An automated identification method for adolescent schizophrenia based on brain electroencephalogram(EEG)entropy features is proposed for further improving the diagnostic accuracy of adolescent schizophrenia.The raw EEG signals are decomposed into 5 commonly used rhythm bands:Delta,Theta,Alpha,Beta,and Gamma.The permutation entropy,fuzzy entropy,and sample entropy are extracted from each rhythm band and then organized into a feature matrix structured by electrode location×frequency band.Finally,an ECA-CNN model integrating efficient channel attention(ECA)and convolutional neural network(CNN)is constructed for feature classification and realizing the automated identification of adolescent schizophrenia.The results demonstrate that the proposed ECA-CNN model has higher recognition accuracy than the traditional machine learning models,achieving an accuracy of 99.08%,a sensitivity of 99.27%,a specificity of 98.85%,a precision of 99.01%,a F1 score of 99.14%,and a Kappa coefficient of 0.9814.This study provides a new idea and method for the diagnosis of adolescent schizophrenia.

Objective To investigate the expression and significance of CD4+CD25+regulatory T cells(CD4+CD25+Treg)and soluble CD30(sCD30)in peripheral blood of lymphoma patients.Methods A total of 83 lymphoma patients admitted to Beijing Aerospace General Hospital from January 2018 to December 2022 were selected as the research subjects,and their peripheral blood CD4+CD25+Treg and sCD30 expressions were statistically analyzed.Spearman analysis was used to investigate the correlation between peripheral blood CD4+CD25+Treg and sCD30 expressions and bone marrow infiltration.At the same time,the research subjects were divided into an infection group(n=26)and a non-infection group(n=57)according to the presence or absence of infection after rituximab chemotherapy.The expressions and differences of peripheral blood CD4+CD25+Treg and sCD30 in the two groups were compared,and the receiver operating characteristic(ROC)curve and area under the curve(AUC)were used to analyze the predictive efficacy.Results The expression of CD4+CD25+Treg and sCD30 in peripheral blood of patients with bone marrow infiltration was higher than that of patients without bone marrow infiltration in the research group(P<0.05);the expression of CD4+CD25+Treg and sCD30 in peripheral blood of lymphoma patients was positively correlated with bone marrow infiltration(r=0.612,0.634,P<0.05);the expression of Tregs and sCD30 in peripheral blood of the infection group after chemotherapy was higher than that of the non-infection group,and the difference was higher than that of the non-infection group(P<0.05);the ROC curve showed that the combined prediction of the difference of CD4+CD25+Treg and sCD30 in peripheral blood for the infection after chemotherapy in lymphoma patients had an AUC of 0.916(0.834～0.965),which was superior to single prediction.Conclusion The high expression of CD4+CD25+Treg and sCD30 in peripheral blood of lymphoma patients is positively correlated with bone marrow infiltration.Combined testing can improve the predictive efficacy of infection after chemotherapy and guide clinical diagnosis and treatment.

An automated identification method for adolescent schizophrenia based on brain electroencephalogram(EEG)entropy features is proposed for further improving the diagnostic accuracy of adolescent schizophrenia.The raw EEG signals are decomposed into 5 commonly used rhythm bands:Delta,Theta,Alpha,Beta,and Gamma.The permutation entropy,fuzzy entropy,and sample entropy are extracted from each rhythm band and then organized into a feature matrix structured by electrode location×frequency band.Finally,an ECA-CNN model integrating efficient channel attention(ECA)and convolutional neural network(CNN)is constructed for feature classification and realizing the automated identification of adolescent schizophrenia.The results demonstrate that the proposed ECA-CNN model has higher recognition accuracy than the traditional machine learning models,achieving an accuracy of 99.08%,a sensitivity of 99.27%,a specificity of 98.85%,a precision of 99.01%,a F1 score of 99.14%,and a Kappa coefficient of 0.9814.This study provides a new idea and method for the diagnosis of adolescent schizophrenia.

Objective:To investigate the effects of LncRNA SNHG20 on epithelial mesenchymal transi-tion(EMT)and microtubule formation in human oral squamous cell carcinoma(OSCC)cells through targeted regulation of the miR-520c-3p/RAB22A pathway.Methods:After real-time fluorescence quanti-tative detection of LncRNA SNHG20,miR-520c-3p,RAB22A mRNA expression levels in OSCC tissues and cells,dual luciferase reporter assay was used to detect the relationship between the three.OSCC cells were randomly separated into control group,sh-NC group,sh-SNHG20 group,sh-SNHG20+anti NC group,and sh-SNHG20+anti miR-520c-3p group.Western blotting was used to detect the expres-sion of N-cadherin,vimentin,and E-cadherin proteins in the OSCC cells.The morphology of HSC-3 cells was observed under microscope.Changes in the number of microtubules formed were detected.The effect of LncRNA SNHG20 on the growth of OSCC tumors and the expression levels of LncRNA SNHG20,miR-520c-3p and RAB22 A in the transplanted tumors were detected by nude mice tumorigenesis experi-ment.Results:LncRNA SNHG20 and RAB22A mRNA were upregulated in the OSCC tissues and cells,while miR-520c-3p was downregulated(P＜0.05).There were binding sites between LncRNA SNHG20 and miR-520c-3p,RAB22A and miR-520c-3p,which had targeted regulation relationship.Compared with the sh-NC group,the sh-SNHG20 group had fewer stromal like cells,more epithelial like cells,incomplete microtubule structure,and fewer nodules.LncRNA SNHG20,RAB22A,N-Cadherin,and vimentin were downregulated,while miR-520c-3p and E-cadherin were upregulated(P＜0.05).Compared with the sh-SNHG20+anti-NC group,the sh-SNHG20+anti-miR-520c-3 p group had a higher number of stromal like cells,a lower number of epithelioid cells,tighter microtubule arrangement,and more micro-tubule nodules.miR-520c-3p and E-cadherin were downregulated,while RAB22A,N-cadherin,and vi-mentin were upregulated(P＜0.05).The transplanted tumor of OSCC in sh-SNHG20 group was smaller and lower than that in sh-NC group.The expression levels of LncRNA SNHG20 and RAB22A in the transplanted tumor tissues were lower than those in sh-NC group,and the expression level of miR-520c-3p was higher than that in sh-NC group(P＜0.05).Conclusion:LncRNA SNHG20 promotes epitheli-al-mesenchymal transition and microtubule formation in human oral squamous cell carcinoma cells by tar-geting the miR-520c-3p/RAB22A pathway.Inhibiting the expression of LncRNA SNHG20 can target and regulate the miR-520c-3p/RAB22A pathway to inhibit EMT and microtubule formation in OSCC cells.

Background/Aims: To evaluate the causal correlation between complement components and non-viral liver diseases and their potential use as druggable targets. Methods: We conducted Mendelian randomization (MR) to assess the causal role of circulating complements in the risk of non-viral liver diseases. A complement-centric protein interaction network was constructed to explore biological functions and identify potential therapeutic options. Results: In the MR analysis, genetically predicted levels of complement C1q C chain (C1QC) were positively associated with the risk of autoimmune hepatitis (odds ratio 1.125, 95% confidence interval 1.018–1.244), while complement factor H-related protein 5 (CFHR5) was positively associated with the risk of primary sclerosing cholangitis (PSC;1.193, 1.048– 1.357). On the other hand, CFHR1 (0.621, 0.497–0.776) and CFHR2 (0.824, 0.703–0.965) were inversely associated with the risk of alcohol-related cirrhosis. There were also significant inverse associations between C8 gamma chain (C8G) and PSC (0.832, 0.707–0.979), as well as the risk of metabolic dysfunction-associated steatotic liver disease (1.167, 1.036–1.314). Additionally, C1S (0.111, 0.018–0.672), C7 (1.631, 1.190–2.236), and CFHR2 (1.279, 1.059–1.546) were significantly associated with the risk of hepatocellular carcinoma. Proteins from the complement regulatory networks and various liver diseaserelated proteins share common biological processes. Furthermore, potential therapeutic drugs for various liver diseases were identified through drug repurposing based on the complement regulatory network. Conclusions Our study suggests that certain complement components, including C1S, C1QC, CFHR1, CFHR2, CFHR5, C7, and C8G, might play a role in non-viral liver diseases and could be potential targets for drug development.

Sheep pox is widespread worldwide and is the most severe animal pox virus infection. This study aimed to identify the key microRNAs (miRNAs) differentially expressed in the exosomes of sheep poxvirus-infected cells and their target genes and related pathways and provide a theoretical basis for an in-depth understanding of the molecular mechanisms of sheep poxvirus-infected cells. In this study, the differentially expressed miRNAs were verified by quantitative polymerase chain reaction (qPCR), and the target genes of miRNAs were predicted and analyzed by bioinformatics. The qPCR results showed that the expression trends of oar-miR-21, oar-miR-10b, oar-let-7f, oar-let-7b, and oar-miR-221 were consistent with the sequencing results. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes results showed that differentially expressed miRNAs were mainly involved in the immune system processes of the Arf6 downstream pathway. The target genes Reactome pathways were mainly enriched in the RAC1 GTPase cycle, CDC42 GTPase cycle, RHO GTPase cycle, RHOV GTPase cycle, and post-transcriptional silencing of small RNAs. The transcription factors SP4, NKX6-1, MEF2A, SP1, EGR1, and POU2F1 that may be connected to sheep pox virus (SPPV)-infected cells were discovered by transcription factor annotation screening. In conclusion, this study screened for differentially expressed miRNAs in SPPV-infected cells and performed a series of bioinformatic analyses of their target genes to provide a theoretical basis for the molecular mechanism of sheep pox virus infections of cells. The data can be used as basic information in future studies on the defense mechanisms against poxvirus infections.

Sheep pox is widespread worldwide and is the most severe animal pox virus infection. This study aimed to identify the key microRNAs (miRNAs) differentially expressed in the exosomes of sheep poxvirus-infected cells and their target genes and related pathways and provide a theoretical basis for an in-depth understanding of the molecular mechanisms of sheep poxvirus-infected cells. In this study, the differentially expressed miRNAs were verified by quantitative polymerase chain reaction (qPCR), and the target genes of miRNAs were predicted and analyzed by bioinformatics. The qPCR results showed that the expression trends of oar-miR-21, oar-miR-10b, oar-let-7f, oar-let-7b, and oar-miR-221 were consistent with the sequencing results. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes results showed that differentially expressed miRNAs were mainly involved in the immune system processes of the Arf6 downstream pathway. The target genes Reactome pathways were mainly enriched in the RAC1 GTPase cycle, CDC42 GTPase cycle, RHO GTPase cycle, RHOV GTPase cycle, and post-transcriptional silencing of small RNAs. The transcription factors SP4, NKX6-1, MEF2A, SP1, EGR1, and POU2F1 that may be connected to sheep pox virus (SPPV)-infected cells were discovered by transcription factor annotation screening. In conclusion, this study screened for differentially expressed miRNAs in SPPV-infected cells and performed a series of bioinformatic analyses of their target genes to provide a theoretical basis for the molecular mechanism of sheep pox virus infections of cells. The data can be used as basic information in future studies on the defense mechanisms against poxvirus infections.

Sheep pox is widespread worldwide and is the most severe animal pox virus infection. This study aimed to identify the key microRNAs (miRNAs) differentially expressed in the exosomes of sheep poxvirus-infected cells and their target genes and related pathways and provide a theoretical basis for an in-depth understanding of the molecular mechanisms of sheep poxvirus-infected cells. In this study, the differentially expressed miRNAs were verified by quantitative polymerase chain reaction (qPCR), and the target genes of miRNAs were predicted and analyzed by bioinformatics. The qPCR results showed that the expression trends of oar-miR-21, oar-miR-10b, oar-let-7f, oar-let-7b, and oar-miR-221 were consistent with the sequencing results. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes results showed that differentially expressed miRNAs were mainly involved in the immune system processes of the Arf6 downstream pathway. The target genes Reactome pathways were mainly enriched in the RAC1 GTPase cycle, CDC42 GTPase cycle, RHO GTPase cycle, RHOV GTPase cycle, and post-transcriptional silencing of small RNAs. The transcription factors SP4, NKX6-1, MEF2A, SP1, EGR1, and POU2F1 that may be connected to sheep pox virus (SPPV)-infected cells were discovered by transcription factor annotation screening. In conclusion, this study screened for differentially expressed miRNAs in SPPV-infected cells and performed a series of bioinformatic analyses of their target genes to provide a theoretical basis for the molecular mechanism of sheep pox virus infections of cells. The data can be used as basic information in future studies on the defense mechanisms against poxvirus infections.

Sheep pox is widespread worldwide and is the most severe animal pox virus infection. This study aimed to identify the key microRNAs (miRNAs) differentially expressed in the exosomes of sheep poxvirus-infected cells and their target genes and related pathways and provide a theoretical basis for an in-depth understanding of the molecular mechanisms of sheep poxvirus-infected cells. In this study, the differentially expressed miRNAs were verified by quantitative polymerase chain reaction (qPCR), and the target genes of miRNAs were predicted and analyzed by bioinformatics. The qPCR results showed that the expression trends of oar-miR-21, oar-miR-10b, oar-let-7f, oar-let-7b, and oar-miR-221 were consistent with the sequencing results. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes results showed that differentially expressed miRNAs were mainly involved in the immune system processes of the Arf6 downstream pathway. The target genes Reactome pathways were mainly enriched in the RAC1 GTPase cycle, CDC42 GTPase cycle, RHO GTPase cycle, RHOV GTPase cycle, and post-transcriptional silencing of small RNAs. The transcription factors SP4, NKX6-1, MEF2A, SP1, EGR1, and POU2F1 that may be connected to sheep pox virus (SPPV)-infected cells were discovered by transcription factor annotation screening. In conclusion, this study screened for differentially expressed miRNAs in SPPV-infected cells and performed a series of bioinformatic analyses of their target genes to provide a theoretical basis for the molecular mechanism of sheep pox virus infections of cells. The data can be used as basic information in future studies on the defense mechanisms against poxvirus infections.

To address the problem of low accuracy in multi-classification recognition of motor imagery electroencephalogram(EEG)signals,a recognition method is proposed based on differential entropy and convolutional neural network for 4-class classification of motor imagery.EEG signals are extracted into 4 frequency bands(Alpha,Beta,Theta,and Gamma)through the filter,followed by the computation of differential entropy for each frequency band.According to the spatial characteristics of brain electrodes,the data structure is reconstructed into three-dimensional EEG signal feature cube which is input into convolutional neural network for 4-class classification.The method achieves an accuracy of 95.88%on the BCI Competition IV-2a public dataset.Additionally,a 4-class classification motor imagery dataset is established in the laboratory for the same processing,and an accuracy of 94.50%is obtained.The test results demonstrate that the proposed method exhibits superior recognition performance.