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Abstract Reactive oxygen species (ROS)-associated anticancer approaches usually suffer from two limitations, i.e., insufficient ROS level and short ROS half-life. Nevertheless, no report has synchronously addressed both concerns yet. Herein, a multichannel actions-enabled nanotherapeutic platform using hollow manganese dioxide (H-MnO2) carriers to load chlorin e6 (Ce6) sonosensitizer and CO donor (e.g., Mn2(CO)10) has been constructed to maximumly elevate ROS level and trigger cascade catalysis to produce CO. Therein, intratumoral H2O2 and ultrasound as endogenous and exogeneous triggers stimulate H-MnO2 and Ce6 to produce •OH and 1O2, respectively. The further cascade reaction between ROS and Mn2(CO)10 proceeds to release CO, converting short-lived ROS into long-lived CO. Contributed by them, such a maximumly-elevated ROS accumulation and long-lived CO release successfully suppresses the progression, recurrence and metastasis of lung cancer with a prolonged survival rate. More significantly, proteomic and genomic investigations uncover that the CO-induced activation of AKT signaling pathway, NRF-2 phosphorylation and HMOX-1 overexpression induce mitochondrial dysfunction to boost anti-tumor consequences. Thus, this cascade catalysis strategy can behave as a general means to enrich ROS and trigger CO release against refractory cancers. Graphic Abstract

Abstract Background In China, economic, urbanization, and policy differences between the eastern and western regions lead to uneven healthcare resources. This disparity is more pronounced in the west due to fewer healthcare personnel per thousand individuals and imbalanced doctor-to-nurse ratios, which exacerbates healthcare challenges. This study examines the spatial distribution of human resources in maternal and child healthcare from 2016 to 2021, highlighting regional disparities and offering insights for future policy development. Methods The data were sourced from the “China Health and Family Planning Statistical Yearbook” (2017) and the “China Health and Health Statistics Yearbook” (2018–2022). This study utilized GeoDa 1.8.6 software to conduct both global and local spatial autocorrelation analyses, using China’s administrative map as the base dataset. Results From 2016 to 2021, there was an upward trend in the number of health personnel and various types of health technical personnel in Chinese maternal and child healthcare institutions. The spatial distribution of these personnel from 2016 to 2021 revealed clusters characterized as high-high, low-low, high-low and low-high. Specifically, high-high clusters were identified in Guangxi, Hunan, Jiangxi, and Guangdong provinces; low-low in Xinjiang Uygur Autonomous Region and Inner Mongolia Autonomous Region; high-low in Sichuan province; and low-high in Fujian and Anhui provinces. Conclusions From 2016 to 2021, there was evident spatial clustering of health personnel and various health technical personnel in Chinese maternal and child healthcare institutions, indicating regional imbalances.

Abstract The application of deep learning models to precision medical diagnosis often requires the aggregation of large amounts of medical data to effectively train high-quality models. However, data privacy protection mechanisms make it difficult to perform medical data collection from different medical institutions. In autism spectrum disorder (ASD) diagnosis, automatic diagnosis using multimodal information from heterogeneous data has not yet achieved satisfactory performance. To address the privacy preservation issue as well as to improve ASD diagnosis, we propose a deep learning framework using multimodal feature fusion and hypergraph neural networks for disease prediction in federated learning (FedHNN). By introducing the federated learning strategy, each local model is trained and computed independently in a distributed manner without data sharing, allowing rapid scaling of medical datasets to achieve robust and scalable deep learning predictive models. To further improve the performance with privacy preservation, we improve the hypergraph model for multimodal fusion to make it suitable for autism spectrum disorder (ASD) diagnosis tasks by capturing the complementarity and correlation between modalities through a hypergraph fusion strategy. The results demonstrate that our proposed federated learning-based prediction model is superior to all local models and outperforms other deep learning models. Overall, our proposed FedHNN has good results in the work of using multi-site data to improve the performance of ASD identification.

Abstract Cloud model similarity algorithm is an important part of cloud modelling theory. Most of the existing cloud model similarity algorithms suffer from poor discriminability, poor classification, unstable results, and low time efficiency. In this paper, a new similarity algorithm is proposed that considers the triangular cloud model distance and shape. First, according to the $${{D}}_{\text{T}}$$ D T distance formula, a new exponential closeness measure is defined, with which the distance similarity of cloud models is characterized. Then, the shape similarity is calculated according to the variance of the cloud model cloud drops. Finally, the two similarities are synthesized to define a similarity algorithm for determining the distance from the $${{D}}_{\text{T}}$$ D T distance formula and shape based on the triangular cloud model (DDTSTCM). In this paper, discriminability, stability, efficiency and theoretical interpretability are taken as the evaluation indices. Equipment security system capability evaluation experiment, cloud model differentiation simulation experiment and time series classification accuracy experiment are set up to verify the effectiveness of the algorithm in terms of the four above aspects. The experimental results show that DDTSTCM has good differentiation and excellent classification effects. In the classification experiment for the time series, the average classification accuracy of DDTSTCM reaches 91.78%, which is at least 2.78% higher than those of the other seven commonly used algorithms. The CPU running efficiency of DDTSTCM is also extremely high, and the average CPU running time of group training is always on the order of milliseconds, which effectively reduces the time cost. Finally, a case study is conducted to analyse a risk assessment problem for China’s island microgrid industry, and the evaluation results based on DDTSTCM are in line with human cognition and have good value for engineering applications. Graphical abstract

Abstract Purpose This study aimed to investigate the risk factors for liver disease comorbidity among older adults in eastern, central, and western China, and explored binary, ternary and quaternary co-morbid co-causal patterns of liver disease within a health ecological model. Method Basic information from 9,763 older adults was analyzed using data from the China Health and Retirement Longitudinal Study (CHARLS). LASSO regression was employed to identify significant predictors in eastern, central, and western China. Patterns of liver disease comorbidity were studied using association rules, and spatial distribution was analyzed using a geographic information system. Furthermore, binary, ternary, and quaternary network diagrams were constructed to illustrate the relationships between liver disease comorbidity and co-causes. Results Among the 9,763 elderly adults studied, 536 were found to have liver disease comorbidity, with binary or ternary comorbidity being the most prevalent. Provinces with a high prevalence of liver disease comorbidity were primarily concentrated in Inner Mongolia, Sichuan, and Henan. The most common comorbidity patterns identified were "liver-heart-metabolic", "liver-kidney", "liver-lung", and "liver-stomach-arthritic". In the eastern region, important combination patterns included "liver disease-metabolic disease", "liver disease-stomach disease", and "liver disease-arthritis", with the main influencing factors being sleep duration of less than 6 h, frequent drinking, female, and daily activity capability. In the central region, common combination patterns included "liver disease-heart disease", "liver disease-metabolic disease", and "liver disease-kidney disease", with the main influencing factors being an education level of primary school or below, marriage, having medical insurance, exercise, and no disabilities. In the western region, the main comorbidity patterns were "liver disease-chronic lung disease", "liver disease-stomach disease", "liver disease-heart disease", and "liver disease-arthritis", with the main influencing factors being general or poor health satisfaction, general or poor health condition, severe pain, and no disabilities. Conclusion The comorbidities associated with liver disease exhibit specific clustering patterns at both the overall and local levels. By analyzing the comorbidity patterns of liver diseases in different regions and establishing co-morbid co-causal patterns, this study offers a new perspective and scientific basis for the prevention and treatment of liver diseases.

Abstract Background Glycopyrrolate-neostigmine (G/N) for reversing neuromuscular blockade (NMB) causes fewer changes in heart rate (HR) than atropine-neostigmine (A/N). This advantage may be especially beneficial for elderly patients. Therefore, this study aimed to compare the cardiovascular effects of G/N and A/N for the reversal of NMB in elderly patients. Methods Elderly patients aged 65–80 years who were scheduled for elective non-cardiac surgery under general anesthesia were randomly assigned to the glycopyrrolate group (group G) or the atropine group (group A). Following the last administration of muscle relaxants for more than 30 min, group G received 4 ug/kg glycopyrrolate and 20 ug/kg neostigmine, while group A received 10 ug/kg atropine and 20 ug/kg neostigmine. HR, mean arterial pressure (MAP), and ST segment in lead II (ST-II) were measured 1 min before administration and 1–15 min after administration. Results HR was significantly lower in group G compared to group A at 2–8 min after administration (P

Abstract Aims Bariatric surgery results in rapid recovery of glucose control in subjects with type 2 diabetes mellitus. However, the underlying mechanisms are still largely unknown. The present study aims to clarify how bariatric surgery modifies pancreatic cell subgroup differentiation and transformation in the single‐cell RNA level. Methods Male, 8‐week‐old Zucker diabetic fatty (ZDF) rats with obesity and diabetes phenotypes were randomized into sleeve gastrectomy (Sleeve, n = 9), Roux‐en‐Y gastric bypass (RYGB, n = 9), and Sham (n = 7) groups. Two weeks after surgery, the pancreas specimen was further analyzed using single‐cell RNA‐sequencing technique. Results Two weeks after surgery, compared to the Sham group, the metabolic parameters including fasting plasma glucose, plasma insulin, and oral glucose tolerance test values were dramatically improved after RYGB and Sleeve procedures (p

BackgroundPrevious observational studies have reported a possible association between circulating lipids and lipid-lowering drugs and male infertility (MIF), as well as the mediating role of circulating vitamin D. Then, due to issues such as bias, reverse causality, and residual confounding, inferring causal relationships from these studies may be challenging. Therefore, this study aims to explore the effects of circulating lipids and lipid-lowering drugs on MIF through Mendelian randomization (MR) analysis and evaluate the mediating role of vitamin D.MethodGenetic variations related to lipid traits and the lipid-lowering effect of lipid modification targets are extracted from the Global Alliance for Lipid Genetics Genome-Wide Association Study. The summary statistics for MIF are from the FinnGen 9th edition. Using quantitative expression feature loci data from relevant organizations to obtain genetic variations related to gene expression level, further to explore the relationship between these target gene expression levels and MIF risk. Two-step MR analysis is used to explore the mediating role of vitamin D. Multiple sensitivity analysis methods (co-localization analysis, Egger intercept test, Cochrane’s Q test, pleiotropy residuals and outliers (MR-PRESSO), and the leave-one-out method) are used to demonstrate the reliability of our results.ResultIn our study, we observed that lipid modification of four lipid-lowering drug targets was associated with MIF risk, the LDLR activator (equivalent to a 1-SD decrease in LDL-C) (OR=1.94, 95% CI 1.14-3.28, FDR=0.040), LPL activator (equivalent to a 1-SD decrease in TG) (OR=1.86, 95% CI 1.25-2.76, FDR=0.022), and CETP inhibitor (equivalent to a 1-SD increase in HDL-C) (OR=1.28, 95% CI 1.07-1.53, FDR=0.035) were associated with a higher risk of MIF. The HMGCR inhibitor (equivalent to a 1-SD decrease in LDL-C) was associated with a lower risk of MIF (OR=0.38, 95% CI 0.17-0.83, FDR=0.39). Lipid-modifying effects of three targets were partially mediated by serum vitamin D levels. Mediation was 0.035 (LDLR activator), 0.012 (LPL activator), and 0.030 (CETP inhibitor), with mediation ratios of 5.34% (LDLR activator), 1.94% (LPL activator), and 12.2% (CETP inhibitor), respectively. In addition, there was no evidence that lipid properties and lipid modification effects of six other lipid-lowering drug targets were associated with MIF risk. Multiple sensitivity analysis methods revealed insignificant evidence of bias arising from pleiotropy or genetic confounding.ConclusionThis study did not support lipid traits (LDL-C, HDL-C, TG, Apo-A1, and Apo-B) as pathogenic risk factors for MIF. It emphasized that LPL, LDLR, CETP, and HMGCR were promising drug targets for improving male fertility.

ObjectiveWhile the pain threshold index (PTI) holds potential as a tool for monitoring analgesia-pain equilibrium, its precision in forecasting postoperative pain in children remains unconfirmed. This study's primary aim was to assess the PTI's predictive precision for postoperative pain.MethodsChildren (aged 2–16 years) undergoing general surgery under general anesthesia were included. Within 5 min prior to the patient's emergence from surgery, data including PTI, wavelet index (WLI), heart rates (HR) and mean arterial pressure (MAP) were collected. Subsequently, a 15-min pain assessment was conducted following the patient's awakening. The accuracy of these indicators in discerning between mild and moderate to severe postoperative pain was evaluated through receiver operating characteristic (ROC) analysis.ResultsThe analysis encompassed data from 90 children. ROC analysis showed that PTI was slightly better than HR, MAP and WLI in predicting postoperative pain, but its predictive value was limited. The area under the curve (AUC) was 0.659 [0.537∼0.780] and the optimal threshold was 65[64–67]. Sensitivity and specificity were determined at 0.90 and 0.50, respectively. In a multivariable logistic regression model, a higher predictive accuracy was found for a multivariable predictor combining PTI values with gender, BMI, HR and MAP (AUC, 0.768; 95%CI, 0.669–0.866). Upon further scrutinizing the age groups, PTI's AUC was 0.796 for children aged 9–16, 0.656 for those aged 4–8, and 0.601 for younger individuals.ConclusionsPTI, when used alone, lacks acceptable accuracy in predicting postoperative pain in children aged 2 to 16 years. However, when combined with other factors, it shows improved predictive accuracy. Notably, PTI appears to be more accurate in older children.

Abstract Background Postoperative pain is common in pediatric urological surgery. The study assess the impact of perioperative intravenous infusion of low-dose esketamine on postoperative pain in pediatric urological surgery. Methods Pediatric patients (n = 80) undergoing urological surgery were randomized into four groups. Patients in the control group were administered an analgesic pump containing only hydromorphone at a dose of 0.1 mg/kg (Hydromorphone Group 1, H1) or 0.15 mg/kg (Hydromorphone Group 2, H2). Patients in the experimental group were injected intravenously with 0.3 mg/kg of esketamine (Esketamine group 1, ES1) or equal volume of saline (Esketamine Group 2, ES2) during anesthesia induction. Esketamine 1.0 mg/kg and hydromorphone 0.1 mg/kg were added to the analgesic pump. Face, Leg, Activity, Crying, and Comfort (FLACC) scale or the Numerical Rating Scale (NRS) and adverse effects were recorded at 2, 6, 24, and 48 h postoperatively. Additionally, total and effective PCA button presses were recorded. Results In comparison to the H1 group, the pain scores were notably reduced at all postoperative time points in both the ES1 and H2 groups. The ES2 group exhibited lower pain scores only at 24 and 48 h postoperatively. When compared to the H2 group, there were no significant differences in pain scores at various postoperative time points in the ES2 group. However, the ES1 group demonstrated significantly lower pain scores at 6, 24 and 48 h postoperatively, and these scores were also significantly lower than those observed in the ES2 group. The total and effective number of PCA button presses in the ES1, ES2 and H2 group were lower than that in the H1 group (P

Few-shot human action recognition, a prominent area in computer vision, has garnered increasing attention and broader use in real-life scenarios. Extracting spatio-temporal skeletal information from human movement videos offers interpretable and data-efficient features. However, existing spatio-temporal feature encoders face challenges such as handling sequence boundaries and coping with noise. In order to solve the above problems, this paper proposes a temporal complement method to optimize the Dynamic Time Warping (DTW) algorithm based on the feature representation of the human skeleton sequence. DTW helps to find optimal alignment between sequences by warping them in the time domain. This is quite useful specially in scenarios where training data is limited. However, DTW has the drawback that the optimal alignment path is highly sensitive to errors in the time series distance matrix. Therefore, we apply a Virtual Adversarial Training method to improve the anti-noise capability of the algorithm. Here, We introduce adversarial perturbations in the training phase to the time series distance matrix, thus incentivizing the model to be resilient to such noise. Our method achieves highest accuracy among protonet, DTW and DASTM methods for the 5-way-1-shot setting for the NTU-S (77.7%), and Kinetics (41.2%) datasets. For the 5-way-5-shot setting, our method achieves highest accuracy of 51.8% for Kinetics dataset when compared with the other approaches.

With the popularization of intelligent cars, users’ understanding of the value of cars gradually changes from a travel tool to a “third living space”, and cabin comfort is becoming a criterion for evaluating the goodness of cars. In this paper, we start from the physical environment and human-computer interaction environment that affect the comfort of the intelligent cockpit of a car and establish a comprehensive comfort evaluation model of the intelligent cockpit of a car based on the support vector machine (SVM) algorithm in machine learning by conducting experiments on the comfort evaluation of the intelligent cockpit of a car and compare it with several classical machine learning algorithms. The mean square error ( $MSE$ ) of the model based on the SVM algorithm is 0.00096, and the coefficient of determination ( $R^{2}$ ) reaches 0.966, which is better than several other algorithms. The results show that the established evaluation model has good generalization ability and can evaluate the comprehensive comfort of the intelligent cockpit of the car, thus helping the cockpit to make timely and accurate comfort adjustments to ensure the occupant’s riding experience. This project provides a reference direction for the comprehensive evaluation of cockpit comfort, which is of great significance for the future development of intelligent cockpit comfort. In addition, the comfort model can be applied to a variety of comfort evaluation scenarios, which has great practical value.

Abstract Background Postpartum depression (PPD) is a common mental disease in postpartum women, which has received more and more attention in society. Ketamine has been confirmed for its rapid antidepressant effect in women with PPD. We speculate that esketamine, an enantiomer of ketamine, pretreatment during cesarean can also reduce the incidence of PPD. Methods All the parturients enrolled in the study were randomly assigned to two groups: the esktamine group (0.2 mg/kg esketamine) and the control group (a same volume of saline). All the drugs were pumped for 40 min started from the beginning of the surgery. The Amsterdam Anxiety and Information Scale (APAIS) scores before the surgery, the Edinburgh postnatal depression scale (EPDS) scores at 4 d and 42 d after surgery, the Pain Numerical Rating Scale (NRS) scores at 6 h, 12 h, 24 h and 48 h post-operation were evaluated, as well as the adverse reactions were recorded. Results A total of 319 parturients were analyzed in the study. The incidence of PPD (EPDS score > 9) in the esketamine group was lower than the control group at 4 days after surgery (13.8% vs 23.1%, P = 0.0430) but not 42 days after surgery (P = 0.0987). Esketamine 0.2 mg/kg could reduce the NRS score at 6 h,12 h and 24 h after surgery, as well as the use of vasoactive drugs during surgery (P 9) at 4 days after delivery but not 42 days. Esketamine reduced the NRS scores at 6 h, 12 h and 24 h after surgery, but the occurrence of maternal side effects such as dizziness, blurred vision, drowsiness and hallucination were increased. Trial registration Registered in the Chinese Clinical Trial Registry (ChiCTR2100053422) on 20/11/2021.

IntroductionSalinization damages soil system health and influences microbial communities structure and function. The response of microbial functions involved in the nutrient cycle to soil salinization is a valuable scientific question. However, our knowledge of the microbial metabolism functions in salinized soil and their response to salinity in arid desert environments is inadequate.MethodsHere, we applied metagenomics technology to investigate the response of microbial carbon (C), nitrogen (N), phosphorus (P), and sulfur (S) cycling and the key genes to salinity, and discuss the effects of edaphic variables on microbial functions.ResultsWe found that carbon fixation dominated the carbon cycle. Nitrogen fixation, denitrification, assimilatory nitrate reduction (ANRA), and nitrogen degradation were commonly identified as the most abundant processes in the nitrogen cycle. Organic phosphorus dissolution and phosphorus absorption/transport were the most enriched P metabolic functions, while sulfur metabolism was dominated by assimilatory sulfate reduction (ASR), organic sulfur transformation, and linkages between inorganic and organic sulfur transformation. Increasing salinity inhibited carbon degradation, nitrogen fixation, nitrogen degradation, anammox, ANRA, phosphorus absorption and transport, and the majority of processes in sulfur metabolism. However, some of the metabolic pathway and key genes showed a positive response to salinization, such as carbon fixation (facA, pccA, korAB), denitrification (narG, nirK, norBC, nosZ), ANRA (nasA, nirA), and organic phosphorus dissolution processes (pstABCS, phnCD, ugpAB). High salinity reduced the network complexity in the soil communities. Even so, the saline microbial community presented highly cooperative interactions. The soil water content had significantly correlations with C metabolic genes. The SOC, N, and P contents were significantly correlated with C, N, P, and S network complexity and functional genes. AP, NH4+, and NO3− directly promote carbon fixation, denitrification, nitrogen degradation, organic P solubilization and mineralization, P uptake and transport, ASR, and organic sulfur transformation processes.ConclusionSoil salinity in arid region inhibited multiple metabolic functions, but prompted the function of carbon fixation, denitrification, ANRA, and organic phosphorus dissolution. Soil salinity was the most important factor driving microbial functions, and nutrient availability also played important roles in regulating nutrient cycling.

Objective: This study aimed to investigate the selected anatomical factors that can potentially influence temporomandibular joint (TMJ) clicking in young adults by assessing TMJ structures and lateral pterygoid muscle (LPM) function using magnetic resonance imaging (MRI).Methods: The patients were divided into four groups: the healthy control group; the clicking on mouth opening group; the clicking on mouth closing group; and the clicking on mouth opening and closing group. Additionally, we used clinical palpation to evaluate the masticatory muscles' functional state and employed MRI using the OCOR-T1WI-FSE-CLOSED, OSAG-PDW-FSE-CLOSED, and OSAG-PDW-FSE-OPEN sequences to analyze the texture of the lateral pterygoid muscle (LPM).Results: The proportion of any articular disc or condylar morphology class did not differ significantly between the TMJ clicking and HC groups. The articular disc position did not differ significantly between the TMJ clicking and HC groups. In the TMJ clicking group, the presence of masticatory muscle dysfunction differed significantly between the clicking and non-clicking sides. Moreover, the LPM accounted for the highest proportion among masticatory muscles with tenderness in all TMJ clicking subgroups (77.78%–100%). Therefore, in the TMJ clicking group, the LPM texture was less defined, more uniform in gray scale, and more similar to local texture (p < 0.0001).Conclusion: The occurrence of TMJ clicking in young adults is unrelated to the TMJ structure but related to the function of masticatory muscles, particularly the LPM.

Objective: Ramucirumab is a VEGFR2 antagonist. The aim of this trial is to evaluate the efficacy and safety of ramucirumab combined with nab-paclitaxel, lobaplatin and S-1 in neoadjuvant and conversion therapy for advanced gastric cancer. Methods: and analysis: This study is a prospective single-center, randomized controlled and open label clinical study, enrolling a total of 140 patients with advanced gastric cancer distributed across two distinct cohorts (Cohort A n = 70; Cohort B n = 70). The central focus of the study lies in evaluating the pathological complete response (pCR) of the cancer post-neoadjuvant or conversion therapy. Secondary endpoints encompass the assessment of the R0 resection rate subsequent to the aforementioned therapies, the occurrence of adverse events (AE), progression-free survival (PFS), overall survival (OS), the objective response rate (ORR), the total response rate and its duration, the disease control rate (DCR), and the duration of overall response (DOR). Ethics: Ethics approval has been obtained from the Ethics Committee at the First Affiliated Hospital (Xijing Hospital) of Air force Military Medical University (KY20232220–F-1). Trial registration: This trial has been registered at the ClinicalTrials.gov: NCT06169410 (registration date: December 5, 2023).

In order to resolve the issues of low efficiency and poor precision in the traditional finishing process of hardened internal gears, a method is proposed for calculating the profile curves of a drum-shaped grinding tool suitable for mass finishing of hardened internal gears. Additionally, the impact of drum-shaped grinding tool installation errors on the tooth surface deviation of internal gears is analyzed. Firstly, the processing principle for the generation grinding of internal gears by the drum-shaped grinding tool is introduced. Based on differential geometry, meshing theory, and two-degree-of-freedom enveloping method, a mathematical model is developed for the generation grinding of internal gears. Profile curves of the drum-shaped grinding tool are obtained by solving the meshing equation between the drum-shaped grinding tool and the internal gear. Then, the tooth surface equation for the internal gear is derived in the presence of drum-shaped grinding tool installation errors. By discretizing the error tooth surface of the internal gear, the average normal deviation of the tooth surface is calculated. In the end, the distribution of normal deviation on the tooth surface of the internal gear with different drum-shaped grinding tool installation errors is acquired, and the influence of four kinds of installation errors on the tooth surface of the internal gear is analyzed. The sensitive direction is identified for drum-shaped grinding tool installation errors on the tooth surface of the internal gear. Consequently, this research provides a calculation method for the drum-shaped grinding tool fit for high-precision and high-efficiency finishing of mass-produced hardened internal gear and offers a reference for correcting deviation in the tooth surface of internal gear with installation errors of the drum-shaped grinding tool.

Background: Resveratrol is a potent phytochemical known for its potential in treating cardiometabolic multimorbidity. However, its underlying mechanisms remain unclear. Our study systematically investigates the effects of resveratrol on cardiometabolic multimorbidity and elucidates its mechanisms using network pharmacology and molecular docking techniques. Methods: We screened cardiometabolic multimorbidity-related targets using the OMIM, GeneCards, and DisGeNET databases, and utilized the DSigDB drug characterization database to predict resveratrol’s effects on cardiometabolic multimorbidity. Target identification for resveratrol was conducted using the TCMSP, SymMap, DrugBank, Swiss Target Prediction, CTD, and UniProt databases. SwissADME and ADMETlab 2.0 simulations were used to predict drug similarity and toxicity profiles of resveratrol. Protein–protein interaction (PPI) networks were constructed using Cytoscape 3.9.1 software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed via the DAVID online platform, and target-pathway networks were established. Molecular docking validated interactions between core targets and resveratrol, followed by molecular dynamics simulations on the optimal core proteins identified through docking. Differential analysis using the GEO dataset validated resveratrol as a core target in cardiometabolic multimorbidity. Results: A total of 585 cardiometabolic multimorbidity target genes were identified, and the predicted results indicated that the phytochemical resveratrol could be a major therapeutic agent for cardiometabolic multimorbidity. SwissADME simulations showed that resveratrol has potential drug-like activity with minimal toxicity. Additionally, 6703 targets of resveratrol were screened. GO and KEGG analyses revealed that the main biological processes involved included positive regulation of cell proliferation, positive regulation of gene expression, and response to estradiol. Significant pathways related to MAPK and PI3K-Akt signaling pathways were also identified. Molecular docking and molecular dynamics simulations demonstrated strong interactions between resveratrol and core targets such as MAPK and EGFR. Conclusions: This study predicts potential targets and pathways of resveratrol in treating cardiometabolic multimorbidity, offering a new research direction for understanding its molecular mechanisms. Additionally, it establishes a theoretical foundation for the clinical application of resveratrol.

BackgroundBaseline serological biomarkers have the potential to predict the benefits of adjuvant chemotherapy in patients with gastric cancer. However, the fluctuating nature of postoperative recurrence risk makes precise treatment challenging. We aimed to develop a risk score in real-time predicting outcomes for postoperative GC patients using blood chemistry tests.Materials and methodsThis was a retrospective, multicentre, longitudinal cohort study from three cancer centres in China, with a total of 2737 GC patients in the pTNM stage Ib to III. Among them, 1651 patients with at least two serological records were assigned to the training cohort. Model validation was carried out using separate testing data with area under curve (AUC). The least absolute shrinkage and selection operator (LASSO) and random forest-recursive feature elimination (RF-RFE) algorithm were used to select the parameters.ResultsThe Cox regression model derived six risk factors to construct a composite score (low-risk: 0-2 score; high risk: 3-6 score), including CEA, CA125, CA199, haemoglobin, albumin, and neutrophil to lymphocyte ratio. The risk score accurately predicted mortality in 1000-time bootstrap (AUROCs:0.658; 95% CI: 0.645, 0.670), with the highest AUROC (0.767; 95% CI: 0.743, 0.791) after 1 year since the gastrectomy. In validation dataset, the risk score had an AUROC of 0.586 (95% CI 0.544, 0.628). Furthermore, patients with high risk at 1 month derived significant clinical benefits from adjuvant chemotherapy (P for interaction

Cancer stem cells (CSCs) are highly related to initiate metastasis and drive tumor relapse/propagation, and the induced cancer stemness and plasticity render cancer intractable to various therapeutic approaches. To address them, a CSC membrane‐based fusion strategy is presented to target and attenuate cancer stemness and plasticity, and accordingly homogenous CSC‐inherited fusion membrane‐coated biomimetic nanoeffectors based on doxorubicin‐loaded hydroxyapatite nanoparticles are engineered. Such biomimetic nanoeffectors coated with fusion membrane consisting of CSCs and cancer cells can not only specifically target the solid breast tumor cells, but also target the latent CSCs. Systematic experiments validate that the constructed nanoeffectors disrupt energy metabolism, trigger lethal mitochondrial apoptosis, remarkably inhibit tumor proliferation, and downregulate the expressions of some target proteins associated with cancer stemness and metastasis to attenuate cancer stemness and the induced plasticity. Contributed by them, such nanoeffectors have been demonstrated to successfully hinder the progression of breast cancer, and decrease lung metastasis in two cancer metastasis mouse models. Such CSCs membrane‐based fusion membrane strategy provides a new candidate avenue rather than the currently dominant immune‐related pathway to repress cancer metastasis via targeting and attenuating cancer stemness.

BackgroundAccording to the Seventh National Census, China's fertility rate is less than 1.5, marking a significant national issue with potential risks. To counter this low birth rate, the Chinese government has relaxed family planning policies and introduced supportive measures.PurposeChanges in birth policy have attracted considerable attention from the people of China. This article aims to study the public's response to the three-child support policy using Weibo as a window. The goal is to provide a more balanced evaluation of current perspectives, enabling policymakers to formulate better fertility information, particularly when anticipating a poor public response to controversial policies.MethodologyThis research uses a crawler to gather data from Sina Weibo. Through opinion mining of Weibo posts on the three-child policy, Weibo users' online opinions on the three-child policy are analyzed from two perspectives: their attention content and sentiment tendency. Using an interrupted time series, it examines changes in online views on the policy, matching policy documents to the time nodes of Weibo posts.FindingsThe public has shown great interest in and provided short-term positive feedback on policies related to improving maternity insurance, birth rewards, and housing subsidies. In contrast, there has been a continuous negative response to policies such as extending maternity leave, which has particularly sparked concerns among women regarding future employment and marital rights protection. On social media, the public's attention to the three-child birth policy has focused mainly on the protection of women's rights, especially legal rights after childbirth, and issues related to physical and mental health. Child-rearing support and economic pressure are also hot topics, involving the daily expenses of multichild families, childcare services, and housing pressure. However, this study also revealed that infertile or single women express a strong desire to have children, but due to limitations in the personal medical insurance system, this desire has not been fully satisfied.ContributionsOur study demonstrates the feasibility of a rapid and flexible method for evaluating the public response to various three-child supportive policies in China using near real-time social media data. This information can help policy makers anticipate public responses to future pandemic three-child policies and ensure that adequate resources are dedicated to addressing increases in negative sentiment and levels of disagreement in the face of scientifically informed but controversial, restrictions.

As an emerging business modality and Internet format, live streaming e-commerce has developed rapidly since its emergence in 2016, especially since the outbreak of the COVID-19 epidemic in late 2019, when an increasing number of businesses from other industries attracted participation. However, with the development of the live streaming e-commerce industry, the industry's market environment is becoming increasingly chaotic. Therefore, during this period, government departments continuously formulate and implement relevant industry policies. In order to exploring the cooperation network structure, policy content distribution, and implementation effectiveness characteristics among publishers, this paper constructs a three-dimensional analysis framework of policy from the perspective of policy tools, policy effectiveness evaluation and policy publishers. The results show that in terms of policy tools, the overall structure of policy tools in the live streaming e-commerce industry is unreasonable, and different types of policy tools are significantly diverse. The proportion of environmental policy tools is greater than that of demand-based and supply-based policy tools, accounting for 62.97%, and among them, the tools related to industry regulation and management account for the largest proportion of the total, which greatly suppresses the enthusiasm of various entities in the industry for development. In terms of policy effectiveness evaluation, most of the policies do not formulate detailed long-, medium-, or short-term goals, nor are the policy priorities, incentive measures, or action modes perfect, indicating that the government's pushing and pulling forces for the live streaming e-commerce industry are insufficient. Finally, in the subject dimension of policy release, the synergy of relevant subjects is constantly improving, but there is also a phenomenon of over-concentration in the synergistic departments.

Abstract Fault rupture is a common phenomenon in geotechnical engineering. To prevent rupture, laneway shoring is performed, prior to which, convergence deformation, failure criteria, and fracture development in soft rocks in the fault rupture zone are carefully analyzed. Then, a supporting structure corresponding to the actual situation of the soft rock in the rupture zone is created. Herein, the water-rich laneway shoring through the fault rupture zone of the Hongqingliang coal mine located in the Inner Mongolia Autonomous Region is taken as the research object. Then, the fracture development and characteristics of argillaceous siltstones and laneway shoring cross-fault rupture zone are studied. Site inspection, indoor and field tests, theoretical analysis, numerical simulation, and field monitoring were used for systematic fracture analysis. Results indicated that laneway shoring through the fault fracture zone in the Hongqingliang coal mine could help prevent disasters. This method was extended to laneway supports built through the fault rupture zones in mines in other areas of China.

Abstract Background After the standardization, recording and follow‐up of imatinib use that significantly prolongs survival of gastrointestinal stromal tumors (GISTs), a comprehensive reassessment of the prognosis of GISTs is necessary and more conductive to treatment options. Methods A total of 2185 GISTs between 2013 and 2016 were obtained from the Surveillance, Epidemiology, and End Results database and comprised our training (n = 1456) and internal validation cohorts (n = 729). The risk factors extracted from univariate and multivariate analyses were used to establish a predictive nomogram. The model was evaluated and tested in the validation cohort internally and in 159 patients with GIST diagnosed between January 2015 and June 2017 in Xijing Hospital externally. Results The median OS was 49 months (range, 0–83 months) in the training cohort and 51 months (0–83 months) in the validation cohort. The concordance index (C‐index) of the nomogram was 0.777 (95% CI, 0.752–0.802) and 0.7787 (0.7785, bootstrap corrected) in training and internal validation cohorts, respectively, and 0.7613 (0.7579, bootstrap corrected) in the external validation cohort. Receiver operating characteristic curves and calibration curves for 1‐, 3‐, and 5‐year overall survival (OS) showed a high degree of discrimination and calibration. The area under the curve showed that the new model performed better than the TNM staging system. In addition, the model could be dynamically visualized on a webpage. Conclusion We developed a comprehensive survival prediction model for assessing the 1‐, 3‐ and 5‐year OS of patients with GIST in the postimatinib era. This predictive model outperforms the traditional TNM staging system and sheds light on the improvement of the prognostic prediction and the selection of treatment strategies for GISTs.

The response of microbiomes to salinity has been clarified in different geographic scales or ecosystems. However, how soil microbial community structure and interaction respond to salinity across wide salinity range and climatic region is still unclearly resolved. To address this issue, we examined the microbial community’s composition in saline soils from two climatic regions (coastal wetland and arid desert). Our research confirms that soil salinity had a negative effect on soil nutrient content. Salinity decreased the relative abundance of bacteria, but increased archaea abundance, leading to the shifts from bacteria dominant community to archaea dominant community. Low-water medium-salinity soil (LWMS) had the most complex archaeal community network, whereas for bacteria, the most complex bacterial community network was observed in low-water high-salinity soils (LWHS). Key microbial taxa differed in three salinity gradients. Salinity, soil water content, pH, total nitrogen (TN), and soil organic carbon (SOC) were the main driving factors for the composition of archaeal and bacterial community. Salinity directly affected archaeal community, but indirectly influenced bacteria community through SOC; pH affected archaeal community indirectly through TN, but directly affected bacterial community. Our study suggests that soil salinity dramatically influences diversity, composition, and interactions within the microbial community.

Mercury (Hg) is a highly toxic contaminant posing serious ecological and human health risks. This study investigates the Hg transfer characteristics and prediction models in a soil–lettuce system, employing bioconcentration factors (BCF), path analysis (PA), and Freundlich-type functions. A pot experiment was conducted in a greenhouse, where lettuce was grown in a range of Chinese agricultural soils (n = 21) and deliberately spiked with Hg using Hg(NO3)2 solution. The results indicated that lettuce grown in Hg-spiked acidic soils (pH < 6.5) accumulated total Hg (THg) levels up to 14.01 µg kg−1, surpassing the safe consumption limit of 10 µg kg−1. The BCF for lettuce THg was less than 1.0, suggesting a low transfer of Hg from soil to lettuce. Notably, BCF values were significantly higher in acidic soils (0.02) compared to alkaline soils (0.005). Path analysis accounted for 82% of the variation in lettuce THg content, identifying soil THg, pH, and amorphous (Amo) Al and Fe oxides as primary direct factors. Additionally, soil-available Hg (AvHg), exchangeable Hg (ExHg), clay, and organic matter (OM) were significant indirect factors affecting lettuce THg content. To validate the findings of the path analysis, an extended Freundlich-type equation was developed using stepwise multiple linear regression (SMLR). This model exhibited high predictive accuracy (R2 = 0.82, p ≤ 0.001), with soil pH, THg, and amorphous Al and Fe oxides being the key variables for predicting Hg transfer in the soil–lettuce system. The insights from this study can guide the management of safe lettuce production in Hg-contaminated soils, ensuring the mitigation of Hg exposure through agricultural produce.

In this study, a pulsed laser operating at a wavelength of 1064 nm and with a pulse width of 100 ns was utilized for the removal of paint from the surface of a 2024 aluminum alloy. The experimental investigation was conducted to analyze the influence of laser parameters on the efficacy of paint layer removal from the aircraft skin’s surface and the subsequent evolution in the microstructure of the laser-treated aluminum alloy substrate. The mechanism underlying laser cleaning was explored through simulation. The findings revealed that power density and scanning speed significantly affected the quality of cleaning. Notably, there were discernible damage thresholds and optimal cleaning parameters in repetitive frequency, with a power density of 178.25 MW/cm2, scanning speed of 500 mm/s, and repetitive frequency of 40 kHz identified as the primary optimal settings for achieving the desired cleaning effect. Thermal ablation and thermal vibration were identified as the principal mechanisms of cleaning. Moreover, laser processing induced surface dislocations and concentrated stress, accompanied by grain refinement, on the aluminum substrate.

Bifidobacterium longum subsp. infantis YLGB-1496 (YLGB-1496) is a probiotic strain isolated from human breast milk. The application of YLGB-1496 is influenced by carbohydrate utilization and genetic stability. This study used genome sequencing and morphology during continuous subculture to determine the carbohydrate utilization characteristics and genetic stability of YLGB-1496. The complete genome sequence of YLGB-1496 consists of 2,758,242 base pairs, 2442 coding sequences, and a GC content of 59.87%. A comparison of carbohydrate transport and metabolism genes of Bifidobacterium longum subsp. infantis (B. infantis) showed that YLGB-1496 was rich in glycosyl hydrolase 13, 20, 25, and 109 gene families. During continuous subculture, the growth characteristics and fermentation activity of the strain were highly stable. The bacterial cell surface and edges of the 1000th-generation strains were progressively smoother and well-defined, with no perforations or breaks in the cell wall. There were 20 SNP loci at the 1000th generation, fulfilling the requirement of belonging to the same strain. The presence of genes associated with cell adhesion and the absence of resistance genes supported the probiotic characteristics of the strain. The data obtained in this study provide insights into broad-spectrum carbohydrate utilization, genomic stability, and probiotic properties of YLGB-1496, which provide theoretical support to promote the use of YLGB-1496.

Nickel-titanium (NiTi) is the most ordinarily used shape memory alloy (SMAs), which has important implications in aerospace, medical devices and so on. However, NiTi parts were limited in their application scope and ability due to the difficulty of processing. Until the appearance of laser powder bed fusion (LPBF) technology, it overcame NiTi alloy preparation's multiple challenges and became the preferred method to fabricate NiTi alloy. Nevertheless, the NiTi parts fabricated by LPBF that have a great shortage still exist in corrosion resistance. Therefore, in this paper, a series of micro-nano structures with different characteristics were constructed in LPBF-NiTi by orthogonal experiment for the first time, which wants to explore the degree of influence of various parameters on the wettability of samples. After variance analysis, the nanolaser processing parameters which are most suitable for constructing lotus leaf structures on NiTi alloy surfaces are obtained. The surface morphology and composition were studied by SEM, XRD, EDS, and XPS, respectively. Finally, the corrosion resistance of samples was tested by electrochemical analysis. The results show that the laser power during processing has the greatest influence on the surface morphology of LPBF-NiTi alloy. And the wettability is affected by surface morphology and –CF/-CF2 adsorption. Furthermore, we compared the corrosion resistance of the superhydrophobic samples which was obtained based on the variance analysis with that of the substrate in 3.5 wt% NaCl solution. The result shows that the corrosion resistance and corrosion stability of superhydrophobic samples are brilliantly increased compared with the substrate.

The present study aims to compare the volume surface area of the condyle, the horizontal condylar axial angle and the disc-condyle angle between temporomandibular disorder (TMD) and asymptomatic volunteers, explore and analyze the relationship between the temporomandibular joint (TMJ) disc position in oblique sagittal plane and the volume surface area of the condyle in young adults with TMD symptoms. 84 young adult volunteers were received TMJ examination by Magnetic Resonance Imaging (MRI) and Cone Beam Computed Tomography (CBCT). TMD and asymptomatic volunteers were 42 each. MRI was used to assess the position of TMJ disc in the oblique sagittal plane with the condyle apex method. CBCT data were used for three-dimensional (3D) reconstruction of condyle and the measurements of the horizontal condylar axial angle and the volume surface area of the condyle. The condylar volume surface area of the TMD group was smaller than that of the asymptomatic group (p < 0.05), the disc condyle angle was larger than that of the asymptomatic group (p < 0.05), and no significant difference was found in the horizontal condylar axial angle (p > 0.05). In terms of correlation, the volume surface area of the condyle were negatively correlated with the position of the articular disc in TMD patients (p < 0.05). This significant negative correlation suggests that the possibility of disc displacement can be considered when poor condylar morphology is found.

The transient characteristics of pressure in the condenser under fault conditions have a crucial impact on the safe operation of the entire nuclear power plant. In order to ascertain whether the condenser pressure of a HPR1000 nuclear power unit meets the requirements of the steam generator, this paper establishes a mathematical model of the condenser, along with the connected steam turbine bypass steam system and circulating water system, based on Apros. The accuracy of the simulation model is verified by comparing the coasting curve of the circulating water pump with the flow change curve under the pump-tripping condition in Apros. Under the initial CCR condition and the half-side operating condition of the condenser, simulation analyses were conducted for two transient sequences involving the loss of normal external power and the simultaneous tripping of two circulating water pumps. The corresponding changes of pressure in the condenser under the transient sequence were obtained. The study reveals that, under different initial conditions and transient sequences, the condenser pressure of the unit can meet the requirements of a 12 s steam discharge to the condenser before the internal pressure of the condenser reaches the “unavailable” set value when the turbine bypass system is under the fault condition. The research findings of this paper can provide reference data for the design, commissioning, and operation of subsequent HPR1000 nuclear power plants.

Soda–lime glass has a wide range of applications in the fields of smart electronics, optical components, and precision originals. In order to investigate the effect of processing parameters on picosecond Bessel laser cutting of soda–lime glass and to achieve high-quality soda–lime glass cutting, a series of cutting experiments were conducted in this study. In this study, it was found that the machining point spacing, the incident laser energy, and the number of burst modes had a significant effect on the machining of the samples. The atomic force microscope (AFM) showed a better quality of roughness of the machined cross-section when the spacing of the machining points was 1 μm, a locally optimal solution was obtained when the number of burst modes was 2, and a locally optimal solution was also obtained when the incident laser power was 11.5 W. In this study, better machining quality was achieved for soda–lime glass of 1 mm thickness, with an average roughness of 158 nm and a local optimum of 141 nm.

Water shortages are the main factor restricting the survival and construction of shelterbelts in sandy areas. Comprehensive analysis of the water balance characteristics of forest stands is crucial for scientifically understanding and regulating the water supply of shelterbelts in sandy areas and formulating appropriate vegetation cultivation and restoration strategies. We simultaneously monitored outer-forest precipitation, canopy interception, stemflow, throughfall, forest transpiration, understory evapotranspiration, and soil moisture content changes in the Salix forest in the Kubuqi Desert during the main growing season (June–October) of 2022. The results showed that the total evapotranspiration of the forest was 185.62 mm, and the components and their proportions of precipitation during the same period were as follows: forest floor evapotranspiration, 94.43 mm (35.88%); stand transpiration, 68.34 mm (25.97%); and canopy interception, 22.85 mm (8.68%). Based on the water balance of the 0–60 cm soil layer and by integrating the changes in soil water storage and the influence of external water transport, the net runoff of the forestland was calculated to be approximately 77.58 mm; that is, the water balance requirements for growth were met. In the future, appropriate irrigation and supplementation can be carried out in June and July to ensure healthier growth in the shelterbelt, and plant photosynthesis and internal physiology can be further studied for cultivation in other desert areas.

Scaffolding is an integral temporary structural system in the field of construction engineering. However, the current scaffolding commonly has the shortcomings of low construction efficiency and high risk. This paper proposes a novel socket-type keyway steel pipe scaffolding, which can well solve the shortcomings of the existing scaffolding. Due to less research related to scaffolding in the past decades, it has resulted in a high number of scaffolding accidents. In order to avoid the occurrence of scaffolding accidents, it is necessary to systematize the study of this novel type of scaffolding. This study is an extremely important reference for the use and design of this novel type of scaffolding. To explore the ultimate load capacity and destabilization mode of the novel socket-type keyway steel pipe scaffolding, full-scale tests were conducted on the socket-type keyway steel pipe scaffolding with cantilever heights of 1.2 m and 0.5 m. The test results indicate that the ultimate load capacity of the scaffolding with a cantilever height of 1.2 m is 196 kN, and the destabilization mode is local instability. The ultimate load capacity with a cantilever height of 0.6 m is 276 kN, and the destabilization mode is half-wave buckling. This phenomenon shows that the different cantilever heights of the scaffolding have a significant effect on the load capacity and destabilization mode. Moreover, the load capacity decreases significantly with increasing cantilever length. The finite element model was established using SAP2000 v21 and compared with the test results. The error between the ultimate load capacity in the finite element linear elastic buckling analysis and the test results is 25%. The error between the calculated ultimate load capacity in the nonlinear buckling analysis considering the initial geometrical defects and the test results is 4%. Therefore, the nonlinear buckling analysis considering the initial geometrical defects is more in line with the force situation of the structure in the real situation.

It is a challenge to polish the interior surface of an additively manufactured component with complex structures and groove sizes less than 1 mm. Traditional polishing methods are disabled to polish the component, meanwhile keeping the structure intact. To overcome this challenge, small-grooved components made of aluminum alloy with sizes less than 1 mm were fabricated by a custom-made printer. A novel approach to multi-phase jet (MPJ) polishing is proposed, utilizing a self-developed polisher that incorporates solid, liquid, and gas phases. In contrast, abrasive air jet (AAJ) polishing is recommended, employing a customized polisher that combines solid and gas phases. After jet polishing, surface roughness ( Sa ) on the interior surface of grooves decreases from pristine 8.596 μ m to 0.701 μ m and 0.336 μ m via AAJ polishing and MPJ polishing, respectively, and Sa reduces 92% and 96%, correspondingly. Furthermore, a formula defining the relationship between linear energy density and unit defect volume has been developed. The optimized parameters in additive manufacturing are that linear energy density varies from 0.135 J mm ^−1 to 0.22 J mm ^−1 . The unit area defect volume achieved via the optimized parameters decreases to 1/12 of that achieved via non-optimized ones. Computational fluid dynamics simulation results reveal that material is removed by shear stress, and the alumina abrasives experience multiple collisions with the defects on the heat pipe groove, resulting in uniform material removal. This is in good agreement with the experimental results. The novel proposed setups, approach, and findings provide new insights into manufacturing complex-structured components, polishing the small-grooved structure, and keeping it unbroken.

The relationships between fine particulate matter (PM2.5) exposure and health effects are complex and incompletely understood. Evidence suggests that PM2.5 exposure alters gut microbiota composition and metabolites, but the connections between these changes remain unclear. The aim of our study was to investigate how gut microbiota are involved in the systemic metabolic changes following PM2.5 gastrointestinal exposure. We used multi-omics approaches, including 16S rRNA sequencing and serum metabolomics, to identify alterations in gut microbes and metabolites of PM2.5-exposed rats. We then explored correlations between perturbed gut microbiota and metabolic changes, and conducted pathway analyses to determine critical metabolic pathways impacted by PM2.5 exposure. To verify links between gut microbiome and metabolome disruptions, we performed fecal microbiota transplantation (FMT) experiment. A total of 30 differential gut microbe taxa were identified between PM2.5 and control groups, primarily in Firmicutes, Acidobacteria, and Proteobacteria phyla. We also identified 30 differential metabolites, including glycerophospholipids, fatty acyls, amino acids and others. Pathway analysis revealed disruptions in glycerophospholipid metabolism, steroid hormone biosynthesis, and linoleic acid metabolism. Through FMT, we confirmed PM2.5 altered phosphatidylcholine and linoleic acid metabolism by changing specific gut bacteria. Our results suggest that PM2.5 gastrointestinal exposure triggers systemic metabolic changes by disrupting the gut microbiome, especially glycerophospholipid and linoleic acid metabolism pathways.

Abstract Abnormal epigenetic regulation is identified to correlate with cancer progression and renders tumor refractory and resistant to reactive oxygen species (ROS)‐based anti‐tumor actions. To address it, a sequential ubiquitination and phosphorylation epigenetics modulation strategy is developed and exemplified by the well‐established Fe‐metal‐organic framework (Fe‐MOF)‐based chemodynamic therapy (CDT) nanoplatforms that load the 26S proteasome inhibitor (i.e., MG132). The encapsulated MG132 can blockade 26S proteasome, terminate ubiquitination, and further inhibit transcription factor phosphorylation (e.g., NF‐κB p65), which can boost pro‐apoptotic or misfolded protein accumulations, disrupt tumor homeostasis, and down‐regulate driving genes expression of metastatic colorectal cancer (mCRC). Contributed by them, Fe‐MOF‐unlocked CDT is magnified to considerably elevate ROS content for repulsing mCRC, especially after combining with macrophage membrane coating‐enabled tropism accumulation. Systematic experiments reveal the mechanism and signaling pathway of such a sequential ubiquitination and phosphorylation epigenetics modulation and explain how it could blockade ubiquitination and phosphorylation to liberate the therapy resistance to ROS and activate NF‐κB‐related acute immune responses. This unprecedented sequential epigenetics modulation lays a solid foundation to magnify oxidative stress and can serve as a general method to enhance other ROS‐based anti‐tumor methods.

It is important to be able to measure the similarity between two uncertain concepts for many real-life AI applications, such as image retrieval, collaborative filtering, risk assessment, and data clustering. Cloud models are important cognitive computing models that show promise in measuring the similarity of uncertain concepts. Here, we aim to address the shortcomings of existing cloud model similarity measurement algorithms, such as poor discrimination ability and unstable measurement results. We propose an EPTCM algorithm based on the triangular fuzzy number EW-type closeness and cloud drop variance, considering the shape and distance similarities of existing cloud models. The experimental results show that the EPTCM algorithm has good recognition and classification accuracy and is more accurate than the existing Likeness comparing method (LICM), overlap-based expectation curve (OECM), fuzzy distance-based similarity (FDCM) and multidimensional similarity cloud model (MSCM) methods. The experimental results also demonstrate that the EPTCM algorithm has successfully overcome the shortcomings of existing algorithms. In summary, the EPTCM method proposed here is effective and feasible to implement.

In 2020, the COVID-19 pandemic had a major impact on China’s foreign trade. Therefore, the Chinese government has proposed a “dual cycle” policy to promote economic development. In 2021, China’s cross-border e-commerce B2B exports accounted for 60 percent. Therefore, this paper studies the impact of government actions on the development of cross-border e-commerce B2B export enterprises under the background of “dual cycle” policy. First, the policies related to the cross-border e-commerce industry in the “dual circulation” policy are screened, and the LDA topic model is used to classify them, i.e., sorting by topic intensity as “fiscal policy”, “tax policy”, “customs clearance policy”, “payment policy” and “talent policy”. After that, based on the analysis results of the LDA topic model, a theoretical basis for the impact of different policies on cross-border e-commerce B2B export companies is established; then an evolutionary game model between the government and cross-border e-commerce B2B export enterprises is constructed. This article also carried out experiments to verify our analysis. The simulation results show that: (1) The government’s appropriate increase in subsidies, tax incentives, infrastructure investment, talent introduction and cultivation, optimized payment system, and supervision can promote enterprises to participate in cross-border e-commerce B2B export trading; (2) excessive government supervision reduces enterprises’ enthusiasm to participate in cross-border e-commerce B2B export trading; (3) the government’s subsidies, tax incentives, and supervision strength have the greatest impact on whether enterprises participate in cross-border e-commerce B2B export trading, followed by the government’s investment in cross-border e-commerce infrastructure, the introduction and cultivation of cross-border e-commerce talents, and the improvement of the payment system. Finally, this paper puts forward relevant policy recommendations to promote the development of cross-border e-commerce B2B export enterprises.

In wireless sensor networks, sensor nodes are deployed to collect data, perform calculations, and forward information to either other nodes or sink nodes. Recently, geographic routing has become extremely popular because it only requires the locations of sensor nodes and is very efficient. However, the local minimum phenomenon, which hinders greedy forwarding, is a major problem in geographic routing. This phenomenon is attributed to an area called a hole that lacks active sensors, which either prevents the packet from being forwarded to a destination node or produces a long detour path. In order to solve the hole problem, mechanisms to detect holes and determine landmark nodes have been proposed. Based on the proposed mechanisms, landmark-based routing was developed in which the source node first sends a packet to the landmark node, and the landmark node then sends the packet to the destination. However, this approach often creates a constant node sequence, causing nodes that perform routing tasks to quickly run out of energy, thus producing larger holes. In this paper, a new approach is proposed in which two virtual ellipses are created with the source, landmark, and destination nodes. Then guide the forwarding along the virtual ellipses. Furthermore, a recursive algorithm is designed to ensure a shortcut even if there are multiple holes or a hole has multiple landmarks. Thus, the proposed approach improves both geographic routing and energy efficiency routing. Simulation experiments show that the proposed approach increases the battery life of sensor nodes, lowers the end-to-end delay, and generates a short path.

SmCo7-based permanent magnets with a TbCu7-type structure have excellent high-temperature performance. However, most of the previously reported SmCo7 nanocrystalline magnets were isotropic, which limited their application. So the preparation of anisotropic SmCo7 magnets with preferred texture is still a challenge. In this work, we prepared anisotropic SmCo6.8Hf0.2 nanocrystalline magnets by hot pressing and hot deformation method. EBSD results indicated that the {0001} orientation texture of the hot deformed magnet was remarkably preferred, which further improved the remanence. Subsequently, the structural evolution process was systematically characterized by TEM. It provides crucial insight for developing high-performance SmCo7-based magnets.Impact Statement: Up to now, most of the previously reported SmCo7 nanocrystalline magnets were isotropic, which limited their application. This work opens up new opportunities to create high-performance SmCo7-based nanostructured magnets.

Abstract Under the background of automobile intelligence, cockpit comfort is receiving increasing attention, and intelligent cockpit comfort evaluation is especially important. To study the intelligent cockpit comfort evaluation model, this paper divides the intelligent cockpit comfort influencing factors into four factors and influencing indices: acoustic environment, optical environment, thermal environment, and human–computer interaction environment. The subjective and objective evaluation methods are used to obtain the subjective weights and objective weights of each index by the analytic hierarchy process and the improved entropy weight method, respectively. On this basis, the weights are combined by using the game theory viewpoint to obtain a comprehensive evaluation model of the intelligent automobile cockpit comfort. Then, the cloud algorithm was used to generate the rank comprehensive cloud model of each index for comparison. The research results found that among the four main factors affecting the intelligent automobile cockpit comfort, human–computer interaction has the greatest impact on it, followed by the thermal environment, acoustic environment, and optical environment. The results of the study can be used in intelligent cockpit design to make intelligent cockpits provide better services for people.

In the field of precision processing technology of spiral bevel gears， the processing technology of ultrasonic lapping gears has been closely followed and studied by many scholars. A vibration system of ultrasonic lapping gear is designed. Under the same conditions concerning the attribute settings， grid partition， and modal analysis settings of the material， the influences of the number， width， length and position on the resonance frequency， vibration mode， displacement node and gear deformation are analyzed by Ansys Workbench； a method for controlling the coupled vibration produced by grooving the transmitted cylinder is established， which can further enrich and improve the existing design theory of the processing vibration system for ultrasonic lapping gears.

Abstract Perioperative cardiac arrest (POCA) is associated with a high mortality rate. This work aimed to study its prognostic factors for risk mitigation by means of care management and planning. A database of 380,919 surgeries was reviewed, and 150 POCAs were curated. The main outcome was mortality prior to hospital discharge. Patient demographic, medical history, and clinical characteristics (anesthesia and surgery) were the main features. Six machine learning (ML) algorithms, including LR, SVC, RF, GBM, AdaBoost, and VotingClassifier, were explored. The last algorithm was an ensemble of the first five algorithms. k-fold cross-validation and bootstrapping minimized the prediction bias and variance, respectively. Explainers (SHAP and LIME) were used to interpret the predictions. The ensemble provided the most accurate and robust predictions (AUC = 0.90 [95% CI, 0.78–0.98]) across various age groups. The risk factors were identified by order of importance. Surprisingly, the comorbidity of hypertension was found to have a protective effect on survival, which was reported by a recent study for the first time to our knowledge. The validated ensemble classifier in aid of the explainers improved the predictive differentiation, thereby deepening our understanding of POCA prognostication. It offers a holistic model-based approach for personalized anesthesia and surgical treatment.

A mathematical model for tooth profile curve of cylinder gear with high-order modification gear surface is established. Applying two-parameter envelope theory to determine the meshing relationship between worm grinding wheel and helical gears，the transverse tooth profile is calculated. The grinding wheel dressing and gear grinding experiments are conducted on worm grinding wheel gear grinding machine. According to the results of tooth profile deviation measurement，the tooth surface modification curve is coincided with the requirements. The experiment results verify the correctness of calculation and effectiveness of dressing for worm grinding wheel profile curve.

Heart failure with preserved ejection fraction (HFpEF) is typically preceded by cardiac hypertrophy. Lycium barbarum L. as functional food show the health benefits of cardiovascular diseases. Whether Lycium barbarum L. protein-derived angiotensin-converting enzyme inhibitory peptide (ACEIP) has effects on improving cardiac hypertrophy is unknown. Here, HFpEF mouse model was established by a high-fat diet and 0.5 g/L Nѡ-Nitro-L-arginine methyl ester hydrochloride (L-NAME) in drinking water. Interventricular septum thickness (IVS), left ventricular posterior wall thickness (LVPW), left ventricular diameter (LVD), ejection fraction (EF) and left ventricular mass (LV Mass) were evaluated by transthoracic echocardiography. Serum n-terminal pro-brain natriuretic peptide (NT-proBNP), Ang II, Ang (1–7) concentrations were measured by ELISA, and hypertrophy by WGA staining. We found that ACEIP significantly improved diastolic dysfunction as reflected by the increase in mitral inflow E and A wave ratio (E/A ratio) and decrease in isovolumic relaxation time (IVRT). Meanwhile, LV Mass, IVS, LVPW and LVD in systolic or diastolic period were significantly reduced by ACEIP. Furthermore, ACEIP reversed protein kinase C β1 (PKCβ1) and extracellular signal-regulated kinase 1/2 (ERK1/2) phosphorylation, which were related to ACE2/Ang (1–7)/MasR axis activation. Our findings indicated that ACEIP could be a potential nutritional approach for the intervention of HFpEF.

ObjectiveUnhealthy foods were a major contributor to the occurrence of chronic non-communicable diseases. The promotion of nutrition labeling in the community can effectively help residents to choose healthy foods, which plays an important role in the prevention of chronic diseases. However, the public awareness of this measure is not clear. Our study used a structural equation model based on the KAP theory to analyze the interaction mechanisms among knowledge, attitude, and practice and aimed to evaluate the relationships among nutrition knowledge, attitude, and practice of residents, which can provide the basis of policy formulation for nutrition education and behavior intervention.MethodsWe carried out a cross-sectional study from May 2022 to July 2022 in the “Community Health Service Center”, and each “Community Service Station” in Yinchuan use a self-designed questionnaire and convenience sampling to evaluate resident nutrition labeling KAP status. This study adopted the structural equation modeling approach to analyze a survey of Chinese individuals through the cognitive processing model, interrelated nutrition knowledge, nutrition label knowledge, attitude, and practice.ResultsAccording to the principle of sample size estimation, a total of 636 individuals were investigated, with the ratio of male to female being 1:1.2. The average score of community residents' nutrition knowledge was 7.48 ± 3.24, and the passing rate was 19.4%. Most residents had a positive attitude toward nutrition labeling, but the awareness rate was only 32.7% and the utilization rate was 38.5%. Univariate analysis showed that women had higher knowledge scores than men (p < 0.05), and young people had higher scores than older adults (p < 0.05), and the difference was significant. Based on the KAP structural equation model (SEM), residents' nutrition knowledge will directly affect their attitude toward nutrition labeling. Attitude played a greater role as an indirect effect between knowledge and behavior, while trust limits residents' practice of nutrition labeling and then affects their practice. It could be explained that nutrition knowledge was the prerequisite for label reading behavior, and attitude was the intermediary effect.ConclusionThe nutrition knowledge and nutrition labeling knowledge of respondents hardly directly support the practice of nutrition labeling, but it can influence the use behavior by forming a positive attitude. The KAP model is suitable for explaining residents' use of nutrition labeling in the region. Future research should focus on better understanding the motivations of residents to use nutrition labeling and the opportunity to use nutrition labeling in real-life shopping settings.

With the rapid development of the automobile industry, the comfort of the cockpit has become the standard for judging the quality of the car. People have also put forward higher requirements for cockpit comfort. In the process of driving, the cockpit environment will constantly change, and the comfort will also change. When the comprehensive comfort level of the cockpit decreases and the occupants feel uncomfortable, the cockpit comfort should be adjusted. In this article, a cockpit comfort evaluation model is established to realize the evaluation of cockpit comfort. In addition, we elaborate the theory of optimal state distance, where the numerical magnitude of the optimal state distance is used to reflect the extent to which an indicator deviates from its optimal state. Also, a cockpit optimal adjustment strategy identification model is established based on the theory, which can obtain the optimal adjustment strategy in a certain cockpit operating environment, facilitate the timely adjustment of the corresponding actuator, and realize the dynamic monitoring and adjustment of cockpit comfort. This project provides a reference direction for cockpit comfort adjustment, which is of great significance for future research and development of automotive cockpit comfort.

Based on the PM6:Y6 binary system, a novel non-fullerene acceptor material, D18-Cl, was doped into the PM6:Y6 blend to fabricate the active layer. The effects of different doping ratios of D18-Cl on organic solar cells were investigated. The best-performing organic solar cell was achieved when the doping ratio of D18-Cl reached 20 wt%. It exhibited a short-circuit current of 28.13 mA/cm2, a fill factor of 70.25%, an open-circuit voltage (Voc) of 0.81 V, and a power conversion efficiency of 16.08%. The introduction of an appropriate amount of D18-Cl expanded the absorption spectrum of the active layer, improved the morphology of the active layer, reduced large molecular aggregation and defects, minimized bimolecular recombination, and optimized the collection efficiency of charge carriers. These results indicate the critical importance of selecting an appropriate third component in binary systems and optimizing the doping ratio to enhance the performance of ternary organic solar cells.