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Abstract Porcine circoviruses, particularly porcine circovirus type 2 (PCV2) and porcine circovirus type 3 (PCV3), significantly impact the global pig industry due to their high prevalence and pathogenicity. Conversely, porcine circovirus type 1 (PCV1) and porcine circovirus type 4 (PCV4) currently have low positivity rates. This study aimed to characterize the distribution and epidemiology of porcine circoviruses in Xinjiang, while also analyzing the genetic diversity and evolution of PCV2 and PCV3, which pose the greatest threats to the industry. In this study, we collected blood and tissue samples from 453 deceased pigs across eight regions in Xinjiang Province from 2022 to 2024. We utilized real-time PCR to detect the presence of PCV1, PCV2, PCV3, and PCV4. The positive rates were 15%, 71%, 25%, and 17%, respectively. Genetic analysis showed 9 PCV2 sequences and 12 PCV3 sequences. The capsid protein of PCV2 showed significant variability. In contrast, the amino acid sequences of capsid in PCV3 were relatively stable. Moreover, we predicted antigenic epitopes for PCV3 capsid using IEDB and ElliPro. The findings from this study provide valuable epidemiological data on PCV coinfection in the Xinjiang region and enhance the understanding of virus diversity nationwide. This research may serve as an important reference for the development of strategies to prevent and control porcine circovirus infections.

Abstract Recently, the widespread adoption of artificial intelligence (AI) has given rise to a significant trust crisis, stemming from the persistent emergence of issues in practical applications. As a crucial component of AI, data has a profound impact on the trustworthiness of AI. Nevertheless, researchers have struggled with the challenge of rationally assessing data quality, primarily due to the scarcity of versatile and effective evaluation methods. To address this trouble, a multi-dimensional hierarchical evaluation system (MDHES) is proposed to estimate the data quality. Initially, multiple key dimensions are devised to evaluate specific data conditions separately by the calculation of individual scores. Then, the strengths and weaknesses among various dimensions can be provided a clearer understanding. Furthermore, a comprehensive evaluation method, incorporating a fuzzy evaluation model, is developed to synthetically evaluate the data quality. Then, this evaluation method can achieve a dynamic balance, and meanwhile achieve a harmonious integration of subjectivity and objectivity criteria to ensure a more precise assessment result. Finally, rigorous experiment verification and comparison in both benchmark problems and real-world applications demonstrate the effectiveness of the proposed MDHES, which can accurately assess data quality to provide a strong data support for the development of trustworthy AI.

Bulk logistics is an important part of the modern logistics system. The degree of digital transformation of bulk logistics has a significant gap compared with other logistics forms. Combined with the successful experience of digital transformation, value co-creation may become one of the key strategies to solve the problem of digital transformation of bulk logistics. This study formulates a four-party evolutionary game model to analyze the strategic choices and the stability of strategy combinations in value co-creation activities among bulk logistics enterprises and related entities and conducts numerical simulation analysis to explore the factors affecting the outcomes of the proposed game. The numerical results demonstrate that the bulk logistics enterprises and government departments are the key players in the game form that drive the success of value co-creation activities, and the additional costs required by various enterprises and the policies and financial support from government departments are key factors affecting strategic choices. Our findings can serve as a reference for bulk logistics enterprises.

Abstract Non-alcoholic Fatty Liver Disease (NAFLD), noted for its widespread prevalence among adults, has become the leading chronic liver condition globally. Simultaneously, the annual disease burden, particularly liver cirrhosis caused by NAFLD, has increased significantly. Neutrophil Extracellular Traps (NETs) play a crucial role in the progression of this disease and are key to the pathogenesis of NAFLD. However, research into the specific roles of NETs-related genes in NAFLD is still a field requiring thorough investigation. Utilizing techniques like AddModuleScore, ssGSEA, and WGCNA, our team conducted gene screening to identify the genes linked to NETs in both single-cell and bulk transcriptomics. Using algorithms including Random Forest, Support Vector Machine, Least Absolute Shrinkage, and Selection Operator, we identified ZFP36L2 and PHLDA1 as key hub genes. The pivotal role of these genes in NAFLD diagnosis was confirmed using the training dataset GSE164760. This study identified 116 genes linked to NETs across single-cell and bulk transcriptomic analyses. These genes demonstrated enrichment in immune and metabolic pathways. Additionally, two NETs-related hub genes, PHLDA1 and ZFP36L2, were selected through machine learning for integration into a prognostic model. These hub genes play roles in inflammatory and metabolic processes. scRNA-seq results showed variations in cellular communication among cells with different expression patterns of these key genes. In conclusion, this study explored the molecular characteristics of NETs-associated genes in NAFLD. It identified two potential biomarkers and analyzed their roles in the hepatic microenvironment. These discoveries could aid in NAFLD diagnosis and management, with the ultimate goal of enhancing patient outcomes.

Abstract Background Ensuring that the scale and hierarchical structure of health human resources are rational, and that medical services are efficient and fair, is an important task of practical significance. On this basis, examining the impact of health human resources on the level of medical services presents a new and formidable challenge. This study aims to delve into how the scale and hierarchical structure of health human resources in China’s four major economic regions affect the fairness and efficiency of medical services, and to identify optimization strategies. Methods This study utilizes provincial panel data from China’s four major economic regions spanning the years 2009 to 2021. Initially, it provides a statistical description of the current state of health human resources and the level of medical services. Subsequently, it employs a fixed-effects model to analyze the impact of the scale and hierarchical structure of health human resources, as well as their interactive effects, on the fairness and efficiency of medical services, and discusses the interactive mechanisms between medical service fairness and medical service efficiency. Furthermore, after conducting a comprehensive evaluation of the level of medical services using the entropy weight method, it explores the regional heterogeneity and temporal dynamics in the influence of the scale and hierarchical structure of health human resources on the level of medical services. Finally, the study examines the scientific validity and rationality of the research findings through various robustness checks, including the substitution of research variables and models. Results The study found that the scale of health human resources has a promoting effect on the equity of medical services (β ≤ 0.643, p ≤ 0.01), but exhibits an inhibitory effect on the efficiency of medical services (β ≥ -0.079, p ≤ 0.1); the hierarchical structure of health human resources shows a positive impact on both the equity and efficiency of medical services (βequity ≤ 0.160, p ≤ 0.01; βefficiency ≤ 0.341, p ≤ 0.05); at the same time, the results indicate that the interactive effect of the scale and hierarchical structure of health human resources promotes equity in medical services (β = 0.067, p ≤ 0.01), but restricts the efficiency of medical services (β ≥ -0.039, p ≤ 0.01); the mechanism by which health human resources affect the level of medical services in China’s western and northeastern regions is more pronounced than in the central and eastern regions; after the implementation of the “Healthy China 2030” Planning Outline, the role of health human resources in the level of medical services has been strengthened; in the robustness tests, the model remains robust after replacing the core explanatory variables, with R2 maintained between 0.869 and 0.972, and the dynamic GMM model test shows a significant second-order lag in the level of medical services (βequity ≤ 0.149, p ≤ 0.01; βefficiency ≤ 0.461, p ≤ 0.01); the channel test results prove that managerial personnel and other technical personnel are key pathways in regulating the impact of medical staff on the level of medical services. Conclusion This study provides an in-depth analysis of the impact of health human resources on the level of medical services, revealing that both the scale and hierarchical structure of health human resources significantly affect the equity and efficiency of medical services. Furthermore, the influence of health human resources on the level of medical services exhibits regional heterogeneity and temporal characteristics. Robustness tests ensure the scientific validity and robustness of the research conclusions. This provides effective references for optimizing the allocation of health human resources and improving the level of medical services.

Abstract In the field of Industrial Internet of Things (IIoT), existing intrusion detection models face challenges in three main areas: low accuracy in detecting attack traffic, feature redundancy when dealing with high-dimensional and complex attack traffic, making it difficult to capture critical information, and a tendency to favor learning common categories while neglecting rare categories when handling imbalanced data. To tackle these challenges, this study introduces an intrusion detection method that combines an attention mechanism, Bidirectional Gated Recurrent Units (BiGRU), and Inception Convolutional Neural Network (Inception-CNN) to enhance the model’s detection rate. Simultaneously, the method employs a mixed sampling strategy for data resampling to address the bias learning issue caused by data imbalance. Additionally, the method employs a hybrid sampling strategy for data resampling to address the bias learning issue caused by data imbalance. It also incorporates denoising techniques to handle potential dataset noise introduced by hybrid sampling. Furthermore, a feature selection method combining Pearson correlation coefficient and Random Forest is applied to eliminate feature redundancy, enhancing the model’s ability to capture crucial information from high-dimensional attack traffic. Experimental validation on internationally recognized datasets (Edge-IIoTset, CIC-IDS2017, and CIC IoT 2023) affirms the reliability of the proposed intrusion detection method. This approach underscores the significance of intrusion detection in the security of Industrial IoT and showcases its potential in addressing pertinent challenges in network security.

Abstract Background The relationship between periodontitis and cardiovascular disease (CVD) has been extensively studied, but the role of biological aging in this relationship remains poorly understood. This study is dedicated to investigating the effect of periodontitis on the incidence of CVD and to elucidating the potential mediating role of biological aging. Furthermore, this study will seek to elucidate the causal association between periodontitis, CVD, and biological aging. Methods We included 3269 participants from the National Health and Nutrition Examination Survey (2009–2014) with diagnostic information on periodontitis and composite CVD events. Biological aging was evaluated by utilizing both the Klemera–Doubal method’s calculated biological age (KDMAge) and phenotypic age (PhenoAge). Logistic regression, restricted cubic spline (RCS) analysis, and subgroup analysis were used for data analysis. Mediation analysis was employed to explore the mediating role of biological aging. Subsequently, Mendelian randomization (MR) analyses were performed using genome-wide association study databases to explore potential causal relationships between periodontitis, CVD, and biological aging. Results Periodontitis was associated with a higher risk of CVD. Participants with periodontitis were found to have increased levels of biological aging, and elevated levels of biological aging were associated with increased CVD risk. Mediation analyses showed a partial mediating effect of biological aging (PhenoAge: 44.6%; KDMAge: 22.9%) between periodontitis and CVD risk. MR analysis showed that periodontitis played a causal role in increasing the risk of small vessel stroke, while myocardial infarction was found to increase the risk of periodontitis. In addition, reverse MR analysis showed that phenotypic aging can increase the risk of periodontitis, and there is a two-way causal relationship between CVD and biological aging. Conclusions Periodontitis is associated with an increased CVD risk, partially mediated by biological aging, with a complex causal interrelationship. Targeted interventions for periodontal health may slow the biological aging processes and reduce CVD risk.

Abstract The development of coronary artery disease (CAD) is significantly affected by impaired endocrine and metabolic status. Under this circumstance, improved prevention and treatment of CAD may result from knowing the connection between metabolites and CAD. This study aims to delve into the causal relationship between human metabolic biomarkers and CAD by using two-sample Mendelian randomization (MR). Utilizing two-sample bidirectional MR analysis, we assessed the correlation between 1400 blood metabolites and CAD, and the metabolites data from the CLSA, encompassing 8299 participants. Metabolite analysis identified 1091 plasma metabolites and 309 ratios as instrumental variables. To evaluate the causal link between metabolites and CAD, we analyzed three datasets: ebi-a-GCST005195 (547,261 European & East Asian samples), bbj-a-159 (29,319 East Asian CAD cases & 183,134 East Asian controls), and ebi-a-GCST005194 (296,525 European & East Asian samples). To estimate causal links, we utilized the IVW method. To conduct sensitivity analysis, we used MR-Egger, Weighted Median, and MR-PRESSO. Additionally, we employed MR-Egger interception and Cochran’s Q statistic to assess potential heterogeneity and pleiotropy. What’s more, replication and reverse analyses were performed to verify the reliability of the results and the causal order between metabolites and disease. Furthermore, we conducted a pathway analysis to identify potential metabolic pathways. 59 blood metabolites and 27 metabolite ratios nominally associated with CAD (P

Abstract Electrochemical reactions via carbocation intermediates remain fundamental transformations that build up molecular functionality and complexity in a sustainable manner. Enantioselective control of such processes is a great challenge in a highly ionic electrolyte solution. Here, we report an anodic generation of chiral α-imino carbocation intermediates by enamine catalysis. The chiral carbocation intermediates can be intercepted by a variety of nucleophiles such as alcohols, water and thiols with high stereoselectivity. The key SN1 step proceeds via a tertiary amine-mediated proton shuttle that facilitates facial selection in reacting with carbocation.

Abstract Objective To investigate the differential expression genes (DEGs) in spinal tuberculosis using transcriptomics, with the aim of identifying novel therapeutic targets and prognostic indicators for the clinical management of spinal tuberculosis. Methods Patients who visited the Department of Orthopedics at the Second Hospital, Lanzhou University from January 2021 to May 2023 were enrolled. Based on the inclusion and exclusion criteria, there were 5 patients in the test group and 5 patients in the control group. Total RNA was extracted and paired-end sequencing was conducted on the sequencing platform. After processing the sequencing data with clean reads and annotating the reference genome, FPKM normalization and differential expression analysis were performed. The DEGs and long non-coding RNAs (LncRNAs) were analyzed for Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment. The cis-regulation of differentially expressed mRNAs (DE mRNAs) by LncRNAs was predicted and analyzed to establish a co-expression network. Results This study identified 2366 DEGs, with 974 genes significantly upregulated and 1392 genes significantly downregulated. The upregulated genes are associated with cytokine-cytokine receptor interactions, tuberculosis, and TNF-α signaling pathways, primarily enriched in biological processes such as immunity and inflammation. The downregulated genes are related to muscle development, contraction, fungal defense response, and collagen metabolism processes. Analysis of LncRNAs from bone tuberculosis RNA-seq data detected a total of 3652 LncRNAs, with 356 significantly upregulated and 184 significantly downregulated. Further analysis identified 311 significantly different LncRNAs that could cis-regulate 777 target genes, enriched in pathways such as muscle contraction, inflammatory response, and immune response, closely related to bone tuberculosis. There are 51 genes enriched in the immune response pathway regulated by cis-acting LncRNAs. LncRNAs that regulate immune response-related genes, such as upregulated RP11-451G4.2, RP11-701P16.5, AC079767.4, AC017002.1, LINC01094, CTA-384D8.35, and AC092484.1, as well as downregulated RP11-2C24.7, may serve as potential prognostic and therapeutic targets. Conclusion The DE mRNAs and LncRNAs in spinal tuberculosis are both associated with immune regulatory pathways. These pathways promote or inhibit the tuberculosis infection and development at the mechanistic level and play an important role in the process of tuberculosis transferring to bone tissue.

Abstract The heat storage capacity of Southern Ocean (SO) buffers future atmospheric warming but differs vastly across climate models. Reducing its projection uncertainty is vital for understanding and evaluating future global sustainability. Using Coupled Model Intercomparison Project Phase 6, we show that the present-day SO high-latitude easterly wind anomalies induced by El Niño is an effective constraint for the projected increase in SO heat content. Models simulating weaker El Niño-induced easterlies generate more equatorward atmospheric teleconnection in the present day. Under global warming, these models have greater capacity in the poleward shift of atmospheric circulation, thus generate stronger future increase in El Niño-induced high-latitude easterlies, slowing the SO heat storage by weakening the northward Ekman transport that underpins the dynamical process for SO heat storage. However, most models overestimate the present-day El Niño-induced easterlies, implying that alleviating this bias would reduce future SO heat storage, thus exacerbating atmospheric warming.

Abstract Understanding the impact of diagenesis on the elastic properties of organic-rich shale reservoirs is essential for evaluating unconventional hydrocarbon reservoirs and interpreting seismic data. Recent advancements in the exploration of the Permian Wujiaping Formation in the eastern Sichuan Basin indicate its potential to become a significant succession within the Sichuan Basin. However, the effect of different lithofacies in the Wujiaping Formation on shale elastic properties under varying diagenetic conditions remains unclear, hindering detailed reservoir interpretation. This study employs X-ray diffraction, thin section analysis, scanning electron microscopy, organic geochemistry, and dynamic elastic property tests to investigate the Wujiaping Formation shale. The results reveal three primary lithofacies types: argillaceous shale, mixed shale, and siliceous shale. Argillaceous shale, subjected to intense compaction, forms a dense rock framework of oriented clay minerals, characterized by low porosity (1.66%), low elastic wave velocity (4122.30 m/s), low elastic modulus (2174.59 m/s), and high Poisson's ratio (32.24 GPa). Mixed shale, dominated by carbonates and quartz, exhibits a rock framework formed through dissolution and cementation, with high elastic wave velocity (5196.54 m/s), relatively high elastic modulus (2975.86 m/s), and moderate Poisson's ratio (58.53 GPa). Siliceous shale, comprising biogenic quartz particles, shows strong resistance to compaction. During hydrocarbon generation, it develops abundant organic matter pores, resulting in the highest porosity (2.36%), high elastic wave velocity (5177.92 m/s), high elastic modulus (2975.86 m/s), and low Poisson's ratio (62.23 GPa). The significant differences in mineral composition and diagenetic processes across the lithofacies lead to distinct elastic properties. This study provides a rock physics framework for the detailed seismic prediction of "sweet spots" in the Wujiaping Formation shale reservoirs and offers new insights into characterizing the diagenesis of unconventional shale reservoirs using geophysical properties.

Abstract Purpose This study aimed to create and validate robust machine-learning-based prediction models for antipsychotic drug (risperidone) continuation in children and teenagers suffering from mania over one year and to discover potential variables for clinical treatment. Method The study population was collected from the national claims database in China. A total of 4,532 patients aged 4–18 who began risperidone therapy for mania between September 2013 and October 2019 were identified. The data were randomly divided into two datasets: training (80%) and testing (20%). Five regularly used machine learning methods were employed, in addition to the SuperLearner (SL) algorithm, to develop prediction models for the continuation of atypical antipsychotic therapy. The area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI) was utilized. Results In terms of discrimination and robustness in predicting risperidone treatment continuation, the generalized linear model (GLM) performed the best (AUC: 0.823, 95% CI: 0.792–0.854, intercept near 0, slope close to 1.0). The SL model (AUC: 0.823, 95% CI: 0.791–0.853, intercept near 0, slope close to 1.0) also exhibited significant performance. Furthermore, the present findings emphasize the significance of several unique clinical and socioeconomic variables, such as the frequency of emergency room visits for nonmental health disorders. Conclusions The GLM and SL models provided accurate predictions regarding risperidone treatment continuation in children and adolescents with episodes of mania and hypomania. Consequently, applying prediction models in atypical antipsychotic medicine may aid in evidence-based decision-making.

Abstract Background Chronic kidney disease (CKD) is a significant risk factor for pulmonary hypertension (PH), a complication that adversely affects patient prognosis. However, the mechanisms underlying this association remain poorly understood. A major obstacle to progress in this field is the lack of a reliable animal model replicating CKD-PH. Methods This study aimed to establish a stable rat model of CKD-PH. We employed a combined approach, inducing CKD through a 5/6 nephrectomy and concurrently exposing the rats to a high-salt diet. The model's hemodynamics were evaluated dynamically, alongside a comprehensive assessment of pathological changes in multiple organs. Lung tissues and serum samples were collected from the CKD-PH rats to analyze the expression of angiotensin-converting enzyme 2 (ACE2), evaluate the activity of key vascular components within the renin–angiotensin–aldosterone system (RAAS), and characterize alterations in the serum metabolic profile. Results At 14 weeks post-surgery, the CKD-PH rats displayed significant changes in hemodynamic parameters indicative of pulmonary arterial hypertension. Additionally, right ventricular hypertrophy was observed. Notably, no evidence of pulmonary vascular remodeling was found. Further analysis revealed RAAS dysregulation and downregulated ACE2 expression within the pulmonary vascular endothelium of CKD-PH rats. Moreover, the serum metabolic profile of these animals differed markedly from the sham surgery group. Conclusions Our findings suggest that the development of pulmonary arterial hypertension in CKD-PH rats is likely a consequence of a combined effect: RAAS dysregulation, decreased ACE2 expression in pulmonary vascular endothelial cells, and metabolic disturbances. Graphical Abstract

Abstract Objective To investigate circadian rhythm-associated long non-coding RNA (lncRNA) signatures in predicting prognosis, metabolism, and immune infiltration in Head and Neck Squamous Cell Carcinoma (HNSC). Methods HNSC samples were collected from the TCGA database. A signature was constructed using Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) methods. The immune cell infiltration was analyzed using CIBERSORT, ssGSEA, and MCPcounter. The RT-qPCR was used to detect the expression of signature lncRNAs. Results A signature comprising 8 lncRNAs was constructed. The constructed signature demonstrated good prognostic prediction capability for HNSC. A nomogram encompassing risk score accurately predicted the long-term OS probability of HNSC. The infiltration levels of T cell, B cell and Macrophages were significantly higher in the high-risk group than in the low-risk group. Cluster analysis showed that the signature lncRNAs could classify the HNSC samples into two clusters. The RT-qPCR suggested that the expression of lncRNAs in signature was consistent with the data in TCGA. Conclusion The circadian rhythm-associated lncRNA signature has potential as a prognostic indicator for HNSC. It exhibits associations with metabolism, immune microenvironment, and drug sensitivity, thereby providing valuable insights for informing the treatment of HNSC.

Abstract Background The number of adult orthodontic patients is increasing, and studies have shown that autophagy is involved in regulating orthodontic tooth movement and plays an important role in aging-related changes. Therefore, we aimed to explore the role of autophagy in aging-related changes during orthodontic tooth movement by establishing a rat orthodontic tooth movement model. Methods Forty-five 6-week-old and sixty-five 8-month-old male Sprague–Dawley rats were selected to represent adolescents and adults and establish orthodontic tooth movement model. They were sacrificed on days 0,1,3,7 and 14. Immunohistochemistry, immunofluorescence and tartrate resistant acid phosphatase (TRAP) staining were applied to measure the expression level of osteogenesis, autophagy, aging factors and osteoclast number in periodontal membrane of left upper first molar during orthodontic tooth movement. Then, we regulated the autophagy level by injecting autophagy activator rapamycin during orthodontic tooth movement and measured these factors and tooth movement distance by micro-computed tomography. Results Aging factor levels in the periodontal membrane were higher in adult rats than in adolescent rats and the autophagy factor levels were lower. The levels of osteogenic factors were lower on the tension side in adult rats than in adolescent rats. The peak osteoclast number on the pressure side occurred later in adult rats than in adolescent rats. The injection of rapamycin increased autophagy, accelerated orthodontic tooth movement in adult rats, and reduced the levels of aging factors. The levels of osteogenic factors were higher and reached those in adolescent rats at some time points. The number of osteoclasts increased significantly in the early stage. Conclusions Autophagy may play a substantial role in regulating aging-related changes in orthodontic tooth movement.

Objective: To evaluate high-resolution computed tomography (HRCT) features of dermatomyositis-/polymyositis- associated interstitial lung disease (DM/PM-ILD). Methods: We retrospectively reviewed the HRCT images of 148 patients with DM/PM-ILD at the First Affiliated Hospital of Xi’an Jiaotong University between Jan. 1, 2014, and Dec. 31, 2019. Results: The HRCT features of DM/PM-ILD were characterized by ground-glass opacities (GGO) (87.2%, 123/141), interlobular septal thickening (78.0%, 110/141), intralobular interstitial thickening (63.8%, 90/141), consolidation (29.1%, 41/141), subpleural lines (26.2%, 37/141), traction bronchiectasis (19.9%, 28/141), and honeycombing (3.5%, 5/141). Pneumomediastinum (3), pleural effusion (15), and pericardial effusion (18) were also observed. The two main radiological patterns were non-specific interstitial pneumonia (NSIP) and organism pneumonia (OP). Conclusion: HRCT features of DM/PM-ILD are heterogeneous, with various radiological patterns. Mastering the main characteristics of HRCT manifestation and the radiological patterns of DM/PM-ILD will be helpful for early identification and timely treatment.

Abstract 1,2-Difunctionalization of alkynes offers a straightforward approach to access polysubstituted alkenes. However, simultaneous multi-component cascade transformations including difunctionalization of two alkynes with both syn- and anti-selectivity in one catalyst system is undeveloped and proves to be a significant challenge. Herein, we report a Nickel-catalyzed four-component reaction to access polysubstituted 1,3-dienes using two terminal alkynes, aryl boroxines, and perfluoroalkyl iodides, wherein the reaction forms three new C-C bonds in a single vessel and serve as a modular strategy to access polysubstituted 1,3-dienes with excellent chemoselectivity, good regioselectivity and exclusive stereoselectivity. Control experiments reveal the plausible reaction mechanism and DFT calculations explain the cause for the formation of this unusual four-component reaction. Furthermore, we successfully incorporate two biologically active units into 1,2,3,4-tetrasubstituted 1,3-dienes, which greatly increases the diversity of molecular scaffolds and brings more potential values to medicinal chemistry, the synthetic utility of our protocol is further demonstrated by the late-stage transformations.

Abstract Objective This study aimed to develop and apply a nomogram with good accuracy to predict the risk of CRAB infections in neuro-critically ill patients. In addition, the difficulties and expectations of application such a tool in clinical practice was investigated. Methods A mixed methods sequential explanatory study design was utilized. We first conducted a retrospective study to identify the risk factors for the development of CRAB infections in neuro-critically ill patients; and further develop and validate a nomogram predictive model. Then, based on the developed predictive tool, medical staff in the neuro-ICU were received an in-depth interview to investigate their opinions and barriers in using the prediction tool during clinical practice. The model development and validation is carried out by R. The transcripts of the interviews were analyzed by Maxqda. Results In our cohort, the occurrence of CRAB infections was 8.63% (47/544). Multivariate regression analysis showed that the length of neuro-ICU stay, male, diabetes, low red blood cell (RBC) count, high levels of procalcitonin (PCT), and number of antibiotics ≥ 2 were independent risk factors for CRAB infections in neuro-ICU patients. Our nomogram model demonstrated a good calibration and discrimination in both training and validation sets, with AUC values of 0.816 and 0.875. Additionally, the model demonstrated good clinical utility. The significant barriers identified in the interview include “skepticism about the accuracy of the model”, “delay in early prediction by the indicator of length of neuro-ICU stay”, and “lack of a proper protocol for clinical application”. Conclusions We established and validated a nomogram incorporating six easily accessed indicators during clinical practice (the length of neuro-ICU stay, male, diabetes, RBC, PCT level, and the number of antibiotics used) to predict the risk of CRAB infections in neuro-ICU patients. Medical staff are generally interested in using the tool to predict the risk of CRAB, however delivering clinical prediction tools in routine clinical practice remains challenging.

Abstract Nowadays, immunotherapy is one of the most promising anti-tumor therapeutic strategy. Specifically, immune-related targets can be used to predict the efficacy and side effects of immunotherapy and monitor the tumor immune response. In the past few decades, increasing numbers of novel immune biomarkers have been found to participate in certain links of the tumor immunity to contribute to the formation of immunosuppression and have entered clinical trials. Here, we systematically reviewed the oncogenesis and progression of cancer in the view of anti-tumor immunity, particularly in terms of tumor antigen expression (related to tumor immunogenicity) and tumor innate immunity to complement the cancer-immune cycle. From the perspective of integrated management of chronic cancer, we also appraised emerging factors affecting tumor immunity (including metabolic, microbial, and exercise-related markers). We finally summarized the clinical studies and applications based on immune biomarkers. Overall, immune biomarkers participate in promoting the development of more precise and individualized immunotherapy by predicting, monitoring, and regulating tumor immune response. Therefore, targeting immune biomarkers may lead to the development of innovative clinical applications.

Abstract In the process of coal-filling mining, the gangue fly-ash slurry (GFS) needs to be transported over a long distance to reach the gobs. The abrupt closure of the valve during the transportation of GFS can result in a water hammer that significantly endangers the stability and safety of the pipeline transport system. To study the fluctuations in pressure induced by abrupt closure of the valve, experiments on the rheological parameters of gangue-coal ash slurry were conducted. Transient numerical simulations were carried out using the computational fluid dynamics method for various valve closing times. The results indicate that, with the increase of slurry concentration, the yield stress of the slurry significantly increases. When the concentration exceeds 76%, the increase in yield stress reaches 38.4% and 35.1%, respectively. Upon valve closure, the internal pressure of the slurry in the pipeline exhibits periodic dynamic oscillations. As the duration of valve closure increases, the frequency of periodic water hammer events decreases. The maximum water hammer pressure caused by valve closure decreases with the increasing distance between the valve and the closure point. At the same time, the intensity of maximum water hammer pressure fluctuations increases with the increase in slurry concentration and flow velocity in the pipeline. The results can provide references for water hammer protection and pipeline selection during the transportation of backfill slurry in mining.

Abstract The new energy vehicle plays a crucial role in green transportation, and the energy management strategy of hybrid power systems is essential for ensuring energy-efficient driving. This paper presents a state-of-the-art survey and review of reinforcement learning-based energy management strategies for hybrid power systems. Additionally, it envisions the outlook for autonomous intelligent hybrid electric vehicles, with reinforcement learning as the foundational technology. First of all, to provide a macro view of historical development, the brief history of deep learning, reinforcement learning, and deep reinforcement learning is presented in the form of a timeline. Then, the comprehensive survey and review are conducted by collecting papers from mainstream academic databases. Enumerating most of the contributions based on three main directions—algorithm innovation, powertrain innovation, and environment innovation—provides an objective review of the research status. Finally, to advance the application of reinforcement learning in autonomous intelligent hybrid electric vehicles, future research plans positioned as “Alpha HEV” are envisioned, integrating Autopilot and energy-saving control.

Abstract. Background:. Patients who undergo coronary artery bypass grafting (CABG) are known to be at a significant risk of experiencing long-term adverse events, emphasizing the importance of regular assessments. Evaluating health-related quality of life (HRQoL) serves as a direct method to gauge prognosis. Our objective is to ascertain the prognostic significance of consecutive HRQoL assessments using the Physical Component Summary (PCS) and Mental Component Summary (MCS) derived from the Short-Form 36 (SF-36) health survey in CABG patients. Methods:. The study population consisted of 433 patients who underwent isolated elective CABG at Fuwai Hospital between 2012 and 2013. SF-36 assessments were conducted during both the hospitalization period and follow-up. The primary endpoint of the study was all-cause mortality, while the secondary outcome was a composite measure including death, myocardial infarction, stroke, and repeat revascularization. We assessed the relationships between the PCS and MCS at baseline, as well as their changes during the first 6 months after the surgery (referred to as ΔPCS and ΔMCS, respectively), and the observed outcomes. Results:. The patients were followed for an average of 6.28 years, during which 35 individuals (35/433, 8.1%) died. After adjusting for clinical variables, it was observed that baseline MCS scores (hazard ratio [HR] for a 1-standard deviation [SD] decrease, 1.57; 95% confidence interval [CI], 1.07–2.30) and ΔMCS (HR for a 1-SD decrease, 1.67; 95% CI, 1.09–2.56) were associated with all-cause mortality. However, baseline PCS scores and ΔPCS did not exhibit a significant relationship with all-cause mortality. Notably, there was a dose-response relationship observed between ΔMCS and the likelihood of all-cause mortality (HRs for the 2nd, 3rd and 4th quartiles compared to the 1st quartile, 0.33, 0.45 and 0.11, respectively). Conclusions:. Baseline MCS and changes in MCS were independent predictors for long-term mortality of CABG. Better mental health status and recovery indicated better prognosis.

Apple is a significant economic crop in China, and leaf diseases represent a major challenge to its growth and yield. To enhance the efficiency of disease detection, this paper proposes an Adaptive Cross-layer Integration Method for apple leaf disease detection. This approach, built upon the YOLOv8s architecture, incorporates three novel modules specifically designed to improve detection accuracy and mitigate the impact of environmental factors. Furthermore, the proposed method addresses challenges arising from large feature discrepancies and similar disease characteristics, ultimately improving the model's overall detection performance. Experimental results show that the proposed method achieves a mean Average Precision (mAP) of 85.1% for apple leaf disease detection, outperforming the latest state-of-the-art YOLOv10s model by 2.2%. Compared to the baseline, the method yields a 2.8% increase in mAP, with improvements of 5.1%, 3.3%, and 2% in Average Precision, Recall, and mAP50-95, respectively. This method demonstrates superiority over other classic detection algorithms. Notably, the model exhibits optimal performance in detecting Alternaria leaf spot, frog eye leaf spot, gray spot, powdery mildew, and rust, achieving mAPs of 84.3%, 90.4%, 80.8%, 75.7%, and 92.0%, respectively. These results highlight the model’s ability to significantly reduce false negatives and false positives, thereby enhancing both detection and localization of diseases. This research offers a new theoretical foundation and direction for future advancements in apple leaf disease detection.

Background Dyslipidemia plays a very important role in the occurrence and development of cardiovascular disease (CVD). Genetic factors, including single nucleotide polymorphisms (SNPs), are one of the main risks of dyslipidemia. 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) is not only the rate-limiting enzyme step of endogenous cholesterol production, but also the therapeutic target of statins. Methods We investigated 405 Han Chinese and 373 Uyghur people who took statins for a period of time, recorded their blood lipid levels and baseline data before and after oral statin administration, and extracted DNA from each subject for SNP typing of HMGCR rs17671591 and rs3761740. The effects of HMGCR rs17671591 and rs3761740 on lipid levels and the effect of statins on lipid lowering in Han Chinese and Uyghur ethnic groups were studied. Results In this study, for rs17671591, the CC vs. TT+CT model was significantly correlated with the level of LDL-C before oral statin in the Uyghur population, but there were no correlations between rs17671591 and the level of blood lipid before oral statin in the Han population. The CC vs. TT+CT and CT vs. CC+TT models were significantly correlated with the level of LDL-C after oral statin in the Uyghur population. There was no significant correlation between rs3761740 with blood lipids before and after oral statin in the Han population. For rs3761740, before oral statin, the CC vs. AA+CA model was significantly correlated with the level of LDL-C, and the CA vs. CC+AA model was significantly correlated with the level of total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), and non-high density lipoprotein cholesterol (HDL-C) in the Uyghur population. After oral statin, the CC vs. AA+CA and CA vs. CC+AA models were significantly correlated with the level of TC, LDL-C, and apolipoprotein (APOB), and the C vs. A model was significantly correlated with the level of TC, triglyceride (TG), LDL-C, and APOB in the Uyghur population. Particularly, the CT vs. CC+TT model of rs17671591 was significantly correlated with the changes of LDL-C after oral statin in the Uyghur population. In this study, we also explored the association of rs17671591 and rs3761740 with the rate of dyslipidemia as a reference. Conclusion We found that HMGCR rs3761740 was correlated with the levels of TC, LDL-C, and non-HDL-C before and after oral statin in Uyghurs, but not with blood lipid levels in the Han population. In the Uyghur population, HMGCR rs17671591 was associated with the level of LDL-C before and after oral statin, and also affected the changes of LDL-C after oral statin.

ObjectiveThe long-term glucose monitoring is essential to the risk assessment of diabetic retinopathy (DR), the aim of this study was to investigate the predictive ability of visit-to-visit fasting blood glucose (FBG) indices on the risk of DR.MethodsThis was a community-based, cohort study conducted from 2013 to 2021. DR was diagnosed by digital fundus photography. The FPG indices included FBG, var. Associations of each FBG indices and DR were estimated using multinomial logistic regression models adjusting for confounders, and discrimination was determined by area under the curve (AUC). Predictive utility of different models was compared by changes in AUC, integrated discrimination improvement (IDI), and net reclassification index (NRI).ResultsThis study analyzed 5054 participants, the mean age was 46.26 ± 11.44 years, and 2620 (51.84%) were women. After adjustment for confounders, the adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for FBG, SD, CV, VIM, ARV, M-FBG, and cumulative FBG load were 1.62 (1.52—1.73), 2.74 (2.38—3.16), 1.78 (1.62—1.95), 1.11 (0.95—1.29), 1.72 (1.56—1.91), 2.15 (1.96—2.36), and 2.57 (2.31—2.85), respectively. The AUC of the model with separate cumulative FBG load and classical risk factors was 0.9135 (95%CI 0.8890—0.9380), and no substantive improvement in discrimination was achieved with the addition of other FBG indices once cumulative FBG load was in the model.ConclusionsCumulative FBG load is adequate for capturing the glucose-related DR risk, and the predictive utility of cumulative FBG load is not significantly improved by adding or replacing other FBG indices in the assessment of DR risk.

Introduction: The treatment of COVID-19 patients, especially high-risk patients, remains a large challenge. Glucocorticoids have been accepted as effective medicines for severe COVID-19. However, the glucocorticoid usage guidelines do not cover all the indications for high-risk patients. Objective: To identify more effective treatments for high-risk patients with COVID-19, this retrospective study analyzed routine epidemiological, clinical, and laboratory data from 33 high-risk patients with COVID-19 in Beijing Gobroad Boren Hospital, Beijing, China, most of whom responded well to treatment. Methods: Severe acute respiratory syndrome coronavirus-2 infection was confirmed via real-time reverse transcriptase polymerase chain reaction assays. Outcome measures such as duration of mechanical ventilation, intensive care unit length of stay, and 28-day mortality were analyzed. Patients were divided into two groups: mild to moderate COVID-19 ( n = 26) and severe COVID-19 ( n = 7). Chest computed tomography images were used to guide methylprednisolone administration or withdrawal. Results: Upon intensive care unit admission, 12.1% of patients were mechanically ventilated with an average partial pressure of oxygen/fraction of inspired oxygen(PaO 2 /FiO 2 ) ratio of 279 ± 146. No coinfections with other endemic viruses were observed. The duration of mechanical ventilation was 16 days (interquartile range: 8–28); the intensive care unit length of stay was 11 (interquartile range: 2–33) days; and the 28-day total mortality was 3.0%. Conclusion: Multivariate regression analysis revealed that low-dose, timely methylprednisolone administration was associated with a lower severe COVID-19 rate and mortality in high-risk patients. For high-risk patients, once there are ground-glass opacities (GGO) in the computed tomography image, continuous and low-dose methylprednisolone administration promotes inflammation remission and protects them from severe COVID-19 or mortality.

Background Immune checkpoint blockade (ICB) has made remarkable achievements, but newly identified armored and cold tumors cannot respond to ICB therapy. The high prevalence of concomitant medications has huge impact on immunotherapeutic responses, but the clinical effects on the therapeutic outcome of armored and cold tumors are still unclear.Methods In this research, using large-scale transcriptomics datasets, the expression and potential biological functions of angiotensin II receptor 1 (AGTR1), the target of angiotensin receptor blocker (ARB), were investigated. Next, the roles of ARB in tumor cells and tumor microenvironment cells were defined by a series of in vitro and in vivo assays. In addition, the clinical impacts of ARB on ICB therapy were assessed by multicenter cohorts and meta-analysis.Results AGTR1 was overexpressed in armored and cold tumors and associated with poor response to ICB therapy. ARB, the inhibitor for AGTR1, only suppressed the aggressiveness of tumor cells with high AGTR1 expression, which accounted for a very small proportion. Further analysis revealed that AGTR1 was always highly expressed in cancer-associated fibroblasts (CAFs) and ARB inhibited type I collagen expression in CAFs by suppressing the RhoA-YAP axis. Moreover, ARB could also drastically reverse the phenotype of armored and cold to soft and hot in vivo, leading to a higher response to ICB therapy. In addition, both our in-house cohorts and meta-analysis further supported the idea that ARB can significantly enhance ICB efficacy.Conclusion Overall, we identify AGTR1 as a novel target in armored and cold tumors and demonstrate the improved therapeutic efficacy of ICB in combination with ARB. These findings could provide novel clinical insight into how to treat patients with refractory armored and cold tumors.

Existing research on fault diagnosis for polymer electrolyte membrane fuel cells (PEMFC) has advanced significantly, yet performance is hindered by variations in data distributions and the requirement for extensive fault data. In this study, a cross-domain adaptive health diagnosis method for PEMFC is proposed, integrating the digital twin model and transfer convolutional diagnosis model. A physical-based high-fidelity digital twin model is developed to obtain diverse and high-quality datasets for training diagnosis method. To extract long-term time series features from the data, a temporal convolutional network (TCN) is proposed as a pre-trained diagnosis model for the source domain, with feature extraction layers that can be reused to the transfer learning network. It is demonstrated that the proposed pre-trained model can hold the ability to accurately diagnose the various fuel cell faults, including pressure, drying, flow, and flooding faults, with 99.92 % accuracy, through the effective capture of the long-term dependencies in time series data. Finally, a domain adaptive transfer convolutional network (DATCN) is established to improve the diagnosis accuracy across diverse fuel cells by learning domain-invariant features. The results show that the DATCN model, tested on three different target domain devices with adversarial training using only 10 % normal data, can achieve an average accuracy of 98.5 % (30 % improved over traditional diagnosis models). This proposed method provides an effective solution for accurate cross-domain diagnosis of PEMFC devices, significantly reducing the reliance on extensive fault data.

Abstract Background Weaning from invasive mechanical ventilation (MV) is a complex and challenging process that involves multiple pathophysiological mechanisms. A combined ultrasound evaluation of the heart, lungs, and diaphragm during the weaning phase can help to identify risk factors and underlying mechanisms for weaning failure. This study aimed to investigate the accuracy of lung ultrasound (LUS), transthoracic echocardiography (TTE), and diaphragm ultrasound for predicting weaning failure in critically ill patients. Methods Patients undergoing invasive MV for > 48 h and who were readied for their first spontaneous breathing trial (SBT) were studied. Patients were scheduled for a 2-h SBT using low-level pressure support ventilation. LUS and TTE were performed prospectively before and 30 min after starting the SBT, and diaphragm ultrasound was only performed 30 min after starting the SBT. Weaning failure was defined as failure of SBT, re-intubation, or non-invasive ventilation within 48 h. Results Fifty-one patients were included, of whom 15 experienced weaning failure. During the SBT, the global, anterior, and antero-lateral LUS scores were higher in the failed group than in the successful group. Receiver operating characteristic curve analysis showed that the areas under the curves for diaphragm thickening fraction (DTF) and global and antero-lateral LUS scores during the SBT to predict weaning failure were 0.678, 0.719, and 0.721, respectively. There was no correlation between the LUS scores and the average E/e’ ratio during the SBT. Multivariate analysis identified antero-lateral LUS score > 7 and DTF 7 and DTF

Abstract Coiled-coil domain-containing 58 (CCDC58) is a member of the CCDC protein family. Similar to other members, CCDC58 exhibits potential tumorigenic roles in a variety of malignancies. However, there is no systematic and comprehensive pan-cancer analysis to investigate the diagnosis, prognosis, immune infiltration, and other related functions of CCDC58. We used several online websites and databases, such as TCGA, GTEx, UALCAN, HPA, CancerSEA, BioGRID, GEPIA 2.0, TIMER 2.0, and TISIDB, to extract CCDC58 expression data and clinical data of patients in pan-cancer. Then, the relationship between CCDC58 expression and diagnosis, prognosis, genetic alterations, DNA methylation, genomic heterogeneity, and immune infiltration level were determined. In addition, the biological function of CCDC58 in liver hepatocellular carcinoma (LIHC) was investigated. Pan-cancer analysis results showed that CCDC58 was differentially expressed in most tumors and showed excellent performance in diagnosis and prediction of prognosis. The expression of CCDC58 was highly correlated with genetic alterations, DNA methylation, and genomic heterogeneity in some tumors. In addition, the correlation analysis of CCDC58 with the level of immune infiltration and immune checkpoint marker genes indicated that CCDC58 might affect the composition of the tumor immune microenvironment. Enrichment analysis showed that CCDC58-related genes were mainly linked to mitosis, chromosome, and cell cycle. Finally, biological function experiments demonstrated that CCDC58 plays an important role in tumor cell proliferation and migration. CCDC58 was first identified as a pan-cancer biomarker. It may be used as a potential therapeutic target to improve the prognosis of patients in the future.

Abstract With the continuous development of wireless communication and artificial intelligence technology, Internet of Things (IoT) technology has made great progress. Deep learning methods are currently used in IoT technology, but deep neural networks (DNNs) are notoriously susceptible to adversarial examples, and subtle pixel changes to images can result in incorrect recognition results from DNNs. In the real‐world application, the patches generated by the recent physical attack methods are larger or less realistic and easily detectable. To address this problem, a Generative Adversarial Network based on Visual attention model and Style transfer network (GAN‐VS) is proposed, which reduces the patch area and makes the patch more natural and less noticeable. A visual attention model combined with generative adversarial network is introduced to detect the critical regions of image recognition, and only generate patches within the critical regions to reduce patch area and improve attack efficiency. For any type of seed patch, an adversarial patch can be generated with a high degree of stylistic and content similarity to the attacked image by generative adversarial network and style transfer network. Experimental evaluation shows that the proposed GAN‐VS has good camouflage and outperforms state‐of‐the‐art adversarial patch attack methods.

Abstract Lithium (Li) metal batteries are regarded as the “holy grail” of next‐generation rechargeable batteries, but the poor redox reversibility of Li anode hinders its practical applications. While extensive studies have been carried out to design lithiophilic substrates for facile Li plating, their effects on Li stripping are often neglected. In this study, by homogeneously loading indium (In) single atoms on N‐doped graphene via In‐N bonds, the affinity between Li and hosting substrates is regulated. In situ observation of Li deposition/stripping processes shows that compared with the N‐doped graphene substrate, the introduction of In effectively promotes its reversibility of Li redox, achieving a dendrite‐free Li anode with much‐improved coulombic efficiency. Interestingly, theoretical calculations demonstrate that In atoms have actually made the substrate less lithophilic via passivating the N sites to avoid the formation of irreversible Li–N bonding. Therefore, a “volcano curve” for reversible Li redox processes is proposed: the affinity of substrates toward Li should be optimized to a moderate value, where the balance for both Li plating and Li stripping processes could be reached. By demonstrating a crucial design principle for Li metal hosting substrates, our finding could trigger the rapid development of related research.

Abstract With the rapid growth of Internet of Vehicles (IoV) technology, the performance and privacy of IoV terminals (IoVT) have become increasingly important. This paper proposes a federated learning model for IoVT classification using connection records (FLM-ICR) to address privacy concerns and poor computational performance in analyzing users' private data in IoV. FLM-ICR, in the horizontally federated learning client-server architecture, utilizes an improved multi-layer perceptron and logistic regression network as the model backbone, employs the federated momentum gradient algorithm as the local model training optimizer, and uses the federated Gaussian differential privacy algorithm to protect the security of the computation process. The experiment evaluates the model's classification performance using the confusion matrix, explores the impact of client collaboration on model performance, demonstrates the model's suitability for imbalanced data distribution, and confirms the effectiveness of federated learning for model training. FLM-ICR achieves the accuracy, precision, recall, specificity, and F1 score of 0.795, 0.735, 0.835, 0.75, and 0.782, respectively, outperforming existing research methods and balancing classification performance and privacy security, making it suitable for IoV computation and analysis of private data.

As the complexity of autonomous vehicles (AVs) continues to increase and artificial intelligence algorithms are becoming increasingly ubiquitous, a novel safety concern known as the safety of the intended functionality (SOTIF) has emerged, presenting significant challenges to the widespread deployment of AVs. SOTIF focuses on issues arising from the functional insufficiencies of the AVs’ intended functionality or its implementation, apart from conventional safety considerations. From the systems engineering standpoint, this study offers a comprehensive exploration of the SOTIF landscape by reviewing academic research, practical activities, challenges, and perspectives across the development, verification, validation, and operation phases. Academic research encompasses system-level SOTIF studies and algorithm-related SOTIF issues and solutions. Moreover, it encapsulates practical SOTIF activities undertaken by corporations, government entities, and academic institutions spanning international and Chinese contexts, focusing on the overarching methodologies and practices in different phases. Finally, the paper presents future challenges and outlook pertaining to the development, verification, validation, and operation phases, motivating stakeholders to address the remaining obstacles and challenges.

Abstract Excessive alternating current (AC) arcs generated in electric systems will accumulate heat and easily cause fire. This paper studies the thermal characteristics of different numbers of AC arc plasma generated in a short gap of copper-cored wires in the air. The number of AC arcs is controlled in the AC arc experiment and an infrared thermal imager measures the temperature change at the specified position. Based on magnetohydrodynamics (MHD), a two-dimensional axisymmetric AC arc discharge numerical simulation model is established. The volt-ampere characteristic of the AC arc is used to solve the MHD simulation model to obtain the same 'zero current' characteristics as the real AC arc in the experiment. A large amount of heat accumulates in the electrode gaps when the arc generation, and then the heat dissipates in the 'zero current' stage. The continuously generated arc makes the temperature higher. The volume of the space area with a temperature higher than 10,000 K increases with the arc current, but is unrelated to the number of arcs. The volume of the space area with a temperature higher than 524.15 K and the temperature on the electrode are both positively correlated with the number of AC arcs and arc current. The results of this study can provide a reference for the detection standard of AC arc faults and the prevention of electrical fire.

Abstract Objective To investigate the mechanism of ultrasound microbubbles (UTMB) promoting stem cells homing to fibrotic liver. Methods Bone marrow derived mesenchymal stem cells (BMSCs) were divided into 5 groups with or without ultrasound microbubbles and continuously irradiated with ultrasound conditions of frequency 1 MHZ and output power 0.6 W/cm2 for different times, and then injected into a mouse model of liver fibrosis through the tail vein with or without ultrasound microbubbles, with sound intensity. The effect of ultrasound microbubbles on MSC expression of CXC chemokine receptor 4 (CXCR4) and homing fibrotic liver was evaluated by flow cytometry (FCM), western blot (WB) and immunohistochemistry (IHC) analysis. Results The level of CXCR4 expression was significantly higher in the ultrasound microbubble group than in the non-intervention group (P

Abstract Background This prospective clinical study aimed to quantitatively evaluate the surface wear of attachments and investigate the associated risk factors. Additionally, the wear values and regions of three types of commonly used attachments were explored. Methods Participants were recruited from the population of patients who received clear aligner therapy from October to December 2022. Intraoral scanning was performed on eligible participants before treatment (T0), immediately after initial bonding of attachments (T1), and at 2 months (T2), 4 months (T3), 6 months (T4), and 8 months (T5) after starting treatment. The attachment volume, average depth and regions of attachment wear were measured using superimposed digitized models. The Kruskal–Wallis test was performed to compare data between multiple groups. Multiple linear regression analyses were performed to evaluate risk factors for the volume of attachment wear. Results A total of 47 patients with 617 attachments were included. As treatment time increased, the attachment volume decreased significantly (P = 0.003). The initial attachment volume was positively related to the volume of attachment wear (β = 0.527, P

Abstract Patients with multiple myeloma (MM) are likely to achieve poor therapeutic response when organs are involved. We produced anti‐B‐cell maturation antigen (BCMA) chimeric antigen receptor (CAR)‐T cells, which are in a trial for patients with relapsed/refractory MM. One enrolled patient developed severe heart failure, highly suspected as light chain cardiac amyloidosis. He exhibited increased N‐terminal pro‐brain natriuretic peptide with a peak of 32 299 ng/mL and heart failure with an ejection fraction of 30%. Anti‐BCMA CAR‐T cells were administered following lymphodepletion. The patient achieved cardiac response within 1 week with a decrease in N‐terminal pro‐brain natriuretic peptide by 80%, an increase in ejection fraction from 30% to 56%, and a haematological response with negative minimal residual disease at 1 month and a complete response at 1 year. To date, this patient has maintained good health without heart failure or haematological relapse. Herein, we show the efficacy of anti‐BCMA CAR‐T cells in patients with MM and severe heart failure.

Intravenous leiomyomatosis (IVL) is a benign disease that originates in the uterus and is characterized by aggressive intravenous growth that can extend to the inferior vena cava and even involve the intracardiac cavity. This extension of the IVL into the right heart is known as intracardiac leiomyomatosis (ICL). The clinical incidence of this disease is extremely low, and the characteristics of atypical aggressive growth lead to diagnostic dilemmas. Thus, studies on this disease have profound clinical significance. Here, we report a case of intracardiac leiomyomatosis and review the relevant literature. A 46-year-old female patient presented with exertive chest tightness and shortness of breath with an onset of approximately half a month. The patient underwent uterine myomectomy in 2018 and recovered well after surgery. On preoperative echocardiography, a hypoechoic mass was detected in the right atrium, which was diagnosed as a leiomyoma. Cardiac magnetic resonance imaging (MRI) revealed a T2-weighted mixed high-signal mass with partial cystic changes that extended from the inferior vena cava into the right atrioventricular cavity, occupying most of the atrial cavity and was misdiagnosed as an atrial mucinous tumor. The patient underwent cardiac tumor resection, tricuspid valvuloplasty, and lower-extremity vascular exploration under general anesthesia with extracorporeal circulation. The final pathological diagnosis was ICL. This is an illustrative analysis of various aspects of the disease, including pathology, etiology, clinical symptoms, imaging diagnosis, and treatment modalities.

Mixed-matrix membranes (MMMs) leverage the processability of polymers and selectivity of Metal-Organic Frameworks (MOFs). However, they still suffer from poor interfacial compatibility and limited scalability in preparation. In certain polymers, MOFs can bridge the pores within the polymer membrane, enhancing the CO2 adsorption and solubility properties, thus selectively boosting the CO2 permeability. In this study, high-performance MMMs were prepared using scalable CALF-20 in combination with PIM-1. MMMs with a 5% doping level achieved CO2 permeability up to 8003 barrer with 25% improvement in CO2/N2 selectivity. This enhancement was attributed to well-designed MMMs, where MOFs matched the abundant non-interconnecting pores in the PIM-1 membrane. This study represents a significant advancement towards scaling up the preparation of high-performance MOF-based MMMs for carbon capture applications.

Objective This study aimed to explore the shared mechanisms and targets between immune checkpoint inhibitor-associated myocarditis (ICIM) and autoimmune myocarditis. Methods Relevant data were retrieved from public datasets and Gene Expression Omnibus (GEO) database. Gene set enrichment analysis (GSEA) of differentially expressed genes (DEGs) was used to identify significant shared signaling pathways between ICIM and non-ICI associated autoimmune myocarditis (NICIAM) represented by ICIM model and experimental autoimmune myocarditis (EAM) model, respectively. Cell type enrichment analysis and immune infiltration analysis by clusterProfiler and ImmuCellAI were performed to identify critical immune cell component involved in ICIM and NICIAM. Additionally, core shared genes across ICIM and NICIAM were identified and validated by various models and methods. Results Interferon-γ response, inflammatory response and allograft rejection signaling were identified as the shared signaling pathways associated with ICIM and NICIAM. Enrichment analysis of cell type supported an important role of increased infiltration of T cells and macrophages in both ICIM and NICIAM. However, the predominant increase of infiltrated T cells was CD4+ T cells in NICIAM, while that were CD8+ T cells in ICIM. Core shared genes Lck and Cd3d expression were found increased in both ICIM and NICIAM, and Lck inhibition was further identified and validated as potential therapeutic approach. Conclusions Our study initially established a comorbidity model to identify potential molecular mechanism including interferon-γ response, inflammatory response and allograft rejection signaling accounting for the concerns of myocarditis risk in patients with preexisting autoimmune disease (PAD) receiving ICI treatment, and supported the therapeutic potential of targeting Lck or Cd3d.

Cnaphalocrocis medinalis granulovirus (CnmeGV), belonging to Betabaculovirus cnamedinalis, can infect the rice pest, the rice leaf roller. In 1979, a CnmeGV isolate, CnmeGV-EP, was collected from Enping County, China. In 2014, we collected another CnmeGV isolate, CnmeGV-EPDH3, at the same location and obtained the complete virus genome sequence using Illumina and ONT sequencing technologies. By combining these two virus isolates, we updated the genome annotation of CnmeGV and conducted an in-depth analysis of its genome features. CnmeGV genome contains abundant tandem repeat sequences, and the repeating units in the homologous regions (hrs) exhibit overlapping and nested patterns. The genetic variations within EPDH3 population show the high stability of CnmeGV genome, and tandem repeats are the only region of high genetic variation in CnmeGV genome replication. Some defective viral genomes formed by recombination were found within the population. Comparison analysis of the two virus isolates collected from Enping showed that the proteins encoded by the CnmeGV-specific genes were less conserved relative to the baculovirus core genes. At the genomic level, there are a large number of SNPs and InDels between the two virus isolates, especially in and around the bro genes and hrs. Additionally, we discovered that CnmeGV acquired a segment of non-ORF sequence from its host, which does not provide any new proteins but rather serves as redundant genetic material integrated into the viral genome. Furthermore, we observed that the host's transposon piggyBac has inserted into some virus genes. Together, dsDNA viruses could acquire non-coding genetic material from their hosts to expand the size of their genomes. These findings provide new insights into the evolution of dsDNA viruses.

AIM2, a cytosolic innate immune receptor, has the capability to recognize double-stranded DNA (dsDNA). This paper delineates the structural features of AIM2 and its mechanisms of activation, emphasizing its capacity to detect cytosolic DNA and initiate inflammasome assembly. Additionally, we explore the diverse functions of AIM2 in different cells. Insights into AIM2-mediated neuroinflammation provide a foundation for investigating novel therapeutic strategies targeting AIM2 signaling pathways. Furthermore, we present a comprehensive review of the roles of AIM2 in neurodegenerative diseases, including Alzheimer’s disease (AD) and Parkinson’s disease (PD). Finally, we discuss its therapeutic implications. In conclusion, a profound understanding of AIM2 in neurodegenerative diseases may facilitate the development of effective interventions to mitigate neuronal damage and slow disease progression.

Purpose: This study aimed to investigated the key chemical components and the effect of the aqueous extract of Schisandra sphenanthera (SSAE) on alcoholic liver disease (ALD) and the related molecular mechanism. Methods: This study employed UPLC-Q-TOF-MS/MS to identify the chemical compositions in SSAE. ALD rat model was established through oral administration of white spirit. Transcriptome sequencing, weighted gene co-expression network construction analysis (WGCNA), and network pharmacology were used to predict key compositions and pathways targeted by SSAE for the treatment of ALD. Enzyme-linked immunosorbent assay (ELISA), biochemical kits, hematoxylin-eosin (HE) staining, Western blotting (WB) analysis, and immunohistochemical analysis were used to validate the mechanism of action of SSAE in treating ALD. Results: Active ingredients such as schisandrin A, schisandrol A, and schisandrol B were found to regulate the PI3K/AKT/IKK signaling pathway. Compared to the model group, the SSAE group demonstrated significant improvements in cellular solidification and tissue inflammation in the liver tissues of ALD model rats. Additionally, SSAE regulated the levels of a spartate aminotransferase (AST), alanine aminotransferase (ALT), alcohol dehydrogenase (ADH), and aldehyde Dehydrogenase (ALDH) in serum (P

Abstract The continued miniaturization of chips demands highly thermally conductive materials and effective thermal management strategies. Particularly, the high‐field transport of the devices built with 2D materials is limited by self‐heating. Here a systematic control of heat flow in single‐side fluorinated graphene (FG) with varying degrees of fluorination is reported, revealing a superior room‐temperature thermal conductivity as high as 128 W m−1 K−1. Monolayer graphene/FG lateral heterostructures with seamless junctions are approached for device fabrication. Efficient in‐plane heat removal paths from graphene channel to side FG are created, contributing significant reduction of the channel peak temperature and improvement in the current‐carrying capability and power density. Molecular dynamics simulations indicate that the interfacial thermal conductance of the heterostructure is facilitated by the high degree of overlap in the phonon vibrational spectra. The findings offer novel design insights for efficient heat dissipation in micro‐ and nanoelectronic devices.

A facile, transition-metal-free, HFIP-promoted method for the synthesis of triarylmethanes through direct Friedel-Crafts reactions of imidazo[1,2-a]pyridines with chlorohydrocarbon derivatives has been described, which allows for efficient synthesis of triarylmethanes containing imidazo[1,2-a]pyridines in good to satisfactory yields at room temperature. This transformation features simple operation, excellent functional group tolerance, and a broad substrate scope.

The flow characteristics of blasthole stemming slurry (BSS), predominantly comprising yellow mud (YM), tail mud (TM), or drilling cuttings (DC), were systematically investigated. Various influencing factors, including slurry mass concentration, the addition of TM or DC, and the mass ratio of TM to YM (TM/YM) and DC to YM (DC/YM), were meticulously examined. Experiments were conducted to assess the fluidity, rheological properties, and bleeding rate of BSS samples, which were prepared by manipulating slurry mass concentration and the proportions of TM or DC. The results indicate that the rheological properties of BSS are suitably described by the Herschel-Bulkley model. A critical mass concentration was identified, beyond which the flowability of BSS rapidly deteriorates. Replacing YM with an equivalent amount of TM at a mass concentration of 59% increased the yield stress by 167.30%, while reducing the bleeding rate to 0 within the 53%–59% mass concentration range. Conversely, replacing YM with DC at a mass concentration of 62% reduced the yield stress by 63.96%, while increasing the 60-minute bleeding rate from 0% to 1.44%. Increasing the TM/YM ratio resulted in reduced fluidity, elevated yield stress, and a variable degree of shear thickening. The degree of shear thickening was highest when the TM/YM ratio was 1, with significant impacts on differential viscosity at higher shear rates. On the other hand, increasing the DC/YM ratio enhanced fluidity, decreased yield stress, and influenced the degree of shear thickening and differential viscosity, with the highest shear thickening and lowest differential viscosity observed at a DC/YM ratio of 3. The bleeding rate of BSS consistently rose with the increase in the DC/YM ratio.

Abstract Copper, a trace element and vital cofactor, plays a crucial role in the maintenance of biological functions. Recent evidence has established significant correlations between copper levels, cancer development and metastasis. The strong redox‐active properties of copper offer both benefits and disadvantages to cancer cells. The intestinal tract, which is primarily responsible for copper uptake and regulation, may suffer from an imbalance in copper homeostasis. Colorectal cancer (CRC) is the most prevalent primary cancer of the intestinal tract and is an aggressive malignant disease with limited therapeutic options. Current research is primarily focused on the relationship between copper and CRC. Innovative concepts, such as cuproplasia and cuproptosis, are being explored to understand copper‐related cellular proliferation and death. Cuproplasia is the regulation of cell proliferation that is mediated by both enzymatic and nonenzymatic copper‐modulated activities. Whereas, cuproptosis refers to cell death induced by excess copper via promoting the abnormal oligomerisation of lipoylated proteins within the tricarboxylic acid cycle, as well as by diminishing the levels of iron‐sulphur cluster proteins. A comprehensive understanding of copper‐related cellular proliferation and death mechanisms offers new avenues for CRC treatment. In this review, we summarise the evolving molecular mechanisms, ranging from abnormal intracellular copper concentrations to the copper‐related proteins that are being discovered, and discuss the role of copper in the pathogenesis, progression and potential therapies for CRC. Understanding the relationship between copper and CRC will help provide a comprehensive theoretical foundation for innovative treatment strategies in CRC management.