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Evidence shows that neutrophils can protect the host against pathogens in multiple ways, including the formation and release of neutrophil extracellular traps (NETs). NETs are web‐like structures composed of fibers, DNA, histones, and various neutrophil granule proteins. NETs can capture and kill pathogens, including bacteria, viruses, fungi, and protozoa. The process of NET formation is called NETosis. According to whether they depend on nicotinamide adenine dinucleotide phosphate (NADPH), NETosis can be divided into two categories: “suicidal” NETosis and “vital” NETosis. However, NET components, including neutrophil elastase, myeloperoxidase, and cell‐free DNA, cause a proinflammatory response and potentially severe diseases. Compelling evidence indicates a link between NETs and the pathogenesis of a number of diseases, including sepsis, systemic lupus erythematosus, rheumatoid arthritis, small‐vessel vasculitis, inflammatory bowel disease, cancer, COVID‐19, and others. Therefore, targeting the process and products of NETosis is critical for treating diseases linked with NETosis. Researchers have discovered that several NET inhibitors, such as toll‐like receptor inhibitors and reactive oxygen species scavengers, can prevent uncontrolled NET development. This review summarizes the mechanism of NETosis, the receptors associated with NETosis, the pathology of NETosis‐induced diseases, and NETosis‐targeted therapy. NETs are involved in the pathogenesis and progression of various diseases, such as sepsis, SLE, RA, SVV, IBD, cancer, and COVID‐19. Components of NETs may act as autoantigens, leading to inflammation and autoimmune diseases. In addition, some diseases aggravate NETosis and cause a vicious circle.

Sign language recognition technology can help people with hearing impairments to communicate with non-hearing-impaired people. At present, with the rapid development of society, deep learning also provides certain technical support for sign language recognition work. In sign language recognition tasks, traditional convolutional neural networks used to extract spatio-temporal features from sign language videos suffer from insufficient feature extraction, resulting in low recognition rates. Nevertheless, a large number of video-based sign language datasets require a significant amount of computing resources for training while ensuring the generalization of the network, which poses a challenge for recognition. In this paper, we present a video-based sign language recognition method based on Residual Network (ResNet) and Long Short-Term Memory (LSTM). As the number of network layers increases, the ResNet network can effectively solve the granularity explosion problem and obtain better time series features. We use the ResNet convolutional network as the backbone model. LSTM utilizes the concept of gates to control unit states and update the output feature values of sequences. ResNet extracts the sign language features. Then, the learned feature space is used as the input of the LSTM network to obtain long sequence features. It can effectively extract the spatio-temporal features in sign language videos and improve the recognition rate of sign language actions. An extensive experimental evaluation demonstrates the effectiveness and superior performance of the proposed method, with an accuracy of 85.26%, F1-score of 84.98%, and precision of 87.77% on Argentine Sign Language (LSA64).

The extensive usage and production of copper may lead to toxic effects in organisms due to its accumulation in the environment. Traditional methods for copper detection are time consuming and infeasible for field usage. It is necessary to discover a real-time, rapid and economical method for detecting copper to ensure human health and environmental safety. Here we developed a colorimetric paper strip method and optimized spectrum method for rapid detection of copper ion based on the specific copper chelator bathocuproinedisulfonic acid disodium salt (BCS). Both biological assays and chemical methods verified the specificity of BCS for copper. The optimized reaction conditions were 50 mM Tris–HCl pH 7.4, 200 µM BCS, 1 mM ascorbate and less than 50 µM copper. The detection limit of the copper paper strip test was 0.5 mg/L by direct visual observation and the detection time was less than 1 min. The detection results of grape, peach, apple, spinach and cabbage by the optimized spectrum method were 0.91 μg/g, 0.87 μg/g, 0.19 μg/g, 1.37 μg/g and 0.39 μg/g, respectively. The paper strip assays showed that the copper contents of grape, peach, apple, spinach and cabbage were 0.8 mg/L, 0.9 mg/L, 0.2 mg/L, 1.3 mg/L and 0.5 mg/L, respectively. These results correlated well with those determined by inductively coupled plasma-mass spectrometry (ICP-MS). The visual detection limit of the paper strip based on Cu-BCS-AgNPs was 0.06 mg/L. Our study demonstrates the potential for on-site, rapid and cost-effective copper monitoring of foods and the environment.

Background The purpose of this study was (a) to investigate the association between the potential anatomical risk factors and medial meniscus posterior root tears (MMPRTs), and (b) to determine the optimal cutoff values of risk factors for discriminating MMPRTs. Methods A retrospective study was conducted, from January 2018 to January 2020, 86 patients with MMPRTs identified by an experienced musculoskeletal radiologist using 3-T magnetic resonance imaging (MRI), and also confirmed during arthroscopic surgery were included in this study. Moreover, MMPRTs patients were matched with 128 patients with other types of medial meniscal tear knees at the same period according to patients’ demographics. We categorized the two patient groups into subgroups based on the causes of meniscus root tears. A subgroup analysis was performed to evaluate the parameter differences between traumatic and degenerative MMPRT in these groups. The associations between clinical and anatomic factors and MMPRTs were analyzed. Additionally, a logistic regression analysis was performed to detect risk factors correlated with MMPRTs. Results Based on the analysis, binary logistic regression models analysis indicated that medial posterior tibial slope (MTS) (odds ratio (OR) = 1.212, P  = 0.005), hip knee ankle (HKA) (OR = 1.657, P  < 0.001) and medial femoral condyle length/medial tibial plateau length (MFCL/MTPL) (OR = 16.597, P  = 0.019) were the risk factors correlated with MMPRTs. A subgroup analysis revealed that the MTS, HKA, and MFCL/MTPL were risk factors associated with traumatic MMPRTs. Additionally, age, MTS, HKA, and MFCL/MTPL were identified as risk factors linked to degenerative MMPRTs. Additionally, the receiver operating characteristic (ROC) curves demonstrated these factors had comparable accuracy at predicting MMPRTs (under the curve were 0.635, 0.700 and 0.627, respectively). The cutoff values of those factors were 7.4º, 2.4º, and 1.2, respectively. Conclusions Based on results from the current study, we identified MTS > 7.4º, HKA > 2.4º and MFCL/MTPL > 1.2 were the risk factors correlated with MMPRTs.

Background Polycystic ovary syndrome (PCOS) is an endocrine and metabolic disorder, and its pathogenesis is still under debate. Trimethylamine-N-oxide (TMAO) is a small, organic compound generated by the gut microbiome with a hypothesized relation to insulin resistance (IR) and low-grade inflammation in PCOS. By comparing plasma TMAO levels in non-PCOS participants and PCOS patients without hyperandrogenism (HA), we aimed to determine whether plasma TMAO levels correlate with PCOS without HA and to analyze their relationship with low-grade inflammation and IR. Methods A total of 27 PCOS patients without HA and 23 non-PCOS participants were enrolled in this study and subdivided into “nonobese” and “obese” arms for each group. Levels of plasma TMAO were quantified, and basic clinical characteristics and plasma biomarkers of inflammation were assessed. Results First, plasma TMAO levels, insulin levels and homeostatic model assessment of insulin resistance (HOMA-IR) values were higher in PCOS patients without HA, especially in the obese subgroup. Second, the levels of the inflammatory factors interleukin (IL)-17A, IL-18 and interferon gamma (IFN-γ) were significantly increased in obese PCOS patients without HA. Third, plasma TMAO levels were associated with body mass index (BMI) in the normal-weight groups, and the obese groups had higher fasting plasma insulin (FINS) and HOMA-IR values. Finally, logistic regression showed that the plasma levels of TMAO and luteinizing hormone/follicle-stimulating hormone (LH/FSH) were independent predictors of PCOS and indicated an increased risk of PCOS. Conclusions Elevated plasma TMAO levels may be associated with the pathogenesis of PCOS without HA and correlated with increased systemic inflammation. Further studies are needed to determine the suitability of TMAO as a predictive biomarker and to identify possible therapies for PCOS.

Background School bullying, a serious problem for the physical and mental health of adolescents, is presently a significant issue in China. It is essential to recognize and comprehend potential risk factors and establish efficient preventive strategies. The purpose of this study was to examine the association between childhood maltreatment and school bullying in adolescents and to assess the mediating role of peer relationships. Methods Between March and April 2024, a cross-sectional survey was conducted among 2119 adolescents aged between 12 and 18 years in Guangdong Province, China. Self-report questionnaires were employed to collect data on childhood maltreatment, school bullying, and peer relationships. Subgroup analyses and mediating effects modeling were employed to analyze the data. Results The results indicated that adolescents who had experienced maltreatment were more at risk of bullying victimization ( OR : 2.92, 95% CI : 2.34–3.64, P  < 0.001), bullying perpetration ( OR : 2.84, 95% CI : 1.99–4.05, P  < 0.001), and bully-victimization ( OR : 2.93, 95% CI : 1.95–4.41, P  < 0.001), compared to adolescents who have not. Sexual abuse showed the most significant connection with all forms of bullying. The mediating effect of peer relationships was found to mediate the association between child maltreatment and bullying behaviour. The results indicated that worse peer relationships may exacerbate the adverse effects of maltreatment experiences and increase the risk of adolescents becoming bullies, either perpetrators or victims of bullying. Conclusions Child maltreatment has been identified as one of the most significant influences on bullying behaviour in adolescents. The quality of peer relationships has been demonstrated to play an important role in preventing and reducing the occurrence of bullying. The results underscore the crucial role of early intervention in cases of child maltreatment and the fostering of positive peer relationships in schools.

Background Recurrent spontaneous abortion (RSA), is a dangerous pregnancy-related condition and is a subject of debate in the gynaecology and obstetrics communities. The objective of this study was to determine the function of DNA Topoisomerase II Alpha (TOP2A) in RSA and elucidate the underlying molecular mechanisms. Methods In vitro models of TOP2A-knockdown and -overexpression were generated by transfecting specific sh-RNA lentivirus and overexpression plasmid, respectively. An in vitro TOP2A inhibition model was established by culturing mouse embryos at the two-cell stage in a medium containing PluriSIn2, a TOP2A inhibitor. Immunohistochemical staining was used to analyse expression of TOP2A in villi tissues of patients with RSA. Western blotting and qRT-PCR were used to analyse the expression of TOP2A and proteins involved in trophoblast functions, the FOXO signalling pathway, and the development of pre-implantation embryos. 5-Ethynyl-2′-deoxyuridine staining, TUNEL assay and flow cytometry were used to further evaluate the effect of TOP2A on cell proliferation and apoptosis. Transwell and wound healing assays were used to evaluate migration and invasion. Moreover, the effect of TOP2A inhibitor on embryos was determined by immunofluorescence and mitochondrial-related dyes. Results Evaluation of clinical samples revealed that the villi tissues of patients that have experienced RSA had lower TOP2A expression compared with that from women who have experienced normal pregnancy ( P  <  0.01 ). In vitro, TOP2A knockdown decreased the proliferation, migration, and invasion of trophoblast cell lines, and increased apoptosis and activation of the FOXO signalling pathway ( P  <  0.05 ). Conversely, TOP2A overexpression reversed these effects. Moreover, in vivo experiments confirmed that inhibition of TOP2A impairs trophectoderm differentiation, embryonic mitochondrial function as well as the developmental rate; however, no differences were noted in the expression of zygotic genome activation-related genes. Conclusions Collectively, our data suggest that lower TOP2A expression is related to RSA as it inhibits trophoblast cell proliferation, migration, and invasion by activation of the FOXO signalling pathway. Additionally, TOP2A inhibition resulted in impaired development of pre-implantation embryos in mice, which could be attributed to excessive oxidative stress. Graphical Abstract

Asphalt overlay is widely used in maintaining and rehabilitating highway system performance. However, explicit calculation methods for the asphalt overlay thickness range is lacking. Taking stone mastic asphalt (SMA) and asphalt concrete (AC) asphalt overlay on cement concrete pavement as examples, the paper proposed a design method for the asphalt overlay thickness range based on the shear performance of the interlayer. Firstly, the shear stress distribution regularities on the asphalt overlay and Portland cement concrete interlayer was calculated with a multilayer elastic theory. Meanwhile, the shear strength was obtained from a series of direct shear tests. The shear characters of the asphalt overlay met with the Mohr–Coulomb criterion, and the shear strength parameters cohesive force c and interface friction angle φ on the interlayer were acquired. Finally, a method for determining the thickness range of double layer asphalt overlay under different traffic conditions was given. The epoxy resin adhesive was recommended for the highway with severe local premature shear failure compared with the modified emulsion asphalt. Therefore, through the above research, the amount of asphalt used is controlled in a reasonable range, thus improving the pavement structure durability and reducing energy consumption.

Condenser heat transfer parameters serve as critical indicators for assessing the operational status of condensers. However, these parameters cannot be directly obtained through measurement or inferred solely from condenser characteristic curves, which limits their practical applicability in performance monitoring. To overcome this limitation, we develop a parameter identification method for condenser heat transfer models based on an improved flower pollination algorithm (FPA). Specifically, a condenser heat transfer model is first formulated, and a fitness function is defined to guide the optimization process. On this basis, three enhancement strategies are introduced: a dynamic pollination probability mechanism, a chaotic initialization scheme, and an elite pollen mutation-crossover operator. These improvements are designed to address inherent shortcomings of the classical FPA, including its tendency to converge prematurely to local optima and its limited fitting performance. Comparative experiments conducted on real operational datasets demonstrate that the proposed improved FPA achieves significantly higher parameter identification accuracy and superior model fitting compared with the classical FPA.

In order to study the temperature distribution in a multi-functional oven and optimize the structural parameters of the oven, the internal temperature uniformity was improved. The test was conducted and the numerical simulation was conducted in two ways. The distribution of temperature field in each layer of ovens was measured in real time using a 13-point distributed thermocouple, and the oven temperature uniformity index was measured and analyzed. The temperature field inside the oven was numerically simulated using computational fluid dynamics. Investigated the heat conduction, convection and radiation effects respectively, and found out the main heat transfer mode of the oven. Further through the test of temperature measurement, verify the accuracy of the numerical simulation method. According to the results of the experiment and simulation, the reason of the uneven temperature field in the original structure of the oven was revealed and analyzed. By changing the structure of the oven tailgate, adjusting the air volume distribution, changing the distribution of the air outlet and other measures, greatly improving the uniformity of the temperature field inside the oven.