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The burgeoning use of titanium alloys in unmanned underwater vehicles has sparked a surge in demand for low-cost titanium alloys that maintain superior mechanical properties. Despite this, a comprehensive understanding of the deformation mechanisms in low-cost titanium alloys with exceptional impact toughness remains elusive. Therefore, the impact toughness and deformation mechanisms of a novel low-cost Ti–6Al–4V-1.5Mo-1.0Fe alloy with two types of bimodal microstructures (BM1 and BM2) and lamellar microstructures (LM1 and LM2) were studied. The BM2 sample demonstrated an impressive balance of mechanical properties, with a yield strength of 1150 MPa, a tensile strength of 1245 MPa, an elongation of 11%, and an impact energy of 42.59 J. The load‒displacement curves indicated that the energy associated with crack initiation accounted for as much as 85% in the BM samples. By integrating nanoindentation and back stress tests, the deformation behavior near the crack path and the mechanisms of crack initiation were examined. The results revealed that crack initiation was intricately linked to the plastic deformation of the microstructures in the vicinity of the notch tips. The activation of {1 01‾ 2} tensile twins in αp, along with the pronounced kink deformation of βt, enhanced the degree of plastic deformation, thereby increasing the crack initiation energy. The proportion of crack propagation energy reached 39% for the LM2 sample. The crack propagation mechanisms were further analyzed via SEM and EBSD. The analysis indicated that the crack propagation energy was synergistically influenced by the deformation in the plastic zone near the crack path and the length of the crack path. The pronounced kink plastic deformation and the convoluted crack path observed in the LM2 sample could alleviate the interface stress concentration, thus improving the energy dissipation during crack propagation.

Abstract Background Renal replacement therapy (RRT) plays a crucial role in managing acute pancreatitis (AP). This study aimed to develop and evaluate predictive models for determining the need for RRT among patients with AP in the intensive care unit (ICU). Methods A retrospective selection of patients with AP was made from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version V2.0). The cohort was randomly divided into a training set (447 patients) and a validation set (150 patients). The least absolute shrinkage and selection operator (LASSO) regression cross-validation method was utilized to identify key features for model construction. Using these features, four machine learning (ML) algorithms were developed. The optimal model was visualized and clarified using SHapley Additive exPlanations (SHAP) and presented as a nomogram. Results The mean age of the cohort was 59.17 years, with an average Acute Physiology and Chronic Health Evaluation II (APACHE II) score of 17.55. Acute kidney injury (AKI) was observed in 52.43% of patients with AP, and 9.05% required RRT. After feature selection, four of 41 clinical factors were ultimately chosen for use in model construction. The Lasso-Logistic Regression (Lasso-LR) model showed a high discriminative ability to predict RRT risk in patients with AP, with an area under the receiver operating characteristic (AUROC) of 0.955 (95% CI 0.924–0.987) in the training set. In the validation set, it maintained its discriminative performance, achieving an AUROC of 0.985 (95% CI 0.970–1.000). Calibration curves indicated an excellent fit in both sets (Brier scores: 0.039 and 0.032, respectively), suggesting high consistency. Decision curve analysis (DCA) highlighted the Lasso-LR model's significant clinical utility in predicting RRT likelihood in patients with AP. Conclusions Developed via the LASSO regression cross-validation method, the Lasso-LR model significantly excels in predicting the requirement for RRT in patients with AP, demonstrating its potential for clinical application.

Abstract Background The Sec14 domain is an ancient lipid-binding domain that evolved from yeast Sec14p and performs complex lipid-mediated regulatory functions in subcellular organelles and intracellular traffic. The Sec14 family is characterized by a highly conserved Sec14 domain, and is ubiquitously expressed in all eukaryotic cells and has diverse functions. However, the number and characteristics of Sec14 homologous genes in soybean, as well as their potential roles, remain understudied. Results In this study, we identified 77 Sec14 genes in the soybean genome that were unevenly distributed across 19 chromosomes. Based on the classification method used for Arabidopsis Sec14 members, GmSec14s can be categorized into three classes: GmPITP1 to GmPITP37, GmSFH1 to GmSFH25, and GmPATL1 to GmPATL15. Structural analysis of the GmSec14 genes revealed that the SFH subfamily contained more introns than the other subfamilies. A total of 10 conserved protein motifs were detected within GmSec14 proteins, with each subfamily possessing unique motifs. Two tandem duplications and 73 segmental duplications were identified among the GmSec14 genes. Additionally, a large number of cis-acting elements, particularly those related to plant hormones, were abundant in the promoter regions of the GmSec14 genes. Tissue expression analysis of the GmSec14 genes indicated that they exhibited distinct tissue-specific expression patterns. In response to salt stress, multiple genes were found to be either upregulated or downregulated. In contrast, the majority of genes were downregulated under drought stress conditions. Notably, 12 GmSec14 genes exhibited significant alterations in expression following salt or drought stress, suggesting a potential role for these genes in stress response mechanisms. Furthermore, the protein interaction network and miRNA regulation associated with GmSec14s were predicted to elucidate the potential functions of GmSec14 members. Conclusions This study provides a systematic and comprehensive examination of the Sec14 gene family in soybean, which will facilitate further functional research into their roles in response to salt and drought tolerance.

Abstract Background Herpes simplex keratitis (HSK) is a recurrent inflammatory disease of cornea primarily initiated by type I herpes simplex virus infection of corneal epithelium. However, early diagnosis of HSK remains challenging due to the lack of specific biomarkers. This study aims to identify biomarkers for HSK through tear metabolomics analysis between HSK and healthy individuals. Methods We conducted a cross-sectional study enrolling 33 participants. Tear samples were collected from one eye of 18 HSK patients and 15 healthy volunteers using Schirmer-strips. Tear metabolomic profiling was performed using high-performance liquid chromatography tandem mass spectrometry (LC–MS/MS). Metabolites were quantified and matched against entries in the human metabolome database (HMDB) and small molecule pathway database (SMPDB) to identify metabolites and metabolic pathways, respectively. Metabolic differences between HSK and control group were determined using multivariate statistical analysis. Results A total of 329 metabolites were identified, of which 18 were significantly altered in HSK patients. Notably, 12 metabolites were significantly increased, and 6 were significantly decreased in HSK patients. The changed metabolites were enriched in these pathways: arginine and proline metabolism, phospholipid biosynthesis, alpha linolenic acid and linoleic acid metabolism, retinol metabolism. To assess the potential utility of tear biomarkers, a predictive model was developed combining 4 metabolites (AUC = 0.998 [95%CI: 0.975, 1]): D-proline, linoelaidic acid, plantagonine, and phosphorylcholine. Conclusions Our study establishes that HSK has a distinctive metabolomic profile, with 4 key elements maybe emerging as potential biomarkers for diagnostic purposes. These findings may provide novel insights into early and rapid diagnosis of HSK.

Abstract The diverse utility of acyclic vinylsilanes has driven the interest in the synthesis of enantioenriched vinylsilanes bearing a Si-stereogenic center. However, the predominant approaches for catalytic asymmetric generation of Si-stereogenic vinylsilanes have mainly relied on transition metal-catalyzed reactions of alkynes with different silicon sources. Here we successfully realize the enantioselective synthesis of linear silicon-stereogenic vinylsilanes with good yields and enantiomeric ratios from simple alkenes under rhodium catalysis. The significance of this transformation lies in its ability to achieve regioconvergent and enantioconvergent conversion, efficiently transforming petroleum-derived isomeric mixtures of olefin feedstocks into a single regio- and stereoisomer product. The practicality of this method is further exemplified by the diverse downstream transformations of these enantioenriched silicon-stereogenic vinylsilanes leveraging the olefin functionality and the leaving group nature of the aryl substituent on silicon as well as the development of chiral π-conjugated double bond systems.

The mechanical properties of the coherently precipitated high-entropy alloys can be further enhanced by enhancing the strain hardening behavior through deformation twins. In this study, a heterogeneously structured Ni45Co21Fe15Cr10Al4·5Ti4.5 (at. %) alloy with micro-meter-sized grains embedded inside a matrix of nanocrystalline or ultrafine grains was obtained through tailored thermomechanical processing steps. The tested alloy exhibited favorable strain hardening behavior, resulting in a remarkable tensile ductility of 32% even under the high yield stress of 1400 MPa. Dense planar defects comprised of deformation twins (DTs) have been activated in the grains composed of γ phase and coherently precipitated γ′ phase during the tensile process at room temperature. The underlying mechanism for the nucleation and growth of DTs in the grains with γ/γ′ duplex phases has been elucidated through transmission electron microscopy observations and density functional theory calculation, emphasizing the importance of the DTs. This research provides new insights into designing high entropy alloys that overcome the trade-off between strength and ductility.

Abstract Background Elderly acute kidney injury (AKI) occurring in the intensive care unit (ICU), particularly when caused or accompanied by sepsis, is linked to extended hospital stays, increased mortality rates, heightened prevalence of chronic diseases, and diminished quality of life. This study primarily utilizes a comprehensive critical care database to examine the correlation of albumin corrected anion gap (ACAG) levels with short-term prognosis in elderly patients with AKI caused or accompanied by sepsis, thus assisting physicians in early identification of high-risk patients. Methods This study utilized data from the Medical Information Mart for Intensive Care IV (MIMIC-IV, v2.0) database. The patient population was divided into death and survival groups based on a 14-day prognosis. Subsequently, the entire population was further categorized into a normal ACAG group (12–20 mmol/L) and a high ACAG group (> 20 mmol/L) based on ACAG levels. The LASSO regression cross-validation method was employed to identify significant risk factors for inclusion in multivariate Cox regression analyses. A restricted cubic spline (RCS) was then employed to visually represent the correlation between ACAG levels and the risk of mortality in patients. Kaplan–Meier curves were utilized to plot the cumulative survival rates at 14 and 30 days for both patient groups. The robustness of the findings was subsequently evaluated through subgroup analyses. Results Our study identified a total of 3741 eligible subjects, revealing higher all-cause mortality rates at both 14-day and 30-day intervals in the high ACAG group compared to the normal ACAG group (χ2 = 87.023, P

A novel Mg-6.2Gd-4.2Sm-1.2Zn alloy with a superior strength-ductility combination was achieved by traditional extrusion process and aging. Based on the characteristics of substitutional solution among rare earth (RE) elements, the Sm substitute part Gd element change the morphology of the LPSO phase, and the volume fraction of the 14H-LPSO phase increases, leading to a finer size and more dispersed distribution. Meanwhile, the Sm addition reduces the level of GB segregation of Zn and Gd, which further affects the precipitation of nano-precipitates during aging. The results offer insight into determining the precipitation behavior of second phases via regulating solute GB segregation.

Abstract Purpose Narrow resection margin hepatocellular carcinoma (NRM-HCC) has a high incidence of early recurrence. Our study was designed to identify prognostic factors in patients with NRM-HCC, establish and validate a nomogram model to predict early recurrence of NRM-HCC patients. Methods We retrospectively analyzed data from 2957 NRM-HCC patients who underwent radical hepatectomy at three medical centers between December 2009 and January 2015. Patients were randomly assigned to a training cohort (n = 2069) and a validation cohort (n = 888). Using univariate and multivariate COX regression to determine early relapse factors in NRM-HCC patients, and used these factors to construct a nomogram. The accuracy of the prediction was evaluated using the C-index, receiver operating characteristic (ROC) and calibration curve. Decision curve analysis (DCA) assessed the predictive value of the models. Finally, the recurrence-free survival of different risks was analyzed using Kaplan-Meier (K-M) method. Results The nomogram of NRM model contains alpha-fetoprotein (AFP), alkaline phosphatase (ALP), tumor size, tumor number, microvascular invasion (MVI), tumor capsular, and satellite nodules. The model shows good discrimination with C-indexes of 0.71 (95% CI: 0.69–0.72) and 0.72 (95% CI: 0.70–0.75) in the train cohort and test cohort respectively. Decision curve analysis demonstrated that the model is clinically useful and the calibration of our model was favorable. Our model stratified patients into two different risk groups, which exhibited significantly different early recurrence. The web-based tools are convenient for clinical practice. Conclusions NRM model demonstrated favorable performance in predicting early recurrence in NRM-HCC patients. This novel model will be helpful to guide postoperative follow-up and adjuvant therapy.

Abstract As a critical technology, anomaly detection ensures the smooth operation of cloud systems while maintaining the market competitiveness of cloud service providers. However, the resource data in real-world cloud systems is predominantly unannotated, leading to insufficient supervised signals for anomaly detection. Moreover, complicated topological associations existed between cloud servers (e.g., computation, storage, and communication). While acquiring resource information, correlating the system topology is challenging. To this end, we propose the GCAD for cloud system anomaly detection, which integrates data augmentation, GraphGRU, contrastive learning, and reconstruction. First, GCAD constructs positive and negative sample pairs through the masking and Gaussian noise data augmentation. Then, the GraphGRU processes extended temporal graph data, extracting and fusing spatiotemporal features from resource status and system topology. In addition, GCAD introduces linear attention for encoding spatiotemporal representations to capture their global correlation information. The weight parameters of the encoder are optimized using a contrastive learning mechanism. Finally, GCAD utilizes a reconstruction technique to calculate anomaly scores, facilitating the evaluation of the state of the cloud system at each time point. Experimental results indicate that GCAD outperforms state-of-the-art compared methods on two real-world datasets that contain topology information.

Abstract Background The region-specific importance of carcinogenic HPV genotypes is required for optimizing HPV-based screening and promoting appropriate multivalent HPV prophylactic vaccines. This information is lacking for Ningbo, one of the first cities of China’s Healthy City Innovation Pilot Program for Cervical Cancer Elimination. Here, we investigated high-risk HPV (HR-HPV) genotype-specific distribution and attribution to biopsy-confirmed cervical intraepithelial neoplasia grade 2 or worse (CIN2+) before mass vaccination in Ningbo, China. Methods A total of 1393 eligible CIN2+ archived blocks (including 161 CIN2, 1107 CIN3, and 125 invasive cervical cancers [ICC]) were collected from 2017 to 2020 in Ningbo. HR-HPV DNA was genotyped using the SPF10-DEIA-LiPA25 version 1 detection system and the SureX HPV 25X Genotyping Kit. Genotype-specific attribution to CIN2+ was estimated using a fractional contribution approach. Results Ranking by the attributable proportions, HPV16 remained the most important genotype in both cervical precancers and cancers, accounting for 36.8% of CIN2, 53.2% of CIN3, and 73.3% of ICC cases. Among cervical precancers, HPV52 (17.3% in CIN2, 12.7% in CIN3) and HPV58 (13.9%, 14.9%) ranked second and third, while HPV33 (8.3%, 7.9%) and HPV31 (6.5%, 4.1%) ranked fourth and fifth, respectively. However, among ICCs, HPV18 (5.7%) accounted for the second highest proportion, followed by HPV33 (5.4%), HPV58 (4.0%), and HPV45 (3.2%). HPV18/45 together accounted for 46.8% of adenocarcinomas, which was slightly lower than that of HPV16 (47.7%). The remaining HR-HPV genotypes (HPV35/39/51/56/59/66/68) combined accounted for only 6.7% of CIN2, 2.9% of CIN3, and 4.2% of ICC. Conclusions With Ningbo’s strong medical resources, it will be important to continue HPV16/18 control efforts, and could broaden to HPV31/33/45/52/58 for maximum health benefits. However, different strategies should be proposed for other HR-HPV genotypes based on their lower carcinogenic risks.

Abstract Load prediction tasks aim to predict the dynamic trend of future load based on historical performance sequences, which are crucial for cloud platforms to make timely and reasonable task scheduling. However, existing prediction models are limited while capturing complicated temporal patterns from the load sequences. Besides, the frequently adopted global weighting strategy (e.g., the self-attention mechanism) in temporal modeling schemes has quadratic computational complexity, hindering the immediate response of cloud servers in complex real-time scenarios. To address the above limitations, we propose a Wavelet decomposition-enhanced External Transformer (WETformer) to provide accurate yet efficient load prediction for cloud servers. Specifically, we first incorporate discrete wavelet transform to progressively extract long-term trends, highlighting the intrinsic attributes of temporal sequences. Then, we propose a lightweight multi-head External Attention (EA) mechanism to simultaneously consider the inter-element relationships within load sequences and the correlations across different sequences. Such an external component has linear computational complexity, mitigating the encoding redundancy prevalent and enhancing prediction efficiency. Extensive experiments conducted on Alibaba Cloud’s cluster tracking dataset demonstrate that WETformer achieves superior prediction accuracy and the shortest inference time compared to several state-of-the-art baseline methods.

To date, the exploration of multi-principal element alloys (MPEAs) has rarely ventured into the realm of hexagonal close-packed (HCP) structures. In this research, we embarked on a pioneering systematic comparison between a single-phase Ti-Zr-Hf HCP-MPEA and Ti regarding their dislocation activities and mesoscale deformation homogeneity. Through large-area high-resolution quasi-in-situ slip trace analysis and crystal plasticity finite element modeling, we identified HCP-MPEA’s significantly enhanced pyramidal slip activities—resulted from minimized disparities among different deformation modes—notably improve the material’s intragranular deformation homogeneity. Alongside MPEA’s intrinsically high slip resistance, it renders HCP-MPEA an outstanding strength-toughness combination relative to its conventional HCP counterparts.

Deep learning has been widely used in landslides detection. However, in practical application, the sample quality often cannot meet the requirements of training models. Some smaller landslides are easy to be omitted if there are multiple landslide objects in one sample. Furthermore, there are some objects with similar shape, texture and colour to landslides (complex backgrounds), such as bare land, roads, water surfaces and artificial buildings. The traditional landslides detection method is easy to confuse landslides and complex backgrounds, which leads to false and omissive detections. To solve the above two problems, a complex background enhancement method with multi-scale samples (MSSCBE) was proposed to improve sample quality. Using the background enhanced samples, the deep learning model can not only learn differences between landslides and complex backgrounds, but also learn the multi-scale features of landslides better. The proposed method was applied to detect landslides that occurred in Jiuzhaigou County, Sichuan Province. Comparative experiments were conducted using Mask R-CNN model. And the model trained with both MSSCBE background enhanced samples and original samples has the best performance. Compared with the model trained with only original samples, Precision, Recall, F1 Score and mIoU is improved by 29.76%, 5.59%, 17.82% and 25.80%, respectively.

Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV), a novel bunyavirus primarily transmitted by Haemaphysalis longicornis, induces severe disease with a high mortality rate. N6-methyladenosine (m6A) is a prevalent internal chemical modification in eukaryotic mRNA that has been reported to regulate viral infection. However, the role of m6A modification during SFTSV infection remains elusive. We here reported that SFTSV RNAs bear m6A modification during infection. Manipulating the expressions or activities of host m6A regulators significantly impacted SFTSV infection. Mechanistically, SFTSV recruited m6A regulators through the nucleoprotein to modulate the m6A modification of viral RNA, eventually resulting in enhanced infection by promoting viral mRNA translation efficiency and/or genome RNA stability. m6A mutations in the S genome diminished virus particle production, while m6A mutations in the G transcript impaired the replication of recombinant vesicular stomatitis virus (rVSV) expressing G protein in vitro and in vivo. Interestingly, m6A modification was evolutionarily conserved and facilitated SFTSV infection in primary tick cells. These findings may open an avenue for the development of m6A-targeted anti-SFTSV vaccines, drugs, and innovative strategies for the prevention and control of tick-borne disease.

Abstract This letter presents a model based on the Cramér–Rao bound theory for calculating the theoretical lower limit of imaging resolution of microwave computational imaging aided by re‐configurable metasurface. The model takes into account two crucial parameters: the signal‐to‐noise ratio and the number of measurements in the imaging process. By simultaneously considering the signal‐to‐noise ratio and the number of measurements, as well as other parameters, the model allows for a comprehensive assessment of the imaging resolution of the imaging system. In addition, both position estimation and intensity estimation are considered, and a new composite statistical resolution concept is proposed, which is more suitable for microwave computational imaging.

Abstract Efficient allocation of tasks and resources is crucial for the performance of heterogeneous cloud computing platforms. To achieve harmony between task completion time, device power consumption, and load balance, we propose a Graph neural network-enhanced Elite Particle Swarm Optimization (EPSO) model for collaborative scheduling, namely GraphEPSO. Specifically, we first construct a Directed Acyclic Graph (DAG) to model the complicated tasks, thereby using Graph Neural Network (GNN) to encode the information of task sets and heterogeneous resources. Then, we treat subtasks and independent tasks as basic task units while considering virtual or physical devices as resource units. Based on this, we exploit the performance adaptation principle and conditional probability to derive the solution space for resource allocation. Besides, we employ EPSO to consider multiple optimization objectives, providing fine-grained perception and utilization of task and resource information. It also increases the diversity of particle swarms, allowing GraphEPSO to adaptively search for the global optimal solution with the highest probability. Experimental results demonstrate the superiority of our proposed GraphEPSO compared to several state-of-the-art baseline methods on all evaluation metrics.

Abstract Background Immunotherapy combined with molecular targeted therapy is increasingly popular in patients with advanced hepatocellular carcinoma (HCC). However, immune-related adverse events(irAEs) brought on by immunotherapy increase the likelihood of side effects, thus it is important to look into ways to address this issue. Methods Different metabolite patterns were established by analyzing metabolomics data in liver tissue samples from 10 patients(divided into severe and mild liver injury) before and after immuno-targeted therapy. After establishing a subcutaneous tumor model of HCC, the mice were divided into PBS group, ascorbic acid(AA) group, and anti-PD1 + tyrosine kinase inhibitor (TKI) group, anti-PD1 + TKI + AA group. Liver tissue were stained with hematoxylin-eosin staining(HE) and the content of aspartate transaminase (AST) and alanine transaminase(ALT) in blood were determined. The mechanism was confirmed by western blotting, mass cytometry, and other techniques. Results Through metabolomics analysis, AA was significantly reduced in the sample of patients with severe liver injury caused by immuno-targeted therapy compared to patients with mild liver injury. The addition of AA in vivo experiments demonstrated a reduction in liver injury in mice. In the liver tissues of the anti-PD1 + TKI + AA group, the protein expressions of SLC7A11,GPX4 and the level of glutathione(GSH) were found to be higher compared to the anti-PD1 + TKI group. Mass cytometry analysis revealed a significant increase in the CD11b+CD44+ PD-L1+ cell population in the AA group when compared to the PBS group. Conclusions AA could reduce liver injury by preventing hepatocyte SLC7A11/GPX4 ferroptosis and improve the immunotherapy effect of anti-PD1 by boosting CD11b+CD44+PD-L1+cell population in HCC.

Abstract Background Mobile health (mHealth) may be an ideal solution for breast cancer (BC) patients in China to access weight management interventions. User retention and engagement are the main challenges faced by mHealth applications. A user persona, which is a user-centered design process, can lead to the development of mHealth that is more acceptable to the needs of target users. This study aimed to investigate the variety of experiences in weight management and the behavioral preferences of BC patients receiving chemotherapy to develop users’ personal information and persona development for the design and implementation of mHealth interventions. Methods Sixteen individual semi-structured in-depth interviews were conducted with BC patients receiving chemotherapy. We employed the thematic analysis method to analyze the interview transcripts in NVivo 11 software. The themes obtained from the analysis were used as the subdomains of personas. A proforma was designed to extract each participant’s experience in each subdomain. Patients who exhibited similar experience in subdomains were grouped into a persona using affinity diagrams. The personas were named according to their prominent features. A questionnaire survey was conducted to validate the personas and to test whether the personas that were generated from the qualitative interview data were applicable to the Chinese population with BC. Results Four themes were identified as subdomains of weight management personas: the perception of weight management while undergoing chemotherapy, symptoms and emotional disturbance, changes in diet and exercise, and health literacy and information seeking. Five personas were ultimately obtained: (1) positive weight controllers, (2) patients who were inactive due to fatigue, (3) young patients who avoided communication, (4) overweight patients with treatment priority, and (5) patients who engaged in irregular exercise. Finally, the quantitative study showed that 51.58% of patients chose one of these five personas to represent themselves in weight management. None of the patient reported selecting options that were not explicitly outlined in the questionnaire and provided personalized descriptions of their weight management characteristics. Conclusions The selected personas were developed from in-depth interviews on biopsychosocial areas. They highlight different weight management patterns in Chinese BC patients and provide implications for both the design of mHealth systems and traditional interventions.

Summary: Continuous renal replacement therapy (CRRT) is a commonly utilized treatment modality for individuals experiencing severe acute kidney injury (AKI). The objective of this research was to construct and assess prognostic models for the timely discontinuation of CRRT in critically ill AKI patients receiving this intervention. Data were collected retrospectively from the MIMIC-IV database (n = 758) for model development and from the intensive care unit (ICU) of Huzhou Central Hospital (n = 320) for model validation. Nine machine learning models were developed by utilizing LASSO regression to select features. In the training set, all models demonstrated an AUROC exceeding 0.75. In the validation set, the XGBoost model exhibited the highest AUROC of 0.798, leading to its selection as the optimal model for the development of an online calculator for clinical applications. The XGBoost model demonstrates significant predictive capabilities in determining the discontinuation of CRRT.

Multiple metabolic diseases are caused by obesity. n-3 polyunsaturated fatty acids (n-3 PUFAs) could prevent obesity. However, the mechanism that n-3 PUFAs ameliorates energy metabolism disorder remains to be elucidated. This study attempted to investigate how n-3 PUFAs impact brown adipose tissue (BAT) and obesity-related signaling pathways in high-fat diet (HFD) induced obese mice. We used fat-1 transgenic mice as an animal model with high n-3 PUFAs. The results showed that n-3 PUFAs mitigated negative impacts of the HFD on the contents of glycaemic and lipid, diminished weight, white adipose tissue content and lipid hoarding in liver tissue, prevented BAT from being infiltrated, and increased microbiota diversity. N-3 PUFAs also upregulated serum interleukin-27 (IL-27) level and mRNAs, protein expression of the key BAT thermogenic genes, uncoupling protein-1 (UCP-1), uncoupling protein-2 (UCP-2). These results demonstrated that endogenous n-3 PUFAs increased BAT burning and energy consumption through the IL-27 pathway, inhibiting obesity.

Abstract Background Spinal cord injury (SCI) is a serious clinical condition that has pathological changes such as increased neuroinflammation and nerve tissue damage, which eventually manifests as fibrosis of the injured segment and the development of a spinal cord cavity leading to loss of function. Cell-based therapy, such as mesenchymal stem cells (MSCs) and neural stem cells (NSCs) are promising treatment strategies for spinal cord injury via immunological regulation and neural replacement respectively. However, therapeutic efficacy is rare reported on combined transplantation of MSC and NSC in acute mice spinal cord injury even the potential reinforcement might be foreseen. Therefore, this study was conducted to investigate the safety and efficacy of co-transplanting of MSC and NSC sheets into an SCI mice model on the locomotor function and pathological changes of injured spinal cord. Methods To evaluate the therapeutic effects of combination cells, acute SCI mice model were established and combined transplantation of hiPSC-NSCs and hMSCs into the lesion site immediately after the injury. Basso mouse scale was used to perform the open-field tests of hind limb motor function at days post-operation (dpo) 1, 3, 5, and 7 after SCI and every week after surgery. Spinal cord and serum samples were collected at dpo 7, 14, and 28 to detect inflammatory and neurotrophic factors. Hematoxylin–eosin (H&E) staining, masson staining and transmission electron microscopy were used to evaluate the morphological changes, fibrosis area and ultrastructure of the spinal cord. Result M&N transplantation reduced fibrosis formation and the inflammation level while promoting the secretion of nerve growth factor and brain-derived neurotrophic factor. We observed significant reduction in damaged tissue and cavity area, with dramatic improvement in the M&N group. Compared with the Con group, the M&N group exhibited significantly improved behaviors, particularly limb coordination. Conclusion Combined transplantation of hiPSC-NSC and hMSC could significantly ameliorate neuroinflammation, promote neuroregeneration, and decrease spinal fibrosis degree in safe and effective pattern, which would be indicated as a novel potential cell treatment option. Graphical abstract

The construction of dams impedes energy exchange and material circulation in rivers, and the operation of hydropower stations negatively impacts the function of river ecosystems. Countries across the globe have implemented various fish protection countermeasures and conducted many associated hydraulic and ecological studies to mitigate the impact of hydropower development on fish survival, maintain the abundance and diversity of fish populations, and restore riverine and lacustrine fish migration routes and habitats. Remarkably, wild fish generally migrate in groups, whereas most contemporary studies on fish passage facilities focus on individual fish. Hence, the behavioral characteristics of fish schools are worth investigating. Given that schooling behavior is a pervasive feature of fish communities and plays an essential role in dealing with potential risks, improving self-adaptation, expanding resilience, and enhancing population sustainability, this study concentrated on investigating its effect on upstream fish migration and decoding the internal mechanism. We conducted an experiment targeting grass carp (Ctenopharyngodon idella) and silver carp (Hypophthalmichthys molitrix), two economically important freshwater fish species in China, on a non-uniform flow ground with low turbulence. The experiment quantified the impact of fish schooling on their ability to overcome flow barriers by examining the ascending sustainability and swimming performance of five-fish groups and one-fish groups at three flow velocity levels (0.25–0.50 m/s, 0.30–0.60 m/s, and 0.35–0.70 m/s) utilizing a novel index system. The new index system employed nondimensionalized ascending sustainability, first-attempt endurance, and first-attempt ascending energy consumption to indicate the fish's persistent ascending ability, ascending efficiency, and ascending energy cost, respectively. Finally, the ascending trajectory of fish was investigated simultaneously to determine the distribution of trajectory and the distribution of the hydrodynamic force factor at the trajectory points. It could be concluded that (1) the influence of schooling behavior on ascending fish behavior was related to the ascending sustainability of individual fish. Schooling behavior significantly increased the ascending sustainability while producing no specific impact on the ascending efficiency at low-level individual ascending sustainability. Inversely, schooling behavior significantly decreased the ascending efficiency while having no particular effect on high-level individual ascending sustainability. Moreover, the contribution of schooling behavior to the ascending sustainability of grass carp varied with the flow velocity, as the ascending sustainability of the five-fish groups was significantly higher (P = 0.030) and lower (P = 0.048) than the one-fish group at the velocity levels of 0.30–0.60 m/s and 0.35–0.70 m/s, respectively. In contrast, schooling behavior holistically improved the upward swimming of silver carp, significantly increasing the ascending sustainability of the five-fish groups at velocity levels of 0.30–0.60 m/s (P = 0.004) and 0.35–0.70 m/s (P < 0.001). (2) The endurance of the first attempt in the juvenile grass carp group was significantly higher than that of the single fish at the velocity levels of 0.25–0.50 m/s (P < 0.001) and 0.35–0.70 m/s (P = 0.005), while the endurance of the first attempt in the juvenile silver carp group was significantly higher than that of the single fish at the velocity levels of 0.25–0.50 m/s (P < 0.001) and 0.30–0.60 m/s (P = 0.005). The endurance of the first attempt in juvenile silver carp decreased significantly in schools (P < 0.001) solely at the velocity level of 0.35–0.70 m/s. In addition, the flow velocity generally increased the first-attempt endurance and cumulative energy consumption of individual and grouped fish. However, since the burst-coast swimming mode forced on juvenile silver carp in high-velocity conditions significantly improved ascending efficiency, the endurance of the first attempt initially increased and then decreased with the flow velocity. (3) Schooling behavior enabled grass carp to swim with less energy and significantly lowered their energy cost at the velocity level of 0.25–0.50 m/s (P < 0.001), whereas it augmented the accumulated energy consumption of five-fish groups in silver carp and significantly increased their energy cost at the velocity level of 0.25–0.50 m/s (P = 0.050). (4) Collectively, juvenile silver carp could find an ideal ascending trajectory more rapidly than juvenile grass carp. The ascending trajectory of grass carp tended to concentrate at first and then disperse with increasing velocity, whereas the trajectory of silver carp tended to concentrate with increasing velocity. In brief, schooling is an unsubstituted behavior in the upstream migration of fish migrants, motivating and inhibiting the fish's upstream movement performance with its primary effect on locomotion in terms of energy consumption, visual response, and the ability to overcome flow barriers. The findings could improve the design of fish protection measures and provide specific recommendations for the operation of fish passage facilities. For example, when silver carp migrate through a fishway, the additional light source can adequately promote schooling behavior and improve their capacity to overcome flow barriers. When grass carp migrate through a fish passage, the additional light source in the rest pond of the fishway can effectively promote schooling behavior, thereby preventing the return of fish owing to a lack of ascending sustainability. Considering that the hydrodynamic environment of natural waters and the size of fish groups are highly complex and variable, the schooling behavior characteristics of fish groups in different water flow environments should be investigated in future research to enrich the database for the planning and implementation of fish protection engineering measures.

Continuous cropping problems constitute threats to perennial plant health and survival. Soil conditioners have the potential to enhance plant disease resistance in continuous cropping systems. However, how microbes and metabolites of the rhizosphere respond to soil conditioner addition remains largely unknown, but this knowledge is paramount to providing innovative strategies to enhance plant adaptation in continuous cropping systems. Here, we found that a biochar conditioner significantly improved plant survival rates in a continuous cropping system. The biochar-induced rhizosphere significantly alters the fungal community, causing a decline in fungal diversity and the downregulation of soil microbial community functionality. Specifically, the biochar-induced rhizosphere causes a reduction in the relative abundance of pathogenic Fusarium sp. and phenolic acid concentration, whose variations are the primary causes of continuous cropping problems. Conversely, we observed an unexpected bacterial diversity increase in rhizospheric and non-rhizospheric soils. Our research further identified key microbial taxa in the biochar-induced rhizosphere, namely, Monographella, Acremonium, Geosmithia, and Funneliformis, which enhance soil nutrient availability, suppress Fusarium sp., mitigate soil acidification, and reduce phenolic acid concentrations. Collectively, we highlight the critical role of regular microbial communities and metabolites in determining plant health during continuous cropping and propose a synthetic microbial community framework for further optimizing the ecological functions of the rhizosphere.

To investigate the propagation behavior of thermal cracks on the wheel tread under the conditions of long downhill ramps, a three-dimensional finite element model of a 1/16 wheel, including an initial thermal crack, was developed using the finite element software ANSYS 17.0. The loading scenarios considered include mechanical wheel–rail loads, both with and without the superposition of thermal wheel–brake shoe friction loads. The virtual crack closure method (VCCM) is employed to analyze the variations in stress intensity factors (SIFs) for Modes I, II, and III (KI, KII, and KIII) at the 0°, mid, and 90° positions along the crack tip. The simulation results show that temperature is a critical factor for the propagation of thermal cracks. Among the SIFs, KII (Mode II) is larger than KI (Mode I) and KIII (Mode III). Specifically, the thermal load on the wheel tread during braking contributes up to 23.83% to KII when the wheel tread reaches the martensitic phase transition temperature due to brake failure. These results are consistent with the observed radial propagation of thermal cracks in wheel treads under operational conditions.

Abstract Due to the controllable degrees of freedom of frequency diverse array in the distance dimension, the frequency diverse multiple‐input multiple‐output (FDA‐MIMO) radar can easily deal with mainlobe interference, which is often difficult to solve in traditional phased arrays. Nevertheless, the performance of FDA‐MIMO radar will suffer from degradation in the scenario where spectrum interferences and signal‐dependent interferences coexist. In order to solve this problem, a novel FDA‐MIMO radar framework via antenna switching is proposed. Based on this framework, an effective method for jointly optimising antenna selection and beamforming against spectrum interferences and signal‐dependent interferences is developed. The resulting optimization problem is nonconvex and NP‐hard owing to the integer constraints caused by antenna selection. By relaxing the integer constraints, the original problem can be transformed into a convex optimization form and an iterative reweighting strategy is used to force the obtained solution to satisfy the integer constraints. Simulation examples show that the proposed algorithm has better performance in output signal‐to‐interference‐plus‐noise ratio (SINR) and beampattern radiation performance than the existing competitive methods.

Abstract Background Patients admitted to the surgical intensive care unit (SICU) often suffer from multi-organ dysfunction and have a high mortality rate. Therefore, finding a simple but effective clinical indicator to predict the prognosis of patients is essential to improve their survival. The aim of this study was to investigate the relationship between blood urea nitrogen to serum albumin ratio (B/A) and short-term mortality among patients from the SICU. Methods All eligible adult patients admitted to the SICU from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were recruited for this study. Participants were divided into a death group (n = 638) and a survival group (n = 2,048) based on the 90-day prognosis, and then grouped by B/A quartiles. We used restricted cubic splines (RCS) to visually analyze the correlation of B/A with 30- and 90-day risk of death. Cumulative survival rates were estimated using Kaplan–Meier survival curves according to B/A quartiles and evaluated using the log-rank test. Cox proportional risk models were developed and sensitivity analyses were performed to explore whether B/A was independently associated with short-term outcomes in SICU patients. Receiver operating characteristic (ROC) curves were analyzed to ascertain the value of B/A for prognosticating 90-day outcome. Results A total of 2686 participants were included in the final study, and their 30-day and 90-day all-cause mortality rates were 17.61% and 23.75%, respectively. The differences in 30-day and 90-day mortality rates were statistically significant among the four groups of patients (all p 9.69) was an independent risk factor for 30-day and 90-day all-cause mortality in SICU patients. The analysis of ROC curves demonstrated that B/A exhibited a significant predictive ability for 90-day mortality, with an optimal threshold of 6.587, a sensitivity of 56.9%, and a specificity of 64.8%. Conclusions Elevated B/A (> 9.69) on admission was an independent risk factor for short-term mortality in SICU patients, and clinicians should pay more attention to this group of patients and intervene clinically at an early stage to reduce mortality.

Abstract Transposable elements (TEs) comprise ~85% of the common wheat genome, which are highly diverse among subgenomes, possibly contribute to polyploid plasticity, but the causality is only assumed. Here, by integrating data from gene expression cap analysis and epigenome profiling via hidden Markov model in common wheat, we detect a large proportion of enhancer-like elements (ELEs) derived from TEs producing nascent noncoding transcripts, namely ELE-RNAs, which are well indicative of the regulatory activity of ELEs. Quantifying ELE-RNA transcriptome across typical developmental stages reveals that TE-initiated ELE-RNAs are mainly from RLG_famc7.3 specifically expanded in subgenome A. Acquisition of spike-specific transcription factor binding likely confers spike-specific expression of RLG_famc7.3-initiated ELE-RNAs. Knockdown of RLG_famc7.3-initiated ELE-RNAs resulted in global downregulation of spike-specific genes and abnormal spike development. These findings link TE expansion to regulatory specificity and polyploid developmental plasticity, highlighting the functional impact of TE-driven regulatory innovation on polyploid evolution.

Abstract Polyploidization is a major driver of genome diversification and environmental adaptation. However, the merger of different genomes may result in genomic conflicts, raising a major question regarding how genetic diversity is interpreted and regulated to enable environmental plasticity. By analyzing the genome-wide binding of 191 trans-factors in allopolyploid wheat, we identified like heterochromatin protein 1 (LHP1) as a master regulator of subgenome-diversified genes. Transcriptomic and epigenomic analyses of LHP1 mutants reveal its role in buffering the expression of subgenome-diversified defense genes by controlling H3K27me3 homeostasis. Stripe rust infection releases latent subgenomic variations by eliminating H3K27me3-related repression. The simultaneous inactivation of LHP1 homoeologs by CRISPR–Cas9 confers robust stripe rust resistance in wheat seedlings. The conditional repression of subgenome-diversified defenses ensures developmental plasticity to external changes, while also promoting neutral-to-non-neutral selection transitions and adaptive evolution. These findings establish an LHP1-mediated buffering system at the intersection of genotypes, environments, and phenotypes in polyploid wheat. Manipulating the epigenetic buffering capacity offers a tool to harness cryptic subgenomic variations for crop improvement.

Abstract The global trade in live wildlife elevates the risk of biological invasions by increasing colonization pressure (the number of alien species introduced to an area). Yet, our understanding of species traded as aliens remains limited. We created a comprehensive global database on live terrestrial vertebrate trade and use it to investigate the number of traded alien species, and correlates of establishment richness for aliens. We identify 7,780 species involved in this trade globally. Approximately 85.7% of these species are traded as aliens, and 12.2% of aliens establish populations. Countries with greater trading power, higher incomes, and larger human populations import more alien species. These countries, along with island nations, emerge as hotspots for establishment richness of aliens. Colonization pressure and insularity consistently promote establishment richness across countries, while socio-economic factors impact specific taxa. Governments must prioritize policies to mitigate the release or escape of traded animals and protect global biosecurity.

Workshop with different fermentation years plays an essential role in the yield and quality of Baijiu. In actual production, the quality of base Baijiu in newly built workshop is inferior to the older one. In this study, the microbiota of workshop environment and fermentation process from two workshops namely N (ferment 2 years) and O (ferment 20 years) and flavor compounds were studied during Xiasha round. Results showed workshop O accumulated more environmental microorganisms and fungi including P. kudriavzevii, Wickerhamomyces anomalus and Saccharomyces sp mainly came from ground. Yeasts including Pichia, Cyberlindnera, Wickerhamomyces and Candida were responsible for flavor substances formation in O while Saccharopolyspora was in N. This study for the first time explored the reasons for the brewing differences among N and O workshop from perspectives of workshop environment, microbial community and flavor substances, providing new ideas for guiding production as well as improvement of Baijiu quality.

Also known as Amomum tsaoko Crevost et Lemaire (A. tsaoko), is a spice and medicinal fruit plant that can be used in daily human life for cooking and health purposes. In Xishuangbanna (Yunnan Province, China) there is an interesting phenomenon where the Amomum maximum Roxb. (A. maximum) is consumed as a fruit by the local people. The spice trade played a significant role in the development of human civilization and the histories of nations. Both of them have high edible and medicinal value. The identification and classification of the metabolic components of both are key to driving the development of related industries. We used SPME-GC–MS (Non-targeted headspace-solid phase microextraction-gas chromatography-mass spectrometry) for its accurate qualitative and quantitative performance, combined with multiple analytical methods, to explain the metabolic components present in the fruits of these two plants. Next, near-infrared (NIR) technology offers researchers the advantage of saving time and being cost-effective. We analyzed the characteristic spectral chemical information of the NIR data. Identified the relevant base group and vibration mode. After analyzing the data of both, it was determined that there are a total of 66 metabolites, with 64 from cardamom and 29 from the substance, showing 37 differences. Among the metabolites, 35 had a significance level of P ≤ 0.05 and VIP ≥ 1, totaling 101 substances. This includes terpenes (37.9 %), aldehydes (12.1 %), organic heterocyclic compounds (7.6 %), alcohols (6.1 %), aromatic compounds (4.5 %), esters (4.5 %), and ketones (4.5 %). This study validates the metabolic components of the two species and provides a clear classification, which will be beneficial for future data-based applications in the fields of food and medicine.

Surgery, chemotherapy, and endocrine therapy have improved the overall survival and postoperative recurrence rates of Luminal A, Luminal B, and HER2-positive breast cancers but treatment modalities for triple-negative breast cancer (TNBC) with poor prognosis remain limited. The effective application of the rapidly developing chimeric antigen receptor (CAR)-T cell therapy in hematological tumors provides new ideas for the treatment of breast cancer. Choosing suitable and specific targets is crucial for applying CAR-T therapy for breast cancer treatment. In this paper, we summarize CAR-T therapy’s effective targets and potential targets in different subtypes based on the existing research progress, especially for TNBC. CAR-based immunotherapy has resulted in advancements in the treatment of breast cancer. CAR-macrophages, CAR-NK cells, and CAR-mesenchymal stem cells (MSCs) may be more effective and safer for treating solid tumors, such as breast cancer. However, the tumor microenvironment (TME) of breast tumors and the side effects of CAR-T therapy pose challenges to CAR-based immunotherapy. CAR-T cells and CAR-NK cells-derived exosomes are advantageous in tumor therapy. Exosomes carrying CAR for breast cancer immunotherapy are of immense research value and may provide a treatment modality with good treatment effects. In this review, we provide an overview of the development and challenges of CAR-based immunotherapy in treating different subtypes of breast cancer and discuss the progress of CAR-expressing exosomes for breast cancer treatment. We elaborate on the development of CAR-T cells in TNBC therapy and the prospects of using CAR-macrophages, CAR-NK cells, and CAR-MSCs for treating breast cancer.

Aiming at issues such as illegal dissemination of network audio data and privacy leakage, a stereo robust watermark algorithm based on parameter optimization was proposed.Firstly, the watermark was embedded by modifying the singular value ratio of odd segment based on the insensitivity of stereo channels to attack, and aiming at minimizing the relative distortion of the two channels.The embedding process was optimized and the perceived quality of the audio was improved.Then, a parameter optimization method was proposed to find optimal parameters on each audio file, and the imperceptibility and robustness were well balanced.The simulation results show that the proposed algorithm has good imperceptibility and robustness against conventional signal processing.

In most filtering algorithms involving measurement data association, handling the complex computations due to multiple hypotheses is necessary. This paper introduces a novel Trajectory Poisson Multi-Bernoulli (TPMB) filter for tracking extended targets, facilitated by a synergy between the model and the data. This filter can track extended targets under unknown process and measurement noise. Initially, on the model-driven side, we compute multi-model transition probabilities using the posterior probabilities from models at two consecutive time points with the targets in high maneuverability state. The accuracy of the tracking algorithm is improved by calculating the improved Interacting Multiple Model (IMM) transition probability at each time step. For the data-driven aspect, the Gate-control Belief Propagation (GBP) is set in the message- passing algorithm to reduce the running time of false hypothesis associations. Thus, it is unnecessary to consider all message information when computing the likelihood matrix for target-measurement associations. Subsequently, the posterior density function of the Adaptive Square Root Cubature Kalman Filter (ASCKF) is constructed to adaptively estimate unknown process and measurement noises, while importance sampling in the current particle filter further mitigates particle degradation. Experiments demonstrate that our algorithm reduces the running time of data associations, alleviates particle degradation, and more accurately tracks maneuvering targets under nonlinear conditions and estimates their states.

Assessing Sustainable Development Goal (SDG) indicator 15.3.1, which refers to the proportion of degraded land to total land area, and analysing its status and drivers is essential for the development of policies to promote the early achievement of SDG target 15.3 of Land Degradation Neutrality (LDN). In this study, Northeast China was selected as the study area, and the progress of indicator 15.3.1 was assessed based on the perspective of Net Primary Productivity (NPP) calculated by the CASA model. WorldPop population spatial distribution data were used as a proxy for human activities, combined with climate data to calculate the effects of changes in temperature, precipitation and population spatial distribution on vegetation NPP based on the partial correlation coefficient method and the Geodetector method. The results showed that 92.81% of the areas that passed the test of significance showed an increasing trend in vegetation NPP from 2000 to 2020. The vegetation NPP was affected by a combination of temperature, precipitation and population. The effects of temperature and precipitation on spatial differences in NPP for various vegetation types were significantly greater than those of population, but in high-density population zones, the effects of population on spatial differences in NPP were generally greater than those of temperature and precipitation. Precipitation was the main driver for spatial variation in NPP in deciduous broad-leaved forests, cultivated vegetation and thickets, while temperature was the main driver for spatial variation in NPP in evergreen coniferous forests. Generally, the warming and wetting trend in Northeast China contributed to the accumulation of NPP in cultivated vegetation, thickets, steppes and grasslands. The sensitivity of NPP to temperature and precipitation in deciduous broad-leaved and deciduous coniferous forests varied according to geographical location.

Background: Sepsis is a prevalent and severe medical condition which is frequently observed in the intensive care unit (ICU). Although numerous biomarkers have been identified to predict the prognosis of sepsis, the lactate dehydrogenase to albumin ratio (LDH/ALB ratio) has not been extensively investigated. The principal objective of this study is to assess the relationship between LDH/ALB ratio and all-cause mortality in patients with sepsis. Methods: This study included all adult critically ill patients with sepsis from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.0) database. Propensity score matching (PSM) analysis was conducted to mitigate bias, and Kaplan-Meier curves were performed to evaluate the cumulative survival across different groups. The association between the LDH/ALB ratio and mortality was examined through restricted cubic spline (RCS) analysis and Cox regression analysis. The robustness of the findings was confirmed through subgroup analyses. Additionally, the prognostic capability of the LDH/ALB ratio was further evaluated using receiver operating characteristic (ROC) curve analysis. Results: There were 6059 adult patients with sepsis enrolled in the final analysis. RCS revealed a non-linear relationship between the LDH/ALB ratio and an increased risk of ICU all-cause mortality (χ2 = 46.900, P

Evaluating the ecological vulnerability of the northwestern region of Liaoning Province, a typical ecologically vulnerable area in China, and exploring its inherent patterns help formulate effective measures for ecological protection and restoration. Existing studies in this region have focused on the county, city, or provincial level, failing to capture the overall ecological vulnerability. Based on the “sensitivity-degradation” model framework, this study employed the Analytic Hierarchy Process, Principal Component Analysis, and geographical detector methods to evaluate the ecological vulnerability in the northwestern region of Liaoning Province from 2000 to 2022 and analyzed the possible driving factors. The results showed that, from 2000 to 2022, areas with moderate or higher vulnerability accounted for an average of 64.7% of the total area, while severely and extremely vulnerable areas accounted for 32.5%. These severely and extremely vulnerable areas are mainly distributed along both banks of the Liuhe River and in the northern part of Liaoning Province, where it adjoins the Horqin Sandy Land. From 2000 to 2022, the overall ecological vulnerability in the northwestern region of Liaoning Province showed a decreasing trend, with the proportion of severe vulnerability significantly decreasing from 35.6% to 8.6%. Vegetation and land use were the primary factors leading to long-term changes in ecological vulnerability. This research can also provide an example for the similar issues in other study areas.

Abstract The zinc ion battery (ZIB) as a promising energy storage device has attracted great attention due to its high safety, low cost, high capacity, and the integrated smart functions. Herein, the working principles of smart responses, smart self‐charging, smart electrochromic as well as smart integration of the battery are summarized. Thus, this review enables to inspire researchers to design the novel functional battery devices for extending their application prospects. In addition, the critical factors associated with the performance of the smart ZIBs are comprehensively collected and discussed from the viewpoint of the intellectualized design. A profound understanding for correlating the design philosophy in cathode materials and electrolytes with the electrode interface is provided. To address the current challenging issues and the development of smart ZIB systems, a wide variety of emerging strategies regarding the integrated battery system is finally prospected.

Abstract Aim To identify the latent classes of a health‐promoting lifestyle and examine the associations of latent class profile with individual characteristics of breast cancer undergoing chemotherapy in China in order to provide some insights and recommendations for targeted and individualized health education of health‐promoting lifestyle. Design A descriptive cross‐sectional survey design was used for this work. Methods A total of 197 patients with breast cancer undergoing chemotherapy recruited from the Breast Cancer Outpatient Chemotherapy Clinic of a Grade 3A hospital were surveyed. Health‐promoting lifestyle was measured using the Health Promotion Lifestyle Profile‐II: Chinese Version Short (HPLP‐IICR). Latent class analysis was used to examine respondents' health‐promoting lifestyle patterns. Associations between the latent class membership and individual characteristics were examined using multinomial logistic regression. Results Four latent classes were identified: Class 1–Good Nutrition and Poor Physical Activity, Class 2–Poor Health Responsibility and Nutrition, Class 3–Active Health‐Promoting Lifestyle, and Class 4–Medium Spiritual Growth and Poor Other Dimensions. Younger respondents and respondents with a higher score in anxiety and depression were more likely to be classified in Class 4 rather than Class 1 or 3. Respondents with low exercise self‐efficacy were more likely to be classified in Class 4 than the others. Respondents in Class 4 had more chemotherapy symptom severity and interference, and cases of menopause were fewer in Class 4 rather than Class 3. Those in Class 4 were more likely to have been diagnosed with cancer within 3 months than those in Class 1.

ABSTRACTImproved strength-ductility synergy is not uncommon among metallic materials with gradient structures of grains and twins. In this work, we report that the texture gradient innately created in Al-Mn strips by twin-roll casting is also capable of increasing the material’s ductility without sacrificing its strength. Analyses based on crystal plasticity theory demonstrated that the underlying mechanism of this texture-gradient-induced ductility enhancement lies in the orientation-dependent slip and grain rotation, which generate backstress, alter the local stress triaxiality, and delay the fracture process. These results advocate the integration of texture gradient design into the fabrication of high-performance gradient materials.

Abstract Previous studies have shown that Ogt-mediated O-GlcNAcylation is essential for neuronal development and function. However, the function of O-GlcNAc transferase (Ogt) and O-GlcNAcylation in astrocytes remains largely unknown. Here we show that Ogt deficiency induces inflammatory activation of astrocytes in vivo and in vitro, and impairs cognitive function of mice. The restoration of O-GlcNAcylation via GlcNAc supplementation inhibits the activation of astrocytes, inflammation and improves the impaired cognitive function of Ogt deficient mice. Mechanistically, Ogt interacts with NF-κB p65 and catalyzes the O-GlcNAcylation of NF-κB p65 in astrocytes. Ogt deficiency induces the activation of NF-κB signaling pathway by promoting Gsk3β binding. Moreover, Ogt depletion induces the activation of astrocytes derived from human induced pluripotent stem cells. The restoration of O-GlcNAcylation inhibits the activation of astrocytes, inflammation and reduces Aβ plaque of AD mice in vitro and in vivo. Collectively, our study reveals a critical function of Ogt-mediated O-GlcNAcylation in astrocytes through regulating NF-κB signaling pathway.

In this study, a simple two-step heat treatment is proposed to design a TRIP metastable β-Zr alloy with good strength-ductility synergy by introducing heterogeneous α precipitates. The heterogeneous α precipitates mainly consist of necklace-like α at β grain boundaries and a small amount of randomly distributed intragranular α. Compared with the sample consisting of single β phase with yield strength of 683 MPa and ductility of 14.6%, yield strength of the designed two samples with heterogeneous α precipitates increases to 781 MPa and 842 MPa respectively, while the ductility increases to 15.3% and decreases to 13.6% respectively. The microstructure analysis shows that the dominant deformation mechanisms of the sample containing single β phase are β to α′ martensitic transformation and domaination of α′ martensite, accompanied by kinking band, and {101¯1}α′ twinning. For samples with heterogeneous α precipitates, the precipitation of α will increase the triggering stress of the kinking band, resulting in an increase in the yield strength at early stage of deformation. More importantly, the unique heterogeneous α structure brings a gently cutting effect of the necklace-like α on β grains and a traversability of the intragranular α to the growing α′ martensite, making the β to α′ martensitic transformation and domaination of α′ martensite slightly inhibited, together with the absorption and transfer of plastic deformation energy by α precipitates endow the alloy with high ductility. The present work can provide inspiration for improving the strength-ductility synergy of metastable β-Zr or β-Ti alloy through heterogeneous precipitate structure design.

{101¯2} twins were introduced into the magnesium (Mg) plate AZ31 via pre-rolling along its transverse direction. The plates, both with and without the pre-induced {101¯2} twins, were subjected to uniaxial tension along different directions. Using crystal plasticity modeling, we found that the strengthening effect of the pre-induced {101¯2} twins on the macroscopic flow stress primarily arised from the increased slip resistance caused by the boundaries, rather than the orientation hardening due to the twinning reorientation (although the latter did make its contribution in some specific loading directions). Besides, the pre-existing {101¯2} twins were found, by both experiments and simulation, to promote the activity of prismatic 〈a〉 and pyramidal in the parent matrix of the material. Further analysis showed that the enhanced non-basal slip activity is related to the {101¯2} twin boundaries' low micro Hall-Petch slope ratios of non-basal slips to basal slip. With the critical resolved shear stress (CRSS) obtained from crystal plasticity modeling and the orientation data from EBSD, a probability-based slip transfer model was proposed. The model predicts higher slip transfer probabilities and thus lower strain concentration tendencies at {101¯2} twin boundaries than that at grain boundaries, which agrees with the experimental observation that the strain localization was primarily associated with the latter. The present findings are helpful scientifically, in deepening our understanding of how the pre-induced {101¯2} twins affect the strength and slip activity of Mg alloys, and technologically, in guiding the design of the pre-strain protocol of Mg alloys.

Abstracts: Background: Tuberculosis (TB) is the leading cause of death from a single infectious disease and ranks 13th among the leading causes of death worldwide. In this study, we aimed to report the burden of TB in 204 countries and territories from 1990 to 2019 by sex, age, and socio-demographic index (SDI). Methods: Annual death number, age-standardized mortality rates (ASMR), and age-standardized disability-adjusted life year (DALY) rates (ASDR) with a 95% uncertainty interval (UI) of TB were derived from the global burden of disease (GBD) 2019 for the time period between 1990 and 2019. The association between the burden of TB and SDI was also investigated. Results: The total death number related to TB decreased by 33.6%, from 1777.5 in 1990–1179.8 in 2019, per 1000 individuals. The global ASMR and ASDR for TB were 14.64 (13.39–16.03) and 590.42 (536.85–646.42), which were 63.5% and 62.8% lower than in 1990, respectively. South Asia, Eastern Sub-Saharan Africa, Southeast Asia, and Western Sub-Saharan Africa had the largest number of TB deaths in 2019. Central Sub-Saharan Africa was the region with the highest ASMR and ASDR in 2019. India had the highest number of TB deaths, and the Central African Republic and Switzerland had the highest and lowest ASMR per 100,000 individuals, respectively. The number of deaths and DALYs were higher in males than in females and the ASDR significantly increased from the 10–14-year-old age group to the 80–84-year-old age group in both sexes. Most cases of TB were caused by drug-susceptible TB. A negative association between the regional SDI and the ASDR of TB was found. Conclusions: From 1990–2019, TB death number, ASMR, and ASDR decreased. It is important to note that, despite the decreasing burden of TB, it remains a major public health problem, especially in low SDI countries. It is necessary to design and implement suitable strategies to address the current situation.

Abstract Background and Objectives Previous studies have reported that the microvascular invasion three‐tiered grading (MiVI‐TTG) scheme is a better prognostic predictor than the two‐tiered microvascular invasion (MiVI) grading scheme in hepatocellular carcinoma. This study aims to explore the prognostic significance of MiVI‐TTG in patients undergoing liver resection for combined hepatocellular‐cholangiocarcinoma (cHCC) and to explore the risk factors for MiVI in cHCC. Methods This research included 208 patients graded as M0, M1, or M2 using the MiVI‐TTG scheme. Predictive performance was assessed by Cox regression analysis, Kaplan–Meier curve with Log rank test, Harrell's c‐index, and time‐dependent areas under the receiver operating characteristic curve (tdAUC). The clinical utility of the two schemes was evaluated by decision cure analysis (DCA). The risk factors for MiVI were evaluated using logistic regression analysis. Results Among 208 cHCC patients, the proportions of M0, M1 and M2 were 38.9%, 36.5%, and 24.5%, respectively. Patients with severe MiVI status had worse recurrence‐free survival and overall survival (OS) based on Kaplan–Meier analysis. M1, M2, and MiVI‐positive were independent risk factors for early recurrence, while M2 and MiVI‐positive were associated with overall survival (OS). MiVI‐TTG had a larger c‐index, tdAUC, and net benefit rate than the two‐tiered MiVI grading scheme for predicting recurrence free survival and OS. AFP≥400 ng/ml was the independent risk factor for MiVI, and satellite nodules were independent risk factors for M2. Conclusions MiVI‐TTG has a greater prognostic value than the two‐tiered MiVI grading scheme in patients undergoing hepatic resection for cHCC.

Engineering metastability can enhance the ductility of alloys, but it often comes at an expense of relatively low yield strength. Here, the authors fabricate a Ti-based alloy with heterogeneous laminated structures and α-nanoprecipitates that enhance yield strength without sacrificing ductility.

Abstract Background Alzheimer’s disease (AD) is a common progressive neurodegenerative disease characterized by memory impairments, and there is no effective therapy. Neural stem/progenitor cell (NSPC) has emerged as potential novel therapy for AD, and we aim to explore whether neural stem/progenitor cell therapy was effective for rodent models of AD. Methods We searched PubMed, Embase, Cochrane Library and Web of Science up to December 6, 2022. The outcomes included cognitive function, pathological features and BDNF. The GetData Graph Digitizer software (version 2.26) was applied to extract numerical values, and RevMan 5.3 and Stata 16 were used to analyze data. The SYRCLE risk of bias tool was used to assess study quality. Results We evaluated 22 mice studies and 8 rat studies. Compared to control groups, cognitive function of NSPC groups of both mice studies (SMD = − 1.96, 95% CI − 2.47 to − 1.45, I 2 = 75%, P

Abstract Background The occurrence and development of gastric cancer are related to microorganisms, which can be used as potential biomarkers of gastric cancer. Objective To screen the microbiological markers of gastric cancer from the microorganisms of gastric juice. Methods Gastric juice samples were collected from 61 healthy people and 78 patients with gastric cancer (48 cases of early gastric cancer and 30 cases of advanced gastric cancer). The bacterial 16 S rRNA V1-V4 region of gastric juice samples was sequenced. The Shannon index, Simpson index, Ace index and Chao index were used to analyze the diversity of gastric juice samples. The RDP classifier Bayesian algorithm was used to analyze the community structure of 97% OTU representative sequences with similar levels. Linear discriminant analysis and ST-test were used to analyze the differences. Six machine learning algorithms, including the logistic regression algorithm, random forest algorithm, neural network algorithm, support vector machine algorithm, Catboost algorithm and gradient lifting tree algorithm, were used to construct risk prediction models for gastric cancer and advanced gastric cancer. Results The microbiota diversity and the abundance of bacteria was different in the healthy group, early gastric cancer and advanced gastric cancer (P