An updated Lnc2Cancer 3.0 (http://www.bio-bigdata.net/lnc2cancer or http://bio-bigdata.hrbmu.edu.cn/lnc2cancer) database, which includes comprehensive data on experimentally supported long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) associated with human cancers. In addition, web tools for analyzing lncRNA expression by high-throughput RNA sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) are described. Lnc2Cancer 3.0 was updated with several new features, including (i) Increased cancer-associated lncRNA entries over the previous version. The current release includes 9254 lncRNA-cancer associations, with 2659 lncRNAs and 216 cancer subtypes. (ii) Newly adding 1049 experimentally supported circRNA-cancer associations, with 743 circRNAs and 70 cancer subtypes. (iii) Experimentally supported regulatory mechanisms of cancer-related lncRNAs and circRNAs, involving microRNAs, transcription factors (TF), genetic variants, methylation and enhancers were included. (iv) Appending experimentally supported biological functions of cancer-related lncRNAs and circRNAs including cell growth, apoptosis, autophagy, epithelial mesenchymal transformation (EMT), immunity and coding ability. (v) Experimentally supported clinical relevance of cancer-related lncRNAs and circRNAs in metastasis, recurrence, circulation, drug resistance, and prognosis was included. Additionally, two flexible online tools, including RNA-seq and scRNA-seq web tools, were developed to enable fast and customizable analysis and visualization of lncRNAs in cancers. Lnc2Cancer 3.0 is a valuable resource for elucidating the associations between lncRNA, circRNA and cancer.

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Individuals with IAD and PG patients present deficiencies in working memory, executive dysfunction and impulsivity, and individuals with IAD are more impulsive than PG patients.

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Background Major depressive disorder (MDD) is characterized by core functional deficits in cognitive inhibition, which is crucial for emotion regulation. To assess the response to ruminative and negative mood states, it was hypothesized that MDD patients have prolonged disparities in the oscillatory dynamics of the frontal cortical regions across the life course of the disease. Method A “go/no-go” response inhibition paradigm was tested in 31 MDD patients and 19 age-matched healthy controls after magnetoencephalography (MEG) scanning. The use of minimum norm estimates (MNE) examined the changes of inhibitory control network which included the right inferior frontal gyrus ( r IFG), pre-supplementary motor area (preSMA), and left primary motor cortex ( l M1). The power spectrum (PS) within each node and the functional connectivity (FC) between nodes were compared between two groups. Furthermore, Pearson correlation was calculated to estimate the relationship between altered FC and clinical features. Result PS was significantly reduced in left motor and preSMA of MDD patients in both beta (13–30 Hz) and low gamma (30–50 Hz) bands. Compared to the HC group, the MDD group demonstrated higher connectivity between l M1 and preSMA in the beta band ( t = 3.214, p = 0.002, FDR corrected) and showed reduced connectivity between preSMA and r IFG in the low gamma band ( t = −2.612, p = 0.012, FDR corrected). The FC between l M1 and preSMA in the beta band was positively correlated with illness duration ( r = 0.475, p = 0.005, FDR corrected), while the FC between preSMA and r IFG in the low gamma band was negatively correlated with illness duration ( r = −0.509, p = 0.002, FDR corrected) and retardation factor scores ( r = −0.288, p = 0.022, uncorrected). Conclusion In this study, a clinical neurophysiological signature of cognitive inhibition leading to sustained negative affect as well as functional non-recovery in MDD patients is highlighted. Duration of illness (DI) plays a key role in negative emotional processing, heighten rumination, impulsivity, and disinhibition.

Many biological indicators related to chronological age have been proposed. Recent studies found that epigenetic clock or DNA methylation age is highly correlated with chronological age. In particular, a significant difference between DNA methylation age (m-age) and chronological age was observed in cancers. However, the prediction and characterization of m-age in pan-cancer remains an explored area. In this study, 1,631 age-related methylation sites in normal tissues were discovered and analyzed. A comprehensive computational model named CancerClock was constructed to predict the m-age for normal samples based on methylation levels of the extracted methylation sites. LASSO linear regression model was used to screen and train the CancerClock model in normal tissues. The accuracy of CancerClock has proved to be 81%, and the correlation value between chronological age and m-age was 0.939 (P < 0.01). Next, CancerClock was used to evaluate the difference between m-age and chronological age for 33 cancer types from TCGA. There were significant differences between predicted m-age and chronological age in large number of cancer samples. These cancer samples were defined as “age-related cancer samples” and they have some differential methylation sites. The differences between predicted m-age and chronological age may contribute to cancer development. Some of these differential methylation sites were associated with cancer survival. CancerClock provided assistance in estimating the m-age in normal and cancer samples. The changes between m-age and chronological age may improve the diagnosis and prognosis of cancers.

Internet addiction is a sort of non-psychoactive substance dependence. The Implicit Association Test (IAT) is used to measure implicit cognition. Event-related potential (ERP) is one of the most widely used methods in cognitive neuroscience research to investigate the physiological correlates of cognitive activity associated with processing information. Further investigating the ERP characteristics of implicit cognitive bias in Internet addiction would be helpful in understanding the nature of Internet addiction. This study investigated the ERP characteristics of implicit cognitive bias in Internet addiction. The participants included 60 Internet-addicted individuals (IAG) and 60 normal controls (NCG). All participants were measured with ERPs using the IAT. The results showed that there was a significant difference in the Internet-related IAT effect for reaction times between IAG and NCG, and there were stronger positive implicit associations toward Internet related cues in IAG than NCG. Using P1, N2, P3, and N4 as dependent variables, a mixed repeated-measures analysis of variance (ANOVA) on the mean latencies and mean amplitudes revealed a significant interaction between the groups (IAG vs. NCG) and stimulus condition (compatible trials vs. incompatible trials) for the N2 and P3 amplitudes; the simple effects analysis showed that the N2 and P3 amplitudes were larger under the IAG-compatible trial conditions than under the IAG-incompatible trial conditions. In the IAG group, the positive implicit associations with Internet-related cues elicited larger N2 and P3 amplitudes at the occipital lobe sites. These results indicated that Internet addictive individuals show stronger positive implicit associations toward Internet-related cues, and the positive implicit associations toward Internet-related cues elicited ERP changes at occipital lobe sites.

Objective: Circular RNAs (circRNAs) function as promising biomarkers and therapeutic targets for coronary artery disease due to their high stability, covalently closed structure and potential gene regulation. We aimed to identify the expression profile and role of circular RNAs (circRNAs) in coronary artery disease (CAD). Methods: We performed RNA sequence analysis of circRNAs in peripheral blood mononuclear cells of 5 CAD patients and 5 controls. Bioinformatics analyses was adopted to explore biological functions of differentially expressed circRNAs. The miRanda and TargetScan tools were used to predict the miRNA targeting interactions and to construct a triple network of differentially expressed gene-circRNA-miRNA-mRNA. Results: In total, 13160 downregulated and 12905 upregulated circRNAs were identified in CAD. A gene ontology annotation analysis showed that genes in the network were involved in organelle organization, cell cycle, mitotic cycle and cellular metabolic process. Parental genes of the 10 dysregulated-circRNAs were involved in metabolism and protein modification, and these circRNAs might regulate gene expression associated with CAD via miRNA sponges. Conclusion: As potential ceRNAs, dysregulated circRNAs may be involved in the pathogenesis of CAD, which provides new insights into diagnosis and prognosis of coronary artery disease.