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Background To establish and validate a radiomics-based model for predicting liver cirrhosis in patients with hepatitis B virus (HBV) by using non-contrast computed tomography (CT). Methods This retrospective study developed a radiomics-based model in a training cohort of 144 HBV-infected patients. Radiomic features were extracted from abdominal non-contrast CT scans. Features selection was performed with the least absolute shrinkage and operator (LASSO) method based on highly reproducible features. Support vector machine (SVM) was adopted to build a radiomics signature. Multivariate logistic regression analysis was used to establish a radiomics-based nomogram that integrated radiomics signature and other independent clinical predictors. Performance of models was evaluated through discrimination ability, calibration and clinical benefits. An internal validation was conducted in 150 consecutive patients. Results The radiomics signature comprised 25 cirrhosis-related features and showed significant differences between cirrhosis and non-cirrhosis cohorts (P < 0.001). A radiomics-based nomogram that integrates radiomics signature, alanine transaminase, aspartate aminotransferase, globulin and international normalized ratio showed great calibration and discrimination ability in the training cohort (area under the curve [AUC]: 0.915) and the validation cohort (AUC: 0.872). Decision curve analysis confirmed the most clinical benefits can be provided by the nomogram compared with other methods. Conclusions Our developed radiomics-based nomogram can successfully diagnose the status of cirrhosis in HBV-infected patients, that may help clinical decision-making.

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Background: Circular RNAs (circRNAs) are now under hot discussion as novel promising bio-markers for patients with hepatocellular carcinoma. The purpose of our study is to identify several competing endogenous RNAs (ceRNAs) networks related to the prognosis and progression of hepatocellular carcinoma, and to further investigate the mechanism of their influence on tumor progression.Methods: First, we obtained gene expression data related to liver cancer from the TCGA database (http://www.portal.gdc.cancer.gov/), including miRNA-seq, RNA-seq and clinical information. A co-expression network was constructed through the WGCNA software package in R software, with the purpose of identifying important microRNAs (miRNAs) and messenger RNAs (mRNAs) related to liver cancer. The DEmRNAs in the key module were analyzed with DAVID (https://david.ncifcrf.gov/summary.jsp) to perform functional enrichment analysis including Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO). The data of miRNA expression and clinical information downloaded from TCGA was utilized for survival analysis to detach the prognostic value of the DEmiRNAs of the key module. Results：201 DEmiRNAs and 3783 DEmRNAs were finally identified through differential expression analysis. The co-expression networks of DEmiRNA and DEmRNA were constructed by using WGCNA. Further analysis confirmed 4 miRNAs in the most significant module (blue module) were associated with the OS of patients with liver cancer, including hsa-miR-92b-3p, hsa-miR-122-3p, hsa-miR-139-5p and hsa-miR-7850-5p. DAVID was used for functional enrichment analysis of 286 co-expressed mRNAs. The Gene Ontology (GO) analysis results showed that the top enriched GO terms were oxidation-reduction process, extracellular exosome and iron ion binding. In Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, the top 3 enriched terms included metabolic pathways, fatty acid degradation and valine, leucine and isoleucine degradation. In addition, we corssed the miRNA-mRNA interactions prediction results with the differentially expressed and prognostic mRNAs, and found that hsa-miR-92b-3p can be related to cytoplasmic polyadenylation element binding protein 3 (CPEB3) and Acyl-CoA Dehydrogenase Long Chain (ACADL). By overlapping the data of predicted circRNAs by circBank and differentially expressed circRNAs of GSE94508, we screened has_circ_0077210 as the upstream regulatory molecule of hsa-miR-92b-3p. Hsa_circ_0077210/hsa-miR-92b-3p/CPEB3&ACADL were validated in hepatic cell carcinoma (HCC) tissues and human protein atlas (HPA) database.Conclusion: Our research provides a mechanistic elucidation of the unknown ceRNA regulatory network in HCC. Hsa_circ_0077210 might serve as an important biomarker to promote the occurrence and development of HCC.

BackgroundCircular RNAs (circRNAs) are now under hot discussion as novel promising biomarkers for patients with hepatocellular carcinoma (HCC). The purpose of our study is to identify several competing endogenous RNA (ceRNA) networks related to the prognosis and progression of HCC and to further investigate the mechanism of their influence on tumor progression.MethodsFirst, we obtained gene expression data related to liver cancer from The Cancer Genome Atlas (TCGA) database (http://www.portal.gdc.cancer.gov/), including microRNA (miRNA) sequence, RNA sequence, and clinical information. A co-expression network was constructed through the Weighted Correlation Network Analysis (WGCNA) software package in R software. The differentially expressed messenger RNAs (DEmRNAs) in the key module were analyzed with the Database for Annotation Visualization and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/summary.jsp) to perform functional enrichment analysis including Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The data of miRNA expression and clinical information downloaded from TCGA were utilized for survival analysis to detach the prognostic value of the DEmiRNAs of the key module.ResultsThe 201 differentially expressed miRNAs (DEmiRNAs) and 3,783 DEmRNAs were preliminarily identified through differential expression analysis. The co-expression networks of DEmiRNAs and DEmRNAs were constructed with WGCNA. Further analysis confirmed four miRNAs in the most significant module (blue module) were associated with the overall survival (OS) of patients with liver cancer, including hsa-miR-92b-3p, hsa-miR-122-3p, hsa-miR-139-5p, and hsa-miR-7850-5p. DAVID was used for functional enrichment analysis of 286 co-expressed mRNAs. The GO analysis results showed that the top enriched GO terms were oxidation–reduction process, extracellular exosome, and iron ion binding. In KEGG pathway analysis, the top three enriched terms included metabolic pathways, fatty acid degradation, and valine, leucine, and isoleucine degradation. In addition, we intersected the miRNA–mRNA interaction prediction results with the differentially expressed and prognostic mRNAs. We found that hsa-miR-92b-3p can be related to CPEB3 and ACADL. By overlapping the data of predicted circRNAs by circBank and differentially expressed circRNAs of GSE94508, we screened has_circ_0077210 as the upstream regulatory molecule of hsa-miR-92b-3p. Hsa_circ_0077210/hsa-miR-92b-3p/cytoplasmic polyadenylation element binding protein-3 (CPEB3) and acyl-Coenzyme A dehydrogenase, long chain (ACADL) were validated in HCC tissue.ConclusionOur research provides a mechanistic elucidation of the unknown ceRNA regulatory network in HCC. Hsa_circ_0077210 might serve a momentous therapeutic role to restrain the occurrence and development of HCC.

Objective. With the development of clinical applications of motor imagery-based brain–computer interfaces (MI-BCIs), a single-channel MI-BCI system that can be easily assembled is an attractive goal. However, due to the low quality of the spectral power features in the traditional MI-BCI paradigm, the recognition performance of current single-channel systems is far lower than that of multi-channel systems, impeding their use in clinical applications. Approach. In this study, the subjects’ right and left hands were stimulated simultaneously at different frequencies to induce steady-state somatosensory evoked potentials (SSSEP). Subjects then performed motor imagery (MI) tasks. A new electroencephalography (EEG) index, inter-stimulus phase coherence (ISPC), was built to measure phase desynchronization of SSSEP caused by MI. Then, ISPC is introduced as a feature into left-hand and right-hand MI recognition. Main results. ISPC analysis found that left-handed MI can cause a significant decrease in phase synchronization in contralateral sensorimotor SSSEP, while right-handed MI has little effect on it, and vice versa. Combining ISPC features with traditional spectral power features, the single-channel left-hand versus right-hand MI recognition accuracy reaches 81.0%, which is much higher than that observed with traditional MI paradigms (about 60%). Significance. This work shows that the hybrid MI-SSSEP paradigm can provide more sensitive EEG features to decode motor intentions, demonstrating its potential for clinical applications.

Hepatocellular carcinoma (HCC) is one of the most fatal tumours worldwide and has a high recurrence rate. Nevertheless, the mechanism of HCC genesis remains partly unexplored, while the efficiency of HCC treatments remains limited. The present study analysed the expression of nuclear receptor subfamily 4 group A member 1 (NR4A1) in tumour‐infiltrating natural killer (NK) cells derived from both human patients with HCC and tumour‐bearing mouse models, as well as the features of NR4A1high and NR4A1low NK cells. In addition, knockout of NR4A1 by CRISPR/Cas9 and adoptive transfer experiments were applied to verify the function of NR4A1 in both tumour‐infiltrating NK cells and anti‐PD‐1 therapy. The present study found that NR4A1 was significantly highly expressed in tumour‐infiltrating NK cells, which mediated the dysfunction of tumour‐infiltrating NK cells by regulating the IFN‐γ/p‐STAT1/IRF1 signalling pathway. Knockout of NR4A1 in NK cells not only restored the antitumour function of NK cells but also enhanced the efficacy of anti‐PD‐1 therapy. The present findings suggest a regulatory role of NR4A1 in the immune progress of NK cells against HCC, which may provide a new direction for immunotherapies of HCC.