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Abstract Objective Relational job characteristics include perceived social worth and perceived social influence. Good relational job characteristics mean that nurses have high prosocial behavior. The purpose of this study was to explore the potential profile of nurses’ relational job characteristics, influencing factors and their differences in turnover intention and subjective well-being, thus finding the most suitable clinical relationship job characteristics. Methods A cross-sectional survey was conducted among 1013 clinical nurses using the general demographic data questionnaire, Relational Job Characteristics scale, Turnover Intention Questionnaire and Campbell index of well-being. A latent profile analysis was performed to explore relational job characteristics latent profiles. Multinomial logistic regression analysis was conducted to examine the predictors of profile membership, and a one-way analysis of variance was applied to compare the turnover intention and subjective well-being in each latent profile. Results Five latent profiles were identified and labeled ‘High prosocial job characteristics’ profile (20.7%), ‘Moderate prosocial job characteristics’ profile (41.7%), ‘High social worth-low social impact perceived’ profile (6.3%), ‘Low social worth‐high social impact perceived’ profile (18.8%) and ‘Low prosocial job characteristics’ profile (12.5%). Factors affecting the different types of nurse relationship job characteristics include age, marital status, hospital department, nursing years, professional title and hospital position. Among them, chief nurse, nurses with more than 20 years of nursing experience and obstetrics and gynecology nurses were more likely to be ‘high prosocial job characteristics’ profile. The turnover intention of nurses in ‘high prosocial job characteristics’ profile was significantly lower than that of other profiles, and their subjective well-being was significantly higher than that of other profiles. Conclusion Improving nurses’ perception of social worth and social impact on clinical work can improve nurses’ prosocial behavior and subjective well-being, and reduce their turnover intention. Nursing managers or policy makers can formulate targeted intervention measures according to the influencing factors of potential profiles.

Abstract Background Glioma is the most common primary brain tumor with high mortality and disability rates. Recent studies have highlighted the significant prognostic consequences of subtyping molecular pathological markers using tumor samples, such as IDH, 1p/19q, and TERT. However, the relative importance of individual markers or marker combinations in affecting patient survival remains unclear. Moreover, the high cost and reliance on postoperative tumor samples hinder the widespread use of these molecular markers in clinical practice, particularly during the preoperative period. We aim to identify the most prominent molecular biomarker combination that affects patient survival and develop a preoperative MRI-based predictive model and clinical scoring system for this combination. Methods A cohort dataset of 2,879 patients was compiled for survival risk stratification. In a subset of 238 patients, recursive partitioning analysis (RPA) was applied to create a survival subgroup framework based on molecular markers. We then collected MRI data and applied Visually Accessible Rembrandt Images (VASARI) features to construct predictive models and clinical scoring systems. Results The RPA delineated four survival groups primarily defined by the status of IDH and TERT mutations. Predictive models incorporating VASARI features and clinical data achieved AUC values of 0.85 for IDH and 0.82 for TERT mutations. Nomogram-based scoring systems were also formulated to facilitate clinical application. Conclusions The combination of IDH-TERT mutation status alone can identify the most distinct survival differences in glioma patients. The predictive model based on preoperative MRI features, supported by clinical assessments, offers a reliable method for early molecular mutation prediction and constitutes a valuable scoring tool for clinicians in guiding treatment strategies.

Abstract The origin of energetic charged particles in universe remains an unresolved issue. Astronomical observations combined with simulations have provided insights into particle acceleration mechanisms, including magnetic reconnection acceleration, shock acceleration, and stochastic acceleration. Recent experiments have also confirmed that electrons can be accelerated through processes such as magnetic reconnection and collisionless shock formation. However, laboratory identifying stochastic acceleration as a feasible mechanism is still a challenge, particularly in the creation of collision-free turbulent plasmas. Here, we present experimental results demonstrating kinetic turbulence with a typical spectrum k −2.9 originating from Weibel instability. Energetic electrons exhibiting a power-law distribution are clearly observed. Simulations further reveal that thermal electrons undergo stochastic acceleration through collisions with multiple magnetic islands-like structures within the turbulent region. This study sheds light on a critical transition period during supernova explosion, where kinetic turbulences originating from Weibel instability emerge prior to collisionless shock formation. Our results suggest that electrons undergo stochastic acceleration during this transition phase.

Abstract Background Mounting evidence shows that tumor-derived extracellular vesicles (EVs) are critical constituents in the tumor microenvironment. The composition and function of EVs often change during cancer progression. However, it remains less clear how cancer cells modulate their own EV biogenesis to promote tumor development. The release of EVs is closely linked to the endolysosome system residing within the cell. The current study aims to decipher the role of endosomal protein DENND10 in cancer development. Results Bioinformatics data mining showed that DENND10 expression is significantly associated with poor prognosis in multiple cancer types and up-regulated in metastatic breast cancer cell lines. DENND10 knockout (DENND10-KO) in breast cancer cells led to defective EV biogenesis due to impaired endolysosomal trafficking. Intriguingly, DENND10-KO cells exhibited reductions in cell spreading, migration, invasion, and metastatic potential in vivo. These deficiencies in cell motility were associated with compromised cytoskeleton organization. Importantly, wild-type conditioned medium or EVs restored the migratory ability and cytoskeletal organization of DENND10-KO cells. Global proteomic profiling revealed that DENND10 depletion led to a distinct EV compositional landscape with remodeled profiles of extracellular matrix (ECM) and adhesion molecules. Consistently, exogenous application of ECM molecules rescued the spreading and migration of DENND10-KO cells. Conclusions In summary, our study unveiled DENND10 as an intrinsic regulator of cell migration that modifies the tumor microenvironment through autocrine EV release, which could be exploited for developing targeted therapies for tumor metastasis.

Galvanized steel plates with Zn–Al–Mg coatings are extensively utilized due to their exceptional corrosion resistance. This study, focusing on the cracking behavior of coatings with varying Mg/Al ratios, was conducted using in-situ tensile tests on different samples. The influence of the Mg/Al ratio on the crack resistance of the sample coatings was systematically summarized. To elucidate this point, five types of Zn–Al–Mg coatings with varying Mg/Al ratios were prepared using the same galvanizing process and tensile testing performed using a scanning electron microscope equipped with in-situ tensile capabilities. Macroscopic digital image statistical techniques were employed to quantify the extent of coating cracking, demonstrating the impact of the Mg/Al ratio on the coatings' crack resistance. The findings suggest that an increase in the Mg/Al ratio deteriorates the crack resistance of the coating, while enhancing its hardness. Moreover, this research offers a novel perspective in evaluating the crack resistance of coatings by comparing the effects of different Mg/Al ratios.

Abstract Background Associations between metabolic status and metabolic changes with the risk of cardiovascular outcomes have been reported. However, the role of genetic susceptibility underlying these associations remains unexplored. We aimed to examine how metabolic status, metabolic transitions, and genetic susceptibility collectively impact cardiovascular outcomes and all-cause mortality across diverse body mass index (BMI) categories. Methods In our analysis of the UK Biobank, we included a total of 481,576 participants (mean age: 56.55; male: 45.9%) at baseline. Metabolically healthy (MH) status was defined by the presence of

Abstract This study aimed to develop and internally validate a nomogram model for assessing the risk of intraoperative hypothermia in patients undergoing video-assisted thoracoscopic (VATS) lobectomy. This study is a retrospective study. A total of 530 patients who undergoing VATS lobectomy from January 2022 to December 2023 in a tertiary hospital in Wuhan were selected. Patients were divided into hypothermia group (n = 346) and non-hypothermia group (n = 184) according to whether hypothermia occurred during the operation. Lasso regression was used to screen the independent variables. Logistic regression was used to analyze the risk factors of hypothermia during operation, and a nomogram model was established. Bootstrap method was used to internally verify the nomogram model. Receiver operating characteristic (ROC) curve was used to evaluate the discrimination of the model. Calibration curve and Hosmer Lemeshow test were used to evaluate the accuracy of the model. Decision curve analysis (DCA) was used to evaluate the clinical utility of the model. Intraoperative hypothermia occurred in 346 of 530 patients undergoing VATS lobectomy (65.28%). Logistic regression analysis showed that age, serum total bilirubin, inhaled desflurane, anesthesia duration, intraoperative infusion volume, intraoperative blood loss and body mass index were risk factors for intraoperative hypothermia in patients undergoing VATS lobectomy (P

Abstract The three-dimensional genome structure organized by CTCF is required for development. Clinically identified mutations in CTCF have been linked to adverse developmental outcomes. Nevertheless, the underlying mechanism remains elusive. In this investigation, we explore the regulatory roles of a clinically relevant R567W point mutation, located within the 11th zinc finger of CTCF, by introducing this mutation into both murine models and human embryonic stem cell-derived cortical organoid models. Mice with homozygous CTCFR567W mutation exhibit growth impediments, resulting in postnatal mortality, and deviations in brain, heart, and lung development at the pathological and single-cell transcriptome levels. This mutation induces premature stem-like cell exhaustion, accelerates the maturation of GABAergic neurons, and disrupts neurodevelopmental and synaptic pathways. Additionally, it specifically hinders CTCF binding to peripheral motifs upstream to the core consensus site, causing alterations in local chromatin structure and gene expression, particularly at the clustered protocadherin locus. Comparative analysis using human cortical organoids mirrors the consequences induced by this mutation. In summary, this study elucidates the influence of the CTCFR567W mutation on human neurodevelopmental disorders, paving the way for potential therapeutic interventions.

Abstract Background Tracheal tube cuff pressure will increase after pneumoperitoneum when the cuff is inflated with air, high pressure can cause tracheal mucosal damage. This prospective trial aimed to assess if inflating with normal saline or lidocaine can prevent increase of tracheal tube cuff pressure and tracheal mucosal damage in laparoscopic surgeries with general anesthesia. Whether changes of tracheal tube cuff transverse diameter (CD) can predict changes of tracheal tube cuff pressure. Methods Ninety patients scheduled for laparoscopic resection of colorectal neoplasms under general anesthesia were randomly assigned to groups air (A), saline (S) or lidocaine (L). Endotracheal tube cuff was inflated with room-temperature air in group A (n = 30), normal saline in group S (n = 30), 2% lidocaine hydrochloride injection in group L (n = 30). After intubation, tracheal tube cuff pressure was monitored by a calibrated pressure transducers, cuff pressure was adjusted to 25 cmH2O (T0.5). Tracheal tube cuff pressure at 15 min after pneumoperitoneum (T1) and 15 min after exsufflation (T2) were accessed. CD were measured by ultrasound at T0.5 and T1, the ability of ΔCD (T1-0.5) to predict cuff pressure was accessed. Tracheal mucous injury at the end of surgery were also recorded. Results Tracheal tube cuff pressure had no significant difference among the three groups at T1 and T2. ΔCD had prediction value (AUC: 0.92 [95% CI: 0.81–1.02]; sensitivity: 0.99; specificity: 0.82) for cuff pressure. Tracheal mucous injury at the end of surgery were 0 (0, 1.0) in group A, 0 (0, 1.0) in group S, 0 (0, 0) in group L (p = 0.02, group L was lower than group A and S, p = 0.03 and p = 0.04). Conclusions Compared to inflation with air, normal saline and 2% lidocaine cannot ameliorate the increase of tracheal tube cuff pressure during the pneumoperitoneum period under general anesthesia, but lidocaine can decrease postoperative tracheal mucosa injury. ΔCD measured by ultrasound is a predictor for changes of tracheal tube cuff pressure. Trial registration Chinese Clinical Trial Registry, identifier: ChiCTR2100054089, Date: 08/12/2021.

Abstract Background Previous research on ABO blood types and stroke has been controversial, predominantly suggesting heightened risk of stroke in non-O blood types. Nonetheless, investigations into the correlation and underlying mechanisms between ABO blood groups and stroke subtypes, especially within Chinese cohorts, remain limited. Methods The ABO blood types of 9,542 ischaemic stroke (IS) patients were inferred using two ABO gene loci (c.261G > del; c.802G > A). The healthy population was derived from the 1000 Genomes Project. Patients were classified by the causative classification system (CCS). Volcano plot and gene ontology (GO) analysis were employed to explore protein differential expression among blood types. Additionally, HT29 and SW480 cell lines with downregulated ABO expression were generated to evaluate its impact on cholesterol uptake and efflux. Results A greater proportion of stroke patients had non-O blood types (70.46%) than did healthy individuals (61.54%). Notable differences in blood type distributions were observed among stroke subtypes, with non-O blood type patients mainly classified as having large artery atherosclerosis (LAA). Clinical baseline characteristics, such as the low-density lipoprotein cholesterol level, activated partial thromboplastin time and thrombin time, varied significantly among blood types. A volcano plot revealed 17 upregulated and 42 downregulated proteins in the O blood type. GO term analysis indicated that downregulated proteins were primarily associated with lipid metabolism pathways. In vitro experiments revealed that reducing ABO gene expression decreased cholesterol uptake and increased cholesterol efflux. Conclusions This study revealed that the non-O blood type increased the risk of LAA stroke through cholesterol metabolism.

Martian dust storms have a profound impact on atmospheric structure, pose multiple risks to Mars landers, and greatly affect the accuracy of sounders. This makes the accurate short-term prediction of dust storms extremely important for future Mars exploration missions. However, traditional statistical analyses fail to accurately capture the variation patterns of dust. Here, we show that the ConvGRU-Seq2Seq model can fully utilize the data to achieve a 12-h forecast of global dust. We found that considering multiple interconnected meteorological elements, particularly the wind field, and accounting for seasonal variations can enhance forecast accuracy. The addition of the Seq2Seq structure reduced the mean squared error (MSE) by 85.3% and the mean absolute error (MAE) by 75.07%, compared with the original ConvGRU model. Among the six models compared, the ConvGRU-Seq2Seq model exhibited the best test performance, with MSE, MAE, and R2 values of 8.73×10−4, 13.48×10−3, and 98.12×10−2, respectively. The model exhibited stable and reliable prediction performance and a more concentrated and accurate spatial distribution of errors. We achieved a rapidly changing dust activity forecast within 12 h with

This paper describes a new approach to control stall and surge instabilities in the compressor system by using of finite time backstepping-based adaptive sliding mode method. The most important innovation of this study is to provide a finite time adaptive control method to simultaneously prevent the stall and surge instabilities in a compressor system in the presence of disturbance and uncertainty in the compressor characteristic curve as well as the throttle valve. The disturbance and uncertainty issues are covered by a robust sliding mode control and the gain coefficients of this controller as well as the estimation of uncertain terms are obtained by using the adaptive method. The Lyapunov stability criterion is used to evaluate the finite-time stability of the closed-loop system. The performance of the proposed method is compared with other literature methods through simulation in Matlab. The simulation results show that the proposed controller is better than the existing methods in terms of surge preventing and robustness against uncertainty and disturbance.

Environmental barrier coatings (EBCs) with thermomechanical robustness against calcium–magnesium–aluminum–silicate (CMAS) deposits are in high demand. The aim of this work was to clarify the influence of Sc3+ on the crystallization behavior of Yb-based coatings against CMAS deposits. The reaction products of solid solutions with compositions traversing the Sc2O3–Yb2O3 system indicate that Sc3+ tends to form [BO6] coordination polyhedra in the crystal structure to promote the formation of garnet and diopside, while Yb3+ occupies 7-, 8-, and 9-coordinate sites to crystallize apatite and silicocarnotite. The transformation of crystalline products from apatite/silicocarnotite to garnet/diopside greatly improves the efficiency of CMAS melt consumption and facilitates the prevention of its further penetration and corrosion. Based on the commonality of cation occupancy in crystallography, an A(CaO+YbO1.5)–B(ScO1.5+MgO+AlO1.5)–T(SiO2) pseudoternary phase diagram is established, which has great potential for describing phase equilibrium in coating-deposit systems and can provide guidance for the compositional design of corrosion-resistant coatings.

Abstract Objectives This study investigated the effectiveness of a deep convolutional neural network (CNN) in diagnosing and staging caries lesions in quantitative light-induced fluorescence (QLF) images taken by a self-manufactured handheld device. Methods A small toothbrush-like device consisting of a 400 nm UV light-emitting lamp with a 470 nm filter was manufactured for intraoral imaging. A total of 133 cases with 9,478 QLF images of teeth were included for caries lesion evaluation using a CNN model. The database was divided into development, validation, and testing cohorts at a 7:2:1 ratio. The accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) were calculated for model performance. Results The overall caries prevalence was 19.59%. The CNN model achieved an AUC of 0.88, an accuracy of 0.88, a specificity of 0.94, and a sensitivity of 0.64 in the validation cohort. They achieved an overall accuracy of 0.92, a sensitivity of 0.95 and a specificity of 0.55 in the testing cohort. The model can distinguish different stages of caries well, with the best performance in detecting deep caries followed by intermediate and superficial lesions. Conclusions Caries lesions have typical characteristics in QLF images and can be detected by CNNs. A QLF-based device with CNNs can assist in caries screening in the clinic or at home. Trial registration The clinical trial was registered in the Chinese Clinical Trial Registry (No. ChiCTR2300073487, Date: 12/07/2023).

Virtual synchronous generators (VSGs) are widely introduced to the renewable power generation, the variable-speed pumped storage units, and so on, as a promising grid-forming solution. It is noted that VSGs can provide virtual inertia for frequency support, but the larger inertia would worsen the synchronization stability, referring to keeping synchronization with the grid during voltage dips. Thus, this paper presents a transient damping method of VSGs for enhancing the synchronization stability during voltage dips. It is revealed that the loss of synchronization (LOS) of VSGs always accompanies with the positive frequency deviation and the damping is the key factor to remove LOS when the equilibrium point exists. In order to enhance synchronization stability during voltage dips, the transient damping is proposed, which is generated by the frequency deviation in active power loop. Additionally, the proposed method can realize seamless switching between normal state and grid fault. Moreover, detailed control design for transient damping gain is given to ensure the synchronization stability under different inertia requirements during voltage dips. Finally, the experimental results are presented to validate the analysis and the effectiveness of the improved transient damping method.

The problem of surface deformation caused by coal mining is acute and usually lasts for a long time. During coal mining, the movement of the overlying strata has a broad range of influences, which may cause surface deformation, surface cracking, and damage to structures (buildings). However, continuous deformation monitoring data are often scarce in practice, making it challenging to predict the surface deformation caused by coal mining. In this context, this paper takes Sichuan’s Guanshan coalfield as the research object and proposes a comprehensive method integrating interferometric synthetic aperture radar (InSAR) technology, the FLAC3D finite difference software, and the probability integral method to predict the surface deformation caused by mining a thin seam of coal. The results show that the trend of surface deformation estimated by the numerical simulation agrees well with the results of InSAR data and the probability integral model when using InSAR historical deformation data to invert the parameters of rock mechanics in the numerical simulation, which is beneficial to improving the reliability of the simulation results. The calculations of the probability integral method are close to the predictions of the FLAC3D numerical simulation, and a settlement deformation of 0.68 ​m is expected to occur in the Guanshan coalfield area. The comprehensive prediction method proposed in this paper effectively enhances the accuracy of surface deformation prediction under the action of mining and can provide a reference for predicting the surface subsidence of similar coal mines.

Abstract In order to provide suitable material selection for such fluid–solid coupling model tests, orthogonal experimental studies were conducted using iron concentrate powder and barite powder as aggregates, cement as cementitious materials, and gypsum and clay as modifiers. This research showed: (1) The ATC plays a dominant role in controlling the strength indexes and water absorption of the material, and these indexes show a significant decrease with the increase of the bone adhesive ratio. For each level of ATC increase, the compressive strength decreases by 0.2 MPa, the elastic modulus decreases by 10–20 MPa, and the cohesion decreases by 25–45 kPa. (2) Mixing gypsum and cement cannot jointly promote strength growth. (3) With the increase of GTC, the water absorption rate of the material increases, while the softening coefficient and permeability coefficient decrease obviously. Gypsum, which accounts for 4–16% of cement content, can be suitable for studying the hydraulic properties of similar materials for most sedimentary rock. Based on Weibull statistical damage theory, a damage constitutive model for the entire process of rock triaxial compression under the combined action of rainwater infiltration and load was established. Due to the influence of internal pores, the experimental and theoretical results have a certain deviation, the higher the confining pressure, the more obvious the deviation. In addition, the higher the rock strength, the less obvious the deviation caused by pores. This damage model can better describe the progressive failure process of rocks after rainwater infiltration, and can provide theoretical reference for the study of slope stability caused by rainwater infiltration.

Abstract Objectives The clinical decision-making regarding choosing surgery alone (SA) or surgery followed by postoperative adjuvant chemotherapy (SPOCT) in esophageal squamous cell carcinoma (ESCC) remains controversial. We aim to propose a pre-therapy PET/CT image-based deep learning approach to improve the survival benefit and clinical management of ESCC patients. Methods This retrospective multicenter study included 837 ESCC patients from three institutions. Prognostic biomarkers integrating six networks were developed to build an ESCC prognosis (ESCCPro) model and predict the survival probability of ESCC patients treated with SA and SPOCT. Patients who did not undergo surgical resection were in a control group. Overall survival (OS) was the primary end-point event. The expected improvement in survival prognosis with the application of ESCCPro to assign treatment protocols was estimated by comparing the survival of patients in each subgroup. Seven clinicians with varying experience evaluated how ESCCPro performed in assisting clinical decision-making. Results In this retrospective multicenter study, patients receiving SA had a median OS 9.2 months longer than controls. No significant differences in survival were found between SA patients with predicted poor outcomes and the controls (p > 0.05). It was estimated that if ESCCPro was used to determine SA and SPOCT eligibility, the median OS in the ESCCPro-recommended SA group and SPOCT group would have been 15.3 months and 24.9 months longer, respectively. In addition, ESCCPro also significantly improved prognosis accuracy, certainty, and the efficiency of clinical experts. Conclusion ESCCPro assistance improved the survival benefit of ESCC patients and the clinical decision-making among the two treatment approaches. Critical relevance statement The ESCCPro model for treatment decision-making is promising to improve overall survival in ESCC patients undergoing surgical resection and patients undergoing surgery followed by postoperative adjuvant chemotherapy. Key Points ESCC is associated with a poor prognosis and unclear ideal treatments. ESCCPro predicts the survival of patients with ESCC and the expected benefit from SA. ESCCPro improves clinicians’ stratification of patients’ prognoses. Graphical Abstract

Abstract Background Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease. Its pathogenesis is not fully understood, and early diagnosis is challenging owing to the lack of effective biomarkers. This study aimed to analyze different samples to identify potential biomarkers and therapeutic targets. Methods Microarray datasets of RA, osteoarthritis (OA), and healthy control (HC) were downloaded from the Gene Expression Omnibus database. R software was used to identify differentially expressed genes (DEGs), which were visualized using volcano and heat maps. Venn diagrams, principal component analysis, gene set enrichment analysis, gene ontology, and Kyoto Encyclopedia of genes and genomes were used to analyze the data. A protein–protein interaction network was constructed, and synovial tissues from patients with RA and OA were collected for verification using the collagen‐induced arthritis mouse model. Results More DEGs were found in synovial tissues than in peripheral blood mononuclear cells or fibroblast‐like synoviocytes. Principal component analysis revealed significant differences between the RA and OA samples, highlighting the unique advantages of synovial tissue. Enrichment analysis revealed that metabolic and cytokine signaling pathways play crucial roles in the development of RA. Further analysis of the four synovial datasets identified 54 DEGs, of which signaling lymphocytic activation molecule family (SLAMF) 8 was identified as the key molecule. SLAMF8 levels were increased in the synovial tissue of patients with RA compared to those of patients with OA (0.38 ± 0.19 vs. 12.40 ± 1.66), and SLAMF8 levels were similarly elevated in collagen‐induced arthritis model mice compared with those in the healthy mice (1.13 ± 0.47 vs. 9.05 ± 2.52). Conclusions This study established the unique advantages of synovial tissue for RA research and identified metabolic and cytokine signaling pathways as important for RA development. Thus, SLAMF8 may be a potential therapeutic target for RA.

Abstract To investigate the significant deformation of the surrounding rock within the dynamic pressure zone of the gateroad, this study utilized the tailgate of the 1506 longwall face in Anyang Coal Mine as the engineering context. A combined approach of field measurement and numerical analysis was employed to explore the deformation and failure mechanisms of the surrounding rock under dynamic pressure. The findings indicate that before the exploitation of the 1506 longwall face, there was a notable reduction in stress across the floor and immediate roof, with minimal stress concentration observed in the coal pillar and the entity rib side. The plastic zone surrounding the tailgate was limited, suggesting a high degree of stability in the entry's surrounding rock. However, during the extraction of the 1506 longwall face, the tailgate, extending 60 m ahead of the working face, was subjected to dynamic pressure, leading to a marked increase in stress within the floor, coal pillar, and immediate roof. Stress concentration was more pronounced on the entity rib side than on the pillar rib side. This resulted in significant fissuring and severe deformation of the entry's surrounding rock. The primary failure mechanism involved damage to both the roof and floor corners, with the severity of damage escalating alongside the stress in the surrounding rock. This culminated in the failure of roof corner bolts and anchor cables, thereby compromising the stability of the entry within the dynamic pressure zone.

Bladder cancer (BC) is the tenth most common malignancy globally. Urothelial carcinoma (UC) is a major type of BC, and advanced UC (aUC) is associated with poor clinical outcomes and limited survival rates. Current options for aUC treatment mainly include chemotherapy and immunotherapy. These options have moderate efficacy and modest impact on overall survival and thus highlight the need for novel therapeutic approaches. aUC patients harbor a high tumor mutation burden and abundant molecular alterations, which are the basis for targeted therapies. Erdafitinib is currently the only Food and Drug Administration (FDA)-approved targeted therapy for aUC. Many potential targeted therapeutics aiming at other molecular alterations are under investigation. This review summarizes the current understanding of molecular alterations associated with aUC targeted therapy. It also comprehensively discusses the related interventions for treatment in clinical research and the potential of using novel targeted drugs in combination therapy.

Abstract Background Soybean mosaic disease caused by soybean mosaic virus (SMV) is one of the most devastating and widespread diseases in soybean producing areas worldwide. The WRKY transcription factors (TFs) are widely involved in plant development and stress responses. However, the roles of the GmWRKY TFs in resistance to SMV are largely unclear. Results Here, 185 GmWRKYs were characterized in soybean (Glycine max), among which 60 GmWRKY genes were differentially expressed during SMV infection according to the transcriptome data. The transcriptome data and RT-qPCR results showed that the expression of GmWRKY164 decreased after imidazole treatment and had higher expression levels in the incompatible combination between soybean cultivar variety Jidou 7 and SMV strain N3. Remarkably, the silencing of GmWRKY164 reduced callose deposition and enhanced virus spread during SMV infection. In addition, the transcript levels of the GmGSL7c were dramatically lower upon the silencing of GmWRKY164. Furthermore, EMSA and ChIP-qPCR revealed that GmWRKY164 can directly bind to the promoter of GmGSL7c, which contains the W-box element. Conclusion Our findings suggest that GmWRKY164 plays a positive role in resistance to SMV infection by regulating the expression of GmGSL7c, resulting in the deposition of callose and the inhibition of viral movement, which provides guidance for future studies in understanding virus-resistance mechanisms in soybean.

Abstract Objectives To investigate whether reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with deep learning reconstruction (DLR) can improve the accuracy of evaluating muscle invasion using VI-RADS. Methods Eighty-six bladder cancer participants who were evaluated by conventional full field-of-view (fFOV) DWI, standard rFOV (rFOVSTA) DWI, and fast rFOV with DLR (rFOVDLR) DWI were included in this prospective study. Tumors were categorized according to the vesical imaging reporting and data system (VI-RADS). Qualitative image quality scoring, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC value were evaluated. Friedman test with post hoc test revealed the difference across the three DWIs. Receiver operating characteristic analysis was performed to calculate the areas under the curve (AUCs). Results The AUC of the rFOVSTA DWI and rFOVDLR DWI were higher than that of fFOV DWI. rFOVDLR DWI reduced the acquisition time from 5:02 min to 3:25 min, and showed higher scores in overall image quality with higher CNR and SNR, compared to rFOVSTA DWI (p 0.05). Conclusions rFOV DWI with DLR can improve the diagnostic accuracy of fFOV DWI for evaluating muscle invasion. Applying DLR to rFOV DWI reduced the acquisition time and improved overall image quality while maintaining ADC value and diagnostic accuracy. Critical relevance statement The diagnostic performance and image quality of full field-of-view DWI, reduced field-of-view (rFOV) DWI with and without DLR were compared. DLR would benefit the wide clinical application of rFOV DWI by reducing the acquisition time and improving the image quality. Key Points Deep learning reconstruction (DLR) can reduce scan time and improve image quality. Reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with DLR showed better diagnostic performances than full field-of-view DWI. There was no difference of diagnostic accuracy between rFOV DWI with DLR and standard rFOV DWI. Graphical Abstract

Abstract Deuterium labeling compounds play a crucial role in organic and pharmaceutical chemistry. The synthesis of such compounds typically involves deuterated building blocks, allowing for the incorporation of deuterium atoms and functional groups into a target molecule in a single step. Unfortunately, the limited availability of synthetic approaches to deuterated synthons has impeded progress in this field. Here, we present an approach utilizing alkyl-substituted thianthrenium salts that efficiently and selectively introduce deuterium at the α position of alkyl chains through a pH-dependent HIE process, using D2O as the deuterium source. The resulting α-deuterated alkyl thianthrenium salts, which bear two deuterium atoms, exhibit excellent selectivity and deuterium incorporation in electrophilic substitution reactions. Through in situ formation of isotopically labelled alkyl halides, these thianthrenium salts demonstrate excellent compatibility in a series of metallaphotoredox cross-electrophile coupling with (hetero)aryl, alkenyl, alkyl bromides, and other alkyl thianthrenium salts. Our technique allows for a wide range of substrates, high deuterium incorporation, and precise control over the site of deuterium insertion within a molecule such as the benzyl position, allylic position, or any alkyl chain in between, as well as neighboring heteroatoms. This makes it invaluable for synthesizing various deuterium-labeled compounds, especially those with pharmaceutical significance.

Abstract The herd immunity against SARS-CoV-2 is continuously consolidated across the world during the ongoing pandemic. However, the potential function of the nonconserved epitopes in the reverse preexisting cross-reactivity induced by SARS-CoV-2 to other human coronaviruses is not well explored. In our research, we assessed T cell responses to both conserved and nonconserved peptides shared by SARS-CoV-2 and SARS-CoV, identifying cross-reactive CD8+ T cell epitopes using enzyme-linked immunospot and intracellular cytokine staining assays. Then, in vitro refolding and circular dichroism were performed to evaluate the thermal stability of the HLA/peptide complexes. Lastly, single-cell T cell receptor reservoir was analyzed based on tetramer staining. Here, we discovered that cross-reactive T cells targeting SARS-CoV were present in individuals who had recovered from COVID-19, and identified SARS-CoV-2 CD8+ T cell epitopes spanning the major structural antigens. T cell responses induced by the nonconserved peptides between SARS-CoV-2 and SARS-CoV were higher and played a dominant role in the cross-reactivity in COVID-19 convalescents. Cross-T cell reactivity was also observed within the identified series of CD8+ T cell epitopes. For representative immunodominant peptide pairs, although the HLA binding capacities for peptides from SARS-CoV-2 and SARS-CoV were similar, the TCR repertoires recognizing these peptides were distinct. Our results could provide beneficial information for the development of peptide-based universal vaccines against coronaviruses.

Abstract Background Obesity is characterized by excessive fat accumulation in the body. Physical activity (PA) is an effective intervention to combat obesity, but the effectiveness of different PA patterns on controlling obesity is unclear. Lipid accumulation product (LAP), derived from waist circumference and triglycerides, is a novel indicator for obesity evaluation. However, the association between PA patterns (i.e., weekend warriors and regularly active) and LAP remains unexplored. This study aims to elucidate the relationship between PA patterns and LAP in US adult population. Methods Adult individuals with complete data on LAP, PA patterns, and other covariates from the National Health and Nutrition Examination Survey (NHANES) database (2007–2018) were included in this study. Multivariate linear regression models were utilized to explore the association between PA patterns and LAP. Subgroup analyses, interaction tests, restricted cubic spline (RCS) regression analyses, and threshold and saturation effect analyses were also performed to investigate the stability and nonlinearity of PA-LAP association, respectively. Results A total of 11,212 participants were included in this study. After adjusting for all potential covariates, being regularly active (RA) (β=-8.85, P

Abstract The ‘Red Fuji’ apple (Malus domestica), is one of the most important and popular economic crops worldwide in the fruit industry. Using PacBio HiFi long reads and Hi-C reads, we assembled a high-quality haplotype-resolved genome of ‘Red Fuji’, with sizes of 668.7 and 668.8 Mb, and N50 sizes of 34.1 and 31.4 Mb. About 97.2% of sequences were anchored in 34 chromosomes. We annotated both haploid genomes, identifying a total of 95,439 protein-coding genes in the two haplotype genomes, with 98% functional annotation. The haplotype-resolved genome of ‘Red Fuji’ apple stands as a precise benchmark for an array of analyses, such as comparative genomics, transcriptomics, and allelic expression studies. This comprehensive resource is paramount in unraveling variations in allelic expression, advancing quality improvements, and refining breeding efforts.

Abstract Background Oral nutritional supplements are one of the preferred methods of nutritional support for postoperative patients. This study aims to investigate the current status of oral nutritional supplements compliance in postoperative patients with digestive tract tumors and its influencing factors. Methods Convenience sampling was employed to select 242 patients who underwent surgery for digestive tract tumors at a tertiary hospital in Shanghai from October 2022 to July 2023 as the study subjects. Data following a normal distribution were analyzed using independent sample t-tests, ANOVA single-factor analysis, Pearson correlation analysis, and multiple linear regression analysis to determine the factors influencing compliance with oral nutritional supplements. Results A total of 252 questionnaires were distributed, with 10 invalid questionnaires excluded, resulting in an effective questionnaire rate of 96.03%. The compliance score for oral nutritional supplements in postoperative patients with digestive tract tumors was (2.40 ± 1.45), General Self-efficacy Scale (GSES) score was (24.72 ± 4.86), Multidimensional Scale of Perceived Social Support Scale (MSPSS) score was (58.67 ± 11.09), and Belief about Medicines Questionnaire Scale (BMQ) score was (0.17 ± 2.78). Multiple linear regression analysis revealed that age, adverse reactions, educational level, self-efficacy, medication beliefs, and social support were factors influencing compliance with oral nutritional supplements in postoperative patients with digestive tract tumors (P

Abstract Background Fostering empathy has been continuously emphasized in the global medical education. Empathy is crucial to enhance patient-physician relationships, and is associated with medical students’ academic and clinical performance. However, empathy level of medical students in China and related influencing factors are not clear. Methods This was a cross-sectional study among medical students in 11 universities. We used the Jefferson Scale of Empathy Student-version of Chinese version to measure empathy level of medical students. Factors associated with empathy were identified by the univariate and multivariate logistic regression analyses. Based on the variables identified above, the nomogram was established to predict high empathy probability of medical students. Receiver operating characteristic curve, calibration plot and decision curve analysis were used to evaluate the discrimination, calibration and educational utility of the model. Results We received 10,901 samples, but a total of 10,576 samples could be used for further analysis (effective response rate of 97.02%). The mean empathy score of undergraduate medical students was 67.38 (standard deviation = 9.39). Six variables including gender, university category, only child or not, self-perception doctor-patient relationship in hospitals, interest of medicine, Kolb learning style showed statistical significance with empathy of medical students (P

Abstract Self-healing smart grids are characterized by fast-acting, intelligent control mechanisms that minimize power disruptions during outages. The corrective actions adopted during outages in power distribution networks include reconfiguration through switching control and emergency load shedding. The conventional decision-making models for outage mitigation are, however, not suitable for smart grids due to their slow response and computational inefficiency. Here, we present a graph reinforcement learning model for outage management in the distribution network to enhance its resilience. The distinctive characteristic of our approach is that it explicitly accounts for the underlying network topology and its variations with switching control, while also capturing the complex interdependencies between state variables (along nodes and edges) by modeling the task as a graph learning problem. Our model learns the optimal control policy for power restoration using a Capsule-based graph neural network. We validate our model on three test networks, namely the 13, 34, and 123-bus modified IEEE networks where it is shown to achieve near-optimal, real-time performance. The resilience improvement of our model in terms of loss of energy is 607.45 kWs and 596.52 kWs for 13 and 34 buses, respectively. Our model also demonstrates generalizability across a broad range of outage scenarios.

This work reports the design and manufacturing of a new electrochemical sensing platform for the monitoring of prednisolone (PE) steroid in physiological fluids. To reach this, palladium (Pd) nanoparticles were successfully deposited on carbon nitride (CN) nanosheets using chemical reduction approach. The prepared CN-Pd hybrid material along with an ionic liquid (IL, 1-ethyl-3-methylimidazolium tetrafluoroborate) were employed for modification of a low expense carbon paste electrode (CPE). The CN-Pd-IL modified CPE was electrochemically characterized to ensure the electrochemical performance towards PE reduction. The important parameters affecting the performance of the PE sensor including CN-Pd dosage and pH of buffer were studied and optimized. The CN-Pd-IL modified CPE illustrated a wide linear response in a PE concentration range of 0.6 nM to 60 nM using SWV methodology. The limit of detection (based on S/N=3) was 0.1 nM at optimal conditions. The suggested PE sensor illustrated the satisfactory reproducibility and good matrix-effectless character. In addition, the CN-Pd-IL modified CPE was facilely used for the electrochemical measuring of PE in the serum samples of athletes with high recovery values (97.6%-102.4%). The proposed methodology can be employed for the sensitive, selective and fast detection of PE.

Hydraulic fracturing is an important technical means to relieve the pressure of coal seam roof. Better understanding of fracture propagation mechanism is of great significance to the safe mining of coal seam. In order to further explore the law of hydraulic fracture propagation, aiming at rock-like specimens commonly used in the laboratory, MatDEM, a particle discrete element numerical simulation software, was used to establish a two-dimensional discrete element numerical model of hydraulic fracturing, and various hydraulic fracturing tests with different injection pressure increments were carried out. The effect of injection pressure increment on the propagation of hydraulic fractures was studied, and the mechanism of model initiation was revealed. The law of fracture generation and propagation was analyzed from mesoscale, and the propagation characteristics of hydraulic fractures were discussed. The results show that ① the effect of injection pressure increment on the model initiation pressure and initiation time presents an opposite trend. With the increase of injection pressure, the increase trend of initiation pressure is slow and gradually approaches to 5.6 MPa. The initiation time decreases with the increase of injection pressure, and the decreasing trend slows down gradually. ② The cumulative number of fractures increases exponentially with time. The hydraulic fracturing process can be divided into four stages (Ⅰ−Ⅳ): no fracture stage, slow fracture growth stage, steady fracture growth stage and rapid fracture growth stage, which correspond to the pre-crack initiation, pre-crack formation, primary fracture propagation and secondary fracture propagation processes respectively. As the injection pressure increment increases, the durations of stage Ⅰ, Ⅱ and Ⅲ decrease, while the duration of stage Ⅳ increases in a fluctuating manner. The number of cracks in each stage is the highest in stage Ⅳ, followed by stage Ⅲ and stage Ⅱ. ③ As the injection pressure increment increases, the number of secondary fractures increases from 8 to 16, and the growth rate of fractures gradually slows down before the stage Ⅲ, and increases rapidly after the stage Ⅳ. When the injection pressure increment increases from 0.03 MPa to 0.70 MPa, the final fracture length increases by 1.79 times. ④ The internal energy of the model increases with the increase of the injection pressure increment, and the energy input speed gradually becomes faster. After the model initiation, high-pressure water forms stress concentration at the crack tip, which promotes the crack to continue to extend. At higher injection pressure increment, the fracture propagation speed becomes faster, and the particle displacement decreases gradually from the pressure hole to the outside of the model. The increment of injection pressure makes the secondary fracture forming position close to the pressure hole, which inhibits the formation and expansion of the primary fracture and promotes the formation and expansion of the secondary fracture. All fracture types are tensile fractures.

Abstract Malus hybrid ‘SH6’ (M. honanensis × M. domestica)is a commonly used apple interstock in China, known for its excellent dwarfing characteristics and cold tolerance. In this study, a combined strategy utilizing PacBio HiFi, Hi-C and parental resequencing data were employed to assemble two haploid genomes for ‘SH6’. After chromosome anchoring, the final hapH genome size was 596.63 Mb, with a contig N50 of 34.38 Mb. The hapR genome was 649.37 Mb, with a contig N50 of 36.84 Mb. Further analysis predicted that repeated sequences made up 59.69% and 62.52% of the entire genome, respectively. Gene annotations revealed 45,435 genes for hapH and 48,261 genes for hapR. Combined with genomic synteny we suggest that the hapR genome originates from its maternal parent M. domestica cv. Ralls Janet, while the hapH genome comes from its paternal parent, M. honanensis. The assembled genome significantly contributes to the discovery of genes associated with apple dwarfing and the molecular mechanisms governing them.

Abstract The citral-type is the most common chemotype in Cinnamomum bodinieri Levl (C. bodinieri), which has been widely used in the daily necessities, cosmetics, biomedicine, and aromatic areas due to their high citral content. Despite of this economic prospect, the possible gene-regulatory roles of citral biosynthesis in the same geographic environment remains unknown. In this study, the essential oils (EOs) of three citral type (B1, B2, B3) and one non-citral type (B0) varieties of C. bodinieri were identified by GC-MS after hydrodistillation extraction in July. 43 components more than 0.10% were identified in the EOs, mainly composed of monoterpenes (75.8–91.84%), and high content citral (80.63–86.33%) were identified in citral-type. Combined transcriptome and metabolite profiling analysis, plant-pathogen interaction(ko04626), MAPK signaling pathway-plant(ko04016), starch and sucrose metabolism(ko00500), plant hormone signal transduction(ko04075), terpenoid backbone biosynthesis (ko00900) and monoterpenoid biosynthesis (ko00902) pathways were enriched significantly. The gene expression of differential genes were linked to the monoterpene content, and the geraniol synthase (CbGES), alcohol dehydrogenase (CbADH), geraniol 8-hydroxylase-like (CbCYP76B6-like) and 8-hydroxygeraniol dehydrogenase (Cb10HGO) were upregulated in the citral-type, indicating that they were associated with high content of geraniol and citral. The activities of CbGES and CbADH in citral type were higher than in non-citral type, which was corroborated by enzyme-linked immunosorbent assay (ELISA). This study on the accumulation mechanism of citral provides a theoretical basis for the development of essential oil of C. bodinieri.

Abstract Micro-light-emitting diodes (Micro-LEDs) are a new type of display device based on the third-generation semiconductor gallium nitride (GaN) material which stands out for its high luminous efficiency, elevated brightness, short response times, and high reliability. The contact between anode layers and P-GaN is one of the keys to improving the performance of the devices. This study investigates the impact of electrode structure design and optimized annealing conditions on the anode contact performance of devices. The Micro-LED device with the size of 9.1 μm whose electrode structure is ITO/Ti/Al/Ni/Cr/Pt/Au (100/50/350/100/500/500/5000 Å) exhibits a significant improvement in contact performance after annealing under the Ar gas atmosphere at 500 °C for 5 min. The optimized device exhibited a current of 10.9 mA and a brightness of 298,628 cd/m2 under 5 V. The EQE peak value of Device A is 10.06% at 400 mA.

Abstract High-speed wide-field fluorescence microscopy has the potential to capture biological processes with exceptional spatiotemporal resolution. However, conventional cameras suffer from low signal-to-noise ratio at high frame rates, limiting their ability to detect faint fluorescent events. Here, we introduce an image sensor where each pixel has individually programmable sampling speed and phase, so that pixels can be arranged to simultaneously sample at high speed with a high signal-to-noise ratio. In high-speed voltage imaging experiments, our image sensor significantly increases the output signal-to-noise ratio compared to a low-noise scientific CMOS camera (~2–3 folds). This signal-to-noise ratio gain enables the detection of weak neuronal action potentials and subthreshold activities missed by the standard scientific CMOS cameras. Our camera with flexible pixel exposure configurations offers versatile sampling strategies to improve signal quality in various experimental conditions.

Abstract Kidney diseases pose a significant threat to human health due to their high prevalence and mortality rates. Worryingly, the clinical use of drugs for kidney diseases is associated with more side effects, so more effective and safer treatments are urgently needed. Oleanolic acid (OA) is a common pentacyclic triterpenoid that is widely available in nature and has been shown to have protective effects in kidney disease. However, comprehensive studies on its role in kidney diseases are still lacking. Therefore, this article first explores the botanical sources, pharmacokinetics, derivatives, and safety of OA, followed by a summary of the anti-inflammatory, immunomodulatory, anti-oxidative stress, autophagy-enhancing, and antifibrotic effects of OA and its analogues in renal diseases, and an analysis of the molecular mechanisms, aiming to provide further insights for the development of novel drugs for the treatment of kidney diseases.

Abstract Senescent cell clearance is emerging as a promising strategy for treating age-related diseases. Senolytics are small molecules that promote the clearance of senescent cells; however, senolytics are uncommon and their underlying mechanisms remain largely unknown. Here, we investigated whether genomic instability is a potential target for senolytic. We screened small-molecule kinase inhibitors involved in the DNA damage response (DDR) in Zmpste24 −/− mouse embryonic fibroblasts, a progeroid model characterized with impaired DDR and DNA repair. 4,5,6,7-tetrabromo-2-azabenzamidazole (TBB), which specifically inhibits casein kinase 2 (CK2), was selected and discovered to preferentially trigger apoptosis in Zmpste24 −/− cells. Mechanistically, inhibition of CK2 abolished the phosphorylation of heterochromatin protein 1α (HP1α), which retarded the dynamic HP1α dissociation from repressive histone mark H3K9me3 and its relocalization with γH2AX to DNA damage sites, suggesting that disrupting heterochromatin remodeling in the initiation of DDR accelerates apoptosis in senescent cells. Furthermore, feeding Zmpste24-deficient mice with TBB alleviated progeroid features and extended their lifespan. Our study identified TBB as a new class senolytic compound that can reduce age-related symptoms and prolong lifespan in progeroid mice.

Abstract Objectives Research has demonstrated that obesity may be associated with rheumatoid arthritis (RA). In addition, gut microbiota and its metabolites contribute to the occurrence and development of RA and obesity. However, the mechanism by which obesity affects RA remains unclear. In this study, we aimed to investigate whether gut microbiota and their metabolites alter the effects of high fat diet (HFD) on the severity of collagen-induced arthritis (CIA) in mice. Methods Briefly, mice were divided into normal group (N), CIA model group (C), HFD group (T), and HFD CIA group (CT). Hematoxylin and Eosin staining(HE) and Safranin O-fast green staining were conducted, and levels of blood lipid and inflammatory cytokines were measured. 16S rDNA sequencing technique and liquid chromatography-mass spectrometry (LC-MS)-based metabolomics were performed to explore changes in the microbiota structure to further reveal the pathomechanism of HFD on CIA. Results HFD aggravated the severity of CIA in mice. The CT group had the highest proportion of microbial abundance of Blautia, Oscillibacter, Ruminiclostridium-9, and Lachnospiraceae UCG 006 at the genus level, but had a lower proportion of Alistipes. Additionally, the fecal metabolic phenotype of the combined CT group shows significant changes, with differential metabolites enriched in 9 metabolic pathways, including primary bile acid biosynthesis, arginine biosynthesis, sphingolipid metabolism, purine metabolism, linoleic acid metabolism, oxytocin signaling pathway, aminoacyl-tRNA biosynthesis, the pentose phosphate pathway, and sphingolipid signaling pathway. Correlation analysis revealed that some of the altered gut microbiota genera were strongly correlated with changes in fecal metabolites, total cholesterol (TC), triglyceride (TG), and inflammatory cytokine levels. Conclusions This study shows that HFD may aggravate inflammatory reaction in CIA mice by altering the gut microbiota and metabolic pathways.

Citrus Huanglongbing (HLB), which is caused by ‘Candidatus Liberibacter asiaticus’ (CLas), is one of the most destructive citrus diseases worldwide, and defense-related Citrus sinensis gene resources remain largely unexplored. Calcium signaling plays an important role in diverse biological processes. In plants, a few calcium-dependent protein kinases (CDPKs/CPKs) have been shown to contribute to defense against pathogenic microbes. The genome of C. sinensis encodes dozens of CPKs. In this study, the role of C. sinensis calcium-dependent protein kinases (CsCPKs) in C. sinensis defense was investigated. Silencing of CsCPK6 compromised the induction of defense-related genes in C. sinensis. Expression of a constitutively active form of CsCPK6 (CsCPK6CA) triggered the activation of defense-related genes in C. sinensis. Complementation of CsCPK6 rescued the defense-related gene induction in an Arabidopsis thaliana cpk4/11 mutant, indicating that CsCPK6 carries CPK activity and is capable of functioning as a CPK in Arabidopsis. Moreover, an effector derived from CLas inhibits defense induced by the expression of CsCPK6CA and autophosphorylation of CsCPK6, which suggests the involvement of CsCPK6 and calcium signaling in defense. These results support a positive role for CsCPK6 in C. sinensis defense against CLas, and the autoinhibitory regulation of CsCPK6 provides a potential genome-editing target for improving C. sinensis defense. [Graphic: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Abstract Flexible sensors have been widely studied for use in motion monitoring, human‒machine interactions (HMIs), personalized medicine, and soft intelligent robots. However, their practical application is limited by their low output performance, narrow measuring range, and unidirectional force detection. Here, to achieve flexibility and high performance simultaneously, we developed a flexible wide-range multidimensional force sensor (FWMFS) similar to bones embedded in muscle structures. The adjustable magnetic field endows the FWMFS with multidimensional perception for detecting forces in different directions. The multilayer stacked coils significantly improved the output from the μV to the mV level while ensuring FWMFS miniaturization. The optimized FWMFS exhibited a high voltage sensitivity of 0.227 mV/N (0.5–8.4 N) and 0.047 mV/N (8.4–60 N) in response to normal forces ranging from 0.5 N to 60 N and could detect lateral forces ranging from 0.2–1.1 N and voltage sensitivities of 1.039 mV/N (0.2–0.5 N) and 0.194 mV/N (0.5–1.1 N). In terms of normal force measurements, the FWMFS can monitor finger pressure and sliding trajectories in response to finger taps, as well as measure plantar pressure for assessing human movement. The plantar pressure signals of five human movements collected by the FWMFS were analyzed using the k-nearest neighbors classification algorithm, which achieved a recognition accuracy of 92%. Additionally, an artificial intelligence biometric authentication system is being developed that classifies and recognizes user passwords. Based on the lateral force measurement ability of the FWMFS, the direction of ball movement can be distinguished, and communication systems such as Morse Code can be expanded. This research has significant potential in intelligent sensing and personalized spatial recognition.

Abstract Porcine reproductive and respiratory syndrome (PRRS), caused by the PRRS virus (PRRSV), has caused substantial economic losses to the global swine industry due to the lack of effective commercial vaccines and drugs. There is an urgent need to develop alternative strategies for PRRS prevention and control, such as antiviral drugs. In this study, we identified ursonic acid (UNA), a natural pentacyclic triterpenoid from medicinal herbs, as a novel drug with anti-PRRSV activity in vitro. Mechanistically, a time-of-addition assay revealed that UNA inhibited PRRSV replication when it was added before, at the same time as, and after PRRSV infection was induced. Compound target prediction and molecular docking analysis suggested that UNA interacts with the active pocket of PTPN1, which was further confirmed by a target protein interference assay and phosphatase activity assay. Furthermore, UNA inhibited PRRSV replication by targeting PTPN1, which inhibited IFN-β production. In addition, UNA displayed antiviral activity against porcine epidemic diarrhoea virus (PEDV) and Seneca virus A (SVA) replication in vitro. These findings will be helpful for developing novel prophylactic and therapeutic agents against PRRS and other swine virus infections.

Abstract Background Miscarriage is a frustrating complication of pregnancy that is common among women of reproductive age. Insufficient decidualization which not only impairs embryo implantation but disturbs fetomaternal immune-tolerance, has been widely regarded as a major cause of miscarriage; however, the underlying mechanisms resulting in decidual impairment are largely unknown. Methods With informed consent, decidual tissue from patients with spontaneous abortion or normal pregnant women was collected to detect the expression profile of UCHL1. Human endometrial stromal cells (HESCs) were used to explore the roles of UCHL1 in decidualization and dNK modulation, as well as the mechanisms involved. C57/BL6 female mice (7–10 weeks old) were used to construct pregnancy model or artificially induced decidualization model to evaluate the effect of UCHL1 on mice decidualization and pregnancy outcome. Results The Ubiquitin C-terminal hydrolase L1 (UCHL1), as a deubiquitinating enzyme, was significantly downregulated in decidua from patients with miscarriage, along with impaired decidualization and decreased dNKs. Blockage of UCHL1 led to insufficient decidualization and resultant decreased expression of cytokines CXCL12, IL-15, TGF-β which were critical for generation of decidual NK cells (dNKs), whereas UCHL1 overexpression enhanced decidualization accompanied by increase in dNKs. Mechanistically, the promotion of UCHL1 on decidualization was dependent on its deubiquitinating activity, and intervention of UCHL1 inhibited the activation of JAK2/STAT3 signaling pathway, resulting in aberrant decidualization and decreased production of cytokines associated with dNKs modulation. Furthermore, we found that inhibition of UCHL1 also disrupted the decidualization in mice and eventually caused adverse pregnancy outcome. Conclusions UCHL1 plays significant roles in decidualization and dNKs modulation during pregnancy in both humans and mice. Its deficiency indicates a poor pregnancy outcome due to defective decidualization, making UCHL1 a potential target for the diagnosis and treatment of miscarriage. Graphical Abstract

Abstract Background Primulina juliae has recently emerged as a novel functional vegetable, boasting a significant biomass and high calcium content. Various breeding strategies have been employed to the domestication of P. juliae. However, the absence of genome and transcriptome information has hindered the research of mechanisms governing the taste and nutrients in this plant. In this study, we conducted a comprehensive analysis, combining the full-length transcriptomics and metabolomics, to unveil the molecular mechanisms responsible for the development of nutrients and taste components in P. juliae. Results We obtain a high-quality reference transcriptome of P. juliae by combing the PacBio Iso-seq and Illumina sequencing technologies. A total of 58,536 cluster consensus sequences were obtained, including 28,168 complete protein coding transcripts and 8,021 Long Non-coding RNAs. Significant differences were observed in the composition and content of compounds related to nutrients and taste, particularly flavonoids, during the leaf development. Our results showed a decrease in the content of most flavonoids as leaves develop. Malate and succinate accumulated with leaf development, while some sugar metabolites were decreased. Furthermore, we identified the different accumulation of amino acids and fatty acids, which are associated with taste traits. Moreover, our transcriptomic analysis provided a molecular basis for understanding the metabolic variations during leaf development. We identified 4,689 differentially expressed genes in the two developmental stages, and through a comprehensive transcriptome and metabolome analysis, we discovered the key structure genes and transcription factors involved in the pathways. Conclusions This study provides a high-quality reference transcriptome and reveals molecular mechanisms associated with the development of nutrients and taste components in P. juliae. These findings will enhance our understanding of the breeding and utilization of P. juliae as a vegetable.

Abstract The dispersion stability of carbonyl iron particle (CIP)-based magnetorheological fluid (MRF) is improved by CIP, which particle is etched with hydrochloric acid (HCl) to form porous structure with many hydroxyl groups and subsequently coated with silane coupling agents that have varying chain lengths. The microstructures, coating effect and magnetism of the CIPs were examined using the Scanning Electron Microscopy, Automatic Surface and Porosity Analyzer (BET), Fourier-Transform Infrared Spectroscopy, Thermogravimetric Analysis and Vibrating Sample Magnetometer. Furthermore, the rheological properties and dispersion stability of the MRFs were assessed using a Rotating Rheometer and Turbiscan-lab. The results revealed that the nanoporous structure appeared on the CIPs and the specific surface area increased remarkably after being etched by hydrochloric acid. Additionally, as the chain length of the silane coupling agent increases, the coated mass on the particles increases, the the density and the saturation magnetization of particles decreased, and the coated particles with different shell thicknesses were obtained; without a magnetic field, the viscosity of MRF prepared by coated particles increase slightly, due to the enhancement of special three-dimensional network structure; under a magnetic field, the viscosity of the MRF decreased distinctly; the sedimentation rate of MRF decreased from 58 to 3.5% after 100 days of sedimentation, and the migration distances of the MRFs were 22.4, 3.7, 2.4, and 0 mm, with particle sedimentation rates of 0.149, 0.019, 0.017, and 0 mm/h, respectively. The MRF with high dispersion stability was obtained, and the etching of CIP by HCl and the proper chain length of the coating of silane coupling agent were proved effective manners to improve the dispersion stability of MRF.

Abstract Background Borderline personality traits play a significant role in nonsuicidal self-injury (NSSI), particularly in depressed youths. NSSI is also highly correlated with negative life events. This research aimed to explore the connections between negative life events, borderline personality traits, and NSSI. Methods The study included 338 depressed youth aged 13 to 25 years. Self-reported measures and clinical interviews were utilized to evaluate the depressive symptoms, borderline personality traits, negative life events, and NSSI behaviours of these participants. Identifying variables linked to NSSI was the aim of our analysis, and we also conducted a mediation analysis to look into the influence of borderline traits on the connection between negative life events and NSSI. Results Of the 338 depressed youth, approximately 59.47% (201/338) displayed NSSI, which was associated with greater clinical severity. Borderline traits had an independent influence on NSSI and it partially explained the connection between negative life events and NSSI, even when accounting for depression symptoms. Depressed youth who were more vulnerable to NSSI behaviours often experienced negative life events such as interpersonal relationships, academic pressure, being punished, and loss. Conclusions Our research suggests that depressed youth who experience more negative life events are more likely to experience NSSI, and negative life events indirectly influence nonsuicidal self-injury through borderline personality traits. Implementing interventions focused on mitigating borderline symptoms could be a promising therapeutic approach for addressing NSSI in young people.