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Cermets generally exhibit a trade-off between strength and energy dissipation capacity. By applying a dual design strategy combining bioinspired architecting and metastability engineering, we developed a transforming interpenetrating-phase cermet made from zirconia ceramic preform infiltrated with an Al-Zn-Mg-Cu alloy. The cermet micro-pillars possessed compressive yield strengths of 773 ± 62 MPa and energy dissipation densities of 110 ± 8 MJ·m−3, 50% and 45% higher than those of the monolithic Al alloy, respectively. These results are attributed to the interpenetrating-phase architecture, stress-induced martensitic transformation in the ceramics, robust interfacial bonding, and high-density dislocations near the interfaces.

Abstract Purpose Accurate detection and resection of the epileptogenic zone (EZ) in patients with long-term epilepsy-associated tumors (LEATs) are significantly correlated with favorable seizure prognosis. However, the relationship between tumors and the EZ remains unknown. This study aimed to evaluate the spatial relationship between LEATs and the EZ, as well as the electrophysiological features of LEATs. Methods We retrospectively studied five patients with LEATs who underwent deep electrode implantation and EZ resection in the hospital. The clinical characteristics, surgical outcomes, localizing features and intracranial SEEG results were reviewed. Results One female and four males (mean age: 25.2 years; median age: 24 years; range: 13–45 years) were included in the study. Five-to-eleven electrodes (mean: 8.4) were implanted per patient. The EZ was located in the tumor and nearby cortex in three cases and in the tumor and distant areas in two cases. Pathological examination revealed ganglioglioma in four cases, two of which were associated with hippocampal sclerosis, and the other case showed a multinodular and vacuolating neuronal tumor with gliosis. All patients were seizure-free for at least 24 months postoperatively. Conclusions SEEG provides valuable insights into the electrophysiological mechanisms of LEATs. The EZ often contains brain tissue around the tumor. However, only a few cases, particularly those with temporoparietal occipital (TPO) area involvement, a long history of epilepsy and other abnormalities on MRI, such as hippocampal sclerosis and focal cortical dysplasia, may include distant areas.

Renal unilateral ischemia-reperfusion injury (UIRI) constitutes a significant global health challenge, with poor recovery leading to chronic kidney disease and subsequent renal fibrosis. Extracellular vesicles (EVs) present substantial potential benefits for renal diseases. However, the limited yield and efficacy of EVs produced through traditional methodologies (2D-EVs) severely restrict their widespread application. Moreover, the efficient and effective strategies for using EVs in UIRI treatment and their mechanisms remain largely unexplored. In this study, we propose an innovative approach by integrating bioprinted mesenchymal stem cell microfiber extracellular vesicles production technology (3D-EVs) with a tail vein injection method, introducing a novel treatment strategy for UIRI. Our comparison of the biological functions of 2D-EVs and 3D-EVs, both in vitro and in vivo, reveals that 3D-EVs significantly outperform 2D-EVs. Specifically, in vitro, 3D-EVs demonstrate a superior capacity to enhance the proliferation and migration of NRK-52E cells and mitigate hypoxia/reoxygenation (H/R)-induced injuries by reducing epithelial-mesenchymal transformation, extracellular matrix deposition, and ferroptosis. In vivo, 3D-EVs exhibit enhanced therapeutic effects, as evidenced by improved renal function and decreased collagen deposition in UIRI mouse kidneys. We further elucidate the mechanism by which 3D-EVs derived from KLF15 ameliorate UIRI-induced tubular epithelial cells (TECs) ferroptosis through the modulation of SLC7A11 and GPX4 expression. Our findings suggest that bioprinted mesenchymal stem cells microfiber-derived EVs significantly ameliorate renal UIRI, opening new avenues for effective and efficient EV-based therapies in UIRI treatment.

The development of conductive coatings has significant implications for microelectronics and electrochemistry. However, conductive coatings may exhibit different electrochemical properties when prepared on different substrate materials. This research explores the comparative performance of graphene, graphene oxide (GO), and silver nanoparticle (Ag NP) composites as conductive coatings on diverse substrate materials, including polydimethylsiloxane (PDMS), polymethyl methacrylate (PMMA), and glass. The study employed various preparation methods, such as mixing conductive materials with substrate materials and preparing copolymer composite materials. The conductive coating approach was found to be the most straightforward and convenient, with broader development prospects and fewer restrictive conditions. The results indicate that the distinct surface characteristics of the substrate materials influence the conductive properties of coating materials. Consequently, results show that graphene exhibits the highest conductivity on all three substrates, while GO is more conductive than Ag NPs on PMMA and PDMS but less conductive than Ag NPs on glass. That offers valuable insights into the selection of substrate materials and coating materials for the preparation of conductive materials.

Abstract The prognosis of septic patients with cirrhosis is worse compared to septic patients without cirrhosis. Early and accurate prognosis determination in patients with cirrhosis and sepsis is pivotal for guiding treatment decisions. The aim of this study was to investigate the association between albumin-corrected anion gap (ACAG) and clinical prognosis of patients with sepsis and cirrhosis. This study extracted data of patients with sepsis and cirrhosis from the Medical Information Mart for Intensive Care (MIMIC-IV) database. A total of 1340 patients (64.6% male) were enrolled. After confounders adjusting, elevated ACAG had a significant association with 28-day mortality (HR1.604; 95% CI 1.258–2.048; P

Abstract Primary dysmenorrhea (PD) is a common global health concern. However, limited studies explored the association between soft drinks intake and PD among female undergraduates in China. To determine the association between soft drinks (carbonated soft drinks, etc.) as well coffee intake and the incidence/severity of PD among female undergraduates in China. We performed a cross-sectional study among 1809 female undergraduates in China from September 29, 2020 to October 22, 2020. The demographic information and menstrual information of the participants were collected by a self-administrated questionnaire. Chi-square test, ANOVA test, and logistic regression test were used to investigate the association between soft drinks intake and the incidence/severity of PD. We also conducted stratification analysis among different locations (rural or urban). The prevalence of PD was 47.1% (n = 852). There were 221 (25.9%) participants suffered from severe pain. In the participants with PD, the OR of carbonated soft drinks intake was 1.244 (95% CI 1.010–1.533). Among the participants with PD from rural areas, the OR of carbonated soft drinks intake was 1.402 (95% CI 1.045–1.881), compared with the non-carbonated soft drink group. In the participants with moderate and severe PD, the OR of coffee intake was 0.451 (95% CI 0.228–0.892), compared with the non-coffee-drinking group. There was a significant association between carbonated soft drinks intake frequency and the severity of PD (P

Abstract To address the problems of low accuracy in fault diagnosis of oil-immersed transformers, poor state perception ability and real-time collaboration during diagnosis feedback, a fault diagnosis method for transformers based on the integration of digital twins is proposed. Firstly, fault sample balance is achieved through Iterative Nearest Neighbor Oversampling (INNOS), Secondly, nine-dimensional ratio features are extracted, and the correlation between dissolved gases in oil and fault types is established. Then, sparse principal component analysis (SPCA) is used for feature fusion and dimensionality reduction. Finally, the Aquila Optimizer (AO) is introduced to optimize the parameters of the Kernel Extreme Learning Machine (KELM), establishing the optimal AO-KELM diagnosis model. The final fault diagnosis accuracy reaches 98.1013%. Combining transformer digital twin models, real-time interaction mapping between physical entities and virtual space is achieved, enabling online diagnosis of transformer faults. Experimental results show that the method proposed in this paper has high diagnostic accuracy and strong stability, providing reference for the intelligent operation and maintenance of transformers.

The three-level converter has become the mainstream converter topology because of its good output power quality and high power factor. The three-level dual pulse width modulation frequency speed control system with rectifier–inverter structure has become a research hotspot in academic circles because of its advantages of bidirectional energy flow, high power quality, and controllable intermediate direct current (DC) voltage. Aiming at the high-performance and high-efficiency control of the three-level neutral point clamped (NPC) rectifier–inverter drive system of an induction motor, this study builds a prediction and loss model of the three-level rectifier–inverter system, constructs a cost function including the midpoint voltage balance and loss optimization, and proposes a model predictive control without weighting factors based on a sequential parallel structure. With the development of the field of power electronics, the control performance and efficiency of the converter have gradually improved, and the model predictive control applied to the converter is no longer limited to the traditional control objectives. The proposed strategy introduces the DC bus midpoint voltage and converter switching frequency control to the traditional sequential model predictive control and constructs a unified cost function with multiple control objectives. According to the actual requirements of the multiple control objectives in the operation of the rectifier–inverter system, the control objectives in the cost function are divided into primary and secondary control objectives and classified into two sequence optimization sets, and different sequence sets are sequentially optimized. In the same sequence set, adaptive parallel optimization is used to select the optimal switching state, which ensures the synchronous optimization of each control object in the sequence, thus avoiding the need for weighting factors. The parallel structure can rank multiple control targets, reduce the number of sequences to increase the number of optional voltage vectors between each sequence and increase the control effect of nonprimary control targets. Moreover, synchronous optimization of control targets of the same importance is realized at the same level, which solves the problem that targets of similar importance must be sequentially optimized in conventional sequential model predictive control, solves the problem that the priority of different targets is difficult to adjust, and has stronger applicability for the complex topology structure with multiple control requirements. The simulation and experimental results showed that the proposed algorithm can improve the steady-state and dynamic performance of the system, reduce the midpoint voltage bias, reduce the switching frequency of the rectifier and inverter, reduce the total harmonic bias, and adjust the midpoint voltage unbalance.

Mine water, as the main potential water supply source for coal mine sites, has a good potential for comprehensive reuse. However, the complex and diverse physical and chemical reactions between the coal seam roof-filling aquifers and the surrounding rocks jointly affect the quality of mine water in coal mines. Therefore, it is of vital significance to determine the status of groundwater quality and its genesis mechanism in different water-filled aquifers for the protection and comprehensive utilization of mine water. Based on the groundwater samples and rock mineral composition data from a well field in Xinjie Taigemiao Mine, this study uses multivariate statistical analysis and hydrogeochemical techniques, and simulates the water chemical equilibrium by PHREEQC software, to explore in depth the chemical characteristics of the groundwater in different aquifers and its vertical zoning laws of mineral dissolution/precipitation, with the aim of revealing the causative mechanism. It is found that ① the chemical characteristics of the groundwater in the mining area show obvious vertical heterogeneity, in which the Zhidan Group is dominated by HCO3-Na-Ca and HCO3-Mg·Ca types, while the Anding Formation to Yan’an Formation is dominated by Cl-SO4-Na and SO4-Na types, TDS, Na+, and \begin{document}$\text{SO}_{\text{4}}^{{2-}} $\end{document} may be key drivers dominating vertical water quality differentiation. ② The concentrations of key water quality indicators, such as TDS, Na+, and \begin{document}$\text{SO}_{\text{4}}^{{2-}} $\end{document}, show a linear relationship with the depth of the aquifer (from the Zhidan Group to the Yan'an Formation), and the analysis of the ionic ratios reveals that the K+ and Na+ mainly originate from the dissolution of silicate minerals, and that the concentrations of Ca2+ and Mg2+ are affected by the dissolution of carbonate, sulfate and silicate minerals. ③ The depth variation of the mineral saturation index shows that dolomite, plagioclase feldspar and rock salt alternate between unsaturated and oversaturated states in different aquifers. In the groundwater of the Zhidan Group and the Anding Formation, many minerals show a tendency of further dissolution, while in the Zhiluo Formation and the Yan’an Formation, the majority of the minerals have already reached the oversaturated state. ④ Water-rock interactions control the hydrochemical composition of mine water at different depths. The hydrochemical components of the uppermost Shidan Group are mainly affected by the dissolution of minerals such as sodium feldspar, potassium feldspar, calcite, chlorite, and so on, and the deeper aquifers show a stronger reaction to the dissolution of silicate minerals, gypsum, rock salts, and pyrite accompanied by alternating adsorption of cations, resulting in the formation of highly mineralized Cl- SO4-Na, SO4-Na type water. This study deeply explores the vertical zoning characteristics of groundwater chemistry in different aquifers in the coal mine area and its mineral dissolution mechanism, which provides a solid scientific foundation for the precise management of mine water resources, water quality regulation and environmental protection, and has important theoretical guidance value and practical application prospects.

Abstract Introduction ARDS (acute respiratory distress syndrome) is the most severe form of acute hypoxic respiratory failure. Most studies related to ARDS have excluded patients with hematologic diseases, let alone allogeneic hematopoietic stem cell transplantation (allo-HSCT) recipients. Numerous patients experiencing severe hypoxic respiratory failure do not meet the Berlin definition due to the limitations of diagnosis and treatment. A new definition of ARDS, remove some diagnosis restrictions, was proposed in 2023. Based on the 2023 new definition of ARDS, we investigated the clinical features of ARDS in allo-HSCT recipients and reported risk factors for in-hospital mortality in allo-HSCT recipients defined by the Berlin definition and the new definition of ARDS respectively. Methods From Jan 2016 to Dec 2020, 135 allo-HSCT recipients identified with the new definition and 87 identified with the Berlin definition at three teaching hospitals were retrospectively included in this study. Variables (demographic information, characteristics of hematologic disease and ARDS episode, laboratory tests and SOFA score) with P

Abstract Objective Subcortical nuclei such as the thalamus and striatum have been shown to be related to seizure modulation and termination, especially in drug‐resistant epilepsy. Enhance diffusion‐weighted imaging (eDWI) technique and tri‐component model have been used in previous studies to calculate apparent diffusion coefficient from ultra high b‐values (ADCuh). This study aimed to explore the alterations of ADCuh in the bilateral thalamus and striatum in MRI‐negative drug‐resistant epilepsy. Methods Twenty‐nine patients with MRI‐negative drug‐resistant epilepsy and 18 healthy controls underwent eDWI scan with 15 b‐values (0–5000 s/mm2). The eDWI parameters including standard ADC (ADCst), pure water diffusion (D), and ADCuh were calculated from the 15 b‐values. Regions‐of‐interest (ROIs) analyses were conducted in the bilateral thalamus, caudate nucleus, putamen, and globus pallidus. ADCst, D, and ADCuh values were compared between the MRI‐negative drug‐resistant epilepsy patients and controls using multivariate generalized linear models. Inter‐rater reliability was assessed using the intra‐class correlation coefficient (ICC) and Bland–Altman (BA) analysis. False discovery rate (FDR) method was applied for multiple comparisons correction. Results ADCuh values in the bilateral thalamus, caudate nucleus, putamen, and globus pallidus in MRI‐negative drug‐resistant epilepsy were significantly higher than those in the healthy control subjects (all p

Abstract Background Alveolar echinococcosis (AE) primarily affects the liver and potentially spreads to other organs. Managing recurrent AE poses significant challenges, especially when it involves critical structures and multiple major organs. Case presentation We present a case of a 59-year-old female with recurrent AE affecting the liver, heart, and lungs following two previous hepatectomies, the hepatic lesions persisted, adhering to major veins, and imaging revealed additional diaphragmatic, cardiac, and pulmonary involvement. The ex vivo liver resection and autotransplantation (ELRA), first in human combined with right atrium (RA) reconstruction were performed utilizing cardiopulmonary bypass, and repairs of the pericardium and diaphragm. This approach aimed to offer a potentially curative solution for lesions previously considered inoperable without requiring a donor organ or immunosuppressants. The patient encountered multiple serious complications, including atrial fibrillation, deteriorated liver function, severe pulmonary infection, respiratory failure, and acute kidney injury (AKI). These complications necessitated intensive intraoperative and postoperative care, emphasizing the need for a comprehensive management strategy in such complicated high-risk surgeries. Conclusions The multidisciplinary collaboration in this case proved effective and yielded significant therapeutic outcomes for a rare case of advanced hepatic, cardiac, and pulmonary AE. The combined approach of ELRA and RA reconstruction under extracorporeal circulation demonstrated distinct advantages of ELRA in treating complex HAE. Meanwhile, assessing diaphragm function during the perioperative period, especially in patients at high risk of developing pulmonary complications and undergoing diaphragmectomy is vital to promote optimal postoperative recovery. For multi-resistant infection, it is imperative to take all possible measures to mitigate the risk of AKI if vancomycin administration is deemed necessary.

Abstract The collective light-matter interaction of chiral supramolecular aggregates or molecular ensembles with confined light fields remains a mystery beyond the current theoretical description. Here, we programmably and accurately build models of chiral plasmonic complexes, aiming to uncover the entangled effects of excitonic correlations, intra- and intermolecular charge transfer, and localized surface plasmon resonances. The intricate interplay of multiple chirality origins has proven to be strongly dependent on the site-specificity of chiral molecules on plasmonic nanoparticle surfaces spanning the nanometer to sub-nanometer scale. This dependence is manifested as a distinct circular dichroism response that varies in spectral asymmetry/splitting, signal intensity, and internal ratio of intensity. The inhomogeneity of the surface-localized plasmonic field is revealed to affect excitonic and charge-transfer mixed intermolecular couplings, which are inherent to chirality generation and amplification. Our findings contribute to the development of hybrid classical-quantum theoretical frameworks and the harnessing of spin-charge transport for emergent applications.

In this study, coal samples' reactive group contents were changed using extractants, and the effects of the reactive group contents spontaneous coal combustion were investigated using infrared spectroscopy, thermogravimetry/derivative thermogravimetry, and differential scanning calorimetry. The results showed that the coal samples' hydroxyl group contents decreased in the order ethylenediamine (3.832 %) > N-methyl-2-pyrollidone mixed solution (2.091 %) > petroleum ether (0.882 %) > toluene (0.495 %) and that the hydroxyl group content was inversely related to the characteristic temperature point. RDG analysis showed that ethylenediamine formed N–H–O hydrogen bonds with hydroxyl-group-bearing molecules, coal molecules formed C–H–O hydrogen bonds with NMP molecules, petroleum ether generated a cumulative dispersive force with aliphatic side chains, and toluene molecules' benzene rings formed a very stable spatial structure with coal molecules' benzene rings. The thermogravimetry/derivative thermogravimetry curves showed that because the characteristic temperature points of the extracted coal samples moved to the high-temperature region from T5 onward, the coal samples had to be heated to a higher temperature to reach the energy required for the reaction. From the DSC thermograms, the exergy decreased in the order toluene (110.68 J/g) > NMP (110.52 J/g) > ethylenediamine (78.29 J/g) > petroleum ether (65.45 J/g). With increasing temperature from T1 to T6, the Pearson correlation coefficients of the alcoholic and phenolic hydroxyl groups were calculated at −0.7, −0.72, −0.93, −0.84, −0.8, −0.8, and −0.93 and −0.72, −0.91, −0.83, −0.79, −0.815, and −0.91, respectively, indicating that the hydroxyl group content influenced the coal's spontaneous combustion more than the other groups' contents.

BackgroundThe incidence and mortality rates of cancer are the highest globally. Developing novel methodologies that precisely, safely, and economically differentiate between benign and malignant lung conditions holds immense clinical importance. This research seeks to construct a predictive model utilizing a combination of diverse biomarkers to effectively discriminate between benign and malignant lung diseases.MethodsThis retrospective study included patients admitted to the two general hospitals in Shanghai from 2014 to 2015. This study was developed using five tumor markers: carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA199), cytokeratin fragment 21-1 (CA211), squamous cell carcinoma antigen (SCC), and neuron specific enolase (NSE). The entire sample was divided into two groups according to the hospital: 1033 cases were included in the development cohort and 300 cases in the validation cohort. Logistic regression analysis was used for univariate analysis to explore individual correlations between each selected clinical variable and lung cancer diagnostic outcome. Diagnostic prediction models were constructed and validated based on independent prognostic factors identified using multifactorial analysis. A nomogram was created using these tumor markers (age and sex were additionally included) and validated using the concordance index and calibration curves. Clinical prediction models were evaluated using decision curve analysis.ResultsFully adjusted multivariate analysis showed that the risk of lung cancer was 2.38 times higher in men than in women. CEA positivity was associated with an 13.41-fold increased risk in lung cancer. The area under the curve (AUC) values for the development cohort and validation cohort models were 0.907 and 0.954, respectively. In the established nomogram, the AUC for the receiver operating characteristic curve was 0.907 (95% CI, 0.889–0.925). The validation model confirmed the strong discriminative power of the nomogram (AUC = 0.954). The described calibration curves demonstrated good fit predictions and observation probabilities. In addition, decision curve analysis concluded that the newly established nomogram has important implications for clinical decision making.ConclusionsCombined prediction models based on CEA, CA199, CA211, SCC, and NSE biomarkers could significantly the differentiation between benign and malignant lung diseases, thus facilitating better clinical decision making.

Abstract Background Focal cortical dysplasia (FCD) is a heterogeneous group of cortical developmental malformations that constitute a common cause of medically intractable epilepsy. FCD type IIIa (FCD IIIa) refers to temporal neocortex alterations in architectural organisation or cytoarchitectural composition in the immediate vicinity of hippocampal sclerosis. Slight alterations in the temporal neocortex of FCD IIIa patients pose a challenge for the preoperative diagnosis and definition of the resection range. Methods We have performed multimodal integration of single‐nucleus RNA sequencing and single‐nucleus assay for transposase‐accessible chromatin sequencing in the epileptogenic cortex of four patients with FCD IIIa, and three relatively normal temporal neocortex were chosen as controls. Results Our study revealed that the most significant dysregulation occurred in excitatory neurons (ENs) and oligodendrocyte precursor cells (OPCs) in the epileptogenic cortex of FCD IIIa patients. In ENs, we constructed a transcription factor (TF)‐hub gene regulatory network and found DAB1high ENs subpopulation mediates neuronal immunity characteristically in FCD IIIa. Western blotting and immunofluorescence were used to validate the changes in protein expression levels caused by some of the key genes. The OPCs were activated and exhibited aberrant phenotypes in FCD IIIa, and TFs regulating reconstructed pseudotime trajectory were identified. Finally, our results revealed aberrant intercellular communication between ENs and OPCs in FCD IIIa patients. Conclusions Our study revealed significant and intricate alterations in the transcriptomes and epigenomes in ENs and OPCs of FCD IIIa patients, shedding light on their cell type‐specific regulation and potential pathogenic involvement in this disorder. This work will help evaluate the pathogenesis of cortical dysplasia and epilepsy and explore potential therapeutic targets. Key points Paired snRNA‐seq and snATAC‐seq data were intergrated and analysed to identify crucial subpopulations of ENs and OPCs in the epileptogenic cortex of FCD IIIa patients and explore their possible pathogenic role in the disease. A TF‐hub gene regulatory network was constructed in ENs, and the DAB1high Ex‐1 mediated neuronal immunity was characterstically in FCD IIIa patients. The OPCs were activated and exhibited aberrant phenotypes in FCD IIIa patients, and TFs regulating reconstructed pseudotime traectory were identified. Aberrant intercelluar communications between ENs and OPCs in FCD IIIa patients were identified.

To efficiently develop hot dry rock and other geothermal energy, a multilateral butted closed loop geothermal system (MBCLGS) is presented in this paper to replace the U-shaped closed-loop geothermal system (UCLGS). Besides, a casing-cement-formation transient heat transfer model is established to investigate the influences of key factors on the heat production of MBCLGS. After thermal-fluid-structural coupling analysis, we can find that higher injected rate and lower fluid temperature can improve heat power but reduce output temperature. In addition, the output temperature and heat power do not increase continuously with the increasing of branch well number. There is an optimal value of branch well number. Longer well pair distance can improve both output temperature and heat power. Considering the drilling technology level and design purpose, the recommended injected flow rate of MBCLGS is 90 m3/h, the injected fluid temperature is 42.5 °C, the number of branch wells is 10 and the well pair distance is 200m. Finally, by comparing MBCLGS and UCLGS, it is found that MBCLGS has a lower temperature decline rate and higher output temperature than UCLGS under the same conditions. It works more stable and has better economy. Overall, the proposal of MBCLGS is expected to promote the efficient development of deep geothermal resources.

Abstract Introduction The purpose of this research was to determine how the P53/microRNA‐34a (miR‐34a)/survivin pathway contributes to oxaliplatin‐induced (L‐OHP) cell inhibition in gastric cancer. Methods The BGC‐823 gastric cancer cells were selected, and we examined their viability following treatment with L‐OHP at different concentrations and time periods. The expression levels of miR‐34a, P53, and survivin in the cells were determined. Results In the 12‐ and 24‐h groups, drug concentration of 15 μg/cm² (p

This review summarizes the research progress over the past 30 years on the relationship between Mycoplasma pneumoniae infection and chronic respiratory diseases such as asthma, chronic obstructive pulmonary disease (COPD), and bronchiectasis. Mycoplasma pneumoniae is a common cause of community-acquired pneumonia, particularly in children and young adults. Key findings from recent studies indicate that M. pneumoniae infection is associated with a higher risk of asthma exacerbations and may contribute to the development of bronchiectasis in susceptible individuals. Additionally, emerging evidence suggests that M. pneumoniae-induced immune dysregulation plays a crucial role in the pathogenesis of chronic lung diseases. This review aims to summarize the current understanding of the potential links between M. pneumoniae pneumonia and various chronic respiratory conditions, including asthma, chronic obstructive pulmonary disease (COPD), and bronchiectasis. We discuss the epidemiological data, pathogenic mechanisms, clinical manifestations, and long-term consequences of M. pneumoniae-related respiratory illnesses. Additionally, we highlight the challenges in diagnosis and treatment, as well as future research directions in this field.

This study investigates the impact of water resource restrictions on thermoelectric and hydroelectric stations, analyzing its influence on demand and electricity prices. It uses General Circulation Models (GCMs) and Soil and Water Assessment Tools (SWAT) to forecast future temperature trends and estimate river flow patterns. The research provides insights into climate change's potential effects on water resources and electricity potential. The study shows a significant decrease in river flow, indicating potential issues with hydroelectric and thermoelectric systems. The study also uses an optimized Echo State Network (ESN) for accurate electricity demand, using the Modified Snow Leopard Optimization (MSLO) algorithm as a new metaheuristic model. The simulation results show a consistent increase in electricity demand scenarios, which is expected to lead to higher supply prices due to decreased production capacity. This could have significant economic effects. The investigation provides a comprehensive understanding of water resource management challenges in power production, aiding in informed decisions in the future energy industry.

Lung cancer remains a leading cause of cancer-related deaths globally, with its incidence steadily rising each year, representing a significant threat to human health. Early detection, diagnosis, and timely treatment play a crucial role in improving survival rates and reducing mortality. In recent years, significant and rapid advancements in artificial intelligence (AI) technology have found successful applications in various clinical areas, especially in the diagnosis and treatment of lung cancer. AI not only improves the efficiency and accuracy of physician diagnosis but also aids in patient treatment and management. This comprehensive review presents an overview of fundamental AI-related algorithms and highlights their clinical applications in lung nodule detection, lung cancer pathology classification, gene mutation prediction, treatment strategies, and prognosis. Additionally, the rapidly advancing field of AI-based three-dimensional (3D) reconstruction in lung cancer surgical resection is discussed. Lastly, the limitations of AI and future prospects are addressed.

In the context of “zero discharge” of mine water and the reverse distribution of coal and water resources in the western mining areas, the direct discharge of high-salinity mine water without proper treatment not only causes immeasurable damage to the local ecological environment, but also leads to serious water resource waste, ultimately constraining the green development of coal industry and the development of ecological civilization. The traditional zero discharge technology for high-salinity wastewater mainly relies on evaporation and crystallization to transform inorganic salts from a solution state to a crystalline state for recovery. From an economic perspective, this technology faces issues such as high investment, high operating costs, and low added value of inorganic salts. Based on this, this paper takes the mine water from a western mine as the raw water, aiming to achieve the resource utilization and desalination of mine water through the membrane integration technology, and focuses on exploring the influence of different operating conditions (operating voltage, feed solution concentration, temperature, acidity and alkalinity, current density, etc.) on the desalination performance of electrodialysis and the acid-base performance of bipolar membrane electrodialysis. Then, based on the experimental data and an economic evaluation model, the economic feasibility is explored, aiming to explore the membrane integration technology suitable for the treatment of high-salinity mine water in the western mining areas, and provide some new research ideas for the development of green resource utilization processes for high-salinity mine water. Through the exploration of the electrodialysis-bipolar membrane electrodialysis experimental process, it is found that the feed solution concentration of the bipolar membrane system should not exceed 80 g/L, the appropriate operating voltage is 18 V, the suitable feed solution temperature is 25 ℃, the feed solution pH should be kept neutral, and constant voltage operation is more suitable. In addition, it is confirmed that the membrane integration system centered on bipolar membrane electrodialysis can achieve the green resource utilization of high-salinity mine water. Taking the total salt content of the electrodialysis system feed solution as an example (20 g/L), the overall net profit is ￥18604299 per year, and it has a significant carbon dioxide emission reduction effect when coupled with a photovoltaic power supply system, with a carbon dioxide emission reduction of over 3162 tons per year, demonstrating good economic and social benefits.

Abstract Background Perihematomal edema (PHE) after post-intracerebral hemorrhage (ICH) has complex pathophysiological mechanisms that are poorly understood. The complicated immune response in the post-ICH brain constitutes a crucial component of PHE pathophysiology. In this study, we aimed to characterize the transcriptional profiles of immune cell populations in human PHE tissue and explore the microscopic differences between different types of immune cells. Methods 9 patients with basal ganglia intracerebral hemorrhage (hematoma volume 50-100 ml) were enrolled in this study. A multi-stage profile was developed, comprising Group1 (n = 3, 0–6 h post-ICH, G1), Group2 (n = 3, 6–24 h post-ICH, G2), and Group3 (n = 3, 24–48 h post-ICH, G3). A minimal quantity of edematous tissue surrounding the hematoma was preserved during hematoma evacuation. Single cell RNA sequencing (scRNA-seq) was used to map immune cell populations within comprehensively resected PHE samples collected from patients at different stages after ICH. Results We established, for the first time, a comprehensive landscape of diverse immune cell populations in human PHE tissue at a single-cell level. Our study identified 12 microglia subsets and 5 neutrophil subsets in human PHE tissue. What’s more, we discovered that the secreted phosphoprotein-1 (SPP1) pathway served as the basis for self-communication between microglia subclusters during the progression of PHE. Additionally, we traced the trajectory branches of different neutrophil subtypes. Finally, we also demonstrated that microglia-produced osteopontin (OPN) could regulate the immune environment in PHE tissue by interacting with CD44-positive cells. Conclusions As a result of our research, we have gained valuable insight into the immune-microenvironment within PHE tissue, which could potentially be used to develop novel treatment modalities for ICH.

Abstract Killer cell lectin-like receptor B1 (KLRB1) is implicated in cancer progression and immunity. In this study, we aimed to evaluate the expression levels of KLRB1 in lung adenocarcinoma (LUAD) and analyze the relationship between KLRB1 expression levels, LUAD progression, and the tumor immune microenvironment. KLRB1 levels in LUAD were analyzed using data from the TCGA and XENA databases. Additionally, the diagnostic values of KLRB1 were analyzed in patients with LUAD. Survival and meta-analyses were employed to investigate the relationship between KLRB1 levels and other prognostic factors in patients with LUAD. Bioinformatics and cellular experiments were used to understand the functions and mechanisms of KLRB1. In addition, correlation analysis was used to investigate the relationship between KLRB1 levels and the immune microenvironment in LUAD. Reduced KLRB1 expression in LUAD was found to positively correlate with tumor size, distant metastasis, pathological stage, age, overall survival, diagnostic value, and disease-specific survival in patients with LUAD (P

Abstract The incorporation of thermal imaging data in RGB-T images has demonstrated its usefulness in cross-modal crowd counting by offering complementary information to RGB representations. Despite achieving satisfactory results in RGB-T crowd counting, many existing methods still face two significant limitations: (1) The oversight of the heterogeneous gap between modalities complicates the effective integration of multimodal features. (2) The absence of mining consistency hinders the full exploitation of the unique complementary strengths inherent in each modality. To this end, we present C4-MIM, a novel Consistency-constrained RGB-T Crowd Counting approach via Mutual Information Maximization. It effectively leverages multimodal information by learning the consistency between the RGB and thermal modalities, thereby enhancing the performance of cross-modal counting. Specifically, we first advocate extracting feature representations of different modalities in a shared encoder to moderate the heterogeneous gap since they obey the identical coding rules with shared parameters. Then, we intend to mine the consistent information of different modalities to better learn conducive information and improve the performance of feature representations. To this end, we formulate the complementarity of multimodality representations as a mutual information maximization regularizer to maximize the consistent information of different modalities, in which the consistency would be maximally attained before combining the multimodal information. Finally, we simply aggregate the feature representations of the different modalities and send them into a regressor to output the density maps. The proposed approach can be implemented by arbitrary backbone networks and is quite robust in the face of single modality unavailable or serious compromised. Extensively experiments have been conducted on the RGBT-CC and DroneRGBT benchmarks to evaluate the effectiveness and robustness of the proposed approach, demonstrating its superior performance compared to the SOTA approaches.

A new spleenwort species, Asplenium guodanum, was found and described from Danxia landform region in Guangdong, China. The new species has close resemblance to A. subcrenatum Ching ex S.H.Wu in morphology, but can be distinguished by having plants small, stipes and rachises not covered with fibrous scales, relatively fewer pairs of pinnae, pinnae short, pinna margin weakly biserrate, pinna apex acute and lower pinnae obviously reduced. Phylogenetic analyses, based on six plastid markers (atpB, rbcL, rps4 & rps4-trnS and trnL & trnL-F) of the new species and its relatives, support a close relationship between A. guodanum and A. subcrenatum. Only one population with no more than 50 individuals were found and, therefore, it is recommended to be classified as Critically Endangered (CR) following IUCN Red List Criteria.

To improve the drill pipe fracture failure phenomenon in deflecting drills with ultra-short radius flexible drill pipes, this study establishes a mechanical model of a deflecting drill with an ultra-short radius flexible drill pipe, numerically simulates the mechanical characteristics of the flexible drill pipe under the conventional drilling process using the finite element analysis method, performs mechanical performance tests on the flexible drill pipe, and optimizes and improves its structure. The results show that, with the gradual increase in the bending angle of the flexible drill pipe unit section, the upper drilling pressure of the flexible drill pipe unit section decreases rapidly and its friction increases approximately linearly. The tensile strength of the optimized ultra-short radius flexible drill pipe is increased by 24.7%, and the minimum threshold of its torsional strength is doubled. This effectively improves the overall strength of the ultra-short radius flexible drill pipe and provides a theoretical basis for downhole drilling stability studies of flexible drill pipes.

Coal is the main energy source in China, and the western region in China is the main coal production area. The protection and utilization of coal mine water is the major technical challenge in the coal mining. The coal green mining research team of China Energy Group has pioneered the technology of underground coal mine reservoirs, which has been widely implemented in the Shendong mining area in Western China, providing over 95% of water needed for mining and ensuring the sustainable development of the mining area. To further enrich and improve the theoretical and technical system of underground coal mine reservoirs, this technology has been promoted and applied under different geological and working conditions in the western coal mining areas to ensure national energy security and water resources protection. The research team has built the original technology experimental platform system for coal mine underground reservoirs, including the comprehensive intelligent experimental platform for underground water transport and protection, the physical modelling platform for coal mine underground reservoirs under multiple coal seams, the dam structure experimental platform for coal mine underground reservoirs, the simulation experimental platform for deep well construction in western areas, the water-rock coupling mechanism experimental platform for underground water reservoirs, the integrated water treatment process experimental platform, and the impact experimental platforms for coal mine underground reservoirs, etc. On these platforms, the researches can be carried out consisting of the transport law of underground water, the optimization of dam structure parameters, the safety and stability of reservoirs, water-rock coupling mechanism, the optimization of mine water treatment, and the impact of caving rock mass on the dam structure under different coal seam occurrence conditions in the western mining areas of China. These platform systems provide a theoretical support and technical verification for the construction, operation, and safety of coal mine underground reservoirs. By utilizing these experimental platforms, various experimental research studies have been conducted, including the stability and seepage of coal mine underground reservoirs under multiple coal seams, the structural safety of coal mine underground reservoirs dam, and the water-rock coupling mechanism of coal mine underground reservoirs. These research results have been applied in actual engineering practice to ensure the safe and stable operation of coal mine underground reservoirs.

Abstract In order to improve the accuracy of transformer fault diagnosis and improve the influence of unbalanced samples on the low accuracy of model identification caused by insufficient model training, this paper proposes a transformer fault diagnosis method based on SMOTE and NGO-GBDT. Firstly, the Synthetic Minority Over-sampling Technique (SMOTE) was used to expand the minority samples. Secondly, the non-coding ratio method was used to construct multi-dimensional feature parameters, and the Light Gradient Boosting Machine (LightGBM) feature optimization strategy was introduced to screen the optimal feature subset. Finally, Northern Goshawk Optimization (NGO) algorithm was used to optimize the parameters of Gradient Boosting Decision Tree (GBDT), and then the transformer fault diagnosis was realized. The results show that the proposed method can reduce the misjudgment of minority samples. Compared with other integrated models, the proposed method has high fault identification accuracy, low misjudgment rate and stable performance.

Abstract Osteofibrous dysplasia (OFD) is a rare, benign, self-limited bone disorder with a relatively low incidence, accounting for approximately 0.2% of all primary bone tumors. It was frequently found intra-cortical of the mid-shaft of the tibia. OFD can also occur in other skeletal regions, including the fibula, ulna, radius, femur, humerus, ischium, rib, tarsus, metatarsals, vertebral, and capitate. OFD can present with asymptomatic, mass, pain, swelling, deformity, and even pathological fracture. OFD might be misdiagnosed as adamantinoma (AD) and because they are three subtypes origin from the same family of bone tumors and have similar imaging features. Moreover, pathology could provide evidence for an accurate diagnosis of OFD, but misdiagnosis may occur due to small sampling materials. To date, few studies have comprehensively introduced the epidemiology, clinical manifestations, pathogenesis, radiological features, pathology, and treatment for OFD. We herein discuss clinical signs, diagnosis methods, and treatment options of OFD to improve the understanding of OFD, which is helpful for accurate diagnosis and appropriate treatment.

Cognitive dysfunction is a core symptom common in psychiatric disorders including depression that is primarily managed by antidepressants lacking efficacy in improving cognition. In this study, we report a novel dual serotonin transporter and voltage-gated potassium Kv7/KCNQ/M-channel inhibitor D01 (a 2-methyl-3-aryloxy-3-heteroarylpropylamines derivative) that exhibits both anti-depression effects and improvements in cognition. D01 inhibits serotonin transporters (Ki = 30.1 ± 6.9 nmol/L) and M channels (IC50 = 10.1 ± 2.4 μmol/L). D01 also reduces the immobility duration in the mouse FST and TST assays in a dose-dependent manner without a stimulatory effect on locomotion. Intragastric administrations of D01 (20 and 40 mg/kg) can significantly shorten the immobility time in a mouse model of chronic restraint stress (CRS)-induced depression-like behavior. Additionally, D01 dose-dependently improves the cognitive deficit induced by CRS in Morris water maze test and increases the exploration time with novel objects in normal or scopolamine-induced cognitive deficits in mice, but not fluoxetine. Furthermore, D01 reverses the long-term potentiation (LTP) inhibition induced by scopolamine. Taken together, our findings demonstrate that D01, a dual-target serotonin reuptake and M channel inhibitor, is highly effective in the treatment-resistant depression and cognitive deficits, thus holding potential for development as therapy of depression with cognitive deficits.

Abstract Background Several studies have proposed grading systems for risk stratification of early‐stage lung adenocarcinoma based on histological patterns. However, the reproducibility of these systems is poor in clinical practice, indicating the need to develop a new grading system which is easy to apply and has high accuracy in prognostic stratification of patients. Methods Patients with stage I invasive nonmucinous lung adenocarcinoma were retrospectively collected from pathology archives between 2009 and 2016. The patients were divided into a training and validation set at a 6:4 ratio. Histological features associated with patient outcomes (overall survival [OS] and progression‐free survival [PFS]) identified in the training set were used to construct a new grading system. The newly proposed system was validated using the validation set. Survival differences between subgroups were assessed using the log‐rank test. The prognostic performance of the novel grading system was compared with two previously proposed systems using the concordance index. Results A total of 539 patients were included in this study. Using a multioutcome decision tree model, four pathological factors, including the presence of tumor spread through air space (STAS) and the percentage of lepidic, micropapillary and solid subtype components, were selected for the proposed grading system. Patients were accordingly classified into three groups: low, medium, and high risk. The high‐risk group showed a 5‐year OS of 52.4% compared to 89.9% and 97.5% in the medium and low‐risk groups, respectively. The 5‐year PFS of patients in the high‐risk group was 38.1% compared to 61.7% and 90.9% in the medium and low‐risk groups, respectively. Similar results were observed in the subgroup analysis. Additionally, our proposed grading system provided superior prognostic stratification compared to the other two systems with a higher concordance index. Conclusion The newly proposed grading system based on four pathological factors (presence of STAS, and percentage of lepidic, micropapillary, and solid subtypes) exhibits high accuracy and good reproducibility in the prognostic stratification of stage I lung adenocarcinoma patients.

Background Superior mesenteric artery syndrome (SMAS) is a rare condition, for which laparoscopic surgery was successfully performed safely and with long-term efficacy.Methods This single center retrospective clinical study comprised 66 patients with SMAS, surgically treated between January 2010 and January 2020, who were allocated to three different surgical groups according to their medical history and symptoms (Laparoscopic duodenojejunostomy, n = 35; Gastrojejunostomy, n = 16; Duodenojejunostomy plus gastrojejunostomy, n = 15). Patient demographics, surgical data and postoperative outcomes were retrieved from the medical records.Results All operations were successfully completed laparoscopically, and with a median follow-up of 65 months, the overall symptom score was significantly reduced from 32 to 8 (p

BackgroundDiffuse alveolar hemorrhage (DAH) is a catastrophic clinical syndrome and one of the manifestations of pulmonary involvement in systemic lupus erythematosus (SLE), which is characterized by hemoptysis, diffuse pulmonary infiltrates, and respiratory failure. However, the treatment options for DAH remain limited, and DAH-related studies are needed to explore more effective therapeutic directions for better disease management and improved prognosis.MethodsThis study utilized the pristane-induced DAH murine model to mimic the pathological process of DAH in patients with SLE. Proteomic analysis was conducted to detect differentially expressed proteins (DEPs) in the plasma of surviving and non-surviving mice, followed by an analysis of biological functions and pathways. The most significant DEP was then confirmed in the plasma of SLE patients with or without DAH and DAH murine model with or without fatal outcomes. Finally, the therapeutic value of haptoglobin (Hp) replacement was validated in a DAH murine model through lung histopathology, RT-qPCR, and survival analysis.ResultsThis study identified 178 DEPs, with 118 upregulated and 60 downregulated DEPs in the non-survival group. Within a set of notable Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, complement and coagulation cascades emerged as the most prominent pathway associated with the process of DAH. Later, the most significant DEP, haptoglobin (Hp), was confirmed to exhibit a significant decrease in the plasma of individuals with SLE-DAH and DAH murine model with poor outcomes by the ELISA test. Finally, compared with the control group, the severity of DAH in the Hp treatment group was alleviated significantly, as manifested by the decreased levels of pro-inflammatory cytokines (IL-6 and TNF-α), increased levels of anti-inflammatory cytokines (IL-10 and TGF-β), and decreased mortality.ConclusionA reduction in plasma Hp levels was observed in SLE-DAH, and the replacement therapy with Hp could alleviate pulmonary hemorrhage and reduce mortality in DAH mice. This study identified Hp as a potential biomarker for its clinical diagnosis and a direction for treatment.

ABSTRACT Some lactic acid bacteria (LAB) can provide significant health benefits, which are critically important for the conservation of endangered animals, such as giant pandas. However, little is known about the diversity and culturability of LAB in the giant panda gut microbiota. To understand the roles of LAB in giant panda conservation, it is critical to culture bacterial strains of interest. In this study, we established a pipeline to culture bacterial strains using enrichment of target bacteria with different liquid media and growth conditions. Then, the strains were isolated in solid media to study their functions. Using 210 samples from the culture enrichment method and 138 culture-independent samples, we obtained 1120 amplicon sequencing variants (ASVs) belonging to Lactobacillales. Out of the 1120 ASVs, 812 ASVs from the culture enrichment approach were twofold more diverse than 336 ASVs from the culture-independent approach. Many ASVs of interest were not detected in the culture-independent approach. Using this pipeline, we isolated many relevant bacterial strains and established a giant panda gut bacteria strain collection that included strains with low-abundance in culture-independent samples and included most of the giant panda LAB described by other researchers. The strain collection consisted of 60 strains representing 35 species of 12 genera. Thus, our pipeline is powerful and provides guidance in culturing gut microbiota of interest in hosts such as the giant panda.IMPORTANCECultivation is necessary to screen strains to experimentally investigate microbial traits, and to confirm the activities of novel genes through functional characterization studies. In the long-term, such work can aid in the identification of potential health benefits conferred by bacteria and this could aid in the identification of bacterial candidate strains that can be applied as probiotics. In this study, we developed a pipeline with low-cost and user-friendly culture enrichment to reveal the diversity of LAB in giant pandas. We compared the difference between culture-independent and culture enrichment methods, screened strains of interest that produced high concentrations of short-chain fatty acids (SCFAs), and we investigated the catalog of virulence factors, antibiotic resistance, butyrate and lactate synthesis genes of the strains at a genomic level. This study will provide guidance for microbiota cultivation and a foundation for future research aiming to understand the functions of specific strains.

IntroductionExtensive research efforts have been dedicated to elucidating the intricate pathways by which gastrointestinal microbiota and their metabolites exert influence on the processes of bone formation. Nonetheless, a notable gap exists in the literature concerning a bibliometric analysis of research trends at the nexus of gastrointestinal microbiota and bone metabolism.MethodsTo address this scholarly void, the present study employs a suite of bibliometric tools including online platforms, CiteSpace and VOSviewer to scrutinize the pertinent literature in the realm of gastrointestinal microbiota and bone metabolism.Results and discussionExamination of the temporal distribution of publications spanning from 2000 to 2023 reveals a discernible upward trajectory in research output, characterized by an average annual growth rate of 19.2%. Notably, China and the United States emerge as primary contributors. Predominant among contributing institutions are Emory University, Harvard University, and the University of California. Pacifici R from Emory University contributed the most research with 15 publications. In the realm of academic journals, Nutrients emerges as the foremost publisher, followed closely by Frontiers in Microbiology and PLOS One. And PLOS One attains the highest average citations of 32.48. Analysis of highly cited papers underscores a burgeoning interest in the therapeutic potential of probiotics or probiotic blends in modulating bone metabolism by augmenting host immune responses. Notably, significant research attention has coalesced around the therapeutic interventions of probiotics, particularly Lactobacillus reuteri, in osteoporosis, as well as the role of gastrointestinal microbiota in the etiology and progression of osteoarthritis. Keyword analysis reveals prevalent terms including gut microbiota, osteoporosis, bone density, probiotics, inflammation, SCFAs, metabolism, osteoarthritis, calcium absorption, obesity, double-blind, prebiotics, mechanisms, postmenopausal women, supplementation, risk factors, oxidative stress, and immune system. Future research endeavors warrant a nuanced exploration of topics such as inflammation, obesity, SCFAs, postmenopausal osteoporosis, skeletal muscle, oxidative stress, double-blind trials, and pathogenic mechanisms. In summary, this study presents a comprehensive bibliometric analysis of global research on the interplay between gastrointestinal microbiota and bone metabolism, offering valuable insights for scholars, particularly nascent researchers, embarking on analogous investigations within this domain.

BackgroundBiliary tract cancer stands as a prevalent illness, posing significant risks to human health, where immune cells are pivotal in both its development and recovery processes. Due to the diverse functionalities exhibited by different immune cell phenotypes within the organism, and the relatively limited research on their relationship with biliary tract cancer, this study employed Mendelian randomization (MR) to explore their potential association, thereby aiding in a better understanding of the causal link between immune cell phenotypes and biliary tract cancer.MethodsIn this study, the causative association of 731 immunophenotype with biliary tract cancer was established using publicly accessible genome-wide association study (GWAS) genetic data through two-sample MR analysis. Sensitivity analyses assess horizontal pleiotropy and heterogeneity of the study findings.ResultsAmong the 731 immunophenotypes examined, a total of 26 immune cell phenotypes were found to exhibit positive results, indicating a significant association with the risk of biliary tract cancer. We confirmed that among these 26 types of immune cells, there are primarily 13 types of B cells; three types of classical dendritic cells (CDCs), including CD80 on myeloid DC, HLA DR on myeloid DC, and Myeloid DC %DC; one type of mature stage T cell,CD4RA on TD CD4+; six types of regulatory T cells; and three types of myeloid cells.

Hydatid cysts of the spleen are rare. Our report details a case wherein an 8-year-old boy with a ruptured splenic hydatid cyst suffered ongoing abdominal pain and shock. Computed Tomography (CT) imaging showed an irregular cyst at the spleen's lower edge with a “floating membranes” sign. Emergency surgery was performed to remove the hydatid cyst and repair the ruptured spleen. During follow-up, the patient was treated with Albendazole orally for 12 months.

Dimension reduction is an effective method for system’s resilience analysis. In this paper, we investigate the effect of network structure on the accuracy of resilience dimension reduction. First, we introduce the resilience dimension reduction method and define the evaluation indicator of the resilience dimension reduction method. Then, by adjusting node connections, preferential connection mechanisms, and connection probabilities, we generate artificial networks, small-world networks and social networks with tunable assortativity coefficients, average clustering coefficients, and modularities, respectively. Experimental results for the gene regulatory dynamics show that the network structures with positive assortativity, large clustering coefficient, and significant community can enhance the accuracy of resilience dimension reduction. The result of this paper indicates that optimizing network structure can enhance the accuracy of resilience dimension reduction, which is of great significance for system resilience analysis and provides a new perspective and theoretical basis for selecting dimension reduction methods in system resilience analysis.

Unilateral Tracheobronchial foreign body (TFB) present a common clinical disease, whereas bilateral TFB is a rare and acute condition associated with high mortality rates. This case study discusses a pediatric patient hospitalized due to respiratory distress following accidental ingestion of peanut kernels. A plain chest CT scan revealed obstructive emphysema in the right main bronchus and a foreign body at the opening of the left main bronchus. Surgical removal of the bilateral TFB under extracorporeal circulation resulted in a successful postoperative recovery, leading to discharge on the 9th day. A comprehensive literature search was conducted across databases including PubMed, Web of Science, EMBASE, Cochrane Library, and CNKI, spanning publications from January 2014 to October 2023, utilizing keywords “bronchial foreign body” and “Peanut”. After deduplication and relevance screening, 9 pertinent literature sources were included. The objective of this study is to enhance clinical practitioners' understanding of TFB management and improve diagnostic and treatment capabilities through analysis of age of onset, clinical manifestations, diagnosis, and treatment approaches in critically ill pediatric patients.

Background: DIP2B is related to cancer progression. This study investigated the roles and pathways of DIP2B in lung adenocarcinoma (LUAD). Methods: DIP2B expression and the relationship between survival time of cancer patients and DIP2B expression were analyzed. The relationship between DIP2B expression and survival time in LUAD patients was evaluated by a meta-analysis. Cox and survival analyses were used to evaluate the prognostic factors and construct a prognostic nomogram. The mechanisms and effects of DIP2B and the relationship between DIP2B expression and the immune microenvironment were investigated using bioinformatics, CCK-8, western blotting, and transwell experiments. Results: DIP2B was overexpressed in LUAD tissues. DIP2B overexpression was associated with shorter prognosis and was an unfavorable risk factor for prognosis in LUAD patients. DIP2B co-expressed genes were involved in cell division, DNA repair, cell cycle, and others. Inhibition of DIP2B expression could downregulate the proliferation, migration, and invasion of LUAD A549 and H1299 cells, which was related to the decrease in CCND1 and MMP2 protein expression. BRCA1 overexpression was associated with short prognosis, and the nomogram formed by DIP2B and BRCA1 was associated with a poor prognosis in LUAD patients. DIP2B expression correlated with immune cells (such as CD8 T cells, Tcm, and iDCs) and cell markers. Conclusion: DIP2B is a potential biomarker of poor prognosis and the immune microenvironment in LUAD. Inhibition of DIP2B expression downregulated cancer cell proliferation, migration, and invasion, which might be related to the decrease in CCND1 and MMP2 protein expression. DIP2B-related nomograms might be useful tools for predicting the prognosis of LUAD patients.

Abstract Background Hematopoietic stem cell transplantation (HSCT) was associated with potentially life-threatening complications. Among patients supported by extracorporeal membrane oxygenation (ECMO), those who underwent HSCT had a worse prognosis than those who did not. Advances in HSCT and critical care management have improved the prognosis of ECMO-supported HSCT patients. Case The patient in the remission stage of lymphoma after 22 months of allogeneic hematopoietic stem cell transplantation, suffered from ARDS, severe neutropenia, thrombocytopenia, and long-term COVID-19. We evaluated the benefits and risks of ECMO for the patient, including the possibility of being free from ECMO, the status of malignancy, the interval from HSCT to ARDS, the function of the graft, the amount of organ failure, and the comorbidities. ECMO was ultimately used to save his life. Conclusions We did not advocate for the general use of ECMO in HSCT patients and we believed that highly selected patients, with well-controlled tumors, few comorbidities, and fewer risk factors for death, tended to benefit from ECMO with well ICU management.

Abstract. Background:. A phase II trial on recombinant human tenecteplase tissue-type plasminogen activator (rhTNK-tPA) has previously shown its preliminary efficacy in ST elevation myocardial infarction (STEMI) patients. This study was designed as a pivotal postmarketing trial to compare its efficacy and safety with rrecombinant human tissue-type plasminogen activator alteplase (rt-PA) in Chinese patients with STEMI. Methods:. In this multicenter, randomized, open-label, non-inferiority trial, patients with acute STEMI were randomly assigned (1:1) to receive an intravenous bolus of 16 mg rhTNK-tPA or an intravenous bolus of 8 mg rt-PA followed by an infusion of 42 mg in 90 min. The primary endpoint was recanalization defined by thrombolysis in myocardial infarction (TIMI) flow grade 2 or 3. The secondary endpoint was clinically justified recanalization. Other endpoints included 30-day major adverse cardiovascular and cerebrovascular events (MACCEs) and safety endpoints. Results:. From July 2016 to September 2019, 767 eligible patients were randomly assigned to receive rhTNK-tPA (n = 384) or rt-PA (n = 383). Among them, 369 patients had coronary angiography data on TIMI flow, and 711 patients had data on clinically justified recanalization. Both used a -15% difference as the non-inferiority efficacy margin. In comparison to rt-PA, both the proportion of patients with TIMI grade 2 or 3 flow (78.3% [148/189] vs. 81.7% [147/180]; differences: -3.4%; 95% confidence interval [CI]: -11.5%, 4.8%) and clinically justified recanalization (85.4% [305/357] vs. 85.9% [304/354]; difference: -0.5%; 95% CI: -5.6%, 4.7%) in the rhTNK-tPA group were non-inferior. The occurrence of 30-day MACCEs (10.2% [39/384] vs. 11.0% [42/383]; hazard ratio: 0.96; 95% CI: 0.61, 1.50) did not differ significantly between groups. No safety outcomes significantly differed between groups. Conclusion:. rhTNK-tPA was non-inferior to rt-PA in the effect of improving recanalization of the infarct-related artery, a validated surrogate of clinical outcomes, among Chinese patients with acute STEMI. Trial registration:. www.ClinicalTrials.gov (No. NCT02835534).

Bipolar blocking and commutation failure in the renewable energy transmission system through ultra-high voltage direct current will produce significant temporary overvoltage. This paper analyzes the physical process of sending end grid overvoltage caused by two types of DC faults and establishes a DC overvoltage model considering renewable energy sources. According to characteristics of the sending end grid, the influence of the system equivalent impedance, the proportion of renewable energy output, the active and reactive power coefficients of the renewable energy sources during the low voltage ride through process on the overvoltage is analyzed respectively, and the relationship between the proportion of renewable energy output and the short-circuit ratio under the overvoltage constraint is constructed. The validity and practicality of the model and analysis method proposed in this paper are verified by combining the typical transmission system at the sending end of the actual power grid and regional power grid systems.

Due to stringent aircraft safety requirements and the high cost of experiments, there is a scarcity of failure samples, which creates a gap between existing diagnostic models and practical applications. To address this issue, we have developed a small-sample civil aircraft fault diagnosis method. This method combines a meta-learning approach to tackle data imbalance with a channel attention mechanism to enhance feature extraction efficiency. Specifically, our approach integrates the advantages of meta-learning and attention regularization, effectively addressing both the imbalance in training sample distribution and the need for human interaction to enhance feature representation. We then evaluated five data imbalances and introduced a fault diagnosis algorithm based on a one-dimensional convolutional network, which has been successfully applied to solve small sample yield tasks in two datasets. Additionally, we provide baseline accuracy under the same conditions for comprehensive comparison and reference. Through extensive experiments, our method achieves competitive performance and demonstrates its superiority in solving imbalanced distribution experimental configurations.

Whale optimization algorithm (WOA) is a swarm-based optimization algorithm with exceptional performance and significant originality. In this study, a novel variant of WOA called nonlinear adaptive weight-based mutated WOA (NAWMWOA) is proposed to overcome the shortcomings of original WOA such as easily falling into local optimum and slow convergence speed. In detail, the proposed NAWMWOA includes three novel strategies as comparing with original WOA. Firstly, a nonlinear convergence factor is embedded into the original WOA to balance exploration and exploitation ability. The second improvement is an adaptive weight strategy, which can enhance the exploratory searching trends and improve the solution accuracy. Moreover, the thirdly proposed hybrid mutation strategy has the function of increasing the accuracy and jumping out of the local optimum. The combination of the three strategies significantly improve convergence efficiency and search accuracy of original WOA. To verify the remarkable performance of the proposed NAWMWOA, a series of illustrious WOA variants and state-of-the-art intelligent algorithms is compared with the NAWMWOA on 37 benchmark functions and three typical engineering problems. The details of experimental and statistics results illustrate that the presented NAWMWOA has higher convergence efficiency and better solution accuracy. As a conclusion, the proposed NAWMWOA is a competitive and outstanding algorithm that can effectively solve optimization problems in practical engineering.

The scarcity and sharing nature of the electromagnetic spectrum present a significant challenge to the stable operation of synthetic aperture radar (SAR) systems, as they are susceptible to interference from other devices operating in the same frequency band, known as radio-frequency interference (RFI). In this article, we propose an effective semiparametric method for suppressing multiple RFI, named the iterative matrix decomposition algorithm based on the Frobenius norm (FIMD), we employ CUR decomposition and a soft-threshold algorithm to update low-rank and sparse matrices within an alternate projection framework. It is observed that there exist distinct distribution characteristics between interference points and strong scattering points in the echo domain. We propose a novel and effective signal protection method, which effectively mitigates the risk of strong scattering points being misidentified as interference signals and subsequently eliminated. In addition, we utilize random singular value decomposition instead of traditional singular value decomposition to enhance convergence speed of. Simulation results demonstrate that our proposed method exhibits superior suppression capability and robustness under varying-to-interference ratio conditions and it can be applied to L0-raw products and L1-SLC products.

Abstract Background Breast cancer is the most common malignant tumor in the world. Intraoperative frozen section of sentinel lymph nodes is an important basis for determining whether axillary lymph node dissection is required for breast cancer surgery. We propose an RRCART model based on a deep-learning network to identify metastases in 2362 frozen sections and count the wrongly identified sections and the associated reasons. The purpose is to summarize the factors that affect the accuracy of the artificial intelligence model and propose corresponding solutions. Methods We took the pathological diagnosis of senior pathologists as the gold standard and identified errors. The pathologists and artificial intelligence engineers jointly read the images and heatmaps to determine the locations of the identified errors on sections, and the pathologists found the reasons (false reasons) for the errors. Through NVivo 12 Plus, qualitative analysis of word frequency analysis and nodal analysis was performed on the error reasons, and the top-down error reason framework of “artificial intelligence RRCART model to identify frozen sections of breast cancer lymph nodes” was constructed based on the importance of false reasons. Results There were 101 incorrectly identified sections in 2362 slides, including 42 false negatives and 59 false positives. Through NVivo 12 Plus software, the error causes were node-coded, and finally, 2 parent nodes (high-frequency error, low-frequency error) and 5 child nodes (section quality, normal lymph node structure, secondary reaction of lymph nodes, micrometastasis, and special growth pattern of tumor) were obtained; among them, the error of highest frequency was that caused by normal lymph node structure, with a total of 45 cases (44.55%), followed by micrometastasis, which occurred in 30 cases (29.70%). Conclusions The causes of identification errors in examination of sentinel lymph node frozen sections by artificial intelligence are, in descending order of influence, normal lymph node structure, micrometastases, section quality, special tumor growth patterns and secondary lymph node reactions. In this study, by constructing an artificial intelligence model to identify the error causes of frozen sections of lymph nodes in breast cancer and by analyzing the model in detail, we found that poor quality of slices was the preproblem of many identification errors, which can lead to other errors, such as unclear recognition of lymph node structure by computer. Therefore, we believe that the process of artificial intelligence pathological diagnosis should be optimized, and the quality control of the pathological sections included in the artificial intelligence reading should be carried out first to exclude the influence of poor section quality on the computer model. For cases of micrometastasis, we suggest that by differentiating slices into high- and low-confidence groups, low-confidence micrometastatic slices can be separated for manual identification. The normal lymph node structure can be improved by adding samples and training the model in a targeted manner.

Highlights An efficient moist-electric generator with ultra-fast electric response to moisture is achieved by triggering Grotthuss protons hopping in the moisture-electric–moisture-sensitive heterostructure. The moist-electric generator produces a quick response (0.435 s), an unprecedented ultra-fast response rate of 972.4 mV s−1 to alternating moisture stimulation and stable output for 8 h. An obstructive sleep apnea hypoventilation syndrome diagnostic system based on a moist-electric generator was developed to monitor hypopnea and apnea in real time and successfully diagnose them with early warning.