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Abstract Two‐dimensional (2D) semiconductors, such as monolayer MoS2, has emerged as a profound material platform in the post‐Moore era due to their versatile applications for high‐performance transistors, memories, photodetectors, neuristors, and so on. Nevertheless, the inherent defects in these atomically thin materials have given rise to significant hysteresis in their field‐effect transistors (FETs), resulting in shifted threshold voltages and elevated power consumptions not only on single‐device levels but also at circuitry scales. We herein report that, by vertically integrating an in‐plane ferroelectric, NbOCl2, with monolayer MoS2 FETs, the hysteresis in both the output and transfer curves of the latter can be greatly suppressed, which we attribute to compensated electromigration currents by the polarization currents of the 2D ferroelectric. This work opens a new avenue to hysteresis‐free 2D transistors without necessitating defect‐free channels, thus allowing for their use in high driving‐voltage scenarios such as power electronics.

The WRKY transcription factors comprise one of the most extensive gene families and serve as pivotal regulators of plant responses to heavy metal stress. They contribute significantly to maintaining plant growth and development by enhancing plant tolerance. However, research on the role of WRKY genes in response to cadmium (Cd) stress in mustard is minimal. In this study, we conducted a genome-wide analysis of the mustard WRKY gene family using bioinformatics. The results revealed that 291 WRKY putative genes (BjuWRKYs) were identified in the mustard genome. These genes were categorized into seven subgroups (I, IIa-e and III) through phylogenetic analysis, with differences in motif composition between each subgroup. Homology analysis indicated that 31.62% of the genes originated from tandem duplication events. Promoter analysis revealed an abundance of abiotic stress-related elements and hormone-related elements within the BjuWRKY genes. Transcriptome analysis demonstrated that most BjuWRKY genes exhibited differential expression patterns at different Cd treatment stages in mustard. Furthermore, 10 BjuWRKY genes were confirmed to respond to Cd stress through the construction of a BjuWRKY protein interaction network, prediction of hub genes, and real-time fluorescence quantitative PCR analysis, indicating their potential involvement in Cd stress. Our findings provide a comprehensive insight into the WRKY gene family in mustard and establish a foundation for further studies of the functional roles of BjuWRKY genes in Cd stress response.

To examine the impact of in situ water maceration in macerating ponds on the degumming process and fiber quality of freshly kenaf and jute whole plants. Different kenaf/jute fresh samples (whole plant, bast fresh hides) were subjected to distinct maceration treatments: padded film + cover film, cover film only, and no film. Water temperature, degumming bacterial colony counts, and fiber quality were assessed. Results revealed that composting pools with padded film + cover film maintained the highest water temperature. For colony count, padded film + cover film treatment displayed the highest colony count for kenaf, and no film treatment had the highest for jute. Kenaf whole fresh rods treated with padded film + cover film and cover film alone demonstrated the highest fiber strengths at 489.01 N and 494.85 N, respectively. Jute whole fresh rods macerated in padded film + cover film achieved the greatest strength at 392.32 N. Comparisons of fresh fiber strength between whole fresh rod and bastshowed a maximum difference of 150.69 N (kenaf) and 152.88 N (jute). Comprehensive analysis concluded, that the most effective degumming method involved using the whole fresh rods of red hemp/jute in maceration ponds equipped with padded film + cover film.

Numerous social media platforms have evolved into fertile grounds for the proliferation of irrational information, expanding the avenues of information dissemination. This paper initially utilized the Weibo and Bilibili social platforms as exemplars and devised a cross-platform two-layer network SEIaIbR-FXYaYbZ dissemination model grounded in classical infectious disease models. Subsequently, this research computed the model equilibrium point, basic reproduction number, and information entropy through dynamic equations. Finally, the model equations were fitted to real cases to determine optimal parameter solutions and conduct simulation analysis. The simulation results reveal that: (i) information entropy values on both platforms are low, with irrational information predominantly influencing public opinion; (ii) concerning various types of information, the augmentation of rational information results in a reduction of irrational information, while the quantity of rational information remains largely unaffected by changes in the quantity of irrational information; (iii) examining different platforms for information dissemination, alterations in the circulation rate and quantity of rational information on the Weibo platform impact the quantity of rational and irrational information on the Bilibili platform, while those changes on the Bilibili platform exert minimal influence on public opinion information on the Weibo platform. The results and corresponding strategies obtained from this study on the cross-platform dissemination of rational and irrational information on Weibo and Bilibili can provide a reference for relevant departments to guide the rational development of online information and enhance the effective management of public opinion in social media platforms.

Generalized Pareto distribution (GPD), an asymmetrical distribution, primarily models exceedances over a high threshold in many applications. Within the peaks-over-threshold (POT) framework, we consider a new GPD parameter estimation method to estimate a common tail risk measure, the value at risk (VaR). The proposed method is more suitable for the POT framework and makes full use of data information. Specifically, our estimation method builds upon the generalized probability weighted moments method and integrates it with the nonlinear weighted least squares method. We use exceedances for the GPD, minimizing the sum of squared differences between the sample and population moments of a function of GPD random variables. At the same time, the proposed estimator uses three iterations and assigns weight to further improving the estimated performance. Under Monte Carlo simulations and with a real heavy-tailed dataset, the simulation results show the advantage of the newly proposed estimator, particularly when VaRs are at high confidence levels. In addition, by simulating other heavy-tailed distributions, our method still exhibits good performance in estimating misjudgment distributions.

With the economic and social development of China, the scale of the power grid continues to expand. Rapid location and diagnosis of power failures have become significant for China to maintain its stable development of power system. In recent years, the Internet of Things (IoT) based on 5G technology has been applied to power grid more widely. Meanwhile, given the fact that the blockchain is traceable and tamper-resistant, the combination of the blockchain and IoT is considered to locate power failures quickly and assist professional maintenance personnel to deduce the cause of failures, minimizing economic loss. With the foundation of IoT sensor node data, this paper designs a decentralized electronic certificate scheme based on blockchain and Interplanetary File System (IPFS) to collect data of each node of the power system and store it in the blockchain. The model of data sharding, storage and certificate optimizes the utilization of storage space of the blockchain, reducing the time required for system access to nodes. Traceability of data stored on blockchain data is employed to quickly and accurately trace faults of the power system, providing strong technical support for the safe and stable operation of China’s power system.

An analysis of the evolution of urban three-dimensional morphology (EUTM) can comprehensively explore the processes and mechanisms of urban evolution and provide a basis for urban design and land use administration. Based on the three-dimensional model of urban built-up areas in two periods, this paper establishes a quantitative index system for the EUTM and discusses the methods of generating isoline maps for each index. The idea of making integrated partition map of urban three-dimensional morphology is developed according to a multidimensional feature space classification method. A quantitative analysis of the EUTM in Nanjing is carried out by using two types of maps.

With the continuous development of economy and society, power demand forecasting has become an important task of the power industry. Accurate power demand forecasting can promote the operation and development of the power supply industry. However, since power consumption is affected by a number of factors, it is difficult to accurately predict the power demand data. With the accumulation of data in the power industry, machine learning technology has shown great potential in power demand forecasting. In this study, gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost) and light gradient boosting machine (LightGBM) are integrated by stacking to build an XLG-LR fusion model to predict power demand. Firstly, preprocessing was carried out on 13 months of electricity and meteorological data. Next, the hyperparameters of each model were adjusted and optimized. Secondly, based on the optimal hyperparameter configuration, a prediction model was built using the training set (70% of the data). Finally, the test set (30% of the data) was used to evaluate the performance of each model. Mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and goodness-of-fit coefficient (R^2) were utilized to analyze each model at different lengths of time, including their seasonal, weekly, and monthly forecast effect. Furthermore, the proposed fusion model was compared with other neural network models such as the GRU, LSTM and TCN models. The results showed that the XLG-LR model achieved the best prediction results at different time lengths, and at the same time consumed the least time compared to the neural network model. This method can provide a more reliable reference for the operation and dispatch of power enterprises and future power construction and planning.

Air pollution is a major global problem, closely related to economic and social development and ecological environment construction. Air pollution data for most regions of China have a close correlation with time and seasons and are affected by multidimensional factors such as meteorology and air quality. In contrast with classical peaks-over-threshold modeling approaches, we use a deep learning technique and three new dynamic conditional generalized Pareto distribution (DCP) models with weather and air quality factors for fitting the time-dependence of the air pollutant concentration and make statistical inferences about their application in air quality analysis. Specifically, in the proposed three DCP models, a dynamic autoregressive exponential function mechanism is applied for the time-varying scale parameter and tail index of the conditional generalized Pareto distribution, and a sufficiently high threshold is chosen using two threshold selection procedures. The probabilistic properties of the DCP model and the statistical properties of the maximum likelihood estimation (MLE) are investigated, simulating and showing the stability and sensitivity of the MLE estimations. The three proposed models are applied to fit the PM2.5 time series in Beijing from 2015 to 2021. Real data are used to illustrate the advantages of the DCP, especially compared to the estimation volatility of GARCH and AIC or BIC criteria. The DCP model involving both the mixed weather and air quality factors performs better than the other two models with weather factors or air quality factors alone. Finally, a prediction model based on long short-term memory (LSTM) is used to predict PM2.5 concentration, achieving ideal results.

Purpose. To report baseline information of a prediabetes mellitus (PDM) cohort with the aim of exploring related factors for the progression of PDM and its complications. Methods. This study is an exploratory and cross-sectional analysis of the baseline data from a cohort study. Residents aged 18 to 70 years from Houtang Village, Nanyue Town, Yueqing City, Zhejiang Province, China, were invited to participate between October 1, 2018 and July 1, 2019. Blood samples were collected for analysis, and questionnaire interviews were conducted to assess behavioral characteristics. The study participants were divided into DM, PDM, and normal groups for comparisons based on their blood work, and multiple multinomial logistic regression analyses were used to assess the risk factors for DM and PDM. Results. Data from 406 participants were used in the baseline analysis, with a mean age of 51.2 ± 11.0 years and 160 (33.0%) males. The number of participants in the DM, PDM, and normal group was 58 (14.3%), 166 (40.9%), and 182 (44.8%), respectively. The prevalence of DM was 14.3%, and the prevalence of PDM was 40.9%. The regression analysis showed that older age (relative risk ratio (RRR) = 1.06; 95% CI, 1.01–1.11, P=0.018), higher systolic blood pressure (RRR = 1.04; 95% CI, 1.004–1.08, P=0.030), higher BMI (RRR = 1.20; 95% CI, 1.06–3.06, P=0.004), higher TG (RRR = 1.80; 95% CI, 1.06–3.06, P=0.029), and higher WBC count (RRR = 1.32; 95% CI, 1.07–1.64, P=0.010) were significantly associated with a higher risk of DM. Meanwhile, higher systolic blood pressure (RRR = 1.03; 95% CI, 1.004–1.06, P=0.025) was the only factor significantly associated with a higher risk of PDM. Conclusion. The prevalence of DM and PDM is relatively high in this wealthy East China village population. Many modifiable risk factors exist for DM and PDM, which will be closely monitored during our longitudinal observation.

At the end of 2019, an outbreak of the novel coronavirus (COVID-19) made a profound impact on the country’s production and people’s daily lives. Up until now, COVID-19 has not been fully controlled all over the world. Based on the clinical research progress of infectious diseases, combined with epidemiological theories and possible disease control measures, this paper establishes a Susceptible Infected Recovered (SIR) model that meets the characteristics of the transmission of the new coronavirus, using the least square estimation (LSE) method to estimate the model parameters. The simulation results show that quarantine and containment measures as well as vaccine and drug development measures can control the spread of the epidemic effectively. As can be seen from the prediction results of the model, the simulation results of the epidemic development of the whole country and Nanjing are in agreement with the real situation of the epidemic, and the number of confirmed cases is close to the real value. At the same time, the model’s prediction of the prevention effect and control measures have shed new light on epidemic prevention and control.

High-volume, low-cost production of graphene is pivotal for the industrial advance of this 2D material. Here, the authors make use of naturally occurring diatomite as a 3D substrate for graphene growth, obtaining non-planar porous graphene structures after removal of the silica templates.

This study investigated the use of hands-on learning video assignments (HLVAs) among middle school students in China during and after the COVID-19 pandemic. Based on the results of HLVAs approach with seventh grade students at Jiefang Road School during the online learning phase, one class was selected to participate in an offline empirical, longitudinal study to further explore the impact of HLVAs approach on students' biology learning. Two data collection instruments were used: hands-on learning students' work evaluation instrument and model competence development instrument to detect changes in students' modeling development. Questionnaire responses from the students in the experimental class two years later, when they were in high school, offer additional perspectives on this approach. Findings indicated that HLVAs approach improves students' work quality, modeling skills, and biology learning outcomes. This study describes hands-on learning strategy based on embodied cognition theoretical perspectives, with implications for curriculum, instruction, and learning. [ABSTRACT FROM AUTHOR]

Abstract Background Currently, there is a lack of research on multi-drug resistant Pseudomonas aeruginosa (MDR-PA) isolation in bronchiectasis-related hemoptysis. The aim of this study to analyze the risk factors for recurrent hemoptysis following bronchial artery embolization (BAE) and compare the recurrent hemoptysis-free rates between MDR-PA, non-MDR-PA, and non-PA isolation. Methods A retrospective study was performed of patients diagnosed with idiopathic bronchiectasis-related recurrent hemoptysis who underwent BAE at an university-affiliated hospital. Patients were categorized based on PA susceptibility tests into non-PA, non-MDR-PA, and MDR-PA groups. Univariate and multivariate Cox regression were conducted to identify independent risk factors for recurrent hemoptysis. The Kaplan-Meier curves was conducted to compare recurrent hemoptysis-free rates after BAE for non-PA, non-MDR-PA, and MDR-PA. Results A total of 432 patients were included. 181 (41.90%) patients experienced recurrent hemoptysis during a median follow-up period of 25 months. MDR-PA isolation (adjusted hazard ratio (aHR) 2.120; 95% confidence interval (CI) [1.249, 3.597], p = 0.005) was identified as an independent risk factor for recurrent hemoptysis. Antibiotic treatment (aHR 0.666; 95% CI [0.476, 0.932], p = 0.018) reduced the risk of recurrent hemoptysis. The cumulative recurrent hemoptysis-free rates for non-PA, non-MDR-PA, and MDR-PA were as follows: at 3 months, 88.96%, 88.24%, and 75.86%, respectively; at 1 year, 73.13%, 69.10%, and 51.72%; and at 3 years, 61.91%, 51.69%, and 41.10% (p = 0.034). Conclusion MDR-PA isolation was an independent risk factor of recurrent hemoptysis post-BAE. Reducing the occurrence of MDR-PA may effectively decrease the recurrence rates of hemoptysis.

Abstract Background The activation of endoplasmic reticulum (ER) stress is an early pathological hallmark of Alzheimer’s disease (AD) brain, but how ER stress contributes to the onset and development of AD remains poorly characterized. Mesencephalic astrocyte-derived neurotrophic factor (MANF) is a non-canonical neurotrophic factor and an ER stress inducible protein. Previous studies reported that MANF is increased in the brains of both pre-symptomatic and symptomatic AD patients, but the consequence of the early rise in MANF protein is unknown. Methods We examined the expression of MANF in the brain of AD mouse models at different pathological stages. Through behavioral, electrophysiological, and neuropathological analyses, we assessed the level of synaptic dysfunctions in the MANF transgenic mouse model which overexpresses MANF in the brain and in wild type (WT) mice with MANF overexpression in the hippocampus. Using proteomic and transcriptomic screening, we identified and validated the molecular mechanism underlying the effects of MANF on synaptic function. Results We found that increased expression of MANF correlates with synapse loss in the hippocampus of AD mice. The ectopic expression of MANF in mice via transgenic or viral approaches causes synapse loss and defects in learning and memory. We also identified that MANF interacts with ELAV like RNA-binding protein 2 (ELAVL2) and affects its binding to RNA transcripts that are involved in synaptic functions. Increasing or decreasing MANF expression in the hippocampus of AD mice exacerbates or ameliorates the behavioral deficits and synaptic pathology, respectively. Conclusions Our study established MANF as a mechanistic link between ER stress and synapse loss in AD and hinted at MANF as a therapeutic target in AD treatment.

With the development of China's economic level and improving people's living standards, the state's supervision of food health and safety has increased. Consumer demand for many people has gradually changed from being satiated to eating well, and high-quality, environmentally friendly, and healthy aquatic products have become increasingly popular with consumers. However, intensive and high-density aquaculture causes the deterioration of water environmental conditions, the increase of anti-nutrient factors and nutritional imbalance caused by the replacement of animal protein with plant protein in feed, and changes in the growth, immunity, and digestive ability of aquatic animals caused by changes in feed nutrients, traditional processing methods, and transportation stress. The above situations encountered in aquaculture have a common impact on aquatic animals and inevitably cause a reduction in the muscle quality of aquatic animals. Therefore, improving the muscle quality of aquatic animals and the quality of aquatic products is an urgent problem with significant research value and potential.To improve aquatic quality, first, it is necessary to first identify the indicators of muscle quality in aquatic animals to improve aquatic quality. However, there is still a lack of a systematic muscle quality evaluation index system in the current aquaculture research. Therefore, this study reviewed the evaluation indices of muscle quality, including meat content, muscle nutrient composition, muscle fiber structure, muscle texture characteristics, and muscle physicochemical indices, to provide a reference for establishing scientific muscle quality evaluation indices. In addition, factors affecting muscle quality must be considered in studies aimed at improving the muscle quality of aquatic animals. Only by understanding the factors affecting muscle quality in aquatic animals can the key factors regulating muscle quality and their mechanisms be studied more comprehensively and scientifically. This study reviewed the factors affecting the muscle quality of aquatic animals, including feed nutrients, feed additives, and the culturing environment, and found that nutrients are key factors in improving the muscle quality of aquatic animals.Protein is an important nutrient, the main component of muscle, and an important indicator of muscle quality. Amino acids are the basic units of proteins and have a vital impact on muscle quality and flavor. Therefore, it is important to study the effects and mechanisms of action of amino acids on muscle quality in aquatic animals. Therefore, the effects of dietary amino acids on the muscle quality of aquatic animals were reviewed in this study, including the effects of amino acids on muscle nutrients, flavor, texture indices, and physical and chemical properties of aquatic animals. Furthermore, the effects of amino acids on muscle quality, including the promotion of protein synthesis, regulation of fat deposition, enhancement of antioxidant activity, and maintenance of intestinal health, were reviewed.In summary, this study summarized the influence of amino acids on the muscle quality of aquatic animals and its mechanism from the aspects of muscle quality evaluation indices, factors affecting meat quality, and the influence of amino acids on muscle quality, providing a reference for further research on the regulation of muscle quality by amino acids and the improvement of feed nutrients on the meat quality of aquatic animals.

Objectives: To evaluate the efficacy and safety of acupuncture combined with five-element music (FEM) as an therapeutic strategy for the physical and mental state of Post-stroke depression patients. Design and setting: Multicenter, randomized clinical trial conducted at 3 hospitals in China and enrolling 237 patients with PSD between June 2019 and April 2021. Participants mild/moderate PSD (17-item GRID Hamilton Depression Scale (HAMD) score 7–24) were randomly assigned (1:1) to acupuncture combined with FEM (AFEM) group or cognitive behavioral therapy (CBT) group. Main outcome measures: The primary outcome was change and differences between the groups in HAMD-17 from baseline to week 12. Secondary outcomes included Fugl-Meyer Assessment Scale score and Stroke-Specific Quality of Life Scale (SS-QOL) score. Results: The 237 patients in this intention-to-treat analysis were randomized into either the AFEM group (n=119) or the cognitive behavioral therapy (CBT) group (n=118). Of these 237 participants, 225 (94.9 %) completed all outcome measurements at week 12. The AFEM and CBT groups both showed significant improvement in HAMD-17 from baseline to week 12. Patients in the AFEM group had significantly lower HAMD-17 scores of −3.56 at week 8 (95 % CI,-4.59 to −2.53; p

Abstract With the rapid development of advanced technologies in the Internet of Things era, higher requirements are needed for next‐generation electronic devices. Fortunately, organic thin film transistors (OTFTs) provide an effective solution for electronic skin and flexible wearable devices due to their intrinsic features of mechanical flexibility, lightweight, simple fabrication process, and good biocompatibility. So far considerable efforts have been devoted to this research field. This article reviews recent advances in various promising and state‐of‐the‐art OTFTs as well as related integrated circuits with the main focuses on: (I) material categories of high‐mobility organic semiconductors for both individual transistors and integrated circuits; (II) effective device architectures and processing techniques for large‐area fabrication; (III) important performance metrics of organic integrated circuits and realization of digital and analog devices for future smart life; (IV) applicable analytical models and design flow to accelerate the circuit design. In addition, the emerging challenges of OTFT‐based integrated circuits, such as transistor uniformity and stability are also discussed, and the possible methods to solve these problems at both transistor and circuit levels are summarized.

IntroductionHumanization is typically adopted to reduce the immunogenicity of murine antibodies generated by hybridoma technology when used in humans.MethodsTwo different strategies of antibody humanization are popularly employed, including “complementarity determining region (CDR) grafting” and “framework (FR) shuffling” to humanize a murine antibody against human programmed death-1 (PD-1), XM PD1. In CDR-grafting humanization, the CDRs of XM PD-1, were grafted into the human FR regions with high homology to the murine FR counterparts, and back mutations of key residues were performed to retain the antigen-binding affinities. While in FR-shuffling humanization, a combinatorial library of the six murine CDRs in-frame of XM PD-1 was constructed to a pool of human germline FRs for high-throughput screening for the most favorable variants. We evaluated many aspects which were important during antibody development of the molecules obtained by the two methods, including antibody purity, thermal stability, binding efficacy, predicted humanness, and immunogenicity, along with T cell epitope prediction for the humanized antibodies.ResultsWhile the ideal molecule was not achieved through CDR grafting in this particular instance, FR-shuffling proved successful in identifying a suitable candidate. The study highlights FR-shuffling as an effective complementary approach that potentially increases the success rate of antibody humanization. It is particularly noted for its accessibility to those with a biological rather than a computational background. DiscussionThe insights from this comparison are intended to assist other researchers in selecting appropriate humanization strategies for drug development, contributing to broader application and understanding in the field.

Currently, most of the ultra-high-dimensional feature screening methods for categorical data are based on the correlation between covariates and response variables, using some statistics as the screening index to screen important covariates. Thus, with the increasing number of data types and model availability limitations, there may be a potential problem with the existence of a class of unimportant covariates that are also highly correlated with the response variable due to their high correlation with the other covariates. To address this issue, in this paper, we establish a model-free feature screening procedure for binary categorical response variables from the perspective of the contribution of features to classification. The idea is to introduce the Jensen-Shannon divergence to measure the difference between the conditional probability distributions of the covariates when the response variables take on different values. The larger the value of the Jensen-Shannon divergence, the stronger the covariate's contribution to the classification of the response variable, and the more important the covariate is. We propose two kinds of model-free ultra-high-dimensional feature screening methods for binary response data. Meanwhile, the methods are suitable for continuous or categorical covariates. When the numbers of covariate categories are the same, the feature screening is based on traditional Jensen-Shannon divergence. When the numbers of covariate categories are different, the Jensen-Shannon divergence is adjusted using the logarithmic factor of the number of categories. We theoretically prove that the proposed methods have sure screening and ranking consistency properties, and through simulations and real data analysis, we demonstrate that, in feature screening, the approaches proposed in this paper have the advantages of effectiveness, stability, and less computing time compared with an existing method.

Abstract Background Despite the relationship between Adverse childhood experiences (ACEs) and depressive symptoms, which has been well researched in general populations, little is known about homosexual and bisexual populations, especially lesbian and bisexual women in China. This study aims to investigate the prevalence of ACEs and depressive symptoms and to analyze the relationship between them among lesbian and bisexual women in China. Methods The eligible participants were aged 16 years or older who report their sexual orientation as homosexual or bisexual. The data was collected through anonymous questionnaires with the help of Lespark in Beijing from July 18 to December 29, 2018, and all participants had informed consent to this study. Univariate analysis and multiple linear regression analyses were performed to explore the relationship between ACEs and depressive symptoms among lesbian and bisexual women. All statistical analyses were conducted by the software of SPSS 22.0. Results Among 301 lesbian and bisexual women, 81.4% were lesbian, 18.4% were bisexual women, and the majority were 21–30 years. As for ACEs, 51.5% reported at least one ACE, in which emotional neglect (22.6%) and emotional abuse (22.3%) were common ACEs. As for depressive symptoms of lesbian and bisexual women, the detection rate was 56.1%. The multiple linear regression analyses showed that abuse (β = 2.95, 95%CI:1.07–4.83) and neglect (β = 3.21, 95%CI:1.09–5.31) were positively associated with depressive symptoms and lesbian and bisexual women with three (β = 4.11, 95%CI: 0.99–7.22) or more (β = 6.02, 95%CI: 3.23–8.78) ACEs suffered from more depressive symptoms than others. Conclusion Adverse childhood experiences (ACEs) and depressive symptoms were at high prevalence among lesbian and bisexual women in China. ACEs were associated with depressive symptoms, especially childhood abuse and neglect experiences that have a significant effect on lesbian and bisexual women mental health.

Background: Chronic rhinosinusitis (CRS) is a heterogeneous disease characterized by persistent sinonasal inflammation and sinus microbiome dysbiosis. Nasal polyps (NPs) are one of the main manifestations that cause diverse clinical symptoms of CRS. Objective: We sought to conduct a bibliometric and visual analysis of articles on CRS and NPs published between 2003 and 2022 to provide researchers with the current state of research and potential directions. Methods: We searched relevant articles from 2003 to 2022 in the Web of Science database. VOSviewer and the Bibliometrix R package were used to perform the bibliometric analysis. Results: A total of 3907 publications were retrieved. The United States made the highest contributions to global research, followed by China. Northwestern University had the most publications. The most published author was C. Bachert, followed by R. P. Schleimer and R. J. Schlosser. The authors with the most co-citations were C. Bachert, W. J. Fokkens, and P. Gevaert. Moreover, the journal with the most publications was the International Forum of Allergy & Rhinology, and the Journal of Allergy and Clinical Immunology was the most cited. “Covid-19,” “biologics,” and “type 2 inflammation” were the top current research hotspots. Conclusions: The United States and Northwestern University were the leading country and institution in researching CRS and NPs. C. Bachert was the most influential expert. The International Forum of Allergy & Rhinology and the Journal of Allergy and Clinical Immunology were leading journals. “Covid-19,” “biologics,” and “type 2 inflammation” were the trending topics.

Background: The guidelines for treating chronic spontaneous urticaria (CSU) recommend using the IgE-targeted biologic omalizumab in patients with antihistamine-refractory disease. Objective: Our aim was to present a bibliometric review of publications related to omalizumab and CSU over the past 2 decades. Methods: Relevant publications from 2003 to 2022 were extracted from the Science Citation Index-Expanded (SCI-EXPANDED) database in the Web of Science Core Collection database as of January 8, 2023. We utilized CiteSpace (version 6.1.R3), VOSviewer (version 1.6.18), and the R package (version 4.2.1) to analyze and visualize the data. The R package bibliometrix (version 4.2.1) was also used. Results: Between 2003 and 2022, a total of 566 articles on omalizumab and CSU were published. Since 2014, there has been a rapid increase in publication output. According to the collaboration network, the most influential country, institute, and scholar were the United States, Charité Universitätsmedizin Berlin, and Marcus Maurer, respectively. The study identified the Journal of Allergy and Clinical Immunology: In Practice as the most productive journal and the Journal of Allergy and Clinical Immunology as the most cocited journal. The analysis of key words revealed the presence of high-frequency terms such as angioedema, IgE, treatment, anti-IgE, asthma, and atopic dermatitis. Moreover, recent studies in this area have concentrated mainly on biomarkers, dupilumab, and coronavirus 2019 (COVID-19). Conclusion: There has been a growing interest in the use of omalizumab in CSU in recent years. The current trending topics in this research are the identification of biomarkers and the development of new mAbs for the treatment of CSU.

IntroductionPhysical and mental health problems among pilots affect their working state and impact flight safety. Although pilots’ physical and mental health problems have become increasingly prominent, their health has not been taken seriously. This study aimed to clarify challenges and support needs related to psychological and physical health among pilots to inform development of a more scientific and comprehensive physical and mental health system for civil aviation pilots.MethodsThis qualitative study recruited pilots from nine civil aviation companies. Focus group interviews via an online conference platform were conducted in August 2022. Colaizzi analysis was used to derive themes from the data and explore pilots’ experiences, challenges, and support needs.ResultsThe main sub-themes capturing pilots’ psychological and physical health challenges were: (1) imbalance between family life and work; (2) pressure from assessment and physical examination eligibility requirements; (3) pressure from worries about being infected with COVID-19; (4) nutrition deficiency during working hours; (5) changes in eating habits because of the COVID-19 pandemic; (6) sleep deprivation; (7) occupational diseases; (8) lack of support from the company in coping with stress; (9) pilots’ yearly examination standards; (10) support with sports equipment; (11) respecting planned rest time; and (12) isolation periods.DiscussionThe interviewed pilots experienced major psychological pressure from various sources, and their physical health condition was concerning. We offer several suggestions that could be addressed to improve pilots’ physical and mental health. However, more research is needed to compare standard health measures for pilots around the world in order to improve their physical and mental health and contribute to overall aviation safety.