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Abstract While social media platforms promote people’s information exchange and dissemination, they also make rumors spread rapidly on online platforms. Therefore, how to detect rumors quickly, timely and accurately has become a hot topic for scholars in related fields. Traditional deep learning models ignore the relationship and topology between nodes in the rumor detection task and use fixed weights or mean aggregation strategies in the feature aggregation process, which fail to capture the complex interactions between nodes and the dynamics of information propagation, limiting the accuracy and robustness of the rumor detection model. To address these problems, we propose a location-aware weighted GraphSAGE rumor detection model GSMA. We first introduce an attention mechanism that dynamically assigns different attention weights to different neighboring nodes for different degrees of aggregation, improving GraphSAGE’s strategy of using mean-value aggregation for all neighboring nodes during the aggregation process; second, we introduce a modulated position encoding into the model and encode the position information of nodes into the features to improve the model’s ability to perceive the relative position and order of nodes; finally, the post text sentiment is incorporated into the features to provide additional semantic information for the model as a way to achieve rumor detection in microblogging platforms. Experiments show that the accuracy of the GSMA model on Ma-Weibo and Weibo23 reaches 97.43% and 97.55%, which is an improvement of 1.11% and 0.77% compared to the benchmark GraphSAGE, and all the evaluation metrics are also improved compared to other optimal rumor detection models.

Abstract Long non-coding RNAs (lncRNAs) have a notable role in the diagnosis and prognosis of cancer. However, the associations between lncRNA-related hub genes (LRHGs) expression and the corresponding outcomes have not been fully understood in lung adenocarcinoma (LUAD). Here, a total of 71 patients diagnosed with LUAD and 60 healthy volunteers at The First Affiliated Hospital of Huzhou University from April, 2023 to December, 2023 were enrolled in the present study. A LRHGs model was established using least absolute shrinkage and selection operator analyses of The Cancer Genome Atlas-LUAD datasets. The underlying mechanisms of the LRHGs were investigated via Gene Set Enrichment Analysis and Gene Set Variation Analysis. Additionally, the diagnostic role of serum HOXD cluster antisense RNA 2 (HOXD-AS2) was assessed by receiver operating characteristic (ROC) curve analysis. Lastly, TCGA-LUAD samples were divided into high- and low-HOXD-AS2 expression groups based on the median expression. The associations between HOXD-AS2 expression and miR-4538 as well as Calmodulin-Dependent Protein Kinase Type II subunit Beta (CAMK2B) levels were conducted through Pearson correlation analysis. A comprehensive analysis identified 141 differentially expressed lncRNAs between 539 LUAD tissues and 59 normal samples. A prognostic marker for overall survival was established by constructing a predictive signature consisting of 9 LRHGs. Subsequently, 474 LUAD samples were categorized into a high or low-risk group based on the median of the risk score. An independent prognostic model was constructed to confirm the validity of this categorization. Further comparisons of the clinicopathological features and LRHG-related pathways were performed between the two groups. Examinations of LRHG expression in two LUAD clusters and of the association between LRHG expression and immune infiltration were also conducted. HOXD-AS2 expression was shown to be elevated in LUAD tissues compared with matched normal tissues, and the serum HOXD-AS2 level was also notably increased in LUAD samples compared with healthy controls. The results of the ROC analysis indicated that the sensitivity and specificity of HOXD-AS2 were higher than that of cytokeratin-19 fragment (CYFRA21-1), which is a serum marker for LUAD. Pearson analyses indicated that miR-4538 level was negatively associated with HOXD-AS2 expression, but CAMK2B level showed positive correlation in LUAD. The results of the present study therefore indicated that the constructed LRHG model, particularly HOXD-AS2, could independently diagnose and predict the prognosis of LUAD, which suggested the underlying mechanism of the HOXD-AS2/miR-4538/CAMK2B, and might offer efficient strategies for LUAD treatment.

Abstract Background Cuproptosis, a recently identified type of programmed cell death triggered by copper, has mechanisms in Wilms tumor (WT) that are not yet fully understood. This research focuses on examining the link between WT and Cuproptosis-related genes (CRGs), with the goal of developing a predictive model for WT. Methods Four gene expression datasets related to WT were sourced from the GEO database. Subsequently, expression profiles of CRGs were extracted for differential analysis and immune infiltration studies. Utilizing 105 WT samples, clusters related to Cuproptosis were identified. This involved analyzing associated immune cell infiltration and conducting functional enrichment analysis. Disease-characteristic genes were pinpointed using weighted gene co-expression network analysis. Finally, the WT risk prediction model was constructed by four machine learning methods: random forest, support vector machine (SVM), generalized linear and extreme gradient strength model. The best-performing machine learning model was chosen, and a nomogram was created. The effectiveness of this predictive model was validated using methods such as the calibration curve, decision curve analysis, and by appiying it to the TARGET-GTEx dataset. Results Thirteen differentially expressed Cuproptosis-related genes were identified. The infiltration level of CD8 + T cells in WT children was lower than that in Normal tissue (NT) children, and the level of M0 infiltration of macrophages and T follicular helper cells was higher than that in NT children. In addition, two clusters of cuproptosis-related WT were identified. Enrichment analysis results indicated that genes in cluster 2 were primarily involved in cell division, nuclear division regulation, DNA biosynthesis process, ubiquitin-mediated proteolysis. The SVM model was judged to be the optimal model using 5 genes. Its accuracy was confirmed through a calibration curve and decision curve analysis, demonstrating satisfactory performance on the TARGET-GTEx validation dataset. Additional analysis revealed that these five genes exhibited high expression in both the TARGET-GTEx validation dataset and sequencing data. Conclusion This research established a link between WT and Cuproptosis. It developed a predictive model for assessing the risk of WT and pinpointed five key genes associated with the disease.

Abstract A dc voltage restorer (dc‐VR) with optimal droop control is developed to reduce the power loss and solve the dynamic current imbalance simultaneously of the zonal dc distribution system integrating multi‐parallel energy storage. Firstly, the power loss model composed of line loss and converter loss is built and it is proved to be a strictly convex function with respect to droop coefficients, which indicates the power loss can be mitigated by optimizing the current distribution. Thus, an image‐based droop optimization method is proposed to search for the optimal droop coefficients. Then, the economy of voltage compensation on power loss reduction is investigated and an ESS‐combined dc‐VR is designed, including an interleaved parallel architecture and a capacitor‐integrated electric spring (C‐ES). Unified virtual inertia is proposed for interleaved parallel bridge arms to make their dynamic performance consistent. And the newly introduced C‐ES can keep the bus voltage at the rated level to reduce the system cost. Therefore, the problem of dynamic currents imbalance is addressed from the points of converter structure (dc‐VR) and control system (unified inertia), and the power loss can be reduced by voltage recovery (C‐ES) and optimizing the current reallocation which is achieved by updating sharing coefficients from the image‐based droop optimization method. Finally, the simulation cases validate the effectiveness of the proposed optimal‐droop dc‐VR on dynamic current balance and power loss reduction, and hardware in the loop experiment results prove the consistent dynamic characteristics of the dc‐VR's arms.

The effects of sintering temperatures on the microstructures and mechanical properties of titanium carbide particles reinforced iron matrix composites (TiC/Fe MCs) fabricated by the spark plasma sintering (SPS) process with pure element powders have been systematically investigated. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), electron back scattering diffractometer (EBSD), and energy dispersive spectroscopy (EDS) have been conducted for microstructural analysis. The results show that with increasing sintering temperatures, the porosity of the composites initially decreases and then increases. Simultaneously, the grain size gradually diminishes while element diffusion becomes more uniform. Upon reaching a critical sintering temperature (1120 °C), the original grain size disappears and carbides undergo decomposition and reprecipitation to reach an equilibrium state, with which optimal comprehensive properties can be achieved (porosity decreases to a minimum of 3.85%, grain size of 2.69 μm, Vickers hardness reaches 595 HV0.5, bending strength is at 662 MPa, coefficient of friction is at 0.74, and wear loss to 0.21 mg). These property enhancements have been attributed to reduced porosity in the composites, decreased grain size, and improved anchoring effect of carbides within the matrix. Additionally, the primary fracture mechanisms and wear mechanisms of TiC/Fe MCs with different process parameters have been analyzed. When the temperature is below 1080 °C, intergranular fracture predominates, whereas transgranular and ductile fractures become predominant above this threshold. When the temperature is below 1120 °C, fatigue wear, oxidation wear, and abrasive wear are predominantly observed. Conversely, when the temperature exceeds 1120 °C, oxidation wear and abrasive wear become the primary mechanisms.

In this work, the environmental fracture behavior of marine steel and its welding joint were compared in artificial seawater. The electrochemical measurement, slow strain rate tensile test, and low-frequency cyclic loading test were conducted. The results showed that the corrosion current density and stress corrosion cracking susceptibility of welding joints were higher than those of base metal, caused by high dislocation density and residual stress in the heat-affected zone. The acidification and ion concentration occurred at the crack tip of the welding joint and basic metal. pH value and Cl− concentration at the crack tip reached 4.1 and 3.8 mol/L, respectively. The crack growth rate of the welding joint was higher than that of base metal. The crack growth behavior was controlled by the mechano-electrochemical effect at the crack tip, and hydrogen embrittlement was the main factor.

In this study, particle-reinforced aluminium matrix composites (PRAMCs) of an Al–Cu–Li alloy were prepared using nano-sized TiB₂+TiC particles. The relationship between TiB₂+TiC nanoparticles and T1 precipitates during the ageing process, as well as the influence of TiC + TiB₂ particles on the growth process of T1 precipitates during the ageing process, were investigated. The grain sizes of the A0 and A1 samples were found to be 249.89 μm and 86.42 μm, respectively. The dislocation density is greater in the deformed A1 sample. The coefficient of thermal expansion (CTE) effect generated by TiC and TiB₂ particles stimulates the precipitation process of T1 precipitates. The A1 alloy reached the peak ageing state in a shorter time and yielded a greater number of T1 precipitates. The precipitation process of T1 precipitate is: SSSS→T1P→T1. The transition from T1P (face-centered cubic, FCC) to T1 (hexagonal close packing, HCP) entails a modification in the order of packing. The recently formed T1P precipitate is attached to the established T1 precipitate and extends along the c-axis through the shared copper-rich layer that has formed on both sides of the mature T1 precipitate. The mechanical properties of sample A1 are optimal at T = 22h, with a yield strength, tensile strength, and elongation of 520 MPa, 553 MPa, and 8.2%, respectively. In comparison to the A0 sample, the yield strength and tensile strength exhibited an increase of 5.05% and 5.13%, respectively.

Aiming at the problems that the failure of members can change the stress state of the structure, and the building may be severely damaged or even collapsed due to aftershock sequences, the effect of aftershock sequences and link failure on the seismic performance of K-eccentrically braced steel frames (K-EBF) was investigated. Incremental dynamic analysis, fragility analysis, and collapse-resistant performance evaluations of 12-story and 18-story K-EBF were conducted by using the maximum inter-story drift as the seismic demand parameter and peak seismic acceleration as the ground motion intensity parameter. The results show that compared with non-considering the effect of aftershock sequences and link failure, under the fortification earthquakes, the two factors (aftershock sequences and link failure) make the θmax of the 12-story and 18-story K-EBF structures increase by 2.3% and 8.4%, and the probability of severe damage increase by 0.6% and 2.8%, respectively; Under rare earthquakes, the θmax of the 12-story and 18-story K-EBF structures increase by 21.0% and 42.1%, and the probability of severe damage failure increase by 11.6% and 19.4%, respectively; In addition, the minimum structural collapse reserve factor decreases by 32.1% and 31.2% for 12-story and 18-story structures, respectively; Overall, aftershock sequences will aggravate the structure damage accumulation, and the negative effect on the structure increases with the intensity of the earthquakes;The failure probabilities of different limit state will further increase after considering the link failure, which will result in a further decrease with the minimum structural collapse reserve factor; Therefore, the effects caused by aftershock sequences and link failure should be fully considered in the seismic performance analysis of K-EBF to reveal the structural real dynamic response under earthquakes. Taking both the damage failure of link failure and the effect of aftershocks into consideration can comprehensively analyze the seismic performance of K-EBF structures, which provides a more reliable basis for seismic design.

Abstract Objective To investigate the prognostic significance of CXCL8 in cervical cancer and its effect on immune response based on bioinformatics method. Methods This study employs the HPA database to investigate CXCL8 expression in normal human tissues.The TIMER2.0 database is utilized to analyze CXCL8 expression across various types of cancer.Utilizing the TCGA database, we analyze the correlation between CXCL8 and the overall survival (OS) and progression-free interval (PFI) of patients with various tumors using R 4.3.2.Additionally, its association with immune checkpoint-related genes across various types of cancer is examined.We further analyze the association between CXCL8 expression and the expression of LAG3, CTLA4, PDCD1, and CD274 in cervical cancer.The TIMER database is used to study the association between CXCL8 and the extent of Tumor-Infiltrating Immune Cells (TIICs) infiltration.Enrichment analysis of genes related to CXCL8 is conducted using the LinkedOmics database. Result CXCL8 is found in a wide range of normal human tissues.In the majority of tumor tissues, CXCL8 expression is elevated compared to their normal counterparts.There is a significant correlation between CXCL8 expression and the overall survival (OS) and progression-free interval (PFI) of patients with various tumors.CXCL8 expression is associated with the expression of diverse immune checkpoint-related genes and the extent of Tumor-Infiltrating Immune Cells (TIICs) infiltration.Genes related to CXCL8 participate in diverse immune-related processes in cervical cancer. Conclusion CXCL8 plays a role in modulating immune infiltration, thereby influencing the prognosis of patients with various tumors, particularly those with cervical cancer.CXCL8 could potentially act as a biomarker for forecasting the prognosis and immune response of patients with tumors.

Abstract Resilience, the ability to maintain fundamental functionality amidst failures and errors, is crucial for complex networked systems. Most analytical approaches rely on predefined equations for node activity dynamics and simplifying assumptions on network topology, limiting their applicability to real-world systems. Here, we propose ResInf, a deep learning framework integrating transformers and graph neural networks to infer resilience directly from observational data. ResInf learns representations of node activity dynamics and network topology without simplifying assumptions, enabling accurate resilience inference and low-dimensional visualization. Experimental results show that ResInf significantly outperforms analytical methods, with an F1-score improvement of up to 41.59% over Gao-Barzel-Barabási framework and 14.32% over spectral dimension reduction. It also generalizes to unseen topologies and dynamics and maintains robust performance despite observational disturbances. Our findings suggest that ResInf addresses an important gap in resilience inference for real-world systems, offering a fresh perspective on incorporating data-driven approaches to complex network modeling.

Based on the oil and gas exploration in the Sichuan Basin, combined with data such as seismic, logging and geochemistry, the basic geological conditions, hydrocarbon types, hydrocarbon distribution characteristics, source- reservoir relationship and accumulation model of the Upper Triassic–Jurassic continental whole petroleum system in the basin are systematically analyzed. The continental whole petroleum system in the Sichuan Basin develops multiple sets of gas-bearing strata, forming a whole petroleum system centered on the Triassic Xujiahe Formation source rocks. The thick and high-quality source rocks in the Upper Triassic Xujiahe Formation provide sufficient gas source basis for the continental whole petroleum system in the basin. The development of conventional-unconventional reservoirs provides favorable space for hydrocarbon accumulation. The coupling of faults and sandbodies provides a high-quality transport system for gas migration. Source rocks and reservoirs are overlapped vertically, and there are obvious differences in sedimentary environment, reservoir lithology and physical properties, which lead to the orderly development of inner-source shale gas, near-source tight gas, and far-source tight–conventional gas in the Upper Triassic–Jurassic, from bottom to top. The orderly change of geological conditions such as burial depth, reservoir physical properties, formation pressure and hydrocarbon generation intensity in zones controlled the formation of the whole petroleum system consisting of structural gas reservoir in thrust zone, shale gas-tight gas reservoir in depression zone, tight gas reservoir in slope zone, and tight gas–conventional gas reservoir in uplift zone on the plane. Based on the theory and concept of the whole petroleum system, the continental shale gas and tight gas resources in the Sichuan Basin have great potential, especially in the central and western parts with abundant unconventional resources.

Abstract Maternal use of e-cigarette (e-cig) aerosols poses significant risks to fetal brain development, potentially increasing susceptibility to neurodevelopmental disorders in later life. However, the underlying mechanisms remain incompletely understood. This study aimed to understand the effects of fetal e-cig exposure on DNA methylome and transcriptomic changes in the neonatal brain. Pregnant rats were exposed to e-cig aerosols, and neonatal brains (5 males and 5 females/group) from both control and e-cig-exposed groups were used for experimental analysis. Results indicated that prenatal e-cig exposure altered site-specific DNA methylation patterns at both CpG and CH (non-CpG) sites, predominantly in intergenic and intronic regions, with sex dimorphism in methylation and gene expression changes. Gene ontology analysis revealed that e-cig exposure not only affected neuron projection development and axonogenesis but also altered pathways related to neurodegeneration and long-term depression. These findings provide novel insights into the dynamic changes of CpG and CH methylation induced by e-cig exposure, underscoring the susceptibility of the developing brain to maternal e-cig exposure and its potential implications for developmental disorders and neurodegenerative diseases later in life.

Abstract The air-water interface of microbubbles represents a crucial microenvironment that can dramatically accelerate reactive oxidative species (ROS) reactions. However, the dynamic nature of microbubbles presents challenges in probing ROS behaviors at the air-water interface, limiting a comprehensive understanding of their chemistry and application. Here we develop an approach to investigate the interfacial ROS via coupling microbubbles with a Fenton-like reaction. Amphiphilic single-Co-atom catalyst (Co@SCN) is employed to efficiently transport the oxidant peroxymonosulfate (PMS) from the bulk solution to the microbubble interface. This triggers an accelerated generation of interfacial sulfate radicals (SO4 •−), with 20-fold higher concentration (4.48 × 10−11 M) than the bulk SO4 •−. Notably, the generated SO4 •− is preferentially situated at the air-water interface due to its lowest free energy and the strong hydrogen bonding interactions with H3O+. Moreover, it exhibits the highest oxidation reactivity toward gaseous pollutants like toluene, with a rate constant of 1010 M−1 s−1-over 100 times greater than bulk reactions. This work demonstrates a promising strategy to harness the air-water interface for accelerating ROS-induced reactions, highlighting the importance of interfacial ROS and its potential application.

Abstract Background Subarachnoid hemorrhage (SAH) is a life -threatening cerebrovascular disease, where early brain injury (EBI) stands as a primary contributor to mortality and unfavorable patient outcomes. Neuronal ferroptosis emerges as a key pathological mechanism underlying EBI in SAH. Targeting ferroptosis for therapeutic intervention in SAH holds significant promise as a treatment strategy. Methods SAH model was induced via intravascular puncture and quantitatively assessed the presence of neuronal ferroptosis in the early phase of SAH using FJC staining, Prussian blue staining, as well as malondialdehyde (MDA) and glutathione (GSH) measurements. Hyaluronic acid-coated ursolic acid nanoparticles (HA-PEG-UA NPs) were prepared using the solvent evaporation method. We investigated the in vivo distribution of HA-PEG-UA NPs in SAH model through IVIS and fluorescence observation, and examined their impact on short-term neurological function and cortical neurological injury. Finally, we assessed the effect of UA on the Nrf-2/SLC7A11/GPX4 axis via Western Blot analysis. Results We successfully developed self-assembled UA NPs with hyaluronic acid to target the increased CD44 expression in the SAH-afflicted brain. The resulting HA-PEG-UA NPs facilitated delivery and enrichment of UA within the SAH-affected region. The targeted delivery of UA to the SAH region can effectively inhibit neuronal ferroptosis, improve neurological deficits, and prognosis in mice. Its mechanism of action is associated with the activation of the Nrf-2/SLC7A11/GPX4 signaling pathway. Conclusions Brain-targeted HA-PEG-UA NPs was successfully developed and hold the potential to enhance SAH prognosis by limiting neuronal ferroptosis via modulation of the Nrf-2/SLC7A11/GPX4 signal. Graphical Abstract

Abstract High altitude exposure negatively affects human attentional function. However, no studies have explored the regulation of attentional and physiological functions from a dietary perspective. A total of 116 Han Chinese students from Tibet University who were born and raised in a plain area and had been living in Tibet for > 2 years were recruited. All participants were male migrants. A food frequency questionnaire, complete blood count, and attention network test were performed on the participants. Pearson’s correlation was applied to assess the reliability and validity of the food frequency questionnaire. Principal component analysis was utilized to extract dietary patterns. A linear mixed model was employed to account for individual differences. The results showed that the five main dietary patterns were coarse grain, alcohol, meat, protein, and snacking dietary patterns. Furthermore, individuals who adhered to the coarse grain dietary pattern and had high mean corpuscular hemoglobin showed better attentional performance. Individuals with high alcohol consumption and systemic immune-inflammation index levels exhibited worse attentional performance. These findings imply that high-altitude migrants should include more coarse grains in their daily diet and avoid excessive alcohol consumption to improve attention.

Abstract PROTAC® (proteolysis-targeting chimera) molecules induce proximity between an E3 ligase and protein-of-interest (POI) to target the POI for ubiquitin-mediated degradation. Cooperative E3-PROTAC-POI complexes have potential to achieve neo-substrate selectivity beyond that established by POI binding to the ligand alone. Here, we extend the collection of ubiquitin ligases employable for cooperative ternary complex formation to include the C-degron E3 KLHDC2. Ligands were identified that engage the C-degron binding site in KLHDC2, subjected to structure-based improvement, and linked to JQ1 for BET-family neo-substrate recruitment. Consideration of the exit vector emanating from the ligand engaged in KLHDC2’s U-shaped degron-binding pocket enabled generation of SJ46421, which drives formation of a remarkably cooperative, paralog-selective ternary complex with BRD3BD2. Meanwhile, screening pro-drug variants enabled surmounting cell permeability limitations imposed by acidic moieties resembling the KLHDC2-binding C-degron. Selectivity for BRD3 compared to other BET-family members is further manifested in ubiquitylation in vitro, and prodrug version SJ46420-mediated degradation in cells. Selectivity is also achieved for the ubiquitin ligase, overcoming E3 auto-inhibition to engage KLHDC2, but not the related KLHDC1, KLHDC3, or KLHDC10 E3s. In sum, our study establishes neo-substrate-specific targeted protein degradation via KLHDC2, and provides a framework for developing selective PROTAC protein degraders employing C-degron E3 ligases.

Abstract Multiple myeloma (MM), a hematological malignancy of the bone marrow, remains largely incurable. The orphan G protein-coupled receptor, GPRC5D, which is uniquely expressed in plasma cells and highly expressed in MM, is a compelling candidate for immunotherapy. In this study, we investigated the efficacy of a combination of DNA vaccine encoding mouse GPRC5D and PD-1 blockade in preventing and treating MM using the 5TGM1 murine model of MM. The mouse vaccine alone was effective in preventing myeloma growth but required PD-1 antibodies to inhibit established MM tumors. We next evaluated the prophylactic and therapeutic efficacy of a nanoplasmid vector encoding human GPRC5D in several murine syngeneic tumor models. Similar results for tumor inhibition were observed, as human GPRC5D-specific T cells and antibodies were induced by DNA vaccines. Taken together, these findings underscore the potential of GPRC5D-targeted DNA vaccines as versatile platforms for the treatment and prevention of MM.

Abstract Air quality is closely linked to human health and social development, making accurate air quality prediction highly significant. The Air Quality Index (AQI) is inherently a time series. However, most previous studies have overlooked its temporal features and have not thoroughly explored the relationship between pollutant emissions and air quality. To address this issue, this study establishes a historical correlation model for air quality based on a time series model—the Gaussian Hidden Markov Model (GHMM)—using industrial exhaust emissions and historical air quality data. Firstly, a traversal method is used to select the optimal number of hidden states for the GHMM. To optimize the traditional GHMM and reduce error accumulation in the prediction process, the Multi-day Weighted Matching method and the Fixed Training Set Length method are utilized. Both direct and indirect prediction modes are then used to predict the AQI in the Zhangdian District. Experimental results indicate that the improved GHMM with the indirect mode provides higher accuracy and more stable state estimation results (MAE = 13.59, RMSE = 17.59, mean forecasted value = 117.94). Finally, the air quality historical correlation model is integrated with the air quality meteorological correlation model from a previous study, further improving prediction accuracy (MAE = 11.59, RMSE = 14.87, mean forecasted value = 120.88). This study demonstrates that the GHMM’s strong ability to analyze temporal features significantly enhances the accuracy and stability of air quality predictions. The integration of the air quality historical correlation model with the air quality meteorological correlation model from a previous study leverages the strengths of each sub-model in handling different feature groups, leading to even more accurate predictions.

Abstract Micro-expressions are spontaneous, rapid and subtle facial movements that can hardly be suppressed or fabricated. Micro-expression recognition (MER) is one of the most challenging topics in affective computing. It aims to recognize subtle facial movements which are quite difficult for humans to perceive in a fleeting period. Recently, many deep learning-based MER methods have been developed. However, how to effectively capture subtle temporal variations for robust MER still perplexes us. We propose a counterfactual discriminative micro-expression recognition (CoDER) method to effectively learn the slight temporal variations for video-based MER. To explicitly capture the causality from temporal dynamics hidden in the micro-expression (ME) sequence, we propose ME counterfactual reasoning by comparing the effects of the facts w.r.t. original ME sequences and the counterfactuals w.r.t. counterfactually-revised ME sequences, and then perform causality-aware prediction to encourage the model to learn those latent ME temporal cues. Extensive experiments on four widely-used ME databases demonstrate the effectiveness of CoDER, which results in comparable and superior MER performance compared with that of the state-of-the-art methods. The visualization results show that CoDER successfully perceives the meaningful temporal variations in sequential faces.

The research focused on addressing various challenges in intelligent top caving theory, intelligent perception and recognition key technology, intelligent caving comprehensive decision-making technology, and remote caving intelligent control technology of fully mechanized top coal caving face. This is being done under the “13th Five-Year” national key research and development plan, specifically designed for the key technology and demonstration of intelligent fully mechanized top coal caving mining method with annual production of 10 million of tons in extra-thick coal seam. The research has resulted in the following outcomes: ① Comprehensive experiments were conducted to understand the interaction process of crushing and migrating of roof and top coal combination (RTCC) and the fragmentation distribution of RTCC under different roof conditions. A three-dimensional laser goaf space detection technology has been developed, and the arching phenomenon of top coal blocks on contact, at coal discharge process with multiple coal discharge ports, has been validated. In addition, the numerical simulation of multi-port intelligent coal caving in extra-thick coal seam is carried out with the constraints of mining and caving coordination, high recovery rate, and low gangue ratio, and the number of coal caving ports is determined. those provide a reliable theoretical basis for optimizing intelligent coal-caving processes. ②The research has explored the geological information and physical characteristics of coal and gangue in the working face, along with full-cycle sensing elements of the top coal caving process. This has led to the development of a comprehensive sensing technology system, including real time detection of top coal thickness, accurate identification of coal and gangue, and dynamic measurement of coal flow, providing crucial data information support for decision making of intelligent coal top caving technology. ③A multi-source information database has been established for the man-machine-environment interface, and a decision-making model has been developed for fully mechanized top caving in extra-thick coal seams. An intelligent coal top caving decision-making software based on the Q-learning algorithm has been created, utilizing artificial intelligence for coal and gangue identification, top coal thickness detection, and coal quantity monitoring. ④A high-precision inertial navigation monitoring and control technology for intelligent fully mechanized caving faces has been developed, enabling real-time positioning, attitude monitoring, and action control for the shearer, hydraulic support, and scraper conveyor. An intelligent mine-integrated communication scheduling system and a remote-integrated control platform for fully mechanized caving have also been established. Those allow for the successful implementation of intelligent coal caving in remote one-button start mode. ⑤Advanced technologies such as ground-penetrating radar for top coal thickness detection, vibration-audio-hyperspectral for coal-gangue identification, and laser three-dimensional scanning for real-time coal caving monitoring are utilized in the 8222 Working Face of Tashan Mine. Intelligent coal caving decision software is applied in fully mechanized caving operations, leading to a control of errors within 10.71% for top coal thickness detection, 9.32% for mixed gangue rate, and 7.8% for coal caving amount. On average, each coal caving cycle now saves about 30 minutes, leading to intelligent and efficient coal caving operations with an annual output of 15 million tons.

Abstract Accurate identification and classification of equipment defects are essential for assessing the health of power equipment and making informed maintenance decisions. Traditional defect classification methods, which rely on subjective manual records and intricate defect descriptions, have proven to be inefficient. Existing approaches often evaluate equipment status solely based on defect grade. To enhance the precision of power equipment defect identification, we developed a multi-label classification dataset by compiling historical defect records. Furthermore, we assessed the performance of 11 established multi-label classification methods on this dataset, encompassing both traditional machine learning and deep learning methods. Experimental results reveal that methods considering label correlations exhibit significant performance advantages. By employing balanced loss functions, we effectively address the challenge of sample imbalance across various categories, thereby enhancing classification accuracy. Additionally, segmenting the power equipment defect classification task, which involves numerous labels, into label recall and ranking stages can substantially improve classification performance. The dataset we have created is available for further research by other scholars in the field.

Abstract Limited data on the correlation between the perineal body (PB) and stress urinary incontinence (SUI) are available. The objectives of this study were to quantify the PB using shear wave elastography (SWE) technology with a high-frequency linear array probe to evaluate the relationship between the properties of PB and stress urinary incontinence (SUI). This study included 64 women with SUI and 70 female control participants. The length, height, perimeter, and area of PB in all participants were calculated using transperineal ultrasound, and the elasticity of PB was assessed by SWE at rest and during the maximal Valsalva maneuver, respectively. In addition, the comparison of PB parameters between the patients with SUI and the healthy participants was conducted. The transperineal ultrasound and SWE examination was performed in 134 participants, and the elastic modulus values were significantly increased from participants at rest to those during the maximal Valsalva maneuver in all participants (E max : 35.59 versus 53.13 kPa, P

Abstract Gastric cancer (GC) remains a significant health challenge due to its high mortality rate and the limited efficacy of current targeted therapies. A critical barrier in developing more effective treatments is the lack of understanding of specific mechanisms driving GC progression. This study investigates the role of Transient Receptor Potential Vanilloid 1 (TRPV1), a non-selective cation channel known for its high Ca2+ permeability and tumor-suppressive properties in gastrointestinal cancers. Specifically, we explore the impact of SUMOylation—a dynamic and reversible post-translational modification—on TRPV1’s function in GC. We demonstrate that SUMOylation of TRPV1 inhibits cell proliferation and migration in MGC-803 and AGS GC cells. By mutating amino acids near TRPV1’s existing SUMO motif (slKpE), we created a bidirectional SUMO motif (EψKψE) that enhances TRPV1 SUMOylation, resulting in further suppression of GC cell proliferation and migration. In vivo studies support these findings, showing that TRPV1 SUMOylation prevents spontaneous tumorigenesis in a mouse GC model. Further investigation reveals that TRPV1 SUMOylation increases the protein’s membrane expression by inhibiting its interaction with the adaptor-related protein complex 2 mu 1 subunit (AP2M1). This elevated membrane expression leads to increased intracellular Ca2+ influx, activating the AMP-activated protein kinase (AMPK) pathway, which in turn inhibits the proliferation and migration of GC cells.

Abstract Winter wheat constitutes approximately 20% of China’s total cereal production. However, calculations of total production based on multiplying the planted area by the yield have tended to produce overestimates. In this study, we generated sample points from existing winter wheat maps and obtained samples for different years using a temporal migration method. Random forest classifiers were then constructed using optimized features extracted from spectral and phenological characteristics and elevation information. Maps of the harvested and planted areas of winter wheat in Chinese eight provinces from 2018 to 2022 were then produced. The resulting maps of the harvested areas achieved an overall accuracy of 95.06% verified by the sample points, and the correlation coefficient between the CROPGRIDS dataset is about 0.77. The harvested area was found to be about 13% smaller than the planted area, which can primarily be attributed to meteorological hazards. This study represents the first attempt to map the winter wheat harvested area at 10–m resolution in China, and it should improve the accuracy of yield estimation.

Abstract Agent-based modeling and simulation have evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. Recently, integrating large language models into agent-based modeling and simulation presents a promising avenue for enhancing simulation capabilities. This paper surveys the landscape of utilizing large language models in agent-based modeling and simulation, discussing their challenges and promising future directions. In this survey, since this is an interdisciplinary field, we first introduce the background of agent-based modeling and simulation and large language model-empowered agents. We then discuss the motivation for applying large language models to agent-based simulation and systematically analyze the challenges in environment perception, human alignment, action generation, and evaluation. Most importantly, we provide a comprehensive overview of the recent works of large language model-empowered agent-based modeling and simulation in multiple scenarios, which can be divided into four domains: cyber, physical, social, and hybrid, covering simulation of both real-world and virtual environments, and how these works address the above challenges. Finally, since this area is new and quickly evolving, we discuss the open problems and promising future directions. We summarize the representative papers along with their code repositories in https://github.com/tsinghua-fib-lab/LLM-Agent-Based-Modeling-and-Simulation .

Abstract The cAMP cascade is increasingly recognized to transduce physiological effects locally through spatially limited cAMP gradients. However, little is known about how adenylyl cyclase enzymes that initiate cAMP gradients are localized. Here we address this question in physiologically relevant striatal neurons and investigate how AC localization impacts downstream signaling function. We show that the major striatal AC isoforms are differentially sorted between ciliary and extraciliary domains of the plasma membrane, and that one isoform, AC9, is uniquely concentrated in endosomes. We identify key sorting determinants in the N-terminal cytoplasmic domain responsible for isoform-specific localization. We further show that AC9-containing endosomes accumulate activated dopamine receptors and form an elaborately intertwined network with juxtanuclear PKA stores bound to Golgi membranes. Finally, we provide evidence that endosomal localization enables AC9 to selectively elevate PKA activity in the nucleus relative to the cytoplasm. Together, these results reveal a precise spatial landscape of the cAMP cascade in neurons and a key role of AC localization in directing downstream PKA signaling to the nucleus.

The genus Dendrostoma is known to inhabit tree barks associated with branch canker diseases in China and several countries of Europe. Previous studies indicated that species of Dendrostoma prefer inhabiting fagaceous hosts, especially species of Castanea. In the present study, we obtained four isolates from cankered branches of Chinese chestnut (C. mollissima) in Rizhao City, Shandong Province, China. Morphological comparisons and phylogenetical analyses of a combined ITS-tef1-rpb2 sequence matrix were conducted, which revealed two new species named Dendrostoma rizhaoense sp. nov. and D. tianii sp. nov. The new taxa are compared with other Dendrostoma species and comprehensive descriptions and illustrations are provided herein.

Diaporthe species are known as endophytes, saprobes and pathogens infecting a wide range of plants and resulting in important crop diseases. In the present study, four strains of Diaporthe were obtained from diseased leaves of Bauhinia variegata in Guangdong Province, China. Phylogenetic analyses were conducted to identify these strains using five gene regions: internal transcribed spacer (ITS), calmodulin (cal), histone H3 (his3), translation elongation factor 1-α (tef1) and β-tubulin (tub2). The results combined with morphology revealed two new species of Diaporthe named D. bauhiniicola in D. arecae species complex and D. guangzhouensis in D. sojae species complex.

Abstract Advanced glycation end products (AGEs) are a diverse range of compounds that are formed when free amino groups of proteins, lipids, and nucleic acids are carbonylated by reactive carbonyl species or glycosylated by reducing sugars. Hyperglycemia in patients with diabetes can cause an overabundance of AGEs. Excess AGEs are generally acknowledged as major contributing factors to the development of diabetic complications because of their ability to break down the extracellular matrix directly and initiate intracellular signaling pathways by binding to the receptor for advanced glycation end products (RAGE). Inflammation and oxidative stress are the two most well-defined pathophysiological states induced by the AGE–RAGE interaction. In addition to oxidative stress, AGEs can also inhibit antioxidative systems and disturb iron homeostasis, all of which may induce ferroptosis. Ferroptosis is a newly identified contributor to diabetic complications. This review outlines the formation of AGEs in individuals with diabetes, explores the oxidative damage resulting from downstream reactions of the AGE-RAGE axis, and proposes a novel connection between AGEs and the ferroptosis pathway. This study introduces the concept of a vicious cycle involving AGEs, oxidative stress, and ferroptosis in the development of diabetic complications.

Abstract Background While small extracellular vesicles (sEVs)-derived circular RNAs (circRNAs) have been emerged as significant players in cancer, the function and underlying mechanism of sEVs-derived circRNAs in anti-cancer immunity remain unclear. Methods Gastric cancer (GC)-derived circRNAs were identified using RNA-seq data from GEO datasets and quantitative reverse transcription polymerase chain reaction (qRT-PCR), RNA immunoprecipitation, dual-luciferase assay, and bioinformatics analysis were performed to investigate the regulatory axis. Transwell assay, wound healing assay, cell counting kit-8 (CCK-8) assay, and xenograft models were used to evaluate its role in GC progression in vivo and in vitro. The delivery of specific circRNAs into sEVs were verified through electron microscopy, nanoparticle tracking analysis (NTA) and fuorescence in situ hybridization (FISH). Flow cytometric analysis and immunohistochemical staining were conducted to find out how specific circRNAs mediated CD8+ T cell exhaustion and resistant to anti-programmed cell death 1 (PD-1) therapy. Results We identified that circ_0001947, packaged by GC-derived sEVs, was obviously elevated in GC and was associated with poor clinical outcome. High circ0001947 level augmented the proliferation, migration, and invasion of GC cells. Mechanistically, circ0001947 sponged miR−661 and miR−671−5p to promote the expression of CD39, which further facilitated CD8+ T cell exhaustion and immune resistance. Conversely, blocking circ_0001947 attenuated CD8+ T cell exhaustion and increased the response to anti-PD−1 therapy. Conclusions Our study manifested the therapeutic potential of targeting sEVs-transmitted circ_0001947 to prohibit CD8+ T cell exhaustion and immune resistance in GC.

Abstract The spatial arrangement of immune cells within the tumor microenvironment (TME) and their interactions play critical roles in the initiation and development of cancer. Several advanced technologies such as imaging mass cytometry (IMC) providing the immunological landscape of the TME with single-cell resolution. In this study, we develop a new method to quantify the spatial proximity between different cell types based on single-cell spatial data. Using this method on IMC data from 416 lung adenocarcinoma patients, we show that the proximity between different cell types is more correlated with patient prognosis compared to the traditional features such immune cell density and fractions. Consistent with previous reports, our results validate that proximity of T helper (Th) and B cells to cancer cells is associated with survival benefits. More importantly, we discover that the proximity of M2 macrophages to multiple immune cells is associated with poor prognosis. When Th/B cells are stratified into M2-distal and M2-proximal, the abundance of the former but not the latter category of Th/B cells is correlated with enhanced patient survival. Additionally, the abundance of M2-distal and M2-proximal cytotoxic T cells (Tc) is respectively associated with good and poor prognosis. Our results indicate that the prognostic effect of Th, Tc, and B cells in the tumor microenvironment is modulated by the nearby M2 macrophages. The proposed new method proposed can be readily applied to all single-cell spatial data for revealing functional impact of immune cell interactions.

In this study, three types of three-layer functionally graded materials (FGMs) were designed by mainting the average content of the reinforcement constant and changing the span of the composition. The B4C particle-reinforced Al-matrix FGMs and a homogeneous composite (HC) with the same average composition were prepared using the laser additive manufacturing technique. The FGMs had a higher average secondary-phase content and grain size than the HC. Large (black) and reticulated (white) secondary phases corresponding to B4C phase, T phase, and MgZn2 were observed in the as-deposited FGM samples. The content of the secondary phase in the middle layer was generally low. The bottom layer, which was in direct contact with the substrate, exhibited the smallest grain size. The hardness and wear resistance significantly improved owing to the high B4C content in the top layer. The flexural behaviors of each layer of the FGM in different directions were systematically studied. The plasticity of the single-layer material decreased with increase in the B4C content. When the bottom layer had a high B4C content, the flexural ability significantly reduced. Among all the samples, G2 with 8% B4C particle content in the top layer exhibited the best comprehensive mechanical properties. The hardness value, wear rate of the top layer, maximum bending stress, and maximum bending strain of the FGM were 177.5 HV, 0.367 × 10−3mm3/(N·m), 585.6 MPa, and 7.36%, respectively. This study can provide a reference value for the future design and development of wear-resistant gradient materials for aerospace applications.

Three types of 7185+TiB2/TiC aluminum matrix composites with different Zn/Mg ratios were prepared in this work through a water-cooled copper casting process. The effects of Zn/Mg ratio on the microstructure and mechanical properties of 20-mm-thick composites were studied by optical microscopy, electron back scattering diffraction, transmission electron microscopy, and tensile mechanical testing. The results showed that the addition of appropriate TiB2/TiC particles refined the as-cast microstructure of the alloy, and with a decrease in Zn/Mg ratio, the grain size distribution became more uniform, the crystalline phase content gradually increased, and the uniformity of the alloy increased. After aging, as the Zn/Mg ratio decreased, the size of the precipitated phase decreased, and the strengthening effect of the alloy improved. The tensile strengths of the surface layer, 1/4 layer, and center position of the A3 alloy were 558, 568, and 572 MPa, respectively. The strength difference among the different thickness layers was the smallest, and the elongation rate was greater than 12%, resulting in the best uniformity.

The precise combination of conflicting biological properties through sophisticated structural and functional design to meet all the requirements of anastomotic healing is of great demand but remains challenging. Here, we develop a smart responsive anastomotic staple (Ti–OH-MC) by integrating porous titanium anastomotic staple with multifunctional polytannic acid/tannic acid coating. This design achieves dynamic sequential regulation of antibacterial, anti-inflammatory, and cell proliferation properties. During the inflammatory phase of the anastomotic stoma, our Ti–OH-MC can release tannic acid to provide antibacterial and anti-inflammatory properties, together with immune microenvironment regulation function. At the same time, as the healing progresses, the multifunctional coating gradually falls off to expose the porous structure of the titanium anastomotic staple, which promotes cell adhesion and proliferation during the later proliferative and remodeling phases. As a result, our Ti–OH-MC exceeds the properties of clinically used titanium anastomotic staple, and can effectively promote the healing. The staple’s preparation strategy is simple and biocompatible, promising for industrialisation and clinical application. This work provides an effective anastomotic staple for anastomotic stoma healing and serve as a reference for the functional design and preparation of other types of titanium-based tissue repair materials.

Abstract The point cloud keypoint detection algorithm like USIP that uses downsampling first and then fine-tuning the sampling points cannot effectively detect the defect part of the single view defect point cloud, resulting in the inability to output the keypoints of the defect part. Therefore, this paper proposes the twin structure key point detection algorithm named TSKPD based on the idea of contrastive learning, which uses two single-view defect point clouds to synthesize relatively more complete key points for learning, so as to promote the network model to learn the features of the complete point cloud. The robustness of key point detection of point cloud is effectively improved, and the detection of single view defect point cloud is realized. The test results on ModelNet40 and ShapeNet datasets show that the coverage rate of TSKPD on the missing part of the single view defect point cloud is 12.62 higher than the existing optimal algorithm.

Inorganic dielectric films have attracted extensive attention in the field of microelectronic and electrical devices because of their wide operating temperature range, small size, and easy integration. Here, we designed and prepared eco-friendly (1-x)Bi0.45Na0.45Ba0.1TiO3-xBi(Mg1/3Nb2/3)O3 multifunctional ferroelectric thin films for energy storage and photovoltaic. The results show that Bi(Mg1/3Nb2/3)O3 can effectively improve the energy storage performance. At x = 0.05, the energy storage density and efficiency are as high as 73.1 J/cm3 and 86.2%, respectively, and can operate stably in a wide temperature range. The breakdown field strength of the thin films increased significantly, and the analysis showed that the addition of Bi(Mg1/3Nb2/3)O3 caused a change in the internal conduction mechanism. At the same time, the generation of polar nanoregions increases the relaxation characteristics, thus improving the energy storage properties. In addition, the thin film material also has excellent ferroelectric photovoltaic properties. This work represents a new design paradigm that can serve as an effective strategy for developing advanced multi-functional materials.

Abstract The pig gut virome plays a vital role in the gut microbial ecosystem of pigs. However, a comprehensive understanding of their diversity and a reference database for the virome are currently lacking. To address this gap, we established a Pig Virome Database (PVD) that comprised of 5,566,804 viral contig sequences from 4650 publicly available gut metagenomic samples using a pipeline designated “metav”. By clustering sequences, we identified 48,299 viral operational taxonomic units (vOTUs) genomes of at least medium quality, of which 92.83% of which were not found in existing major databases. The majority of vOTUs were identified as Caudoviricetes (72.21%). The PVD database contained a total of 2,362,631 protein-coding genes across the above medium-quality vOTUs genomes that can be used to explore the functional potential of the pig gut virome. These findings highlight the extensive diversity of viruses in the pig gut and provide a pivotal reference dataset for forthcoming research concerning the pig gut virome.

Abstract NPR anchor cable is a new type of support material with negative Poisson's ratio effect, which is widely used in mine support because of its superb compensating mechanical effect. In order to study more deeply the support effect of NPR anchor cable in soft rock large deformation tunnel, indoor test, numerical simulation and field monitoring were used to study the strong weathering carbonaceous slate tunnel in Min County. The study shows that NPR anchor cable has extraordinary compensating mechanical behavior for soft rock large deformation tunnel, which can control the deformation of tunnel surrounding rock below 300 mm and keep the constant resistance value around 350 kN, which has obvious effect on the control of broken rock. To provide a basis for other research on support for large deformation tunnels in soft rock.

Abstract Background Owing to the lack of evidence-based medical studies with large sample sizes, the surgical approach for the radical resection of rectal neuroendocrine tumors remains controversial. Methods We retrospectively collected the medical records of patients with rectal neuroendocrine tumors who underwent radical resection at 17 large tertiary care hospitals in China between January 1, 2010, and April 30, 2022. All patients were divided into laparoscopic and open surgery groups. After propensity score matching to reduce confounders, the postoperative and oncologic outcomes were compared between the groups. Results We enrolled 174 patients with rectal neuroendocrine tumors who underwent radical surgery. After random matching, 124 patients were included in the comparison (62, laparoscopic surgery group; 62, open surgery group). The laparoscopic surgery group had fewer complications (14.5% vs. 35.5%, P = 0.007) and superior relapse-free survival (P = 0.048). Subgroup analysis revealed that the laparoscopic surgery group had fewer complications (10.9% vs. 34.7%, P = 0.004), shorter postoperative hospital stays (9.56 ± 5.21 days vs. 12.31 ± 8.61 days, P = 0.049) and superior relapse-free survival (P = 0.025) in the rectal neuroendocrine tumors ≤ 4 cm subgroup. Conclusions Laparoscopic surgery was associated with improved postoperative outcomes and oncologic prognosis for patients with rectal neuroendocrine tumors ≤ 4 cm; it can serve as a safe and feasible option for radical surgery of rectal neuroendocrine tumors.

Abstract Background To review the changes and survey on status quo of the surgical treatment for esophageal cancer in China. The differences in diagnosis and treatment for esophageal cancer among hospitals in different regions across China were also investigated. Methods We sent questionnaires to 46 hospitals across China, investigating the volume of esophageal cancer surgeries, surgical procedures, and perioperative management under the guidance of esophageal surgery chiefs. Results A total of 46 questionnaires were sent out and collected. The survey results showed that in the past 5 years, the volume of surgeries for esophageal cancer remained stable by 23.9% of those hospitals, increased by 30.4%, and decreased by 45.7%. Of those patients treated by surgery, 19.1% were in the early stages, and 80.9% were in locally advanced stages. In terms of surgical procedures, 73.4% of the patients were treated by minimally invasive surgery and 85.7% of esophageal substitutes were a gastric conduit, 93.1% of the substitutes were pulled to the neck through the esophageal bed. For the lymph node dissection, 78.5% of the patients had a complete two‐field lymph node dissection including the para‐recurrent laryngeal nerve lymph nodes. Of the patients with neoadjuvant therapy, 53.5% received chemotherapy or chemotherapy plus immunotherapy (47.0%), and 43.5% had chemoradiation. Conclusions Currently, in China, minimally invasive surgery‐oriented multimodality treatment, including complete two‐field lymph node dissection, has become the standard approach for esophageal cancer management. Over the past decade, this standardized approach has significantly improved prognosis compared to previous decades.

Bear bile has been a valuable and effective medicinal material in traditional Chinese medicine (TCM) for over 13 centuries. However, the current practice of obtaining it through bear farming is under scrutiny for its adverse impact on bear welfare. Here, we present a new approach for creating artificial bear bile (ABB) as a high-quality and sustainable alternative to natural bear bile. This study addresses the scientific challenges of creating bear bile alternatives through interdisciplinary collaborations across various fields, including resources, chemistry, biology, medicine, pharmacology, and TCM. A comprehensive efficacy assessment system that bridges the gap between TCM and modern medical terminology has been established, allowing for the systematic screening of therapeutic constituents. Through the utilization of chemical synthesis and enzyme engineering technologies, our research has achieved the environmentally friendly, large-scale production of bear bile therapeutic compounds, as well as the optimization and recomposition of ABB formulations. The resulting ABB not only closely resembles natural bear bile in its composition but also offers advantages such as consistent product quality, availability of raw materials, and independence from threatened or wild resources. Comprehensive preclinical efficacy evaluations have demonstrated the equivalence of the therapeutic effects from ABB and those from commercially available drained bear bile (DBB). Furthermore, preclinical toxicological assessment and phase I clinical trials show that the safety of ABB is on par with that of the currently used DBB. This innovative strategy can serve as a new research paradigm for developing alternatives for other endangered TCMs, thereby strengthening the integrity and sustainability of TCM.

It is of great practical significance to reveal the law of coal powder migration and production in the unsaturated flow stage of the reservoir for the efficient extraction of coalbed methane (CBM). The gas-liquid-solid three-phase flow simulation device was used to set different coal fines particle sizes, injection flow rates, fracture widths and coal fines mass fraction. The experiment of coal fines production and migration characteristics at the initial stage of gas production in coalbed methane reservoirs was carried out, and the variation characteristics of coal fines precipitation, output and gas phase permeability and liquid phase permeability were analyzed. The research results show that with the increase of fracture width, the output quality of coal fines showed an increasing trend, and the depositional volumes of coal fines first increase and then decrease, reaching the maximum value when the fracture width was 0.1 mm. With the increase of coal fines mass fraction, the output values first increase and then decrease (the peak point of 0.15‰), and the depositional volumes of coal fines of different sizes all increase, indicating that the migration of coal fines in the reservoir has a certain extreme value of mass fraction. If it exceeds the extreme value, a large amount of coal fines will deposit and block fractures. Reasonable control of the water and gas production rate of CBM can effectively control the output of coal fines. With the increase of injection flow rate, the amount of pulverized coal deposition and the amount of pulverized coal production increased first and then decreased. When the injection flow rate is 5.0 mL/min, the amount of pulverized coal deposition is maximum, and when the injection flow rate is 7.5 mL/min, the amount of pulverized coal production is relatively high. The evolution characteristics of liquid phase permeability show two trends: gradually decreasing and first stabilizing and then decreasing gradually, while the evolution characteristics of gas permeability are more complex. According to the change of coal permeability, coal fines output and depositional characteristics, coal fines migration in fractures can be divided into three stages: slow deposition, rapid deposition and complete plugging. The research results can provide theoretical guidance for the reasonable control of coal fines production in the field of coalbed methane.

Background/Aims Metabolic dysfunction-associated steatotic liver disease (MASLD) has become an increasingly important health challenge, with a substantial rise linked to changing lifestyles and global obesity. Ursolic acid, a natural pentacyclic triterpenoid, has been explored for its potential therapeutic effects. Given its multifunctional bioactive properties, this research further revealed the pharmacological mechanisms of ursolic acid on MASLD. Methods Drug target chips and bioinformatics analysis were combined in this study to explore the potential therapeutic effects of ursolic acid on MASLD. Molecular docking simulations, surface plasmon resonance analyses, pull-down experiments, and co-immunoprecipitation assays were used to verify the direct interactions. Gene knockdown mice were generated, and high-fat diets were used to validate drug efficacy. Furthermore, initial CD4+ T cells were isolated and stimulated to demonstrate our findings. Results In this study, the multifunctional extracellular matrix phosphorylated glycoprotein secreted phosphoprotein 1 (SPP1) was investigated, highlighting its capability to induce Th17 cell differentiation, amplifying inflammatory cascades, and subsequently promoting the evolution of MASLD. In addition, this study revealed that in addition to the canonical TGF-β/IL-6 cytokine pathway, SPP1 can directly interact with ITGB1 and CD44, orchestrating Th17 cell differentiation via their joint downstream ERK signaling pathway. Remarkably, ursolic acid intervention notably suppressed the protein activity of SPP1, suggesting a promising avenue for ameliorating the immunoinflammatory trajectory in MASLD progression. Conclusions Ursolic acid could improve immune inflammation in MASLD by modulating SPP1-mediated Th17 cell differentiation via the ERK signaling pathway, which is orchestrated jointly by ITGB1 and CD44, emerging as a linchpin in this molecular cascade.

The limit load is an important input parameter of analytical flaw assessment procedures. The accuracy of limit load solutions affects the accuracy of these procedures. The present paper evaluates the influence of a class of the work functions involved in the upper bound theorem on the upper bound limit load of a round highly undermatched tensile bar. It is assumed that the weld contains a crack. The boundary value problem is axisymmetric. The work functions considered cover the entire range of physically reasonable yield criteria, assuming the material is isotropic and incompressible. The kinematically admissible velocity field chosen accounts for some features of the real velocity field. In particular, the kinematically admissible velocity field is singular near the interface between the base material and weld. As a result, the new solution predicts a more accurate limit load than available solutions for the von Mises and Tresca yield criteria. Moreover, the effect of the generalized yield criterion associated with the work functions above on the limit load is shown.

Abstract Background To explore the role of GAB2 in pan-cancer based on bioinformatics analysis. Methods Based on TCGA and GTEx databases, we used TIMER2.0 online analysis tool and R language to analyze the expression of GAB2 in pan-cancer. We used Kaplan–Meier Plotter to analyze the relationship between GAB2 and OS and RFS in pan-cancer. We utilized the CPTAC database to examine the expression of phosphorylated GAB2 in pan-cancer. We investigated the effects of mutation features on the occurrence and development of human cancers by cBioPortal and COSMIC. Using the database, we conducted an analysis of molecular compounds that have the potential to interact with GAB2 through molecular docking. Moreover, we use the TIMER to explore the relationship between GAB2 and immune cell infiltration, and draw relevant heatmaps by R language. Results GAB2 was abnormally expressed in various tumors and was associated with prognosis. There were differences in the expression of GAB2 phosphorylation in tumor tissues and corresponding normal tissues among different types of tumors. GAB2 interacts with Docetaxel and was associated with immune cell infiltration in various tumors. Conclusion GAB2 participates in regulating immune infiltration and affects the prognosis of patients. GAB2 may serve as a potential tumor marker.

In order to further improve the heat storage capacity of solar greenhouse walls and improve the indoor thermal environment, the application of paraffin-expanded perlite composite phase change material (PCM-PE) in greenhouses was studied. The transient system simulation program (TRNSYS) was used to build a model of a fabricated composite wall solar greenhouse, and measured data from sunny and cloudy days were used to verify the accuracy of the model. The model was used to analyze the changes in indoor temperature and the unit cost of the greenhouse after PCM-PE was added to the inner surfaces of the structures, such as the north roof, the side walls, and the north wall, respectively, as well as the optimal thickness of the greenhouse when PCM-PE was added to the north roof, the side walls, and the north wall. The results show that the addition of PCM-PE to the inner surfaces of different greenhouse structures has a significant effect on increasing the average indoor temperature, and the addition of PCM-PE to the inner surfaces of the side walls makes the average indoor temperature increase by 1.32 ℃ on sunny days, with the lowest unit cost of 2 094 Yuan/℃; When PCM-PE is added to the north roof, side wall, and north wall with an optimal thickness of 50 mm, the average indoor temperature and the average temperature of the north wall increase by 3.9 ℃ and 3.7 ℃ on sunny days, and by 2.2 ℃ and 2.3 ℃ on cloudy days, respectively; After adding 50 mm PCM-PE, the heat transfer coefficient of the greenhouse wall is reduced by 15% and the thermal resistance increases by 9.9% compared with that of the test greenhouse, which has a positive effect on maintaining the indoor temperature and reducing the energy consumption of the greenhouse. The effect of applying PCM-PE to different structures of greenhouses is analyzed considering the unit cost, which provides some reference for constructing greenhouses with good economy and high heat storage performance.

Abstract Brain tumors are regarded as one of the most lethal forms of cancer, primarily due to their heterogeneity and low survival rates. To tackle the challenge posed by brain tumor diagnostic models, which typically require extensive data for training and are often confined to a single dataset, we propose a diagnostic model based on the Prewitt operator and a graph isomorphic network. Firstly, during the graph construction stage, edge information is extracted from MRI (magnetic resonance imaging) images using the Prewitt filtering algorithm. Pixel points with a gray value intensity greater than 128 are designated as graph nodes, while the remaining pixel points are treated as edges of the graph. Secondly, the graph data is inputted into the GIN model for training, with model parameters optimized to enhance performance. Compared with existing work using small sample sizes, the GraphMriNet model has achieved classification accuracies of 100%, 100%, 100%, and 99.68% on the BMIBTD, CE-MRI, BTC-MRI, and FSB open datasets, respectively. The diagnostic accuracy has improved by 0.8% to 5.3% compared to existing research. In a few-shot scenario, GraphMriNet can accurately diagnose various types of brain tumors, providing crucial clinical guidance to assist doctors in making correct medical decisions. Additionally, the source code is available at this link: https://github.com/keepgoingzhx/GraphMriNet .