Search

Background Personalized medicine has gained more attention for cancer precision treatment due to patient genetic heterogeneity in recent years. However, predicting the efficacy of antitumor drugs in advance remains a significant challenge to achieve this task. Objective This study aims to predict the efficacy of antitumor drugs in individual cancer patients based on clinical data. Methods This paper proposes to predict personalized antitumor drug efficacy based on clinical data. Specifically, we encode the clinical text of cancer patients as a probability distribution vector in hidden topics space using the Latent Dirichlet Allocation (LDA) model, named LDA representation. Then, a neural network is designed, and the LDA representation is input into the neural network to predict drug response in cancer patients treated with platinum drugs. To evaluate the effectiveness of the proposed method, we gathered and organized clinical records of lung and bowel cancer patients who underwent platinum-based treatment. The prediction performance is assessed using the following metrics: Precision, Recall, F1-score, Accuracy, and Area Under the ROC Curve (AUC). Results The study analyzed a dataset of 958 patients with non-small cell cancer treated with antitumor drugs. The proposed method achieved a stratified 5-fold cross-validation average Precision of 0.81, Recall of 0.89, F1-score of 0.85, Accuracy of 0.77, and AUC of 0.81 for cisplatin efficacy prediction on the data, which most are better than those of previous methods. Of these, the AUC value is at least 4% higher than those of the previous. At the same time, the superior result over the previous method persisted on an independent dataset of 266 bowel cancer patients, showing the generalizability of the proposed method. These results demonstrate the potential value of precise tumor treatment in clinical practice. Conclusions Combining LDA and neural networks can help predict the efficacy of antitumor drugs based on clinical text. Our approach outperforms previous methods in predicting drug clinical efficacy.

Hydro-meteorological monitoring through satellites in arid and semi-arid regions is constrained by the coarse spatial resolution of precipitation data, which impedes detailed analyses. The objective of this study is to evaluate various machine learning techniques for developing a downscaling framework that generates high spatio-temporal resolution precipitation products. Focusing on the Hai River Basin, we evaluated three machine learning approaches—Extreme Gradient Boosting (XGBoost), Random Forest (RF), and Back Propagation (BP) neural networks. These methods integrate environmental variables including land surface temperature (LST), Normalized Difference Vegetation Index (NDVI), Digital Elevation Model (DEM), Precipitable Water Vapor (PWV), and albedo, to downscale the 0.1° spatial resolution Global Precipitation Measurement (GPM) product to a 1 km resolution. We further refined the results with residual correction and calibration using terrestrial rain gauge data. Subsequently, utilizing the 1 km annual precipitation, we employed the moving average window method to derive monthly and daily precipitation. The results demonstrated that the XGBoost method, calibrated with Geographical Difference Analysis (GDA) and Kriging spatial interpolation, proved to be the most accurate, achieving a Mean Absolute Error (MAE) of 58.40 mm for the annual product, representing a 14 % improvement over the original data. The monthly and daily products achieved MAE values of 11.61 mm and 1.79 mm, respectively, thus enhancing spatial resolution while maintaining accuracy comparable to the original product. In the Hai River Basin, key factors including longitude, latitude, DEM, LST_night, and PWV demonstrated greater importance and stability than other factors, thereby enhancing the model's precipitation prediction capabilities. This study provides a comprehensive assessment of the annual, monthly, and daily high-temporal and high-spatial resolution downscaling processes of precipitation, serving as an important reference for hydrology and related fields.

BackgroundLung is the largest mucosal area of the human body and directly connected to the external environment, facing microbial exposure and environmental stimuli. Therefore, studying the internal microorganisms of the lung is crucial for a deeper understanding of the relationship between microorganisms and the occurrence and progression of lung cancer.MethodsTumor and adjacent nontumor tissues were collected from 38 lung adenocarcinoma patients and used nanopore sequencing technology to sequence the 16s full-length sequence of bacteria, and combining bioinformatics methods to identify and quantitatively analyze microorganisms in tissues, as well as to enrich the metabolic pathways of microorganisms.Resultsthe microbial composition in lung adenocarcinoma tissues is highly similar to that in adjacent tissues, but the alpha diversity is significantly lower than that in adjacent tissues. The difference analysis results show that the bacterial communities of Streptococcaceae, Lactobacillaceae, and Neisseriales were significantly enriched in cancer tissues. The results of metabolic pathway analysis indicate that pathways related to cellular communication, transcription, and protein synthesis were significantly enriched in cancer tissue. In addition, clinical staging analysis of nicotine exposure and lung cancer found that Haemophilus, paralinfluenzae, Streptococcus gordonii were significantly enriched in the nicotine exposure group, while the microbiota of Cardiobactereae and Cardiobacterales were significantly enriched in stage II tumors. The microbiota significantly enriched in IA-II stages were Neisseriaeae, Enterobacteriales, and Cardiobacterales, respectively.ConclusionNanopore sequencing technology was performed on the full length 16s sequence, which preliminarily depicted the microbial changes and enrichment of microbial metabolic pathways in tumor and adjacent nontumor tissues. The relationship between nicotine exposure, tumor progression, and microorganisms was explored, providing a theoretical basis for the treatment of lung cancer through microbial targets.

Abstract Background Severe bacterial infections can trigger acute lung injury (ALI) and acute respiratory distress syndrome, with bacterial pathogen‐associated molecular patterns (PAMPs) exacerbating the inflammatory response, particularly in COVID‐19 patients. Cyclic‐di‐GMP (CDG), one of the PAMPs, is synthesized by various Gram‐positve and Gram‐negative bacteria. Previous studies mainly focused on the inflammatory responses triggered by intracellular bacteria‐released CDG. However, how extracellular CDG, which is released by bacterial autolysis or rupture, activates the inflammatory response remains unclear. Methods The interaction between extracellular CDG and myeloid differentiation protein 2 (MD2) was investigated using in vivo and in vitro models. MD2 blockade was achieved using specific inhibitor and genetic knockout mice. Site‐directed mutagenesis, co‐immunoprecipitation, SPR and Bis‐ANS displacement assays were used to identify the potential binding sites of MD2 on CDG. Results Our data show that extracellular CDG directly interacts with MD2, leading to activation of the TLR4 signalling pathway and lung injury. Specific inhibitors or genetic knockout of MD2 in mice significantly alleviated CDG‐induced lung injury. Moreover, isoleucine residues at positions 80 and 94, along with phenylalanine at position 121, are essential for the binding of MD2 to CDG. Conclusion These results reveal that extracellular CDG induces lung injury through direct interaction with MD2 and activation of the TLR4 signalling pathway, providing valuable insights into bacteria‐induced ALI mechanisms and new therapeutic approaches for the treatment of bacterial co‐infection in COVID‐19 patients.

The present study involves the preparation of continuous carbon fiber samples treated with epoxy-based sizing agent (EP) and vinyl ester resin-based sizing agent (VE), alongside untreated fibers, aiming to explore the influence pattern of interfacial differences caused by these sizing agents on the compressive properties of carbon fiber composites. Surface analysis, including Scanning Electron Microscope (SEM), Atomic Force Microscope (AFM), and X-ray Photoelectron Spectroscopy (XPS), followed by testing the mechanical properties of carbon fibers and the composite materials. Results indicate that, compared to unsized carbon fibers, EP and VE increase the O atom content on the carbon fiber surface by 13.0% and 18.1%, respectively, and enhance the proportion of active C atoms by 11.3% and 20.3%, respectively. The interlaminar shear strength (GB/T) of carbon fibers is improved by 9.3% and 20.0%, respectively. Given the compatibility between the sizing agent and the matrix resin, VE improves the open-hole compressive strength of composites by 6.7% compared to EP. This improvement in interface bonding performance positively impacts the open-hole compressive properties of the composites, though it has limited effect on the 0° compressive and post-impact compressive strengths. Following EP and VE sizing, the 0° compressive strength increases by 11.8% and 13.6%, respectively, with VE only resulting in a marginal 1.6% improvement over EP. The enhancements in both interlaminar shear strength and open-hole compressive strength are attributed to the increased number of active functional groups at the fiber-resin interface, facilitated by sizing agents, which promote stronger chemical bonding and thus improved load transfer between the fibers and the matrix. VE demonstrates superior performance over EP in regulating the interface state of carbon fibers.The presence or absence of a sizing agent has a more significant impact on the compressive properties of carbon fiber composites than the type of sizing agent used. These findings provide valuable insights for optimizing the preparation and enhancing the compressive performance of carbon fiber composite materials.

Abstract Objectives The application of a growing rod technique can retain the growth and development potential of the spine and thorax while controlling the progression of scoliosis deformity. Theoretically, convex side short fusion combined with a concave side single growing rod technique can significantly reduce the asymmetric growth of the spine in the vertex region in most patients. However, the final clinical outcome of various techniques is yet to be clearly determined and compared between studies. Therefore, we compared the efficacy of these two growing rod techniques in treating early onset scoliosis. Methods In a retrospective study of 152 EOS patients seen between 2013.1 and 2019.12, 36 cases of EOS patients were selected for inclusion. Among the 36 cases, 11 cases were treated with convex side short fusion combined with a concave side single growing rod technique, group (A) The remaining 25 cases were treated with traditional bilateral growing rod technique, group (B) Age, gender, etiology, follow-up time, Cobb angle of main curve, T1-S1 height, coronal trunk shift, sagittal vertical axis (SVA), Cobb angle of thoracic kyphosis at last follow-up, and Cobb angle at proximal junction kyphosis of the first and last post-operation follow-up were recorded. In addition, internal fixation related complications, infection, nervous system complications were recorded as well. Results There was no statistically significant difference between group A and group B in preoperative age, Cobb angle of main curve, coronal trunk shift, T1-S1 height, SVA, Cobb angle of thoracic kyphosis (p > 0.05). However, at the last follow-up (Group A, mean 4.4 ± 1.01 years; Group B, mean 3.6 ± 0.01 years) the Cobb angle of the main curve was less and T1-S1 height greater in group A compared with group B (p 0.05). There was no statistically significant difference in the coronal imbalance ratio, thoracic kyphosis abnormality ratio, or the occurrence PJK ratio between group A and group B at the last follow-up (p > 0.05), but the sagittal imbalance ratio and internal fixation abnormality ratio were higher in group A than in the group B (p

Modern social networks are especially beneficial for spreading rumors since they perform as multichannel communication platforms. The spread of false information has a detrimental impact on people, communities, and businesses. Media reports significantly affect rumor propagation by providing inhibiting factors. In this paper, we propose a new ISCRM fractional-order model to analyze the law of rumor propagation and provide appropriate control strategies. First, under fractional differential equations, the boundedness and non-negativeness of the solutions are obtained. Second, the local and global asymptotic stability of the rumor-free equilibrium and rumor-permanence equilibrium are proved. Third, employing Pontryagin's maximum principle, the conditions necessary for fractional optimum control are derived for the rumor model, and the optimal solutions are analyzed. Finally, several numerical simulations are presented to verify the accuracy of the theoretical results. For instance, while media reports can mitigate the propagation of rumors across various dynamic regions, they are unable to completely restrain rumor spread.

Objective Prostate hyperplasia and cancer are more prevalent in middle-aged and elderly men. Previous studies have linked both disorders to androgen receptors. Herein, efforts were made to identify factors associated with prostate cancer in patients ≥60 years, aiming to enhance their health management.Methods An analytical framework was established utilizing the “Prostate Cancer Early Warning Dataset” from the National Clinical Medical Science Data Center. Variables selection was conducted through LASSO regression, followed by multifactorial logistic stepwise regression to construct a predictive model.Results A total of 1,502 patients with BPH and 294 with combined PCa were hereby included. Multivariate regression delineated several independent predictors of PCa coexistence, including age (OR [95% CI]: 1.06 [1.04–1.09], p

Abstract Complex natural fracture networks typically consist of multiple clusters, whose connectivity is rarely quantified. Therefore, for each identified fracture network, we propose a connectivity metric that accounts for individual fracture clusters and their interactions. This metric evaluates contributions from all fracture clusters, considering their relative sizes and interactions among the isolated clusters, which in turn depend on the hydraulic conductance of the interconnecting rock matrix. Furthermore, we investigate how the system connectivity depends on fracture sealing, alterations of central clusters, and cluster linkage. Fracture sealing strongly impacts overall fracture connectivity, with 5 percent of sealed fractures reducing connectivity by 20 percent. The connectivity reduction is small when transitioning the central cluster from the largest to the smallest one. However, the largest cluster significantly contributes to overall connectivity, while the smallest one contributes minimally. Natural fracture networks increase connectivity by linking more clusters, with heterogeneity and anisotropy playing pivotal roles.

BackgroundBedside lung ultrasonography has been widely used in neonatal intensive care units (NICUs). Lung ultrasound scores (LUS) may predict the need for pulmonary surfactant (PS) application. PS replacement therapy is the key intervention for managing moderate to severe neonatal respiratory distress syndrome (NRDS), with early PS administration playing a positive role in improving patient outcomes. Lung ultrasonography aids in the prompt diagnosis of NRDS, while LUS offers a semi-quantitative assessment of lung health. However, the specific methodologies for utilizing LUS in clinical practice remain controversial. This study hypothesizes that, in very preterm infants [

Recent studies in Western cultures suggested emotion regulation goals have important implications for mental health. This study aimed to test the factor structure of Emotion Regulation Goals Scale (ERGS) in a Chinese cultural context. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were first used to examine the factor structure of the ERGS, and then reliability and validity tests were conducted to examine the psychometric properties of the ERGS. Results showed that the original five-factor model demonstrated fit during both EFA and CFA, and was thus adopted for further psychometric analyses. Most of the five factors were significantly associated with emotion regulation tendencies and negative emotional outcomes (e.g., depression), except for the non-significant associations between pro-hedonic goals and expressive suppression, and pro-social and impression management goals with depression. The ERGS also showed good internal consistency and split-half reliability. However, the test-retest reliabilities varied substantially across the five factors. The pro-hedonic goal had a higher test-retest reliability, whereas the contra-hedonic, performance, pro-social, and impression management goals showed lower values, especially the latter two. In brief, the ERGS showed a promising five-factor structure in assessing emotion regulation goals in Chinese cultural context.

Background: Antidepressants are widely used to manage depression and other psychiatric diseases. A previous study revealed that hepatotoxicity was the main adverse event related to antidepressants. Therefore, drug-induced liver injury (DILI) caused by antidepressants deserves more attention. Objectives: To investigate DILI adverse events reported due to antidepressant use in the United States Food and Drug Administration Adverse Events Reporting System (FAERS) database. Research design: A disproportionality analysis of spontaneously reported adverse events was conducted to assess the association between antidepressant drugs and DILI. Methods: FAERS data from 1 January 2004 to 31 December 2021 were compiled and analyzed using the reporting odds ratio (ROR) and information component (IC). Results: As per the FAERS database, of the 324,588 cases that were administered antidepressants, 10,355 were identified as cases with DILI. Among the identified 42 antidepressants, nefazodone ( n = 47, ROR = 7.79, IC = 2.91), fluvoxamine ( n = 29, ROR = 4.69, IC = 2.20), and clomipramine ( n = 24, ROR = 3.97, IC = 1.96) had the highest ROR for cholestatic injury; mianserin ( n = 3, ROR = 21.46, IC = 3.99), nefazodone ( n = 264, ROR = 18.67, IC = 3.84), and maprotiline ( n = 15, ROR = 5.65, IC = 2.39) for hepatocellular injury; and nefazodone ( n = 187, ROR = 12.71, IC = 0.48), clomipramine ( n = 35, ROR = 2.07, IC = 0.26), and mirtazapine ( n = 483, ROR = 1.96, IC = 0.94) for severe drug-related hepatic disorders. Only nefazodone elicited hepatic failure signals ( n = 48, ROR = 18.64, IC = 4.16). There are limited reports on the adverse reactions of relatively new antidepressant drugs, such as milnacipran, viloxazine, esketamine, and tianeptine, and those not approved by the Food and Drugs Administration, such as reboxetine and agomelatine. Conclusion: A significant association was observed between DILI and nefazodone. Duloxetine and clomipramine were associated with three DILI categories, except hepatic failure. The disproportionality analysis cannot conclude on a definite causal link between antidepressants and DILI. Additional research is required to assess new-generation antidepressants for their propensity to cause DILI.

The manufacturing sector is the main battlefield of energy saving and carbon reduction in China, and vigorously promoting energy saving and carbon reduction in manufacturing and enhancing the green development level are the key links to support China's realization of the dual-carbon goal. The article adopts the SBM-GML model to measure the level of green development of the manufacturing industry in China. Based on this, it analyzes the spatio-temporal characteristics and the evolution law of the level of green development of the manufacturing industry by using the Dagum Gini Coefficient and Kernel Density Estimation. Using a spatial econometric model to explore the influencing factors of the level of green development of the manufacturing industry. The study finds that the green development level of the manufacturing industry has achieved remarkable results in recent years, but there are differences in the development level of each region. The regional differences in the level of green development of the manufacturing industry are significant. The optimization of manufacturing structure is a key factor influencing the level of green development of the manufacturing industry, and there is a positive spatial spillover effect of manufacturing structure optimization. However, The green development of the manufacturing industry shows a negative spatial spillover effect. The article proposes optimization paths based on the requirements of dual-carbon targets and regional characteristics, which is an important inspiration and reference for the green development level of the manufacturing industry in the world.

Chronic subdural hematoma (CSDH) is a chronic space-occupying lesion formed by blood accumulation between the arachnoid membrane and the dura mater. Atorvastatin is of increasing clinical interest for CSDH. We performed a meta-analysis of published randomized controlled trials (RCTs) and used objective data as the primary outcomes to provide an evidence-based analysis of the efficacy of atorvastatin for CSDH treatment. Databases of MEDLINE (via PubMed), EMBASE, the Cochrane Library, Scopus, Web of Science, ScienceDirect, Chinese National Knowledge Infrastructure (CNKI), Cqvip database (CQVIP), and Wanfang database were systematically searched for RCTs reporting the use of atorvastatin for CSDH treatment. Odds ratio (OR), standard mean difference (SMD), and 95% confidence intervals (CIs) were used as summary statistics. I-square (I2) test was performed to assess the impact of study heterogeneity on the results of the meta-analysis. Nine relevant RCTs with 611 patients were identified for inclusion in this meta-analysis. Compared to controls, atorvastatin treatment had a significantly higher effectiveness (OR: 7.41, 95% CI: 3.32-16.52, P < 0.00001, I2 = 0%), lower hematoma volume (SMD: −0.46. 95% CI: −0.71 to −0.20, P = 0.0005, I2 = 0%), higher activities of daily living-Barthel Index (ADL-BI) (SMD: 2.07, 95% CI: 1.06-3.09, P < 0.0001, I2 = 92%), and smaller Chinese stroke scale (CSS) (SMD: -1.10, 95% CI: −1.72 to −0.48, P = 0.0005, I2 = 57%). In view of these findings, we conclude that the outcomes of experimental group are superior to the control group with respect to effectiveness, hematoma volume, ADL-BI, and CSS based on nine RCTs with 611 patients. Atorvastatin is beneficial to CSDH patients without surgery.

The precipitation behavior of Nb-rich phase in Al-free and 1Al Nb-bearing ferritic stainless steels (FSSs) at 700 °C were investigated. The results show that Nb-bearing carbides and Laves phases with mutual transformation relationships are precipitated in both Al-free and 1Al Nb-bearing FSSs at the early stage of aging. At this stage, the coarsening rate of Laves phase is higher than that of Nb2C phase, and the addition of Al can promote the precipitation of Laves phase and weaken the precipitation of (Nb, Ti)2C phase. As the aging time extended to 60 min, the Nb-rich phase in the two experimental steels was mainly Laves phase, and the intragranular Laves phase showed feather like aggregation distribution. On the one hand, the added Al can be enriched in the Laves phase to produce a tailing morphology, on the other hand, it can reduce the diffusion rate of Nb atoms in the matrix, thereby weakening the aggregation state of the intragranular Laves phase. During the coarsening process of Laves phase, the addition of Al can reduce the coarsening rate of Laves phase by 7.45 times.

Abstract Background Multiple rib fractures can lead to flail chest with up to 35% mortality rate due to severe pulmonary complications. Current treatments of flail chest remain controversial. Studies have shown that surgical treatments can improve outcomes and reduce mortality, comparing to non-operative treatments. Current surgical fixation methods focus on stabilization of ribs on the outward facing side, and they require division of intercostal muscles. Damages to surrounding nerves and vessels may lead to chronic pain. This study tests a novel interior fixation method that minimizes neurovascular injuries. Methods Twelve healthy canines were divided in two surgical operation groups for exterior and interior fixation using titanium metal plates. Osteotomy with oblique fractures was prepared under general anesthesia. Exterior fixation was performed in open surgery. Interior fixation was minimally invasive using custom made tools including a flexible shaft extension screwdriver, solid plate stand, guiding wire loop and metal plates with threaded holes. Results Respiratory and cardiovascular functions (RR, PO2, PCO2, SpO2, and HR) together with body temperature were measured before anesthesia and within 48 h after surgery. The difference in measurements was not statistically significant between the two groups before surgery with P values greater than 0.05. However, the interior group canines had better RR and PO2 values starting from the 24th hour, and better PCO2, SpO2, and HR values starting from the 48th hour. It took longer operation time to complete the minimally invasive interior fixation surgery (P value less than 0.001), but the total blood loss was less than the exterior fixation group (P value less than 0.001). Results also showed that interior group canines suffered less pain, and they had quicker recovery in gastrointestinal and physical mobility. Conclusions The investigative interior fixation method was safe and effective in rib stabilization on a canine rib fracture model, comparing to the exterior fixation method. The interior fixation was minimally invasive, with less damages to tissues and nerves surrounding the ribs, leading to better postoperative outcomes.

Idiopathic pulmonary fibrosis (IPF) is a progressive and chronic disease that significantly impacts patient quality of life, and its incidence is on the rise. The pathogenesis of IPF remains poorly understood. Alveolar type 2 (AT2) cells are crucial in the onset and progression of IPF, yet the specific mechanisms involved are not well defined. Lon protease 1 (LONP1), known for its critical roles in various diseases, has an unclear function in IPF. Our research investigated the impact of Lonp1 gene deletion on AT2 cell functionality and its subsequent effect on IPF development. We generated a bleomycin-induced pulmonary fibrosis mouse model with a targeted Lonp1 knockout in AT2 cells and assessed the consequences on AT2 cell function and fibrosis progression. Additionally, we constructed the MLE12 cells with stable Lonp1 knockdown and utilized transcriptome sequencing to identify pathways altered by the Lonp1 knockdown. Our results indicated that mice with AT2 cell-specific Lonp1 knockout exhibited more severe fibrosis compared to controls. These mice exhibited a reduction in AT2 and AT1 cell populations, along with an increase in p53- and p21-positive AT2 cells. Lonp1 knockdown in MLE12 cells led to the upregulation of aging-associated pathways, with fibroblast growth factor 2 (Fgf2) gene emerging as a central gene interconnecting these pathways. Therefore, loss of Lonp1 appears to promote AT2 cell aging and exacerbate bleomycin-induced pulmonary fibrosis. Fgf2 emerges as a pivotal downstream gene associated with cellular senescence. This study uncovers the role of the Lonp1 gene in pulmonary fibrosis, presenting a novel target for investigating the pathological mechanisms and potential therapeutic approaches for IPF.

Anti-tumor drug efficacy prediction poses an unprecedented challenge to realizing personalized medicine. This paper proposes to predict personalized anti-tumor drug efficacy based on clinical data. Specifically, we encode the clinical text as numeric vectors featured with hidden topics for patients using Latent Dirichlet Allocation model. Then, to classify patients into two classes, responsive or non-responsive to a drug, drug efficacy predictors are established by machine learning based on the Latent Dirichlet Allocation topic representation. To evaluate the proposed method, we collected and collated clinical records of lung and bowel cancer patients treated with platinum. Experimental results on the data sets show the efficacy and effectiveness of the proposed method, suggesting the potential value of clinical data in cancer precision medicine. We hope that it will promote the research of drug efficacy prediction based on clinical data.

The Xianshuihe fault zone in the eastern Qinghai–Tibetan Plateau is an important active tectonic boundary. Understanding its stress state is important for characterizing the dynamic evolution of the Qinghai–Tibet Plateau and the mechanism of the frequent occurrence of large earthquakes. Using 30 years of in-situ stress data from the Xianshuihe active fault zone, we statistically analyzed the spatial distribution characteristics of the stress in the region. The study area is generally characterized by a strike-slip stress field. Nevertheless, the stress state is vulnerable to topography and shows high spatial variation near the Earth’s surface at a depth of 0–400 m. The local stress near the fault zone varies from the far-field stress. The orientations of the maximum horizontal principal stress possess an elliptical shape around the fault zone, while its magnitudes become hump-like as the distance increases from the fault. The large difference in properties between the fault zone and its adjacent rocks contributes to the differentiation of the direction of the local stress field near the fault. The results allow us to formulate a preliminary hypothesis that a rigid lateral extrusion model may control the nonuniformity of the local stress field in the Xianshuihe fault zone and preferentially interpret the tectonic uplift of the southeastern margin of the Qinghai–Tibet Plateau. Further, the stress accumulation in the shallow crustal regions of the Xianshuihe fault zone is relatively high, indicating that some segments of the fault zone are critically unstable. Kangding area (the Zheduotang segment and the Yalahe segment) and Luhuo segment hold relatively high potential for large earthquakes. The results of this study are of great significance for revealing the mechanism of fault–stress field interactions and for understanding the dynamic evolution mechanism of the uplift of the Qinghai–Tibet Plateau.

Scientific communication holds a pivotal role within research institutions. This study establishes three distinct categories of indicators, tailored to the unique attributes of these institutions, aiming to assess their performance in scientific communication. Employing a rigorous two-stage data envelopment analysis (DEA) approach, we meticulously calculate output efficiency, feedback efficiency, and overall efficiency. Subsequently, we cluster the efficiency outcomes and delve into the factors that influence them. Drawing from the clustering insights and identified influencing factors, we formulate targeted scientific communication strategies tailored to the needs of these research institutions.

Diabetic cardiomyopathy (DCM) represents a common pathological state brought about by diabetes mellitus (DM). Patchouli alcohol (PatA) is known for its diverse advantageous effects, notably its anti-inflammatory properties and protective role against metabolic disorders. Despite this, the influence of PatA on DCM remains relatively unexplored. To explore the effect of PatA on diabetes-induced cardiac injury and dysfunction in mice, streptozotocin (STZ) was used to mimic type 1 diabetes in mice. Serological markers and echocardiography show that PatA treatment protects the heart against cardiomyopathy by controlling myocardial fibrosis but not by reducing hyperglycemia in diabetic mice. Discovery Studio 2017 software was used to perform reverse target screening of PatA, and we found that JAK2 may be a potential target of PatA. RNA-seq analysis of heart tissues revealed that PatA activity in the myocardium was primarily associated with the inflammatory fibrosis through the Janus tyrosine kinase 2 (JAK2)/signal transducer and activator of the transcription 3 (STAT3) pathway. In vitro, we also found that PatA alleviates high glucose (HG) + palmitic acid (PA)-induced fibrotic and inflammatory responses via inhibiting the JAK2/STAT3 signaling pathway in H9C2 cells. Our findings illustrate that PatA mitigates the effects of HG + PA- or STZ-induced cardiomyopathy by acting on the JAK2/STAT3 signaling pathway. These insights indicate that PatA could potentially serve as a therapeutic agent for DCM treatment.

Nowadays, rumors spread more rapidly than before, leading to more panic and instability in society. Therefore, it is essential to seek out propagation law in order to prevent rumors from spreading further and avoid unnecessary harm. There is a connection between rumor models and symmetry. The consistency of a system or model is referred to as the level of symmetry under certain transformations. For this purpose, we propose a fractional-order Ignorant–Latent–Spreader–Remover (ILSR) rumor propagation model that incorporates media reports and a nonlinear inhibition mechanism. Firstly, the boundedness and non-negativeness of the solutions are derived under fractional differential equations. Secondly, the threshold is used to evaluate and illustrate the stability both locally and globally. Finally, by utilizing Pontryagin’s maximum principle, we obtain the necessary conditions for the optimal control in the fractional-order rumor propagation model, and we also obtain the associated optimal solutions. Furthermore, the numerical results indicate that media reports can decrease the spread of rumors in different dynamic regions, but they cannot completely prevent rumor dissemination. The results are also exhibited and corroborated by replicating the model with specific hypothetical parameter values. It can be inferred that fractional order yields more favorable outcomes when rumor permanence in the population is higher. The presented method facilitates the acquisition of profound insights into the dissemination dynamics and subsequent consequences of rumors within a societal network.

Abstract Topologically protected photonic edge states offer unprecedented robust propagation of photons that are promising for waveguiding, lasing, and quantum information processing. Here, we report on the discovery of a class of hybrid topological photonic crystals that host simultaneously quantum anomalous Hall and valley Hall phases in different photonic band gaps. The underlying hybrid topology manifests itself in the edge channels as the coexistence of the dual-band chiral edge states and unbalanced valley Hall edge states. We experimentally realize the hybrid topological photonic crystal, unveil its unique topological transitions, and verify its unconventional dual-band gap topological edge states using pump-probe techniques. Furthermore, we demonstrate that the dual-band photonic topological edge channels can serve as frequency-multiplexing devices that function as both beam splitters and combiners. Our study unveils hybrid topological insulators as an exotic topological state of photons as well as a promising route toward future applications in topological photonics.

Abstract Obesity increases the risk for cardiovascular diseases and induces cardiomyopathy. Chronic inflammation plays a significant role in obesity-induced cardiomyopathy and may provide new therapeutic targets for this disease. Doublecortin-like kinase 1 (DCLK1) is an important target for cancer therapy and the role of DCLK1 in obesity and cardiovascular diseases is unclear. Herein, we showed that DCLK1 was overexpressed in the cardiac tissue of obese mice and investigated the role of DCLK1 in obesity-induced cardiomyopathy. We generated DCLK1-deleted mice and showed that macrophage-specific DCLK1 knockout, rather than cardiomyocyte-specific DCLK1 knockout, prevented high-fat diet (HFD)-induced heart dysfunction, cardiac hypertrophy, and fibrosis. RNA sequencing analysis showed that DCLK1 deficiency exerted cardioprotective effects by suppressing RIP2/TAK1 activation and inflammatory responses in macrophages. Upon HFD/palmitate (PA) challenge, macrophage DCLK1 mediates RIP2/TAK1 phosphorylation and subsequent inflammatory cytokine release, which further promotes hypertrophy in cardiomyocytes and fibrogenesis in fibroblasts. Finally, a pharmacological inhibitor of DCLK1 significantly protects hearts in HFD-fed mice. Our study demonstrates a novel role and a pro-inflammatory mechanism of macrophage DCLK1 in obesity-induced cardiomyopathy and identifies DCLK1 as a new therapeutic target for the treatment of this disease. Upon HFD/PA challenge, DCLK1 induces RIP2/TAK1-mediated inflammatory response in macrophages, which subsequently promotes cardiac hypertrophy and fibrosis. Macrophage-specific DCLK1 deletion or pharmacological inhibition of DCLK1 protects hearts in HFD-fed mice.

We present the scintillation velocity measurements of FRB 20201124A from the Five-hundred-meter Aperture Spherical radio Telescope observations, which reveal an annual variation. This annual variation is further supported by changes detected in the scintillation arc as observed from the secondary spectrum. We attribute the annual velocity variation to the presence of a moderately anisotropic scattering screen located at a distance of 0.4 ± 0.1 kpc from Earth. Our results prove that the scintillation of this fast radio burst (FRB) is mainly caused by material close to Earth on a Galactic scale. However, scintillation observations of other FRBs may expose their surrounding environment or uncover possible orbital motion if scintillation is caused by materials in their host galaxy.

Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial disease that cannot be cured, and treatment options for IPF are very limited. Early diagnosis, close monitoring of disease progression, and timely treatment are therefore the best options for patients due to the irreversibility of IPF. Effective markers help doctors judge the development and prognosis of disease. Recent research on traditional biomarkers (KL-6, SP-D, MMP-7, TIMPs, CCL18) has provided novel ideas for predicting disease progression and prognosis. Some emerging biomarkers (HE4, GDF15, PRDX4, inflammatory cells, G-CSF) also provide more possibilities for disease prediction. In addition to markers in serum and bronchoalveolar lavage fluid (BALF), some improvements related to the GAP model and chest HRCT also show good predictive ability for disease prognosis.

Abstract Background and objective Sudden cardiac death (SCD) is one of the leading causes of death in cardiovascular diseases. Monitoring the state of the heart in real time and giving early warning of possible dangers by using ambulate electrocardiogram signals are the keys to prevent cardiovascular death. However, due to the diversity inducing factors of SCD and great individual differences, accurate prediction of SCD using electrocardiogram is a hard task, especially applied in portable electrocardiograph. Methods This paper proposed a multi-domain features fusion algorithm to predict SCD. Heart rate variability (HRV) signals was used to investigate the characters of SCD. A multiscale variation feature extracted from multiscale poincare plots was proposed to demonstrate the dynamic changes of HRV along different scales. A time-domain feature, Shannon entropy and this multiscale variation feature were combined by using SVM classifier to classify SCD. HRV signals from different time periods prior to SCD onset were used to test the effectiveness of the SCD prediction algorithm. And the dynamic variation characteristics of SCD prediction accuracy for each minute were also studied. Results In the prediction of SCD using the 70-min HRV signals before the onset of SCD, the average prediction accuracy only using the multiscale variation feature reached to 85.83%, which verified the effectiveness and high specificity of this multiscale variation feature. By combining time domain, Shannon entropy and the multiscale variation feature, the average prediction accuracy was improved to 91.22%. Through fusing multi-domain feature extracted in this paper, the advance prediction time was increased to 70 min before the onset of SCD. Conclusions A feature with high sensitivity and specificity is proposed to predict SCD. By fusing multi-domain features of HRV signals, a high prediction accuracy is achieved and the advance prediction ability is improved. The algorithm is low computational complexity and easy to integrate into cardiovascular intelligent monitoring equipment, making the intelligent monitoring and real-time early warning of SCD becomes possible.

The quenching-partitioning-tempering (QPT) treatment was carried out on a low carbon bainitic steel, and the effect of tempering temperature on the microstructure and mechanical properties of the QPT processed steel was investigated. The findings demonstrate that as the tempering temperature increases, the yield strength decreases gradually, while the tensile strength decreases first and then increases. However, the elongation exhibits a trend of increasing first and then decreasing with increasing the tempering temperature. When the tempering temperature is 340 °C, the best mechanical properties can be obtained with the yield strength of 1495 MPa, tensile strength of 1806 MPa, elongation of 17.7%, and product of strength and elongation up to 32.92 GPa%. Such excellent mechanical properties are related to the synergistic combination of tempered martensite, low carbon bainite, retained austenite and carbides.

A 20-month-old girl was diagnosed with Guillain – Barré syndrome (GBS) based on progressive muscle weakness, areflexia, and albuminocytologic dissociation of the cerebrospinal fluid. Despite timely and systematic treatment, she eventually became paralyzed. There is a temporal correlation between the girl’s GBS and the DTaP vaccination, but the exact causal relationship between the two is still debatable. Furthermore, we summarized clinical features of other 45 published GBS cases after DTP vaccines (or vaccine substances containing tetanus) through a systematic review. The mean onset age, sex distribution, onset time after vaccination, detection of antiganglioside antibodies, and other basic clinical features of GBS after DTP vaccination (or vaccine substances containing tetanus) were analyzed. The temporal pattern of GBS after vaccination was similar to that of GBS after infection. Herein, we report this rare case of presumptive pediatric GBS after DTaP vaccination and review similar cases to draw the attention of medical personnel to similar events after vaccination. An association between DTP vaccines and GBS has been proposed, and the causal relationship between these two incidents are worthy further exploration. Moreover, surveillance and vigilance for GBS after vaccination are highly recommended.

Introduction: The shear strength deterioration of red-bed rockfill under the dry-wet cycle is the key factor affecting the slope stability of accumulation body. Studying the strength deterioration law and deterioration mechanism of red-bed rockfill can provide theoretical support for slope stability control.Methods: Through the disintegration resistance test of argillaceous siltstone rockfill in Lanping lead-zinc Mine, the disintegration characteristics of red-bed soft rock were studied. The effects of the number of dry-wet cycles on the cohesion, internal friction angle, shear dilation rate and shear modulus of the red-bed rockfill were investigated by using a dry-wet cycle shear tester to conduct shear tests on the reduced scale graded soil material, and the strength deterioration mechanism of the soils was revealed from the perspective of meso-structure.Results: The results showed that argillaceous siltstone was rich in clay minerals and produces strong disintegration when exposed to water. The disintegration process could be divided into three stages: massive disintegration stage, transitional stage and stabilization stage. With the accumulation of dry-wet cycles, the shear dilation rate and shear modulus of the argillaceous siltstone rockfill gradually decrease, and the shear failure developed gradually from strain hardening to shear plastic flow, and the characteristic of weak stress softening occurred. After eight dry-wet cycles, the cohesion and internal friction angle of argillaceous siltstone rockfill materials decreased by 89.87% and 18.94%, respectively, indicating a higher effect on the cohesion than on the internal friction angle.Discussion: The thickening of the bound water between the fine particles on the shear surface, the weakening of the coarse particle attachment, and the increase in the number of directionally arranged fine particles were the main reasons for the continuous deterioration of the soil strength.

Abstract Background Obstructive sleep apnea syndrome (OSAS) is associated with various cardiovascular diseases and has aroused public concern. Early detection for declining myocardial function is of great significance. This study was aimed at noninvasively evaluating the subclinical left ventricular (LV) myocardial dysfunction with LV pressure–strain loop (PSL) in patients with OSAS having normal LV ejection fraction. Methods We enrolled 200 patients with OSAS who visited the Beijing Chaoyang Hospital between February 2021 and December 2021. According to the apnea–hypopnea index (AHI), patients were divided into mild, moderate, and severe groups. The global longitudinal strain (GLS) of the left ventricle was analyzed by two-dimensional speckle tracking echocardiography. The LV PSL was used to assess global work index (GWI), global constructive work (GCW), global waste work (GWW), and global work efficiency (GWE), and comparisons were made among groups. Results GLS was significantly lower in the severe group than in mild and moderate group. GWI, GCW, and GWE were lower in the severe group than in mild and moderate groups. GWW was significantly higher in the severe group than in the mild group. GLS, GWI, and GWE were moderately correlated with AHI (Spearman’s ρ = −0.468, −0.321, and −0.319, respectively; P

Abstract Background Although catheter ablation (CA) is an effective treatment for non-valvular atrial fibrillation (AF), a good many of patients still have a recurrence following post-operation. Prediction of AF recurrence by evaluating left atrial (LA) phase function with speckle tracking echocardiography (STE) may be helpful for risk stratification and clinical management for AF patients. Therefore, the current study aimed to assess the prognostic value of LA strains in non-valvular AF patients after CA. Methods A total of 95 non-valvular AF patients (70.5% paroxysmal AF, 56.8% males, mean age 63.2 ± 9.7 years) were included in this retrospective study between October 2019 and August 2020. Transthoracic echocardiography was performed in all the subjects and STE was used to analyze the LA reservoir strain (LASr), LA conduit strain (LAScd) and LA contractile strain (LASct) during different phases before CA. Patients were followed up with until January 2022. The endpoint was AF recurrence. Results Over a median follow-up period of 26.0 months (interquartile range, 24.7–26.7 months), 26 patients experienced recurrence and 69 stayed in sinus rhythm. Compared with no-recurrence group, maximum volume of LA (LAVmax), minimum volume of LA (LAVmin) and LA volume index (LAVI) were increased in the recurrence group, while LAEF, LASr and LASct were worsened (P

Candida albicans is a ubiquitous fungus that can cause superficial and systemic infections in humans. Neutrophils play a crucial role in controlling C. albicans infections. When C. albicans enters the bloodstream, it tends to get trapped in capillary vessels. However, the behavior of neutrophils in combating capillary-residing fungi has not been fully characterized. In this study, we used transgenic mice and whole mount imaging to investigate the growth of C. albicans and its interaction with innate immune cells in different organs. We observed that C. albicans rapidly grows hyphae within hours of infection. Following intravenous infection, we observed two waves of neutrophil recruitment, both of which significantly contributed to the elimination of the fungi. The first wave of neutrophils was induced by complement activation and could be prevented by C5aR blockade. Interestingly, we discovered that the fungicidal effect in the lungs was independent of adhesion molecules such as Mac-1, LFA-1, and ICAM-1. However, these molecules played a more significant role in the optimal killing of C. albicans in the kidney. Importantly, the initial difference in killing efficiency resulted in significantly reduced survival in knockout mice lacking these adhesion molecules. We identified a second wave of neutrophil recruitment associated with hyphal growth and tissue damage, which was independent of the aforementioned adhesion molecules. Overall, this study elucidates the dual wave of neutrophil recruitment during C. albicans infection and highlights the importance of early fungal clearance for favorable disease outcomes.

We observe systematic profile changes in the visible pulsar of the compact double neutron star system PSR J1946+2052 using observations with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The interpulse of PSR J1946+2052 changed from a single-peak to a double-peak shape from 2018–2021. We attribute this evolution as the result of the relativistic spin precession of the pulsar. With the high sensitivity of FAST, we also measure significant polarization for the first time, allowing us to model this with the precessional rotating vector model. Assuming, to the first order, a circular hollow-cone-like emission beam pattern and taking the validity of general relativity (GR), we derive the binary’s orbital inclination angle ( ${{63}^{\circ }}_{-{3}^{\circ }}^{+{5}^{\circ }}$ ) and pulsar’s spin geometry. The pulsar’s spin vector and the orbital angular momentum vector are found to be only slightly misaligned ( ${{0.}^{\circ }21}_{-{0.}^{\circ }10}^{+{0.}^{\circ }28}$ ). The quoted uncertainties do not reflect the systematic uncertainties introduced by our model assumptions. By simulating future observations of profile and polarization evolution, we estimate that we could constrain the precession rate within a 43% uncertainty in 9 yr. Hence, we suggest that the system’s profile evolution could be combined with precise pulsar timing to test GR in the future.

We observed the nearby radio pulsar B0950+08, which has a 100% duty cycle, using the Five-hundred-meter Aperture Spherical Radio Telescope. We obtained the polarization profile for its entire rotation, which enabled us to investigate its magnetospheric radiation geometry and the sparking pattern of the polar cap. After we excluded part of the profile in which the linear polarization factor is low (≲30%) and potentially contaminated by jumps in position angle, the rest of the swing in polarization position angle fits a classical rotating vector model (RVM) well. The best-fit RVM indicates that the inclination angle, α , and the impact angle, β , of this pulsar, are 100.°5 and −33.°2, respectively, suggesting that the radio emission comes from two poles. We find that, in such RVM geometry, either the annular vacuum gap model or the core vacuum gap model would require that the radio emissions come from a high-altitude magnetosphere with heights from ∼0.25 R _LC to ∼0.56 R _LC , with R _LC being the light cylinder radius. Both the main and interpulses’ sparking points are located away from the magnetic pole, which could relate to the physical conditions on the pulsar surface.

Objectives: The purpose of this study is to evaluate the clinical application value of metagenomic next-generation sequencing (mNGS) in central nervous system (CNS) infections.Methods: Both mNGS and routine examination of cerebrospinal fluid (CSF) samples from patients with CNS infections retrospectively analyzed the efficacy of mNGS in this cohort and were ultimately compared with a clinical diagnosis.Results: A total of 94 cases consistent with CNS infections were included in the analysis. The positive rate for mNGS is 60.6% (57/94), which is significantly higher than 20.2% (19/94; p < 0.01) detected using conventional methods. mNGS detected 21 pathogenic strains that could not be detected by routine testing. Routine tests were positive for two pathogens but negative for mNGS. The sensitivity and specificity of mNGS in the diagnosis of central nervous system infections were 89.5% and 44%, respectively, when compared with traditional tests. At discharge, 20 (21.3%) patients were cured, 55 (58.5%) patients showed improvements, five (5.3%) patients did not recover, and two (2.1%) patients died.Conclusion: mNGS has unique advantages in the diagnosis of central nervous system infections. mNGS tests can be performed when patients are clinically suspected of having a central nervous system infection but no pathogenic evidence.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent malignancy worldwide. Accumulating evidence suggests that persistent HPV infection is closely related to a subset of HNSCC types, and the incidence of human papillomavirus (HPV)-positive HNSCC has been annually increasing in recent decades. Although the carcinogenesis of HPV-positive HNSCC has not been completely elucidated, it has been well confirmed that E6 and E7, the main viral oncoproteins are responsible for the maintenance of malignant transformation, promotion of cell proliferation, and increase in tumor invasion. Moreover, compared with HPV-negative HNSCC, HPV-positive HNSCC shows some special clinical-pathological features, which are possibly related to HPV infection and their specific regulatory mechanisms. Non-coding RNA (ncRNA) is a class of RNA lacking the protein-coding function and playing a critical regulatory role via multiple complex molecular mechanisms. NcRNA is an important regulatory pattern of epigenetic modification, which can exert significant effects on HPV-induced tumorigenesis and progression by deregulating downstream genes. However, the knowledge of ncRNAs is still limited, hence, a better understanding of ncRNAs could provide some insights for exploring the carcinogenesis mechanism and identifying valuable biomarkers in HPV-positive HNSCC. Therefore, in this review, we mainly focused on the expression profile of ncRNAs (including lncRNA, miRNA, and circRNA) and explored their regulatory role in HPV-positive HNSCC, aiming to clarify the regulatory mechanism of ncRNAs and identify valuable biomarkers for HPV-positive HNSCC.

Cancer is a major threat to human health, with high mortality and a low cure rate, continuously challenging public health worldwide. Extensive clinical application of traditional Chinese medicine (TCM) for patients with poor outcomes of radiotherapy and chemotherapy provides a new direction in anticancer therapy. Anticancer mechanisms of the active ingredients in TCM have also been extensively studied in the medical field. As a type of TCM against cancer, Rhizoma Paridis (Chinese name: Chonglou) has important antitumor effects in clinical application. The main active ingredients of Rhizoma Paridis (e.g., total saponins, polyphyllin I, polyphyllin II, polyphyllin VI, and polyphyllin VII) have shown strong antitumor activities in various cancers, such as breast cancer, lung cancer, colorectal cancer, hepatocellular carcinoma (HCC), and gastric cancer. Rhizoma Paridis also has low concentrations of certain other active ingredients with antitumor effects, such as saponins polyphyllin E, polyphyllin H, Paris polyphylla-22, gracillin, and formosanin-C. Many researchers have studied the anticancer mechanism of Rhizoma Paridis and its active ingredients. This review article describes research progress regarding the molecular mechanism and antitumor effects of the active ingredients in Rhizoma Paridis, suggesting that various active ingredients in Rhizoma Paridis may be potentially therapeutic against cancer.

The grassland ecosystems of Mongolia are among the most sensitive to global climate change because of the arid and semiarid climate. As a key source of primary productivity for livestock, the quantification of the carrying capacity in grassland for the winter and early spring period is crucial for sustainable livestock management and livelihoods of herders in Mongolia. In this study, we used remote sensing data and ancillary data to propose a framework to estimate the aboveground biomass(AGB) and the carrying capacity of grassland (GCC) using the Google Earth Engine (GEE) environment. We analysed the spatial and temporal changes in the GCC for the winter-spring period in Mongolia during 2000–2020, and the grassland carrying status index for winter-spring period (GCSIW) was proposed to reflect grassland utilization and livestock carrying status over the past 21 years. Our study demonstrated the effectiveness of AGB and GCC estimation using the Carnegie-Ames-Stanford Approach (CASA) model with the root-to-crown ratio method within the GEE environment. The AGB model validation showed good performance with an R2 of 0.67–0.71 and RMSE of 22.91–28.94 g/m2. Significant increases in AGB and GCC over the 21 years were found in Mongolian grasslands and most provinces. The average GCSIW increased significantly during 2000–2020 in the whole country and all provinces, indicating the increasing stocking density and the overexploited status of grassland in recent years. The multiregression analysis further showed that the dramatic increase in livestock populations contributed 87.5% and 55%-99% to the variations in the GSCIW for the grassland and seventeen provinces, respectively. These results will be useful and helpful in supporting sustainable grassland management and the sustainable livelihoods of herders in Mongolia.

A 4.5 wt.% Si non-oriented electrical steel with a thickness of 0.50 mm was prepared following a conventional process route. Due to the insufficient formability of high-Si steels, this study focuses on the effect of warm rolling temperature on the evolution of microstructure and texture in the hot-rolled sheet after appropriately selected annealing process. The optical microscope (OM) and field emission scanning electron microscope (SEM) with EBSD equipment were utilized to characterize the microstructure evolution during the fabrication process. The results show that the warm rolling temperature significantly impacts the evolution of the microstructure and texture of the 4.5 wt.% Si steel. When rolling at a lower temperature, shear bands appeared within the plate. The shear band vanished as the rolling temperature increased, and obvious delamination can be observed. When further increasing the temperature, the dynamic recrystallization occurred on the surface layer of the plate. The increase of the warm rolling temperature reduced the average grain size after final annealing, and the structural delamination was more obvious. The microstructural characteristics of the warm-rolled sheet affect the subsequent evolution of the texture. Affected by shear bands and delamination, different warm-rolled sheets have different recrystallization textures after final annealing.

Parcel-based crop classification using multi-temporal satellite optical images plays a vital role in precision agriculture. However, optical image sequences may be incomplete due to the occlusion of clouds and shadows. Thus, exploring inherent time-series features to identify crop types from incomplete optical image sequences is a significant challenge. This study developed a contrastive-learning-based framework for time-series feature representation to improve crop classification using incomplete Sentinel-2 image sequences. Central to this method was the combined use of inherent time-series feature representation and machine-learning-based classifications. First, preprocessed multi-temporal Sentinel-2 satellite images were overlaid onto precise farmland parcel maps to generate raw time-series spectral features (with missing values) for each parcel. Second, an enhanced contrastive learning model was established to map the raw time-series spectral features to their inherent feature representation (without missing values). Thirdly, eXtreme Gradient-Boosting-based and Long Short-Term Memory-based classifiers were applied to feature representation to produce crop classification maps. The proposed method is further discussed and validated through parcel-based time-series crop classifications in two study areas (one in Dijon of France and the other in Zhaosu of China) with multi-temporal Sentinel-2 images in comparison to the existing methods. The classification results, demonstrating significant improvements greater than 3% in overall accuracy and 0.04 in F1 scores over comparison methods, indicate the effectiveness of the proposed contrastive-learning-based time-series feature representation for parcel-based crop classification utilizing incomplete Sentinel-2 image sequences.

Inhibiting the tyrosine kinase activity of epidermal growth factor receptor (EGFR) using small-molecule tyrosine kinase inhibitors (TKIs) or monoclonal antibodies is often ineffective in treating cancers harboring wild-type EGFR. Given the fact that EGFR possesses a kinase-independent pro-survival function, more effective inhibition of EGFR-mediated signals is therefore necessary. In this study, we investigated the effects of using a combination of low-dose nimotuzumab and theasinensin A to evaluate whether the inhibitory effect of nimotuzumab on NCI-H441 cancer cells was enhanced. Here, theasinensin A, a novel epigallocatechin-3-gallate (EGCG) derivative, was identified and its potent anticancer activity against wild-type EGFR NSCLC was demonstrated in vitro; the anticancer activity was induced through degradation of EGFR. Mechanistic studies further revealed that theasinensin A bound directly to the EGFR extracellular domain, which decreased interaction with its ligand EGF in combination with nimotuzumab. Theasinensin A significantly promoted EGFR degradation and repressed downstream survival pathways in combination with nimotuzumab. Meanwhile, treatment with theasinensin A and nimotuzumab prevented xenograft growth, whereas the single agents had limited effect. Thus, the combination therapy of theasinensin A with nimotuzumab is a powerful candidate for treatment of wild-type EGFR cancers.

The reciprocating shear mechanical properties and strength deterioration mechanisms of rockfill materials are of great research significance for high-fill slope stability analysis. To study the shear strength characteristics of argillaceous siltstone rockfill materials with different fabric characteristics under reciprocating shear loading, we analyzed the shear strength, hysteresis loop area, damping ratio, shear strength parameter, and shear stiffness of coarse-grained soils with different coarse grain contents using a coarse-grained soil direct shear testing machine capable of reciprocating shear and revealed their strength deterioration mechanism. The test results show that the shear strength of argillaceous siltstone rockfill materials is significantly affected by the coarse grain content and the number of reciprocating shears. Specifically, the shear strength increases with the coarse grain content and decreases with the number of reciprocating shears. The hysteresis loop area is positively correlated with the coarse grain content and negatively correlated with the number of reciprocating shears. The damping ratio is not related to the coarse grain content but tends to decrease with the number of reciprocating shears. Soil cohesion and the internal friction angle increase with the coarse grain content and decrease with the number of reciprocating shears. The soil failure shear stiffness is linearly correlated with the coarse grain content, and the normalized shear stiffness is logarithmically related to the number of reciprocating shears. According to these relationships, an empirical formula for the shear stiffness of argillaceous siltstone rockfill materials under different coarse grain contents and different numbers of reciprocating shears can be established to provide a basis for analyzing rockfill stability.

Although a graph-based semisupervised learning (SSL) approach can utilize limited numbers of labeled samples for hyperspectral image (HSI) classification, it is difficult to use the large amount of pixels in an HSI to construct a large-scale graph. In this article, we therefore propose a superpixel-based graph model for HSI classification, using anchor graph regularization to improve the extraction of local and nonlocal spatial information. To avoid the large-scale graph problem, the superpixel-based graph model constructs a scalable anchor graph using a small number of anchor points for graph-based SSL. The proposed approach consists of three key components: First, local and nonlocal features are extracted from the principal components of an HSI using the locally grouped order pattern and the nonlocal binary pattern approaches. Second, the extracted features are combined with the original spectral information and used as input to an improved simple line iteration clustering method to obtain superpixels, the centers of which are used as anchors in the anchor graph approach. Third, we use superpixel-based graph regularization to model the global information among the superpixels for better predictions of the label of each unlabeled pixel sample. Experimental results demonstrate that the proposed approach outperforms other state-of-the-art semisupervised HSI classification approaches for cases with a limited quantity of labeled samples.

Abstract Influenza A virus infection causes a series of diseases, but the factors associated with disease severity are not fully understood. Disruption of the endothelial glycocalyx contributes to acute lung injury in sepsis, but has not been well studied in H1N1 influenza. We aim to determine whether the plasma glycocalyx components levels are predictive of disease severity in H1N1 influenza. This prospective observational study included 53 patients with influenza A (H1N1) during the influenza season, and 30 healthy controls in our hospital. Patients were grouped by severity and survival. We collected clinical data and blood samples at admission. Inflammatory factors (tumor necrosis factor-α, interleukin-6, interleukin-10) and endothelial glycocalyx components (syndecan-1, hyaluronan, heparan sulfate) were measured. The plasma levels of syndecan-1, hyaluronan, and heparan sulfate were significantly higher in patients with severe influenza A (H1N1) than in mild cases. Syndecan-1 and hyaluronan were positively correlated with disease severity, which was indicated by the APACHE II and SOFA scores and lactate levels, and negatively correlated with albumin levels. At a cutoff point ≥ 173.9 ng/mL, syndecan-1 had a 81.3% sensitivity and 70.3% specificity for predicting of 28-day mortality. Kaplan–Meier analysis demonstrated a strong association between syndecan-1 levels and 28-day mortality (log-rank 11.04, P = 0.001). Elevated plasma levels of syndecan-1 has a potential role in systemic organ dysfunction and may be indicative of disease severity in patients with influenza A (H1N1).

A combination of Floquet engineering and higher-order topological insulators has been lately only theoretically proposed. Here the authors experimentally realize an acoustic waveguides array to demonstrate a Floquet higherorder topological insulator extending its band topology from first order to higher order.

This paper presents a method to identify the damages in frame structures with slender beams. This method adjusts the parameters of the structure to match the analytical and the measured displacements. The effect of transverse shear deformation on the nodal analytical displacement is analyzed, and the parameter identification of frame structures with slender beams is performed. The results demonstrate that parameter-identification accuracy can be considerably improved by considering the transverse shear deformation in the frame structure with slender beams. The proposed method can accurately identify the damages in frame structures with slender beams using displacement measurements.

This research was aimed to investigate the magnetic resonance imaging (MRI) features of brain structure and neuroendocrine levels in patients with first-episode schizophrenia. 25 hospitalized patients with first-episode schizophrenia were selected as the observation group, while 25 healthy people were selected as the control group. All the objects underwent MRI examination, and the images as well as gray matter density of the original image data were analyzed under voxel-based morphometry (VBM). The cortisol and prolactin in the observation group were detected, and the levels were compared. The Pearson correlation analysis was adopted to analyze the correlation between cortisol and prolactin levels and the total score of the Positive and Negative Syndrome Scale (PANSS). The results showed that the gray matter volume of the precentral gyrus, superior frontal gyrus, middle frontal gyrus, inferior frontal gyrus, postcentral gyrus, inferior parietal lobule, superior parietal lobule, and anterior cingulate cortex of the observation group decreased, while the volume of cerebellar gray matter increased. The levels of cortisol and prolactin in the observation group (387.54 ± 117.69 μg/L and 804.16 ± 267.13 μIU/mL, respectively) were significantly higher than those in the control group (138.46 ± 62.47 μg/L and 397.54 ± 203.82 μIU/mL, respectively), and the differences were statistically significant (P