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Text classification is widely studied by researchers in the natural language processing field. However, real-world text data often follow a long-tailed distribution as the frequency of each class is typically different. The performance of current mainstream learning algorithms in text classification suffers when the training data are highly imbalanced. The problem can get worse when the categories with fewer data are severely undersampled to the extent that the variation within each category is not fully captured by the given data. At present, there are a few studies on long-tailed text classification which put forward effective solutions. Encouraged by the progress of handling long-tailed data in the field of image, we try to integrate effective ideas into the field of long-tailed text classification and prove the effectiveness. In this paper, we come up with a novel approach of feature space reconstruction with the help of three-way decisions (3WDs) for long-tailed text classification. In detail, we verify the rationality of using a 3WD model for feature selection in long-tailed text data classification, propose a new feature space reconstruction method for long-tailed text data for the first time, and demonstrate how to effectively generate new samples for tail classes in reconstructed feature space. By adding new samples, we enrich the representing information of tail classes, to improve the classification results of long-tailed text classification. After some comparative experiments, we have verified that our model is an effective strategy to improve the performance of long-tailed text classification.

In recent years, there has been increasing interest in the use of kilohertz frequency alternating current (KHFAC) to block peripheral nerves. However, there is still a lack of direct data and mechanistic studies on the treatment of neuropathic pain by KHFAC. Based on this, we applied a high-frequency bipolar rectangular stimulus pulse to chronic constriction injury of sciatic nerve mice (CCI), and explored the optimal stimulation frequency and current by recording the compound muscle action potential (CMAP). We found that KHFAC could significantly alleviate the mechanical and thermal allodynia in neuropathic pain mice without any effect of movement function following 7 days of high-frequency electrical stimulation of the sciatic nerve. KHFAC inhibited the expression of TRPV1 and NMDAR2B, which could also inhibit the activation of astrocytes and microglia in the spinal cord. The administration of TRPV1 pathway activator could partially reverse the antinociceptive effects of KHFAC, while TRPV1 pathway inhibitor could achieve analgesic effects similar to KHFAC. Therefore, we believe that KHFAC inhibits the activation of spinal dorsal horn glial cells, especially astrocytes and microglia, through nociceptive afferent fibers by inhibiting the activation of TRPV1/NMDAR2B signaling pathway. In summary, KHFAC has a potential to be a novel intervention for the treatment of neuropathic pain.

Social media has become a popular means for people to consume and share news. However, it also enables the extensive spread of fake news, that is, news that deliberately provides false information, which has a significant negative impact on society. Especially recently, the false information about the new coronavirus disease 2019 (COVID-19) has spread like a virus around the world. The state of the Internet is forcing the world's tech giants to take unprecedented action to protect the "information health" of the public. Despite many existing fake news datasets, comprehensive and effective algorithms for detecting fake news have become one of the major obstacles. In order to address this issue, we designed a self-learning semi-supervised deep learning network by adding a confidence network layer, which made it possible to automatically return and add correct results to help the neural network to accumulate positive sample cases, thus improving the accuracy of the neural network. Experimental results indicate that our network is more accurate than the existing mainstream machine learning methods and deep learning methods.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a complex clinical syndrome and difficult diagnosis. The fusion of multimodal data improves the accuracy of ASD diagnosis, benefiting from the complementary information contained in the multimodal data. The aim of this study was to diagnose ASD using predictors based on integrated resting state MRI (rs-fMRI) and genetic data. Our study used fMRI and gene expression data from 71 participants in the National Database for Autism Research (NDAR). T-test and SVM-RFE were used for feature reduction and optimal feature selection. To make the best use of the features extracted from each data source, we used the EasyMKL to establish a classification model for the prediction of ASD rather than simply concatenating feature matrices. The experimental results validate the effectiveness of our method. In addition, the imaging and genetic features we extracted have been shown to be significantly associated with ASD supported by previous studies.

Purpose WeChat official account (WCOA) is an emerging and important platform for academic library services, which greatly accelerates the development of this field. This article aims to identify key evaluation indicators for users' satisfaction of the Academic Library WeChat Official Account (ALWCOA) as a reference for future improvements. Design/methodology/approach Based on the updated DeLone and McLean (D&M)’s model and Delphi method, an evaluation system of ALWCOA satisfaction was constructed. Then 212 university students were recruited to fill out a questionnaire on evaluation indicators. The grey relational analysis (GRA) and Pareto's principle were employed to analyze the questionnaire and select key evaluation indicators. Findings An ALWCOA service satisfaction evaluation system with three evaluation dimensions and 15 evaluation indicators was constructed, and three key evaluation indicators were identified, including service responsiveness, information timeliness and system security. Practical implications This article provides a strategy for assessing ALWCOA service satisfaction, as well as insights for improving of ALWCOA service. Specifically, academic libraries should pay more attention to improving service responsiveness, information timeliness and system security. Originality/value This article innovatively applied the updated D&M model in academic library service. Additionally, it facilitates the development of research fields, such as academic library services, microservices and user service evaluation, and provides a case study to better understand the WCOA.

The concept of Big Data is popular in a variety of domains. The purpose of this review was to summarize the features, applications, analysis approaches, and challenges of Big Data in health care. Big Data in health care has its own features, such as heterogeneity, incompleteness, timeliness and longevity, privacy, and ownership. These features bring a series of challenges for data storage, mining, and sharing to promote health-related research. To deal with these challenges, analysis approaches focusing on Big Data in health care need to be developed and laws and regulations for making use of Big Data in health care need to be enacted. From a patient perspective, application of Big Data analysis could bring about improved treatment and lower costs. In addition to patients, government, hospitals, and research institutions could also benefit from the Big Data in health care.

Background: Gastric cancer (GC) is one of the most common malignant tumors worldwide with a high incidence and mortality, making it urgent to search for potential biomarkers to improve the prognosis of patients. Integrin β (ITGB) superfamily members have been reported to participate in the biological process in various tumors. However, the expression and prognostic value of ITGBs in GC have not been clarified. In this study, the expression and roles of ITGBs in stomach adenocarcinoma (STAD) were investigated with ONCOMINE, UALCAN, The Human Protein Atlas, GEPIA, Kaplan-Meier Plotter, NetworkAnalyst, cBioPortal, STRING, GeneMANIA, David 6.8 and TIMER. Results: The transcriptional levels of ITGB1, 2, 4, 5, 6 and 8, and the protein expression of ITGB4, 5, 6 and 8 were significantly elevated while the transcriptional level of ITGB7 was significantly reduced in GC. High mRNA expression of ITGB1, 3 and 5, and low mRNA expression of ITGB4 were associated with short overall survival (OS), and high mRNA expression of ITGB6 was associated with short disease-free survival (DFS) in STAD patients. We also identified DAB2 as the potential transcription factor for ITGB3 and ITGB5, and TFAP2A for ITGB4 in STAD. Moreover, the functions of ITGB superfamily members were primarily related to regulation of actin cytoskeleton, focal adhesion and PI3K-Akt signalling pathway. The expression of ITGBs was significantly correlated with the infiltration of diverse immune cells, B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil and dendritic cell.Conclusion: Taken together, our study indicated that ITGB superfamily members could be a potential prognostic target in the development of anti-STAD therapeutics. However, further experimental studies are still necessary to elucidate the mechanism of ITGBs.

Gastric cancer (GC) represents a widespread malignancy with a poor prognosis. Hence, discovering reliable biomarkers is necessary. The cell division cycle-associated protein (CDCA) family, comprising CDCA1-8, plays a key role in tumor progression. However, whether CDCA expression has prognostic value in GC, especially stomach adenocarcinoma (STAD), has not been elucidated yet. Consequently, we conducted a multifaceted study using bioinformatic tools aimed at exploring CDCA expression levels and appraising their potential prognostic values in patients with STAD. All eight CDCAs were significantly upregulated in STAD tissues compared with healthy tissues. Elevated CDCA4/7/8 mRNA expression predicted a short overall survival, and increased CDCA7 transcriptional levels predicted a short disease-free survival. The most frequent alteration in patients with STAD was low mRNA expression. The functional enrichment analysis incorporating the gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathways showed that the cell cycle, foxO signaling pathway, and Epstein-Barr virus were relevant to the main functions of CDCAs. Finally, the immune infiltration analysis revealed a significant correlation between CDCA expression and the infiltration extent of six immunocytes. Therefore, differentially expressed CDCAs may represent potential biomarkers for the prognosis of patients with STAD that can improve survival. Furthermore, this study might offer new ideas for the design and development of immunotherapeutic drugs.

The outbreak and worldwide spread of COVID-19 has resulted in a high prevalence of mental health problems in China and other countries. This was a cross-sectional study conducted using an online survey and face-to-face interviews to assess mental health problems and the associated factors among Chinese citizens with income losses exposed to COVID-19. The degrees of the depression, anxiety, insomnia, and distress symptoms of our participants were assessed using the Chinese versions of the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7), the Insomnia Severity Index-7 (ISI-7), and the revised 7-item Impact of Event Scale (IES-7) scales, respectively, which found that the prevalence rates of depression, anxiety, insomnia, and distress caused by COVID-19 were 45.5%, 49.5%, 30.9%, and 68.1%, respectively. Multivariable logistic regression analysis was performed to identify factors associated with mental health outcomes among workers with income losses during COVID-19. Participants working in Hubei province with heavy income losses, especially pregnant women, were found to have a high risk of developing unfavorable mental health symptoms and may need psychological support or interventions.

Breast cancer stem cells (BCSCs) contribute to intra-tumoral heterogeneity and therapeutic resistance. However, the binary concept of universal BCSCs co-existing with bulk tumor cells is over-simplified. Through single-cell RNA-sequencing, we found that Neu, PyMT and BRCA1-null mammary tumors each corresponded to a spectrum of minimally overlapping cell differentiation states without a universal BCSC population. Instead, our analyses revealed that these tumors contained distinct lineage-specific tumor propagating cells (TPCs) and this is reflective of the self-sustaining capabilities of lineage-specific stem/progenitor cells in the mammary epithelial hierarchy. By understanding the respective tumor hierarchies, we were able to identify CD14 as a TPC marker in the Neu tumor. Additionally, single-cell breast cancer subtype stratification revealed the co-existence of multiple breast cancer subtypes within tumors. Collectively, our findings emphasize the need to account for lineage-specific TPCs and the hierarchical composition within breast tumors, as these heterogenous sub-populations can have differential therapeutic susceptibilities.

Background The social Q&A community quickly becomes a popular platform for consumers to find health information because of its convenience and interactivity. Methods Based on the 10,861 depression questions collected in the Zhihu, the largest Q&A platform in China, we divided the healthy information needs description into nine categories with Latent Dirichlet Allocation (LDA). We also divided the healthy information needs type into Physiological, affective and cognitive needs based on the Wilson model. Results The results show that the largest categories are depression symptom and social activities while the less concerned health information is prevention and medical insurance. More attention is paid to cognitive needs. We also find there is no strong correlation between attention and needs type. Conclusions The purpose of this paper is to refine the consumer health information needs types to better understand the consumer health information characteristic in China.

Ongoing biomarker development programs have been designed to identify serologic or imaging signatures of clinico-pathologic entities, assuming distinct biological boundaries between them. Identified putative biomarkers have exhibited large variability and inconsistency between cohorts, and remain inadequate for selecting suitable recipients for potential disease-modifying interventions. We launched the Cincinnati Cohort Biomarker Program (CCBP) as a population-based, phenotype-agnostic longitudinal study. While patients affected by a wide range of neurodegenerative disorders will be deeply phenotyped using clinical, imaging, and mobile health technologies, analyses will not be anchored on phenotypic clusters but on bioassays of to-be-repurposed medications as well as on genomics, transcriptomics, proteomics, metabolomics, epigenomics, microbiomics, and pharmacogenomics analyses blinded to phenotypic data. Unique features of this cohort study include (1) a reverse biology-to-phenotype direction of biomarker development in which clinical, imaging, and mobile health technologies are subordinate to biological signals of interest; (2) hypothesis free, causally- and data driven-based analyses; (3) inclusive recruitment of patients with neurodegenerative disorders beyond clinical criteria-meeting patients with Parkinson's and Alzheimer's diseases, and (4) a large number of longitudinally followed participants. The parallel development of serum bioassays will be aimed at linking biologically suitable subjects to already available drugs with repurposing potential in future proof-of-concept adaptive clinical trials. Although many challenges are anticipated, including the unclear pathogenic relevance of identifiable biological signals and the possibility that some signals of importance may not yet be measurable with current technologies, this cohort study abandons the anchoring role of clinico-pathologic criteria in favor of biomarker-driven disease subtyping to facilitate future biosubtype-specific disease-modifying therapeutic efforts.

In response to the increasingly serious ecological and environmental crisis, China has upgraded its national strategy from environmental protection to ecological civilization. China has carried out comprehensive publicity and education on ecological civilization. Many universities also arrange ecological civilization courses for students, or infuse ecological civilization into traditional courses. This paper investigates Chinese university students’ ecological civilization cognition and behavior. Based on the 13404 questionnaires of 152 universities and using the multinomial logit regression model, the authors explored the relationship between Chinese university students’ cognition and behavior. This paper divides the students’ ecological civilization cognition into two parts, one being the common-sense cognition that comes from China’s long-term public ecological and environmental education and the other one being the cognition of national ecological civilization strategy that comes from the recent intensive and comprehensive political publicity. This paper finds that university students with the latter cognition show a stronger willingness to implement ecological civilization behavior. This result reveals the role of China’s political publicity on ecological civilization in terms of influencing its citizens’ behavior, and provides inspiration for other countries to publicize environmental politics and promote public environmental protection via mass media.

Qidong hepatitis B virus (HBV) infection cohort (QBC) is a prospective community-based study designed to investigate causative factors of primary liver cancer (PLC) in Qidong, China, where both PLC and HBV infection are highly endemic. Residents aged 20-65 years, living in seven townships of Qidong, were surveyed using hepatitis B surface antigen (HBsAg) serum test and invited to participate in QBC from June 1991 to December 1991. A total of 852 and 786 participants were enrolled in HBsAg-positive and HBsAg-negative sub-cohorts in May 1992, respectively. All participants were actively followed up in person, received HBsAg, alanine aminotransferase (ALT), alpha-fetoprotein (AFP) tests and upper abdominal ultrasonic examination, and donated blood and urine samples once or twice a year. The total response rate was 99.6%, and the number of incident PLC was 201 till the end of February 2017. The ratio of incidence rates was 12.32 (95% confidence interval[CI]=7.16-21.21, P < 0.0001) in HBsAg-positive arm compared with HBsAg-negative arm. The relative risk of PLC was 13.25 (95% CI=6.67-26.33, P < 0.0001) and 28.05 (95% CI=13.87-56.73, P < 0.0001) in the HBsAg+/HBeAg- group and the HBsAg+/HBeAg+ group, respectively, as compared to the HBsAg-/HBeAg- group. A series of novel PLC-related mutations including A2159G, A2189C and G2203W at the C gene, A799G, A987G and T1055A at the P gene of HBV genome were identified by using samples from the cohort. The mutation in hepatitis B virus (HBV) basal core promoter region of HBV genome has an accumulative effect on the occurrence of PLC. In addition, the tripartite relationship of aflatoxin exposure, P53 mutation and PLC was also investigated. Dynamic prediction model for PLC risk by using its long-term follow-up information and serial blood samples for QBC was developed. This model is expected to improve the efficiency of PLC screening in HBV infection individuals.

Qidong City, China, has had high liver cancer incidence from endemic hepatitis B virus (HBV) infection and dietary exposure to aflatoxin. Based on etiologic studies, we began interventions in 1980 to reduce dietary aflatoxin and initiate neonatal HBV vaccination. We studied trends in liver cancer incidence rates in the 1.1 million inhabitants of Qidong and examined trends in aflatoxin exposure, staple food consumption, HBV infection markers and annual income. Aflatoxin exposure declined greatly in association with economic reform, increased earnings and educational programs to shift staple food consumption in the total population from moldy corn to fresh rice. A controlled neonatal HBV vaccination trial began in 1983 and ended in November, 1990, when vaccination was expanded to all newborns. Liver cancer incidence fell dramatically in young adults. Compared with 1980–83, the age-specific liver cancer incidence rates in 2005–08 significantly decreased 14-fold at ages 20–24, 9-fold at ages 25–29, 4-fold at ages 30–34, 1.5-fold at ages 35–39, 1.2-fold at ages 40–44 and 1.4-fold at ages 45–49, but increased at older ages. The 14-fold reduction at ages 20–24 might reflect the combined effects of reduced aflatoxin exposure and partial neonatal HBV vaccination. Decrease incidence in age groups >25 years could mainly be attributable to rapid aflatoxin reduction. Compared with 1980–83, liver cancer incidence in 1990–93 significantly decreased 3.4-fold at ages 20–24, and 1.9-fold at ages 25–29 when the first vaccinees were

To evaluate whether first-degree family history of liver cancer plays a role in liver cancer incidence by prospective evaluation of a patient cohort in Qidong, China over a 20-year period.In May 1992, 708 hepatitis B surface antigen (HBsAg) carriers and 730 HBsAg-negadve controls from Qidong city were enrolled for participation in a prospective cohort study ending in November 2012.Follow-up was carried out every 6 to 12 months, and evaluations included serum assays to measure concentrations of alpha fetoprotein (AFP), HBsAg and alanine aminotransferase (ALT), as well as abdominal ultrasound to assess liver disease.The relationship between baseline (study entry) information of patients with first-degree family history of liver cancer and liver cancer incidence during the two decades of study was statistically assessed.There were 172 newly diagnosed liver cancer cases in the cohort during 25 753 person-years (py) of follow-up, representing an incidence of 667.88/100 000 py.The incidence rates of liver cancer among participants with or without liver cancer family history were 1 244.36/100 000 py and 509.70/100 000 py respectively, and the between-group difference reached the threshold for statistical significance (P less than 0.01, Relative Risk (RR):2.44, 95% Confidence Interval (CI):1.80-3.31).The incidence rates of liver cancer among participants who had a sibling with liver cancer and participants who had a parent with liver cancer were not significantly different (P0.05), but the liver cancer incidence among participants who had a mother with liver cancer was significantly higher than that of participants who had a father with liver cancer (P0.05, RR:1.86, 95% CI:1.03-3.36). Among the participants with liver cancer family history, 56.52% (39/69) were diagnosed before 50 years old, and this rate was significantly higher than that of participants without a family history of liver cancer (40.78%, 42/103, P less than 0.05).The incidence rate of liver cancer among the participants who were family history-positive and HBsAg-positive was significantly higher than that of participants who were family history-negative but HBsAg-positive (P0.01, RR:1.75, 95% CI:1.29-2.38), and was 59.59 times higher than for participants who were family history-negative and HBsAgnegative.Subgroup analysis of liver cancer incidence among participants who were family history-positive but HBsAg-negative and participants who were family history-negative and HBsAg-negative produced anRR of 2.60, but there was no statistically significant difference between the two subgroups (P0.05).At the study's end, the incidence rates of liver cancer for the different subgroups were 32.21% for the family history-positive and HBsAgpositive participants, 19.80% for the family history-negative and HBsAg-positive participants, 1.71% for the family history-positive and HBsAg-negative participants, and 0.65% for the family history-negative and HBsAg-negative participants.First-degree family history of liver cancer is a risk factor of liver cancer in Chinese patients from Qidong, and exhibits synergism with HBsAg-positivity for incidence of liver cancer.

We assessed the separate and combined effects of hepatitis B virus (HBV), hepatitis C virus (HCV), and aflatoxin in causing hepatocellular carcinoma (HCC) in Qidong, China. A consecutive series of 181 pathologic-diagnosed HCC cases were studied for hepatitis B surface antigen (HBsAg), anti-HBc, HBV X gene sequence, anti-HCV, the 249ser-p53 mutation, and chronic hepatitis pathology. Each of the 181 incident HCC cases had markers for HBV infection and hepatitis pathology; only 6 of 119 cases were coinfected with HCV. The 249ser-p53 mutation was found in 54% (97/181) of HCC cases and in all 7 cases with tissue for analysis from the hepatitis cohort but in none of 42 matched cases from Beijing. The estimated cumulative dose of aflatoxin B1 in these 7 cases ranged from 0.13 to 0.49 mg/kg. Follow-up data through 13.25 years on a cohort of 145 men with chronic HBV hepatitis showed that the relative risk from aflatoxin exposure was 3.5 (1.5-8.1). A similar relative risk was found using 249ser-p53 mutation as a marker for aflatoxin exposure. In conclusion, HBV hepatitis is ubiquitous in Qidong HCC cases, whereas HCV contributes little to its risk. The 249ser-p53 mutation appears to result from coexposure to aflatoxin and HBV infection. Even modest levels of aflatoxin exposure tripled the risk of HCC in HBV-infected men.

We followed 145 men with chronic hepatitis B virus (HBV) hepatitis for 10 years to determine whether exposure to aflatoxin, or concomitant exposure to hepatitis C virus (HCV), or family history of hepatocellular carcinoma (HCC) increased the risk of developing HCC. We collected 8 monthly urine samples before beginning follow-up and pooled them to detect aflatoxin metabolite M1 (AFM1). AFM1 was detected in 78 (54%) of the subjects. The risk of HCC was increased 3.3-fold (with a 95% confidence interval of 1.2-8.7) in those with detectable AFM1 (above 3.6 ng/L). This relative risk was adjusted for age and for HCV status. The attributable risk from exposure to detectable AFM1 was 0.553 (0.087, 0.94). The relative risk of fatal cirrhosis for those with elevated AFM1 was 2.8 (0.6, 14.3), and the odds of having a persistently elevated alanine transaminase (ALT) were 2.5-fold greater in those with detectable AFM1 (P =.007). Concomitant infection with HCV increased the risk of HCC 5.8-fold (2. 0-17), adjusted for age and AFM1 status. A family history of HCC increased the risk of HCC 5.6-fold, adjusted for age and AFM1. Four men with detectable AFM1 and HCC all had missense mutation in codon 249 of the p53 gene in cancer tissues. This study shows that exposure to AFM1 can account for a substantial part of the risk of HCC in men with chronic HBV hepatitis and adds importantly to the evidence that HCV and family history of HCC increase the risk of HCC in men with chronic HBV hepatitis.