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The role of non-coding RNAs in regulating biological processes associated with cancer progression, such as proliferation, migration, and apoptosis, has been extensively studied. Long non-coding RNAs (lncRNAs) play a role in regulating these processes through various mechanisms, including transcriptional and post-transcriptional modifications. In post-transcriptional regulation, lncRNAs can bind to specific miRNAs and affect their function, which can either promote or inhibit cancer development. The interaction between lncRNAs, miRNAs, and mRNAs forms a network known as competitive endogenous RNA (ceRNA), which is involved in cancer progression or inhibition. One specific miRNA called miR-26a-5p has been identified as having tumor-suppressive properties. However, when lncRNAs bind to and inhibit miR-26a-5p, it can lead to cancer progression. Therefore, targeting this ceRNA network could be a promising strategy for preventing cancer development. This review will first discuss the anticancer effects of miR-26a-5p and then explore the involvement of the lncRNA-miR26a-5p-mRNA axis in cancer progression and potential targeted therapies. [ABSTRACT FROM AUTHOR]

In the case of emergency evacuation of large places, the rapid evacuation of pedestrians has always been a matter of great concern. However, research on pre-movement behavior and decision-making fatigue behavior of pedestrians in emergency evacuation situations is limited. In order to study how to improve evacuation efficiency under the introduction of exit-choice system, this paper uses the cellular automata model to simulate different exit arrangements and exit numbers at different time intervals of information update by the system. It is found that there is an optimal time interval of information update when three exits of a room have different widths, and the evacuation time significantly reduces compared to real-time update. The potential mechanism of the optimal time interval of information update is that the evacuees can be reasonably allocated to each exit, so that the passage capacity of each exit can be maximized, and the evacuation time is significantly reduced. Sensitivity analysis shows that the change of exit location has an important influence on the evacuation time. The different pre-movement times of pedestrians have a certain degree of influence on the evacuation time of real-time update. The different distance parameters and flow parameters had a significant impact on the evacuation time in the real-time update case. [ABSTRACT FROM AUTHOR]

Accurate forecasting of PM2.5 concentrations serves as a critical tool for mitigating air pollution. This study introduces a novel hybrid prediction model, termed MIC-CEEMDAN-CNN-BiGRU, for short-term forecasting of PM2.5 concentrations using a 24-hour historical data window. Utilizing the Maximal Information Coefficient (MIC) for feature selection, the model integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Convolutional Neural Network (CNN), and Bidirectional Recurrent Gated Neural Network (BiGRU) to optimize predictive accuracy. We used 2016 PM2.5 monitoring data from Beijing, China as the empirical basis of this study and compared the model with several deep learning frameworks. RNN, LSTM, GRU, and other hybrid models based on GRU, respectively. The experimental results show that the prediction results of the hybrid model proposed in this question are more accurate than those of other models, and the R2 of the hybrid model proposed in this paper improves the R2 by nearly 5 percentage points compared with that of the single model; reduces the MAE by nearly 5 percentage points; and reduces the RMSE by nearly 11 percentage points. The results show that the hybrid prediction model proposed in this study is more accurate than other models in predicting PM2.5. [ABSTRACT FROM AUTHOR]

This study aimed to explore the potential of employing machine learning algorithms based on intracranial pressure (ICP), ICP-derived parameters, and their complexity to predict the severity and short-term prognosis of traumatic brain injury (TBI). A single-center prospectively collected cohort of neurosurgical intensive care unit admissions was analyzed. We extracted ICP-related data within the first 6 hours and processed them using complex algorithms. To indicate TBI severity and short-term prognosis, Glasgow Coma Scale score on the first postoperative day and Glasgow Outcome Scale-Extended score at discharge were used as binary outcome variables. A univariate logistic regression model was developed to predict TBI severity using only mean ICP values. Subsequently, 3 multivariate Random Forest (RF) models were constructed using different combinations of mean and complexity metrics of ICP-related data. To avoid overfitting, five-fold cross-validations were performed. Finally, the best-performing multivariate RF model was used to predict patients' discharge Glasgow Outcome Scale-Extended score. The logistic regression model exhibited limited predictive ability with an area under the curve (AUC) of 0.558. Among multivariate models, the RF model, combining the mean and complexity metrics of ICP-related data, achieved the most robust ability with an AUC of 0.815. Finally, in terms of predicting discharge Glasgow Outcome Scale-Extended score, this model had a consistent performance with an AUC of 0.822. Cross-validation analysis confirmed the performance. This study demonstrates the clinical utility of the RF model, which integrates the mean and complexity metrics of ICP data, in accurately predicting the TBI severity and short-term prognosis. [Display omitted] [ABSTRACT FROM AUTHOR]

Droughts are increasing in frequency and intensity as the global climate changes. Risk assessment for agricultural drought disasters is an important approach for disaster prevention and mitigation. Based on the formation mechanism of natural disaster risk, the index system model of agricultural drought risk assessment in North China was constructed, and the robustness of the established risk assessment model was tested by using the internal test method. Then based on the characteristics of agricultural drought risk formation in North China, the paper proposes corresponding risk prevention recommendations. The conclusions were as follows: when adjusting the indices and methods in the risk assessment model, the range of changes in the agricultural drought risk ranking for each city was mostly 1-2.5 places, and the model was relatively robust. With the exception of Beijing and Tianjin, which had the highest disaster prevention and mitigation capacity, central and northern China had the highest agricultural drought risk, which was previously linked to the high risk and vulnerability of these regions. The agricultural drought risk in northern Henan and southern Shandong is low, mainly due to the low risk. The 34 cities in North China can be divided into 6 agricultural drought risk clusters, which are not dispersed in space and cross-city distribution, and have good aggregation. Cluster 4, located in the northernmost mountainous areas, has the highest risk of drought, which is associated with high environmental vulnerability and low capacity for disaster prevention and mitigation, so agricultural areas should be reduced and agricultural input should be increased. Clusters 2, 5 and 6, located in the central and southern regions, have higher grain acreage and yields due to drought, so agricultural drought risk can be further reduced by increasing agricultural input and improving irrigation guarantee rate. [ABSTRACT FROM AUTHOR]

Objectives: To explore the relationship between Fuhrman grade of renal cell carcinoma (RCC) and the DDD score. Methods: We reviewed the records of 527 nonmetastatic RCC patients. Demographic, clinical, and pathologic characteristics were reviewed. Binary logistic regression was used to explore the independent risk factors for high‐grade RCC (HGRCC). Results: Sex, BMI (Body Mass Index), RNS, and DDD score were significantly correlated with HGRCC. Based on these independent risk factors, we constructed two predictive models integrating the RNS and DDD scores with sex and BMI to predict tumor grade. The calibration curves of the predictive model showed good agreement between the observations and predictions. The concordance indexes (C‐indexes) of the predictive models were 0.768 (95% CI, 0.713–0.824), and 0.809 (95% CI, 0.759–0.859). Receiver operating characteristic (ROC) curves were performed to compare the predictive power of the nomograms, and the prediction model including the DDD score had better prognostic ability (p = 0.01). Conclusions: This study found that RNS, DDD score, BMI, and sex were independent predictors of HGRCC. We developed effective nomograms integrating the above risk factors to predict HGRCC. Of note, the nomogram including the DDD score achieves better prediction ability for HGRCC. [ABSTRACT FROM AUTHOR]

Public's rational flood mitigation behaviors depend on accurate perception of flood risks. The use of natural language for flood risk perception is an effective approach, and it is critical to ensure the accuracy and comprehensibility of the flood information provided by the system in natural language dialogues. This study presents a framework for large language model (LLM) that is constrained by flood knowledge and can interact with geographic information system (GIS), aimed at enhancing the public's perception of flood risks. We tested the performance of LLM within this framework and the results demonstrate that LLM can generate accurate information about floods under the constraints of entities and relationships in the knowledge graph, and interact with GIS to produce personalized knowledge through real-time coding. Furthermore, we conducted flood risk perception experiments on users with different cognitive levels. The results indicate that using natural language dialogue can narrow the differences brought about by cognitive levels, allowing the public to equally access knowledge related to flood events. [ABSTRACT FROM AUTHOR]

As an important application of virtual geographic environments (VGEs), virtual disaster scenes are essential in enhancing the public's risk awareness. However, existing virtual disaster scene visualization methods lack expert guidance and fail to meet the public's requirements, resulting in an ineffective public understanding. Therefore, this paper proposes a knowledge-guided disaster scene 3D visualization framework. First, the public's demand for disaster scene visualization is analyzed, and a geographic knowledge graph of disaster scenes is constructed. Second, through the guidance of the knowledge graph, the virtual disaster scenes are fusion modeled and suitability represented. Third, a diverse organization and adaptive scheduling method of disaster scene data for multi-computing devices is established. Finally, we developed a prototype system for disaster scene visualization, selected a typical disaster, and conducted cognitive experiments with eye-tracking technology. The results show that the proposed method can effectively support the adaptive visualization of virtual disaster scenes for four computing devices and maintain an efficient frame rate. In addition, compared with other disaster scene visualization methods, our framework incorporates semantic knowledge of scene, user, demand, and space. It can effectively convey disaster information and help the public cognize disaster risks and has significant advantages in modeling standardization, personalization, and adaptability. [ABSTRACT FROM AUTHOR]

Following the West, China exhibits a proactive attitude and conservative actions to developing entrepreneurial universities. This article deconstructs such a paradoxical approach by analysing the scholarly literature, policy discourses, and empirical data and their various perceptions of entrepreneurial universities in the Greater Bay Area (GBA). We conducted 71 interviews in four case universities to obtain empirical data for triangulation with the literature and policies. Our main research findings include the following: (1) there is a desire to introduce the concept of entrepreneurial universities from the West, along with their characteristics and aims; (2) China's policy discourse of excellence and pragmatism affects entrepreneurship education and technology transfer; and (3) an emerging identity of entrepreneurial universities is constrained by attitudes and barriers at the institutional level. China's perceptions and practices reflect a lack of sustainability of and fragmented approach to developing entrepreneurial universities, with strong implications for establishing entrepreneurial universities elsewhere. [ABSTRACT FROM AUTHOR]

Traditional solar cells face the challenges of high cost and limited conversion efficiency, which seriously limits their promotion in practical applications. Therefore, this article proposes a novel GaAs thin-film solar cell based on algae's/GaAs heterojunction. It utilizes the finite difference time domain (FDTD) method to simulate the propagation of electromagnetic waves and the process of light absorption in the cell under specific boundary conditions. The simulation experimental results demonstrate that the introduction of indium tin oxide (ITO) and Ag plasma into solar cell structure significantly enhances the light trapping capability of the cell. Under the irradiation of standard light AM1.5, the proposed cell structure maintains an absorption rate of more than 95% in the wavelength range of 300–743 nm, with an average absorption rate of 97.29%. Especially at the wavelength of 547 nm, it has an absorption rate of up to 99.87%. In addition, the short-circuit current is 30.152 mA/cm2, the open-circuit voltage is 1.226 V, and the photoelectric conversion efficiency (PCE) is increased to 33.22%. The research result indicates when light illuminates the surface of the metal particles after incorporating Ag nanoparticles into the ITO grating, the free electrons within the metal are excited, resulting in a resonance effect. This allows for a highly concentrated and localized electromagnetic wave on the metal surface, which improving the solar cell's absorption efficiency of sunlight. The research will promote the development of photovoltaic technology and provide an effective strategy and reference for the manufacture of high-performance thin-film solar cells. [ABSTRACT FROM AUTHOR]

In order to realize optical sensing with high sensitivity and the figure of merit, in this study, we propose a metal–insulator-metal (MIM) waveguide structure based on the transmission properties of surface plasmon excitations (SPPs). This structure consists of main waveguide with a metal baffle (MWMB) combined with a copper coin-type ring cavity (CCTRC) and a double semi-elliptical ring cavity (DSERC). We study the electromagnetic characteristics, transmission performance, and sensing performance of the structure by simulating numerical calculations using the finite element method. In addition, we optimize the structural parameters. The results indicate that when the transverse magnetic (TM) wave is incident on the main waveguide, the designed MIM waveguide structure exhibits double Fano resonance peaks at incident wavelengths at 842 nm and 926 nm, with total electric field energies of 2.93 × 10−14 J and 2.35 × 10−14 J, respectively. At the same wavelengths, total magnetic field energies are 1.33 × 10−14 J and 1.32 × 10−14 J, respectively. Therefore, the proposed structure can be used for the refractive index sensor. The extant structure's sensitivity and the figure of merit are 1150 nm/RIU and 115, respectively. The resonance wavelength shift was identified, allowing the present structure to measure the concentration of aqueous vitamin C solutions. [ABSTRACT FROM AUTHOR]

Phosphatases can dephosphorylate phosphorylated kinases, leading to their inactivation, and ferroptosis is a type of cell death. Therefore, our aim is to identify phosphatases associated with ferroptosis by analyzing the differentially expressed genes (DEGs) of the Luminal A Breast Cancer (LumABC) cohort from the Cancer Genome Atlas (TCGA). An analysis of 260 phosphatase genes from the GeneCard database revealed that out of the 28 DEGs with high expression, only the expression of pyruvate dehydrogenase phosphatase 2 (PDP2) had a significant correlation with patient survival. In addition, an analysis of DEGs using gene ontology, Kyoto Encyclopedia of Genes and Genomes and gene set enrichment analysis revealed a significant variation in the expression of ferroptosis-related genes. To further investigate this, we analyzed 34 ferroptosis-related genes from the TCGA-LumABC cohort. The expression of long-chain acyl-CoA synthetase 4 (ACSL4) was found to have the highest correlation with the expression of PDP2, and its expression was also inversely proportional to the survival rate of patients. Western blot experiments using the MCF-7 cell line showed that the phosphorylation level of ACSL4 was significantly lower in cells transfected with the HA-PDP2 plasmid, and ferroptosis was correspondingly reduced (p < 0.001), as indicated by data from flow cytometry detection of membrane-permeability cell death stained with 7-aminoactinomycin, lipid peroxidation, and Fe2+. Immunoprecipitation experiments further revealed that the phosphorylation level of ACSL4 was only significantly reduced in cells where PDP2 and ACSL4 co-precipitated. These findings suggest that PDP2 may act as a phosphatase to dephosphorylate and inhibit the activity of ACSL4, which had been phosphorylated and activated in LumABC cells. Further experiments are needed to confirm the molecular mechanism of PDP2 inhibiting ferroptosis. [ABSTRACT FROM AUTHOR]

Efficient geovisualization is beneficial for understanding geospatial phenomena, an important research direction for GISers and Cartographers. However, the current research on geovisualization overemphasizes the visual effects while neglecting the prominent representation of crucial information and failing to consider the user's cognitive workload of information processing. Following the laws of visual perception of the human eyes, this article proposes a visual attention-guided augmented representation approach of geographic scenes that involves area of interest computation, background simplification, and compound graphic variables. Finally, we select bridge stress visualization as a case study for experimental analysis. The experimental results of eye-tracking show that augmented representation could draw the participants' attention to areas of interest in a short time, increasing their duration of fixations and the accuracy of completing given tasks. These findings suggest that our approach can enhance geographic scenes' cognitive efficiency, offers a new idea for the theoretical studies of geovisualization, and holds promising potential for broader application in various geographical phenomena visualization. [ABSTRACT FROM AUTHOR]

Major differences in beach erosion between two neighboring artificial beaches Xiangluwan Beach (XL beach) and Meiliwan Beach (ML beach) in Zhuhai, China, were studied after Super Typhoon Hato. In this study, a fully nonlinear Boussinesq wave model (FUNWAVE)-Total Variation Diminishing (TVD) was used to distinguish the main impact factors, their relative contributions, and the hydrodynamic mechanisms underlying the different beach responses. Results show that compared to the ML beach, the main reason for the relatively weak erosion on Xiangluwan (XL) beach was the smaller beach berm height (accounting for approximately 75.9% of the erosion response). Regarding the beach with a higher berm, the stronger wave-induced undertow flow, along with the higher sediment concentration, led to a higher offshore sediment transport flux, resulting in more severe erosion relative to the beach with a smaller berm height. The second most important reason explaining the weak erosion on XL beach was the absence of seawalls (accounting for approximately 17.9% of the erosion response). Wave reflection induced by the seawall could cause higher suspended sediment concentration, resulting in a toe scouring near the seawall. The offshore submerged breakwater protected XL beach slightly (accounting for approximately 6.1% of the erosion response). Due to the higher water level induced by storm surge, most of the wave energy could penetrate through the submerged breakwater. The effect of the larger berm width of XL beach was negligible. Compared to the beach with a larger berm width, the erosion/deposition regions in the beach with a narrower berm width showed shoreward migration, without significant changes in the erosion/deposition extent. Despite of this, the larger berm width could reduce the wave energy reaching the shoreline. This study of the storm stability of artificial beaches may be applied to beach restoration design. [ABSTRACT FROM AUTHOR]

It is essential to establish a digital twin scene, which helps to depict the dynamically changing geographical environment accurately. Digital twins could improve the refined management level of intelligent tunnel construction; however, research on geographical twin models primarily focuses on modeling and visual description, which has low analysis efficiency. This paper proposes a knowledge-guided intelligent analysis method for the geometric deformation of tunnel excavation profile twins. Firstly, a dynamic data-driven knowledge graph of tunnel excavation twin scenes was constructed to describe tunnel excavation profile twin scenes accurately. Secondly, an intelligent diagnosis algorithm for geometric deformation of tunnel excavation contour twins was designed by knowledge guidance. Thirdly, multiple visual variables were jointly used to support scene fusion visualization of tunnel excavation profile twin scenes. Finally, a case was selected to implement the experimental analysis. The experimental results demonstrate that the method in this article can achieve an accurate description of objects and their relationships in tunnel excavation twin scenes, which supports rapid geometric deformation analysis of the tunnel excavation profile twin. The speed of geometric deformation diagnosis is increased by more than 90% and the cognitive efficiency is improved by 70%. The complexity and difficulty of the deformation analysis operation are reduced, and the diagnostic analysis ability and standardization of the geographic digital twin model are effectively improved. [ABSTRACT FROM AUTHOR]

A large volume of research reporting the pull-out behaviour of root systems is available, but no study has considered the effects of soil drainage. This work implemented a modified three-dimensional embedded beam element model in a finite element platform that solved model equations by using a fully hydromechanically coupled algorithm. The model was validated against published centrifuge pull-out tests on root analogues, and the validated model was then applied to study parametrically the influence of the ratio of uplift rate to soil hydraulic conductivity on pull-out behaviour. The results demonstrated that the model can well capture the prepeak behaviour of the root systems up to the peak pull-out resistance. The generation of negative pore–water pressure (pex) owing to soil dilation upon root–soil interfacial shearing was the major reason for increased pull-out resistances under partially drained conditions. Compared with other root systems, root systems with smaller branch angles and deeper branch depths mobilised considerably more significant plastic deviatoric strains in the soil in their vicinity, generating more negative pex. Hyperbolic dimensionless backbone curves were derived to explain the transitional pull-out behaviours of root systems of different geometries under drainage conditions that ranged from fully drained to undrained. [ABSTRACT FROM AUTHOR]

Simple Summary: Birds have excellent visual–spatial associative learning abilities and heavily rely on them for navigation, homing, and foraging. In birds, the hippocampus (Hp) and nidopallium caudolaterale (NCL) play critical roles in this cognitive process. To enhance our understanding of how bird Hp and NCL cooperate to support visual–spatial associative learning, we examined the neural activities of the Hp and NCL of pigeons and explored their interaction dynamics during the learning process. We found that pigeons' behavioral changes during learning are accompanied by modifications in their interaction patterns in the Hp–NCL network. The enhanced theta-band synchronization between the Hp and NCL, as well as the dynamics of Hp–NCL interaction, provides insight into the potential mechanism of the Hp–NCL network during spatial associative learning. Learning the spatial location associated with visual cues in the environment is crucial for survival. This ability is supported by a distributed interactive network. However, it is not fully understood how the most important task-related brain areas in birds, the hippocampus (Hp) and the nidopallium caudolaterale (NCL), interact in visual–spatial associative learning. To investigate the mechanisms of such coordination, synchrony and causal analysis were applied to the local field potentials of the Hp and NCL of pigeons while performing a visual–spatial associative learning task. The results showed that, over the course of learning, theta-band (4–12 Hz) oscillations in the Hp and NCL became strongly synchronized before the pigeons entered the critical choice platform for turning, with the information flowing preferentially from the Hp to the NCL. The learning process was primarily associated with the increased Hp–NCL interaction of theta rhythm. Meanwhile, the enhanced theta-band Hp–NCL interaction predicted the correct choice, supporting the pigeons' use of visual cues to guide navigation. These findings provide insight into the dynamics of Hp–NCL interaction during visual–spatial associative learning, serving to reveal the mechanisms of Hp and NCL coordination during the encoding and retrieval of visual–spatial associative memory. [ABSTRACT FROM AUTHOR]

Discrimination between tectonic earthquakes (EQs) and quarry blasts is important for accurate EQ cataloguing and seismic hazard analysis. However, reliable classification of these two types of seismic events is challenging with no prior knowledge of source parameters. Here, we applied deep learning to perform this classification task in southern California and eastern Kentucky. Since the two regions differ significantly in available labelled data, class imbalance and waveform characteristics, we adopted different strategies for them. We directly trained a convolutional neural network (CNN) for southern California due to its data abundancy. To alleviate the class imbalance, the blast data were augmented by repeated sampling. The model for California yields F1-scores of >83.5 per cent when estimated by individual stations and >98.1 per cent by network average (i.e. averaging the CNN's outputs on all available stations for each event). As eastern Kentucky has a much smaller data size, we apply transfer learning to the pre-trained California model to fit the Kentucky data. The transfer-learned model yields F1-scores of >86.9 per cent when estimated by individual stations and >96.7 per cent by network average. The transfer-learned model outperforms the model re-trained from scratch for the Kentucky data. Gradient-weighted class activation mapping shows the S onset and the S long-period coda are important to identify EQs and blasts, respectively. By visual inspections of the seismograms, the source locations, the origin time and the P -wave polarities, we verified that most of the events falsely predicted by our models are actually mislabelled by seismic analysts. Our models thus show great potential in helping seismic analysts find those mislabelled events which remain hidden in the historical catalogue. Our results demonstrate that deep learning can achieve high accuracy in seismic event discrimination and that transfer learning is effective and efficient to generalize deep learning models across different regions. [ABSTRACT FROM AUTHOR]

Social media platforms play a vital role in determining valuable tourist objectives, which greatly aids in optimizing tourist path planning. As data classification and analysis methods have advanced, machine learning (ML) algorithms such as the k-means algorithm have emerged as powerful tools for sorting through data collected from social media platforms. However, traditional k-means algorithms have drawbacks, including challenges in determining initial seed values. This paper presents a novel approach to enhance the k-means algorithm based on survey and social media tourism data for tourism path recommendations. The main contribution of this paper is enhancing the traditional k-means algorithm by employing the genetic algorithm (GA) to determine the number of clusters (k), select the initial seeds, and recommend the best tourism path based on social media tourism data. The GA enhances the k-means algorithm by using a binary string to represent initial centers and to apply GA operators. To assess its effectiveness, we applied this approach to recommend the optimal tourism path in the Red Sea State, Sudan. The results clearly indicate the superiority of our approach, with an algorithm optimization time of 0.01 s. In contrast, traditional k-means and hierarchical cluster algorithms required 0.27 and 0.7 s, respectively. [ABSTRACT FROM AUTHOR]

This paper investigates the wave propagation in the graphene platelets (GPLs)-enhanced functionally graded porous plates. The governing equations of motion are obtained using the first-order shear deformation plate theory (FSDT). Subsequently, the equations are transformed into the state-space form. The wave dispersion relation is derived by solving the state space equation by means of the method of reverberation-ray matrix and the accuracy of this approach is validated through a comparative analysis with the results from relevant literature. In addition, parametric analyses are carried out, including boundary conditions, porosity coefficient, GPL mass fraction, porosity distribution, GPL distribution, and thickness-to-width ratio, on the dispersion behavior of functionally graded GPLs-reinforced porous plates. The use of GPLs in these composites is particularly promising, and the findings offer valuable insights into the design of composites with tailored properties for specific engineering applications. [ABSTRACT FROM AUTHOR]

Artificial intelligence decision systems play an important supporting role in the field of medical information. Medical image analysis is an important part of decision systems and an even more important part of medical diagnosis and treatment. The wealth of cellular information in histopathological images makes them a reliable means of diagnosing tumors. However, due to the large size, high resolution, and complex background structure of pathology images, deep learning methods still have various difficulties in the recognition of pathology images. Based on this, this study proposes a two‐stage continuous improvement‐based approach for pathology image recognition in medical decision systems. For pathology images with complex backgrounds, normalization and enhancement is performed to remove the effects of noise color, and light‐dark inconsistencies on the segmentation network. The continuous refinement PSP Net (CRPSPNet) is then designed for accurate recognition of the pathology images. CRPSPNet is divided into two stages: Pyramid Scene Parsing Network segmentation to obtain coarse segmentation results; and continuous refinement model refines the results of the first stage. Experiments using more than 1,000 osteosarcoma pathology images have shown that the method gives more accurate results with fewer computer resources and processing time than traditional optimization models. Its Intersection over Union achieves 0.76. [ABSTRACT FROM AUTHOR]

Additive microfabrication processes based on localized electroplating enable the one‐step deposition of micro‐scale metal structures with outstanding performance, e.g., high electrical conductivity and mechanical strength. They are therefore evaluated as an exciting and enabling addition to the existing repertoire of microfabrication technologies. Yet, electrochemical processes are generally restricted to conductive or semiconductive substrates, precluding their application in the manufacturing of functional electric devices where direct deposition onto insulators is often required. Here, the direct, localized electrodeposition of copper on a variety of insulating substrates, namely Al2O3, glass and flexible polyethylene, is demonstrated, enabled by electron‐beam‐induced reduction in a highly confined liquid electrolyte reservoir. The nanometer‐size of the electrolyte reservoir, fed by electrohydrodynamic ejection, enables a minimal feature size on the order of 200 nm. The fact that the transient reservoir is established and stabilized by electrohydrodynamic ejection rather than specialized liquid cells can offer greater flexibility toward deposition on arbitrary substrate geometries and materials. Installed in a low‐vacuum scanning electron microscope, the setup further allows for operando, nanoscale observation and analysis of the manufacturing process. [ABSTRACT FROM AUTHOR]

Subarachnoid hemorrhage (SAH) is a neurological disorder that severely damages the brain and causes cognitive impairment. MicroRNAs are critical regulators in a variety of neurological diseases. MiR-497-5p has been found to be downregulated in the aneurysm vessel walls obtained from patients with aneurysmal subarachnoid hemorrhage, but its functions and mechanisms in SAH have not been reported. Therefore, this study was designed to investigate the effect of miR-497-5p and its related mechanisms in SAH. We established an in vitro SAH model by exposing PC12 cells to oxyhemoglobin (oxyHb). We found that miR-497-5p was downregulated in SAH serum and oxyHb-treated PC12 cells, and its overexpression inhibited the oxyHb-induced apoptosis, inflammatory response and oxidative stress via activation of the Nrf2 pathway. Mechanistically, the targeting relationship between miR-497-5p and Otx1 was verified by luciferase reporter assays. Moreover, Otx1 upregulation abolished the protective effects of miR-497-5p upregulation against oxyHb-induced apoptosis, inflammation and oxidative stress in PC12 cells. Collectively, our findings indicate that miR-497-5p could inhibit the oxyHb-induced SAH damage by targeting Otx1 to activate the Nrf2/HO-1 pathway, which provides a potential therapeutic target for SAH treatment. [ABSTRACT FROM AUTHOR]

The detail and representation of a spatial layout varies with scale. This affects an individual's learning effectiveness and understanding, in turn directly influencing their behavior in a fire evacuation. However, the impact of layout learning methods with different spatial scales on fire evacuation behavior, and the relationship between spatial cognition and evacuation effects, remains unclear. We conducted spatial layout learning across three scales with 81 participants and simulated a fire evacuation scenario in a mobile virtual reality for groups. We collected evacuation decision-making and user experience questionnaires as . The results demonstrate that small-scale learning objects are the easiest for participants to understand in terms of spatial layout and relationships, but their performance in fire evacuation is poor. Large-scale learning objects significantly improve participants' evacuation efficiency. Spatial layout learning plays a crucial role in fire evacuation outcomes, but traditional spatial knowledge acquisition measurement methods cannot predict fire evacuation performance. This study sheds light on how spatial cognition influences fire evacuation behavior and provides a more reliable fire evacuation simulation method based on mobile virtual reality (MVR). [ABSTRACT FROM AUTHOR]

Numerous studies have demonstrated that NLRP3 inflammasomes are key players in the progression of atrial fibrillation (AF) in heart failure with preserved ejection fraction (HFpEF). This study aimed to analyse the effect of pharmacological inhibition of NLRP3 inflammasomes using dapansutrile (DAPA), an oral NLRP3-specific inhibitor. Dahl salt-sensitive rats were fed a high-salt diet (HSD, 8% NaCl) to induce HFpEF. Either DAPA (200 mg/kg/day) or saline was administered daily via gavage for 4 weeks. Electrophysiological studies were performed to assess the AF inducibility. Confocal fluorescence microscopy and western blot analysis were used to study calcium handling. The DAPA-treated HFpEF rats were less prone to AF induction by programmed electrical stimulation. Atrial fibrosis and inflammation were attenuated in DAPA-treated HFpEF hearts. Dapansutrile treatment showed an increase in the Ca2+ transient sarcoplasmic reticulum-Ca2+ load, and protein expression of SERCA2; NCX1 and phosphorylation of PLB at Thr17 were decreased following DAPA treatment. The increased frequency of spontaneous Ca2+ spark in the HFpEF rats was related to the hyperphosphorylation of RyR2 at Ser2814, which was blunted in DAPA treatment. Dapansutrile treatment also decreased the phosphorylation of CaMKII expression in the HFpEF rats. Mechanistically, DAPA exerts an anti-arrhythmic effect, mainly by inhibiting activation of the NLRP3 inflammasome. These data provide evidence that the beneficial cardiac effects of DAPA are associated with reduced atrial inflammation and improved CaMKII-dependent Ca2+-handling abnormalities via blunting activation of the NLRP3 inflammasome, and DAPA may be beneficial in a rat model of HFpEF-induced AF. [ABSTRACT FROM AUTHOR]

Background: The benefit-risk profile of direct oral anticoagulants (DOAC) therapy in patients with hypertrophic cardiomyopathy (HCM) and atrial fibrillation (AF) has not been well established yet. This study aimed to evaluate the efficacy and safety of DOAC compared with vitamin K antagonists (VKA) in patients with HCM and AF. Methods: PubMed, EMBASE, the Cochrane Library, and clinicaltrials.gov were searched to identify studies comparing DOAC with VKA in patients with HCM and AF. The primary endpoint was thromboembolic events. The relative risks and standard errors were pooled by random-effect models using the generic inverse variance method. Results: Seven observational studies involving 9395 patients were included in this meta-analysis. Compared to the VKA group, the DOAC group displayed a similar risk of thromboembolic events [RR (95%CI): 0.93 (0.73–1.20), p = 0.59] and ischemic stroke [RR (95%CI): 0.65 (0.33–1.28), p = 0.22]. The incidence of major bleeding was comparable between the two groups [RR (95%CI): 0.75 (0.49–1.15), p = 0.19]. Meanwhile, DOAC therapy was superior to VKA therapy in reducing the incidences of all-cause death [RR (95%CI): 0.44 (0.35–0.55), p < 0.001], cardiovascular death [RR (95%CI): 0.41 (0.22–0.75), p = 0.004], and intracranial hemorrhage [RR (95%CI): 0.42 (0.24–0.74), p = 0.003]. Conclusion: In patients with HCM and AF, DOAC therapy was similar to VKA therapy in reducing the risk of thromboembolic events, without increasing bleeding risk. In addition, the DOAC group displayed significant advantages in reducing mortality and intracranial hemorrhage compared with the VKA group. Further randomized controlled trials are needed to provide more evidence for DOAC therapy in this population. [ABSTRACT FROM AUTHOR]

The tensile strength of rocks is affected by loading conditions, specifically direct and Brazilian tension, as well as water saturation. But the fundamental reasons for the differences between direct tensile strength σ td and Brazilian tensile strength σ tb , and their degradation induced by water saturation, are not yet fully understood. Here, we report a series of direct tensile and Brazilian tests performed on marble and granite rocks under both dry and water-saturated conditions. We employed the acoustic emission (AE) technique and further analyzed the recorded AE waveforms using a methodology based on the statistical analysis of dominant frequency to infer the intrinsic failure process of studied rocks under different water and loading conditions. Our results show that water saturation causes substantial reductions in both σ td and σ tb , with the reduction in σ tb being greater. A correspondence between AE waveforms distributed in high and low dominant frequency bands (H-type and L-type waveform) and rock failure types is found, that is, the H-type waveforms correspond to the micro-shear failures, and the L-type waveforms correspond to the micro-tensile failures. Based on this, the generation of abundant micro-shear failures is the cause of enhancement in σ tb in rocks compared to its σ td , and the reductions in σ td and σ tb for saturated rocks result from increasing micro-tensile failures. Furthermore, the friction-weakening effect induced by lubricating water films is responsible for the tensile strength reduction of saturated marble and granite under direct and Brazilian tension. The pronounced friction-weakening effect resulting from the widespread friction condition in the Brazilian test facilitates the σ tb loss. In addition to the friction-weakening effect, stress corrosion could also be a secondary cause of the tensile strength reduction of saturated granite. Highlights: The corresponding relationship between acoustic emission waveform types with micro-failure patterns is built. Reasons for the difference in measured tensile strength under direct and Brazilian tension are proposed. Water-weakening effects on the tensile strength of rocks under direct tension and Brazilian loading are revealed. [ABSTRACT FROM AUTHOR]

Highly evolutionarily conserved multiprotein complexes termed Complex of Proteins Associated with Set1 (COMPASS) are required for histone 3 lysine 4 (H3K4) methylation. Drosophila Set1, Trx, and Trr form the core subunits of these complexes. We show that flies deficient in any of these three subunits demonstrated high lethality at eclosion (emergence of adult flies from their pupal cases) and significantly shortened lifespans for the adults that did emerge. Silencing Set1, trx, or trr in the heart led to a reduction in H3K4 monomethylation (H3K4me1) and dimethylation (H3K4me2), reflecting their distinct roles in H3K4 methylation. Furthermore, we studied the gene expression patterns regulated by Set1, Trx, and Trr. Each of the COMPASS core subunits controls the methylation of different sets of genes, with many metabolic pathways active early in development and throughout, while muscle and heart differentiation processes were methylated during later stages of development. Taken together, our findings demonstrate the roles of COMPASS series complex core subunits Set1, Trx, and Trr in regulating histone methylation during heart development and, given their implication in congenital heart diseases, inform research on heart disease. [ABSTRACT FROM AUTHOR]

Background: As the largest substantive organ of animals, the liver plays an essential role in the physiological processes of digestive metabolism and immune defense. However, the cellular composition of the pig liver remains poorly understood. This investigation used single-nucleus RNA sequencing technology to identify cell types from liver tissues of pigs, providing a theoretical basis for further investigating liver cell types in pigs. Results: The analysis revealed 13 cells clusters which were further identified 7 cell types including endothelial cells, T cells, hepatocytes, Kupffer cells, stellate cells, B cells, and cholangiocytes. The dominant cell types were endothelial cells, T cells and hepatocytes in the liver tissue of Dahe pigs and Dahe black pigs, which accounts for about 85.76% and 82.74%, respectively. The number of endothelial cells was higher in the liver tissue of Dahe pigs compared to Dahe black pigs, while the opposite tendency was observed for T cells. Moreover, functional enrichment analysis demonstrated that the differentially expressed genes in pig hepatic endothelial cells were significantly enriched in the protein processing in endoplasmic reticulum, MAPK signaling pathway, and FoxO signaling pathway. Functional enrichment analysis demonstrated that the differentially expressed genes in pig hepatic T cells were significantly enriched in the thyroid hormone signaling pathway, B cell receptor signaling pathway, and focal adhesion. Functional enrichment analysis demonstrated that the differentially expressed genes in pig hepatic hepatocytes were significantly enriched in the metabolic pathways. Conclusions: In summary, this study provides a comprehensive cell atlas of porcine hepatic tissue. The number, gene expression level and functional characteristics of each cell type in pig liver tissue varied between breeds. [ABSTRACT FROM AUTHOR]

Ceramide NP (Cer‐NP) has favorable effects in treating dry skin and barrier damage; nevertheless, their efficacy is hindered by a relatively low skin permeability. The most common used method to evaluate drug permeability in cosmetic filed is Franz diffusion cell, which have limitations in terms of experimental materials and manipulation, making it difficult to reliably quantify drug permeability in vivo on the human skin. In contrast, confocal Raman spectroscopy (CRM) is regarded as a versatile tool for tracking of the penetration of active molecules through the skin, which is non‐invasive, non‐destructive, and real‐time and allows in vivo testing of ceramide permeability and efficacy as well. The goal of this study was to track the skin penetration of Cer‐NP nanoemulsions (NEs) into the inner forearm skin, and to assess the short‐term effects of Cer‐NP on stratum corneum (SC) thickness, hydration, and intercellular lipids (ICL) conformation order using the water content and lateral packing order Slat = I2880/I2850, which were obtained by CRM data. Cer‐NP penetrated into the SC and epidermis, and the amount of penetration reduced with depth and increased with duration and finally retained in the SC. The results also uncovered Cer‐NP‐promoted SC hydration and increased SC thickness and Slat. The research mentioned above demonstrated that Cer‐NP NEs successfully penetrated the skin and performed moisturizing and barrier restoration functions. [ABSTRACT FROM AUTHOR]

The utilization of a low-frequency (<200 MHz) RF system in storage facilitates the attainment of ultra-low emittances in synchrotron light sources through on-axis injection. This paper focuses on the development of a low-frequency normal conducting (NC) cavity with higher-order mode (HOM) damping for fourth-generation synchrotron light sources. We propose a novel approach to achieve efficient HOM damping in a NC cavity by optimizing the lowest frequency HOM and implementing a beam-line absorber. Notably, unlike conventional NC cavities, the presence of a large beam tube for the beam-line absorber does not compromise the accelerating performance in a coaxial resonant cavity, enabling effective HOM damping while maintaining a high shunt impedance. Through simulations, the prototype design of a 166.6 MHz HOM-damped cavity demonstrates a fundamental mode impedance of ∼8 MΩ, with longitudinal and transverse HOM impedances below 2.0 and 50 kΩ/m, respectively. [ABSTRACT FROM AUTHOR]

This paper proposes a fast and accurate semantic segmentation of road crack video in a complex dynamic environment. First, a fast key frame selection algorithm is designed by combining the interframe dissimilarity constrained video frame difference method (FDM) and shot interval sampling method (SISM). Second, the complex and dynamic characteristics of application scenarios are studied, and a high-precision crack semantic segmentation DBPNet containing a densely diverse branch module (DDBM) and diverse branch pyramid module (DBPM) is proposed, which can not only focus on the local aggregation of the same scale feature but also fuse and reconstruct long-distance related semantic features. Finally, a dynamic video data set of cracks in complex environments, including multiple types of interference, different weather and lighting is established, and experimental analysis is carried out. The results show that the proposed method can improve the efficiency of video crack detection by 5–7 times compared to the method without using key frames, and the detection accuracy can reach 72.85%, which can adapt to dynamic video changes in a variety of complex scenes. The proposed network, DBPNet, outperforms the current state-of-the-art methods in road crack semantic segmentation on challenging data sets in terms of both Dice and MIOU. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new discontinuous sensor and a finite difference hybrid unequal-sized weighted essentially non-oscillatory (WENO) scheme with fifth-order accuracy for solving shallow water equations with or without source terms. The developed discontinuous sensor is directly designed based on the highest degree polynomial obtained from the five-point stencil in the unequal-sized WENO procedures, and can automatically identify the discontinuous region without manually adjusting the parameters related to the problem. Subsequently, a hybrid unequal-sized WENO scheme is developed through this newly designed discontinuous sensor, which uses the cheap linear scheme in the smooth regions and the existing expensive unequal-sized WENO scheme in the vicinity of discontinuous, thus achieving the goal of inheriting the excellent characteristics of the unequal-sized WENO scheme while reducing its computing time. Finally, some benchmark numerical examples are provided to verify the performance of this new WENO scheme for solving shallow water equations in terms of high-order accuracy, exact conservation property, shock capture capability, and computational efficiency. [ABSTRACT FROM AUTHOR]

Charge trapping memory with the P-Si/Al2O3/LaTiO/Al2O3/Pt structure was fabricated by a pulsed laser deposition system. An innovative high-k nanocrystal-amorphous phase structure could be stably formed in the charge trapping layer. The La2O3 nanocrystals are embedded in amorphous TiO2. Numerous charge traps are generated at the phase interface, which could significantly increase the charge trapping capability. A larger memory window of 16.56 V at ±12 V sweep voltage is observed, comparing with a lower value of 5.52 V for the simple amorphous structure. The device also demonstrated excellent stability, with only a 13% charge loss rate after 10 years and an unchanged memory window after 105 program/erase cycles. It is attributed to the structure that the amorphous phase isolates the trapped electrons around the nanocrystal and, thus, is resistant to loss. This work could provide an approach to generating charge traps by phase separation of high-k materials for future nonvolatile memory applications. [ABSTRACT FROM AUTHOR]

Species generally exhibit one‐state aromaticity either in the lowest singlet state (S0) or the lowest triplet state (T1) according to the Hückel's and Baird's rules. Hence, it is rare for species exhibit two‐state aromaticity in both the S0 and T1 states (termed as adaptive aromaticity), let alone adaptive σ aromaticity. Here, we report adaptive σ aromaticity in unsaturated rhenacyclopropene rings via density functional theory (DFT) calculations. Various aromaticity indices including NICS, ACID, EDDB together with isodesmic reactions support the adaptive σ aromaticity in these rhenacyclopropene rings. As the T1 state of these species is formed by the ππ* excitation, the σ‐aromaticity of these three‐membered rings in the S0 state could hold in the T1 state. In addition, the aromaticity effect of the fused rings is also examined. Our findings expand the family of adaptive σ aromaticity, enriching the metallaaromatic chemistry. [ABSTRACT FROM AUTHOR]

The addition of silicon carbide whiskers as reinforcing elements into the composite matrix plays the role of reinforcement and toughening, which can accelerate the renewal of traditional material products. Among the many reinforcing phases, the main advantage of silicon carbide whisker-reinforced composites is that they improve the strength, hardness, wear resistance, and high-temperature stability of the composites. Therefore, the application of silicon carbide whisker-reinforced composites under severe conditions such as high temperature, high pressure, high speed, and friction is of great importance. Its wide range of applications, involving aerospace, machinery manufacturing, the electronics industry, etc., has important scientific research significance and practical application value. In recent years, China has developed rapidly in the production of silicon carbide whiskers. This paper introduces the nature of silicon carbide whiskers, the strengthening mechanism, and the current research status of silicon carbide whiskers in the application of different matrix composites for performance enhancement, discusses the future challenges of related research work, and gives an outlook on the application prospects of silicon carbide whiskers. [ABSTRACT FROM AUTHOR]

Effectively integrating and correlating multisource data involved in the bridge construction process is crucial for the improvement of the bridge informatization level. In the current issues of dynamic numerous data and low information sharing between different engineering departments, the traditional information management methods are inefficient in providing comprehensive and accurate data support for construction safety. Focusing on the bridge construction stage, this article proposes a dynamic data‐driven construction method of railway bridge construction knowledge graph (KG) in combination with dynamic data (materials, personnel, equipment and sensors) in the construction process and KG technology. By taking a railway bridge as a case, the study develops a prototype system and analyzes the effectiveness of bridge construction KG in material traceability, personnel and equipment management and construction safety guidance, which can provide comprehensive and accurate data support for bridge construction management and construction optimization. The results show that: (1) bridge construction KG that takes into account the dynamic features of bridge projects can effectively integrate multiple elements; (2) the bridge construction KG is dynamically updated through real‐time comparison and advance prediction based on the dynamic data collected by multi‐sensing equipment at the construction site, and can provide effective data support for guiding bridge construction safety; and (3) the construction management prototype system based on railway bridge construction KG can provide accurate data support for material traceability, personnel and equipment management and assisted risk event decision‐making. The results of the comparative experiment between the KG group and the spreadsheet group showed that utilizing the KG saved approximately 50% of time and achieved a 20% higher accuracy rate in the material traceability task compared to the spreadsheet group. In general, this study proposes a dynamic data‐driven construction method of railway bridge construction KG, which can effectively realize the effective integration and management of multisource data in the bridge construction process, provide the necessary scientific basis for fine bridge management, and help to improve bridge informatization management level. [ABSTRACT FROM AUTHOR]

Rock masses in engineering applications are often simultaneously soaked in a moist environment and exposed to dynamic loads with different rates. It is therefore essential to understand the mechanical behavior and failure mechanism of rocks by considering the coupled effects of water saturation and rate dependence. In this study, numerous dynamic compression tests were conducted on marble and granite under oven-dried and water-saturated conditions using a split Hopkinson pressure bar apparatus. Some indices such as dynamic compressive strength, dynamic increase factor, and dissipation energy density, were unitized to investigate the mechanical behavior and failure mechanism of saturated rocks. The test results show that, regardless of the moisture state, the dynamic strength is positively sensitive to the strain rate. The existence of water contributes to the reduction of dynamic strength and elastic modulus. The dynamic strength reduction of saturated marble decreases with increasing strain rates, while that of saturated granite remains almost unchanged. As the strain rate increases, the dissipation energy density of both types of rock increases, and the ratio of energy utilization significantly decreases. Integrated investigations on the rate dependence of dynamic strength and water-weakening mechanisms suggest that the propagation and development of cracks through the region of mineral grains are responsible for strength enhancement under increasing strain rates. The overall strength reduction of saturated marble is mainly governed by the coupled effects of pore-water pressure and viscosity. With an increase in the strain rate, the strengthening viscosity effect diminishes the strength reduction primarily caused by the increasing effect of pore-water pressure. The dynamic strength of saturated granite is mainly controlled by the rate effect, and its various water-weakening effects remain almost unchanged with an increasing strain rate. The current work investigates the coupled effects of water saturation and rate dependence on the mechanical and fracturing behaviors of two different types of rock under dynamic loading conditions. It turns out that water saturation causes dynamic strength reduction, and this reduction, which depends on the rock type, is closely related to the loading rate. For carbonate rocks, the dynamic strength reduction induced by water can be suppressed by the increasing strain rate, but this is not applicable for siliceous rocks with low porosity. The results of this work highlight to engineers that lithology and microstructure are predominant factors affecting the dynamic mechanical and fracturing behavior of rocks in a water environment. The common water-weakening phenomenon in some rocks can be inhibited by the loading rate, resulting in a conservative engineering design. However, more academic and practical investigations on the coupled effects of water saturation and loading rate are required since the rock water-weakening affected by multiple factors is a complicated topic in vague. [ABSTRACT FROM AUTHOR]

Recently, deep learning has been widely used in the classification of EEG signals and achieved satisfactory results. However, the correlation between EEG electrodes is rarely considered, which has been proved that there are indeed connections between different brain regions. After considering the connections between EEG electrodes, the graph convolutional neural network is applied to detect human motor intents from EEG signals, where EEG data are transformed into graph data through phase lag index, time-domain and frequency-domain features with different signal bands. Meanwhile, a multi-scale attention mechanism is proposed to the network to improve the accuracy of classification. By using the multi-scale attention-based graph convolutional neural network, the accuracy of 93.22% is achieved with 10-fold cross-validation, which is higher than the compared methods which ignore the spatial correlations of EEG signals. [ABSTRACT FROM AUTHOR]

• MCU complexes regulated efferocytosis by regulating Ca2+ concentration and ROS generation, and this can become a new therapeutic target. • Effective efferocytosis inhibited foam cell formation and inflammatory cytokine release. • These findings may offer new therapeutic strategies for the treatment of AS. Efferocytosis dysfunction contributes to the progression and rupture of atherosclerotic plaques. Efferocytosis is crucially modulated by intracytoplasmic Ca2+, and mitochondrial calcium uniporter (MCU) complex proteins serve as key channels for regulating Ca2+ concentration. Therefore, it was speculated that MCU may affect the development of atherosclerosis (AS) by regulating efferocytosis. In the present study, we aimed to investigate whether MCU could affect foam cell formation by regulating efferocytosis. We stimulated primary macrophages (Møs) using oxidized low-density lipoprotein (ox-LDL) to mimic the atherosclerotic microenvironment and treated them with Ru360, an MCU-specific inhibitor, and UNC1062, an inhibitor of efferocytosis. Additionally, we conducted double staining to determine the Mø efferocytosis rate. We measured the expression of MCU complexes and efferocytosis-associated proteins using western blotting (WB) and real-time quantitative polymerase chain reaction (RT-qPCR), respectively. In addition, we separately detected the Ca2+ level in the cytoplasm and mitochondria (MT) using Fluo-4 AM and Rhod-2 methods. We separately determined the reactive oxygen species (ROS) level in cytoplasm and MT using dichlorodihydrofluorescein diacetate (DCFH-DA) fluorescent probing method and Mito-SOXTM superoxide indicator staining. Additionally, we conducted the enzyme-linked immunosorbent assay (ELISA) to detect the production of interleukin-6 (IL-6), interleukin-18 (IL-18), interleukin-1β (IL-1β), and tumor necrosis factor-alpha (TNF-α). Oil Red O staining was performed to measure cytoplasmic lipid levels. Ru360 attenuated ox-LDL-induced efferocytosis dysfunction, and attenuated the upregulation of MCU and MCUR1 induced by ox-LDL, and meanwhile attenuated the downregulation of MCUb induced by ox-LDL. Ru360 attenuated the decrease of intracytoplasmic Ca2+ concentration induced by ox- LDL, Ru360 also attenuated the ROS production induced by ox- LDL, attenuated the release of IL-6, IL-18, IL-1β, and TNF-α induced by ox- LDL, and attenuated the increase of intracytoplasmic lipid content induced by ox-LDL. UNC1062 attenuated the effects of Ru360 in reducing inflammatory cytokines and intracytoplasmic lipid content. In this study, we found that MCU inhibition modulated intracytoplasmic Ca2+ concentration, improved impaired Mø efferocytosis, and reduced ROS generation. Macrophage efferocytosis removed apoptotic cells and prevented the release of inflammatory factor and foam cell formation, and this can be a potential new therapeutic target for alleviating atherosclerosis. [ABSTRACT FROM AUTHOR]

This paper proposes a fast and accurate semantic segmentation of road crack video in a complex dynamic environment. First, a fast key frame selection algorithm is designed by combining the interframe dissimilarity constrained video frame difference method (FDM) and shot interval sampling method (SISM). Second, the complex and dynamic characteristics of application scenarios are studied, and a high-precision crack semantic segmentation DBPNet containing a densely diverse branch module (DDBM) and diverse branch pyramid module (DBPM) is proposed, which can not only focus on the local aggregation of the same scale feature but also fuse and reconstruct long-distance related semantic features. Finally, a dynamic video data set of cracks in complex environments, including multiple types of interference, different weather and lighting is established, and experimental analysis is carried out. The results show that the proposed method can improve the efficiency of video crack detection by 5–7 times compared to the method without using key frames, and the detection accuracy can reach 72.85%, which can adapt to dynamic video changes in a variety of complex scenes. The proposed network, DBPNet, outperforms the current state-of-the-art methods in road crack semantic segmentation on challenging data sets in terms of both Dice and MIOU. [ABSTRACT FROM AUTHOR]

Informatization is an important trend in the field of mountain highway management, and the digital twin is an effective way to promote mountain highway information management due to the complex and diverse terrain of mountainous areas, the high complexity of mountainous road scene modeling and low visualisation efficiency. It is challenging to construct the digital twin scenarios efficiently for mountain highways. To solve this problem, this article proposes a knowledge-guided fusion expression method for digital twin scenes of mountain highways. First, we explore the expression features and interrelationships of mountain highway scenes to establish the knowledge graph of mountain highway scenes. Second, by utilizing scene knowledge to construct spatial semantic constraint rules, we achieve efficient fusion modeling of basic geographic scenes and dynamic and static ancillary facilities, thereby reducing the complexity of scene modeling. Finally, a multi-level visualisation publishing scheme is established to improve the efficiency of scene visualisation. On this basis, a prototype system is developed, and case experimental analysis is conducted to validate the research. The results of the experiment indicate that the suggested method can accomplish the fusion modelling of mountain highway scenes through knowledge guidance and semantic constraints. Moreover, the construction time for the model fusion is less than 5.7 ms; meanwhile, the dynamic drawing efficiency of the scene is maintained above 60 FPS. Thus, the construction of twinned scenes can be achieved quickly and efficiently, the effect of replicating reality with virtuality is accomplished, and the informatisation management capacity of mountain highways is enhanced. [ABSTRACT FROM AUTHOR]

Objective: To observe the effect of niacinamide‐containing body emollients combined with a cleansing gel on the clinical symptoms of mild atopic dermatitis (AD) in adults. Methods: From July 2022 to January 2023, adults with mild AD were enrolled at Huashan Hospital Affiliated to Fudan University using single‐center, randomized and placebo‐controlled methods. They were divided into three groups: the control group, treatment group 1 (T1) receiving niacinamide‐containing body emollients alone, and treatment group 2 (T2) receiving emollients plus niacinamide‐containing cleansing gel. All patients were orally administered 10 mg of ebastine tablets daily. AD severity (SCORAD score), peak pruritus numeric rating scale (PP‐NRS), patient‐oriented measure of eczema (POEM), dermatological quality of life index (DLQI) score, transepidermal water loss (TEWL), and stratum corneum water content (SCWC) were measured by the same dermatologist at days 0, 7, 14, and 28. Results: A total of 122 patients were enrolled, including 38 in the control group, 42 in the T1 group and 42 in the T2 group. There were no obvious adverse reactions at the end of the study and the clinical scores and stratum corneum barrier of all the groups improved significantly relative to baseline. The SCORAD, PP‐NRS, DLQI, TEWL and SCWC scores in T1 group (12.43 ± 3, 3.3 ± 0.9, 7.1 ± 2.33, 17.1 ± 9.12, 67.2 ± 21.46, seperately) and T2 group (11.17 ± 3.26, 3 ± 1.3, 6.5 ± 2.11, 16.3 ± 9.12, 69.4 ± 24.52, seperately) were significantly improved than the control group(15.1 ± 3.64, 4.3 ± 1.7, 9.5 ± 2.46, 21.2 ± 9.47, 52.7 ± 22.43, seperately) at the endpoint of the study, while compared the POEM scores, only T2 group showed the difference with control group (5.2 ± 1.4 vs. 6 ± 1.6). The epidermal barrier parameters of TEWL and SCWC in the T2 group (17.57 ± 5.24, 66.46 ± 21.38, seperately) were significantly better than that of the T1 (19.96 ± 4.45, 56.45 ± 20.48, seperately) and control group(21.89 ± 7.03, 51.56 ± 16.58, seperately) on the 14th day of follow‐up. Conclusion: The use of niacinamide‐containing body emollients can significantly improve the clinical symptoms, quality of life, and skin barrier function in patients with mild AD. The addition of niacinamide‐containing cleansing gel can also affect the clinical efficacy at certain time points. [ABSTRACT FROM AUTHOR]

The n→π* interactions describing attractive force between lone pairs (lps) of nucleophile and carbonyl or polarized unsaturated bonds have recently attracted growing attentions in various disciplines. So far, such non‐covalent driving force are mainly concentrated to intramolecular systems. Intermolecular n→π* interactions in principle could produce fascinated supramolecular systems or facilitate organic reactions, however, they remain largely underexplored due to the very weak energy of individual interaction. This review attempts to give an overview of the challenging intermolecular n→π* interactions, much efforts emphasize the supramolecular systems, catalytic processes and spectroscopic measurements. [ABSTRACT FROM AUTHOR]

The purpose of this study was to explore the semantic computed tomography (CT) features associated with BRCA1 -associated protein 1 (BAP1) and/or tumor protein p53 (TP53) mutation in clear cell renal cell carcinoma (ccRCC). Clinical characteristics and gene mutation information of 336 ccRCC patients were retrieved from The Cancer Genome Atlas–Kidney Renal Clear Cell Carcinoma database (TCGA-KIRC). Kaplan-Meier analysis was performed to examine prognosis by gene mutation. The CT imaging data and gene mutation information of 156 ccRCC patients treated between January 2019 and January 2021 (the training cohort) were retrospectively analyzed. The CT imaging information and gene mutation data of 123 patients with ccRCC were downloaded from The Cancer Imaging Archive and The Cancer Genome Atlas database (the external validation cohort). Univariate Chi-square test and multivariate binary logistic regression analysis were performed to determine predictors of gene mutation; a nomogram was developed using these predictors. Receiver operating characteristic curve analysis and the Hosmer-Lemeshow test were performed to evaluate the performance of the nomogram. Kaplan-Meier analysis showed that BAP1 and/or TP53 mutation was significantly correlated with worse survival outcome. Multivariate binary logistic regression analysis indicated ill-defined margin (P =.001), spiculated margin (P =.018), renal vein invasion (P =.002), and renal pelvis invasion (P =.001) were independent predictors of BAP1 and/or TP53 mutation. A nomogram containing these 4 semantic CT features was constructed; the area under the receiver operating characteristic curves was 0.872 (95% CI, 0.809-0.920). The Hosmer-Lemeshow test showed acceptable goodness-of-fit for the nomogram (X2 = 1.194, P =.742). The nomogram was validated in the validation cohort; it showed good accuracy (area under the receiving operating characteristic curve = 0.819, 95% CI, 0.740-0.883) and was well calibrated (X2 = 3.934, P =.559). Semantic CT features are a potential and promising method for predicting BAP1 and/or TP53 mutation status in ccRCC patients. [ABSTRACT FROM AUTHOR]

Objective: Phase transfer entropy ( T E θ ) methods perform well in animal sensory–spatial associative learning. However, their advantages and disadvantages remain unclear, constraining their usage. Method: This paper proposes the performance baseline of the T E θ methods. Specifically, four T E θ methods are applied to the simulated signals generated by a neural mass model and the actual neural data from ferrets with known interaction properties to investigate the accuracy, stability, and computational complexity of the T E θ methods in identifying the directional coupling. Then, the most suitable method is selected based on the performance baseline and used on the local field potential recorded from pigeons to detect the interaction between the hippocampus (Hp) and nidopallium caudolaterale (NCL) in visual–spatial associative learning. Results: (1) This paper obtains a performance baseline table that contains the most suitable method for different scenarios. (2) The T E θ method identifies an information flow preferentially from Hp to NCL of pigeons at the θ band (4–12 Hz) in visual–spatial associative learning. Significance: These outcomes provide a reference for the T E θ methods in detecting the interactions between brain areas. [ABSTRACT FROM AUTHOR]

Dihydromyricetin (DMY) has poor solubility and stability in water, thus limiting its application. The aim of this study was to evaluate the effect of Cordyceps militaris polysaccharide (CMP) on the solubility, stability and antioxidant activity of DMY. The solubility assay showed that the solubility of DMY in water increased approximately 3 times. The stability of DMY was increased by 1.34 times as determined by thermostatic acceleration method. The phase solubility assay showed that DMY could form AL-type inclusion complex with CMP. Infrared spectroscopy (FT-IR), scanning electron microscopy (SEM) and thermogravimetric assays of the CMP-DMY composition revealed that the binding of CMP to DMY should be attributed to the macromolecular structure, surface porous structure of CMP, and the formation of non-covalent bonding interactions. The results of in vitro antioxidant assays showed that the CMP-DMY inclusion complex inhibited DPPH, ABTS, superoxide and hydroxyl radicals by 67.24 %, 99.89 %, 41.38 % and 35.25 %, respectively. Therefore, CMP can be used as a new material to help DMY dissolution in the future, and the inclusion complex should have good prospects for application in terms of ABTS radical scavenging efficacy. [Display omitted] • Cordyceps militaris (CMP) could improve the solubility of dihydromyricetin (DMY). • CMP could improve the stability of DMY. • CMP and DMY could form the AL type of inclusion complex in water. • The CMP-DMY inclusion complex has good performance in clearing ABTS free radical. [ABSTRACT FROM AUTHOR]

WW domain containing E3 ubiquitin protein ligase 2 (WWP2) is a member of the NEDD4 E3 ubiquitin ligase family. WWP2 ligase activity is regulated by the 2, 3‐linker auto‐inhibition. Tyrosine phosphorylation of the 2, 3‐linker was identified as an activating means for releasing the auto‐inhibition of WWP2. However, the tyrosine kinase (TK) for the phosphorylation and activation remains unknown. In this report, we have found that non‐receptor TK ACK1 binds to the WW3 domain of WWP2 and phosphorylates WWP2. ACK1 phosphorylates WWP2 at the 2, 3‐linker and partially activates the ubiquitination ligase activity. Unexpectedly, tyrosine phosphorylation of the 2, 3‐linker seems not a major mode for activation of WWP2, as ACK1 causes much higher activation of the 2, 3‐linker tyrosine phosphorylation defective mutants of WWP2 than that of wild‐type WWP2. Furthermore, epidermal growth factor (EGF) stimulates tyrosine phosphorylation of WWP2 and this EGF‐stimulated phosphorylation of WWP2 is mediated by ACK1. Finally, knockdown of WWP2 by shWWP2 inhibits the EGF‐dependent cell proliferation of lung cancer A549 cells, suggesting that WWP2 may function in the EGFR signaling in lung cancer progression. Taken together, our findings have revealed a novel mechanism underlying activation of WWP2. [ABSTRACT FROM AUTHOR]

Water has substantial effects on the tensile failure behavior of rock engineering materials in excavations and underground openings. However, our understanding of the tensile failure process of wet rock and its water-weakening mechanism is limited. In this sense, a series of uniaxial tension tests, coupled with acoustic emission (AE) signal monitoring, were carried out on dry, natural, and saturated marble rock. Importantly, the dominant frequencies of AE waveforms recorded during the tension loading were analyzed by a newly introduced quantitative statistical method. The test results show that the increasing water content of marble rock leads to significant strength reductions while having no relation with the twin-peak feature of dominant frequency bands of AE waveforms. The statistical analysis suggests that the dominant micro-tensile failures always appear before micro-shear failures and increase slightly with an increase in water content. The weak pore water pressure causes the initial release moments of micro-tensile failures for natural and saturated rocks to be advanced. With increasing water contents, more micro-tensile failures carrying less energy occur, while the amount and energy of micro-shear failure both reduce significantly. The mechanism involved in the drastic tensile strength reduction is likely to be friction weakening because of the water films, which is manifested by a significant loss in the amount and energy of micro-shear failures. This work provides a reasonable explanation for the tensile strength reduction of water-bearing rock by connecting the rock micro-failure and the dominant frequency of AE waveform signals released. [ABSTRACT FROM AUTHOR]

The utilization of CO2 as a non‐toxic and cheap feedstock for C1 is a desirable route to achieve high value‐added chemicals. In this context, we report a highly efficient ruthenium‐catalyzed semi‐hydrogenation reaction of CO2‐derived ureas. Various alkyl and aryl urea derivatives were successfully hydrogenated to obtain the corresponding recyclable amines and formamides (up to 97 % yield), highlighting the good substrate applicability of this method, which makes this method a sustainable alternative for the hydrogenation of CO2 to formamides in the presence of amines. In the meantime, we have discovered a new pathway that enables rapid hydrogenation of urea derivatives even at lower H2 pressure (<5 bar). This methodology might provide a new insight into the reduction functionalization of CO2 under mild pressure to form new C−N bond. Based on the control experiments and the observed intermediate products, we clarify the mechanism for selective semi‐hydrogenation of ureas. [ABSTRACT FROM AUTHOR]