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Background In China, the prevalence of HUA in the Pearl River Delta (PRD) region of Guangdong Province has not been extensively investigated. Therefore, this study investigated the prevalence of HUA and its related factors among people aged 20–99 years in nine cities in the PRD. Materials and Methods We selected 6491 health check participants from 9 cities in the PRD and collected participants’ anthropometric and biochemical test results for a cross-sectional study. We included 6491 participants and assessed their blood pressure (BP), body mass index (BMI), total cholesterol (TC), triglycerides (TG), glucose (Glu) and serum uric acid (UA) to analyze the regional prevalence of HUA and its related factors. HUA was indicated when fasting serum UA level was >420 μmol/L in men and >360 μmol/L in women. Results Overall prevalence of HUA in our cohort was 34.05%; prevalence was higher in men than in women (41.53% vs 26.14%, P < 0.001). Characteristics associated with HUA were hypertension (odds ratio (OR), 5.506; 95% confidence interval (CI), 4.402–6.889), higher body mass index (BMI; OR: 1.746; 95% CI: 1.560–1.954), age 31–40 years (OR: 0.829; 95% CI: 0.706–0.973), age 61–70 years (OR: 1.434; 95% CI: 1.194–1.722) and age ≥71 years (OR: 1.742; 95% CI: 1.397–2.173). In all subjects, serum UA was positively correlated with Glu, TG and TC. After we adjusted for age, BMI and BP, multivariate logistic regression analysis showed that HUA risk factors were high TC (OR: 1.770; 95% CI: 1.459–2.147) and TG (OR: 1.961; 95% CI: 1.632–2.357) in men; and high Glu (OR: 1.508; 95% CI: 1.084–2.099), TC (OR: 1.341; 95% CI: 1.084–1.660) and TG (OR: 1.680; 95% CI: 1.290–2.187) in women. Conclusion The prevalence of HUA was relatively high in the PRD of Guangdong Province. Relevant governmental bodies should focus on early diagnosis, early treatment and early intervention.

Objective: To investigate the incidence of malignant transformation and P53 and P16 expression in teratomatous skin of ovarian mature cystic teratoma. Materials and Methods: Data on ovarian teratoma specimens in nearly 10 years were reviewed. P53 and P16 expression were detected by immunohistochemistry in 25 cases of teratomatous skin of ovarian mature cystic teratoma, 20 cases of squamous cell carcinoma and 2 cases of squamous cell carcinoma originated from teratomatous skin. Results: Of 1913 cases of ovarian mature cystic teratoma in nearly 10 years, only two cases of squamous cell carcinoma were found in teratomatous skin, with malignant transformation rate of 0.1045%. P53 expression was detected in 2 cases squamous cell carcinoma originated from teratomatous skin and P16 overexpression in one. There were no expressions of P53 and P16 in 25 cases of teratomatous skin of ovarian mature cystic teratoma. Of 20 cases of squamous cell carcinoma P53 overexpression (positive rate of 55%) was detected in 11 cases, P16 overexpression (positive rate of 35%) in 7 cases. The positive rates of P53 and P16 expression in squamous cell carcinomas were significantly higher than that in the teratomatous skins (p< 0.001, p= 0.002). Conclusions: There was low risk of malignant transformation in teratomatous skin of ovarian mature cystic teratoma which can be explained by lower P53 and P16 expressionin teratomas than that in squamous cell carcinoma.

Nasopharyngeal carcinoma (NPC) is a common malignancy of the head and neck. The aim of the present study was to conduct an integrated bioinformatics analysis of differentially expressed genes (DEGs) and to explore the molecular mechanisms of NPC. Two profiling datasets, GSE12452 and GSE34573, were downloaded from the Gene Expression Omnibus database and included 44 NPC specimens and 13 normal nasopharyngeal tissues. R software was used to identify the DEGs between NPC and normal nasopharyngeal tissues. Distributions of DEGs in chromosomes were explored based on the annotation file and the CYTOBAND database of DAVID. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied. Additionally, a protein-protein interaction (PPI) network, constructed using the STRING database and visualized by Cytoscape, was used to identify hub genes, key modules and important transcription factors (TFs). A total of 906 DEGs were identified; 434 (47.90%) DEGs were upregulated and 472 (52.10%) were downregulated. The DEGs were demonstrated to be enriched in chromosome 7p15-p14, 2q31, 1q21-q22, 1q21, 4q21 and 1p31-p22. DEGs were mainly enriched for the following GO terms: 'Cilium movement', 'microtubule bundle formation' and 'axoneme assembly'. KEGG pathway enrichment analysis revealed that pathways for 'cell cycle', 'DNA replication', 'interleukin-17 signaling', 'amoebiasis' and 'glutathione metabolism' were enriched. In addition, a PPI network comprising 867 nodes and 1,241 edges was constructed. Finally, five hub genes (aurora kinase A, cell division cycle 6, mitotic arrest deficient 2-like 1, DNA topoisomerase 2α and TPX2 microtubule nucleation factor), 8 modules, and 14 TFs were identified. Modules analysis revealed that cyclin-dependent kinase 1 and exportin 1 were involved in the pathway of Epstein-Barr virus infection. In summary, the hub genes, key modules and TFs identified in this study may promote our understanding of the pathogenesis of NPC and require further in-depth investigation.

Background:: Prediction biomarkers associated with prognosis and lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) are needed to facilitate clinicians in choosing appropriate therapies. Objective:: We hope to identify key genes associated with LNM and prognosis in PTC. Methods:: GSE29265, GSE33630, GSE3467, GSE3678 and GSE58545 gene expression profiles were acquired from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between PTC tissues and normal thyroid tissues were selected with the GEO2R tool, and common DEGs among the five datasets were integrated with Venn software online. A protein-protein interaction (PPI) network of the common DEGs was visualized. We analyzed the PPI network and determined core genes using the Cytoscape software. Furthermore, we employed UALCAN to verify the expression and promoter methylation status of the core genes in thyroid carcinoma (THCA). Additionally, the Kaplan–Meier plotter online tool was used to analyze the relationship between overall survival and core gene expressions in THCA. Results:: TNS3, DUSP6, DUSP4 and PTPRE were identified as core genes. Expression of these 4 genes and the promoter methylation status of DUSP4 and PTPRE were strongly associated with LNM (P<0.05). High expression of 3 genes (DUSP6, DUSP4 and PTPRE) was related with significantly better survival than low expression of the 3 genes in THCA. In contrast, high TNS3 expression was related to significantly worse survival (P<0.05). Conclusion:: TNS3, DUSP6, DUSP4, PTPRE and DUSP4 and PTPRE promoter methylation status might be useful predictive biomarkers of LNM in PTC. Additionally, these genes may be prognostic biomarkers in PTC.