RESULTS: We propose a succinct representation of the distance matrices which tremendously reduces the space requirement. We give a complete solution, called SuperRec, for the inference of chromosomal structures from Hi-C data, through iterative solving the large-scale weighted multidimensional scaling problem.
CONCLUSIONS: SuperRec runs faster than earlier systems without compromising on result accuracy. The SuperRec package can be obtained from http://www.cs.cityu.edu.hk/~shuaicli/SuperRec .
MATERIALS AND METHODS: We propose a mixed-method study of mental health assessment that combines psychological questionnaires with facial emotion analysis to comprehensively evaluate the mental health of students on a large scale. The Depression Anxiety and Stress Scale-21(DASS-21) is used for the psychological questionnaire. The facial emotion recognition model is implemented by transfer learning based on neural networks, and the model is pre-trained using FER2013 and CFEE datasets. Among them, the FER2013 dataset consists of 48 × 48-pixel face gray images, a total of 35,887 face images. The CFEE dataset contains 950,000 facial images with annotated action units (au). Using a random sampling strategy, we sent online questionnaires to 400 college students and received 374 responses, and the response rate was 93.5%. After pre-processing, 350 results were available, including 187 male and 153 female students. First, the facial emotion data of students were collected in an online questionnaire test. Then, a pre-trained model was used for emotion recognition. Finally, the online psychological questionnaire scores and the facial emotion recognition model scores were collated to give a comprehensive psychological evaluation score.
RESULTS: The experimental results of the facial emotion recognition model proposed to show that its classification results are broadly consistent with the mental health survey results. This model can be used to improve efficiency. In particular, the accuracy of the facial emotion recognition model proposed in this paper is higher than that of the general mental health model, which only uses the traditional single questionnaire. Furthermore, the absolute errors of this study in the three symptoms of depression, anxiety, and stress are lower than other mental health survey results and are only 0.8%, 8.1%, 3.5%, and 1.8%, respectively.
CONCLUSION: The mixed method combining intelligent methods and scales for mental health assessment has high recognition accuracy. Therefore, it can support efficient large-scale screening of students' psychological problems.
METHODS: We searched related articles from January 1998 to December 2020 to obtain the prevalence and relative risks (or odds ratio) of GC associated with H. pylori in Asia. The burden of GC attributable to H. pylori infection was quantified by Population Attributable Fraction (PAF) and Disability-adjusted life-years (DALYs).
RESULTS: We quantified the burden of GC attributable to H. pylori infection with 415.6 thousand DALYs and 38.03% PAF through the five included Asian countries in 2019. The study found that the burden had obvious regional differences. The DALYs ranged from 298.9 thousand in China to 1.9 thousand in Malaysia, and the PAFs were between 58.00% in Japan and 30.89% in China. The average prevalence of H. pylori in the included general population was estimated to be 56.29%.
CONCLUSIONS: Helicobacter pylori poses a huge disease burden of GC to the population, and its eradication should receive attention, especially in the countries with high incidence of and mortality due to GC.
MATERIAL AND METHODS: Differential gene expression was identified using the "limma" package in R. Prognosis-related LncRNAs were identified via univariate Cox regression analysis, while a prognostic model was crafted using multivariate Cox regression analysis. Survival analysis was conducted using Kaplan-Meier curves. The precision of the prognostic model was assessed through ROC analysis. Subsequently, the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were executed on the TCGA dataset via the TIDE database. Fractions of 24 types of immune cell infiltration were obtained from NCI Cancer Research Data Commons using deconvolution techniques. The protein expression levels encoded by specific genes were obtained through the TPCA database.
RESULTS: In this research, we have identified 85 LncRNAs associated with TP53 mutations and developed a corresponding signature referred to as TP53MLncSig. Kaplan-Meier analysis revealed a lower 3-year survival rate in high-risk patients (46.9%) compared to low-risk patients (74.2%). The accuracy of the prognostic TP53MLncSig was further evaluated by calculating the area under the ROC curve. The analysis yielded a 5-year ROC score of 0.793, confirming its effectiveness. Furthermore, a higher score for TP53MLncSig was found to be associated with an increased response rate to immune checkpoint blocker (ICB) therapy (p = .005). Patients possessing high-risk classification exhibited lower levels of P53 protein expression and higher levels of genomic instability.
CONCLUSION: The present study aimed to identify and validate LncRNAs associated with TP53 mutations. We constructed a prognostic model that can predict chemosensitivity and response to ICB therapy in HCC patients. This novel approach sheds light on the role of LncRNAs in TP53 mutation and provides valuable resources for analyzing patient prognosis and treatment selection.
METHODS: PsycINFO, Web of Science, and PubMed databases were searched for articles published between January 1998 and December 2018. Fifty-seven studies met the inclusion criteria. All studies implemented the generative retrieval strategy by inducing memories through cue words or pictures, the life-stage method, or open-ended retrieval method. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement guidelines were followed for this review.
RESULTS: Most studies reported that patients with schizophrenia retrieve less specific autobiographical memories when compared to a healthy control group, while only three studies indicated that both groups performed similarly on memory specificity. Patients with schizophrenia also exhibited earlier reminiscence bumps than those for healthy controls. The relationship between comorbid depression and autobiographical memory specificity appeared to be independent because patients' memory specificity improved through intervention, but their level of depression remained unchanged. The U-shaped retrieval pattern for memory specificity was not consistent. Both the connection between the history of attempted suicide and autobiographical memory specificity, and the relationship between psychotic symptoms and autobiographical memory specificity, remain inconclusive. Patients' memory specificity and coherence improved through cognitive training.
CONCLUSIONS: The overgeneral recall of autobiographical memory by patients with schizophrenia could be attributed to working memory, the disturbing concept of self, and the cuing method implemented. The earlier reminiscence bump for patients with schizophrenia may be explained by the premature closure of the identity formation process due to the emergence of psychotic symptoms during early adulthood. Protocol developed for this review was registered in PROSPERO (registration no: CRD42017062643).
METHODS: We Searched China National Knowledge Infrastructure Database, Wan fang Database, CQVIP Journal Database、Web of Science Core Collection, Elsevier SD, Springer Online Journals, Medline, EBSCO-ERIC, SAGE Online Journals, PsycINFO, PsycArticles and ProQuest Dissertations and Theses。85 studies (90 independent effect size) were included from 2016 to 2023。The pooled correlation coefficient of the association between fear of missing out and mobile phone addiction was calculated by a random effects model using Comprehensive Meta-Analysis(Version 3.3).
RESULTS: The main effect analysis revealed a high positive correlation between fear of missing out and mobile phone addiction (r = 0.47, 95%CI [0.44, 0.50]). Furthermore, the measurements of mobile phone addiction moderated the strength of the association between fear of missing out and mobile phone addiction, with the highest correlation measured using MPATS and the lowest correlation measured using MPDQ. The age, gender, year of publication, cultural background, and the measurements of fear of missing out had no significant effect on the correlation between fear of missing out and mobile phone addiction.
CONCLUSION: The results indicated that fear of missing out was closely related to mobile phone addiction, which complied with the I-PACE model. Psychological services and mental health services should be developed to reduce the emergence of fear of missing out in the digital age and thus alleviate dependence on devices.