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In response to the problems of unclear distribution of deep-water pre-salt carbonate reservoirs and formation conditions of large oil fields in the Santos passive continental margin basin, based on comprehensive utilization of geological, seismic, and core data, and reconstruction of Early Cretaceous prototype basin and lithofacies paleogeography, it is proposed for the first time that the construction of pre-salt carbonate build-ups was controlled by two types of isolated platforms: inter-depression fault-uplift and intra-depression fault-high. The inter-depression fault-uplift isolated platforms are distributed on the present-day pre-salt uplifted zones between depressions, and are built on half- and fault-horst blocks that were inherited and developed in the early intra-continental and inter-continental rift stages. The late intra-continental rift coquinas of the ITP Formation and the early inter-continental rift microbial limestones of the BVE Formation are continuously constructed; intra-depression fault-high isolated platforms are distributed in the current pre-salt depression zones, built on the uplifted zones formed by volcanic rock build-ups in the early prototype stage of intra-continental rifts, and only the BVE microbial limestones are developed. Both types of limestones formed into mound-shoal bodies, that have the characteristics of large reservoir thickness and good physical properties. Based on the dissection of large pre-salt oil fields discovered in the Santos Basin, it has been found that both types of platforms could form large-scale combined structural-stratigraphic traps, surrounded by high-quality lacustrine and lagoon source rocks at the periphery, and efficiently sealed by thick high-quality evaporite rocks above, forming the optimal combination of source, reservoir and cap in the form of “lower generation, middle storage, and upper cap”, with a high degree of oil and gas enrichment. It has been found that the large oil fields are all bottom water massive oil fields with a unified pressure system, and they are all filled to the spill-point. The future exploration is recommended to focus on the inter-depression fault-uplift isolated platforms in the western uplift zone and the southern section of eastern uplift zones, as well as intra-depression fault-high isolated platforms in the central depression zone. The result not only provides an important basis for the advanced selection of potential play fairways, bidding of new blocks, and deployment of awarded exploration blocks in the Santos Basin, but also provides a reference for the global selection of deep-water exploration blocks in passive continental margin basins.

Abstract Background The aim of this study is to assess the efficacy of a multiparametric ultrasound imaging omics model in predicting the risk of postoperative recurrence and molecular typing of breast cancer. Methods A retrospective analysis was conducted on 534 female patients diagnosed with breast cancer through preoperative ultrasonography and pathology, from January 2018 to June 2023 at the Affiliated Cancer Hospital of Xinjiang Medical University. Univariate analysis and multifactorial logistic regression modeling were used to identify independent risk factors associated with clinical characteristics. The PyRadiomics package was used to delineate the region of interest in selected ultrasound images and extract radiomic features. Subsequently, radiomic scores were established through Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support Vector Machine (SVM) methods. The predictive performance of the model was assessed using the receiver operating characteristic (ROC) curve, and the area under the curve (AUC) was calculated. Evaluation of diagnostic efficacy and clinical practicability was conducted through calibration curves and decision curves. Results In the training set, the AUC values for the postoperative recurrence risk prediction model were 0.9489, and for the validation set, they were 0.8491. Regarding the molecular typing prediction model, the AUC values in the training set and validation set were 0.93 and 0.92 for the HER-2 overexpression phenotype, 0.94 and 0.74 for the TNBC phenotype, 1.00 and 0.97 for the luminal A phenotype, and 1.00 and 0.89 for the luminal B phenotype, respectively. Based on a comprehensive analysis of calibration and decision curves, it was established that the model exhibits strong predictive performance and clinical practicability. Conclusion The use of multiparametric ultrasound imaging omics proves to be of significant value in predicting both the risk of postoperative recurrence and molecular typing in breast cancer. This non-invasive approach offers crucial guidance for the diagnosis and treatment of the condition.

The examination of highway travel behaviour during the COVID-19 pandemic can provide valuable insights into the impacts of the pandemic and associated policies on human mobility patterns. This paper proposes a comprehensive examination, measurement and characterisation approach in the perspective of network and community structure. To capture the changes in travel behaviour, four stages were defined based on four consecutive Augusts from 2019 to 2022, during which varying levels of restrictions were implemented. The findings reveal interesting trends in travel patterns. In 2020, after the clearance of pandemic cases, there was a remarkable increase of over 10% in highway trips. However, in 2021, with the emergence of COVID-19 variants, there was a significant decline of over 30% in highway trips. By employing complex network analysis, key metrics of the primary network, including link weight, node flux and network connectivity, exhibited a notable decrease during the pandemic. These changes in network properties also reflect the spatial heterogeneity of highway travel demand. Moreover, the outcomes of community detection shed light on the evolution of the highway community structure, highlighting the efficacy of a community-collaboration strategy for highway management during public emergency events, as it fosters strong local interaction within the community.

Abstract Background This study aimed to investigate the potential differences in the influence of impaired glucose tolerance (IGT) with and without metabolic syndrome (MetS) on cardiovascular (CV) events and mortality. Methods Participants having IGT with MetS (IGT_MetS), those having IGT without MetS (IGT_non_MetS), and those having normal glucose tolerance (NGT) without MetS (NGT_non_MetS) (N = 246, N = 294, and N = 471, respectively) were included in this study. Cox proportional hazards regression was used to examine the relationship among these three groups and CV events and mortality. Results Over the 30‐year follow‐up period, 57 (12.1%) participants having NGT_non_MetS, 55 (18.71%) with IGT_non_MetS, and 74 (30.08%) with IGT_MetS experienced CV mortality. After adjusting for risk factors, the hazard ratios for CV mortality were 2 (95% confidence interval [CI], 1.38–2.91) for the IGT_non_MetS group and 2.96 (95% CI, 2.09–4.19) for the IGT_MetS group, compared with the NGT_non_MetS group. Similar patterns were observed for CV events, with hazard ratios of 1.49 (95% CI, 1.19–1.88) for the IGT_non_MetS group and 1.97 (95% CI, 1.58–2.47) for the IGT_MetS group. Sensitivity analysis revealed that the hazard ratios of the IGT_non_MetS and IGT_MetS groups indicated a higher risk of all‐cause mortality, myocardial infarction events or myocardial infarction mortality, and stroke events or stroke mortality compared with that of the NGT_non_MetS group. Conclusion IGT_non_MetS increased the risk of CV mortality and events. Furthermore, when it occurred in conjunction with MetS, it further increased the risk of CV mortality and events. This suggested that active intervention is required.

BackgroundThe association between years of non-diabetes status after diagnosis of impaired glucose tolerance (IGT) and the risk of long-term death and cardiovascular outcomes needed to be clarified.Methods and findingsIn this post hoc analysis, we included 540 individuals with IGT who participated in the original Da Qing Diabetes Prevention Study (DQDPS). In the DQDPS, all participants were diagnosed with IGT by a 75 g oral glucose tolerance test and randomized to intervention or control groups with a 6-year lifestyle intervention trial. After the completion of the trial, death, cardiovascular events, and microvascular complications were monitored over a 30-year follow-up. In this post hoc analysis, the Cox analysis assessed the extended risk of these outcomes in individuals who either remained non-diabetes status or progressed to diabetes at the end of 2, 4, and 6 years after diagnosis of IGT. In all participants, the difference in the cumulative incidence rate of the outcomes between the diabetes and non-diabetes group gradually increased over 30 years. Compared with the diabetes group, a significantly lower risk of all-cause death (hazard ratio [HR]: 0.74; 95% confidence interval [CI]: 0.57 to 0.97, p = 0.026), cardiovascular events (HR: 0.63; 95% CI: 0.49 to 0.82, p < 0.001), and microvascular complications (HR: 0.62; 95% CI: 0.45 to 0.86, p = 0.004) first emerged in individuals who remained non-diabetes at the 4 years visit, whereas the significant risk reduction in cardiovascular death was first observed at the end of 6 years (HR: 0.56; 95% CI: 0.39 to 0.81, p = 0.002) after adjustment for age, sex, smoking status, BMI, systolic blood pressure, blood glucose, total cholesterol, intervention, and medications (including insulin plus oral hypoglycaemics, antihypertensives, and lipid-lowering agents). The results in the original intervention group alone were similar to the whole group. The main limitations of our study are the limited number of participants and the sole ethnicity of the Chinese population.ConclusionsIn this study, we observed that maintaining several years of non-diabetes status after IGT diagnosis was associated with a significant reduction in long-term risk of death and vascular complications, and for most of these outcomes, maintaining at least 4 years of non-diabetes status may be needed to achieve a significant risk reduction.

Abstract Class B1 G protein-coupled receptors (GPCRs) are important regulators of many physiological functions such as glucose homeostasis, which is mainly mediated by three peptide hormones, i.e., glucagon-like peptide-1 (GLP-1), glucagon (GCG), and glucose-dependent insulinotropic polypeptide (GIP). They trigger a cascade of signaling events leading to the formation of an active agonist–receptor–G protein complex. However, intracellular signal transducers can also activate the receptor independent of extracellular stimuli, suggesting an intrinsic role of G proteins in this process. Here, we report cryo-electron microscopy structures of the human GLP-1 receptor (GLP-1R), GCG receptor (GCGR), and GIP receptor (GIPR) in complex with Gs proteins without the presence of cognate ligands. These ligand-free complexes share a similar intracellular architecture to those bound by endogenous peptides, in which, the Gs protein alone directly opens the intracellular binding cavity and rewires the extracellular orthosteric pocket to stabilize the receptor in a state unseen before. While the peptide-binding site is partially occupied by the inward folded transmembrane helix 6 (TM6)–extracellular loop 3 (ECL3) juncture of GIPR or a segment of GCGR ECL2, the extracellular portion of GLP-1R adopts a conformation close to the active state. Our findings offer valuable insights into the distinct activation mechanisms of these three important receptors. It is possible that in the absence of a ligand, the intracellular half of transmembrane domain is mobilized with the help of Gs protein, which in turn rearranges the extracellular half to form a transitional conformation, facilitating the entry of the peptide N-terminus.

Abstract Background Feedback is critical to improving practitioners’ clinical practice and professional growth. Although they are still considered junior practitioners, their feedback-seeking experiences have yet to be investigated. This study aimed to understand the fundamental thoughts and experiences of new graduate nurses regarding feedback-seeking and to identify the main factors that influence their feedback-seeking behaviors. Methods Conducting a descriptive phenomenological study, semi-structured in-depth interviews with newly graduated nurses from four hospitals in Zhejiang Province, China, face-to-face or via video call in the hospital conference room through purposive and snowball sampling. Interview data were evaluated using Colaizzi’s 7-step phenomenological data analysis. The COREQ checklist was followed. Results A total of 15 new graduate nurses were interviewed as a sample, and 13 categories emerged from our data. They were categorized into four central elements: (1) perceptions and attitudes, (2) drivers, (3) dilemmas and needs, and (4) transformation and growth. Conclusions This study found that new graduate nurses have various needs but face dilemmas in the feedback-seeking process. Nursing managers should be proficient at providing positive leadership, collaborating with clinical mentors to foster an atmosphere where new graduate nurses may obtain honest, transparent, and fair feedback, and exercising caution when providing negative feedback.

Abstract Background Higher levels of palmitoyl sphingomyelin (PSM, synonymous with sphingomyelin 16:0) are associated with an increased risk of cardiovascular disease (CVD) in people with diabetes. Whether circulating PSM levels can practically predict the long-term risk of CVD and all-cause death remains unclear. This study aimed to investigate whether circulating PSM is a real predictor of CVD death in Chinese adults with or without diabetes. Methods A total of 286 and 219 individuals with and without diabetes, respectively, from the original Da Qing Diabetes Study were enrolled. Blood samples collected in 2009 were used as a baseline to assess circulating PSM levels. The outcomes of CVD and all-cause death were followed up from 2009 to 2020, and 178 participants died, including 87 deaths due to CVD. Cox proportional hazards regression was used to estimate HRs and their 95% CIs for the outcomes. Results Fractional polynomial regression analysis showed a linear association between baseline circulating PSM concentration (log-2 transformed) and the risk of all-cause and CVD death (p 0.05), in all participants after adjustment for confounders. When the participants were stratified by PSM-tertile, the highest tertile, regardless of diabetes, had a higher incidence of CVD death (41.5 vs. 14.7 and 22.2 vs. 2.9 per 1000 person-years in patients with and without diabetes, respectively, all log-rank p

Abstract The percent global glomerulosclerosis is a key factor in determining the outcome of renal transfer surgery. At present, the rate is typically computed by pathologists, which is labour intensive and nonstandardized. With the development of Deep Learning (DL), DL-based segmentation models can be used to better identify and segment normal and sclerosed glomeruli. Based on this, we can better quantify percent global glomerulosclerosis to reduce the discard rate of donor kidneys. We used 51 whole slide images (WSIs) from different institutions that are publicly available on the internet. However, the number of sclerosed glomeruli is much smaller than that of normal glomeruli in different WSIs, which can reduce the effectiveness of Deep Learning. For better sclerosed glomerular identification and segmentation performance, we modified and trained a GAN (generative adversarial network)-based image inpainting model to obtain more synthetic sclerosed glomeruli. Our proposed inpainting method achieved an average SSIM (Structural Similarity) of 0.8086 and an average PSNR (Peak Signal-to-Noise Ratio) of 22.8943 dB in the area of generated sclerosed glomeruli. We obtained sclerosed glomerular segmentation performance improvement by adding synthetic sclerosed glomerular images and achieved the best Dice of glomerular segmentation in different test sets based on the modified Unet model.

Urban air mobility (UAM) extends urban transportation to low-altitude airspace using electric vertical take-off and landing (eVTOL) vehicle to reduce traffic congestion. The vertical take-off and landing (VTOL) site connecting ground and air transport is the critical infrastructure of the UAM. Determining its locations is essential for the design and operation of the air route. This study focuses on the problem of the location of the VTOL site, using Shenzhen as the study area, and establishes an integer programming model with the objective of maximizing travel cost savings to identify the optimal locations of the VTOL sites. This study is different from existing ones in that it explicitly considers the three-dimensional spatial availability of VTOL sites. Geographic information system (GIS) tools are used to identify locations that satisfy two-dimensional (2D) planar availability, and an obstacle assessment model of the approach/departure and transitional surfaces of the VTOL site is built to further screen the locations. The selected potential sites are used as input to the integer programming model, ensuring that the locations identified to establish the VTOL site are optimal. The impact of the number of VTOL sites, the user's transfer time at the VTOL sites, and the eVTOL pricing on the model solution is also discussed. Although this study uses Shenzhen as a research object, the proposed methodology is generalized and applicable to any other city or region, providing recommendations and references for initial planning and related operations of the UAM in selected areas.

Within the context of contemporary society, the propagation of information is often subject to the influence of inter-individual connectivity, and individuals may exhibit divergent receptive attitudes towards identical information, a phenomenon denoted as the Hesitant-Common (HECO) trait. In light of this, the present study initially constructs a propagation network model devoid of correlation configurations to investigate the HECO characteristics within weighted social networks. Subsequently, the study employs a theoretical framework for edge partitioning, predicated on edge weights and HECO traits, to quantitatively analyze the mechanisms of individual information dissemination. Theoretical analyses and simulation outcomes consistently demonstrate that an augmentation in the proportion of common individuals facilitates both the diffusion and adoption of information. Concurrently, a phase transition crossover is observed, wherein the growth pattern of the ultimate adoption range, denoted as R(∞), transitions from a first-order discontinuous phase transition to a second-order continuous phase transition as the proportion of common individuals increases. An escalation in the weight distribution exponent is found to enhance information propagation. Furthermore, a reduction in the heterogeneity of degree distribution is conducive to the spread of information. Conversely, an increase in degree distribution heterogeneity and a diminution in the collective decision-making capacity can both exert inhibitory effects on the propagation of information.

Mild cognitive impairment (MCI) is a precursor to neurodegenerative diseases such as Alzheimer’s disease, and an early diagnosis and intervention can delay its progression. However, the brain MRI images of MCI patients have small changes and blurry shapes. At the same time, MRI contains a large amount of redundant information, which leads to the poor performance of current MCI detection methods based on deep learning. This article proposes an MCI detection method that integrates the attention mechanism and parallel dilated convolution. By introducing an attention mechanism, it highlights the relevant information of the lesion area in the image, suppresses irrelevant areas, eliminates redundant information in MRI images, and improves the ability to mine detailed information. Parallel dilated convolution is used to obtain a larger receptive field without downsampling, thereby enhancing the ability to acquire contextual information and improving the accuracy of small target classification while maintaining detailed information on large-scale feature maps. Experimental results on the public dataset ADNI show that the detection accuracy of the method on MCI reaches 81.63%, which is approximately 6.8% higher than the basic model. The method is expected to be used in clinical practice in the future to provide earlier intervention and treatment for MCI patients, thereby improving their quality of life.

Objective: This prospective study aims to evaluate acute irradiation-induced xerostomia during radiotherapy by utilizing the normalized iodine concentration (NIC) derived from energy spectrum computed tomography (CT) iodine maps. Methods: In this prospective study, we evaluated 28 patients diagnosed with nasopharyngeal carcinoma. At 4 distinct stages of radiotherapy (0, 10, 20, and 30 fractions), each patient underwent CT scans to generate iodine maps. The NIC of both the left and right parotid glands was obtained, with the NIC at the 0-fraction stage serving as the baseline measurement. After statistically comparing the NIC obtained in the arterial phase, early venous phase, late venous phase, and delayed phase, we chose the late venous iodine concentration as the NIC and proceeded to analyze the variations in NIC at each radiotherapy interval. Using the series of NIC values, we conducted hypothesis tests to evaluate the extent of change in NIC within the parotid gland across different stages. Furthermore, we identified the specific time point at which the NIC decay exhibited the most statistically significant results. In addition, we evaluated the xerostomia grades of the patients at these 4 stages, following the radiation therapy oncology group (RTOG) xerostomia evaluation standard, to draw comparisons with the changes observed in NIC. Results: The NIC in the late venous phase exhibited the highest level of statistical significance ( P

Abstract Background Self-management plays an important role in the disease management of glaucoma patients. The effectiveness of the program can be improved by assessing the patient’s perspective and needs to tailor self-management support. Most studies have focused on assessing one of these self-management behaviours, such as medication adherence, and there is a lack of systematic assessment of the support needs and challenges of self-management for patients with glaucoma. Therefore, in this study, we conducted an in-depth investigation into the self-management challenges and support needs of patients with primary glaucoma, providing a basis for nursing staff to implement self-management support. Method The phenomenological method and semistructured interviews were used in this study. A total of 20 patients with primary glaucoma were recruited between June and December 2022. Colaizzi’s analysis method was used to analyse the interview data. Results Challenges for patients include becoming an expert in glaucoma, managing negative emotions, adapting to daily life changes and resuming social activities. To address these challenges, four themes of patient self-management support needs were identified: (1) health information support, (2) social support, (3) psychological support, and (4) daily living support. Conclusion Patients with primary glaucoma experience varying degrees of challenge in dealing with medical, emotional, and social aspects. Comprehending the support needs of patients, healthcare professionals should deliver targeted, personalized and comprehensive self-management interventions to enhance their capacity of patients to perform self-management and improve their quality of life.

Abstract Background Gastric cancer patients harboring a TP53 mutation exhibit a more aggressive and chemoresistant phenotype. Unfortunately, efforts to identify the vulnerabilities to overcome these aggressive malignancies have made minimal progress in recent years. Therefore, there is an urgent need to explore the novel therapeutic strategies for this subclass. Histone methylation modulators are critical epigenetic targets for cancer therapies that help maintain the malignancies of cancers harboring TP53 mutations and senescence evasion. Triggering senescence is now considered to benefit multiple cancer therapies. Furthermore, senescence-based “one-two punch” therapy was validated in clinical trials. Therefore, we hypothesized that screening epigenetic modulators might help identify a novel vulnerability to trigger senescence in gastric cancer harboring TP53 mutations. Results We developed a novel efficient approach to identify senescence inducers by sequentially treating cells with drug candidates and senolytic agents. Based on this, we demonstrated that QC6352 (a selective KDM4C inhibitor) efficiently triggered cellular senescence in gastric cancer harboring TP53 mutations. More importantly, the “one-two punch’ therapy consisting of QC6352 and SSK1 eliminates tumor cells harboring TP53 mutations. This finding highlights a potential therapeutic strategy for the aggressive subgroup of gastric cancer. Besides, the functions of QC6352 were totally unknown. We demonstrated that QC6352 might possess far more powerful anti-tumor capacities compared to the traditional genotoxic drugs, 5-Fu and Oxaliplatin. Conclusions This initial investigation to identify a senescence inducer revealed that QC6352 triggers senescence in gastric cancer cells harboring TP53 mutations by regulating the SP1/CDK2 axis through suppressing KDM4C. QC6352 and senolytic agent-SSK1 represent a novel ‘one-two punch’ therapeutic strategy for the more malignant gastric cancer subtypes.

The maturation of wheat flour is a transformative process that elevates its processing and culinary attributes to their peak performance levels. Despite extensive research on starch and gluten protein modifications, the impact of lipid changes has been largely unexplored. This study addresses this gap by examining the maturation of freshly milled wheat flour at 15 °C, 25 °C, and 40 °C over 60 days, focusing on enzymatic activities—lipase, lipoxidase, and catalase—and lipid metabolites, including free fatty acids, conjugated trienes, p-anisidine value, and total oxidation value. The results of this study showed that free fatty acids continued to increase at all temperatures, with the most significant increase of 50% at 15 °C. The p-anisidine value followed a pattern of initial increase followed by a decline, while conjugated trienes were markedly higher at 40 °C, suggesting temperature’s significant influence on lipid peroxidation. Notably, total oxidation values became erratic post 30 days, indicating a shift in oxidative dynamics. This study underscores the correlation between lipid metabolites and enzymatic activities, revealing the enzymes’ pivotal role in lipid oxidation. The interplay of temperature and time offers valuable insights for optimizing wheat flour maturation, ensuring superior quality for various applications.

The acceleration of the nitrogen cycle and the nitrogen excess observed in some coastal waters has increased interest into understanding the biochemical and molecular basis of nitrogen metabolism in various microorganisms. To investigate nitrogen metabolism of a novel heterotrophic nitrification and aerobic denitrification bacterium Klebsiella aerogenes strain (B23) under nitrogen-rich conditions, we conducted physiological and transcriptomic high-throughput sequencing analyses on strain B23 cultured on potassium nitrate–free or potassium nitrate–rich media. Overall, K. aerogenes B23 assimilated 82.47% of the nitrate present into cellular nitrogen. Further, 1,195 differentially expressed genes were observed between K. aerogenes B23 cultured on potassium nitrate–free media and those cultured on potassium nitrate-rich media. Gene annotation and metabolic pathway analysis of the transcriptome were performed using a series of bioinformatics tools, including Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Non-Redundant Protein Database annotation. Accordingly, the nitrogen metabolism pathway of K. aerogenes B23 was analyzed; overall, 39 genes were determined to be involved in this pathway. Differential expression analysis of the genes involved in the nitrogen metabolism pathway demonstrated that, compared to the control, FNR, NarK/14945, fdx, gshA, proB, proA, gapA, argH, artQ, artJ, artM, ArgR, GAT1, prmB, pyrG, glnS, and Ca1 were significantly upregulated in the nitrogen-treated K. aerogenes B23; these genes have been established to be involved in the regulation of nitrate, arginine, glutamate, and ammonia assimilation. Further, norV, norR, and narI were also upregulated in nitrogen-treated K. aerogenes B23; these genes are involved in the regulation of NO metabolism. These differential expression results are important for understanding the regulation process of key nitrogen metabolism enzyme genes in K. aerogenes B23. Therefore, this study establishes a solid foundation for further research into the expression regulation patterns of nitrogen metabolism–associated genes in K. aerogenes B23 under nitrogen-rich conditions; moreover, this research provides essential insight into how K. aerogenes B23 utilizes nutritional elements.

Drivers’ fault emergency response behavior can easily lead to crashes, resulting in significant economic and property losses. Exploring the causes of improper emergency response behavior is crucial for regulating driver behavior and preventing crash. Therefore, based on crashes data between commercial motor vehicles (CMVs) and noncommercial motor vehicles (NCMVs) that occurred in China from 2014 to 2018, this study established a binary logistic regression model. It systematically analyzed the key factors influencing drivers’ fault emergency response behaviors in terms of individuals, vehicles, road conditions, environment, and corporate management. Additionally, it compared the differences in the influencing factors of fault emergency response behaviors between drivers of CMV and NCMV. The results indicate that the model fits well. The presence of faulty emergency response behavior in drivers is significantly correlated with five factors: age, gender, fatigue driving, speeding, and weather conditions. Moreover, these factors have different impacts on CMV drivers and NCMV drivers. Fatigue driving and speeding have a more significant impact on CMV drivers, while other factors are more pronounced for NCMV drivers. This study can provide valuable insights for the development of measures aimed at reducing the severity of CMV-NCMV crashes.

Abstract Sphingosine (Sph) plays important roles in various complex biological processes. Abnormalities in Sph metabolism can result in various diseases, including neurodegenerative disorders. However, due to the lack of rapid and accurate detection methods, understanding sph metabolic in related diseases is limited. Herein, a series of near‐infrared fluorogenic probes DMS‐X (X = 2F, F, Cl, Br, and I) are designed and synthesized. The fast oxazolidinone ring formation enables the DMS‐2F to detect Sph selectively and ultrasensitively, and the detection limit reaches 9.33 ± 0.41 nm. Moreover, it is demonstrated that DMS‐2F exhibited a dose‐ and time‐dependent response to Sph and can detect sph in living cells. Importantly, for the first time, the changes in Sph levels induced by Aβ42 oligomers and H2O2 are assessed through a fluorescent imaging approach, and further validated the physiological processes by which Aβ42 oligomers and reactive oxygen species (ROS)‐induce changes in intracellular Sph levels. Additionally, the distribution of Sph in living zebrafish is successfully mapped by in vivo imaging of a zebrafish model. This work provides a simple and efficient method for probing Sph in living cells and in vivo, which will facilitate investigation into the metabolic process of Sph and the connection between Sph and disease pathologies.

Abstract With the accelerated operation of subway networks, the increasing number of subway transfer stations results in inefficient passenger travel. The target of this paper is to solve the research question of how to reduce transfer waiting time (TWTT) for heterogeneous passengers. The key problem is to determine the optimal concerted train timetable considering the transfer walking time (TWKT) of the passengers. On the basis of field survey data, the regression method was used to establish a TWKT prediction model for general passengers (G) and vulnerable passengers (V), including the elderly, passengers traveling with children, and those carrying large luggage. Afterward, a two-objective integer programming model was formulated to minimize the subway operating costs and TWTT for each group, in which V is given the priority weight to ensure social equity. The headway, loading capacity, and TWKT of heterogeneous passengers were set as optimization model constraints. A genetic algorithm (GA) was designed to find the optimal solution. A case study in which the Beijing Jianguomen Station was selected as the key transfer station was conducted to verify the performance of the proposed model. Key results show that the total TWTT for V and G can be reduced by 18.6% and 27.2%, respectively, with one train saved. Results of the parameter sensitivity analysis reveal the interconnection between the operating cost, heterogeneous passenger proportion, and transfer time. The proposed model can be used for improving transfer efficiency for passengers while considering the enterprise operating costs.

To scientifically analyze the effect of offshore wind farm on intertidal beach stability, this paper summarized the research progress of intertidal zone dynamic change analysis at home and abroad. The method of hypothetical sandbank surface discrimination (HSSD) was proposed. The topographic changes that caused by offshore wind turbine construction in intertidal zone were estimated quantitatively from single phase DEM, the contribution rate and contribution mode of the erosion and deposition change of offshore sand body terrain offshore caused by wind turbine construction and operation were analyzed. The multi temporal intertidal zone DEM was based on enhanced waterline method (EWM). It carried out the quantitative assessment of the safety and stability of offshore wind turbines due to the change of intertidal tidal flat erosion and deposition. The practical application proved that the scheme could be used for the influence of offshore wind turbines on intertidal zone topographic changes with quantitative remote sensing monitoring.

Based on the typical dissection of various onshore tight oil fields in China, the tight oil migration and accumulation mechanism and enrichment-controlling factors in continental lake basins are analyzed through nuclear magnetic resonance (NMR) displacement physical simulation and Lattice Boltzmann numerical simulation by using the samples of source rock, reservoir rock and crude oil. In continental lake basins, the dynamic forces driving hydrocarbon generation and expulsion of high-quality source rocks are the foundational power that determines the charging efficiency and accumulation effect of tight oil, the oil migration resistance is a key element that influences the charging efficiency and accumulation effect of tight oil, and the coupling of charging force with pore-throat resistance in tight reservoir controls the tight oil accumulation and sweet spot enrichment. The degree of tight oil enrichment in continental lake basins is controlled by four factors: source rock, reservoir pore-throat size, anisotropy of reservoir structure, and fractures. The high-quality source rocks control the near-source distribution of tight oil, reservoir physical properties and pore-throat size are positively correlated with the degree of tight oil enrichment, the anisotropy of reservoir structure reveals that the parallel migration rate is the highest, and intralayer fractures can improve the migration and accumulation efficiency and the oil saturation.

Abstract Purpose To compare the effect of traditional conjunctival sac swab sampling (A) with aerosolization ocular surface microorganism sampling (B),a novel microbial sampling method, in detecting ocular microbial infection. Methods The study included 61 participants (122 eyes) enrolled at the Eye Hospital, Wenzhou Medical University from December, 2021 to March, 2023. Each eye of the participants underwent sampling first with method A then B.Before aerosolization sampling, the air environment was disinfected and sampled as blank air control sample. Subsequently, the air pulses impinging the ocular surface causes dehiscence of the tear film covering the ocular surface and aerosols are formed.The microorganisms from the ocular surface attach to the aerosols generated as aerosolization ocular surface microorganism and be sampled as subject sample by bio-aerosol sampler.The samples were collected and incubated at 25℃ for 3–5 days and 37℃ for 24–48 h.The colonies were counted and identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Results The accuracy in Group B was higher than that in Group A (45.8% vs. 38.3%, P = 0.289). There was a slight level of agreement between the results from both the sampling methods (k = 0.031, P = 0.730). The sensitivity in Group B was higher than that in Group A (57.1% vs. 35.7%, P = 0.453). The specificity results in Group B was higher than that in Group A (44.3% vs. 38.7%, P = 0.480). There were 12 and 37 types of microbes detected in Groups A and B, respectively. Conclusions Compared with traditional swab sampling, the novel aerosolization sampling method shows higher accuracy and more comprehensive detection of microbes; however, it cannot completely replace swab sampling. The novel method can be a novel conducive strategy and supplement swab sampling to auxiliary diagnose ocular surface infection.

Abstract Objective To assess the diagnostic efficacy of 18F-FDG PET/MRI for lymph node (LN) metastasis primary staging in patients with colorectal cancer (CRC). Methods This study was conducted and reported in accordance with the PRISMA-DTA statement. Electronic databases (PubMed, Embase, Cochrane Library) were searched for studies on 18F-FDG PET/MRI for diagnosing LN metastasis. The pooled sensitivity (SEN), specificity (SPE), and area under the curve (AUC) were applied to assess the diagnostic performance. Heterogeneity was identified and processed using meta-regression and sensitivity analysis. All data analyses were performed via STATA 15 and Meta-Disc 1.4 software. Results There were finally 7 studies included, involving a total of 184 patients. The Spearman rank correlation coefficient was 0.108 (P = 0.818), with no threshold-effect observed. The pooled SEN was 0.81 (95%CI 0.66–0.90) and the SPE was 0.89 (95% CI 0.73–0.96). In sub-groups, prospective groups demonstrated to have the highest SEN of 0.92 (95%CI 0.79–1.00). The studies conducted by Catalano et al. and Kang et al. were considered to be potential sources of heterogeneity. Conclusion 18F-FDG PET/MRI has shown remarkable diagnostic performance in identification of LN metastases in newly diagnosed CRC patients. It would be of great application value for the primary staging of CRC lymph node metastases.

Abstract Aims To explore the effects of training programs for ophthalmic specialist nurses in Zhejiang Province of China. Methods The training program included one month of theoretical training and three months of practical clinical training. The Two-Tutor system was used in training. The training contents were mainly set up around four modules: specialty knowledge and clinical skills, management, clinical teaching, and nursing research. We used theoretical examination, clinical practice assessment and trainee evaluation to assess the effectiveness of the training program. Before and after the training, the trainees’ core competence was assessed by a homemade questionnaire. Results In total, 48 trainees from 7 provinces (municipalities) in China participated in the training program. All trainees passed theoretical and clinical practice examinations and trainee evaluations. Their core competencies were significantly improved after training (p

ABSTRACTThe musculoskeletal system is important for balancing metabolic activity and maintaining health. Recent studies have shown that distortions in homeostasis of the intestinal microbiota are correlated with or may even contribute to abnormalities in musculoskeletal system function. Research has also shown that the intestinal flora and its secondary metabolites can impact the musculoskeletal system by regulating various phenomena, such as inflammation and immune and metabolic activities. Most of the existing literature supports that reasonable nutritional intervention helps to improve and maintain the homeostasis of intestinal microbiota, and may have a positive impact on musculoskeletal health. The purpose of organizing, summarizing and discussing the existing literature is to explore whether the intervention methods, including nutritional supplement and moderate exercise, can affect the muscle and bone health by regulating the microecology of the intestinal flora. More in-depth efficacy verification experiments will be helpful for clinical applications.

Brown adipose tissue (BAT) is a major site of non-shivering thermogenesis in mammals and plays an important role in energy homeostasis. Nuclear factor-erythroid 2-related factor 1 (NFE2L1, also known as Nrf1), a master regulator of cellular metabolic homeostasis and numerous stress responses, has been found to function as a critical driver in BAT thermogenic adaption to cold or obesity by providing proteometabolic quality control. Our recent studies using adipocyte-specific Nfe2l1 knockout [Nfe2l1(f)-KO] mice demonstrated that NFE2L1-dependent transcription of lipolytic genes is crucial for white adipose tissue (WAT) homeostasis and plasticity. In the present study, we found that Nfe2l1(f)-KO mice develop an age-dependent whitening and shrinking of BAT, with signatures of down-regulation of proteasome, impaired mitochondrial function, reduced thermogenesis, pro-inflammation, and elevated regulatory cell death (RCD). Mechanistic studies revealed that deficiency of Nfe2l1 in brown adipocytes (BAC) primarily results in down-regulation of lipolytic genes, which decelerates lipolysis, making BAC unable to fuel thermogenesis. These changes lead to BAC hypertrophy, inflammation-associated RCD, and consequently cold intolerance. Single-nucleus RNA-sequencing of BAT reveals that deficiency of Nfe2l1 induces significant transcriptomic changes leading to aberrant expression of a variety of genes involved in lipid metabolism, proteasome, mitochondrial stress, inflammatory responses, and inflammation-related RCD in distinct subpopulations of BAC. Taken together, our study demonstrated that NFE2L1 serves as a vital transcriptional regulator that controls the lipid metabolic homeostasis in BAC, which in turn determines the metabolic dynamics, cellular heterogeneity and subsequently cell fates in BAT.

Summary: Image-based AI has thrived as a potentially revolutionary tool for predicting molecular biomarker statuses, which aids in categorizing patients for appropriate medical treatments. However, many methods using hematoxylin and eosin-stained (H&E) whole-slide images (WSIs) have been found to be inefficient because of the presence of numerous uninformative or irrelevant image patches. In this study, we introduced the region of biomarker relevance (ROB) concept to identify the morphological areas most closely associated with biomarkers for accurate status prediction. We actualized this concept within a framework called saliency ROB search (SRS) to enable efficient and effective predictions. By evaluating various lung adenocarcinoma (LUAD) biomarkers, we showcased the superior performance of SRS compared to current state-of-the-art AI approaches. These findings suggest that AI tools, built on the ROB concept, can achieve enhanced molecular biomarker prediction accuracy from pathological images.

In order to solve the complexity problem caused by the uncertainty of control system models, this paper utilizes visual sensors and intelligent control technology, and uses data-driven machine learning algorithms to extract representations from the original video for video representation learning, providing crucial semantic features for related tasks. Convolutional Neural Network (CNN) greatly improves the utilization efficiency of visual data and model performance, and realizes the recognition of complex application scenarios. In this paper, an intelligent system control method of time-domain vision sensor is proposed. The proposed method locate, track and measure the speed of moving objects based on CNN and image acquisition device, Asynchronous Temporal Vision Sensor (ATVS). The experimental results show that our proposed algorithm has improved its overall performance through video feature learning and clustering. It not only pays more attention to video spatial information to enhance the discrimination ability of learned video representations, such as scenes and objects, but also improves the tracking performance of visual sensors under various interference attributes.

Abstract Background This study aimed to develop cardiovascular disease (CVD) risk equations for Chinese patients with newly diagnosed type 2 diabetes (T2D) to predict 10-, 20-, and 30-year of risk. Methods Risk equations for forecasting the occurrence of CVD were developed using data from 601 patients with newly diagnosed T2D from the Da Qing IGT and Diabetes Study with a 30-year follow-up. The data were randomly assigned to a training and test data set. In the training data set, Cox proportional hazard regression was used to develop risk equations to predict CVD. Calibration was assessed by the slope and intercept of the line between predicted and observed probabilities of outcomes by quintile of risk, and discrimination was examined using Harrell’s C statistic in the test data set. Using the Sankey flow diagram to describe the change of CVD risk over time. Results Over the 30-year follow-up, corresponding to a 10,395 person-year follow-up time, 355 of 601 (59%) patients developed incident CVD; the incidence of CVD in the participants was 34.2 per 1,000 person-years. Age, sex, smoking status, 2-h plasma glucose level of oral glucose tolerance test, and systolic blood pressure were independent predictors. The C statistics of discrimination for the risk equations were 0.748 (95%CI, 0.710–0.782), 0.696 (95%CI, 0.655–0.704), and 0.687 (95%CI, 0.651–0.694) for 10-, 20-, and 30- year CVDs, respectively. The calibration statistics for the CVD risk equations of slope were 0.88 (P = 0.002), 0.89 (P = 0.027), and 0.94 (P = 0.039) for 10-, 20-, and 30-year CVDs, respectively. Conclusions The risk equations forecast the long-term risk of CVD in patients with newly diagnosed T2D using variables readily available in routine clinical practice. By identifying patients at high risk for long-term CVD, clinicians were able to take the required primary prevention measures.

Abstract Background We aimed to examine the association between glycated hemoglobin (HbA1c), microvascular complications, and subclinical left ventricular (LV) systolic dysfunction, and to determine the strength of the correlation in asymptomatic patients with type 2 diabetes mellitus (T2DM). Methods Global longitudinal strain (GLS) was employed to assess the subclinical LV function of 152 enrolled T2DM patients with preserved LV ejection fraction, with the cutoff for subclinical LV systolic dysfunction predefined as GLS

Abstract We present the unrefined instanton partition functions of various 5d gauge theories with matter beyond the fundamental representation as sums over Young diagrams. By using these explicit expressions, we verify a range of identities among the instanton partition functions predicted by Higgsing procedures of fivebrane web diagrams and representation theory.

Abstract Background Diabetic retinopathy (DR) is one of the major blinding eye diseases worldwide. Psychological, emotional and social problems of DR patients are prominent. The aim of this study is to explore the experiences of patients with different phases of DR from hospital to home based on the “Timing It Right” framework, and to provide a reference for formulating corresponding intervention strategies. Methods The phenomenological method and semi-structured interviews were used in this study. A total of 40 patients with DR in different phases were recruited from a tertiary eye hospital between April and August 2022. Colaizzi’s analysis method was used to analyse the interview data. Results Based on the “Timing It Right” framework, different experiences in five phases of DR before and after Pars Plana Vitrectomy (PPV) were extracted. The patients experienced complicated emotional reactions and inadequate coping skills during the pre-surgery phase, increased uncertainty during the post-surgery phase, insufficient confidence and the decision to change during the discharge preparation phase, eagerness for professional support and moving forward in exploration during the discharge adjustment phase, and courageous acceptance and positive integration during the discharge adaptation phase. Conclusion The experiences of DR patients with vitrectomy in different phases of disease are ever-changing, and medical staff should provide personalized support and guidance to help DR patients get through the hard times smoothly and enhance the quality of hospital-family holistic care.

Abstract Background The triglyceride glucose (TyG) index has been considered a new biomarker for the diagnosis of angiocardiopathy and insulin resistance. However, the association of the TyG index with subclinical left ventricular (LV) systolic dysfunction still lacks comprehensive exploration. This study was carried out to examine this relationship in patients with type 2 diabetes mellitus (T2DM). Methods A total of 150 T2DM patients with preserved LV ejection fraction (LVEF ≥ 50%) from June 2021 to December 2021 were included in this study. The subclinical LV function was evaluated through global longitudinal strain (GLS), with the predefined GLS 9.83) n = 37) were conducted. A negative correlation of the TyG index with GLS (r = -0.307, P

Abstract Immunotherapy has greatly improved outcomes for patients with advanced melanoma, but good predictive biomarkers remain lacking in clinical practice. Although increasing evidence has revealed a vital role of pyroptosis in the tumor microenvironment (TME), it remains unclear for pyroptosis as a predictive biomarker for immunotherapy in melanoma. RNA sequencing data and annotated clinical information of melanoma patients were obtained from four published immunotherapy datasets. LASSO regression analysis was conducted to develop a pyroptosis‐based model for quantifying a pyroptosis score in each tumor. Based on four clinical cohorts, we evaluated the predictive capability of the model using multiple immunotherapeutic outcomes, including clinical benefits, overall survival (OS), and progression‐free survival (PFS). Furthermore, we depicted the distinctive TME features associated with pyroptosis. Compared with the group with low pyroptosis scores, the group with high pyroptosis scores consistently achieved better durable clinical benefits in four independent cohorts and the meta‐cohort. ROC analysis validated that the pyroptosis‐based model was a reliable biomarker for predicting clinical benefits from immunotherapy in melanoma. Survival analyses showed that the group with high pyroptosis scores harbored more favorable OS and PFS than those with low pyroptosis scores. Molecular analysis revealed that tumors with high pyroptosis scores displayed a typical immune‐inflamed phenotype in TME, including enrichment of immunostimulatory pathways, increased level of tumor‐infiltrating lymphocytes, upregulation of immune effectors, and activation of the antitumor immune response. Our findings suggested that the pyroptosis‐related model associated with multiple immune‐inflamed characteristics might be a reliable tool for predicting clinical benefit and survival outcomes from immunotherapy in melanoma.

Abstract Background The optimal glycemic control level in diabetic patients undergoing coronary artery bypass grafting (CABG) with cardiopulmonary bypass (On-Pump) remains unclear. Therefore, this study aimed to investigate the effect of different blood glucose control levels and glucose fluctuations on in-hospital adverse outcomes in diabetic patients undergoing on-pump CABG. Method A total of 3918 patients with diabetes undergoing CABG were reviewed in this study. A total of 1638 patients were eligible for inclusion and were categorized into strict, moderate and liberal glucose control groups based on post-operative mean blood glucose control levels of

The driver's stochastic nature is one of the important causes of traffic oscillation. To better describe the impact of the driver's stochastic characteristics on car-following behavior, we propose a stochastic full velocity difference model (SFVDM) considering the stochastic variation of the desired velocity. In order to mitigate traffic oscillation caused by driving stochasticity, we further propose a stable speed guidance model (S-SFVDM) by leveraging vehicle-to-infrastructure communication. Stochastic linear stability conditions are derived to demonstrate the prominent influence of the driver's stochasticity on the stability of traffic flow and the improvement of traffic flow stability by the proposed guidance strategy, respectively. We present numerical tests to demonstrate the effectiveness of the proposed models. The results show that the SFVDM can capture the traffic oscillation caused by the driver's stochastic desired velocity and reproduce the same disturbance growth pattern as in the field experiment. The results also indicate that the S-SFVDM can significantly expand the stable area of traffic flow to decrease the negative impact on traffic flow stability caused by the driver's stochastic nature.

Fabrication of 3D covalent organic framework thin films is challenging. Here the authors report on a liquid-liquid interfacial approach based on physical-organic considerations to synthesize an ultrathin covalent crystal film.

Abstract Excess passengers gathering on the urban rail transit platform in a short time brings huge security risks to passengers and the daily operation of urban rail transit. However, the real‐time monitoring method of passenger flows, which relies on manual methods, cannot satisfy the requirement of daily operations at the network level anymore. This study proposes a dynamic data‐driven computation and monitoring method for the number of waiting passengers on platforms to recognize the operational risk in real‐time. For waiting passengers on platforms, the waiting time duration before boarding is also calculated based on a first‐come‐first‐service basis. It can be used to provide real‐time information services to passengers and evaluate service quality. Moreover, the proposed methodology relies solely on the AFC data and the train timetable, which makes it easy to implement in the daily operation of any urban rail transit system. Finally, taking the Beijing rail transit network as a case study, the real‐time number of waiting passengers on each platform, and the time duration passengers should wait before boarding are calculated dynamically. Meanwhile, the spatio‐temporal distribution of passengers’ waiting time and waiting passengers are detailly analyzed based on the method of cluster analysis and the complex network theory.

How to effectively and accurately evaluate and analyze the volatility and reliability of travel speed on urban road before and after students back to school is a hot and key problem in urban road traffic congestion governance research. The Beijing 3rd Ring Road was taken as the research object and the impacts of the students back to school on the volatility and reliability of the travel speed of road sections were qualitatively and quantitatively analyzed based on the road section travel speed data during the weekday morning peak (7:00–8:59). The results showed that the travel speed of the Beijing 3rd Ring Road had cyclicity, time variability, large-scale volatility, and light congestion during the weekday morning peak, and the volatility and reliability indexes of the travel speed of road sections significantly decreased under the impact of the students back to school. The data showed that after the students back to school, the maximum reduction ratio of average travel speed was larger than 55%, and the maximum travel speed reliability reduction value was larger than 0.85 based on the evaluation model of travel speed reliability of car commuters. The research results provide data and theoretical support for urban road traffic congestion mitigation and governance.

A novel re-entrant honeycomb metamaterial based on 3D-printing technology is proposed by introducing chiral structures into diamond honeycomb metamaterial (DHM), named chiral-diamond-combined honeycomb metamaterial (CDCHM), and has been further optimized using the assembly idea. Compared with the traditional DHM, the CDCHM has better performance in static and vibration isolation. The static and vibration properties of the DHM and CDCHM are investigated by experiments and simulations. The results show that the CDCHM has a higher load-carrying capacity than that of the DHM. In addition, the vibration isolation optimal design schemes of the DHM and CDCHM are examined by experiments and simulations. It is found that the vibration suppression of the CDCHM is also improved greatly. In particular, the optimization approach with metal pins and particle damping achieves a wider bandgap in the low-frequency region, which can strengthen the suppression of low-frequency vibrations. And the introduction of particle damping can not only design the frequency of the bandgap via the alteration of the dosage, but also enhance the damping of the main structure. This work presents a new design idea for metamaterials, which provides a reference for the collaborative design of the static and vibration properties of composite metamaterials.

During the methanol-to-aromatics (MTA) process, a large amount of water is generated, while the influence and mechanism of water on the activity and selectivity of the light olefin aromatization reaction are still unclear. Therefore, a study was conducted to systematically investigate the effects of water on the reactivity and the product distribution in ethylene aromatization using infrared spectroscopy (IR), intelligent gravitation analyzer (IGA), and X-ray absorption fine structure (XAFS) characterizations. The results demonstrated that the presence of water reduced ethylene conversion and aromatic selectivity while increasing hydrogen selectivity at the same contact time. This indicated that water had an effect on the reaction pathway by promoting the dehydrogenation reaction and suppressing the hydrogen transfer reaction. A detailed analysis using linear combination fitting (LCF) of Zn K-edge X-ray absorption near-edge spectroscopy (XANES) on Zn/HZSM-5 catalysts showed significant variations in the state of existence and the distribution of Zn species on the deactivated catalysts, depending on different reaction atmospheres and water contents. The presence of water strongly hindered the conversion of ZnOH+ species, which served as the active centers for the dehydrogenation reaction, to ZnO on the catalyst. As a result, the dehydrogenation activity remained high in the presence of water. This study using IR and IGA techniques revealed that water on the Zn/HZSM-5 catalyst inhibited the adsorption of ethylene on the zeolite, resulting in a noticeable decrease in ethylene conversion and a decrease in aromatic selectivity. These findings contribute to a deeper understanding of the aromatization reaction process and provide data support for the design of efficient aromatization catalysts.

Abstract Background As the main pathological basis for various cardiovascular and cerebrovascular diseases, atherosclerosis has become one of the leading causes of death and disability worldwide. Emerging evidence has suggested that Rho GTPase Rnd3 plays an indisputable role in cardiovascular diseases, although its function in atherosclerosis remains unclear. Here, we found a significant correlation between Rnd3 and pyroptosis of aortic endothelial cells (ECs). Methods ApoeKO mice were utilized as a model for atherosclerosis. Endothelium‐specific transgenic mice were employed to disrupt the expression level of Rnd3 in vivo. Mechanistic investigation of the impact of Rnd3 on endothelial cell pyroptosis was carried out using liquid chromatography tandem mass spectrometry (LC‐MS/MS), co‐immunoprecipitation (Co‐IP) assays, and molecular docking. Results Evidence from gain‐of‐function and loss‐of‐function studies denoted a protective role for Rnd3 against ECs pyroptosis. Downregulation of Rnd3 sensitized ECs to pyroptosis under oxidized low density lipoprotein (oxLDL) challenge and exacerbated atherosclerosis, while overexpression of Rnd3 effectively prevented these effects. LC‐MS/MS, Co‐IP assay, and molecular docking revealed that Rnd3 negatively regulated pyroptosis signaling by direct interaction with the ring finger domain of tumor necrosis factor receptor‐associated factor 6 (TRAF6). This leads to the suppression of K63‐linked TRAF6 ubiquitination and the promotion of K48‐linked TRAF6 ubiquitination, inhibiting the activation of NF‐κB and promoting the degradation of TRAF6. Moreover, TRAF6 knockdown countered Rnd3 knockout‐evoked exacerbation of EC pyroptosis in vivo and vitro. Conclusions These findings establish a critical functional connection between Rnd3 and the TRAF6/NF‐κB/NLRP3 signaling pathway in ECs, indicating the essential role of Rnd3 in preventing pyroptosis of ECs.

Abstract Purpose To investigate mental health and self-management in glaucoma patients during the COVID-19 pandemic in China and to describe the correlation between anxiety, depression, glaucoma, and self-management. Methods This cross-sectional study included glaucoma patients who enrolled in the case management platform and completed an online survey. The survey included the Generalized Anxiety Disorder (GAD-7), Patient Health Questionnaire (PHQ-9), and Glaucoma Self-Management Questionnaire (GSMQ). Results Among 109 glaucoma patients enrolled in this study, the proportions of patients suffering from depression and anxiety during the COVID-19 pandemic were 26.6% and 20.2%, respectively. A statistical association was found between depression and self-management behaviour in these glaucoma patients (r = -0.247, P = 0.010). The self-management scores in patients less than 35 years were lower than those in patients aged 35–60 years (P = 0.046). The scores of body function promotion in men were lower than those in women (P = 0.048). Patients with primary school education and below had lower scores in the medical management of disease than those with either middle school education (P = 0.032) or community college education or higher (P = 0.022). Conclusion A high proportion of anxiety and depression was found in glaucoma patients during the COVID-19 pandemic. Better self-management behaviour was associated with stronger mental health regulation. It is important to help glaucoma patients improve their self-management behaviours, especially for young men with low educational levels.

Background: Oxidative stress could seriously affect the growth performance of piglets. As natural extracts of Alfalfa (Medicago sativa), alfalfa saponins have been shown to function as antioxidants in piglets in vivo. However, few studies have investigated the effects and mechanism of alfalfa saponins against oxidative stress in piglet cells in vitro. In the current study, piglets’ small intestinal epithelial cell line (IPEC-J2) was explored to investigate the protective effects of alfalfa saponins on injured cells induced by H2O2. Methods: To investigate the effects and mechanism of alfalfa saponins against oxidative stress in piglet cells, the cell viability, activity of antioxidant enzymes, LDH and the amount of MDA were detected in H2O2-treated cells after the cells were pre-incubated with alfalfa saponins. The mechanism of alfalfa saponins against H2O2-induced oxidative cell damage was explored by detecting the expression of mitochondrial apoptosis-related proteins. Furthermore, the signaling pathway of alfalfa saponins in IPEC-J2 cells under oxidative stress was also investigated. Results: The results indicated that alfalfa saponins could rescue cell viability, elevate the activity of antioxidant enzymes and down-regulate the activity of LDH and the amount of MDA in H2O2-induced cells. Conclusion: Alfalfa saponins could inhibit oxidative stress-induced cell mitochondrial apoptosis through the MAPK signaling pathway, thereby providing a new method for improving antioxidant stress ability by means of nutritional regulation.

Dental caries is a biofilm-related preventable infectious disease caused by interactions between the oral bacteria and the host’s dietary sugars. As the microenvironments in cariogenic biofilms are often acidic, pH-sensitive drug delivery systems have become innovative materials for dental caries prevention in recent years. In the present study, poly(DMAEMA-co-HEMA) was used as a pH-sensitive carrier to synthesize a chlorhexidine (CHX)-loaded nanomaterial (p(DH)@CHX). In vitro, p(DH)@CHX exhibited good pH sensitivity and a sustained and high CHX release rate in the acidic environment. It also exhibited lower cytotoxicity against human oral keratinocytes (HOKs) compared to free CHX. Besides, compared with free CHX, p(DH)@CHX showed the same antibacterial effects on S. mutans biofilms. In addition, it had no effect on eradicating healthy saliva-derived biofilm, while free CHX exhibited an inhibitory effect. Furthermore, the 16s rDNA sequencing results showed that p(DH)@CHX had the potential to alter oral microbiota composition and possibly reduce caries risk. In conclusion, the present study presents an alternative option to design an intelligent material to prevent and treat dental caries.