Objective: Idiopathic intracranial hypertension (IIH) is a condition of unknown etiology associated with venous sinus stenosis. This study aimed to develop a magnetic resonance venography (MRV)-based radiomics model for predicting a high trans-stenotic pressure gradient (TPG) in IIH patients diagnosed with venous sinus stenosis. Materials and Methods: This retrospective study included 105 IIH patients (median age [interquartile range], 35 years [27– 42 years]; female:male, 82:23) who underwent MRV and catheter venography complemented by venous manometry. Contrast enhanced-MRV was conducted under 1.5 Tesla system, and the images were reconstructed using a standard algorithm. Shape features were derived from MRV images via the PyRadiomics package and selected by utilizing the least absolute shrinkage and selection operator (LASSO) method. A radiomics score for predicting high TPG (≥ 8 mmHg) in IIH patients was formulated using multivariable logistic regression; its discrimination performance was assessed using the area under the receiver operating characteristic curve (AUROC). A nomogram was constructed by incorporating the radiomics scores and clinical features. Results: Data from 105 patients were randomly divided into two distinct datasets for model training (n = 73; 50 and 23 with and without high TPG, respectively) and testing (n = 32; 22 and 10 with and without high TPG, respectively). Three informative shape features were identified in the training datasets: least axis length, sphericity, and maximum three-dimensional diameter.The radiomics score for predicting high TPG in IIH patients demonstrated an AUROC of 0.906 (95% confidence interval, 0.836– 0.976) in the training dataset and 0.877 (95% confidence interval, 0.755–0.999) in the test dataset. The nomogram showed good calibration. Conclusion Our study presents the feasibility of a novel model for predicting high TPG in IIH patients using radiomics analysis of noninvasive MRV-based shape features. This information may aid clinicians in identifying patients who may benefit from stenting.

Objective To screen the epithelial mesenchymal transformation(EMT)-related genes in lung adenocarcinoma,perform functional enrichment analysis and construct protein interaction network(PPI).Ac-cording to the competitive endogenous RNA(ceRNA)hypothesis and the effect of gene expression on the prognosis of patients,the ceRNA network was constructed.Methods The differentially expressed genes be-tween lung adenocarcinoma tissues and normal tissues were screened by gene expression map and tumor ge-nome map database,and the genes were imported into GenClip3 to obtain EMT-related genes.Metascape was used to perform gene ontology and Kyoto encyclopedia of gene and genome enrichment analysis,and STRING database was used to construct PPI and obtain EMT key genes.The relationship between key genes and prog-nosis was analyzed by Kaplan-Meier analysis.Analysis tools such as miRTarbase,miRNet database,and EN-CORI were used to construct ceRNA networks.Results In this study,156 lung adenocarcinoma EMT-related genes and their key genes cadherin 1,interleukin-6,matrix metalloproteinase-9,platelet endothelial cell adhe-sion molecule,cyclin-dependent kinase inhibitor 2A,α1-Ⅰcollagen gene,secreted phosphoprotein 1,TIMP in-hibitor of matrix metalloproteinase-1,caveolin-1 and Zeste homologue enhance core 2(EZH2)-1 were identi-fied.The PPI of key genes was predicted,and the therapeutic drugs targeting these key genes including salvia miltiorrhiza,ginseng lu,ginseng leaf and ginseng flower were also predicted.The prognostic ceRNA regulatory network of EZH2/hsa-miR-101-3p/GSEC was constructed.Conclusion This study describes using bioinfor-matics methods system in the process of EMT gene interactions,according to the lung adenocarcinoma pa-tients clinical data to construct the prognosis of the EMT process related ceRNA network,for the treatment and prognosis of lung adenocarcinoma judgment provides a new way of thinking.

Closed-loop hospital management can effectivly cope with the COVID-19 pandemic. In order to ensure the continuity of treatments for hemodialysis patients under closed-loop management and minimize possible medical and infection risks, Huashan Hospital affiliated to Fudan University and 9 hospitals in Shanghai established a hemodialysis alliance in January 2021.The alliance optimized hemodialysis resources within the region through overall planning by preparing sites, materials and personnel shifts in advance, and establishing management systems and work processes to ensure that patients could be quickly and orderly diverted to other blood dialysis centers for uninterrupted high-quality hemodialysis services, in case that some hemodialysis centers in the alliance under closed-loop management.From November 2021 to April 2022, 317 of 1 459 hemodialysis patients in the alliance were diverted to other centers for treatment, accumulating 1 215 times/cases of treatments without obvious adverse reactions. The practice could provide a reference for medical institutions to quickly establish mutual support mode under major public health events.