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Abstract The brain’s white matter connections are thought to provide the structural basis for its functional connections between distant brain regions but how our brain selects the best structural routes for functional communications remains poorly understood. In this study, we propose a Unified Structural and Functional Connectivity (USFC) model and use an “economical assumption” to create the brain’s first “traffic map” reflecting how frequently each segment of the brain structural connection is used to achieve the global functional communication system. The resulting USFC map highlights regions in the subcortical, default-mode, and salience networks as the most heavily traversed nodes and a midline frontal-caudate-thalamus-posterior cingulate-visual cortex corridor as the backbone of the whole brain connectivity system. Our results further revealed a striking negative association between structural and functional connectivity strengths in routes supporting negative functional connections, as well as significantly higher efficiency metrics and better predictive performance for cognition in the USFC connectome when compared to structural and functional ones alone. Overall, the proposed USFC model opens up a new window for integrated brain connectome modeling and provides a major leap forward in brain mapping efforts for a better understanding of the brain’s fundamental communication mechanisms.

Abstract This study investigated the role of mitochondrial dynamics in postoperative cognitive dysfunction (POCD) and assessed the therapeutic potential of mitochondrial modulation, particularly through the inhibition of dynamin-related protein 1 (DRP1) with Mdivi-1. Our findings indicated that DRP1 inhibition substantially mitigated neuroinflammation mediated by microglial cells, contributing to improved cognitive function in POCD models. The administration of Mdivi-1 led to a notable decrease in mitochondrial fission, reduced reactive oxygen species (ROS) production, and stabilization of mitochondrial membrane potential, all of which correlate with diminished neuroinflammation, as evidenced by lower NOD-like receptor family pyrin domain containing 3 (NLRP3)/ interleukin-1β (IL-1β) expression in microglial cells. Importantly, Mdivi-1 treatment was also found to enhance synaptic plasticity, increasing synaptic spine density in the hippocampal region of POCD mice. This improvement in mitochondrial health and synaptic integrity was paralleled by enhanced cognitive performance, as demonstrated in Y-maze tests. These results underscored the critical role of mitochondrial dynamics in the pathophysiology of POCD and suggested that targeting mitochondrial dysfunction, specifically through DRP1 inhibition, could be an effective approach for POCD treatment.

Abstract Timely and effective interventions after tracheal mucosal injury are lack in clinical practices, which elevate the risks of airway infection, tracheal cartilage deterioration, and even asphyxiated death. Herein, we proposed a biomaterial-based strategy for the repair of injured tracheal mucosal based on a copper hydrogen phosphate nanosheets (CuHP NSs) functionalized commercial hydrogel (polyethylene glycol disuccinimidyl succinate-human serum albumin, PH). Such CuHP/PH hydrogel achieved favorable injectability, stable gelation, and excellent adhesiveness within the tracheal lumen. Moreover, CuHP NSs within the CuHP/PH hydrogel effectively stimulate the proliferation and migration of endothelial/epithelial cells, enhancing angiogenesis and demonstrating excellent tissue regenerative potential. Additionally, it exhibited significant inhibitory effects on both bacteria and bacterial biofilms. More importantly, when injected injured site of tracheal mucosa under fiberoptic bronchoscopy guidance, our results demonstrated CuHP/PH hydrogel adhered tightly to the tracheal mucosa. The therapeutic effects of the CuHP/PH hydrogel were further confirmed, which significantly improved survival rates, vascular and mucosal regeneration, reduced occurrences of intraluminal infections, tracheal stenosis, and cartilage damage complications. This research presents an initial proposition outlining a strategy employing biomaterials to mitigate tracheal mucosal injury, offering novel perspectives on the treatment of mucosal injuries and other tracheal diseases.

The genus Micryletta is widely distributed in South China and Southeast Asia. Although significant progress has been made in the diversity and taxonomy of this genus over the past few years, the distribution range and taxonomy of some species still remain controversial, especially in M. inornata sensu lato. Consequently, limitations at national borders have resulted in a lack of comparative research on species from different countries. To resolve the classification dispute, assess species diversity, and determine the distribution range of Micryletta, a series of specimens were collected from the Yunnan Province of China and Thailand during herpetological surveys from 2009 to 2020. Subsequent analyses based on morphological and molecular data revealed a distinct and previously unknown lineage from western Thailand, which we formally describe as a new species. Furthermore, our study confirms that M. ‘inornata’, previously known from Mengla, Yunnan, was actually M. menglienica, and further extends its distribution range to Thailand and Laos. In addition, our findings extend the latitudinal distribution of M. inornata and M. subaraji northward into southern Thailand. Notably, this study brings the total number of known species in the genus Micryletta from 13 to 14, with the count rising from three to six species in Thailand and from one to three in Laos. Our study further confirms that species diversity within the genus Micryletta is underestimated and emphasizes the important role that international collaborations play in taxonomy. Intensifying field surveys in other regions (e.g., Myanmar, Vietnam, and Guangxi of China) will be extremely necessary in the future to clarify any taxonomic questions and reevaluate the distribution range of these species.

Abstract Background Respiratory infectious diseases have the highest incidence among infectious diseases worldwide. Currently, global monitoring of respiratory pathogens primarily focuses on influenza and coronaviruses. This study included influenza and other common respiratory pathogens to establish a local respiratory pathogen spectrum. We investigated and analyzed the co-infection patterns of these pathogens and explored the impact of lifting non-pharmaceutical interventions (NPIs) on the transmission of influenza and other respiratory pathogens. Additionally, we used a predictive model for infectious diseases, utilizing the commonly used An autoregressive comprehensive moving average model (ARIMA), which can effectively forecast disease incidence. Methods From June 2023 to February 2024, we collected influenza-like illness (ILI) cases weekly from the community in Xuanwu District, Nanjing, and obtained 2046 samples. We established a spectrum of respiratory pathogens in Nanjing and analysed the age distribution and clinical symptom distribution of various pathogens. We compared age, gender, symptom counts, and viral loads between individuals with co-infections and those with single infections. An autoregressive comprehensive moving average model (ARIMA) was constructed to predict the incidence of respiratory infectious diseases. Results Among 2046 samples, the total detection rate of respiratory pathogen nucleic acids was 53.37% (1092/2046), with influenza A virus 479 cases (23.41%), influenza B virus 224 cases (10.95%), and HCoV 95 cases (4.64%) being predominant. Some pathogens were statistically significant in age and number of symptoms. The positive rate of mixed infections was 6.11% (125/2046). There was no significant difference in age or number of symptoms between co-infection and simple infection. After multiple iterative analyses, an ARIMA model (0,1,4), (0,0,0) was established as the optimal model, with an R2 value of 0.930, indicating good predictive performance. Conclusions The spectrum of respiratory pathogens in Nanjing, Jiangsu Province, was complex in the past. The primary age groups of different viruses were different, causing various symptoms, and the co-infection of viruses did not correlate with the age and gender of patients. The ARIMA model estimated future incidence, which plateaued in subsequent months.

Abstract Background With the fast-paced advancements of robot technology, human–robot interaction (HRI) has become increasingly popular and complex, and self-efficacy in HRI has received extensive attention. Despite its popularity, this topic remains understudied in China. Objective In order to provide a psychometrically sound instrument in China, this study aimed to translate and validate the Self-Efficacy in Human–Robot Interaction Scale (SE-HRI) in two Chinese adult samples (N1 = 300, N2 = 500). Methods The data was analyzed by SPSS 26.0 and Amos 24.0. Item analysis and exploratory factor analysis were conducted using Sample 1 data. Confirmatory factor analysis, criterion-related validity analysis, and reliability analysis were then performed using Sample 2 data. Results The results revealed that the Chinese SE-HRI scale consisted of 13 items in a two-factor model, suggesting a good model fit. Moreover, general self-efficacy and willingness to accept the use of artificial intelligence (AI) were both positively correlated with self-efficacy in HRI, while negative attitudes toward robots showed an inverse correlation, proving the Chinese SE-HRI scale exhibited excellent criterion-related validity. Conclusion The Chinese SE-HRI scale is a reliable assessment tool for evaluating self-efficacy in HRI in China. The study discussed implications and limitations, and suggested future directions.

Abstract Background Recent studies have highlighted type 2 diabetes (T2DM) as a significant risk factor for the development of metabolic dysfunction-associated fatty liver disease (MAFLD). This investigation aimed to assess electroacupuncture’s (EA) impact on liver morphology and function in T2DM rats, furnishing experimental substantiation for its potential to stall MAFLD progression in T2DM. Methods T2DM rats were induced by a high-fat diet and a single intraperitoneal injection of streptozotocin, and then randomly assigned to five groups: the T2DM group, the electroacupuncture group, the metformin group, combination group of electroacupuncture and metformin, combination group of electroacupuncture and Compound C. The control group received a standard diet alongside intraperitoneal citric acid - sodium citrate solution injections. After a 6-week intervention, the effects of each group on fasting blood glucose, lipids, liver function, morphology, lipid droplet infiltration, and fibrosis were evaluated. Techniques including Western blotting, qPCR, immunohistochemistry, and immunofluorescence were employed to gauge the expression of key molecules in AMPK-associated glycolipid metabolism, insulin signaling, autophagy, and fibrosis pathways. Additionally, transmission electron microscopy facilitated the observation of liver autophagy, lipid droplets, and fibrosis. Results Our studies indicated that hyperglycemia, hyperlipidemia and IR promoted lipid accumulation, pathological and functional damage, and resulting in hepatic steatosis and fibrosis. Meanwhile, EA enhanced the activation of AMPK, which in turn improved glycolipid metabolism and autophagy through promoting the expression of PPARα/CPT1A and AMPK/mTOR pathway, inhibiting the expression of SREBP1c, PGC-1α/PCK2 and TGFβ1/Smad2/3 signaling pathway, ultimately exerting its effect on ameliorating hepatic steatosis and fibrosis in T2DM rats. The above effects of EA were consistent with metformin. The combination of EA and metformin had significant advantages in increasing hepatic AMPK expression, improving liver morphology, lipid droplet infiltration, fibrosis, and reducing serum ALT levels. In addition, the ameliorating effects of EA on the progression of MAFLD in T2DM rats were partly disrupted by Compound C, an inhibitor of AMPK. Conclusions EA upregulated hepatic AMPK expression, curtailing gluconeogenesis and lipogenesis while boosting fatty acid oxidation and autophagy levels. Consequently, it mitigated blood glucose, lipids, and insulin resistance in T2DM rats, thus impeding liver steatosis and fibrosis progression and retarding MAFLD advancement.

This paper presents a novel approach that simultaneously enables photovoltaic (PV) inversion and flexible arc suppression during single-phase grounding faults. Inverters compensate for ground currents through an arc-elimination function, while outputting a PV direct current (DC) power supply. This method effectively reduces the residual grounding current. To reduce the dependence of the arc-suppression performance on accurate compensation current-injection models, an adaptive fuzzy neural network imitating a sliding mode controller was designed. An online adaptive adjustment law for network parameters was developed, based on the Lyapunov stability theorem, to improve the robustness of the inverter to fault and connection locations. Furthermore, a new arc-suppression control exit strategy is proposed to allow a zero- sequence voltage amplitude to quickly and smoothly track a target value by controlling the nonlinear decrease in current and reducing the regulation time. Simulation results showed that the proposed method can effectively achieve fast arc suppression and reduce the fault impact current in single-phase grounding faults. Compared to other methods, the proposed method can generate a lower residual grounding current and maintain good arc-suppression performance under different transition resistances and fault locations.

Abstract The freezing and thawing cycle is one of the primary causes of damage and instability to buildings in seasonal frost regions. During this process, the mechanical properties of soil are affected, leading to settlement, cracking, or deformation of infrastructure. Mitigating or reducing the occurrence of building frost damage in seasonal frost regions has become an important subject of study. Freeze–thaw (F–T) action will influence the distribution of moisture inside the reinforced soil and change the strength of thawing soil, which is closely related to the main influencing factors, such as initial moisture content, compaction degree, reinforced spacing, number of freeze–thaw cycles (FTC), freezing temperature, and effective vertical stress. Cohesion is an important index to determine the shear strength of clay, which is important to analyze the change in cohesion after F–T. Meanwhile, cohesion is closely related to soil moisture content. This study conducted orthogonal experiments on these primary influencing factors (6 factors at 5 levels) through FTC tests, triaxial tests, and moisture content tests to determine the undrained cohesion and moisture content of the clay after FTC, thereby establishing the influence of reinforcement on soil strength under freeze–thaw conditions. Based on the experimental results, SPSS software was used to fit the regression equations of undrained cohesion and moisture content expressed by the main influencing factors at different heights of the clay. Optimization options for the main influencing factors were obtained with Matlab software when the highest undrained cohesion values 6.8, 10.6, 8.9 kPa and lowest moisture content values 24.0%, 24.3%, 26.2% appeared in upper, middle and lower parts of the testing clay structure respectively, in conditions of − 15 °C freezing temperature and 5 times FTC. And determined the optimal combinations of moisture content, reinforcement spacing, compaction density, and vertical load at different heights. Decreasing reinforced spacing in silty clay was beneficial for liquid underwater seepage after F–T. The redistribution of internal moisture in the soil sample strengthened its undrained cohesion, thereby increasing the soil's shear strength. Comparing reinforcement conditions at different locations, it was found that when there were 3 layers of reinforcement with a spacing of 150 mm between them, this spacing was optimal. It played a significant role in improving the soil's shear strength and enhancing its bearing capacity. For reinforced clay itself, the order of the main factors influencing the undrained cohesion of soil after F–T, from high to low, was initial moisture content, reinforced spacing, and compaction degree.

Abstract Fungal diseases are the main factors affecting the quality and production of vegetables. Rapid and accurate detection of pathogenic spores is of great practical significance for early prediction and prevention of diseases. However, there are some problems with microscopic images collected in the natural environment, such as complex backgrounds, more disturbing materials, small size of spores, and various forms. Therefore, this study proposed an improved detection method of GCS-YOLOv8 (Global context and CARFAE and Small detector-optimized YOLOv8), effectively improving the detection accuracy of small-target pathogen spores in natural scenes. Firstly, by adding a small target detection layer in the network, the network’s sensitivity to small targets is enhanced, and the problem of low detection accuracy of the small target is effectively improved. Secondly, Global Context attention is introduced in Backbone to optimize the CSPDarknet53 to 2-Stage FPN (C2F) module and model global context information. At the same time, the feature up-sampling module Content-Aware Reassembly of Features (CARAFE) was introduced into Neck to enhance the ability of the network to extract spore features in natural scenes further. Finally, we used an Explainable Artificial Intelligence (XAI) approach to interpret the model’s predictions. The experimental results showed that the improved GCS-YOLOv8 model could detect the spores of the three fungi with an accuracy of 0.926 and a model size of 22.8 MB, which was significantly superior to the existing model and showed good robustness under different brightness conditions. The test on the microscopic images of the infection structure of cucumber down mildew also proved that the model had good generalization. Therefore, this study realized the accurate detection of pathogen spores in natural scenes and provided feasible technical support for early predicting and preventing fungal diseases.

Abstract Slot structure is the equilibrium result of market demand side and slot resource supply side, while slot parameters reflect the operational support capacity of the aviation system. Time parameters reflect the operational support capability of the aviation system. Time structure should not only reflect changes in market demand, but also meet the constraints of operational efficiency. Constructing a reasonable 18–24 h timetable profile for busy airports that meets normal expectations for declared capacity and seasonal scheduling is a challenge in civil aviation slot management. This study utilizes historical data on airport flights and weather conditions to establish a regression prediction model for the time structure using K-means clustering and partial least squares regression. Additionally, ensemble learning is employed to forecast flight delay levels. The findings demonstrate that random forest yields favorable results in regression and prediction tasks, allowing for the integration of upper (good weather) and lower (severse weather) limits of the time profile with delay predictions as time parameter intervals. Consequently, the flights falling within these intervals achieve an average delay level of less than 15 min which meets the expectations of normal flight.

Seed coat color affects the appearance and commodity quality of mung beans (Vigna radiata L.). The substances that affect mung bean seed coat color are mainly flavonoids, which have important medicinal value. Mapping the seed coat color gene in mung beans would facilitate the development of new varieties and improve their value. In this study, an F2 mapping population consisting of 546 plants was constructed using Jilv9 (black seed coat) and BIS9805 (green seed coat). Using bulk segregated analysis (BSA) sequencing and kompetitive allele-specific PCR (KASP) markers, the candidate region related to seed coat color was finally narrowed to 0.66 Mb on chromosome (Chr.) 4 and included eight candidate genes. Combined transcriptome and metabolome analyses showed that three of the eight candidate genes (LOC106758748, LOC106758747, and LOC106759075) were differentially expressed, which may have caused the differences in flavonoid metabolite content between Jilv9 and BIS9805. These findings can provide a research basis for cloning the genes related to seed coat color and accelerate molecular marker-assisted selection breeding in mung beans.

Abstract Backgrounds Fat infiltration of skeletal muscle has been recognized as a common feature of many degenerative muscle disorders. Retinol binding protein 4 (RBP4) is an adipokine that has been demonstrated to be correlated with the presence and severity of sarcopenia in the elderly. However, the exact role and the underlying mechanism of RBP4 in muscle atrophy remains unclear. Methods Denervation‐induced muscle atrophy model was constructed in wild‐type and RBP4 knockout mice. To modify the expression of RBP4, mice were received intramuscular injection of retinol‐free RBP4 (apo‐RBP4), retinol‐bound RBP4 (holo‐RBP4) or oral gavage of RBP4 inhibitor A1120. Holo‐RBP4‐stimulated C2C12 myotubes were treated with siRNAs or specific inhibitors targeting signalling receptor and transporter of retinol 6 (STRA6)/Janus kinase 2 (JAK2)/Signal transducer and activator of transcription 3 (STAT3) pathway. Fat accumulation, myofibre cross‐sectional area, myotube diameter and the expression of muscle atrophy markers and myogenesis markers were analysed. Results The expression levels of RBP4 in skeletal muscles were significantly up‐regulated more than 2‐fold from 7 days and sustained for 28 days after denervation. Immunofluorescence analysis indicated that increased RBP4 was localized in the infiltrated fatty region in denervated skeletal muscles. Knockout of RBP4 alleviated denervation‐induced fatty infiltration and muscle atrophy together with decreased expression of atrophy marker Atrogin‐1 and MuRF1 as well as increased expression of myogenesis regulators MyoD and MyoG. By contrast, injection of retinol‐bound holo‐RBP4 aggregated denervation‐induced ectopic fat accumulation and muscle atrophy. Consistently, holo‐RBP4 stimulation also had a dose‐dependent effect on the reduction of C2C12 myotube diameter and myofibre cross‐sectional area, as well as on the increase of Atrogin‐1and MuRF1 expression and decrease of MyoD and MyoG expression. Mechanistically, holo‐RBP4 treatment increased the expression of its membrane receptor STRA6 (>3‐fold) and promoted the phosphorylation of downstream JAK2 and STAT3. Inhibition of STRA6/JAK2/STAT3 pathway either by specific siRNAs or inhibitors could decrease the expression of Atrogin‐1 and MuRF1 (>50%) and decrease the expression of MyoD and MyoG (>3‐fold) in holo‐RBP4‐treated C2C12 myotube. RBP4 specific pharmacological antagonist A1120 significantly inhibited the activation of STRA6/JAK2/STAT3 pathway, ameliorated ectopic fat infiltration and protected against denervation‐induced muscle atrophy (30% increased myofibre cross‐sectional area) in mice. Conclusions In conclusion, our data reveal that RBP4 promotes fat infiltration and muscle atrophy through a STRA6‐dependent and JAK2/STAT3 pathway‐mediated mechanism in denervated skeletal muscle. Our results suggest that lowering RBP4 levels might serve as a promising therapeutic approach for prevention and treatment of muscle atrophy.

Abstract Background The Health and Medical Assistance Program for Poverty Alleviation is part of China’s targeted poverty elimination strategy, which aims to protect poor people’s right to health and prevent them from becoming trapped in or returning to poverty because of illness. Many tasks have been defined in this program, including raising the medical insurance level, providing a triage system, improving medical and health services, and enhancing people’s health. One pivotal aspect of this initiative involves equitable health resource allocation, a key measure aimed at bolstering medical and health services. This study aimed to analyze and compare health resource allocations in different counties in Northwest China after the implementation of the program. Methods The Gini coefficient quantifies the level of distributional equality, the Theil index assesses the sources of inequality, and the Health Resource Agglomeration Degree gauges the accessibility of health resources. Results 1) The health resource allocation distributed based on population(Gini Coefficient 0.35) among counties in Northwest China. 2) The contribution rate within non-impoverished counties is higher than that of impoverished counties, which means the inequality within non-impoverished counties. 3) The allocation of beds in medical institutions by area in non-impoverished counties was better than that in impoverished counties, and accessibility to health services for residents in non-impoverished counties was better than that in impoverished counties. Conclusion The analysis of health resource allocation among the five provinces in Northwest China revealed significant differences in equality among the five provinces in Northwest China, and the differences were mainly derived from the non-impoverished counties. Although the equality is gradually improving, the number of health resources in impoverished counties remain lower than that in non-impoverished counties.Subsequently, it is essential to ensure equitable distribution of healthcare resources while also taking into account their utilization and quality.

Abstract Visual adaptive devices have potential to simplify circuits and algorithms in machine vision systems to adapt and perceive images with varying brightness levels, which is however limited by sluggish adaptation process. Here, the avalanche tuning as feedforward inhibition in bionic two-dimensional (2D) transistor is proposed for fast and high-frequency visual adaptation behavior with microsecond-level accurate perception, the adaptation speed is over 104 times faster than that of human retina and reported bionic sensors. As light intensity changes, the bionic transistor spontaneously switches between avalanche and photoconductive effect, varying responsivity in both magnitude and sign (from 7.6 × 104 to −1 × 103 A/W), thereby achieving ultra-fast scotopic and photopic adaptation process of 108 and 268 μs, respectively. By further combining convolutional neural networks with avalanche-tuned bionic transistor, an adaptative machine vision is achieved with remarkable microsecond-level rapid adaptation capabilities and robust image recognition with over 98% precision in both dim and bright conditions.

Accelerating the exploration and development of deep ( > 1 000 m)coalbed methane (CBM) resources is an important way for the large-scale development of CBM and an important development direction in recent years. Guizhou Province is rich in CBM resources, with a large proportion of deep CBM resources. However, up to now, the geological research and exploration of deep CBM resources have not been carried out. Based on the geological background of CBM in Guizhou, this paper analyzes the geological characteristics and resource potential of deep CBM in Guizhou Province using a large number of CBM well test data. The research results show that the deep CBM resources in Guizhou are mainly distributed in many syncline units of the Liupanshui, North Guizhou and Zhina coalfields. Sedimentary differentiation and structural zoning lead to regional differences in the geological conditions of deep CBM reservoirs. The Liupanshui coalfield is characterized by “obvious overpressure, low temperature and high stress”, the Zhina coalfield is characterized by “overpressure, high temperature and low stress”, and the northern Guizhou coalfield is characterized by “overpressure, high temperature and high stress”. The permeability of deep CBM reservoir is low, and the permeability of 1 000 m deep will be generally lower than 0.1×10−15 m2. The CBM content of the coal reservoir is relatively high. The average CBM content of the middle-rank coal reservoir represented by the Liupanshui coalfield is 10.03 m3/t, and the average CBM content of the high-rank coal reservoir represented by the Zhina and Qianbei coalfields is 14.51 m3/t, and the deep supersaturation phenomenon is more obvious at 400 m. Based on the prediction model of free gas and adsorbed gas, considering the change of coal rack, it is predicted that the overall gas content in the deep part will further increase, and the supersaturation phenomenon will be more obvious, and the proportion of free gas will increase. At about 2000 m, the proportion of free gas will generally reach 10%−25%, and the proportion of free gas in medium-rank coal is higher than that in high-rank coal. On this basis, the geological resources of CBM in the key synclines of Guizhou Province with a depth of more than 2000 m are calculated. Based on the calculation results, the geological resources of CBM in Guizhou Province is 3.85 trillion m3, of which the geological resources of CBM in the depth of 1000 m reach 1.90 trillion m3, and the deep CBM resources in the Liupanshui and northern Guizhou coalfields account for a large proportion. Considering the scale and abundance of resources comprehensively, the development sequence is proposed. The Panguan-Tucheng-Zhaozihe-Jiupu'an syncline and the Gemudi syncline are the preferred development units. The above synclines are large gas fields with high abundance.

In Guizhou Province, there are many coal-bearing structural units, many layers of coal, thin thickness, and most of them are low permeability reservoirs, so it is advisable to adopt the process of “staged fracturing and combined layer drainage and production” to develop coalbed methane. Taking Banguan syncline coalbed methane well as an example, this study analyzed the fracturing effect of two vertical Wells on the basis of the scale of fracturing reconstruction, and then studied the influence of fracturing reconstruction effect on the gas and water production of coalbed methane Wells, and finally summarized the reasonable threshold of efficient fracturing construction parameters of Banguan syncline coalbed methane Wells. The results show that hydraulic fracturing is an effective way to increase permeability of low permeability reservoir, and the permeability increase multiple is closely related to the scale of fracturing reconstruction. The differences of sand addition, liquid addition and single-hole displacement per meter of coal seam between the two Wells of Banguan syncline lead to the permeability ratio of 55∶1 after fracturing reconstruction, and the permeability difference after reconstruction is large. Increasing the liquid addition, sand addition and single hole displacement per meter of coal seam is beneficial to improving the transformation effect of coal seam and gas production. It is recommended that the liquid addition per meter of coal seam should not be less than 400 m3, the sand addition per meter of coal seam should not be less than 20 m3, the fracturing construction displacement should not be less than 8 m3/min, and the single hole displacement should be controlled above 0.2 m3/min. According to the permeability of the coal seam after fracturing and reconstruction, it can be appropriate to quickly discharge and depressurize the coalbed methane Wells with good reconstruction effect. Otherwise, the intensity of discharge and production should be controlled to reduce the sensitivity damage of the reservoir caused by fast discharge and depressurization. The research results can provide technical reference for the permeability and energy improvement of low permeability coal seam in this block.

Abstract Objective The objective of the present study was to explore the correlation between the advanced lung cancer inflammation index (ALI) and in‐hospital mortality among patients diagnosed with community‐acquired pneumonia (CAP). Methods Data from the Medical Information Mart for Intensive Care‐IV database were adopted to analyze the in‐hospital mortality of ICU patients with CAP. Upon admission to the ICU, fundamental data including vital signs, critical illness scores, comorbidities, and laboratory results, were collected. The in‐hospital mortality of all CAP patients was documented. Multivariate logistic regression (MLR) models and restricted cubic spline (RCS) analysis together with subgroup analyses were conducted. Results This study includes 311 CAP individuals, involving 218 survivors as well as 93 nonsurvivors. The participants had an average age of 63.57 years, and the females accounted for approximately 45.33%. The in‐hospital mortality was documented to be 29.90%. MLR analysis found that ALI was identified as an independent predictor for in‐hospital mortality among patients with CAP solely in the Q1 group with ALI ≤ 39.38 (HR: 2.227, 95% CI: 1.026–4.831, P = 0.043). RCS analysis showed a nonlinear relationship between the ALI and in‐hospital mortality, with a turning point at 81, and on the left side of the inflection point, a negative correlation was observed between ALI and in‐hospital mortality (HR: 0.984, 95% CI: 0.975–0.994, P = 0.002). The subgroup with high blood pressure showed significant interaction with the ALI. Conclusion The present study demonstrated a nonlinear correlation of the ALI with in‐hospital mortality among individuals with CAP. Additional confirmation of these findings requires conducting larger prospective investigations.

Abstract Cryptosporidiosis is a worldwide zoonotic disease. Oxymatrine, an alkaloid extracted and isolated from the plant bitter ginseng, has been reported to have therapeutic effects on cryptosporidiosis. However, the underlying mechanism of its action remains unclear. In this study, we utilized network pharmacology and experimental validation to investigate the mechanism of oxymatrine in the treatment of cryptosporidiosis. First, the potential targets of drugs and diseases were predicted by TCMSP, Gene Cards, and other databases. Following the intersection of drug-disease targets, the DAVID database was used to implement the enrichment analysis of GO functions and KEGG pathways, and then the network diagram of "intersected target-KEGG" relationship was constructed. Autodock 4.2.6 software was used to carry out the molecular docking of core targets to drug components. Based on the establishment of a mouse model of cryptosporidiosis, the validity of the targets in the TNF/NF-κB signaling pathway was confirmed using Western blot analysis and Quantitative Rea-ltime-PCR. A total of 41 intersectional targets of oxymatrine and Cryptosporidium were generated from the results, and five core targets were screened out by network analysis, including RELA, AKT1, ESR1, TNF, and CASP3. The enrichment analysis showed that oxymatrine could regulate multiple gene targets, mediate TNF, Apoptpsis, IL-17, NF-κB and other signaling pathways. Molecular docking experiments revealed that oxymatrine was tightly bound to core targets with stable conformation. Furthermore, we found through animal experiments that oxymatrine could regulate the mRNA and protein expression of IL-6, NF-κB, and TNF-α in the intestinal tissues of post-infected mice through the TNF/NF-κB signaling pathway. Therefore, it can be concluded that oxymatrine can regulate the inflammatory factors TNF-α, NF-κB, and IL-6 through the TNF/NF-κB signaling pathway for the treatment of cryptosporidiosis. This prediction has also been validated by network pharmacology and animal experiments.

Abstract Hemangioma of infancy is the most common vascular tumor during infancy and childhood. Despite the proven efficacy of propranolol treatment, certain patients still encounter resistance or face recurrence. The need for frequent daily medication also poses challenges to patient adherence. Bleomycin (BLM) has demonstrated effectiveness against vascular anomalies, yet its use is limited by dose-related complications. Addressing this, this study proposes a novel approach for treating hemangiomas using BLM-loaded hyaluronic acid (HA)-based microneedle (MN) patches. BLM is encapsulated during the synthesis of polylactic acid (PLA) microspheres (MPs). The successful preparation of PLA MPs and MN patches is confirmed through scanning electron microscopy (SEM) images. The HA microneedles dissolve rapidly upon skin insertion, releasing BLM@PLA MPs. These MPs gradually degrade within 28 days, providing a sustained release of BLM. Comprehensive safety assessments, including cell viability, hemolysis ratio, and intradermal reactions in rabbits, validate the safety of MN patches. The BLM@PLA-MNs exhibit an effective inhibitory efficiency against hemangioma formation in a murine hemangioma model. Of significant importance, RNA-seq analysis reveals that BLM@PLA-MNs exert their inhibitory effect on hemangiomas by regulating the P53 pathway. In summary, BLM@PLA-MNs emerge as a promising clinical candidate for the effective treatment of hemangiomas. Graphical Abstract

Abstract Public health events (PHEs) have emerged as significant threats to human life, health, and economic growth. PHEs, such as COVID-19, have prompted a reevaluation for enhanced regular prevention and control (RPC). In this study, we focus on the core concept of prevention and control intensity (PCI), and establish a neoclassical economic growth model from the long-term and macro perspective to balance life protection and economic growth. The model construct the mechanism of PCI on economic growth through population dynamics and capital accumulation under the backdrop of RPC for PHEs. We find the conditions for PCI when the economy achieves steady state, and provides an algorithm establishing the optimal strategy that maximises per capita disposable income based on the optimal PCI and consumption. Simulation result quantifies an inverted U-shaped relationship between PCI and capital per capita, output per capita and consumption per capita in the steady state. The model suggests that, given the PHEs of inducing potential unemployment shock, it is worthwhile to combine the implementation of moderate PCI with coordinated policies of income distribution.

Abstract Topological phases in photonic systems have garnered significant attention, often relying on precise structural design for generating non-trivial topological phases. However, this dependency on fixed structures limits their adaptability. This study systematically explores incident angle-induced topological phase transitions in a one-dimensional photonic crystal (PC). Both TE and TM polarized modes undergo topological phase transitions at the same critical transition angles. Additionally, the TM-polarized mode undergoes a unique topological phase transition at the Brewster angle. When these two kinds of transition angles coincide, even if the band structure of the TM-polarized mode undergoes an open-close-reopen process, the topological properties of the corresponding bandgap remain unchanged. Based on theoretical analysis, we design the composite PCs comprising two interfaced PCs having common bandgaps but different topological properties. By tuning the incident angle, we theoretically and experimentally achieve TE-TM splitting of topological interface states in the visible region, which may have potential applications in optical communications, optical switching, photonic integrated circuits, and so on.

Abstract Background Non-pharmaceutical interventions (NPIs) have been widely utilised to control the COVID-19 pandemic. However, it is unclear what the optimal strategies are for implementing NPIs in the context of coronavirus vaccines. This study aims to systematically identify, describe, and evaluate existing ecological studies on the real-world impact of NPIs in containing COVID-19 pandemic following the roll-out of coronavirus vaccines. Methods We conducted a comprehensive search of relevant studies from January 1, 2021, to June 4, 2023 in PubMed, Embase, Web of science and MedRxiv. Two authors independently assessed the eligibility of the studies and extracted the data. A risk of bias assessment tool, derived from a bibliometric review of ecological studies, was applied to evaluate the study design, statistical methodology, and the quality of reporting. Data were collected, synthesised and analysed using qualitative and quantitative methods. The results were presented using summary tables and figures, including information on the target countries and regions of the studies, types of NPIs, and the quality of evidence. Results The review included a total of 17 studies that examined the real-world impact of NPIs in containing the COVID-19 pandemic after the vaccine roll-out. These studies used five composite indicators that combined multiple NPIs, and examined 14 individual NPIs. The studies had an average quality assessment score of 13 (range: 10–16), indicating moderately high quality. NPIs had a larger impact than vaccination in mitigating the spread of COVID-19 during the early stage of the vaccination implementation and in the context of the Omicron variant. Testing policies, workplace closures, and restrictions on gatherings were the most effective NPIs in containing the COVID-19 pandemic, following the roll-out of vaccines. The impact of NPIs varied across different time frames, countries and regions. Conclusion NPIs had a larger contribution to the control of the pandemic as compared to vaccination during the early stage of vaccine implementation and in the context of the omicron variant. The impact of NPIs in containing the COVID-19 pandemic exhibited variability in diverse contexts. Policy- and decision-makers need to focus on the impact of different NPIs in diverse contexts. Further research is needed to understand the policy mechanisms and address potential future challenges.

Abstract Background Sarcopenia is characterized by progressive loss of muscle mass and function due to aging. DNA methylation has been identified to play important roles in the dysfunction of skeletal muscle. The aim of our present study was to explore the whole blood sample‐based methylation changes of skeletal muscle function‐related factors in patients with sarcopenia. Methods The overall DNA methylation levels were analysed by using MethlTarget™ DNA Methylation Analysis platform in a discovery set consistent of 50 sarcopenic older adults (aged ≥65 years) and 50 age‐ and sex‐matched non‐sarcopenic individuals. The candidate differentially methylated regions (DMRs) were further validated by Methylation‐specific PCR (MSP) in another two independent larger sets and confirmed by pyrosequencing. Receiver operating characteristic (ROC) curve analysis was used to determine the optimum cut‐off levels of fibroblast growth factor 2 (FGF2)_30 methylation best predicting sarcopenia and area under the ROC curve (AUC) was measured. The correlation between candidate DMRs and the risk of sarcopenia was investigated by univariate analysis and multivariate logistic regression analysis. Results Among 1149 cytosine‐phosphate‐guanine (CpG) sites of 27 skeletal muscle function‐related secretary factors, 17 differentially methylated CpG sites and 7 differentially methylated regions (DMRs) were detected between patients with sarcopenia and control subjects in the discovery set. Further methylation‐specific PCR identified that methylation of fibroblast growth factor 2 (FGF2)_30 was lower in patients with sarcopenia and the level was decreased as the severity of sarcopenia increased, which was confirmed by pyrosequencing. Correlation analysis demonstrated that the methylation level of FGF2_30 was positively correlated to ASMI (r = 0.372, P

Abstract The rapid expansion of low‐voltage distributed photovoltaic (PV) systems with decentralized layouts poses significant data collection challenges. The scarcity of data amplifies prediction complexities, affecting the operational security and stability of distribution networks. To enhance predictive accuracy for distributed regional PV power generation, including unmonitored low‐voltage systems, this paper proposes a novel prediction approach that combines weight optimization and transfer learning. Firstly, to more accurately extrapolate from neighbouring monitored PV to estimate unmonitored PV outputs, a novel SSA‐MLP‐XGBoost model is proposed for monitored PV power plants, in which the hyperparameters of multilayer perceptron (MLP) and (extreme gradient boosting) XGBoost models are fine‐tuned using the sparrow search algorithm (SSA), and the optimized models are synergistically integrated to heighten prediction precision for monitored plants. Secondly, based on the predicted power curves of monitored PV power plants, a weight optimization model is presented to optimize the combined weights between unmonitored and monitored power stations. Furthermore, the power generation model from monitored facilities is transplanted to unmonitored plants for power generation estimation. Ultimately, the authors combine the weight optimization and transfer learning model to get more accurate and robust model. Validation across three regional distributed photovoltaic clusters demonstrates a noteworthy improvement in prediction accuracy—20%, 7.5%, and 25% for the respective clusters compared to the existing methods.

Abstract Objective About 10% of patients after cardiopulmonary bypass (CPB) would undergo acute liver injury, which aggravated the mortality of patients. Ac2-26 has been demonstrated to ameliorate organic injury by inhibiting inflammation. The present study aims to evaluate the effect and mechanism of Ac2-26 on acute liver injury after CPB. Methods A total of 32 SD rats were randomized into sham, CPB, Ac, and Ac/AKT1 groups. The rats only received anesthesia, and rats in other groups received CPB. The rats in Ac/AKT1 were pre-injected with the shRNA to interfere with the expression of AKT1. The rats in CPB were injected with saline, and rats in Ac and Ac/AKT1 groups were injected with Ac2-26. After 12 h of CPB, all the rats were sacrificed and the peripheral blood and liver samples were collected to analyze. The inflammatory factors in serum and liver were detected. The liver function was tested, and the pathological injury of liver tissue was evaluated. Results Compared with the sham group, the inflammatory factors, liver function, and pathological injury were worsened after CPB. Compared with the CPB group, the Ac2-26 significantly decreased the pro-inflammatory factors and increased the anti-inflammatory factor, improved liver function, and ameliorated the pathological injury. All the therapeutic effects of Ac2-26 were notably attenuated by the shRNA of AKT1. The Ac2-26 increased the GSK3β and eNOS, and this promotion was inhibited by the shRNA. Conclusion The Ac2-26 significantly treated the liver injury, inhibited inflammation, and improved liver function. The effect of Ac2-26 on liver injury induced by CPB was partly associated with the promotion of AKT1/GSK3β/eNOS.

Neurodegenerative diseases (NDDs) are prevalent in the elderly. The pathogenesis of NDDs is complex, and currently, there is no cure available. With the increase in aging population, over 20 million people are affected by common NDDs alone (Alzheimer’s disease and Parkinson’s disease). Therefore, NDDs have profound negative impacts on patients, their families, and society, making them a major global health concern. Rho-associated kinases (ROCKs) belong to the serine/threonine protein kinases family, which modulate diverse cellular processes (e.g., apoptosis). ROCKs may elevate the risk of various NDDs (including Huntington’s disease, Parkinson’s disease, and Alzheimer’s disease) by disrupting synaptic plasticity and promoting inflammatory responses. Therefore, ROCK inhibitors have been regarded as ideal therapies for NDDs in recent years. Fasudil, one of the classic ROCK inhibitor, is a potential drug for treating NDDs, as it repairs nerve damage and promotes axonal regeneration. Thus, the current review summarizes the relationship between ROCKs and NDDs and the mechanism by which fasudil inhibits ROCKs to provide new ideas for the treatment of NDDs.

IntroductionScalp arteriovenous fistula (AVF) is a rare and intricate vascular anomaly characterized by a direct connection between an artery and a vein, without an intervening capillary system. This anomaly can induce significant local hemodynamic changes and is associated with various complications, such as pain, a pulsatile mass, increasing swelling, and venous hypertension skin ulcerations which may be non-healing. This study aimed to evaluate the efficacy and safety of interventional embolization treatments for scalp AVF at Shandong Provincial Hospital.MethodsThis retrospective clinical analysis assessed 21 patients who underwent interventional embolization between 2018 and 2024. Patients included were those treated in the vascular surgery department at Shandong Provincial Hospital, who had comprehensive medical records and follow-up data. Treatment methods, outcomes, and complications were thoroughly analyzed through patient medical records.ResultsAmong the patients studied, direct puncture was the most prevalent treatment method, employed in 42.86% (9/21) of cases, followed by various combinations of arterial, venous, and direct approaches. Ethanol, used in 85.71% (18/21) of the cases, demonstrated its broad efficacy and application in clinical settings. Immediate imaging post-treatment confirmed a cure rate of 85.71% (18/21). The main postoperative complications included swelling, with some patients also experiencing nodules, scabbing, or hair loss.ConclusionInterventional embolization has proven to be a safe and effective method for managing scalp AVF, significantly minimizing complications. Future research should focus on further optimizing these treatment methods to enhance efficacy and improve patient quality of life.

The receptive field (RF) plays a crucial role in convolutional neural networks (CNNs) because it determines the amount of input information that each neuron in a CNN can perceive, which directly affects the feature extraction ability. As the number of convolutional layers in CNNs increases, there is a decay of the RF according to the two-dimensional Gaussian distribution. Thus, an effective receptive field (ERF) can be used to characterize the available part of the RF. The ERF is calculated by the kernel size and layer number within the neural network architecture. Currently, ERF calculation methods are typically applied to single-channel input data that are both independent and identically distributed. However, such methods may result in a loss of effective information if they are applied to more general (i.e., multi-channel) datasets. Therefore, we proposed a multi-channel ERF calculation method. By conducting a series of numerical experiments, we determined the relationship between the ERF and the convolutional kernel size in conjunction with the layer number. To validate the new method, we used the recently published global wave surrogate model for climate simulation (GWSM4C) and its accompanying dataset. According to the newly established relationship, we refined the kernel size and layer number in each neural network of the GWSM4C to produce the same ERF but lower RF attenuation rates than those of the original version. By visualizing the gradient map at several points in West African and East Pacific areas, the high gradient value regions confirmed the known swell sources, which indicated effective feature extraction in these areas. Furthermore, the new version of the GWSM4C yielded better prediction accuracy for significant wave height in global swell pools. The root mean square errors in the West African and East Pacific regions reduced from approximately 0.3 m, in the original model to about 0.15 m, in the new model. Moreover, these improvements were attributed to the higher efficiency of the newly modified neural network structure that allows the inclusion of more historical winds while maintaining acceptable computational consumption.

Abstract With the International Conference on Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) E17 guidelines in effect from 2018, the design of Asia‐inclusive multiregional clinical trials (MRCTs) has been streamlined, thereby enabling efficient simultaneous global development. Furthermore, with the recent regulatory reforms in China and its drug administration joining the ICH as a full regulatory member, early participation of China in the global clinical development of novel investigational drugs is now feasible. This would also allow for inclusion of the region in the geographic footprint of pivotal MRCTs leveraging principles of the ICH E5 and E17. Herein, we describe recent case examples of model‐informed Asia‐inclusive global clinical development in the EMD Serono portfolio, as applied to the ataxia telangiectasia and Rad3‐related inhibitors, tuvusertib and berzosertib (oncology), the toll‐like receptor 7/8 antagonist, enpatoran (autoimmune diseases), the mesenchymal–epithelial transition factor inhibitor tepotinib (oncology), and the antimetabolite cladribine (neuroimmunological disease). Through these case studies, we illustrate pragmatic approaches to ethnic sensitivity assessments and the application of a model‐informed drug development toolkit including population pharmacokinetic/pharmacodynamic modeling and pharmacometric disease progression modeling and simulation to enable early conduct of Asia‐inclusive MRCTs. These examples demonstrate the value of a Totality of Evidence approach where every patient's data matter for de‐risking ethnic sensitivity to inter‐population variations in drug‐ and disease‐related intrinsic and extrinsic factors, enabling inclusive global development strategies and timely evidence generation for characterizing benefit/risk of the proposed dosage in Asian populations.

ObjectiveThe aim of this investigation is to explore the efficacy of combined exercise in elderly patients with hypertension. Moreover, we aim to delve into the underlying mechanisms governing blood pressure regulation, with the objective of promoting the adoption of this exercise regimen among elderly hypertensive individuals.MethodsIn our study, we conducted a thorough search across multiple databases, including PubMed, Web of Science, Cochrane Library, Embase, and Scopus. This extensive search resulted in the preliminary screening of 2,347 articles. Among these, 9 studies were carefully selected for an in-depth analysis. For our meta-analysis, we employed Review Manager 5.3 and Stata 15.0, enabling us to perform detailed subgroup analyses and assess the possibility of publication bias.ResultsIn comparison to the control group (n = 194), individuals enrolled in the combined exercise group (n = 200) exhibited a notable decrease in both resting systolic blood pressure (SBP) [weighted mean difference (WMD) = −11.17 mm Hg, 95% confidence interval (CI) (−17.13, −5.22), Z = 3.68, P

Abstract To enhance the anesthetic efficacy and reduce toxic side effects, a strategy is proposed involving the utilization of general anesthetics of Propofol (Pro) and Etomidate (Eto) to synergistic inhibition GABA receptors simultaneously. Four‐in‐one molecular aggregates were prepared to implement this strategy, which comprised of Pro and Eto with the bridging molecule monoglyceride monooleate (GMO) and surfactant F127 through intermolecular forces. The blood‐brain barrier (BBB) targeted lactoferrin (LF) is affixed to their surface, obtaining the final molecular aggregates. By employing lactoferrin enrich aggregates to the BBB, followed by ultrasound combine microbubbles to open the BBB, a remarkable 4.5‐fold enhancement in brain drug delivery was achieved. The molecular aggregates group maintained stable parameters of heart rate, diastolic blood pressure, and systolic blood pressure. A notable increase of more than twice therapeutic index (TI) value was observed, implying their higher anesthesia efficiency and reduced toxicity. Electroencephalogram (EEG) experiments demonstrate a significant elevation in the proportion of δ waves from 28% to 80% for aggregates, accompanied by a nearly fivefold reduction in the proportion of θ waves, meaning a significant improvement in synergistic anesthesia effectiveness (interaction index 0.289) with lower drug dosage. Furthermore, mouse immunofluorescence brain slice experiments suggest Pro and Eto enter the GABA receptor simultaneously, resulting in synergistic inhibition of GABA receptors.

Abstract BackgroundVideo-based error correction (VBEC) in medical education could offer immediate feedback, promote enhanced learning retention, and foster reflective practice. However, its application in cardiopulmonary resuscitation (CPR) training has not been investigated. ObjectiveThe objective of this study is to assess whether the VBEC procedure could improve the training performance of CPR among anesthesiology residents. MethodsA quasi-experimental study was conducted among anesthesiology residents between December 2022 and April 2023. Primary outcomes included a posttraining knowledge test and practical assessment scores. Secondary outcomes included the number of residents who correctly conducted CPR at each step, the rate of common mistakes during the CPR process, and the self-assessment results. A total of 80 anesthesiology residents were divided into a VBEC group (n=40) and a control group (n=40). The VBEC group underwent a 15-minute VBEC CPR training, whereas the control group underwent a 15-minute video-prompting CPR training. ResultsThe posttraining knowledge test score of the VBEC group was significantly higher than that of the control group (73, SD 10.5 vs 65.1, SD 11.4; PPPPP ConclusionsVBEC may be a promising strategy compared to video prompting for CPR training among anesthesiology residents.

Summary: Lavender essential oil (LEO) has been shown to relieve pain in humans, but the underlying neural mechanisms remain unknown. Here, we found that inhalation exposure to 0.1% LEO confers antinociceptive effects in mice with complete Freund adjuvant (CFA)-induced inflammatory pain through activation of projections from the anterior piriform cortex (aPir) to the insular cortex (IC). Specifically, in vivo fiber photometry recordings and viral tracing data show that glutamatergic projections from the aPir (aPirGlu) innervate GABAergic neurons in the IC (ICGABA) to inhibit local glutamatergic neurons (ICGlu) that are hyperactivated in inflammatory pain. Optogenetic or chemogenetic activation of this aPirGlu→ICGABA→Glu pathway can recapitulate the antinociceptive effects of LEO inhalation in CFA mice. Conversely, artificial inhibition of IC-projecting aPirGlu neurons abolishes LEO-induced antinociception. Our study thus depicts an LEO-responsive olfactory system circuit mechanism for alleviating inflammatory pain via aPir→IC neural connections, providing evidence to support development of aroma-based treatments for alleviating pain.

Giant cell glioblastoma often exhibits genome instability and is frequently associated with mutations in genes involved in DNA repair pathways including TP53 and DNA mismatch repair genes. Several germline mutations have been identified in giant cell glioblastoma, including mutations of MSH1 and MSH2, TP53, and POLE. We have documented a case of a germline mutation in CHEK2, another gene crucial to DNA repair, in a patient with giant cell glioblastoma. The CHEK2 mutation was inherited from the patient’s father, who had a history of gastric cancer and renal cell carcinoma. In addition to the germline CHEK2 mutation, the giant cell glioblastoma exhibited a genome-wide loss of heterozygosity, a characteristic observed in a subset of giant cell glioblastomas. Additional mutations detected in the tumor included TP53, PTEN, and a PTPRZ1-MET fusion. This represents the first reported case of a CHEK2 germline mutation in giant cell glioblastoma, further supporting the significance of impaired DNA repair mechanisms in the development of this disease.

Background: Few studies have compared the performances of those reported miRNAs as biomarkers for heart failure with reduced EF (HFrEF) in a population at high risk. The purpose of this study is to investigate comprehensively the performance of those miRNAs as biomarkers for HFrEF. Methods: By using bioinformatics methods, we also examined these miRNAs' target genes and possible signal transduction pathways. We collected serum samples from patients with HFrEF at Zhongshan Hospital. Receiver operating characteristic (ROC) curves were used to evaluate the accuracy of those miRNAs as biomarkers for HFrEF. miRWALK2.0, Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to predict the target genes and pathways of selected miRNAs. Results: The study included 48 participants, of whom 30 had HFrEF and 18 had hypertension with normal left ventricular ejection fraction (LVEF). MiR-378, miR-195-5p were significantly decreased meanwhile ten miRNAs were remarkably elevated (miR-21-3p, miR-21-5p, miR-106-5p, miR-23a-3p, miR-208a-3p, miR-1-3p, miR-126-5p, miR-133a-3p, miR-133b, miR-223-3p) in the serum of the HFrEF group. Conclusion: The combination of miR 133a-3p, miR 378, miR 1-3p, miR 106b-5p, and miR 133b has excellent diagnostic performance for HFrEF, and there is a throng of mechanisms and pathways by which regulation of these miRNAs may affect the risk of HFrEF.

Analyzing capacity degradation characteristics and accurately predicting the knee point of capacity are crucial for the safety management of lithium-ion batteries (LIBs). However, the degradation mechanism of LIBs is complex. A key but challenging problem is how to clarify the degradation mechanism and predict the knee point. According to the external characteristics such as capacity decline gradievnt and the peak value of increment capacity curve (IC curve), the capacity degradation can be divided into four stages, including initial decline stage, slow decline stage, transition stage and high-speed decline stage. The degradation mechanism of LIBs is compared from the longitudinal and horizontal aspects, respectively. Among them, the battery usage from the initial stage to the end of life (EOL) is longitudinal analysis. The battery under different conditions, such as charging and discharging, different discharge rate, different cathode material degradation mechanism is horizontal analysis. Moreover, a method based on neural network is proposed to predict the knee point. Two features are used to predict the capacity and cycle of the knee point, which are the gradient of the capacity degradation curve and the difference of the IC curve with the maximum correlation. The experimental results show that a two-dimensional surface can be obtained using only the first 100 cycles, which can provide a reference for the position of the knee point accurately prediction.

Background: Calcitriol (Cal) is the most active metabolite of vitamin D and has antioxidant and anti-inflammatory properties. The aim of this study was to investigate the role of Cal in noise-induced hearing loss (NIHL) to further elucidate the mechanism of noise-induced oxidative stress in the mouse cochlea. Methods: C57BL/6 J mice were given six intraperitoneal injections of Cal (500 ng/kg/d). After 14 days of noise exposure, auditory brainstem response (ABR) thresholds, and the cochlear outer hair cell loss rate were analysed to evaluate auditory function. Real-time fluorescence quantitative PCR, immunofluorescence and western blotting were performed in vitro after the treatment of cochlear explants with 100 µM tert-butyl hydroperoxide (TBHP) for 2.5 h and HEI-OC1 cells with 250 µM TBHP for 1.5 h. Results: In vivo experiments confirmed that Cal pretreatment mitigated NIHL and outer hair cell death. The in vitro results demonstrated that Cal significantly reduced TBHP-induced cochlear auditory nerve fibre degradation and spiral ganglion neuron damage. Moreover, treatment with Cal inhibited the expression of oxidative stress-related factors (3-NT and 4-HNE) and DNA damage-related factors (γ-H2A.X) and attenuated TBHP-induced apoptosis in cochlear explants and HEI-OC1 cells. A total of 1479 upregulated genes and 1443 downregulated genes were screened in cochlear tissue 1 h after noise exposure. The level of transcription factor 3 (ATF3) was significantly elevated in HEI-OC1 cells after TBHP stimulation. Gene Transcription Regulation Database （GTRD）and Cistrome database analyses revealed that the downstream target gene of ATF3 is dual specificity phosphatase 1 (DUSP1). Cistrome DB Toolkit database results showed that the transcription factor of DUSP1 was ATF3. In addition, the ChIP-PCR results indicated that ATF3 might be a direct transcription factor of DUSP1. Conclusion: The results of our study suggest that Cal attenuates NIHL and inhibits noise-induced apoptosis by regulating the ATF3/DUSP1 signalling pathway.

The protection dead-zone and threshold setting difficulties of the residual current devices (RCDs) in low-voltage distribution networks may lead to the misidentification of electric shock fault, resulting in severe life-threatening accidents. This paper proposes an electric shock fault identification method based on artificial intelligence for RCDs. Firstly, Mallat discrete wavelet transform (DWT) is applied to efficiently extract non-stationary electric shock feature signals from the total residual current with various noises, preventing weak non-stationary electric shock feature signals from being filtered out. Based on the average and maximum components of the signal mutation, an adaptive threshold can be determined to detect electric shock accurately, avoiding the false activation of RCDs caused by load fluctuations. Subsequently, an autoencoder (AE) is built to mine the non-linear features in which the signal of electric shock on living gradually rises and the signal of electric shock on non-living remains stable. Finally, a back propagation neural network (BPNN) is trained to classify the electric shock types from the non-linear features. The simulation and experiment have been conducted to obtain total residual current data under different conditions, and the electric shock fault real-time identification hardware platforms are developed. The accuracy of electric shock fault detection and classification can reach 100 %, which has advanced its practical applicability.

Abstract Resistive switching memories have garnered significant attention due to their high‐density integration and rapid in‐memory computing beyond von Neumann's architecture. However, significant challenges are posed in practical applications with respect to their manufacturing process complexity, a leakage current of high resistance state (HRS), and the sneak‐path current problem that limits their scalability. Here, a mild‐temperature thermal oxidation technique for the fabrication of low‐power and ultra‐steep memristor based on Ag/TiOx/SnOx/SnSe2/Au architecture is developed. Benefiting from a self‐assembled oxidation layer and the formation/rupture of oxygen vacancy conductive filaments, the device exhibits an exceptional threshold switching behavior with high switch ratio exceeding 106, low threshold voltage of ≈1 V, long‐term retention of >104 s, an ultra‐small subthreshold swing of 2.5 mV decade−1 and high air‐stability surpassing 4 months. By decreasing temperature, the device undergoes a transition from unipolar volatile to bipolar nonvolatile characteristics, elucidating the role of oxygen vacancies migration on the resistive switching process. Further, the 1T1R structure is established between a memristor and a 2H‐MoTe2 transistor by the van der Waals (vdW) stacking approach, achieving the functionality of selector and multi‐value memory with lower power consumption. This work provides a mild‐thermal oxidation technology for the low‐cost production of high‐performance memristors toward future in‐memory computing applications.

Apportioning pollution sources under compound pollution conditions is challenging in river pollution source analysis. The positive matrix factorization (PMF) model is widely used to analyze river pollution sources. However, the identification of pollutants in this model relies primarily on the subjective experience of the researchers, leading to ineffective identification of different contaminants from similar sources. In this study, we propose a comprehensive deviation index (CDI) to quantitatively identify pollution source types based on the PMF and observed source profiles. Taking the subtropical Xizhijiang River Basin as a case study, we quantitatively identified the pollution sources and their contributions to dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP) using observed water quality and pollution sources data. The results showed that the eight major pollutants in the study region exhibited significant positive correlations, indicating the similarity of pollutant sources in the watershed. The PMF model identified three primary pollution sources with coefficients of determination for observed versus predicted concentrations ranging from 0.60 to 0.98. The CDI unveiled that the watershed's three pollution sources were farmland, rural, and wastewater treatment plants (WTPs). Farmland emerges as the predominant contributor to DOC (68.04 %), TC (63.29 %), and TDP (44.51 %). Rural notably contributes to NH3-N, PO43−, TDP, and TN, with percentages of 86.37 %, 57.65 %, 41.40 %, and 30.45 %, respectively. WTPs significantly contribute to NO2−, NO3−, and TN, accounting for 71.81 %, 57.39 %, and 37.26 %, respectively. Incorporating source fingerprints into the PMF model, the CDI can accurately identify pollution sources, improve the interpretability of source identification, and mitigate uncertainty in the multiple-source unknown receptor model. These findings have immediate and practical implications for river ecosystem management and pollution control, providing a more effective method for identifying and addressing pollution sources.

Mariculture ponds are essential components of the coastal wetland, which are often criticized by eutrophication risk for the dissolved inorganic nitrogen (DIN) input to the coastal zone by the culture tailwater. However, the reduce of this DIN pollution was difficult because the tailwater is hard to collect and the treatment is inefficient and expensive. Sesuvium Portulacastrum is a coastal vegetation which has high efficiency in DIN absorption from the seawater and sediment. In this study, we use Sesuvium Portulacastrum as a tool species to study the control behavior of the DIN in mariculture ponds wetland. The change trend of DIN in pond water and benthic species in pond sediment was investigated. The results showed that Sesuvium Portulacastrum reduced NH4+, NO3-, and NO2- in the pond water by 83.21%, 95.22%, and 91.32%, respectively. The species number of benthic organisms was enhanced from 2 to 5 and the species structure was more optimized in Sesuvium Portulacastrum pond than control pond. At the end of the experiment, eutrophication indicator species (Capitella capitata) was disappeared in the Sesuvium Portulacastrum pond. Those suggest that the coastal vegetation (Sesuvium Portulacastrum) have great potential to eliminate DIN pollutants in mariculture pond wetland.

Abstract In the past, hydrogen sulfide (H2S) was recognized as a toxic and dangerous gas; in recent years, with increased research, we have discovered that H2S can act as an endogenous regulatory transmitter. In mammals, H2S‐catalyzing enzymes, such as cystathionine‐β‐synthase, cystathionine‐γ‐lyase, and 3‐mercaptopyruvate sulfurtransferase, are differentially expressed in a variety of tissues and affect a variety of biological functions, such as transcriptional and posttranslational modification of genes, activation of signaling pathways in the cell, and metabolic processes in tissues, by producing H2S. Various preclinical studies have shown that H2S affects physiological and pathological processes in the body. However, a detailed systematic summary of these roles in health and disease is lacking. Therefore, this review provides a thorough overview of the physiological roles of H2S in different systems and the diseases associated with disorders of H2S metabolism, such as ischemia–reperfusion injury, hypertension, neurodegenerative diseases, inflammatory bowel disease, and cancer. Meanwhile, this paper also introduces H2S donors and novel release modes, as well as the latest preclinical experimental results, aiming to provide researchers with new ideas to discover new diagnostic targets and therapeutic options.

BackgroundRestricting salt, caffeine, and alcohol intake is commonly recommended as a first-line treatment for patients with Ménière’s disease (MD). However, it remains unclear whether these interventions effectively improve symptoms of MD. Therefore, we conducted a bidirectional two-sample Mendelian randomization (MR) analysis to evaluate the relationship between these dietary modifications and MD.MethodsSummary statistics for salt added to food, alcohol consumption, coffee consumption, and MD were sourced from the United Kingdom Biobank, GSCAN, and the FinnGen study, involving up to 941,280 participants. The main analyses were performed using the random-effects inverse-variance weighted (IVW) approach and were complemented by four additional methods. Multiple sensitivity analyses were performed to validate the findings, and both forward and reverse MR analyses were employed to address potential reverse causality bias.ResultsThe primary MR results using the IVW method revealed that salt added to food (OR = 0.719, 95% CI: 0.429–1.206; p = 0.211), alcohol consumption (OR = 0.834, 95% CI: 0.427–1.628; p = 0.595), and coffee consumption (OR = 0.852, 95% CI: 0.555–1.306; p = 0.461) were not significantly correlated with MD. In reverse analysis, no evidence of significant effect was found from MD to salt added to food (OR = 1.000, 95% CI: 0.993–1.007; p = 0.957), alcohol consumption (OR = 0.998, 95% CI: 0.987–1.008; p = 0.682), and coffee consumption (OR = 0.998, 95% CI: 0.985–1.011; p = 0.72).ConclusionThis MR analysis did not identify convincing evidence to support the idea that restricting salt, caffeine, and alcohol intake is beneficial for the treatment of MD.

IntroductionThus far, the impact of kaolin mining activities on the surrounding native plants and rhizosphere microecology has not been fully understood.MethodsIn this study, we used 16S rRNA high-throughput sequencing to examine the impact of kaolin mining on the rhizosphere bacterial communities and functions of three local plant species: Conyza bonariensis, Artemisia annua, and Dodonaea viscosa.ResultsThe results showed that kaolin mining significantly reduced the diversity of rhizosphere bacteria in these plants, as indicated by the Shannon, Simpson, Chao1, and observed species indices (p

TTFields is a novel FDA-approved technology utilized for treating glioblastoma multiforme (GBM) within the brain. Presently, the effectiveness of therapy is evaluated through MRI imaging at random two-month intervals. Electrical impedance is an important and effective parameter for reflecting changes in tissue properties. In TTFields treatment for brain tumors, electrodes attached to the scalp deliver electric field energy to the tumor region. We hypothesize that these electrodes can also serve as sensors to detect impedance changes caused by tumor alterations in real time, thus continuously assessing the effectiveness of the treatment. In this work, we propose and scrutinize this hypothesis by conducting an in silico study to confirm the potential feasibility of the proposed concept. Our results indicate that the impedance amplitude change measured between opposing TTFields electrode arrays utilizing voltage and frequency of 50 V and 200 kHz (typical TTFields treatment parameters), has enough resolution (> 1mm) and Signal-to-Noise Ratio (> 40 dB) to evaluate tumor size change in the head. The impedance detection technique may be a significant augmentation to TTFields cancer treatment, enabling the continuous evaluation of safety and efficacy throughout the procedure.

ObjectivePreoperative diagnosis for follicular thyroid cancer (FTC) remains challenging. The purpose of this study was to explore the maximum intensity projection (MIP) features, which can be utilized for reconstructing and characterizing the structure of microvascular in tissue, associated with FTC, and to explore the independent risk factors for FTC in combination with multimodal ultrasonography and blood indicators.MethodsThis single-center, prospective, single-blind, observational study included patients with suspected follicular thyroid carcinoma based on preoperative ultrasonography findings. All patients underwent routine ultrasonography, contrast-enhanced ultrasonography (CEUS), and correlated blood indexes tests. Offline MIP reconstruction of the CEUS images was performed. The tumor was histologically diagnosed postoperatively. Multivariable logistics regression was utilized for analyzing MIP characteristics combined with multimodal ultrasonography and preoperative blood indicators to identify independent risk factors for FTC.ResultsIn this study, 61 thyroid nodules were finally included according to the atretic criteria. (1) Compared with traditional color profile ultrasonography and CEUS, MIP technology can provide more information regarding microvascular characteristics inside thyroid tumors. The short, rod-like, crossed, curved and firework-like features of MIP images revealed statistically significant differences between the benign and malignant groups. (2) Multivariable logistic regression analysis indicated that the firework-like MIP characteristics of microvascular, thyroglobulin (Tg) level and vessel intensity (VI) value were independent risk factors for malignancy.Conclusion(1) MIP technology has potential applications in the differential diagnosis of follicular thyroid carcinoma from benign lesions. (2) Firework MIP microvascular characteristics, Tg values and VI values can serve as parameters for the differential diagnosis of follicular thyroid carcinoma from benign lesions. This study provides a novel approach idea for preoperative multimodal differentiation of follicular thyroid carcinoma from benign lesions.