A replication study separates polymorphisms behind migraine with and without depression

The largest migraine genome-wide association study identified 38 candidate loci. In this study we assessed whether these results replicate on a gene level in our European cohort and whether effects are altered by lifetime depression. We tested SNPs of the loci and their vicinity with or without interaction with depression in regression models. Advanced analysis methods such as Bayesian relevance analysis and a neural network based classifier were used to confirm findings. Main effects were found for rs2455107 of PRDM16 (OR = 1.304, p = 0.007) and five intergenic polymorphisms in 1p31.1 region: two of them showed risk effect (OR = 1.277, p = 0.003 for both rs11209657 and rs6686879), while the other three variants were protective factors (OR = 0.4956, p = 0.006 for both rs12090642 and rs72948266; OR = 0.4756, p = 0.005 for rs77864828). Additionally, 26 polymorphisms within ADGRL2, 2 in REST, 1 in HPSE2 and 33 mostly intergenic SNPs from 1p31.1 showed interaction effects. Among clumped results representing these significant regions, only rs11163394 of ADGRL2 showed a protective effect (OR = 0.607, p = 0.002), all other variants were risk factors (rs1043215 of REST with the strongest effect: OR = 6.596, p = 0.003). Bayesian relevance analysis confirmed the relevance of intergenic rs6660757 and rs12128399 (p31.1), rs1043215 (REST), rs1889974 (HPSE2) and rs11163394 (ADGRL2) from depression interaction results, and the moderate relevance of rs77864828 and rs2455107 of PRDM16 from main effect analysis. Both main and interaction effect SNPs could enhance predictive power with the neural network based classifier. In summary, we replicated p31.1, PRDM16, REST, HPSE2 and ADGRL2 genes with classic genetic and advanced analysis methods. While the p31.1 region and PRDM16 are worthy of further investigations in migraine in general, REST, HPSE2 and ADGRL2 may be prime candidates behind migraine pathophysiology in patients with comorbid depression.

Pan-Cancer Analyses of the Tumor Microenvironment Reveal That Ubiquitin-Conjugating Enzyme E2C Might Be a Potential Immunotherapy Target

Increasing evidence indicated that the tumor microenvironment (TME) played a crucial role in cancer initiation and progression. Ubiquitin-conjugating enzyme E2C (UBE2C) was differentially expressed in many cancer types. However, the immunological and prognostic roles of UBE2C were unclear. Differentially expressed genes (DEGs) of 29 cancer types were downloaded from GEPIA2 and 4 cancer types failed to download owing to no DEGs. Furthermore, the gene expression profiles, mutation data, and survival data of 33 cancer types were obtained from UCSC Xena. Clinical stage relevance, tumor mutational burden (TMB), TME relevance analysis, and gene set enrichment analysis (GSEA) of DEGs in 33 cancer types were performed. And DEGs were identified in oral squamous cell carcinoma (OSCC) by biological experiments. Previous studies indicated that UBE2C was related to the prognosis of many cancers. In our study, the higher UBE2C expression level meant a terminal clinical stage in 8 cancer types and the expression level of UBE2C was related to TMB in 20 cancer types. In addition, both immune relevance analysis and GSEA showed that UBE2C might participate in immune response in many cancers. Furthermore, the UBE2C mRNA level and protein level were all identified as upregulated in OSCC cell lines and tissues. UBE2C was differentially expressed in many cancer types and related to the pathogenesis and TME of many cancers, which might be a potential diagnostic and therapeutic biomarker.

Moral Analysis in the Videos of English Fairy Tales Channel and Its Relevance to Narrative Text Learning in Senior High School

This study analyzes the moral values of legends and fairy tales on the English Fairy Tales YouTube channel and examines its relevance to narrative text learning in schools. The approach used is qualitative research, with descriptive type. The sample videos taken from the English Fairy Tales channel are five videos. According to theory, analysis of moral values is carried out by looking at video samples and describing them. In contrast, relevance analysis will be carried out by reviewing the applicable learning syllabus. The research found that the videos analyzed contain values always to be grateful to God, care for others, be diligent, be brave, help each other, keep promises, and never give up. In addition, the moral values found in legends and fairy tales on the English Fairy Tales YouTube channel have relevance to the teaching of narrative texts in class X of Senior High School because the moral values contained in legends and fairy tales on the English Fairy Tales YouTube channel can support the use of English Fairy Tales channel videos as learning media that is in line with the learning competence.

Kernel-Based Phase Transfer Entropy with Enhanced Feature Relevance Analysis for Brain Computer Interfaces

Neural oscillations are present in the brain at different spatial and temporal scales, and they are linked to several cognitive functions. Furthermore, the information carried by their phases is fundamental for the coordination of anatomically distributed processing in the brain. The concept of phase transfer entropy refers to an information theory-based measure of directed connectivity among neural oscillations that allows studying such distributed processes. Phase TE is commonly obtained from probability estimations carried out over data from multiple trials, which bars its use as a characterization strategy in brain–computer interfaces. In this work, we propose a novel methodology to estimate TE between single pairs of instantaneous phase time series. Our approach combines a kernel-based TE estimator defined in terms of Renyi’s α entropy, which sidesteps the need for probability distribution computation with phase time series obtained by complex filtering the neural signals. Besides, a kernel-alignment-based relevance analysis is added to highlight relevant features from effective connectivity-based representation supporting further classification stages in EEG-based brain–computer interface systems. Our proposal is tested on simulated coupled data and two publicly available databases containing EEG signals recorded under motor imagery and visual working memory paradigms. Attained results demonstrate how the introduced effective connectivity succeeds in detecting the interactions present in the data for the former, with statistically significant results around the frequencies of interest. It also reflects differences in coupling strength, is robust to realistic noise and signal mixing levels, and captures bidirectional interactions of localized frequency content. Obtained results for the motor imagery and working memory databases show that our approach, combined with the relevance analysis strategy, codes discriminant spatial and frequency-dependent patterns for the different conditions in each experimental paradigm, with classification performances that do well in comparison with those of alternative methods of similar nature.

Moral Analysis in the Videos of Dongeng Kita Channel and Its Relevance to Indonesian Learning

This research aims to analyze the moral values in folklore videos on the Dongeng Kita Youtube channel and analyze its relevance to Indonesian learning in schools. The approach of this research is qualitative research, with a descriptive type. There are six video samples taken from the Dongeng Kita channel. The moral analysis is conducted by observing the sample videos and describing it according to theory, while relevance analysis is done by reviewing the applicable learning syllabus. The research found that the videos contained moral values of respect for others, not being disobedient to parents, being honest, not being lazy, not being bad, not being greedy, keeping promises, and not cheating. Besides, moral values were found to have relevance in Indonesian learning for the grade VII of Junior High Schools because the moral values can support the use of the Dongeng Kita channel as a learning media that is linear with the learning competencies of the 2013 Curriculum, which aims to develop student moral. It is expected that Indonesian teachers in schools will take advantage of the Dongeng Kita channel as a learning media to make learning more enjoyable.