Advanced biomanufacturing and evaluation of adeno-associated virus.

Recombinant adeno-associated virus (rAAV) has been developed as a safe and effective gene delivery vehicle to treat rare genetic diseases. This study aimed to establish a novel biomanufacturing process to achieve high production and purification of various AAV serotypes (AAV2, 5, DJ, DJ8). First, a robust suspensive production process was developed and optimized using Gibco Viral Production Cell 2.0 in 30-60 mL shaker flask cultures by evaluating host cells, cell density at the time of transfection and plasmid amount, adapted to 60-100 mL spinner flask production, and scaled up to 1.2-2.0-L stirred-tank bioreactor production at 37 °C, pH 7.0, 210 rpm and DO 40%. The optimal process generated AAV titer of 7.52-8.14 × 1010 vg/mL. Second, a new AAV purification using liquid chromatography was developed and optimized to reach recovery rate of 85-95% of all four serotypes. Post-purification desalting and concentration procedures were also investigated. Then the generated AAVs were evaluated in vitro using Western blotting, transmission electron microscope, confocal microscope and bioluminescence detection. Finally, the in vivo infection and functional gene expression of AAV were confirmed in tumor xenografted mouse model. In conclusion, this study reported a robust, scalable, and universal biomanufacturing platform of AAV production, clarification and purification.

A CD276-Targeted Antibody-Drug Conjugate to Treat Non-Small Lung Cancer (NSCLC).

Non-small cell lung cancer (NSCLC) patients, accounting for approximately 85% of lung cancer cases, are usually diagnosed in advanced stages. Traditional surgical resection and radiotherapy have very limited clinical benefits. The objective of this study was to develop and evaluate a targeted therapy, antibody-drug conjugate (ADC), for NSCLC treatment. Specifically, the CD276 receptor was evaluated and confirmed as an ideal surface target of NSCLC in the immunohistochemistry (IHC) staining of seventy-three patient tumor microarrays and western blotting analysis of eight cell lines. Our anti-CD276 monoclonal antibody (mAb) with cross-activity to both human and mouse receptors showed high surface binding, effective drug delivery and tumor-specific targeting in flow cytometry, confocal microscopy, and in vivo imaging system analysis. The ADC constructed with our CD276 mAb and payload monomethyl auristatin F (MMAF) showed high anti-NSCLC cytotoxicity to multiple lines and effective anti-tumor efficacy in both immunocompromised and immunocompetent NSCLC xenograft mouse models. The brief mechanism study revealed the integration of cell proliferation inhibition and immune cell reactivation in tumor microenvironments. The toxicity study did not detect off-target immune toxicity or peripheral toxicity. Altogether, this study suggested that anti-CD276 ADC could be a promising candidate for NSCLC treatment.

Nonconforming gender expression and insufficient sleep among adolescents during COVID-19 school closure and after school reopening.

BACKGROUND: Gender nonconformity (GNC) (i.e., gender expression that differs from gender role expectations for feminine or masculine appearance and behavior) is an under-researched area of adolescent sleep health. The COVID-19 lockdown offers an opportunity to understand how the effect of GNC on adolescent health outcomes changes between school closure and reopening. METHODS: We conducted a cross-sectional study in Shanghai, China, in 2020. The sample size for analysis was 3,265. The age-specific insufficient sleep was estimated according to National Sleep Foundation's sleep duration recommendations. The self-perceived and self-rated GNC were measured by the two items "On the same scale that goes from 100% as a girl to 100% as a boy, where do you think others see you?" and "On a scale that goes from feeling 100% like a girl to feeling 100% like a boy, where do you see yourself?", and birth sex. In addition, we calculated sex-stratified adjusted odds ratios (AORs) of insufficient sleep for students with high and moderate GNC compared to students with low GNC. Finally, we measured the AORs with self-perceived and self-rated GNC during COVID-19 school closure and reopening. RESULTS: Among 3,265 students in grade 6-12 in the analytic sample, 1,567(48.0%) were assigned female at birth (AFAB), 3,188 (97.6%) Han, and 1,921(58.8%) in grade 6-9. Among AFAB students, high self-perceived GNC was significantly associated with insufficient sleep (AOR,1.65; 95%CI,1.30-2.09) during school closure. Insufficient sleep was associated with high self-rated GNC (AOR,1.73; 95%CI,1.23-2.44) and moderate self-rated GNC (AOR,1.69; 95%CI,1.29-2.22) during school closure. After school reopening, neither self-perceived nor self-rated GNC was associated with insufficient sleep among AFAB students. Among assigned male at birth (AMAB) students, none of the two kinds of GNC was associated with insufficient sleep in the two periods during the COVID-19 pandemic. CONCLUSIONS: This study suggests GNC is only associated with insufficient sleep among AFAB students during school closure. Furthermore, the association is nonsignificant among AMAB students. These findings indicate that GNC-related stigma within the family could be a risk factor for insufficient sleep among AFAB adolescents.

StemSC: a cross-dataset human stemness index for single-cell samples.

BACKGROUND: Stemness is defined as the potential of cells for self-renewal and differentiation. Many transcriptome-based methods for stemness evaluation have been proposed. However, all these methods showed low negative correlations with differentiation time and can't leverage the existing experimentally validated stem cells to recognize the stem-like cells. METHODS: Here, we constructed a stemness index for single-cell samples (StemSC) based on relative expression orderings (REO) of gene pairs. Firstly, we identified the stemness-related genes by selecting the genes significantly related to differentiation time. Then, we used 13 RNA-seq datasets from both the bulk and single-cell embryonic stem cell (ESC) samples to construct the reference REOs. Finally, the StemSC value of a given sample was calculated as the percentage of gene pairs with the same REOs as the ESC samples. RESULTS: We validated the StemSC by its higher negative correlations with differentiation time in eight normal datasets and its higher positive correlations with tumor dedifferentiation in three colorectal cancer datasets and four glioma datasets. Besides, the robust of StemSC to batch effect enabled us to leverage the existing experimentally validated cancer stem cells to recognize the stem-like cells in other independent tumor datasets. And the recognized stem-like tumor cells had fewer interactions with anti-tumor immune cells. Further survival analysis showed the immunotherapy-treated patients with high stemness had worse survival than those with low stemness. CONCLUSIONS: StemSC is a better stemness index to calculate the stemness across datasets, which can help researchers explore the effect of stemness on other biological processes.

Integrated multi-omics analysis reveals miR-20a as a regulator for metabolic colorectal cancer.

Single-driver molecular events specific to the metabolic colorectal cancer (CRC) have not been clearly elucidated. Herein, we identified 12 functional miRNAs linked to activated metabolism by integrating multi-omics features in metabolic CRC. These miRNAs exhibited significantly enriched CRC driver miRNAs, significant impacts on CRC cell growth and significantly correlated metabolites. Importantly, miR-20a is minimally expressed in normal colorectal tissues but highly expressed in metabolic CRC, suggesting the potential therapeutic target. Bioinformatics analyses further revealed miR-20a as the most powerful determinant that regulates a cascade of dysregulated events, including Wnt signaling pathway, core enzymes involved in FA metabolism program and triacylglycerol abundances. In vitro assays demonstrated that elevated miR-20a up-regulated FA synthesis enzymes via Wnt/ß-catenin signaling, and finally promoted proliferative and migration of metabolic CRC cells. Overall, our study revealed that miR-20a promoted progression of metabolic CRC by regulating FA metabolism and served as a potential target for preventing tumor metastasis.

Biomedical data, computational methods and tools for evaluating disease-disease associations.

In recent decades, exploring potential relationships between diseases has been an active research field. With the rapid accumulation of disease-related biomedical data, a lot of computational methods and tools/platforms have been developed to reveal intrinsic relationship between diseases, which can provide useful insights to the study of complex diseases, e.g. understanding molecular mechanisms of diseases and discovering new treatment of diseases. Human complex diseases involve both external phenotypic abnormalities and complex internal molecular mechanisms in organisms. Computational methods with different types of biomedical data from phenotype to genotype can evaluate disease-disease associations at different levels, providing a comprehensive perspective for understanding diseases. In this review, available biomedical data and databases for evaluating disease-disease associations are first summarized. Then, existing computational methods for disease-disease associations are reviewed and classified into five groups in terms of the usages of biomedical data, including disease semantic-based, phenotype-based, function-based, representation learning-based and text mining-based methods. Further, we summarize software tools/platforms for computation and analysis of disease-disease associations. Finally, we give a discussion and summary on the research of disease-disease associations. This review provides a systematic overview for current disease association research, which could promote the development and applications of computational methods and tools/platforms for disease-disease associations.

IndGOterm: a qualitative method for the identification of individually dysregulated GO terms in cancer.

Individual pathway analysis can dissect heterogeneities among different cancer patients and provide efficient guidelines for individualized therapy. However, the existence of the batch effect brings extensive limitations for the application of many individual methods for pathway analysis. Previously, researchers proposed that methods based on within-sample relative expression ordering (REO) of the genes are notably insensitive to 'batch effects'. In this article, we focus on the Gene Ontology (GO) database and propose an individual qualitative GO term analysis method (IndGOterm) based on the REO of genes. Compared with some current widely used single-sample enrichment analysis methods, such as ssGSEA and GSVA, IndGOterm has a predominance of ignoring the batch effects caused by diverse technologies. Through the survival and drug responses analysis, we found IndGOterm could capture more terms connected to cancer than other single-sample enrichment analysis methods. Furthermore, through the application of IndGOterm, we found some terms that present different dysregulation models that manifest heterogenetic in homologous patients. Collectively, these results attested that IndGOterm could capture useful information from patients and be a useful tool to reveal the intrinsic characteristic of cancer. An open-source R statistical analysis package 'IndGOterm' is available at https://github.com/robert19960424/IndGOterm.

Association between sexting and mental health among secondary vocational school students / 中国学校卫生

Objective@#To explore the prevalence of sexting among secondary vocational school students and to examine the correlation between sexting and mental health, so as to provide evidence for prevention and intervention on adolescents mental health.@*Methods@#In April 2021, three secondary vocational schools from central urban area, outskirts and outer suburbs in Shanghai, among 1 580 students were selected by cluster sampling.@*Results@#The proportions of students who received and who forwarded others private photos or videos were 11.96% and 2.78%, respectively. The proportion of students who sent others personal photos or videos was 2.54%. And the proportions of boys were higher than those of girls ( χ 2=45.89, 24.09, 6.66, P <0.01). The results of multivariable Logistic analysis showed that compared with those who had never sexted, students who had ever had any sexting were at higher risk of anxiety ( OR=2.40, 95%CI =1.59-3.61), depression( OR=1.86, 95%CI =1.25-2.75), non suicidal self injury intention ( OR=2.34, 95%CI =1.48-3.69) and suicidal intention ( OR=2.96, 95%CI =1.83-4.79)( P < 0.05 ).@*Conclusion@#There is a significant correlation between sexting and mental health among secondary vocational school students. The latent risks of sexting should be included in the curriculum of comprehensive sex education for teenagers to enhance their media literacy and decision making capability, so as to prevent sexual assault or abuse caused by sexting and promote sexual and reproductive health and as well as mental health of adolescents.

Relationship between gender role attitudes and depression among adolescents / 中国学校卫生

Objective@#To explore the relationship between gender role attitudes (GRA) and adolescent depression to provide evidence for the promotion of mental health among adolescents.@*Methods@#A total of 1 549 students from grades 6 to 8 in three public middle schools in Jing an District of Shanghai were selected by stratified cluster sampling. The baseline and follow up surveys were conducted by anonymous electronic questionnaire on mobile tablets from November to December in 2017 and 2018, respectively. The GRA Scale and the Depression Scale were used to collect subjects attitudes towards traditional role assignment and power inequality between men and woman and depression in family and sexual relationships. The multivariate Generalized Estimating Equations (GEE) model was adopted to examine the relationship between GRA and depression.@*Results@#The mean score of the GRA Scale was (2.52±0.83) and (2.29±0.86), while the score of Depression Scale was (15.92±5.08) and (16.48±5.29), in the baseline and follow up survey, respectively ( P <0.05). After controlling the covariates of age, bullied experience, body image, social cohesion, etc., the multivariate GEE model indicated traditional GRA was significantly associated with a higher risk of depression among both boys and girls ( β boys =0.38, β girls =0.41, P <0.05).@*Conclusion@#Traditional GRA may increase the risk of depression in adolescents, suggesting that cultivating a positive and equal GRA among this population group may help to prevent depression.

The pattern of romantic and sexual related experiences among Chinese young adolescents: an exploration with multi-group latent class analysis.

BACKGROUND: Studies on very young adolescents' romantic and sexual experiences would help inform the context in which early sex arises. However, such studies are scant in China due to sparse data and cultural issues. METHOD: This study used the GEAS baseline data conducted among1776 adolescents in Shanghai. Multi-group latent class analysis was used to explore adolescents' romantic and sexual experiences patterns and subgroups. Multi-nominal logistic regression was performed to identify the factors distinguishing different subgroups subsequently. RESULTS: There were gender differences in the lifetime prevalence for very young adolescents' romantic and sexual-related behaviors. The Multi-group latent class analysis indicated that the participants could be classified into three classes: general group, early romance group, and sex exploratory group. Multi-nominal logistic regression showed youth in the early romance group were more likely to had friends of both gender, ever had a romantic relationship, and had more autonomy in deciding where to go than the general group; while male respondents in the sex exploratory group were older, ever had a romantic relationship, believed that boys should be more sexually active and more proactive than girls, had more autonomy on deciding where to go, and perceived less school connection and neighborhood cohesion. Female respondents in the sex exploratory group were older and less empowered in decision-making than the general group. CONCLUSIONS: The result provides a picture of romantic and sexual behavior patterns among both gender of very young adolescents in China. Current sex education needs not only to be culturally appropriate but also to address the harm of gender inequality and stereotypes, as well as to provide accessible and supportive services to help young adolescents personalize their received information and strengthen their skills in communication, decision making, and critical thinking.

Studies on teenagers' romantic and sexual experiences would help to prevent early sex arises before it really takes place. However, such studies are limited, especially in China. The traditional culture thought that youth should not start romance before college. This study used the Global Early Adolescent Study Shanghai site baseline data collected among1776 teenagers to explore their romantic and sexual experiences patterns and identify the influencing factors. There were significant gender differences in teenagers' romantic and sexual-related behaviors. According to the multi-group latent class analysis, we classified the teenagers into three classes: the general group, the early romance group, and the sex exploratory group. The multi-nominal logistic regression showed youth in the early romance group were more likely to had friends of both boys and girls, ever had boyfriend/girlfriend and were freer to go out than the general group; while boys in the sex exploratory group were older, ever had a boyfriend/girlfriend, believed it was normal for boys to be sexually active than girls, had more freedom to go out, and had less perception of care from school adults and neighborhood. Girls in the sex exploratory group were older and less likely to make decisions on their own. Given the result we found, we call for health researchers and educators to conduct sex education programs promoting more equal gender norms and provide services to help young adolescents get right information and strengthen their skills in communication, decision making and critical thinking.

The effect of COVID-19 school closures on adolescent sleep duration: an uncontrolled before-after study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic affected almost 1.6 billion students or more than 90% of learners globally. However, the effect of school closures during COVID-19 pandemic on adolescent sleep duration remains unclear. METHODS: We undertook a cross-sectional electronic survey in six junior and senior high schools in Shanghai, China from late June to early July 2020. We evaluated the changes of sleep duration on weekdays by comparing sleep duration hours and insufficient sleep (< 9 h for children aged 6-13 years or < 8 h for teenagers aged 14-17 years) in COVID-19 school closures and after school reopening. We also investigated possible sex differences in the changes of sleep duration. RESULTS: A total of 3265 students completed the survey, the mean age was 14.56 ± 1.99 years, 1567 (47.99%) were girls and 1344 (41.17%) were in grades 10-12. The overall sleep duration decreased from 8.88 h in school closures to 7.77 h after school reopening, and the change (difference: - 1.11 h; 95%CI: - 1.16, - 1.07; P < 0.001) was statistically significant. The prevalence of insufficient sleep increased sharply from 21.10 to 63.98%, and the change (ratio:3.03; 95%CI:2.84, 3.23; P < 0.001) was statistically significant. Besides, the changes were greater in girls than in boys. CONCLUSION: Results of this study revealed that sleep duration was longer and percentage of sufficient sleep was higher during COVID-19 school closures in adolescent students.

Correlations of impulsivity and aggressive behaviours among adolescents in Shanghai, China using bioecological model: cross-sectional data from Global Early Adolescent Study.

OBJECTIVE: To examine the correlations between impulsivity and aggressive behaviours among Chinese adolescents. DESIGN: A school-based cross-sectional study. SETTING: Three primary middle schools located in less developed communities of Shanghai. PARTICIPANTS: 1524 adolescents aged 11-16 years. MEASURES: The impulsivity was measured by Barratt Impulsivity Scale, and the aggressive behaviours were determined by self-reports. Data were collected through computer-assisted self-interview using tablets. Multivariate Firth logistic regression model was conducted to examine correlations between total, attentional, motor, and non-planning impulsivity and aggressive behaviours, respectively. RESULTS: Totally, 7.48% of participants reported aggressive behaviours toward others during the past 6 months. The proportion of aggressors among boys and girls was 10.60% and 4.18%, respectively. Results of the multivariate regression suggested the risk of aggressive behaviours was significantly increased among those with the highest tertile of total impulsivity (adjusted OR (aOR)boys=3.14, 95% CI: 1.48 to 6.65; aORgirls=3.74, 95% CI: 1.10 to 12.76) and motor impulsivity (aORboys=2.91, 95% CI: 1.46 to 5.82; aORgirls=3.57, 95% CI: 1.25 to 10.20.), comparing with those with the lowest tertile, for boys and girls, respectively. Besides, younger age, lower social cohesion and being bullied within 6 months were associated with a higher risk of aggressive behaviours among girls. Less family caring and being bullied within 6 months were associated with the risk among boys. CONCLUSIONS: The present study indicates a positive association between impulsivity and aggressive behaviours, with a more salient correlation between motor impulsivity subtrait and aggressive behaviour among both boys and girls. Furthermore, adolescents' aggressive behaviours were affected by multiple factors from individuals, family, peers and community. Comprehensive intervention strategies such as controlling the aggressor's impulsivity, helping them better channel their anger, creating a better family, school and neighbourhood environment, and providing support and services for victims of violence are needed.

The Association between Gender Role Attitudes and Alcohol Use among Early Adolescents in Shanghai, China.

BACKGROUND: Adolescent alcohol use was a major social and public health concern given its negative impacts. Previous studies indicated gender role attitudes (GRA) were associated with alcohol use; however, few studies focused on early adolescents (10 to 14 years) and similar researches were not found in China. Objective: This study sought to explore the association between GRA and alcohol use among early adolescents. Methods: A cross-sectional study was conducted among students in grades six to eight across three public secondary schools in Shanghai, China. Data were collected by Computer-Assisted Self-Interview (CASI) questionnaire on mobile tablets. Alcohol use was measured by self-report, and six items with 5-point Likert-type options assessed the attitude toward traditional gender roles. The logistic regression model was adopted to examine the associations between GAR and alcohol use. Results: Totally 1,631 adolescents aged 10 to 14 years with 50.33% of boys included in this study. The mean score of GRA in drinkers was significantly higher than nondrinkers among boys (3.03 vs. 2.78, p < 0.001) but not girls (2.15 vs. 2.18, p = 0.499). After controlling the covariates of age, depression, peers' substance use, social cohesion, etc., we found that more traditional GRA was associated with a higher risk of alcohol use among boys (OR = 1.39, 95%CI: 1.11-1.75), whereas the association was not significant among girls (OR = 0.96, 95%CI: 0.74-1.24). Conclusions: Traditional GRA may increase the risk of alcohol use among early adolescent boys, suggesting that altering traditional GRA among this population group may help to prevent alcohol use.

A Cancer-Specific Qualitative Method for Estimating the Proportion of Tumor-Infiltrating Immune Cells.

Tumor-infiltrating immune cells are important components in the tumor microenvironment (TME) and different types of these cells exert different effects on tumor development and progression; these effects depend upon the type of cancer involved. Several methods have been developed for estimating the proportion of immune cells using bulk transcriptome data. However, there is a distinct lack of methods that are capable of predicting the immune contexture in specific types of cancer. Furthermore, the existing methods are based on absolute gene expression and are susceptible to experimental batch effects, thus resulting in incomparability across different datasets. In this study, we considered two common neoplasms as examples (colorectal cancer [CRC] and melanoma) and introduced the Tumor-infiltrating Immune Cell Proportion Estimator (TICPE), a cancer-specific qualitative method for estimating the proportion of tumor-infiltrating immune cells. The TICPE was based on the relative expression orderings (REOs) of gene pairs within a sample and is notably insensitive to batch effects. Performance evaluation using public expression data with mRNA mixtures, single-cell RNA-Seq (scRNA-Seq) data, immunohistochemistry data, and simulated bulk RNA-seq samples, indicated that the TICPE can estimate the proportion of immune cells with levels of accuracy that are clearly superior to other methods. Furthermore, we showed that the TICPE could effectively detect prognostic signals in patients with tumors and changes in the fractions of immune cells during immunotherapy in melanoma. In conclusion, our work presented a unique novel method, TICPE, to estimate the proportion of immune cells in specific cancer types and explore the effect of the infiltration of immune cells on the efficacy of immunotherapy and the prognosis of cancer. The source code for TICPE is available at https://github.com/huitingxiao/TICPE.

Multilevel prioritization of gene regulators associated with consensus molecular subtypes of colorectal cancer.

Consensus molecular subtypes (CMSs) are emerging as critical factor for prognosis and treatment of colorectal cancer. Gene regulators, including chromatin regulator, RNA-binding protein and transcriptional factor, are critical modulators of cancer hallmark, yet little is known regarding the underlying functional mechanism in CMSs. Herein, we identified a core set of 235 functional gene regulators (FGRs) by integrating genome, epigenome, transcriptome and interactome of CMSs. FGRs exhibited significant multi-omics alterations and impacts on cell lines growth, as well as significantly enriched cancer driver genes and pathways. Moreover, common FGRs played different roles in the context of CMSs. In accordance with the immune characteristics of CMSs, we found that the anti-tumor immune pathways were mainly activated by FGRs (e.g. STAT1 and CREBBP) in CMS1, while inhibited by FGRs in CMS2-4. FGRs mediated aberrant expression of ligands, which bind to receptor on immune cells, and modulated tumor immune microenvironment of subtypes. Intriguingly, systematic exploration of datasets using genomic and transcriptome co-similarity reveals the coordinated manner in FGRs act in CMSs to orchestrate their pathways and patients' prognosis. Expression signatures of the FGRs revealed an optimized CMS classifier, which demonstrated 88% concordance with the gold-standard classifier, but avoiding the influence of sample composition. Overall, our integrative analysis identified FGRs to regulate core tumorigenic processes/pathways across CMSs.

NIDM: network impulsive dynamics on multiplex biological network for disease-gene prediction.

The prediction of genes related to diseases is important to the study of the diseases due to high cost and time consumption of biological experiments. Network propagation is a popular strategy for disease-gene prediction. However, existing methods focus on the stable solution of dynamics while ignoring the useful information hidden in the dynamical process, and it is still a challenge to make use of multiple types of physical/functional relationships between proteins/genes to effectively predict disease-related genes. Therefore, we proposed a framework of network impulsive dynamics on multiplex biological network (NIDM) to predict disease-related genes, along with four variants of NIDM models and four kinds of impulsive dynamical signatures (IDSs). NIDM is to identify disease-related genes by mining the dynamical responses of nodes to impulsive signals being exerted at specific nodes. By a series of experimental evaluations in various types of biological networks, we confirmed the advantage of multiplex network and the important roles of functional associations in disease-gene prediction, demonstrated superior performance of NIDM compared with four types of network-based algorithms and then gave the effective recommendations of NIDM models and IDS signatures. To facilitate the prioritization and analysis of (candidate) genes associated to specific diseases, we developed a user-friendly web server, which provides three kinds of filtering patterns for genes, network visualization, enrichment analysis and a wealth of external links (http://bioinformatics.csu.edu.cn/DGP/NID.jsp). NIDM is a protocol for disease-gene prediction integrating different types of biological networks, which may become a very useful computational tool for the study of disease-related genes.

PrGeFNE: Predicting disease-related genes by fast network embedding.

Identifying disease-related genes is of importance for understanding of molecule mechanisms of diseases, as well as diagnosis and treatment of diseases. Many computational methods have been proposed to predict disease-related genes, but how to make full use of multi-source biological data to enhance the ability of disease-gene prediction is still challenging. In this paper, we proposed a novel method for predicting disease-related genes by using fast network embedding (PrGeFNE), which can integrate multiple types of associations related to diseases and genes. Specifically, we first constructed a heterogeneous network by using phenotype-disease, disease-gene, protein-protein and gene-GO associations; and low-dimensional representation of nodes is extracted from the network by using a fast network embedding algorithm. Then, a dual-layer heterogeneous network was reconstructed by using the low-dimensional representation, and a network propagation was applied to the dual-layer heterogeneous network to predict disease-related genes. Through cross-validation and newly added-association validation, we displayed the important roles of different types of association data in enhancing the ability of disease-gene prediction, and confirmed the excellent performance of PrGeFNE by comparing to state-of-the-art algorithms. Furthermore, we developed a web tool that can facilitate researchers to search for candidate genes of different diseases predicted by PrGeFNE, along with the enrichment analysis of GO and pathway on candidate gene set. This may be useful for investigation of diseases' molecular mechanisms as well as their experimental validations. The web tool is available at http://bioinformatics.csu.edu.cn/prgefne/.

Influence of impulsivity on adolescents pornography use / 中国学校卫生

Objective@#To explore the influence of impulsive traits of adolescent on pornography use through the analysis of the Global Early Adolescent Study(GEAS) longitudinal survey data collected in Shanghai, and to provide evidence for adolescent sexual health promotion.@*Methods@#Totally 1 512 students from grades 6 to 8 in three middle schools in a district of Shanghai were selected for the present study by stratified cluster sampling method. Baseline and two-wave follow-up investigation were conducted between 2017 and 2020. Three waves of pornography use and social demographic information were collected using electronic questionnaire through tablets while impulsivity were tested only once during the follow-up in 2018 using the paper and pencil based Barratt Impulsivity Scale, version11 (BIS-11). General statistical description and panel data statistical description, as well as multilevel mixed effect linear model were used to do the analysis.@*Results@#About 32.7% (494) of the adolescents reported the experience of watching pornography in threewave analysis. Boys were more impulsive than girls in the motor subscale (16.33±3.25, 15.66±2.93, t=4.13, P<0.01) while girls were more impulsive than boys in the nonplanning subscale (23.65±5.11, 22.83±5.21, t=-3.03, P<0.01). Mixed effect linear model result showed that impulsivity was correlated with pornography use(β=0.001, P<0.01); higher impulsivity in motor and attention were correlated with more frequent pornography use(P<0.01). Being female, perceived more parental awareness and perceived care from school adults would decrease the use of pornography while spent more than 3 hours on internet would increase the use of pornography (P<0.01).@*Conclusion@#There are stable correlations between impulsivity and pornography use. It is urgent to equip young adolescents with the necessary ability to distinguish the good from the bad in the mass and internet media world.

Association between adverse childhood experiences and adolescent alcohol use / 中国学校卫生

Objective@#To explore the association between adverse childhood experiences (ACEs) and adolescent alcohol use and to provide evidence for prevention and intervention.@*Methods@#A total of 1 550 students from grades 6 to 8 in three public middle schools in a district of Shanghai were selected by stratified cluster sampling method. The baseline and follow up investigation were conducted by anonymous electronic questionnaire in mobile tablet from November to December in 2017 and 2018, respectively. The latent class analysis (LCA) was applied for the classification of ACEs, while the multivariate generalized estimating Equations (GEE) model was adopted to examine the association between ACEs and adolescent alcohol use.@*Results@#The ACEs was divided into 3 classes by LCA: high exposure (8.97%), abuse and neglect (38.97%), low exposure (52.06%). The multivariate GEE model indicates the risk of alcohol drinking among adolescents in high exposure and abuse and neglect classes were significantly higher than their counterparts in low exposure class ( OR=2.65, 95%CI=1.72-4.07; OR=1.50, 95%CI =1.14-1.96, respectively).@*Conclusion@#The effect of ACEs on alcohol use may vary across different latent classes. Supportive childhood environment may contribute to decrease the risk of adolescent drinking behavior.

Identification of EMT-related high-risk stage II colorectal cancer and characterisation of metastasis-related genes.

BACKGROUND: Our laboratory previously reported an individual-level prognostic signature for patients with stage II colorectal cancer (CRC). However, this signature was not applicable for RNA-sequencing datasets. In this study, we constructed a robust epithelial-to-mesenchymal transition (EMT)- related gene pair prognostic signature. METHODS: Based on EMT-related genes, metastasis-associated gene pairs were identified between metastatic and non-metastatic samples. Then, we selected prognosis-associated gene pairs, which were significantly correlated with disease-free survival of stage II CRC using multivariate Cox regression model, as the EMT-related prognosis signature. RESULTS: An EMT-related signature composed of fifty-one gene pairs (51-GPS) for prediction-relapse risk of patients with stage II CRC was developed, whose prognostic efficiency was validated in independent datasets. Moreover, 51-GPS achieved better predictive performance than other reported signatures, including a commercial signature Oncotype Dx colon cancer and an immune-related gene pair signature. Besides, EMT-related functional gene sets achieved high enrichment scores in high-risk samples. Especially, loss-of-function antisense approach showed that DEGs between the predicted two clusters were metastasis-related. CONCLUSIONS: The EMT-related gene pair signature can identify the high relapse-risk patients with stage II CRC, which can facilitate individualised management of patients.