks and possibilities for improving the agricultural total factor productivity in the European Union (EU). To this aim, the paper first surveys the key challenges for the modern agricultural economy. Then, the case of the EU is discussed by looking at the convergence in the partial productivity indicators (including the GHG emission) and growth efficiency that relate to the gap in the total factor productivity growth. The results suggest that the EU member states exhibited growth inefficiency (i.e., a gap in the total factor productivity growth) of 5–9% on average during 2004–2021. The paper also discusses the possibilities to utilize the production theory for assessing the pathways towards improvements in the productivity and sustainability of the EU agriculture.

Abstract Pulsed electromagnetic field (PEMF) therapy has been extensively investigated in clinical studies for the treatment of angiogenesis-related diseases. However, there is a lack of research on the impact of PEMFs on energy metabolism and mitochondrial dynamics during angiogenesis. The present study included tube formation and CCK-8 assays. A Seahorse assay was conducted to analyze energy metabolism, and mitochondrial membrane potential assays, mitochondrial imaging, and reactive oxygen species assays were used to measure changes in mitochondrial structure and function in human umbilical vein endothelial cells (HUVECs) exposed to PEMFs. Real-time polymerase chain reaction was used to analyze the mRNA expression levels of antioxidants, glycolytic pathway-related genes, and genes associated with mitochondrial fission and fusion. The tube formation assay demonstrated a significantly greater tube network in the PEMF group compared to the control group. The glycolysis and mitochondrial stress tests revealed that PEMFs promoted a shift in the energy metabolism pattern of HUVECs from oxidative phosphorylation to aerobic glycolysis. Mitochondrial imaging revealed a wire-like mitochondrial morphology in the control group, and treatment with PEMFs led to shorter and more granular mitochondria. Our major findings indicate that exposure to PEMFs accelerates angiogenesis in HUVECs, likely by inducing energy metabolism reprogramming and mitochondrial fission.

Introduction: MDM2 is known as the primary negative regulator of p53, and MDM2 promotes lung cancer fibrosis and lung injury through p53-dependent and p53-independent pathways. However, the mechanism by which MDM2 influences the pathogenesis of asthma is unknown. In this study, we investigated the function of MDM2 in lung epithelial cells in type 2 lung inflammation. Methods: We used type II alveolar epithelial cell-specific heterozygous knockout of Mdm2 mice to validate its function. Then papain-induced asthma model was established, and changes in inflammation were observed by measuring immunohistochemistry and flow cytometry analysis. Results: In this study, we knockdown the mouse Mdm2 gene in type 2 alveolar epithelial cells. We demonstrated that heterozygous Mdm2 gene-deleted mice were highly susceptible to protease allergen papain-induced pulmonary inflammation characterized by increased ILC2 numbers, IL-5 and IL-13 cytokine levels, and lung pathology. A mechanistic study showed that following the decreased expression of Mdm2 in lung epithelial cells and A549 cell line, p53 was overactivated, and the expression of its downstream genes p21, Puma, and Noxa was elevated, which resulted in apoptosis. After Mdm2 knockdown, the mRNA expression of inflammation-related gene IL-25, HMGB1, and TNF-α were increased, which further amplified the downstream ILC2 response and lung inflammation. Conclusion: These results indicate that Mdm2 maintains the homeostasis of lung epithelial cells by targeting P53 and regulates the function of lung epithelial cells under type 2 lung inflammation.

Building use identification is crucial in urban planning and management. Current identification methods often rely on a single data source and neglect spatial proximity. In this paper, we propose a stepwise urban building use identification framework that integrates remote sensing and social sensing data with spatial constraints based on the association of buildings with Point of Interest (POI), Area of Interest (AOI) and remote sensing data. First, the study data are preprocessed using geometric correction and POI and AOI reclassification. Then, we identify buildings with the quantitative-density index of the POIs as well as the spatial relationships between the AOIs and the buildings. Next, we generate Traffic Analysis Zones (TAZs) from road network data and utilize the similarity in physical features of buildings from remote sensing data to identify building use within spatial constraints. Finally, POI kernel density estimation is used to determine the semantic features of the buildings, and the similarity of the features between the buildings is utilized to identify the remaining buildings. The specificity of our proposed framework lies not only in the combination of multiple source data at the building-level but also in the introduction of the spatial relationships of AOIs and spatial constraints. Shenyang is selected as an example. The proposed framework identifies buildings as commercial, residential, industrial, public service and scenic spots. The accuracy assessment indicates that the proposed framework performs well, with an Overall Accuracy (OA) of 87.1% and a kappa coefficient (kappa) of 73.4%. The results of the comparison experiments show that the consideration of spatial constraints and the integration of multiple data sources help to improve the accuracy of building use identification. The proposed framework provides a new tool for better identification of urban building use, and the generated data are suitable for in-depth analyses such as building-level urban heat islands.

Abstract Silicon nitride (Si3N4) is a bioceramic material with potential applications. Customization and high reliability are the foundation for the widespread application of Si3N4 bioceramics. This study constructed a new microwave heating structure and successfully prepared 3D printed dense Si3N4 materials, overcoming the adverse effects of a large amount of 3D printed organic forming agents on degreasing and sintering processes, further improving the comprehensive performance of Si3N4 materials. Compared with control materials, the 3D printed Si3N4 materials by microwave sintering have the best mechanical performance: bending strength is 928 MPa, fracture toughness is 9.61 MPa·m1/2. Meanwhile, it has the best biocompatibility and antibacterial properties, and cells exhibit the best activity on the material surface. Research has shown that the excellent mechanical performance and biological activity of materials are mainly related to the high-quality degreasing, high cleanliness sintering environment, and high-quality liquid-phase sintering of materials in microwave environments.

Under the conditions of deep high stress, weak surrounding rock, and strong mining influence, the surrounding rock of deep-buried roadway frequently experiences large deformations, the controllability of large deformation support for this type of surrounding rock is generally poor, and the conventional anchor bolts often break or fail to anchor due to their low elongation rate, which cannot adapt to the large deformation of the roadway, resulting in the risk of roof caving in the roadway. The constant resistance device by using composite expansion pipe (CRD-cep) used in conjunction with cable bolt has been invented. The main structures include a stop end cover, an expansion pipe, an integrated tray and a conical lock. The conical lock overcomes the approximately constant composite resistance generated by the “expansion grinding” of the expanding pipe, thus, the constant resistance of the cable bolt during the large deformation process of the surrounding rock is achieved. The mechanical characteristics and working stability of the resistance stabilizer are improved by theoretical analysis, numerical simulation and static tensile testing and other comprehensive research methods, and the influence of the expansion increment and lock cone angle of the composite expansion tube constant resistance device on the deformation of the expansion pipe and the composite resistance of the CRD-cep has been understood. The test results indicate that the composite resistance of the CRD-cep is mainly divided into two processes: the fast rising resistance stage and the near constant resistance stage, and the nearly constant resistance section as the main stage reaches 85% to 90% of the entire test process. The lock cone angle and expansion increment directly affect the deformation of the expansion pipe and the mechanical characteristics of the CRD-cep. When the lock cone angle is less than 20°, the deformation of the expanding pipe is uniform and the composite resistance of the CRD-cep is stable. The expanding increment determines the size of the CRD-cep. The required constant resistance of the cable bolt can be obtained by adjusting the expanding increment. When the diameter of the anchor rope used is 17.8 mm, the lock cone angle is 15° and the expansion increment is 5 mm, the constant resistance of the CRD-cep is about 265.92 kN, when the diameter of the anchor rope used is 21.8 mm, the lock cone angle is 15° and the expansion increment is 8 mm, the constant resistance of the CRD-cep is about 424.15 kN, and the working state is stable and reliable, which can better meet the constant resistance support requirements of large deformation roadway. The CRD-cep has the characteristics of strong working stability, adjustable constant resistance stroke and resistance, simple structure, and convenient installation, which is an effective supplement to the control technology of surrounding rock in large deformation roadway.

Since the outbreak of the coronavirus disease 2019 (COVID-19) epidemic in 2019, the public health system has faced enormous challenges. Tracking the individuals who test positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a key step for interrupting chains of transmission of SARS-CoV-2 and reducing COVID-19-associated mortality. With the increasing of asymptomatic infections, it is difficult to track asymptomatic infections through epidemiological surveys and virus whole-genome sequencing. However, due to the cross-reactivity of neutralizing antibodies produced by multiple virus subtypes, neutralizing antibody detection cannot be used to determine whether an individual has a history of infection with a specific subtype of SARS-CoV-2. We recruited 4 human leukocyte antigen A2 (HLA-A2) infections, 15 individuals who received three doses of inactivated vaccines, and 30 breakthrough infections after vaccination and discussed a case-tracking approach to detect epitope-specific CD8+ T cells in the peripheral blood of close contacts, including accurate HLA typing based on ribonucleic acid (RNA)-sequencing and flow cytometry data and the comparison and characterization of SARS-CoV-2 HLA-A2 and HLA-A24 epitope-specific CD8+ T cells. From individuals who received three doses of inactivated vaccine, we observed that the CD8+ T cell specificity for ancestral epitopes was significantly higher than for mutated epitopes, and the fold change of CD8+ T cells corresponding to mutated epitopes relative to ancestral epitopes was less than 1. The enzyme-linked immunospot (ELISpot) results further validate this result. This study forms a “method for understanding the infection history of SARS-CoV-2 subtypes based on the proportion of epitope-specific CD8+ T cells in the peripheral blood of subjects”, covering up to 46 % of the population, including HLA-A2+ and HLA-A24+ donors, providing a novel method for SARS-CoV-2 infected case tracing.

Abstract Prediction of glioma is crucial to provide a precise treatment plan to optimize the prognosis of children with glioma. However, studies on the grading of pediatric gliomas using radiomics are limited. Meanwhile, existing methods are mainly based on only radiomics features, ignoring intuitive information about tumor morphology on traditional imaging features. This study aims to utilize multiparametric magnetic resonance imaging (MRI) to identify high-grade and low-grade gliomas in children and establish a classification model based on radiomics features and clinical features. A total of 85 children with gliomas underwent tumor resection, and part of the tumor tissue was examined pathologically. Patients were categorized into high-grade and low-grade groups according to World Health Organization guidelines. Preoperative multiparametric MRI data, including contrast-enhanced T1-weighted imaging, T2-weighted imaging, T2-weighted fluid-attenuated inversion recovery, diffusion-weighted images, and apparent diffusion coefficient sequences, were obtained and labeled by two radiologists. The images were preprocessed, and radiomics features were extracted for each MRI sequence. Feature selection methods were used to select radiomics features, and statistically significant clinical features were identified using t-tests. The selected radiomics features and conventional MRI features were used to train the AutoGluon models. The improved model, based on radiomics features and conventional MRI features, achieved a balanced classification accuracy of 66.59%. The cross-validated areas under the receiver operating characteristic curve for the classifier of AutoGluon frame were 0.8071 on the test dataset. The results indicate that the performance of AutoGluon models can be improved by incorporating conventional MRI features, highlighting the importance of the experience of radiologists in accurately grading pediatric gliomas. This method can help predict the grade of pediatric glioma before pathological examination and assist in determining the appropriate treatment plan, including radiotherapy, chemotherapy, drugs, and gene surgery.

Objective Bone marrow mesenchymal stem cells (BMSCs) show significant potential for osteogenic differentiation. However, the underlying mechanisms of osteogenic capability in osteoporosis‐derived BMSCs (OP‐BMSCs) remain unclear. This study aims to explore the impact of YTHDF3 (YTH N6‐methyladenosine RNA binding protein 3) on the osteogenic traits of OP‐BMSCs and identify potential therapeutic targets to boost their bone formation ability. Methods We examined microarray datasets (GSE35956 and GSE35958) from the Gene Expression Omnibus (GEO) to identify potential m6A regulators in osteoporosis (OP). Employing differential, protein interaction, and machine learning analyses, we pinpointed critical hub genes linked to OP. We further probed the relationship between these genes and OP using single‐cell analysis, immune infiltration assessment, and Mendelian randomization. Our in vivo and in vitro experiments validated the expression and functionality of the key hub gene. Results Differential analysis revealed seven key hub genes related to OP, with YTHDF3 as a central player, supported by protein interaction analysis and machine learning methodologies. Subsequent single‐cell, immune infiltration, and Mendelian randomization studies consistently validated YTHDF3's significant link to osteoporosis. YTHDF3 levels are significantly reduced in femoral head tissue from postmenopausal osteoporosis (PMOP) patients and femoral bone tissue from PMOP mice. Additionally, silencing YTHDF3 in OP‐BMSCs substantially impedes their proliferation and differentiation. Conclusion YTHDF3 may be implicated in the pathogenesis of OP by regulating the proliferation and osteogenic differentiation of OP‐BMSCs.

Abstract The long non-coding RNA X-inactive specific transcript (lncRNA XIST) and MUC1 gene are dysregulated in chronic inflammation and cancer; however, there is no known interaction of their functions. The present studies demonstrate that MUC1-C regulates XIST lncRNA levels by suppressing the RBM15/B, WTAP and METTL3/14 components of the m6A methylation complex that associate with XIST A repeats. MUC1-C also suppresses the YTHDF2-CNOT1 deadenylase complex that recognizes m6A sites and contributes to XIST decay with increases in XIST stability and expression. In support of an auto-regulatory pathway, we show that XIST regulates MUC1-C expression by promoting NF-κB-mediated activation of the MUC1 gene. Of significance, MUC1-C and XIST regulate common genes associated with inflammation and stemness, including (i) miR-21 which is upregulated across pan-cancers, and (ii) TDP-43 which associates with the XIST E repeats. Our results further demonstrate that the MUC1-C/XIST pathway (i) is regulated by TDP-43, (ii) drives stemness-associated genes, and (iii) is necessary for self-renewal capacity. These findings indicate that the MUC1-C/XIST auto-regulatory axis is of importance in cancer progression.

To accurately predict the dynamic characteristics of MR mounting, the nonlinear electromagnetic coupling law between MR liquid and soft magnetic material and the solid-liquid interaction, the electromagnetic coupling and fluid-structure coupling mathematical models and numerical simulation models of MR mounting are established. Through the magnetorheological mounting test, the simulation results are compared with the experimental results, and the validity of the numerical simulation model is verified. On this basis, the distribution effect of electromagnetic coupling in a magnetic circuit is analyzed. According to the Bingham model, the variation rule of magnetorheological fluid damping force was deduced. The magnetic field simulation results are introduced into the fluid model and the fluid-solid model, and the fluid-solid coupling effect of the numerical model of magnetorheological mounting is calculated. The dynamic and static characteristics of magnetorheological mounting under different current excitation conditions are simulated. It provides the basis for designing and simulating multi-physical field simulation of MR mounting.

BackgroundWhether lymph node metastasis in non-small cell lung cancer is critical to clinical decision-making. This study was to develop a non-invasive predictive model for preoperative assessing lymph node metastasis in patients with non-small cell lung cancer (NSCLC) using radiomic features from chest CT images.Materials & methodsIn this retrospective study, 247 patients with resectable non-small cell lung cancer (NSCLC) were enrolled. These individuals underwent preoperative chest CT scans that identified lung nodules, followed by lobectomies and either lymph node sampling or dissection. We extracted both intratumoral and peritumoral radiomic features from the CT images, which were used as covariates to predict the lymph node metastasis status. By using ROC curves, Delong tests, Calibration curve, and DCA curves, intra-tumoral-peri-tumoral model performance were compared with models using only intratumoral features or clinical information. Finally, we constructed a model that combined clinical information and radiomic features to increase clinical applicability.ResultsThis study enrolled 247 patients (117 male and 130 females). In terms of predicting lymph node metastasis, the intra-tumoral-peri-tumoral model (0.953, 95%CI 0.9272-0.9792) has a higher AUC compared to the intratumoral radiomics model (0.898, 95%CI 0.8553-0.9402) and the clinical model (0.818, 95%CI 0.7653-0.8709). The DeLong test shows that the performance of the Intratumoral and Peritumoral radiomics models is superior to that of the Intratumoral or clinical feature model (p

The glycolytic enzyme cytoplasmic glyceraldehyde-3-phosphate dehydrogenase (GAPC3) is involved in multiple biological processes in plants, including transcriptional regulation, and material metabolism. However, the relationship between OsGAPC3 and the quality traits of rice is poorly understood. Here we identify OsGAPC3 mutations that enhance the protein content and grain nutritional quality of rice by regulating the OsAAP6 gene expression. The number and volume of type-II protein bodies in the endosperm of the OsGAPC3 mutants, and GPC increase significantly. We report significant increases in chalkiness area and degree, and decreases for starch content, gel consistency, and taste value. Results of proteomic detection and analysis reveal that OsGAPC3 affects the major storage substances (proteins and starch) metabolism in rice, and the accumulation of proteins and starch in the endosperm. Additionally, the OsGAPC3 mutation significantly decreases the rice-seedling salt tolerance. Therefore, OsGAPC3 affects multiple quality traits of rice, participates in regulating rice-seedling salt-stress response. These data can be used to design better-quality and stronger salt-resistant rice varieties.

INTRODUCTION: As the penetration rate of renewable energy increases and patterns of energy demand evolve, fluctuations on both the supply and demand sides of electricity are becoming more pronounced. Consequently, accurate forecasting of community residential electrical loads has become crucial. OBJECTIVES: Although the widespread adoption of smart meters among residents provides abundant data for model training, strict challenges arise during the training process due to the need for privacy protection and data security. METHODS: This paper proposes a privacy-preserving community residential short-term electric load forecasting method based on federated learning. Initially, the method applies shared random masking encryption to the sensitive data of community residents, ensuring data privacy while maintaining consistency with the original data after preprocessing. Subsequently, a private data aggregation scheme is established to perform dynamic clustering of the community’s electrical load. RESULTS: The clustered model then serves as the basis for establishing individual load forecasting models for each category of community residents to predict short-term electrical loads. Finally, an empirical analysis is performed using the electrical load data from 120 households across 6 communities in a city in Southern China. CONCLUSION: The analysis demonstrates that the proposed method can achieve the prediction of community residential electrical loads without sharing residents’ data, thus verifying the effectiveness of this approach.

This study explores the role of disulfidptosis in monocytes and its relation to postmenopausal osteoporosis (PMOP). Using single-cell RNA sequencing and microarray assays, we identified key genes: LONRF1, ACAP2, IPO9, and PGRMC2. Through differential analysis, Weighted Gene Co-expression Network Analysis (WGCNA), and machine learning, these genes were linked to PMOP. Functional enrichment and ROC curve analysis demonstrated their effectiveness in distinguishing postmenopausal fracture patients from healthy individuals. Notably, PGRMC2 exhibited significant expression differences, highlighted by a notable Area Under the Curve (AUC) value of 0.665. Further investigation involved Western blotting and immunohistochemical assays, revealing decreased PGRMC2 expression in ovariectomized (OVX) mice. This decrease was consistent across both experimental methods, emphasizing PGRMC2's role in PMOP. Moreover, PGRMC2 was predominantly present in macrophages compared to monocytes within bone tissue and was significantly located in bone marrow mesenchymal stem cells (BM-MSCs) in PMOP patients. It was also abundantly found in osteoblasts and adipocytes. Additionally, a Mendelian randomization analysis using the TwoSampleMR R package, with data from decode and GWAS databases, was conducted. This analysis showed a significant impact of PGRMC2 on osteoporosis risk (p = 0.0048, OR = 0.6836), suggesting a potential protective effect against the disease. Our results suggest that PGRMC2 may facilitate the differentiation of monocytes into macrophages in bone tissue, influencing the behavior of BM-MSCs. This, in turn, could impact the progression and severity of PMOP. The study provides new insights into the molecular mechanisms underlying postmenopausal osteoporosis and highlights the potential of PGRMC2 as a therapeutic target or biomarker for this condition.

Objectives: To assess the effects of timing of maternal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and vaccination status on placental transfer of antibodies to neonates. Methods: In this cross-sectional study, chemiluminescence was employed to measure SARS-CoV-2 IgG antibody titers in paired maternal-infant samples from women infected during pregnancy who were vaccinated or unvaccinated. Generalized linear regression assessed factors affecting antibody transfer in infected pregnant women and neonatal titers. Results: The group with ≥90 days between infection and delivery showed a higher antibody transfer rate than the

IntroductionMesenchymal stromal cells (MSCs) have been extensively studied as a potential treatment for steroid refractory acute graft-versus-host disease (aGVHD). However, the majority of clinical trials have focused on bone marrow-derived MSCs.MethodsIn this study, we report the outcomes of 86 patients with grade III-IV (82.6% grade IV) steroid refractory aGVHD who were treated with human umbilical cord-derived mesenchymal stromal cells (UC-MSCs). The patient cohort included 17 children and 69 adults. All patients received intravenous infusions of UC-MSCs at a dose of 1 × 106 cells per kg body weight, with a median of 4 infusions (ranging from 1 to 16).ResultsThe median time between the onset of aGVHD and the first infusion of UC-MSCs was 7 days (ranging from 3 to 88 days). At day 28, the overall response (OR) rate was 52.3%. Specifically, 24 patients (27.9%) achieved complete remission, while 21 (24.4%) exhibited partial remission. The estimated survival probability at 100 days was 43.7%. Following a median follow-up of 108 months (ranging from 61 to 159 months), the survival rate was approximately 11.6% (10/86). Patients who developed acute lower GI tract and liver GVHD exhibited poorer OR rates at day 28 compared to those with only acute lower GI tract GVHD (22.2% vs. 58.8%; p= 0.049). No patient experienced serious adverse events.DiscussionThese finding suggest that UC-MSCs are safe and effective in both children and adults with steroid refractory aGVHD. UC-MSCs could be considered as a feasible treatment option for this challenging conditon. (NCT01754454).

Abstract Compared with the traditional two‐step localization methods, the direct position determination (DPD) method is more robust at low signal‐to‐noise ratio. However, to guarantee the optimal location result, the computational complexity of DPD with grid search is too high, especially for moving targets. Therefore, a new DPD method is proposed for moving targets with low computational complexity. First, using a proposed cost function, the position information is obtained from the received array signals directly, which enhances the accuracy of localization. Second, utilizing the method of successional difference the velocity is extracted, which avoid the multi‐dimensional grid search and reduces the computational complexity. Simulation results demonstrate that the proposed method reduces the computational complexity greatly and outperforms the conventional methods.

Laser powder bed fusion (L-PBF) of Mg alloys has provided tremendous opportunities for customized production of aeronautical and medical parts. Layer thickness (LT) is of great significance to the L-PBF process but has not been studied for Mg alloys. In this study, WE43 Mg alloy bulk cubes, porous scaffolds, and thin walls with layer thicknesses of 10, 20, 30, and 40 µm were fabricated. The required laser energy input increased with increasing layer thickness and was different for the bulk cubes and porous scaffolds. Porosity tended to occur at the connection joints in porous scaffolds for LT40 and could be eliminated by reducing the laser energy input. For thin wall parts, a large overhang angle or a small wall thickness resulted in porosity when a large layer thicknesses was used, and the porosity disappeared by reducing the layer thickness or laser energy input. A deeper keyhole penetration was found in all occasions with porosity, explaining the influence of layer thickness, geometrical structure, and laser energy input on the porosity. All the samples achieved a high fusion quality with a relative density of over 99.5% using the optimized laser energy input. The increased layer thickness resulted to more precipitation phases, finer grain sizes and decreased grain texture. With the similar high fusion quality, the tensile strength and elongation of bulk samples were significantly improved from 257 MPa and 1.41% with the 10 µm layer to 287 MPa and 15.12% with the 40 µm layer, in accordance with the microstructural change. The effect of layer thickness on the compressive properties of porous scaffolds was limited. However, the corrosion rate of bulk samples accelerated with increasing the layer thickness, mainly attributed to the increased number of precipitation phases.

Abstract Aims Cardiovascular disease is the leading cause of death worldwide. Anxiety disorders are common psychiatric conditions associated with cardiovascular outcomes. This two‐sample Mendelian randomization (MR) study investigated the causal relationship between anxiety disorders and coronary heart disease (CHD), myocardial infarction (MI), heart failure (HF), and atrial fibrillation (AF). Methods Single nucleotide polymorphisms (SNPs) associated with anxiety disorders (16 730 cases; 101 021 controls) were obtained from the UK Biobank genome‐wide association study (GWAS). Cardiovascular outcome data were derived from the FinnGen study (CHD: 21 012 cases and 197 780 controls; MI: 12 801 cases and 187 840 controls; HF: 23 397 cases and 194 811 controls; and AF: 22 068 cases and 116 926 controls). Inverse variance weighted (IVW), MR–Egger, weighted median, simple mode, and weighted mode analyses examined causality. Results IVW analysis demonstrated significant causal relationships between anxiety disorders and increased risk of CHD [odds ratio (OR): 4.496; 95% confidence interval (CI): 1.777–11.378; P = 0.002], MI (OR: 5.042; 95% CI: 1.451–17.518; P = 0.011), and HF (OR: 3.255; 95% CI: 1.461–7.252; P = 0.004). No relationship was observed with AF (OR: 1.775; 95% CI: 0.612–5.146; P = 0.29). Other methods showed non‐significant associations. Two‐way analysis indicated no reverse causality. Conclusions Anxiety disorders were causally associated with greater risk of CHD, MI, and HF but not AF among individuals of European descent. Further research on mediating mechanisms and in diverse populations is warranted.

Laser powder bed fusion (L-PBF) has been employed to additively manufacture WE43 magnesium (Mg) alloy biodegradable implants, but WE43 L-PBF samples exhibit excessively rapid corrosion. In this work, dense WE43 L-PBF samples were built with the relativity density reaching 99.9%. High temperature oxidation was performed on the L-PBF samples in circulating air via various heating temperatures and holding durations. The oxidation and diffusion at the elevated temperature generated a gradient structure composed of an oxide layer at the surface, a transition layer in the middle and the matrix. The oxide layer consisted of rare earth (RE) oxides, and became dense and thick with increasing the holding duration. The matrix was composed of α-Mg, RE oxides and Mg24RE5 precipitates. The precipitates almost disappeared in the transition layer. Enhanced passivation effect was observed in the samples treated by a suitable high temperature oxidation. The original L-PBF samples lost 40% weight after 3-day immersion in Hank's solution, and broke into fragments after 7-day immersion. The casted and solution treated samples lost roughly half of the weight after 28-day immersion. The high temperature oxidation samples, which were heated at 525 °C for 8 h, kept the structural integrity, and lost only 6.88% weight after 28-day immersion. The substantially improved corrosion resistance was contributed to the gradient structure at the surface. On one hand, the outmost dense layer of RE oxides isolated the corrosive medium; on the other hand, the transition layer considerably inhibited the corrosion owing to the lack of precipitates. Overall, high temperature oxidation provides an efficient, economic and safe approach to inhibit the corrosion of WE43 L-PBF samples, and has promising prospects for future clinical applications.

Abstract Senile osteoporosis is mainly caused by osteoblasts attenuation, which results in reduced bone mass and disrupted bone remodeling. Numerous studies have focused on the regulatory role of m6A modification in osteoporosis; however, most of the studies have investigated the differentiation of bone marrow mesenchymal stem cells (BMSCs), while the direct regulatory mechanism of m6A on osteoblasts remains unknown. This study revealed that the progression of senile osteoporosis is closely related to the downregulation of m6A modification and methyltransferase-like 3 (METTL3). Overexpression of METTL3 inhibits osteoblast aging. Methylated RNA immunoprecipitation sequencing (MeRIP-seq) revealed that METTL3 upregulates the stability of Hspa1a mRNA, thereby inhibiting osteoblast aging. Moreover, the results demonstrated that METTL3 enhances the stability of Hspa1a mRNA via m6A modification to regulate osteoblast aging. Notably, YTH N6-methyladenosine RNA binding protein 2 (YTHDF2) participates in stabilizing Hspa1a mRNA in the METTL3-mediated m6A modification process, rather than the well-known degradation function. Mechanistically, METTL3 increases the stability of Hspa1a mRNA in a YTHDF2-dependent manner to inhibit osteoblast aging. Our results confirmed the significant role of METTL3 in osteoblast aging and suggested that METTL3 could be a potential therapeutic target for senile osteoporosis.

Microglia are resident immune cells in the central nervous system (CNS) that play vital roles in CNS development, homeostasis and disease pathogenesis. Genetic defects in microglia lead to microglial dysfunction, which in turn leads to neurological disorders. The correction of the specific genetic defects in microglia in these disorders can lead to therapeutic effects. Traditional genetic defect correction approaches are dependent on viral vector-based genetic defect corrections. However, the viruses used in these approaches, including adeno-associated viruses, lentiviruses and retroviruses, do not primarily target microglia; therefore, viral vector-based genetic defect corrections are ineffective in microglia. Microglia replacement is a novel approach to correct microglial genetic defects via replacing microglia of genetic defects with allogenic healthy microglia. In this paper, we systematically review the history, rationale and therapeutic perspectives of microglia replacement, which would be a novel strategy for treating CNS disorders.

Abstract Suicidal behavior and non-suicidal self-injury (NSSI) are common in adolescent patients with major depressive disorder (MDD). Thus, delineating the unique characteristics of suicide attempters having adolescent MDD with NSSI is important for suicide prediction in the clinical setting. Here, we performed psychological and biochemical assessments of 130 youths having MDD with NSSI. Participants were divided into two groups according to the presence/absence of suicide attempts (SAs). Our results demonstrated that the age of suicide attempters is lower than that of non-attempters in participants having adolescent MDD with NSSI; suicide attempters had higher Barratt Impulsiveness Scale (BIS-11) impulsivity scores and lower serum CRP and cortisol levels than those having MDD with NSSI alone, suggesting levels of cortisol and CRP were inversely correlated with SAs in patients with adolescent MDD with NSSI. Furthermore, multivariate regression analysis revealed that NSSI frequency in the last month and CRP levels were suicidal ideation predictors in adolescent MDD with NSSI, which may indicate that the increased frequency of NSSI behavior is a potential risk factor for suicide. Additionally, we explored the correlation between psychological and blood biochemical indicators to distinguish suicide attempters among participants having adolescent MDD with NSSI and identified a unique correlation network that could serve as a marker for suicide attempters. Our research data further suggested a complex correlation between the psychological and behavioral indicators of impulsivity and anger. Therefore, our study findings may provide clues to identify good clinical warning signs for SA in patients with adolescent MDD with NSSI.

ObjectiveTo analyze current situation and problems of maternal health care services provided by primary medical institutions in China for making relevant policy recommendations. MethodsDuring May – June 2022, we extracted the data of 2021 on the establishment and operation of obstetrics and gynecology departments submitted by 4 737 township health centers and 1 669 community health service centers in 6 provinces (Zhejiang and Jiangsu, Hubei and Henan, Sichuan and Guizhou representing eastern, central, and western socio-economic regions of China) from the 'Information System of Quality Medical Service at Grassroots Level Program' initiated by National Health Commission. Descriptive statistics and multiple linear regression analysis were conducted using stata16.0 software to examine the status and influencing factors of maternal health care services provided by the primary institutions. ResultsFor the township health centers and community health service centers, the proportions of institutions with gynecology departments were 72.79% (3 448/4 737) and 79.51% (1 327/1 669) and proportions of those with obstetrics departments were 29.07% (1 377/4 737) and 14.92% (249/1 669), respectively; the proportion of the community health service centers with practicing obstetricians and gynecologists was 82.92% (1 384/1 669), higher than that (61.98%, 2 936/4 737) of the township health centers. The provision of obstetrics and gynecology services in the primary medical institutions was relatively low in quality and quantity. For example, the proportions of township health centers and community health service centers providing midwifery for women with singleton delivery were 22.38% (1 060/4 737) and 10.37% (173/1 669), respectively, with an average daily service of less than one midwifery process. The equipment allocation rates for automatic biochemical analyzers and other related instruments were above 80% for all the primary institutions. The proportions of township health centers and community health service centers supplied with at least one type of drugs on uterine contraction were 51.11% (2 421/4 737) and 49.13% (820/1 669) respectively. The results of multivariate linear logistic regression analysis showed that region, number of staff in active service, number of beds available, proportion of pregnant women with contracted service, and equipment of color Doppler ultrasound instrument had significant influence on the rates of pregnant women registration in first trimester and postpartum visit; the establishment of gynecology departments only had a significant impact on the rate of postpartum visitation. ConclusionThe capability of maternal health services in primary medical institutions is gradually shrinking, and some of the institutions cannot meet the conditions for providing maternal health care services and can only assume responsibility for information management. The assessment criteria and service content of maternal health projects in primary medical institutions need to be adjusted urgently.

Urban Comprehensive Carrying Capacity (UCCC) can describe the development of a city and is an important guarantee for its sustainable development. Production-Living-Ecological Space (PLES) is an important guideline for the optimal development of China’s land space in the new era. Based on the PLES, we construct a UCCC index system and analyzed the spatial and temporal distribution characteristics of the UCCC of each city in Zhejiang Province from 2006 to 2020. In addition, a coupling coordination degree model and an obstacle degree model are introduced to analyze the coupling coordination degree of the development of PLES of each city and the main constraint indicators, respectively, and a GM(1,1) model is used to predict the UCCC of each city in Zhejiang Province from 2021 to 2025. The study indicates that (1) the UCCC of each city is steadily increasing, with a growth rate of over 30% in 15 years. (2) As of 2020, the highest degree of coupling coordination reaches only 0.508, and it remains a major challenge for cities to improve the coordination degree of land use. (3) Some production space and living space indicators are the main obstacle indicators hindering the development of the UCCC in Zhejiang Province. (4) The forecast results show that the UCCC in each city will still maintain an upwards trend in the following 6 years and will gradually reach a high carrying capacity level.

To achieve the safe and stable structural condition of the roof along the goaf under the roof cutting by dense drilling method, the stress distribution and fracture process of the roof strata between normal and dense drilling conditions were studied. Based on rock fracture theory and elastic theory, the stress distribution of the surrounding rock between dense drilling and the fracture process were analyzed before and after mining, clarifying the cutting mechanism of dense drilling and the interaction mechanism of concentrated stress between adjacent drilling. The calculation formula for the tensile-shear stress of the surrounding rock between dense drilling in the arc-shaped triangular panel structure at the end of the working face was derived. Based on this, the influence of different parameters on the tensile-shear stress of the surrounding rock between drilling was analyzed, and a determination method for the key parameters of roof cutting by dense drilling holes along the goaf was proposed. Research has shown that the dense drilling mainly increases the concentration of the surrounding rock's tensile and shear stress by changing the stress conditions around the densely drilled holes before and after mining, causing the expansion and connection of fractures between drilling and forming key rock layers for cutting. Before mining, the drill holes are mainly affected by horizontal compression stress, and after mining, the stress gradually changes to the tensile and shear stress caused by the rotation and subsidence of the goaf roof, and the state of the surrounding rock between the holes transitions from the weakening stage to the formation of crack stage, and then to the fracture stage. The magnitude of the tensile and shear stress of the surrounding rock between the densely drilled holes mainly depends on the thickness of the key rock layer and the ratio of the hole diameter to the hole spacing, and is negatively correlated with the hole height and spacing, and positively correlated with the angle and diameter of the drill holes. Based on this, a method for determining the key parameters of intensive drilling and cutting is proposed, and a plan for intensive drilling and cutting in the goaf with hard roof conditions on the 3124 N working face of Longtan Mine is designed, with a hole length of 8.3 m, an angle of 15°, a hole diameter of 48 mm, and a spacing of 500 mm. The deformation of the goaf roof after cutting is controllable and the overall stability is good, which proves that the arrangement parameters of intensive drilling and cutting are reasonable, and the determination method for the key parameters of roof cutting by dense drilling holes is effective and feasible.

Abstract Background Lysine methyltransferase 2D (KMT2D) mediates mono‐methylation of histone H3 lysine 4 (H3K4me1) in mammals. H3K4me1 mark is involved in establishing an active chromatin structure to promote gene transcription. However, the precise molecular mechanism underlying the KMT2D‐mediated H3K4me1 mark modulates gene expression in triple‐negative breast cancer (TNBC) progression is unresolved. Methods and Results We recognized Y‐box‐binding protein 1 (YBX1) as a “reader” of the H3K4me1 mark, and a point mutation of YBX1 (E121A) disrupted this interaction. We found that KMT2D and YBX1 cooperatively promoted cell growth and metastasis of TNBC cells in vitro and in vivo. The expression levels of KMT2D and YBX1 were both upregulated in tumour tissues and correlated with poor prognosis for breast cancer patients. Combined analyses of ChIP‐seq and RNA‐seq data indicated that YBX1 was co‐localized with KMT2D‐mediated H3K4me1 in the promoter regions of c‐Myc and SENP1, thereby activating their expressions in TNBC cells. Moreover, we demonstrated that YBX1 activated the expressions of c‐Myc and SENP1 in a KMT2D‐dependent manner. Conclusion Our results suggest that KMT2D‐mediated H3K4me1 recruits YBX1 to facilitate TNBC progression through epigenetic activation of c‐Myc and SENP1. These results together unveil a crucial interplay between histone mark and gene regulation in TNBC progression, thus providing novel insights into targeting the KMT2D‐H3K4me1‐YBX1 axis for TNBC treatment. Highlights YBX1 is a KMT2D‐mediated H3K4me1‐binding effector protein and mutation of YBX1 (E121A) disrupts its binding to H3K4me1. KMT2D and YBX1 cooperatively promote TNBC proliferation and metastasis by activating c‐Myc and SENP1 expression in vitro and in vivo. YBX1 is colocalized with H3K4me1 in the c‐Myc and SENP1 promoter regions in TNBC cells and increased YBX1 expression predicts a poor prognosis in breast cancer patients.

Abstract As a potential solution to improve wireless security, specific emitter identification is a lightweight access authentication technology. However, the existed deep learning‐based specific emitter identification methods are highly dependent on the training sample size, leading to serious overfitting problem when the training samples are inadequate, which obstructs their practical applications. To address this issue, an innovative data augmentation method to effectively expand the sample size is proposed. In this design, after data preprocessing, a random integration based data augmentation is applied to integrate several initial samples and generate new samples. Furthermore, compared with the existed methods, chaotic sequences are utilized to randomly set the integration weight of each initial sample, and thus enhancing the diversity of augmented samples. The superiority of the proposed chaotic integration‐based data augmentation method in accuracy, generalization ability and robustness is validated by the hardware implementation on digital mobile radio portable radios.

Due to the fluctuating and intermittent nature of wind energy, its prediction is uncertain. Hence, this paper suggests a method for predicting wind power in the short term and analyzing uncertainty using the VDM-TCN approach. This method first uses Variational Mode Decomposition (VDM) to process the data, and then utilizes the temporal characteristics of Temporal Convolutional Neural Network (TCN) to learn and predict the dataset after VDM processing. Through comparative experiments, we found that VDM-TCN performs the best in short-term wind power prediction. In wind power prediction for 4-h and 24-h horizons, the RMSE errors were 1.499% and 4.4518% respectively, demonstrating the superiority of VDM-TCN. Meanwhile, the Gaussian Mixture Model (GMM) can effectively quantify the uncertainty of wind power generation at different time scales.

Cytoplasmic 6-phosphogluconate dehydrogenase (G6PGH) is a key enzyme in the pentose phosphate pathway that is involved in regulating various biological processes such as material metabolism, and growth and development in plants. However, it was unclear if OsG6PGH1 affected rice grain quality traits. We perform yeast one-hybrid experiments and reveal that OsG6PGH1 may interact with OsAAP6. Subsequently, yeast in vivo point-to-point experiments and local surface plasmon resonance experiments verified that OsG6PGH1 can bind to OsAAP6. OsG6PGH1 in rice is a constitutive expressed gene that may be localized in the cytoplasm. OsAAP6 and protein-synthesis metabolism-related genes are significantly upregulated in OsG6PGH1 overexpressing transgenic positive endosperm, corresponding to a significant increase in the number of protein bodies II, promoting accumulation of related storage proteins, a significant increase in grain protein content (GPC), and improved rice nutritional quality. OsG6PGH1 positively regulates amylose content, negatively regulates chalkiness rate and taste value, significantly affects grain quality traits such as appearance, cooking, and eating qualities of rice, and is involved in regulating the expression of salt stress related genes, thereby enhancing the salt-stress tolerance of rice. Therefore, OsG6PGH1 represents an important genetic resource to assist in the design of high-quality and multi-resistant rice varieties.

BackgroundElevated PPP4C expression has been associated with poor prognostic implications for patients suffering from lung adenocarcinoma (LUAD). The extent to which PPP4C affects immune cell infiltration in LUAD, as well as the importance of associated genes in clinical scenarios, still requires thorough investigation.MethodsIn our investigation, we leveraged both single-cell and comprehensive RNA sequencing data, sourced from LUAD patients, in our analysis. This study also integrated datasets of immune-related genes from InnateDB into the framework. Our expansive evaluation employed various analytical techniques; these included pinpointing differentially expressed genes, constructing WGCNA, implementing Cox proportional hazards models. We utilized these methods to investigate the gene expression profiles of PPP4C within the context of LUAD and to clarify its potential prognostic value for patients. Subsequent steps involved validating the observed enhancement of PPP4C expression in LUAD samples through a series of experimental approaches. The array comprised immunohistochemistry staining, Western blotting, quantitative PCR, and a collection of cell-based assays aimed at evaluating the influence of PPP4C on the proliferative and migratory activities of LUAD cells.ResultsIn lung cancer, elevated expression levels of PPP4C were observed, correlating with poorer patient prognoses. Validation of increased PPP4C levels in LUAD specimens was achieved using immunohistochemical techniques. Experimental investigations have substantiated the role of PPP4C in facilitating cellular proliferation and migration in LUAD contexts. Furthermore, an association was identified between the expression of PPP4C and the infiltration of immune cells in these tumors. A prognostic framework, incorporating PPP4C and immune-related genes, was developed and recognized as an autonomous predictor of survival in individuals afflicted with LUAD. This prognostic tool has demonstrated considerable efficacy in forecasting patient survival and their response to immunotherapeutic interventions.ConclusionThe involvement of PPP4C in LUAD is deeply intertwined with the tumor’s immune microenvironment. PPP4C’s over-expression is associated with negative clinical outcomes, promoting both tumor proliferation and spread. A prognostic framework based on PPP4C levels may effectively predict patient prognoses in LUAD, as well as the efficacy of immunotherapy strategy. This research sheds light on the mechanisms of immune interaction in LUAD and proposes a new strategy for treatment.

Diagenetic physical simulation is a reliable means to study patterns of pore evolution and variations of physical properties, however, the current compaction model is mostly based on sandstone, and there is a lack of quantitative compaction and porosity reduction studies for more complex rock fabrics. In order to simulate the continuous change of intergranular porosity in the reservoir under compaction during the diagenesis of buried sedimentary strata, a self-designed diagenesis simulation experimental system was adopted. Using different modern sediment samples, the simulation experiment of mechanical compaction of glutenite was carried out. The experiment shows that during the process of mechanical compaction of glutenite, the change of porosity with depth is segmented, and there is a good logarithmic relationship between depth and porosity in the process of diagenetic compaction. The larger the grain size in the reservoir rock, the better the pore preservation capacity; When the sand particles fill the pores among gravel, stable secondary support structure formed by gravel and sand grades can effectively take over the bearing pressure, and when the sand-grade particle content is about 30%, the pressure-bearing capacity is the strongest; Intergranular heterobase filling is greater in samples with high heterobase content, high heterobasic content is not favourable to the preservation of primary pores. This study provides favorable experimental support for the preservation mechanism of deep clastic reservoir pores, and has important theoretical and practical significance for oil and gas exploration in the study area. The use of simulation experiment provides a useful idea for the evaluation and prediction of reservoirs and the search for favorable reservoir development zones in the future.

Moraxella catarrhalis (M. catarrhalis) was an underestimated respiratory infection pathogen that has been largely overlooked. The limited availability of rapid and sensitive detection methodologies has hindered M. catarrhalis diagnostic in clinical settings and contributed to its underestimation. To address this issue, we devised two recombinase polymerase amplification (RPA)-based assays for rapid, sensitive and reliable detection of M. catarrhalis, termed M. catarrhalis-RPA-Flu and M. catarrhalis-RPA-LFB, which utilized fluorescence and nanoparticle-based lateral flow biosensor (LFB) for reporting the detection results, respectively. In both assays, the specific copB gene of M. catarrhalis was amplified at 37°C for only a period of 20 minutes. In M. catarrhalis-RPA-Flu system, the detection results were analyzed by either using a real-time fluorescent detector or by direct observation using the naked eye under blue light, while, in M. catarrhalis-RPA-LFB system, biosensors were used for interpreting the results without any specialized instruments. Both methods were able to finalize the entire detection process within a duration of 40 minutes, detect down to 35 fg genomic DNA per test, and correctly differentiate M. catarrhalis from non-M. catarrhalis strains. The feasibility of both techniques was validated by analyzing 96 BALF (Broncho alveolar lavage fluid) samples in clinical settings. Collectively, the newly developed two RPA-based assays exhibit great potential for rapid and accurate identification of M. catarrhalis in standard microbiology laboratories as well as diagnosis of M. catarrhalis infection in clinical settings.

Abstract Background In a multi‐institutional clinical study, we assessed the prognostic significance of a novel indicator preoperative peripheral blood immune (PBIS) scores that combined ratios of preoperative lymphocyte, monocyte, and neutrophil of renal cell carcinoma (RCC) patients undergoing laparoscopic nephrectomy. Methods Between January 2014 and December 2019, 438 patients with RCC were retrospectively analyzed in three centers. We used X‐tile software to obtain the optimum cut‐off values for neutrophils, monocytes, and lymphocytes to classify the patients. To assess the relationship between PBIS score and overall survival (OS), and cancer‐specific survival (CSS) in patients with RCC by Kaplan–Meier survival curves and Cox regression analyses. In addition, predictive OS and CSS nomograms were constructed. The discriminative ability of nomogram and predictive performance accuracy were verified with consistency index (C‐index), calibration curves, receiver operating curve (ROC) curves, decision curve analysis (DCA) curves, and time‐dependent ROC curves. Results The optimum cutoff values for monocytes, lymphocytes, and neutrophils were 0.46, 1.01, and 4.50, respectively. We divided patients into four subgroups according to PBIS scores, which were significantly associated with M‐stage (p = 0.008), T‐stage (p

Glioma is a common tumor originating in the brain that has a high mortality rate. Temozolomide (TMZ) is the first-line treatment for high-grade gliomas. However, a large proportion of gliomas are resistant to TMZ, posing a great challenge to their treatment. In the study, the specific functions and mechanism(s) by which cortistatin (CORT) regulates TMZ resistance and glioma progression were evaluated. The decreased expression of CORT was detected in glioma tissues, and highly expressed CORT was associated with a better survival rate in patients with glioma. CORT overexpression notably decreased the capacity of glioma cells to proliferate and migrate in vitro and to form tumors in vivo. CORT overexpression also markedly suppressed the viability and enhanced the apoptosis of TMZ-resistant U251 cells by regulating MGMT, p21, and Puma expression. Importantly, CORT overexpression reduced the resistance of gliomas to TMZ in vivo. CORT expression was negatively correlated with MGMT expression in both glioma tissues and cells, and it was found that CORT inhibited NF-κB pathway activation in glioma cells, thereby inhibiting MGMT expression. In conclusion, CORT regulates glioma cell growth, migration, apoptosis, and TMZ resistance by weakening the activity of NF-κB/p65 and thereby regulating MGMT expression. The CORT/NF-κB/MGMT axis might be regarded as a molecular mechanism contributing to the resistance of glioma to TMZ. Our data also suggest that CORT regulates the viability and metastatic potential of glioma cells, independent of its effects on TMZ resistance, providing evidence of novel therapeutic targets for glioma that should be evaluated in further studies.

Early screening for Mild Cognitive Impairment (MCI) is crucial in delaying cognitive deterioration and treating dementia. Conventional neuropsychological tests, commonly used for MCI detection, often lack ecological validity due to their simplistic and quiet testing environments. To address this gap, our study developed an immersive VR supermarket cognitive assessment program (IVRSCAP), simulating daily cognitive activities to enhance the ecological validity of MCI detection. This program involved elderly participants from Chengdu Second People’s Hospital and various communities, comprising both MCI patients (N=301) and healthy elderly individuals (N=1027). They engaged in the VR supermarket cognitive test, generating complex datasets including User Behavior Data, Tested Cognitive Dimension Game Data, Trajectory Data, and Regional Data. To analyze this data, we introduced an adaptive ensemble learning method for imbalanced samples. Our study’s primary contribution is demonstrating the superior performance of this algorithm in classifying MCI and healthy groups based on their performance in IVRSCAP. Comparative analysis confirmed its efficacy over traditional imbalanced sample processing methods and classic ensemble learning voting algorithms, significantly outperforming in metrics such as recall, F1-score, AUC, and G-mean. Our findings advocate the combined use of IVRSCAP and our algorithm as a technologically advanced, ecologically valid approach for enhancing early MCI detection strategies. This aligns with our broader aim of integrating realistic simulations with advanced computational techniques to improve diagnostic accuracy and treatment efficacy in cognitive health assessments.

Wildfires cause substantial damage and present considerable risks to both natural ecosystem and human societies. A precise and prompt evaluation of wildfire-induced damage is crucial for effective postfire management and restoration. Considerable advancements have been made in monitoring and mapping fire-affected areas through feature engineering and machine learning techniques. However, existing methods often exhibit several limitations, such as complicated and time-intensive procedures on manual labeling, and a primary focus on binary classification, which only distinguishes between burned and nonburned areas. In response, this study develops a wildfire burn severity assessment model, BiRAUnet-NBR, which can not only accurately identify fire-affected areas, but also assess the burn severity levels (low, moderate, and high) within those areas. Built upon the standard U-Net architecture, the proposed BiRAUnet-NBR first incorporates bitemporal Sentinel 2 Level-2A remote sensing imagery, captured before and after a wildfire, which enables the model to better distinguish burned areas from the background and identify the severity level of the resulting burns. In addition, it further enhances the standard U-Net architecture by fusing additional spectral layers, such as the normalized burn ratio (NBR) derived from post- and prefire images, therefore, informing the detection of burn areas. Moreover, BiRAUnet-NBR also integrates attention mechanism, enabling the model to pay more attention to meaningful features and burn areas, and residual blocks in the decoder module, which not only significantly improves segmentation results but also enhances training stability and prevents the issue of vanishing gradients. The experimental results demonstrate the superiority of the proposed model in both multiclass and binary mapping of wildfire burn areas, achieving an overall accuracy over 95%. Furthermore, it outperforms baseline algorithms, including support vector machine, random forest, eXtreme gradient boosting, and fully convolutional network, with an average improvement of 18% in F1-score and 15% in mean intersection over union.