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Abstract Background Dupilumab inhibiting the signaling of interleukin(IL)-4 and IL-13 was recommended for the treatment of severe asthma in children ≥ 6 years old according to the Global Initiative for Asthma (GINA,2024).This study aimed to analyse the efficacy and safety of dupilumab in paediatric patients with moderate-to-severe asthma and comorbid type 2 inflammatory disease in a real-world population. Methods We evaluated the medical records of paediatric patients with moderate-to-severe asthma and comorbid type 2 inflammatory diseases, such as atopic dermatitis (AD) and allergic rhinitis (AR), receiving dupilumab treatment. Results Twenty-five children (16 boys; mean age, 9.32 ± 2.58 years) were included. All the patients were diagnosed with moderate-to-severe asthma, 92% (23/25) with AR, and 64.0% (16/25) with AD. Among the 25 patients, no severe adverse reactions occurred, the times of severe asthma exacerbation were significantly lower, and the Asthma Control Test (ACT) / Child-Asthma Control Test (C-ACT) scores were significantly higher than those before the 24-week dupilumab treatment (all P = 0.00). The Patient-Oriented Eczema Measure(POEM) and Peak Pruritus Numerical Rating Scale(NRS), Rhinitis Four-point, and Rhinitis Visual Analogue Scale(VAS) scores were significantly lower than those at baseline (all P

Abstract Aims This study aimed to investigate the association of soluble suppression of tumorigenicity‐2 (sST2) measured by point‐of‐care testing assay with clinical outcomes in patients hospitalized with heart failure after adjusting for other predictors including N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP) and high‐sensitivity cardiac troponin T (hs‐cTnT). Methods A total of 1726 consecutive patients hospitalized with heart failure from July 2015 to December 2021 were enrolled. Baseline serum sST2 concentrations were measured by immunofluorescence assay. Primary endpoint event was the composite of all‐cause death, heart transplantation, or left ventricular assist device. Results During the median follow‐up duration of 682 days, 434 patients (25.1%) suffered from primary endpoint events. Baseline sST2 remained an independent predictor of the primary endpoint event in patients hospitalized with heart failure after adjusting for other predictors including NT‐proBNP and hs‐cTnT [per log (unit) increase, adjusted hazard ratio (HR) (95% confidence interval) (CI): 1.20 (1.09, 1.32), P

Abstract A method based on Gabor spectral mode transmissibility functions (GSMTFs) is proposed to detect local damage in a cantilevered structure under nonstationary ambient excitations. Gabor transformation and singular value decomposition are used to reduce the influences of other vibration modes on Gabor spectral mode transmissibility functions and process nonstationary structural responses, respectively. A new state characteristic based on the fundamental structure frequency is formulated on the basis of the GSMTFs, eventually leading to the development of a new damage indicator. The probability density functions of the damage indicator for healthy and damaged states can be estimated from the measured data, and the receiver operating characteristic (ROC) curve derived from these probability distributions and the corresponding area under the ROC curve (AUC) are used to determine the damage location. A six-degree-of-freedom system and a typical transmission tower are numerically studied, and the results show that the proposed method can estimate the structural damage location under nonstationary random loads. The proposed method is further validated with a planar frame in the laboratory, which exhibits multiple damage elements via random force hammer excitations. The results show that the AUC values computed for certain parts of the structure containing the damaged elements are greater than those for other parts of the structure, indicating the effectiveness of the proposed method. Moreover, the proposed method is compared with the dot product difference (DPD) index, and the results from the laboratory planar frame demonstrate that the proposed method can better identify damage.

Abstract Background Non‐small cell lung cancer (NSCLC) is one of the most prevalent and severe malignant tumors in the world and its molecular mechanism is still unclear. In recent years, increasing evidence indicates the significant roles of circRNAs in NSCLC. It has been determined that 2‐methoxyestradiol (2‐MeOE2) exerts antitumor roles in many cancers. However, the molecular mechanism of 2‐MeOE2 in regulating the development of lung cancer needs further elucidation. Methods The expression levels of circ_0010235, microRNA‐34a‐5p (miR‐34a‐5p), and nuclear factor of activated T cells 5 (NFAT5) were detected by quantitative real‐time polymerase chain reaction (qRT‐PCR). Cell proliferation, apoptosis and invasion were detected by cell counting kit‐8 (CCK‐8), 5‐ethynyl‐2′‐deoxyuridine (EdU) assay, flow cytometry and transwell assays, respectively. The interaction between miR‐34a‐5p and circ_0010235 or NFAT5 was predicted by bioinformatic software and confirmed by dual‐luciferase reporter assay. Results Our data showed 2‐MeOE2 hindered cell proliferation, invasion and induced apoptosis in NSCLC, which could be reversed by upregulation of circ_0010235 and NFAT5 or miR‐34a‐5p knockdown. Circ_0010235 and NFAT5 expression levels were increased, and miR‐34a‐5p expression level was decreased in NSCLC tissues and cells. In addition, 2‐MeOE2 treatment suppressed the expression of circ_0010235 and NFAT5 while promoted the expression of miR‐34a‐5p. Furthermore, circ_0010235 functioned as a molecular sponge of miR‐34a‐5p to regulate NFAT5 expression. Knockdown of circ_0010235 or 2‐MeOE2 treatment constrained tumor growth in vivo, and circ_0010235 depletion enhanced the inhibitory effect of 2‐MeOE2 on tumor growth in vivo. Conclusion These findings demonstrated that 2‐MeOE2 retarded NSCLC progression by modulating the circ_0010235/miR‐34a‐5p/NFAT5 axis, thus providing a new perspective for 2‐MeOE2 treatment in NSCLC.

This paper conducts an in-depth study on the gasification treatment of Organic Solid Waste (OSW) and its carbon emissions, intending to fill the gap in the existing literature regarding the calculation methods for carbon emissions from OSW gasification. The study establishes a methodology for calculating carbon emission factors during the OSW gasification process and explores the potential for negative carbon emissions. For this purpose, indicator including the Carbon Dioxide Equivalent Warming Number (CEWN) is used to assess the greenhouse gas emissions of the gasification process by calculating carbon emission factors under different gasification conditions. It is found that within a certain range, increasing the gasification temperature, Equivalence Ratio (ER), and Steam to Biomass ratio (S/B) can positively influences the achievement of negative carbon emissions. These findings hold significant implications for optimizing the OSW gasification process, reducing carbon emissions, and ultimately achieving carbon neutrality. Furthermore, this study fills a critical void in the gasification field within the IPCC framework and offers essential guidance for promoting to achieve peak carbon emissions in the gasification industry and accelerating the goal of carbon neutrality.

Background: This study aims to investigate the association between nine tag single nucleotide polymorphisms (SNPs) in the C3 gene locus and the risk of coronary artery disease (CAD) as well as lipid levels in the Chinese population, and to further explore the interactions between SNPs and environmental factors that may be associated with CAD risk. Methods: A case-control study was conducted to investigate the association between CAD and C3 gene polymorphisms in a hospital setting. The study consisted of 944 CAD patients with a mean age of 55.97 ± 10.182 years and 897 non-CAD controls with a mean age of 55.94 ± 9.162 years. There were 565 males and 288 females in the CAD group and 583 males and 314 females in the control group. TagSNPs in the C3 gene were identified by employing the improved multiplex ligation detection reaction (iMLDR) technique, and multifactor dimensionality reduction (MDR) analysis was utilized to investigate the C3 gene–environment and gene–gene interactions in relation to the risk of CAD. Results: Results of the polymorphism study indicated that the CC genotype of rs7257062 was more frequent in the CAD group compared to the control group (10.9% vs 7.7%), with a statistically significant difference (p = 0.009). Moreover, the TT and CC + CT genotype groups of rs7257062 in the CAD subgroup showed a significant difference in terms of serum triglyceride levels (2.326 ± 1.889 vs 2.059 ± 1.447, p = 0.019). Analysis of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A (ApoA), and apolipoprotein B (ApoB) levels revealed no significant differences between the TT and CC + CT genotypes. Furthermore, no significant differences in serum lipid levels were observed between genotypes of the other SNPs. Multivariable logistic analysis, controlling for gender, age, body mass index (BMI), triglycerides (TG), TC, HDL-C, LDL-C, ApoA and ApoB, demonstrated that rs7257062 was still an independent risk factor of CAD (OR = 1.499, 95% CI: 1.036–2.168, p = 0.032). MDR analysis revealed that the rs7257062 interacted significantly with environmental factors such as smoking, diabetes, hypertension, BMI, and TG (p < 0.05). Conclusions: The rs7257062 variation of the C3 gene could be linked to both lipid balance and the risk of CAD. It is conceivable that the interplay between C3 polymorphisms and environmental elements could account for the etiology of CAD.

(1) Background: Chinese news text is a popular form of media communication, which can be seen everywhere in China. Chinese news text classification is an important direction in natural language processing (NLP). How to use high-quality text classification technology to help humans to efficiently organize and manage the massive amount of web news is an urgent problem to be solved. It is noted that the existing deep learning methods rely on a large-scale tagged corpus for news text classification tasks and this model is poorly interpretable because the size is large. (2) Methods: To solve the above problems, this paper proposes a Chinese news text classification method based on key feature enhancement named KFE-CNN. It can effectively expand the semantic information of key features to enhance sample data and then combine the zero–one binary vector representation to transform text features into binary vectors and input them into CNN model for training and implementation, thus improving the interpretability of the model and effectively compressing the size of the model. (3) Results: The experimental results show that our method can significantly improve the overall performance of the model and the average accuracy and F1-score of the THUCNews subset of the public dataset reached 97.84% and 98%. (4) Conclusions: this fully proved the effectiveness of the KFE-CNN method for the Chinese news text classification task and it also fully demonstrates that key feature enhancement can improve classification performance.

Background: Factor Xa (FXa) is a mediator initiating and accelerating atherosclerosis (AS). Both macrophage and vascular smooth muscle cells (VSMCs) participate in AS progression. This study was aimed to investigate the mechanisms underlying the effects of the FXa inhibitor rivaroxaban on AS.Methods: Rivaroxaban was administered to AS mice. Primary macrophages were exposed to FXa, treated with rivaroxaban, and transfected with siRNA silencing protease-activated receptor 2 (PAR2), hypoxia-inducible factor 1α (HIF1α), delta-like receptor 4 (Dll4), and Akt. Interaction between macrophages and VSMCs was assessed by co-culturing systems. Atherosclerotic lesions were evaluated by oil red O stain. Fluorescent staining was used to determine the cell phenotypes. Secretions of inflammatory cytokines and collagen were assessed by ELISA and Sircol assays. Western blotting was used to evaluate the protein expression and phosphorylation levels.Results: Rivaroxaban reduced lesion area, accumulation of M1 macrophages, and contractile-synthetic phenotypic conversion of VSMCs in atherosclerotic plaques. FXa exposure induced polarization of macrophages toward M1 and Dll4 high expression, which were inhibited by PAR2, Akt1, and HIF1α silencing. Rivaroxaban treatment inhibited PAR2/Akt/HIF1α signaling activation and Dll4 expression in FXa-exposed macrophages. By cell-to-cell contact, M1 macrophages induced Notch signaling activation in VSMCs which committed contractile-synthetic conversion. Rivaroxaban treatment and Dll4 silencing incapacitated macrophage in inducing phenotypic conversion of VSMCs upon cell-to-cell contact.Conclusion: Rivaroxaban suppresses AS by inhibiting FXa-induced PAR2/Akt/HIF1α signaling activation-mediated macrophage M1 polarization and high Dll4 expression. These macrophages facilitated VSMCs to perform contractile-synthetic phenotypic conversion upon macrophage-VSMCs cell-to-cell contact.

Fine-grained Named entity recognition (NER) is crucial to natural language processing (NLP) applications like relation extraction and knowledge graph construction. Most existing fine-grained NER systems suffer from inefficiency problem as they use manually annotated training datasets. To address such issue, our NER system could automatically generate datasets from Wikipedia in distant supervision paradigm through mapping hyperlinks in Wikipedia documents to Freebase. In addition, previous NER models can not effectively process fine-grained labels with more than 100 types. So we introduce a `BIO' tagging strategy which can identify the position and type attributes simultaneously. Such tagging scheme transfers NER problem into a sequence-to-sequence (seq2seq) based issue. We propose a seq2seq framework to comprehend the input sentence in a comprehensive way. Specifically, we adopt a Bi-LSTM as the encoder to equally process the past and future information of the input. Then we add a self-attention mechanism to handle the long-term dependency problem in a long sequence. When classifying the entity tags, we choose CRF model as it adds more constraints to avoid position logical problem. Experiments are performed on large-scale datasets for fine-grained NER tasks. Experimental results verify the effectiveness of FSeqC, and it outperforms other state-of-the-art alternatives consistently and significantly.

Introduction Glucose-induced insulin resistance is a typical character of diabetes. Nicorandil is now widely used in ischemic heart disease. Nicorandil shows protective effects against oxidative and endoplasmic reticulum (ER) stress, which are involved in insulin resistance. Here, we investigated mechanisms of nicorandil’s novel pharmacological activity on insulin resistance in diabetes.Research design and methods Nicorandil was administrated to streptozotocin-induced animals with diabetes and high glucose exposed skeletal muscle cells. Insulin resistance and glucose tolerance were evaluated. Molecular mechanisms concerning oxidative stress, ER stress signaling activation and glucose uptake were assessed.Results Nicorandil attenuated high glucose-induced insulin resistance without affecting fasting blood glucose and glucose tolerance in whole body and skeletal muscle in rats with diabetes. Nicorandil treatment suppressed protein kinase C/nicotinamide adenine dinucleotide phosphate oxidases system activities by reducing cytoplasmic free calcium level in skeletal muscle cells exposed to high glucose. As a result, the oxidative stress-mediated ER stress protein kinase RNA-like endoplasmic reticulum kinase (PERK)/eukaryotic initiation factor 2α/activating transcription factor 4/CEBP homologous protein/tribbles homolog (TRB)3 signaling pathway activation was inhibited. Nicorandil downregulated expression of TRB3 and thus facilitated Akt phosphorylation in response to insulin stimulation, leading to glucose transporter4 plasma membrane translocation which promoted glucose uptake capability of skeletal muscle cells.Conclusions By reducing cytoplasmic calcium, nicorandil alleviated high glucose-induced insulin resistance by inhibiting oxidative stress-mediated ER stress PERK pathway.

As a vital measure to obtain valuable information and intelligence, web news are flooding all corners of the Internet anytime, anywhere. Traditionally, templates or hand-designed features are utilized to extract the content from web pages, but these models have higher time cost and lower extensibility. Recently, many scholars leverage DOM-tree-based or text-density-based models to extract the contents which have better extensibility and lower time cost, but most of them are hard to extract the content accurately and completely and are easy to introduce the noises. In this paper, we propose a title-based web content extracting model TWCEM to extract the contents of each web page, which leverage the title information to extract the web content. Compared with other extraction model, TWCEM can filter the noises effectively and locate the content positions more accurately. In this experiment, we evaluate the proposed model on real-life websites, and TWCEM achieves state-of-the-art results and outperforms its competitors on both extraction performance and time cost.

The mechanical strength of spider silk is the highest among all natural fibers, and its flexibility is also excellent; this phenomenon can be explained geometrically, due to its hierarchical structure, the last cascade of which beginning with well-ordered macromolecules. The inner topological structure of a nanofiber plays an important role in controlling its functions, e.g., its mechanical, electrical and chemical properties. This paper shows that nanoparticles can be well-ordered in the electrospinning process as a result, the nanofibers’ properties can be adjusted. Some experiments are designed to verify our theoretical prediction.

Open domain relation prediction is an important task in triples extraction. When faced with the task of constructing large-scale knowledge graph systems, with the exception of structured data, it is necessary to automatically extract triples from a large amount of unstructured text to expand entities and relations. Although a large number of English open relation prediction methods have achieved good performance, the high-performance system for open domain Chinese triples extraction remains undeveloped due to the lack of large-scale Chinese annotation corpora and the difficulty of Chinese language processing. In this paper, we propose an integrated open domain Chinese triples hierarchical extraction method (CTHE) to solve this problem, considering the advantages of Bi-LSTM-CRF and Att-Bi-GRU models based on the pre-trained BERT encoding model. This method can recognize the named entities from Chinese sentences to establish entity pairs, and implement hierarchical extraction of specific and open relations based on the user-defined schema library and attention mechanism. The experimental results demonstrate the effectiveness of this method, which achieved stable performance on the test dataset, and better precision and F1-score in comparison with state-of-the-art Chinese open domain triples extraction methods. Furthermore, a large-scale annotated dataset for a Chinese named entity recognition (NER) task is established, which provides support for research on Chinese NER tasks.

Background: This study aims to investigate the association between nine tag single nucleotide polymorphisms (SNPs) in the C3 gene locus and the risk of coronary artery disease (CAD) as well as lipid levels in the Chinese population, and to further explore the interactions between SNPs and environmental factors that may be associated with CAD risk. Methods: A case-control study was conducted to investigate the association between CAD and C3 gene polymorphisms in a hospital setting. The study consisted of 944 CAD patients with a mean age of 55.97 ± 10.182 years and 897 non-CAD controls with a mean age of 55.94 ± 9.162 years. There were 565 males and 288 females in the CAD group and 583 males and 314 females in the control group. TagSNPs in the C3 gene were identified by employing the improved multiplex ligation detection reaction (iMLDR) technique, and multifactor dimensionality reduction (MDR) analysis was utilized to investigate the C3 gene–environment and gene-gene interactions in relation to the risk of CAD. Results: Results of the polymorphism study indicated that the CC genotype of rs7257062 was more frequent in the CAD group compared to the control group (10.9% vs 7.7%), with a statistically significant difference (p = 0.009). Moreover, the TT and CC + CT genotype groups of rs7257062 in the CAD subgroup showed a significant difference in terms of serum triglyceride levels (2.326 ± 1.889 vs 2.059 ± 1.447, p = 0.019). Analysis of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A (ApoA), and apolipoprotein B (ApoB) levels revealed no significant differences between the TT and CC + CT genotypes. Furthermore, no significant differences in serum lipid levels were observed between genotypes of the other SNPs. Multivariable logistic analysis, controlling for gender, age, body mass index (BMI), triglycerides (TG), TC, HDL-C, LDL-C, ApoA and ApoB, demonstrated that rs7257062 was still an independent risk factor of CAD (OR = 1.499, 95% CI: 1.036-2.168, p = 0.032). MDR analysis revealed that the rs7257062 interacted significantly with environmental factors such as smoking, diabetes, hypertension, BMI, and TG (p < 0.05). Conclusions: The rs7257062 variation of the C3 gene could be linked to both lipid balance and the risk of CAD. It is conceivable that the interplay between C3 polymorphisms and environmental elements could account for the etiology of CAD. [ABSTRACT FROM AUTHOR]