Integrative Analyses Identify Potential Key Genes and Calcium-Signaling Pathway in Familial Atrioventricular Nodal Reentrant Tachycardia Using Whole-Exome Sequencing

BackgroundAtrioventricular nodal reentrant tachycardia (AVNRT) is a common arrhythmia. Growing evidence suggests that family aggregation and genetic factors are involved in AVNRT. However, in families with a history of AVNRT, disease-causing genes have not been reported.ObjectiveTo investigate the genetic contribution of familial AVNRT using a whole-exome sequencing (WES) approach.MethodsBlood samples were collected from 20 patients from nine families with a history of AVNRT and 100 control participants, and we systematically analyzed mutation profiles using WES. Gene-based burden analysis, integration of previous sporadic AVNRT data, pedigree-based co-segregation, protein-protein interaction network analysis, single-cell RNA sequencing, and confirmation of animal phenotype were performed.ResultsAmong 95 related reference genes, seven candidate pathogenic genes have been identified both in sporadic and familial AVNRT, including CASQ2, AGXT, ANK2, SYNE2, ZFHX3, GJD3, and SCN4A. Among the 37 reference genes from sporadic AVNRT, five candidate pathogenic genes were identified in patients with both familial and sporadic AVNRT: LAMC1, ryanodine receptor 2 (RYR2), COL4A3, NOS1, and ATP2C2. To identify the common pathogenic mechanisms in all AVNRT cases, five pathogenic genes were identified in patients with both familial and sporadic AVNRT: LAMC1, RYR2, COL4A3, NOS1, and ATP2C2. Considering the unique internal candidate pathogenic gene within pedigrees, three genes, TRDN, CASQ2, and WNK1, were likely to be the pathogenic genes in familial AVNRT. Notably, the core calcium-signaling pathway may be closely associated with the occurrence of AVNRT, including CASQ2, RYR2, TRDN, NOS1, ANK2, and ATP2C2.ConclusionOur pedigree-based studies demonstrate that RYR2 and related calcium signaling pathway play a critical role in the pathogenesis of familial AVNRT using the WES approach

Inhibition of Osteoclastogenesis and Bone Resorption in vitro and in vivo by a prenylflavonoid xanthohumol from hops

Excessive RANKL signaling leads to superfluous osteoclast formation and bone resorption, is widespread in the pathologic bone loss and destruction. Therefore, targeting RANKL or its signaling pathway has been a promising and successful strategy for this osteoclast-related diseases. In this study, we examined the effects of xanthohumol (XN), an abundant prenylflavonoid from hops plant, on osteoclastogenesis, osteoclast resorption, and RANKL-induced signaling pathway using both in vitro and in vivo assay systems. In mouse and human, XN inhibited osteoclast differentiation and osteoclast formation at the early stage. Furthermore, XN inhibited osteoclast actin-ring formation and bone resorption in a dose-dependent manner. In ovariectomized-induced bone loss mouse model and RANKL-injection-induced bone resorption model, we found that administration of XN markedly inhibited bone loss and resorption by suppressing osteoclast activity. At the molecular level, XN disrupted the association of RANK and TRAF6, resulted in the inhibition of NF-κB and Ca(2+)/NFATc1 signaling pathway during osteoclastogenesis. As a results, XN suppressed the expression of osteoclastogenesis-related marker genes, including CtsK, Nfatc1, Trap, Ctr. Therefore, our data demonstrated that XN inhibits osteoclastogenesis and bone resorption through RANK/TRAF6 signaling pathways. XN could be a promising drug candidate in the treatment of osteoclast-related diseases such as postmenopausal osteoporosis

Diagnostic Accuracy of Deep Learning and Radiomics in Lung Cancer Staging: A Systematic Review and Meta-Analysis

BackgroundArtificial intelligence has far surpassed previous related technologies in image recognition and is increasingly used in medical image analysis. We aimed to explore the diagnostic accuracy of the models based on deep learning or radiomics for lung cancer staging.MethodsStudies were systematically reviewed using literature searches from PubMed, EMBASE, Web of Science, and Wanfang Database, according to PRISMA guidelines. Studies about the diagnostic accuracy of radiomics and deep learning, including the identifications of lung cancer, tumor types, malignant lung nodules and lymph node metastase, were included. After identifying the articles, the methodological quality was assessed using the QUADAS-2 checklist. We extracted the characteristic of each study; the sensitivity, specificity, and AUROC for lung cancer diagnosis were summarized for subgroup analysis.ResultsThe systematic review identified 19 eligible studies, of which 14 used radiomics models and 5 used deep learning models. The pooled AUROC of 7 studies to determine whether patients had lung cancer was 0.83 (95% CI 0.78–0.88). The pooled AUROC of 9 studies to determine whether patients had NSCLC was 0.78 (95% CI 0.73–0.83). The pooled AUROC of the 6 studies that determined patients had malignant lung nodules was 0.79 (95% CI 0.77–0.82). The pooled AUROC of the other 6 studies that determined whether patients had lymph node metastases was 0.74 (95% CI 0.66–0.82).ConclusionThe models based on deep learning or radiomics have the potential to improve diagnostic accuracy for lung cancer staging.Systematic Review Registrationhttps://inplasy.com/inplasy-2022-3-0167/, identifier: INPLASY202230167

TCP1 regulates PI3K/AKT/mTOR signaling pathway to promote proliferation of ovarian cancer cells

Abstract Objective TCP1 is one of the eight subunits of the TCP1 ring complex (TRiC) or the multi-protein mammalian cytosolic chaperone complex. TRiC participates in protein folding and regulates the expression of multiple signaling proteins and cytoskeletal components in cells. Although the clinical importance of its subunits has been clarified in various carcinomas, the function of TCP1 in ovarian cancer (OC) remains unclear. We aimed to identify the association between the expression of TCP1 and the development of epithelial OC (EOC) and patient prognosis, and explore the underlying mechanisms of TCP1 on the tumor progression of OC cells. Methods TCP1 protein expression was tested in various ovarian tissues by immunohistochemistry, and the correlation between TCP1 expression and clinical physiologic or pathologic parameters of patients with EOC was analyzed. The relationship between TCP1 expression and the prognosis of patients with OC was investigated and analyzed using the Kaplan–Meier (KM) plotter online database. The expression level of TCP1 was then tested in different OC cell lines by Western blotting. Further, a model using OC cell line A2780 was constructed to study the functions of TCP1 in growth, migration, and invasion of human EOC cells. Finally, the possible regulating signaling pathways were discussed. Results TCP1 protein expression in OC or borderline tissues was significantly higher than that in benign ovarian tumors and normal ovarian tissue. The upregulated expression of TCP1 in OC was positively associated with the differentiation grade and FIGO stage of tumors and predicted poor clinical outcomes. Compared with IOSE-80 cells, TCP1 protein was overexpressed in A2780 cells. TCP1 knockdown using shRNA lentivirus inhibited the viability of A2780 cells. Western blotting showed that the phosphatidylinositol-3 kinase (PI3K) signaling pathway was activated in the tumor invasion in EOC driven by TCP1. Conclusion Upregulated TCP1 is correlated with the poor prognosis of patients with OC. The mechanism of cancer progression promoted by TCP1 upregulation may be linked to the activation of the PI3K signaling pathway, and TCP1 may serve as a novel target for the treatment of OC

Detuned Plasmonic Bragg Grating Sensor Based on a Defect Metal-Insulator-Metal Waveguide

A nanoscale Bragg grating reflector based on the defect metal-insulator-metal (MIM) waveguide is developed and numerically simulated by using the finite element method (FEM). The MIM-based structure promises a highly tunable broad stop-band in transmission spectra. The narrow transmission window is shown to appear in the previous stop-band by changing the certain geometrical parameters. The central wavelengths can be controlled easily by altering the geographical parameters. The development of surface plasmon polarition (SPP) technology in metallic waveguide structures leads to more possibilities of controlling light at deep sub-wavelengths. Its attractive ability of breaking the diffraction limit contributes to the design of optical sensors