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Abstract Background Food safety stands as a critical public health concern in China. People’s perceptions and communication regarding food safety crises significantly impact their emotions and food preferences. The rise of social media has also complicated information sharing and decision-making. Exploring public’s cognitive, emotional and behaviral responses toward food safety risks is crucial for improving food safety practices and public health. Methods From fall 2018 to fall 2023, 23 in-depth interviews were held using a semi-structured protocol aligned with the Risk Analysis Framework (RAF) components: risk assessment, communication, and management. Results Our findings showed that the public blamed unethical agriculture practices and food processing for food safety issues. People, dissatisfied with mainstream media, turned to social media to collect food safety information. Many adopted self-protective behaviors, assuming personal responsibility for food safety. Conclusion Findings from this study highlighted individuals’ concerns about environmental pollution and the use of chemical substances in food safety issues. The results underscored the need for accurate and prompt media coverage, stronger government regulation, industry self-regulation, and targeted consumer education to effectively tackle these challenges.

Chronic diabetic wounds are the most common complication for diabetic patients. Due to high oxidative stress levels affecting the entire healing process, treating diabetic wounds remains a challenge. Here, we present a strategy for continuously regulating oxidative stress microenvironment by the catalyst-like magnesium-gallate metal-organic framework (Mg-GA MOF) and developing sprayable hydrogel dressing with sodium alginate/chitosan quaternary ammonium salts to treat diabetic wounds. Chitosan quaternary ammonium salts with antibacterial properties can prevent bacterial infection. The continuous release of gallic acid (GA) effectively eliminates reactive oxygen species (ROS), reduces oxidative stress, and accelerates the polarization of M1-type macrophages to M2-type, shortening the transition between inflammation and proliferative phase and maintaining redox balance. Besides, magnesium ions adjuvant therapy promotes vascular regeneration and neuronal formation by activating the expression of vascular-associated genes. Sprayable hydrogel dressings with antibacterial, antioxidant, and inflammatory regulation rapidly repair diabetic wounds by promoting neurovascular network reconstruction and accelerating re-epithelialization and collagen deposition. This study confirms the feasibility of catalyst-like MOF-contained sprayable hydrogel to regulate the microenvironment continuously and provides guidance for developing the next generation of non-drug diabetes dressings.

Abstract Objective To investigate the current situation of emergency preparation and emergency drill in the CSSD, and analyze its influence on the nurses’ emergency attitude and ability. Methods This study employed a multicenter stratified sampling method, conducted from January to June 2023 using the online survey, participants completed the general data, emergency preparedness and drill questionnaire, public health emergency response questionnaire and emergency capacity scale. An independent samples t test or Kruskal-Wallis test was used to analyse differences in nurses’ emergency capacity and attitudes. Results The data from 15 provinces 55 hospitals in China. Overall, 77.58% of participants’ institutions set up emergency management teams, 85.45% have an emergency plan and revise it regularly. 92.12% store emergency supplies. All survey staff participated in the emergency drill, which predominantly consisted of individual drills (51.52%), with 90.30% being real combat drills, 49.09% of participants engaging in drills every quarter, and 91.52% of the drill’s participants exceeding 50%. The respondents’ emergency attitude score was (29.346 ± 6.029), their emergency ability score was (63.594 ± 10.413), and those with rescue experience showed a more positive attitude (Z = -2.316, P = 0.021). Different titles, education levels, rescue experience and the frequency of emergency drill affected the emergency rescue ability of the respondents (P

Abstract In this study, We aim to explore the association between the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), lymphocyte to monocyte ratio (LMR) and prognostic nutritional index (PNI) and distant metastasis of gastric cancer and develop an efficient nomogram for screening patients with distant metastasis. A total of 1281 inpatients with gastric cancer were enrolled and divided into the training and validation set.Univariate, Lasso regression and Multivariate Logistic Regression Analysis was used to identify the risk factors of distant metastasis. The independent predictive factors were then enrolled in the nomogram model. The nomogram’s predictive perform and clinical practicality was evaluated by receiver operating characteristics (ROC) curves, calibration curves and decision curve analysis. Multivariate Logistic Regression Analysis identified d-dimer, CA199, CA125, NLR and PNI as independent predictive factors. The area under the curve of our nomogram based on these factors was 0.838 in the training cohort and 0.811 in the validation cohort. The calibration plots and decision curves demonstrated the nomogram’s good predictive performance and clinical practicality in both training and validation cohort. Therefore,our nomogram could be an important tool for clinicians in screening gastric cancer patients with distant metastasis.

Background: Triple-negative breast cancer (TNBC) is a subtype of breast cancer characterized by poor prognosis due to the absence of effective targeted therapies. Emerging evidence indicates that the gut microbiota and its metabolites play a key role in the occurrence and development of TNBC. This study aimed to explore the metabolic changes and potential mechanisms associated with TNBC. Objectives: This study aimed to explore the potential relationship between targeted metabolites and the gut microbiota in TNBC. Design: We recruited 8 participants, including 4 with TNBC and 4 with benign fibroadenomas as controls. Methods: The gut microbiota was analyzed using metagenomics on fecal samples. Liquid chromatography–mass spectrometry (LC-MS) was employed to identify differential metabolites in serum and fecal samples. The correlation between the gut microbiota and metabolites was analyzed using Spearman’s correlation analysis. Results: Analysis of altered serum metabolites in the TNBC group revealed changes, particularly in carboxylic acids and derivatives, benzene, and substituted derivatives. Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway analysis revealed significant enrichment in 18 pathways. Regarding fecal metabolites, differences between the 2 groups also included carboxylic acids and derivatives, benzene, and substituted derivatives, with 28 metabolic pathways enriched based on KEGG pathway analysis. Metagenomics analysis showed differences in the relative abundance of Anaerococcus , Fischerella , and Schizosaccharomyces at the genus level, which have been previously associated with breast cancer. Furthermore, 4 serum metabolites—L-glutamine, citrate, creatinine, and creatine—along with 9 fecal metabolites, were associated with the aforementioned microbiota. Conclusion: Our findings highlight distinct metabolite profiles in the serum and feces of patients with TNBC. The identification of gut microbiota and their associated metabolites provides new insights into the pathophysiological mechanisms underlying TNBC.

Abstract To identify different patterns of neurogenic lower urinary tract dysfunction management among Chinese community-dwelling individuals with spinal cord injury and explore the factors associated with latent classes. This was a cross-sectional study conducted in communities throughout China Mainland. Participants were recruited through the China Association of Persons with Physical Disability and a total of 2582 participants was included in the analysis. The data were collected by a questionnaire consisting of socio-demographic factors, disease-related factors, and a list of 8 bladder management methods. Latent class analysis was used to identify different latent classes of neurogenic lower urinary tract dysfunction management. Then the multinomial logistic regression was applied to analyze the relationship between neurogenic lower urinary tract dysfunction management patterns and socio-demographic and disease-related factors. Neurogenic lower urinary tract dysfunction management pattern among community-dwelling individuals with spinal cord injury was divided into four latent classes: “urinal collecting apparatus dominated pattern” (40.3%), “bladder compression dominated pattern” (30.7%), “intermittent catheterization dominated pattern” (19.3%) and “urethral indwelling catheterization dominated pattern” (9.6%). Multinomial logistic regression analysis found that the employment status, residential region, nursing need, payment method for catheterization products, hand function, time since spinal cord injury, urinary incontinence and concerns about social interaction affected by urination problems were significantly associated with latent classes. Only 19.3% of people used the intermittent catheterization as their main neurogenic lower urinary tract dysfunction management method. More attention needs to be paid to the promotion of the standardization process of intermittent catheterization in community-dwelling individuals with spinal cord injury. The associated factors of the four classes can be used for tailored and targeted interventions to increase the use of intermittent catheterization.

Abstract Background Reintroduction represents an effective strategy for the conservation of endangered wildlife, yet it might inadvertently impact the native ecosystems. This investigation assesses the impact of reintroducing endangered Przewalski's horses into the desert grassland ecosystem of the Kalamaili Nature Reserve (KNR), particularly its effect on the spatial distribution of ticks. In a 25 km2 core area of Przewalski's horse distribution, we set up 441 tick sampling sites across diverse habitats, including water sources, donkey trails, and grasslands, recording horse feces and characteristics to analyze the occurrence rate of ticks. Additionally, we gathered the data of 669 fresh feces of horses. To evaluate the spatial dynamics between these feces and ticks, we used methods such as Fixed Kernel Estimation (FKE), Moran’s I spatial autocorrelation index, and Generalized Linear Models (GLM). Results The dominant species of ticks collected in the core area were adult Hyalomma asiaticum (91.36%). Their occurrence rate was higher near donkey trails (65.99%) and water sources (55.81%), particularly in areas with the fresh feces of Przewalski's horses. The ticks’ three risk areas, as defined by FKE, showed significant overlap and positive correlation with the distribution of Przewalski's horses, with respective overlap rates being 90.25% in high risk, 33.79% in medium risk, and 23.09% in low risk areas. Moran's I analysis revealed a clustering trend of the fresh feces of Przewalski's horses in these areas. The GLM confirmed a positive correlation between the distribution of H. asiaticum and the presence of horse fresh feces, alongside a negative correlation with the proximity to water sources and donkey trails. Conclusions This study reveals the strong spatial correlation between Przewalski's horses and H. asiaticum in desert grasslands, underlining the need to consider interspecific interactions in wildlife reintroductions. The findings are crucial for shaping effective strategies of wildlife conservation and maintaining ecological balance.

【Objective】Functional modifications of plant histones, including acetylation modification and methylation modification, play important roles in plant growth and development and in response to adversity. The biological functions and molecular mechanisms of the histone modification (HM) gene family in tomato are still unclear. The present study aims to further clarify the biological functions of the HM genes in tomato, and to lay a foundation for the study of their molecular mechanisms and genetic improvement of tomato.【Method】We identified tomato HM members based on the tomato genome database, systematically analyzed the phylogeny, gene structure, and chromosomal localization of its HM gene family members with bioinformatics methods, and analyzed the spatio-temporal expression patterns of the tomato HM gene family through an online transcriptome database.【Result】A total of 148 tomato HM genes were identified in this study, including 32 encoded histone acetyltransferase (HAT), 11 encoded histone deacetylase (HDAC), 50 encoded histone methyltransferase (HMT), and 55 encoded histone demethylase (HDM). The 148 genes were unevenly distributed on different chromosomes, with the highest number of genes on chromosome 3 (21 genes) and the lowest number of genes on chromosome 12 (4 genes). Gene structure characterization showed that the exons varied greatly among tomato HM genes, with the most exons amounting to 34 and the least to only 1. Protein structure domain analysis showed that Solyc07g064130, Solyc11g005670 and Solyc10g006480 contained only the Ubl structure domains, Solyc07g062100, Solyc10g077110 and Solyc03g083310 contained only the Zn-finger structure domain, another 10 proteins contain the Bromo structure domain, 48 proteins contained only the SET structure domain, and other proteins contained other structure domains such as PLN02529 and PRMT5. In addition, the homologous proteins of tomato HM were distantly related to those of both Arabidopsis and Oryza sativa, and the protein sequences of the tomato HM were more closely related to those of the Arabidopsis thaliana than to those of Oryza sativa. Based on the clustering analysis, the tomato HM members were divided into four families, HAT, HDAC, HMT, and HDM. Tissue expression analysis showed that the HAT family was highly expressed in flowers at 30 d after germination (F30), fruits at 10 d post-anthesis (10DPA), flowers (fr), roots (rr), and immature fruits (Plgfr); the HDAC family was highly expressed in flowers (F30) and immature fruits (Plgfr); the HMT family was highly expressed in flowers (F30), when 50% of the whole plant flowers open (F45), flower buds (br), 3 cm fruits (3fr), and immature 5 cm fruits (PB+5fr); the HDM family was highly expressed in flowers (F30), when 50% of the whole plant flowers open (F45), flower buds (br), flowers (fr), roots (rr), 3 cm fruits (3fr), and immature 5 cm fruits (PB+5fr).【Conclusion】The gene structures of different tomato HM vary greatly and contain multiple functional structural domains. The homologous members of tomato HM are distant from those of Arabidopsis thaliana and Oryza sativa, and tomato HM are expressed in different growth and developmental stages of plants and in different organ tissues, suggesting that this class of genes may be involved in a variety of growth and developmental processes in tomato.

Spontaneous combustion of coal in goaf is one of the main factors inducing mine fire, which accounts for 90% of mine fire. In order to achieve accurate prevention and control of spontaneous combustion in goaf, it is necessary to accurately obtain the high temperature point temperature in goaf. Based on Yanbei Coal Mine as the engineering background, this paper analyzes the index gases produced during the oxidation and heating process of coal samples, establishes the index system of coal spontaneous combustion temperature prediction, and then carries out the research of multi-index gas coal spontaneous combustion temperature prediction based on deep learning. Firstly, the coal samples collected from Yanbei Coal Mine were tested for coal oxidation and temperature rise. According to the experimental results, they were divided into single gas index and compound gas index. The change law of each index with temperature rise was analyzed, and the appropriate index was determined as the prediction index of coal spontaneous combustion temperature. The prediction index of coal spontaneous combustion temperature is processed by multi-source data processing method, the data is cleaned by Cook distance method and multiple interpolation method, and the prediction index system of coal spontaneous combustion temperature is established by grey correlation analysis method. Elman neural network was used to build a prediction model, and after determining the model structure and hyper-parameters, a prediction model of coal spontaneous combustion temperature was established to obtain an accurate prediction of the temperature in the process of coal oxidation and heating.

Abstract Cellular behavior is regulated by mechanical signals within the cellular microenvironment. Additionally, changes of temperature, blood flow, and muscle contraction also affect cellular state and the development of diseases. In clinical practice, physical therapy techniques such as ultrasound, vibration, exercise, cold therapy, and hyperthermia are commonly employed to alleviate pain and treat diseases. However, the molecular mechanism about how these physiotherapy methods stimulate local tissues and control gene expression remains unknow. Fortunately, the discovery of YAP filled this gap, which has been reported has the ability to sense and convert a wide variety of mechanical signals into cell-specific programs for transcription, thereby offering a fresh perspective on the mechanisms by which physiotherapy treat different diseases. This review examines the involvement of Hippo/YAP signaling pathway in various diseases and its role in different physical therapy approaches on diseases. Furthermore, we explore the potential therapeutic implications of the Hippo/YAP signaling pathway and address the limitations and controversies surrounding its application in physiotherapy.

Abstract Lysophosphoglycerides (LPLs) have been reported to accumulate in myocardium and serve as a cause of arrhythmias in acute myocardial ischemia. However, in this study we found that LPLs level in the ventricular myocardium was decreased by the onset of acute myocardial ischemia in vivo in rats. Decreasing of LPLs level in left ventricular myocardium, but not right, was observed within 26 min of left myocardial ischemia, regardless of whether arrhythmias were triggered. Lower LPLs level in the ventricular myocardium was also observed in aconitine-simulated ventricular fibrillation (P

Objective In the current mainstream of train auxiliary power supply systems, such as cross-supply method and extended supply method, the failure of a single SIV (auxiliary inverter) can impact the normal operation of electrical equipment on the train. As an emerging control technology, the grid-connected power supply has its advantages and requires in-depth research into its control technology. Method Taking Shanghai Rail Transit Line 8 as example, issues related to slow response and low reliability in the auxiliary power supply system for the third batch of purchased train are addressed. For the design of the fourth batch of purchased trains, a dual-bus grid-connected power supply scheme based on TCMS (train control and management system) control is proposed. Specifically, four TLKs (grid-connected contactors) are arranged in the middle car to link four independent medium-voltage buses together. The medium-voltage bus structure of the auxiliary power supply system under this scheme is introduced, the action sequence during the internal start-up stages and grid-connected start-up stages of SIV are analyzed, and the logics of grid-connected power supply control, SIV start-up and fault protection are expounded. Result & Conclusion The time required for grid-connected power supply in the proposed scheme is significantly reduced (minimum of 2.5 seconds). The medium-voltage bus topology with dual-bus and multiple TLKs avoids system functionality overall failure due to bus short-circuits, improving the reliability of train auxiliary power supply system. The grid-connected power supply technology based on TCMS control is expected to be a development direction of auxiliary power supply technology for urban rail transit trains in the future.

BackgroundR3HDM1, an RNA binding protein with one R3H domain, remains uncharacterized in terms of its association with tumor progression, malignant cell regulation, and the tumor immune microenvironment. This paper aims to fill this gap by analyzing the potential of R3HDM1 in diagnosis, prognosis, chemotherapy, and immune function across various cancers.MethodsData was collected from the Firehost database (http://gdac.broadinstitute.org) to obtain the TCGA pan-cancer queue containing tumor and normal samples. Additional data on miRNA, TCPA, mutations, and clinical information were gathered from the UCSC Xena database (https://xenabrowser.net/datapages/). The mutation frequency and locus of R3HDM1 in the TCGA database were examined using the cBioPortal. External validation through GEO data was conducted to assess the differential expression of R3HDM1 in different cancers. Protein expression levels were evaluated using the Clinical Proteomics Tumor Analysis Alliance (CPTAC). The differential expression of R3HDM1 was verified in lung adenocarcinoma cell lines and normal lung glandular epithelial cells via RT-qPCR. Cell migration and proliferation experiments were conducted by knocking down the expression of R3HDM1 in two lung adenocarcinoma cell lines using small interfering RNA. The biological role of R3HDM1 in pan-cancer was explored using the GSEA method. Multiple immune infiltration algorithms from the TIMER2.0 database was employed to investigate the correlation between R3HDM1 expression and the tumor immune microenvironment. Validation of transcriptome immune infiltration was based on 140 single-cell datasets from the TISCH database. The study also characterized a pan-cancer survival profile and analyzed the differential expression of R3HDM1 in different molecular subtypes. The relationship between R3HDM1 and drug resistance was investigated using four chemotherapy data sources: CellMiner, GDSC, CTRP and PRISM. The impact of chemicals on the expression of R3HDM1 was explored through the CTD database.ResultThe study revealed differential expression of R3HDM1 in various tumors, indicating its potential as an early diagnostic marker. Changes in somatic copy number (SCNA) and DNA methylation were identified as factors contributing to abnormal expression levels. Additionally, the study found that R3HDM1 expression is associated with clinical features, metabolic pathways, and important pathways related to metastasis and the immune system. High expression of R3HDM1 was linked to poor prognosis across different tumors and altered drug sensitivity. Furthermore, the expression of R3HDM1 showed significant correlations with immune modulatory molecules and biomarkers of lymphocyte subpopulation infiltration. Finally, the study highlighted four chemicals that could influence the expression of R3HDM1.ConclusionOverall, this study proposes that R3HDM1 expression is a promising biomarker for predicting the prognosis of cancer, especially lung adenocarcinoma, and the efficacy of immunotherapy, demonstrating the rationale for further exploration in the development of anti-tumor therapies.

Abstract Pure shift NMR spectroscopy enables the robust probing on molecular structure and dynamics, benefiting from great resolution enhancements. Despite extensive application landscapes in various branches of chemistry, the long experimental times induced by the additional time dimension generally hinder its further developments and practical deployments, especially for multi‐dimensional pure shift NMR. Herein, this study proposes and implements the fast, reliable, and robust reconstruction for accelerated pure shift NMR spectroscopy with lightweight attention‐assisted deep neural network. This deep learning protocol allows one to regain high‐resolution signals and suppress undersampling artifacts, as well as furnish high‐fidelity signal intensities along with the accelerated pure shift acquisition, benefitting from the introduction of the attention mechanism to highlight the spectral feature and information of interest. Extensive results of simulated and experimental NMR data demonstrate that this attention‐assisted deep learning protocol enables the effective recovery of weak signals that are almost drown in the serious undersampling artifacts, and the distinction and recognition of close chemical shifts even though using merely 5.4% data, highlighting its huge potentials on fast pure shift NMR spectroscopy. As a result, this study affords a promising paradigm for the AI‐assisted NMR protocols toward broader applications in chemistry, biology, materials, and life sciences, and among others.

Steel wires are widely employed in structural engineering due to their robust strength. However, the emergence of pitting corrosion significantly impacts their capacity, fatigue performance, and mechanical traits, with no specific codes addressing this issue. To assess the load-bearing capacity of corroded steel wires, predict their remaining fatigue life, and analyze failure modes, a comprehensive physical test was conducted. Mechanical evaluations of corroded wires were followed by 3D scanning to analyze corrosion attributes and fracture surface morphology. Using fuzzy reliability theory, a model estimated wire capacity under varying corrosion degrees. Subsequent fatigue testing explored performance and developed a predictive residual life model. Investigation results revealed a rapid and gradual decrease in capacity's reliability coefficient. Corroded wire fracture morphologies were classified as typical and multi-source cracks, including subtypes like cracks expanding in the same plane and step-like fractures. All wire types exhibited a cracking threshold exceeding 5.6 MPa·m1/2, with fracture intensity declining as corrosion severity increased. Notably, the model better suited slightly corroded wires, showing up to 30.93 % relative error for severely corroded wires. Enhancing accuracy for the latter entails considering additional factors to refine the model.