The correlation analysis between the appearance anxiety and personality traits of the medical staff on nasal and facial pressure ulcers during the novel coronavirus disease 2019 outbreak.

Aim: To investigate the psychological status of medical staff with medical device-related nasal and facial pressure ulcers (MDR PUs) during the outbreak of COVID-19, analyse the correlation between their psychological status and personality traits, so as to provide a reference for personalized psychological support. Design: A total of 207 medical staff who were treating the COVID-19 epidemic from Hunan and Hubei provinces were enrolled in this analytic questionnaire-based study. Methods: We used these measures: Eysenck Personality Questionnaire Short Scale (EPQ-RSC), Social Appearance Anxiety Scale (SAAS), Positive and Negative Affect Scale (PANAS) and demographic information forms online. Results: Medical staff wearing protective equipment are particularly susceptible to nasal and facial MDR PUs, which is increasing their social appearance anxiety; neuroticism is significantly related to social appearance anxiety and negative emotion. We should pay more attention to their psychological state, cultivate good personality characteristics and reduce negative emotions, and thereby alleviate their MDR PUs-related appearance anxiety.

Bioinformatic analysis of differentially expressed genes as prognostic markers in pheochromocytoma and paraganglioma tumors.

The pathogenesis of pheochromocytoma and paraganglioma (PCPG) catecholamine-producing tumors is exceedingly complicated. Here, we sought to identify important genes affecting the prognosis and survival rate of patients suffering from PCPG. We analyzed 95 samples obtained from two microarray data series, GSE19422 and GSE60459, from the Gene Expression Omnibus (GEO) repository. First, differentially expressed genes (DEGs) were identified by comparing 87 PCPG tumor samples and eight normal adrenal tissue samples using R language. The GEO2R tool and Venn diagram software were applied to the Database for Annotation, Visualization and Integrated Discovery (DAVID) to analyze Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO). We further employed Cytoscape with the Molecular Complex Detection (MCODE) tool to make protein-protein interactions visible for the Search Tool for Retrieval of Interacting Genes (STRING). These procedures resulted in 30 candidate DEGs, which were subjected to Kaplan-Meier analysis and validated by Gene Expression Profiling Interactive Analysis (GEPIA) to determine their influence on overall survival rate. Finally, we identified ALDH3A2 and AKR1B1, two genes in the glycerolipid metabolism pathway, as being particularly enriched in PCPG tumors and correlated with T and B tumor-infiltrating immune cells. Our results suggest that these two DEGs are closely associated with the prognosis of malignant PCPG tumors.