BackgroundSleep disturbance occur among nurses at a high incidence.AimTo develop a Nomogram and a Artificial Neural Network (ANN) model to predict sleep disturbance in clinical nurses.MethodsA total of 434 clinical nurses participated in the questionnaire, a cross-sectional study conducted from August 2021 to June 2022.They were randomly distributed in a 7:3 ratio between training and validation cohorts.Nomogram and ANN model were developed using predictors of sleep disturbance identified by univariate and multivariate analyses in the training cohort; The 1000 bootstrap resampling and receiver operating characteristic curve (ROC) were used to evaluate the predictive accuracy in the training and validation cohorts.ResultsSleep disturbance was found in 180 of 304 nurses(59.2%) in the training cohort and 80 of 130 nurses (61.5%) in the validation cohort.Age, chronic diseases, anxiety, depression, burnout, and fatigue were identified as risk factors for sleep disturbance. The calibration curves of the two models are well-fitted. The sensitivity and specificity (95% CI) of the models were calculated, resulting in sensitivity of 83.9%(77.5–88.8%)and 88.8% (79.2–94.4%) and specificity of83.1% (75.0–89.0%) and 74.0% (59.4–84.9%) for the training and validation cohorts, respectively.ConclusionsThe sleep disturbance risk prediction models constructed in this study have good consistency and prediction efficiency, and can effectively predict the occurrence of sleep disturbance in clinical nurses.

ObjectiveDermatomyositis (DM) positive with anti-melanoma differentiation-associated gene 5 (anti-MDA5-DM) is a systemic autoimmune disease with high mortality. This study aimed to explore the risk factors of death in anti-MDA5-DM and validate a prediction model for all-cause mortality in anti-MDA5-DM.MethodWe conducted a retrospective study using a single-centre cohort of patients with newly onset anti-MDA5-DM from June 1, 2018 to August 31, 2021. Patients were divided into four groups according to baseline ground-glass opacity (GGO) score: Group A, GGO ≤ 1; Group B, 1 < GGO ≤ 2; Group C, 2 < GGO ≤ 3; Group D, GGO > 3. The primary outcome was death during the follow-up. Secondary outcomes included death within 3, 6, 12 months, severe infection, and remission during the first 12 months.ResultsA total of 200 patients were included in the study. Based on multivariable Cox regression, the prognostic factors at baseline were identified as CRP > 5 mg/L, serum ferritin (SF) > 600ng/ml, positive anti-Ro52 antibody, prophylactic use of compound sulfamethoxazole (SMZ Co), four-category GGO score: GGO ≤ 1, 1 < GGO ≤ 2, 2 < GGO ≤ 3, GGO > 3. The final mortality of four groups was 16.4, 22.2, 48.5, 92.0%, respectively. Compared with Group A, the Hazards Ratio (HR) of Group B was 1.408, (p = 0.408), HR of Group C was 3.433 (p = 0.005), HR of Group D was 4.376 (p = 0.001).ConclusionsGGO score is a reliable predictor for risk stratification in anti-MDA5-DM and may provide guidance for individualized managements of patients.

The human genome encodes more than 350 kinds of Krüppel-associated box (KRAB) domain-containing zinc-finger proteins (KZFPs), KRAB-type ZNF transcription factor family (KZNF) plays a vital role in gene regulatory networks. The KZNF family members include a large number of highly homologous genes, gene subtypes and pseudogenes, and their expression has a high degree of tissue specificity and precision. Due to the high complexity of its regulatory network, the KZNF gene family has not been researched in sufficient, and the role of its members in the occurrence of cancer is mostly unexplored. In this study, ZNF880 was significantly associated with overall survival (OS) and disease-free survival (DFS) in colorectal carcinoma (CRC) patients. Low ZNF880 expression resulted in shorter OS and DFS. Combined with Colon adenocarcinoma (COAD) and Rectum adenocarcinoma (READ) data collection in the TCGA database, we found that ZNF880 was significantly down-regulated in CRC. Further analysis of the sequence variation of ZNF880 in CRC showed that ZNF880 accumulated a large number of SNV in the C2H2 domain and KRAB domain, while promoter region of ZNF880 also showed high methylation in COAD and READ. Combined with the Cbioportal and TIMER databases, the expression of mutant ZNF880 was significantly lower in COAD compared to the wild type. Simultaneously, the lncRNA-miRNA-ZNF880 ceRNA regulatory network was constructed through co-expression and miRNAs target gene prediction, demonstrating the precision of the ZNF880 regulatory network. In addition, the decreased expression of ZNF880 caused the significant immune infiltration decreases of CD8 + cells in COAD. In contrast, the immune infiltration of CD4 + cells and macrophages in COAD is positively correlated with ZNF880. Finally, through protein–protein interaction (PPI) network analysis and transcription factor target gene prediction, we screened out the genes most likely to be related to the function of ZNF880. CENPK, IFNGR2, REC8 and ZBTB17 were identified as the most closely functioning genes with ZNF880, which may indicate that ZNF880 has important links with the formation of cell centromere, tumor immunity, cell cycle and other pathways closely related to the occurrence of CRC. These studies show that the down-regulation of ZNF880 gene is closely related to CRC, and the targeted change of the expression of its regulatory molecules (miRNA and lncRNA) may be a new perspective for CRC treatment.