A novel minimally invasive surgical technique (LONG procedure) for treating chylopericardium.

Background: Chylopericardium is a rare disease resulting from lymphatic system dysfunction and characterized by recurrent chylous pericardial effusion and cardiac compression. Traditional treatments like fasting, somatostatin injection and ligation of pericardial lymphatic vessels are less effective, with high recurrence rate. Fenestration is regarded as the last resort for treating chylopericardium.

Proteome-wide mendelian randomization identifies causal plasma proteins in interstitial lung disease.

Interstitial lung disease (ILD) has shown limited treatment advancements, with minimal exploration of circulating protein biomarkers causally linked to ILD and its subtypes beyond idiopathic pulmonary fibrosis (IPF). In this study, we aimed to identify potential drug targets and circulating protein biomarkers for ILD and its subtypes. We utilized the most recent large-scale plasma protein quantitative trait loci (pQTL) data detected from the antibody-based method and ILD and its subtypes' GWAS data from the updated FinnGen database for Mendelian randomization analysis.

Risk factors for the mortality of hemodialysis patients with COVID-19 in northern Hunan province, China.

Purpose: Exploring the risk factors for mortality of hemodialysis patients undergoing COVID-19 and the changes in mortality before and after the opening of the epidemic in northern Hunan province, China.

Methods: We analyzed 230 hemodialysis patients with COVID-19 in the Yiyang Central Hospital from November 01, 2022 to February 28, 2023. Demographic data, laboratory data and public diseases were collected.

Quantum and complex-valued hybrid networks for multi-principal element alloys phase prediction.

This study introduces a hybrid network model for phase classification, integrating quantum networks and complex-valued neural networks. This architecture uses elemental composition as its only input, eliminating complex feature engineering. Parameterized quantum networks handle sparse elemental data and convert data from real to complex domains, increasing information dimensionality.

CT Multidimensional Radiomics Combined with Inflammatory Immune Score For Preoperative Prediction of Pathological Grade in Esophageal Squamous Cell Carcinoma.

Rationale And Objectives: Inflammation and immune biomarkers can promote angiogenesis and proliferation and metastasis of esophageal squamous cell carcinoma (ESCC). The degree of pathological grade reflects the tumor heterogeneity of ESCC. The purpose is to develop and validate a nomogram based on enhanced CT multidimensional radiomics combined with inflammatory immune score (IIS) for predicting poorly differentiated ESCC.