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Abstract Introduction Anxiety and depression often co-occur in adolescents, with factors from family and school playing a significant role in the comorbidity. However, network analysis has not examined and clarified the detailed bridge and central symptoms of this comorbidity caused by online learning and perceived parental relationships across different COVID-19 times. Methods Over four months, 2,356 secondary school students completed the Patient Health Questionnaire-9 and Generalized Anxiety Disorder Scale-7. Participants were divided into harmonious and disharmonious groups based on their answers to a question about parental conflicts. Results The results indicated that adolescents perceiving more parental conflicts showed a denser comorbidity network after four months of online learning. Significant bridge symptoms decreased from three to two across two waves in the harmonious group, while in the disharmonious group, they increased from two to three. The number of central symptoms increased from one in wave 1 to three in wave 2 for the harmonious group, while four in wave 1 decreased to two in wave 2 for the disharmonious group. Furthermore, the CLPN analysis revealed that the strongest positive cross-lagged edge intensity between symptoms was anhedonia—energy in the harmonious group, with anhedonia being the most trigger symptom. In contrast, for the disharmonious group, guilt—suicide and trouble relaxing—excessive worry were the strongest cross-lagged edge, and trouble relaxing was the most trigger symptom. Conclusion These findings may have implications for interventions designed to promote adolescent mental health in the context of online learning and parental conflicts.

Abstract Background Nursing students are faced with multiple challenges and have a higher probability of suffering from anxiety. The current study aims to explore the relation between empathy and anxiety, examining the mediation and moderation effects of insomnia and self-compassion, respectively. Methods This study employed a convenient sampling method, recruiting 1,161 nursing students (female = 923, male = 238, Meanage = 18.37, SDage = 2.38) from three universities in China. These students completed the questionnaires online, including General Anxiety Disorder -7 (GAD-7), Jefferson Scale of Physician Empathy-Nursing student (JSPE-NS), Youth Self-rating Insomnia Scale -8 (YSIS-8), and Self-Compassion Scale (SCS). The study employed latent variable structural equation models to analyze the relation and mechanisms between empathy and anxiety. Then, the mediated role of insomnia and the moderated role of self-compassion were examined. Results The prevalence rates of anxiety and insomnia in the current sample are 18.24% and 26.76%, respectively. The results showed that empathy could negatively predict anxiety, with a significant mediating effect of insomnia between them (B = -0.081, p

Abstract Background This study aims to determine the satisfaction and future training needs of general practice residents participating in a novel model of ambulatory teaching aligned with the specifications for standardized residency training in outpatient management issued by the Chinese Medical Doctor Association (CMDA). Methods A cross-sectional survey of the satisfaction and training needs was conducted among general practice residents at West China Hospital, Sichuan University. Patient characteristics and preceptors’ feedback on the residents’ performance were also analyzed. Results The study involved 109 residents (30.28% men) and 161 patients (34.78% men; age: 52.63 ± 15.87 years). Residents reported an overall satisfaction score of 4.28 ± 0.62 with the ambulatory teaching program. Notably, residents scored lower in the Subjective-Objective-Assessment-Plan (SOAP) evaluation when encountering patients with the greater the number of medical problems (P

Study region: China. Study focus: This research aims to address the limitations of existing VPD reanalysis data, which are characterized by coarse spatial resolution and insufficient accuracy validation. Using ERA5-Land, TerraClimate, GLDAS time series data, and additional predictors such as vegetation indices, land cover types, terrain, and surface temperature, the study developed a random forest (RF) model to estimate VPD (named RF-VPD). Two independent experiments, station-to-station and year-to-year, were conducted to evaluate the models accuracy against in-situ data. New hydrological insights for the region: Machine learning-based downscaling methods offer a potential solution to enhance the accuracy of VPD spatiotemporal distribution. In this study, we utilized ERA5-Land, TerraClimate, and GLDAS time series, vegetation indices, land cover types, terrain, and surface temperature data as predictors to estimate VPD using three machine learning models, named RF-VPD. VPD station data were computed based on meteorological data from 2481 meteorological stations in China, and two independent experiments (station-to-station and year-to-year) were employed to evaluate the estimation accuracy of RF-VPD using this data as a reference. Additionally, the station-to-station statistics of the VPD reanalysis data and the consistency between the RF-VPD and in-situ VPD data were examined. Overall, the random forest model performed the best in predicting VPD (R²=0.98, NSE=0.98, MAE=0.04, RMSE=0.06, RSR=0.13, and KGE=0.98). The high accuracy demonstrated in year-to-year and station-to-station experiments, coupled with the strong consistency between RF-VPD data and in-situ observations, underscores the robustness and applicability of RF-VPD models in capturing spatiotemporal patterns. Furthermore, our study demonstrates the dynamic impact of hydrothermal transfer processes and meteorological factors on RF-VPD products. The high-resolution RF-VPD product derived from this method has significant potential for practical applications, including drought monitoring, agricultural productivity assessments, fire risk evaluations, and water resource management. Furthermore, the developed RF-VPD model can be a valuable complement to existing VPD datasets, offering higher accuracy and resolution. By improving the prediction of VPD dynamics, this research provides important tools for climate change adaptation, ecosystem monitoring, and sustainable resource management.

Social Networking Sites Addiction (SNSA) has become increasingly prevalent among university students, posing significant challenges to their mental health and academic performance. The psychological mechanisms and personality traits contributing to this addiction are not yet fully understood. This study explored the mediating effect of attachment avoidance (AA) between relatedness frustration (RF) and SNSA, as well as the moderating roles of Conscientiousness and Neuroticism from the Big Five personality traits. Data were collected from 489 university students (M = 18.81, SD = 0.92) using the Relatedness Frustration Scale, Ten-Item Personality Inventory in Chinese, Experiences in Close Relationships Scale (ECR) Short Form, and Social Networking Sites Addiction Scale. The findings were as follows: (1) RF significantly predicted SNSA; (2) RF significantly predicted AA, which in turn significantly predicted SNSA, indicating a partial mediation; and (3) Conscientiousness and Neuroticism moderated the effect of RF on SNSA, with higher levels of these traits amplifying the positive effect of RF on SNSA. The study concluded that individuals facing RF may avoid real-life attachments and seek connections online, increasing the risk of SNSA, especially for those with high levels of Conscientiousness and Neuroticism.

The mitochondrial calcium uniporters (MCUs) are a family of calcium unidirectional transporters important for cytoplasmic Ca2+ signals. Though the MCU proteins in several plant species have been investigated, genome-wide analysis of MCUs in alfalfa is lacking. Here, via genome-wide analysis, a total of 5, 20, and 6 MCU genes were identified in three different alfalfa cultivars, namely Medicago truncatula Jemalong A17, Medicago sativa XinJiangDaYe, and M. sativa Zhongmu No. 1, respectively. They were further phylogenetically classified into three subfamilies. Most MCU genes have only one intron, and gene duplication events of MCU genes were observed within each alfalfa accession and between different accessions. All alfalfa MCU proteins contained a highly conserved MCU domain and 10 conserved motifs, featuring two transmembrane domains and a DI/VME motif. According to the tissue expression data of M. sativa Zhongmu No. 1, MsMCU6.2 was the most abundant transcript with the highest expression in the leaf, and MsMCU5 and MsMCU1.2 showed higher expression levels in the stem than other tissues. We analyzed the expression profiles of five MCU genes (MsMCU1.1/1.2/5/6.1/6.2) under salt, drought, and cold stresses via qRT-PCR assays. All five MCU genes were induced by drought stress, except MsMCU5, whose expression was up-regulated by salt stress, while cold stress slightly altered MsMCU expression. Nine potential interacting proteins and three miRNAs targeting MtMCUs were predicted. These results provide detailed knowledge of alfalfa MCU genes and suggest their potential functions in abiotic stress response.

Tibial dyschondroplasia (TD) is a severe bone disease that affects fast-growing broiler chickens and causes economic loss. Despite previous studies, the regulatory mechanism of TD remains unclear and is thought to be primarily based on thiram induction, which may differ from that of naturally occurring diseases. To better understand TD, a digital X-ray machine was used in the present study to determine its incidence in four hundred yellow-feathered broiler chickens. The results showed that the incidence of TD was 22% after 6 weeks and gradually decreased after 8 and 10 weeks. The body weight of broilers with TD decreased significantly compared to that of NTD broilers. In addition, the length and density of the tibia were reduced after eight and 10 weeks, and the density of the tibia was reduced after 6 weeks compared with the NTD chickens. This study also examined tibial quality parameters from TD (n = 12) and NTD broilers (n = 12) and found that bone mineral content, bone mineral density, bone ash content, calcium content, and phosphorus content were significantly reduced in TD broilers. Transcriptome analysis revealed 849 differentially expressed genes (DEGs) in the growth plate between TD (n = 6) and NTD groups (n = 6). These genes were enriched in ECM-receptor interaction, cytokine-cytokine receptor interaction, calcium signaling pathway, and TGF-β signaling. Genes encoding the alpha chain of type XII collagen, that is, COL1A1, COL5A1, and COL8A1) were identified as critical in the regulatory network of TD. Gene set enrichment analysis (GSEA) revealed that the pathways of cartilage development, circulatory system development, and nervous system development were changed in the growth plates of TD birds. In the blood transcriptome, 12 DEGs were found in TD (n = 4) and NTD chickens (n = 4), and GSEA revealed that the pathways from TD broilers’ blood related to the phagosome, linoleic acid metabolism, monoatomic ion homeostasis, and calcium ion transport were downregulated. This study provides a comprehensive understanding of TD, including its effects on tibial quality, tibial changes, and the circulatory system, along with identifying important genes that may lead to the development of TD.

Abstract Purpose Automatic segmentation of brain tumors by deep learning algorithm is one of the research hotspots in the field of medical image segmentation. An improved FPN network for brain tumor segmentation is proposed to improve the segmentation effect of brain tumor. Materials and methods Aiming at the problem that the traditional full convolutional neural network (FCN) has weak processing ability, which leads to the loss of details in tumor segmentation, this paper proposes a brain tumor image segmentation method based on the improved feature pyramid networks (FPN) convolutional neural network. In order to improve the segmentation effect of brain tumors, we improved the model, introduced the FPN structure into the U-Net structure, captured the context multi-scale information by using the different scale information in the U-Net model and the multi receptive field high-level features in the FPN convolutional neural network, and improved the adaptability of the model to different scale features. Results Performance evaluation indicators show that the proposed improved FPN model has 99.1% accuracy, 92% DICE rating and 86% Jaccard index. The performance of the proposed method outperforms other segmentation models in each metric. In addition, the schematic diagram of the segmentation results shows that the segmentation results of our algorithm are closer to the ground truth, showing more brain tumour details, while the segmentation results of other algorithms are smoother. Conclusions The experimental results show that this method can effectively segment brain tumor regions and has certain generalization, and the segmentation effect is better than other networks. It has positive significance for clinical diagnosis of brain tumors.

Background: The role of Ferroptosis in the course of sepsis-induced myopathy is yet unclear. The objective of our work is to identify key genes connected with Ferroptosis in sepsis-induced myopathy and investigate possible pharmaceutical targets related to this process. This research aims to provide new insights into the management of sepsis-induced myopathy. Methods: We got the GSE13205 dataset from the Gene Expression Omnibus (GEO) and extracted Ferroptosis-associated genes from the FerrDb database. After conducting a functional annotation analysis of these genes, we created a protein-protein interaction network using Cytoscape software to identify important genes. Subsequently, we employed CMap to investigate prospective pharmaceuticals that could target these crucial genes. Results: A total of 61 genes that are expressed differently (DEGs) have been found concerning Ferroptosis. These genes are involved in a wide range of biological functions, including reacting to signals from outside the cell and the availability of nutrients, programmed cell death, controlling apoptosis, and responding to peptides, chemical stressors, and hormones. The KEGG pathway study revealed that these pathways are involved in Ferroptosis, autophagy, P53 signaling, PI3K-Akt signaling, mTOR signaling, HIF-1 signaling, endocrine resistance, and different tumorigenic processes. In addition, we created a network that shows the simultaneous expression of important genes and determined the top 10 medications that have the potential to treat sepsis-induced myopathy. Conclusion: The bioinformatics research undertaken sheds insight into the probable role of Ferroptosis-associated genes in sepsis-induced myopathy. The identified critical genes show potential as therapeutic targets for treating sepsis-induced myopathy, offering opportunities for the development of tailored medicines.

The sustainability challenges associated with utilizing forage fish sourced from ocean catch as fish meal and fish oil in the aquaculture industry has increased the demand for alternative feeds. Previous research indicates that Black Soldier Fly Larvae (BSFL; Hermetia illucens) can partially replace fish meal and/or fish oil in the diets of farmed aquaculture species without compromising fish growth or efficiency. The objective of our study was to identify the amount of pelagic fish from ocean catch that could be spared from fish meal and fish oil production by integrating BSFL in the diets of three aquaculture species, Atlantic Salmon (Salmo salar), Rainbow Trout (Oncorhynchus mykiss), and Whiteleg Shrimp (Litopenaeus vannamei) in the United States. Annual output for these aquaculture species was collected for 2017–2019. For each specie, we calculated the total metric tons (MT) of spared pelagic fish, by taxa, from fish meal and fish oil production based on total lifetime food intake and dietary replacement rates of fish meal and fish oil by BSFL as established in previous literature. At the highest level of dietary BSFL substitution for fish meal and/or fish oil that did not sacrifice performance of the three aquaculture species, 40,843 MT of pelagic fish could be spared from ocean catch in the U.S. per year. Therefore, integrating BSFL in the diets of aquaculture species could reduce the demand for pelagic fish sourced from ocean catch and positively contribute to the sustainability of aquaculture production.

The current study was designed based on the two-process model of the relatedness need to investigate the cyber-psychological mechanisms in the relationship between relatedness frustration and social networking sites (SNSs) behaviors. Chinese college students (N = 494; 190 males; Mage = 18.81 ± .92) were recruited to complete online questionnaires to measure relatedness frustration, relatedness satisfaction, affiliation motivation, and WeChat engagement. Path analyses indicated that relatedness frustration was directly related to defensive WeChat engagement and indirectly related to WeChat involvement and active engagement via affiliation motivation. Affiliation motivation played a significant mediating role, with the relationship between affiliation motivation and WeChat involvement being moderated by relatedness satisfaction. Specifically, this relationship existed only when the level of relatedness satisfaction was high. This study helps to understand motivational coping mechanisms among people with different levels of relatedness satisfaction in relation to SNSs after experiencing relatedness frustration. Potential limitations and future directions of this paper to the cyber-psychology literature are discussed.

Eggs are a vital dietary component for humans, and it is beneficial to increase egg production to support poultry farming. Initially, the egg production rate rises rapidly with young hens until it reaches its peak, and then it declines gradually. By extending the duration of peak egg production, the hens’ performance can be enhanced significantly. Previous studies found dynamic changes in gut microbiota during egg-laying, and several species of microbiota isolated from the chicken gut improved egg-laying performance. However, the interaction between microbes and host gene expression is still unclear. This study provides a more comprehensive understanding of chicken egg-laying by examining dynamic alterations in the microbiota of the entire intestinal tract (i.e., duodenum, jejunum, and ileum) and gene expression. The microbial community in the intestine underwent significant changes during different egg-laying periods (i.e., pre-, peak-, and late-laying periods). Metagenomic functional analysis showed that the relative abundance of biosynthesis of amino acids, secondary metabolites, and cofactors decreased significantly in the duodenum, jejunum, and ileum of aging hens. The relative levels of aldosterone, GnRH, insulin, growth hormone, and other hormone-related pathways increased dramatically in the intestinal microbiota during egg-laying, but only in the microbiota located in the duodenum and ileum. Transcriptome analysis suggested that genes associated with various transport processes were upregulated consistently in the small intestine during egg-laying; genes involved in the development of intestinal structure were down-regulated; and genes involved in response to DNA damage and stress were consistent with changes in laying rate. The abundance of Lactobacillus was related to the expression of ANGPTRL1, ANGPTRL2, ANGPT1L, and NOXO1 in the duodenum; Muricomes was correlated significantly with NFKBIZ, LYG2, and IRG1L expression in the jejunum; and Campylobacter was correlated positively with the expression of KMT2A and USF3 in the ileum. These results indicated that the intestinal microbiota and host gene expression may influence egg production jointly.

Spelling difficulties is referred to as dictation difficulties in China. The visual-auditory binding deficit hypothesis suggested that Chinese dictation difficulties can be correlated with deficits in binding visual and auditory information. However, how Chinese characters are mentally represented in children with dictation difficulties remained unexplored. In this study, 20 children with dictation difficulties and 18 chronically age-matched controls completed dictation tasks using grapheme cues, syllable cues, and grapheme-syllable cues. Dictation accuracy was recorded. Findings showed that under the grapheme cue condition, dictation accuracy between the two groups did not differ significantly; under the grapheme-syllable and the syllable condition, dictation accuracy in children with dictation difficulties was significantly lower compared to controls. These findings supported that the graphemic and phonological representations of Chinese characters might loosely associated in the mental lexicon of children with dictation difficulties. Intervention strategies should take into account improving their ability to associate graphemes and syllables of Chinese characters.

The analysis and inference of program play an important role in software development, maintenance and migration. How to efficiently obtain high quality information from program code has become a hot research topic. In recent years, a large number of researchers have introduced the deep learning-based representation technology into the code analysis tasks. The deep learning model can automatically extract the implicit and useful features implicit in the source code, which can alleviate the dependence on the manual construct feature. This paper first introduces the background and basic concepts of code representation, and summarizes the recent research work on deep learning-based code representation learning from the perspective of code static information analysis. Furthermore, this paper introduces the application of code representation on three tasks, code clone detection, code search and code completion. Finally, it discusses the challenges of deep learning-based code representation and the possible research directions in this field.

Abstract Background Pyroptosis is a newly discovered form of cell programmed necrosis, but its role and mechanism in cancer cells remain unclear. The aim of this study is to systematically analyze the transcriptional sequencing data of breast cancer (BC) to find a pyroptosis-related prognostic marker to predict the survival of BC patients. Methods The original RNA sequencing (RNA-seq) expression data and corresponding clinical data of BC were downloaded from The Cancer Genome Atlas (TGCA) database, followed by differential analysis. The pyroptosis-related differentially expressed genes (DE-PRGs) were employed to perform a computational difference algorithm and Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) was utilized to avoid overfitting. A total of 4 pyroptosis-related genes (PRGs) with potential prognostic value were identified, and a risk scoring formula was constructed based on these genes. According to the risk scores, the patients could be classified into high- and low-risk score groups. The potential molecular mechanisms and properties of PRGs were explored by computational biology and verified in Gene Expression Omnibus (GEO) datasets. In addition, the quantitative real time PCR (RT-qPCR) and Human Protein Atlas (HPA) were performed to validate the expression of the key genes. Results A PRGs signature, which was an independent prognostic factor, was constructed, and could divide patients into high- and low-risk groups. The results from the prognostic analysis indicated that the survival was significantly poorer in the high-risk group than in the low-risk group both in TCGA and in GEO, indicating that the signature is valuable for survival prediction and personalized immunotherapy of BC patients. Conclusions The pyroptosis-related biomarkers were identified for BC prognosis. The findings of this study provide new insights into the development of the efficacy of personalized immunotherapy and accurate cancer treatment options.

BackgroundN-nitrosodimethylamine (NDMA), a new disinfection by-product in drinking water, has attracted extensive attention due to its high detection rate and concentration. ObjectiveTo investigate the concentration of NDMA in drinking water in Nanjing situated in the lower Yangtze River Basin of China, and to evaluate associated human health risk. MethodsIn dry period (January–March) and wet period (July–September) of 2021, raw water, finished water, and tap water from 16 centralized water treatment plants in Nanjing were collected to detect the concentration of NDMA in water samples by solid phase extraction and gas chromatography-triple quadrupole mass spectrometry with programmable temperature vaporizer-based large volume injection. The concentrations of NDMA in water samples of different water types, water periods, and disinfection methods were analyzed, and the daily exposure levels and carcinogenic risk values of NDMA in drinking water of different exposure routes and different exposed populations were calculated. Monte Carlo simulation was implemented with Crystal Ball 11 software to establish a health risk assessment model and conduct sensitivity analysis. ResultsA total of 61 drinking water samples were collected in Nanjing, and NDMA was positive in all the water samples, with concentrations ranging from 1.36 to 25.65 ng·L−1 and an overall average concentration of (8.00±4.06) ng·L−1. There were no statistically significant differences in the average concentrations of NDMA among raw water, finished water, and tap water samples (F=2.875, P=0.064), between wet season and dry season (t=−0.855, P=0.397), or among different disinfection methods by liquid chlorine, sodium hypochlorite, and chlorine dioxide (F=0.977, P=0.385). The results of health risk assessment showed that the average carcinogenic risk of NDMA and its P95 were 5.95×10−6 and 1.12×10−5 respectively for oral intake of drinking water, and the values for dermal contact were both lower than 1.00×10−6. The mean carcinogenic risks of exposure to drinking water NDMA in children, adolescents, and adults were 1.84×10−6, 8.27×10−7, and 3.28×10−6, respectively. The results of sensitivity analysis showed that the contributions of daily drinking water volume and NDMA concentration in drinking water to the calculated health risk were high, and the contribution of body weight was negative. ConclusionThere is a potential carcinogenic risk of NDMA in the drinking water of Nanjing section of the lower Yangtze River Basin，but it is within the acceptable range.

BackgroundN-nitrosamines, a group of by-products of drinking water disinfection, have strong cytotoxicity to mammals. N-nitrosamines in drinking water are at the ng·L−1 level, and its accurate qualitative and quantitative analysis is difficult, so it is necessary to develop a sensitive and accurate method to determine N-nitrosamines in drinking water.ObjectiveTo establish a solid phase extraction-gas chromatography tandem mass spectrometry (GC-MS/MS) method for simultaneous determination of 10 kinds of N-nitrosamines in drinking water. To apply the established method to determine the levels of 10 kinds of N-nitrosamines in drinking water in Nanjing, and to understand the pollution status.MethodsCoconut charcoal solid phase extraction (SPE) cartridge and HLB Pro SPE cartridge were compared for the extraction efficiency of 10 N-nitrosamines in drinking water. A coconut charcoal SPE cartridge and a HLB Pro SPE cartridge were concatenated using a SPE connector, and then formed two combinations: coconut charcoal (top)-HLB Pro (bottom) and HLB Pro (top)-coconut charcoal (bottom), to extract the spiked samples, and combined with direct and independent elution ways to obtain the best extraction efficiency. From November to December 2021, 9 raw water, 10 finished water, and 7 tap water samples were collected from 9 municipal water supply units in Nanjing with 1 L brown glass sampling bottles. An 1.0 L drinking water sample was added with the isotope internal standard to prepare a test sample containing an isotope internal standard concentration of 25 ng·L−1. The automatic SPE instrument loaded all the 1.0 L drinking water samples to the tandem SPE cartridge of the HLB Pro (top)-coconut charcoal (bottom) at the rate of 15 mL·min−1. After extraction, the HLB Pro SPE cartridge and coconut charcoal SPE cartridge were transferred to the solid phase extraction vacuum device and eluted with 10 mL of dichloromethane respectively, then the dichloromethane eluents were combined, and concentrated to about 1.0 mL by nitrogen blowing after a small amount of the upper aqueous phase was removed. The concentrated solution was detected by GC-MS/MS and quantified by isotope internal standard method.ResultsThe comparison of sample spike recovery experiments showed that coconut charcoal solid phase extraction (SPE) cartridge and HLB Pro SPE cartridge presented highcomplementarity for the extraction efficiency of 10 N-nitrosamines in drinking water. Using HLB Pro (top)-coconut charcoal (bottom), independent elution, and combined with eluents, the optimal extraction efficiency was obtained. Under these conditions, by GC MS/MS, the 10 N-nitrosamines showed a good linear relationship within the range of 2–50 ng·L−1, the correlation coefficients were all greater than 0.9996, the method detection limit was 0.149–0.211 ng·L−1, and the limit of quantification was 0.596–0.844 ng·L−1. At the spiked concentrations of 5.0, 15, and 30 ng·L−1, the average recoveries of the 10 kinds of N-nitrosamines were 88.0%–104.8%, and the relative standard deviations were 1.22%–4.87%. When applying the method to determine the concentrations of the 10 N-nitrosamines in Nanjing drinking water, the results showed that the 10 N-nitrosamines were positive in different degrees in raw water, finish water, and terminal water, the detection rates were 0%–100%, and the concentrations were ND–27.6 ng·L−1.ConclusionThis tandem solid phase extraction-gas chromatography tandem mass spectrometry method can achieve simultaneous determination of a variety of N-nitrosamines in drinking water with high sensitivity and high throughput.

With the development of service-oriented architecture (SOA) technology, the amount of Web service is increasing. Clustering or classifying Web services correctly are an effective way to improve the quality of Web service discovery and the efficiency of Web service composition. However, the existing Web service modeling methods (such as latent Dirichlet allocation topic model) are difficult to obtain accurate and effective Web service representation from a sparse Web service dataset for Web service clustering. To solve this problem, this paper proposes a multi-dimensional information-based Web service representation method (MISR). First, it generates word vectors which contain topic and semantic information implicit in Web service description with Gaussian mixture model and Word2Vec. Then, the MISR algorithm combines tag-word relationship, popularity, and co-occurrence information together for generating multi-dimensional information Web service representation. Web service clustering and Web service classification are used for evaluating the effectiveness of MISR. Based on a real-world dataset of API services, the experiment results show that compared with LDA, Word2Vec, Doc2Vec, WT-LDA, HDP-SOM, GWSC, the proposed method has 38.8%, 54.5%, 15.3%, 33.3%, 44.7%, 9.7% improvement in Micro-F1 value.

This study examined the mediating effect of meaning in life and the moderating effect of interpersonal trust on the relationship between regulatory emotional self-efficacy (RESE) and prosocial behavior among Chinese college students. RESE and prosocial behavior were evaluated via a survey of 942 participants (51.59% females), showing that RESE was linked to prosocial behavior, and meaning in life mediated the relationship between RESE and prosocial behavior. Additionally, the interpersonal trust could reinforce RESE and meaning in life. In summary, RESE can not only be directly related to the prosocial behavior of college students through the meaning in life, and interpersonal trust can promote the relationship between RESE and meaning in life.

ObjectRepeated quarantine policies over the past 3 years have led to poor psychological consequences for the public. Previous studies have proved that the quarantine policy leaves individuals vulnerable to anxiety, depression, and insomnia, especially among college students. This study aims to explore whether psychological problems during isolation continue with the release of isolation.MethodsOverall, 2,787 college students both answered a web-based survey during and after the closure management was lifted. The Patient Health Questionnaire, Generalized Anxiety Disorder Scale, and Youth Self-rating Insomnia Scale were measured. The cross-lagged path model was used to explore the influence of psychological impact during isolation on the individual after the release.ResultsWe found that anxiety and sleep disturbance levels alleviated significantly after quarantine, except for depression. As expected, a bidirectional relationship exists between anxiety, depression, and sleep disturbance. Moreover, depression and sleep disturbance can predict post quarantine depression, sleep disturbance, and anxiety, yet anxiety cannot predict sleep disturbance afterward.ConclusionTimely and effective intervention for anxiety, depression, and insomnia during isolation is essential for individuals to repair themselves quickly after the release.

Object: Numerous studies show that depression and anxiety have an adverse effect on life satisfaction among college students. Moreover, neuroticism affects depression, anxiety, and life satisfaction. Comparing the low-neuroticism and high-neuroticism groups, the current study used network analysis to examine the relationship between depression, anxiety, and life satisfaction among college students. Methods: A sample consisted of 1233 college students from China who completed the Big Five Inventory-2 (BFI-2), Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS), and Satisfaction With Life Scale (SWLS).All students were divided into two groups according to levels of neuroticism. Depression-anxiety symptom networks and flow networks were formed. Results: “Insomnia” (SAS19) and “Sleep disturbance” (SDS4) are bridge symptoms of groups with varying neuroticism. In addition, compared to the group with low levels of neuroticism, the group with high levels of neuroticism showed more depression symptoms in bridge symptoms and greater global strength. Many depression-anxiety symptoms are negatively associated with life satisfaction, and “Emptiness” (SDS18) is an important symptom in the high-neuroticism group’s flow network. Conclusion: This study contributes to our understanding of the connection between depression, anxiety, neuroticism, and life satisfaction. In addition, the current study identified the essential symptoms to target in depression and anxiety intervention and life satisfaction enhancement among college students.

BackgroundDue to tremendous academic pressure, Chinese high school students suffer from severe depression, anxiety, and sleep disturbances. Moreover, senior high school students commonly face more serious mental health problems than junior high school students. However, the co-occurrence and internal relationships of depression, anxiety, and sleep disturbances clusters are scarcely examined among high students. Therefore, the current study inspected relationships between depression, anxiety, and sleep disturbance symptoms through network analysis and identified key symptoms bolstering the correlation and intensifying the syndromes.MethodsA total of 13,999 junior high school students (Mage = 13.42 years, SDage = 1.35, 50% females) and 12,550 senior high school students (Mage = 16.93 years, SDage = 1.67, 47% females) were recruited in Harbin. We constructed networks for all students, junior high group, and senior high group, including data from the Youth Self-rating Insomnia Scale-3 (YSIS-3), the Generalized Anxiety Disorder-2 (GAD-2), and the Patient Health Questionnaire-2 (PHQ-2). The indices of “strength” was used to identify symptoms' centrality, and “bridge strength” was used to find specific nodes that could bridge anxiety, depression, and sleep disturbance.ResultsThe networks of all students, junior high and senior high students, were stable and accurate. Among all networks, “Nervousness” (GAD1) had the highest strength, and “Nervousness”–“Excessive worry” (GAD1-GAD2) had the strongest correlation. “Nervousness” (GAD1) also functioned as the bridge symptom among junior high students, while “Sad mood” (PHQ2) among senior high students. Senior high students scored higher than junior high students on all items and had a tighter network structure.ConclusionsIn networks consisting of anxiety, depression, and sleep disturbance, anxiety plays a conspicuous role in comorbidity among junior high school students, which transforms into depression among senior high school students. Treatments or interventions should be focused on these critical symptoms.

BackgroundBesides physical changes, elderly adults are prone to have mental disorders such as anxiety, depression, and sleep disturbance, and the pandemic of COVID-19 worsened the situation. However, internal relationships and co-occurrence of psychopathologies were scarcely examined. Therefore, in the current study, through network analysis, we inspected relationships among symptoms of depression, anxiety, and sleep disturbance and identified key symptoms that espoused the disease.MethodsWe asked 1,302 elderly adults to fill in Patient Health Questionnaire-2 (depressive symptoms), the Generalized Anxiety Disorder-2 (anxiety symptoms), and the Youth Self-rating Insomnia Scale (sleep disturbance) and then constructed three networks for elderly adults, male elderly, and female elderly. Via network analysis, we accomplished four goals. First, we identified symptom with the highest centrality (i.e., strength) index for each network; then, we found the strongest correlation (i.e., edges) in each network; thirdly, we confirmed specific nodes that could bridge anxiety, depression, and sleep disturbance; the last was to compare networks based on genders. Network stability and accuracy tests were performed.ResultsNetworks of elderly adults, male elderly, and female elderly were stable, accurate, and intelligible. Among all networks, “Nervousness”- “Excessive worry” (GAD-1- GAD-2) had the strongest correlation, and “Nervousness” (GAD-1) had the highest strength and bridge strength value. When we made a comparison between female elderly's and male elderly's networks, except for the significant difference in the mean value of “Difficulty initiating sleep” (YSIS-3), the findings showed that the two networks were similar. Network stability and accuracy proved to be reliable.ConclusionsIn networks of anxiety, depression, and sleep disturbance, anxiety played a conspicuous role in comorbidity, which could be a target for practical intervention and prevention.

Loneliness and depression are significant mental health challenges among college students; however, the intricate relationship between these phenomena remains unclear, particularly in the context of self-compassion. In this comprehensive study, we employ a cross-lagged panel network (CLPN) analysis to investigate the symptom-level association between depression and loneliness while exploring the potential moderating influence of self-compassion. Our sample consisted of 2785 college students, who were categorized into high- and low-self-compassion groups based on scores from the Self-Compassion Scale. Depressive symptoms were assessed using the Patient Health Questionnaire-9, while the UCLA Loneliness Scale-8 measured loneliness expressions. Our findings indicate that self-compassion plays a crucial role in the relationship between depression and loneliness. Specifically, we observed distinctive patterns within the high and low-self-compassion groups. In the low-self-compassion group, “energy” emerged as the most influential symptom, whereas “motor function” exhibited the highest influence in the high-self-compassion group. Furthermore, among individuals with high self-compassion, the pathway from depression to loneliness was characterized by “guilt—being alone when desired,” while the reverse path from loneliness to depression encompassed “left out—feeling sad” and “left out—anhedonia.” Conversely, in the low-self-compassion group, depression and loneliness demonstrated a more intricate mutual triggering relationship, suggesting that self-compassion effectively moderates the association between these variables. This study provides valuable insights into the underlying mechanisms driving the interplay between depression and loneliness, shedding light on the pivotal role of self-compassion in this intricate dynamic.

Background: The COVID-19 pandemic and the shift to online learning have increased the risk of Internet addiction (IA) among adolescents, especially those who are depressed. This study aims to identify the core symptoms of IA among depressed adolescents using a cross-lagged panel network framework, offering a fresh perspective on understanding the interconnectedness of IA symptoms. Methods: Participants completed the Internet addiction test and the Patient Health Questionnaire-9. A total of 2415 students were initially included, and after matching, only 342 students (a cutoff score of 8) were retained for the final data analysis. A cross-lagged panel network analysis was conducted to examine the autoregressive and cross-lagged trajectories of IA symptoms over time. Results: The incidence rate of depression rose remarkably from 14.16% (N = 342) to 17.64% (N = 426) after the four-month online learning. The symptom of “Anticipation” exhibited the highest out-expected influence within the IA network, followed by “Stay online longer” and “Job performance or productivity suffer”. Regarding the symptom network of depression, “Job performance or productivity suffer” had the highest in-expected influence, followed by “Life boring and empty”, “Snap or act annoyed if bothered”, “Check email/SNS before doing things”, and “School grades suffer”. No significant differences were found in global network strength and network structure between waves 1 and 2. Conclusion: These findings prove the negative effects of online learning on secondary students’ mental health and have important implications for developing more effective interventions and policies to mitigate IA levels among depressed adolescents undergoing online learning.

Background: Although the clinical utility of attachment security priming has been suggested in recent years, the effect of attachment security priming on social anxiety and its core symptoms (i.e., attention bias) remains unspecified. Therefore, the present study explored the potential effectiveness of repeated attachment security priming in alleviating social anxiety and attention bias among Chinese college students. Methods: Fifty-six college students with high social anxiety were randomly assigned to the attachment security priming group (n = 30) or control group (n = 26). The priming group completed seven attachment security priming sessions over 2 weeks (every 2 days), and the control group was assigned to a waitlist for 2 weeks. Results: The results revealed that individuals in the priming group reported less social anxiety after 2 weeks of security attachment priming, and those in the control group did not change significantly. The results also showed that there was no significant change in the attention bias of individuals with social anxiety before and after the intervention. Conclusions: Our findings indicate that attachment security priming is a promising alternative intervention option for social anxiety. The potential clinical implications of security attachment priming are discussed.

Identification of protective factors to prevent firefighters' anxiety and depression is meaningful. We explored whether emotion-regulation strategies mediate the relationship between personality traits and anxiety and depression among Chinese firefighters. Approximately, 716 Chinese firefighters were recruited and completed the Emotion Regulation Questionnaire (ERQ), Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), and Big Five Inventory−2 (BFI-2) Scale. Results (N = 622) indicated that only negative emotionality traits could predict anxiety symptoms. Meanwhile, the multilevel mediation effect analyses showed that conscientiousness through cognitive reappraisal could reduce anxiety and depression symptoms in Chinese firefighters. Our findings clarify Chinese firefighters' underlying emotion-regulation process between personality traits and anxiety and depression. Implications, limitations, and future directions are discussed.

Conquering print-sound mappings (e.g., grapheme-phoneme correspondence rules) is vital for developing fluent reading skills. In neuroimaging research, this ability can be indexed by activation differences between audiovisual congruent against incongruent conditions in brain areas such as the left superior temporal cortex. In line with it, individuals with dyslexia have difficulty in tasks requiring print-sound processing, accompanied by a reduced neural integration. However, existing evidence is almost restricted to alphabetic languages. Whether and how multisensory processing of print and sound is impaired in Chinese dyslexia remains underexplored. In this study, we applied a passive audiovisual integration paradigm with functional magnetic resonance imaging to investigate the possible dysfunctions in processing character-sound (opaque; semantics can be automatically accessed) and pinyin-sound associations (transparent; no particular meaning can be confirmed) in Chinese dyslexic children. Unexpectedly, the dyslexic group did not show reduced neural integration compared with typically developing readers in either character or pinyin experiment. However, the results revealed atypical correlations between neural integration and different reading abilities in dyslexia. Specifically, while the neural integration in the left inferior frontal cortex in processing character-sound pairs correlated with silent reading comprehension in both children with and without dyslexia, it was associated with morphological awareness (semantic-related) in controls but with rapid naming (phonological-related) in dyslexics. This result indicates Chinese dyslexic children may not use the same grapho-semantic processing strategy as their typical peers do. As for pinyin-sound processing, while a stronger neural integration in the direction of “congruent > incongruent” in the left occipito-temporal cortex and bilateral superior temporal cortices was associated with better oral reading fluency in the control group, an opposite pattern was found in dyslexia. This finding may reflect dyslexia's dysfunctional recruitment of the regions in grapho-phonological processing, which further impedes character learning.

Previous studies have found that individuals with dyslexia perform poorly in paired associate learning (PAL) tasks, which were explained by a deficit in cross-modal association or verbal demand in alphabetic language. However, the nature of PAL deficits in non-alphabetic languages remains unclear. In this study, we conducted PAL and priming tasks in visual–visual, visual–verbal, verbal–visual, and verbal–verbal conditions to dissociate the cross-modal and verbal demands in Chinese children with dyslexia. In Experiment 1, children with dyslexia performed worse in verbal-involved PAL (visual–verbal, verbal–visual, and verbal–verbal) than the control children. Experiment 2 revealed that children with dyslexia performed better than the control children in the verbal–visual condition. Our results suggest that children with dyslexia have an intact ability to form cross-modal associations, which also implies that phonological deficits might be the key to PAL deficits in Chinese children with dyslexia.

The development of near-infrared-II (NIR-II) fluorescence imaging has implemented real-time detection of biological cells, tissues and body, monitoring the disease processes and even enabling the direct conduct of surgical procedures. NIR-II fluorescence imaging provides better imaging contrast and penetration depth, benefiting from the reducing photon scattering, light absorption and autofluorescence. The majority of current NIR-II fluorophores suffer from uncontrollable emission wavelength and low quantum yields issues, impeding the clinical translation of NIR-II bioimaging. By lengthening the polymethine chain, tailoring heterocyclic modification and conjugating electron-donating groups, cyanine dyes have been proved to be ideal NIR-II fluorophores with both tunable emission and brightness. However, a simpler and faster method for synthesizing NIR-II dyes with longer wavelengths and better stability still needs to be explored. This minireview will outline the recent progress of cyanine dyes with NIR-II emission, particularly emphasizing their pharmacokinetic enhancement and potential clinical translation.

Summary: Carbonized polymer dots (CPDs) are impressive imaging probes with great potential for enriching the library of metal-free fluorescent materials, yet current strategies have struggled to achieve products that emit full-color light in a single reaction system. Establishing an efficient and robust synthesis approach that unlocks the color barrier to the luminescence centers of specific CPDs remains a challenge. Herein, the surface-state engineering of pyridine and amide in the indole system to create a palette of resolvable full-color light-emissive CPDs is reported. Detailed structural analysis revealed that cationic polymerization and oxidation reactions potentially contribute to the formation of the main frameworks and emission centers of the final CPDs, with emissive oxygen- and nitrogen-based centers fixed by cross-linked polymer structures. This study provides valuable insight into the energy absorbance and photoluminescence mechanism of CPDs and introduces additional reactants (benzo heterocycle) into CPD research.

The sustainability challenges associated with utilizing forage fish sourced from ocean catch as fish meal and fish oil in the aquaculture industry has increased the demand for alternative feeds. Previous research indicates that Black Soldier Fly Larvae (BSFL; Hermetia illucens) can partially replace fish meal and/or fish oil in the diets of farmed aquaculture species without compromising fish growth or efficiency. The objective of our study was to identify the amount of pelagic fish from ocean catch that could be spared from fish meal and fish oil production by integrating BSFL in the diets of three aquaculture species, Atlantic Salmon (Salmo salar), Rainbow Trout (Oncorhynchus mykiss), and Whiteleg Shrimp (Litopenaeus vannamei) in the United States. Annual output for these aquaculture species was collected for 2017-2019. For each specie, we calculated the total metric tons (MT) of spared pelagic fish, by taxa, from fish meal and fish oil production based on total lifetime food intake and dietary replacement rates of fish meal and fish oil by BSFL as established in previous literature. At the highest level of dietary BSFL substitution for fish meal and/or fish oil that did not sacrifice performance of the three aquaculture species, 40,843 MT of pelagic fish could be spared from ocean catch in the U.S. per year. Therefore, integrating BSFL in the diets of aquaculture species could reduce the demand for pelagic fish sourced from ocean catch and positively contribute to the sustainability of aquaculture production. [ABSTRACT FROM AUTHOR]

Background: The advancement of communication technology and the impact of the COVID-19 pandemic have led to an increased reliance on online education. However, the effects of the long-term use of smart devices for online learning on students' social anxiety and problematic smartphone use (PSU) and the role of fear of missing out (FoMO) in this process have yet to be fully explored. Methods: This study analysed longitudinal data from 2,356 high school students (female 5 1,137 (48.26%), mean age 5 13.84, SD age 5 1.37) in China, divided into high- and low-FoMO groups based on their scores on the FoMO scale, to examine the impact of four months of online learning on social anxiety and PSU. The Social Anxiety Scale (SAS) and Mobile Phone Addiction Index (MPAI) were used to assess social anxiety and PSU symptoms. Results: The undirected symptom networks revealed more bridge symptoms among the students in the high-FoMO group, although their overall symptom scores decreased. The results of the directed cross-lagged panel networks showed that "productivity loss" predicted other symptoms in the low-FoMO group but that "afraid of negative evaluation" was the predictor in the high-FoMO group. Meanwhile, "withdrawal/escape" and "productivity loss" were the symptoms that were most affected by other symptoms in the high-FoMO and low-FoMO groups, respectively. Conclusions: The current study therefore sheds light on the changes in social anxiety and PSU symptoms among secondary school students during long-term online learning, as well as the moderating role of FoMO. [ABSTRACT FROM AUTHOR]

This study developed an efficient method to simultaneously separate and purify syringoside and oleuropein from Syringa oblata Lindl. extract using macroporous resins. The adsorption and desorption property of 11 resins were systematically evaluated. Based on the adsorption performance, HPD-100B resin was selected for the separation of syringoside and oleuropein. The HPD-100B resin fitted well to the Langmuir isotherm model (R2 > 0.97), as ascertained by the results of the static adsorption experiment. Kinetic and dynamic adsorption/desorption experiments were conducted using the HPD-100B resin to optimize the separation parameters of syringoside and oleuropein. On the optimal parameters, syringoside and oleuropein were obtained from the 20% and 40% ethanol eluates, respectively. In addition, the adsorption effluent (15–60 BV) contained a large amount of syringoside with less impurities; therefore, this part was also collected for further syringoside separation and enrichment of syringoside. By only one cycle treatment, the syringoside and oleuropein contents in the final products increased by 7.1-fold and 8.2-fold, respectively, compared to the initial extract. The method developed in this study provides a potential basis for the industrial-scale enrichment and separation of syringoside and oleuropein from S. oblata extract.

Current reported spatiotemporal solutions for fusing multisensor aerosol optical depth (AOD) products used to recover gaps either suffer from unacceptable accuracy levels, i.e., fixed rank smooth (FRS), or high time costs, i.e., Bayesian maximum entropy (BME). This problem is generally more serious when dealing with multiple AOD products in a long time series or over large geographic areas. This study proposes a new, effective, and efficient enhanced FRS method (FRS-EE) to fuse satellite AOD products with uncertainty constraints. AOD products used in the fusion experiment include Moderate Resolution Imaging SpectroRadiometer (MODIS) DB/DT_DB_Combined AOD and Multiangle Imaging SpectroRadiometer (MISR) AOD across mainland China from 2016 to 2017. Results show that the average completeness of original, initial FRS fused, and FRS-EE fused AODs with uncertainty constraints are 22.80%, 95.18%, and 65.84%, respectively. Although the correlation coefficient (R = 0.77), root mean square error (RMSE = 0.30), and mean bias (Bias = 0.023) of the initial FRS fused AODs are relatively lower than those of original AODs compared to Aerosol Robotic Network (AERONET) AOD records, the accuracy of FRS-EE fused AODs, which are R = 0.88, RMSE = 0.20, and Bias = 0.022, is obviously improved. More importantly, in regions with fully missing original AODs, the accuracy of FRS-EE fused AODs is close to that of original AODs in regions with valid retrievals. Meanwhile, the time cost of FRS-EE for AOD fusion was only 2.91 h; obviously lower than the 30.46 months taken for BME.

Studies on Chinese dictation difficulties have focused on visual processing and phonological processing. In recent decades, attention has shifted to the ability to bind visual and auditory information. However, such studies are scarce and rarely focus on how this ability influences children’s learning and writing of Chinese characters. In this study, a group of children with Chinese dictation difficulties and a control group without such difficulties were instructed to learn rarely used Chinese characters under three learning modes: grapheme learning, syllable learning, and grapheme-syllable learning. Participants’ learning time and writing accuracy were recorded under each learning mode. Findings showed that under the grapheme learning mode, learning time and writing accuracy failed to differ significantly between the two groups. However, under the grapheme-syllable learning mode, the writing accuracy of children with dictation difficulties was significantly lower than controls. These findings, taken together, suggested that for children with dictation difficulties, learning graphemes and syllables at the same time did not improve their writing performance as much as the controls. Under the syllable learning mode, learning time and writing accuracy failed to differ significantly between the two groups. The findings contributed to a better understanding of the Chinese dictation difficulties.

Avian leukosis virus subgroup J (ALV-J) is an avian oncogenic retrovirus that induces myeloid tumors and hemangiomas in chickens and causes severe economic losses with commercial layer chickens and meat-type chickens. High-throughput sequencing followed by quantitative real-time polymerase chain reaction and bioinformatics analyses were performed to advance the understanding of regulatory networks associated with differentially expressed non-coding RNAs and mRNAs that facilitate ALV-J infection. We examined the expression of mRNAs, long non-coding RNAs (lncRNAs), and miRNAs in the spleens of 20-week-old chickens infected with ALV-J and uninfected chickens. We found that 1723 mRNAs, 7,883 lncRNAs and 13 miRNAs in the spleen were differentially expressed between the uninfected and infected groups (P < 0.05). Transcriptome analysis showed that, compared to mRNA, chicken lncRNAs shared relatively fewer exon numbers and shorter transcripts. Through competing endogenous RNA and co-expression network analyses, we identified several tumor-associated or immune-related genes and lncRNAs. Along transcripts whose expression levels significantly decreased in both ALV-J infected spleen and tumor tissues, BCL11B showed the greatest change. These results suggest that BCL11B may be mechanistically involved in tumorigenesis in chicken and neoplastic diseases, may be related to immune response, and potentially be novel biomarker for ALV-J infection. Our results provide new insight into the pathology of ALV-J infection and high-quality transcriptome resource for in-depth study of epigenetic influences on disease resistance and immune system.