Sepsis is a common disease with very costly, potentially deadly implications. Early prediction of Sepsis and initiation of antibiotic is widely considered as an important determinant of patient survival. Cross-institutional validation and implementation of algorithms for early prediction of Sepsis at a minimum require common data formats, streaming analytic platforms for timely risk assessment, and interoperable and standardized interfaces. In this work we present an open-source cloud-based analytic pipeline, which receives de-identified patient data from an interoperable server and produces real-time Sepsis risk scores for Intensive Care Unit (ICU) patients.
Study Question: Can a panel of plasma protein biomarkers be identified to accurately and specifically diagnose endometriosis?
Summary Answer: A novel panel of 10 plasma protein biomarkers was identified and validated, demonstrating strong predictive accuracy for the diagnosis of endometriosis.
What Is Known Already: Endometriosis poses intricate medical challenges for affected individuals and their physicians, yet diagnosis currently takes an average of 7 years and normally requires invasive laparoscopy. Consequently, the need for a simple, accurate non-invasive diagnostic tool is paramount.
The microtubule motor cytoplasmic dynein-1 transports and positions various organelles, but the molecular basis of this functional diversity is not fully understood. Cargo adaptors of the Hook protein family recruit dynein to early endosomes (EE) in fungi and human cells by forming the FTS-Hook-FHIP (FHF) complex. By contrast, the Hook homolog ZYG-12 recruits dynein to the nuclear envelope (NE) in the meiotic gonad and mitotic early embryo by forming a Linker of Nucleoskeleton and Cytoskeleton (LINC) complex.
Objectives: In patients with interstitial lung disease (ILD), the diaphragm typically rises as the lungs chronically shrink. However, the grade of restriction differs in each patient. It is currently unknown, how disparities between actual and predicted recipient total lung capacity (TLC), impact changes in lung function parameters and long-term outcomes following lung transplantation (LTx).
Hunan Key Laboratory of Cancer Metabolism, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, 410013, China.
Purpose: Our study aims to develop and validate a novel molecular marker for the prognosis and diagnosis of hepatocellular carcinoma (HCC) MATERIALS & METHODS: We retrospectively analyzed mRNA expression profile and clinicopathological data of HCC patients fetched from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and The International Cancer Genome Consortium (ICGC) datasets. Univariate Cox regression analysis was performed to collect differentially expressed mRNA (DEmRNAs) from HCC and non-tumor tissues, and YEATS2, a prognostic marker, was identified by further analysis. ROC curve, survival analysis and multivariate Cox regression analysis as well as nomograms were used to evaluate the prognosis of this gene.
Department of Neurology, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, China.
Background: Malnutrition, post-stroke depression (PSD), post-stroke anxiety (PSA), and post-stroke fatigue (PSF) in stroke survivors have complex relationships and are associated with adverse stroke outcomes.
Aims: This research aims to explore the temporal and directional relationships between malnutrition, PSD, PSA, and PSF after stroke in older adults.
Methods: Patients aged 65 years and older with their first ischemic stroke from two centers were selected and assessed at baseline, 3 months and 12 months.
