Reproducibility of ultrasound-derived fat fraction in measuring hepatic steatosis.

Purpose: Steatotic liver disease (SLD) has become the most common cause of chronic liver disease. Nevertheless, the non-invasive quantitative diagnosis of steatosis is still lacking in clinical practice. This study aimed to evaluate the reproducibility of the new parameter for steatosis quantification named ultrasound-derived fat fraction (UDFF).

Comparing Three Ultrasound-Based Techniques for Diagnosing and Grading Hepatic Steatosis in Metabolic Dysfunction-Associated Steatotic Liver Disease.

Rationale And Objectives: To compare the diagnostic accuracy and grading ability of ultrasound-derived fat fraction (UDFF), controlled attenuation parameters (CAP), and hepatic/renal ratio (HRR) for hepatic steatosis in metabolic dysfunction-associated steatotic liver disease (MASLD) using magnetic resonance imaging proton density fat fraction (PDFF) as the gold standard.

Methods: Patients suspected of having MASLD in our hospital between October 2023 and May 2024 were divided into the MASLD group and the control group. All patients underwent UDFF, CAP, and PDFF examinations.

Performance of ATT and UDFF in the diagnosis of non-alcoholic fatty liver: An animal experiment.

Objective: To establish a Bama minipigs model with Non-Alcoholic Fatty Liver (NAFL) induced by a high-fat diet and investigate the application of attenuation coefficient (ATT) and ultrasound-derived fat fraction (UDFF) in the diagnosis of NAFL.

Methods: Six-month-old male Bama minipigs were randomly divided into normal control and high-fat groups (n = 3 pigs per group), and fed with a control diet and high-fat diet for 32 weeks. Weight and body length were measured every four weeks, followed by quantitative ultrasound imaging (ATT and UDFF), blood biochemical markers, and liver biopsies on the same day.

Simultaneously mapping loci related to two plant architecture traits by phenotypic recombination BSA/BSR in peanut (Arachis hypogaea L.).

We developed a new method phenotypic recombination BSA/BSR (PR-BSA/BSR), which could simultaneously identify the candidate genomic regions associated with two traits in a segregating population. Bulked segregant analysis sequencing (BSA-seq) has been widely used for identifying the genomic regions affecting a certain trait. In this study, we developed a modified BSA/bulked segregant RNA-sequencing (BSR-seq) method, which we named phenotypic recombination BSA/BSR (PR-BSA/BSR), to simultaneously identify candidate genomic regions associated with two traits in a segregating population.

Identification of prognostic biomarkers associated with tumor microenvironment in ceRNA network for esophageal squamous cell carcinoma: a bioinformatics study based on TCGA database.

Background: Esophageal squamous cell carcinoma (ESCC) is the most common histological type of esophageal cancer in the world with high incidence rate and poor prognosis. Infiltrated immune and stromal cells are vital components of tumor microenvironment (TME) and have a significant impact on the progression of ESCC. The competitive endogenous RNA (ceRNA) hypothesis has been proved important in the molecular biological mechanisms of tumor development.

Identification of immunophenotypes in esophageal squamous cell carcinoma based on immune gene sets.

Purpose: Esophageal squamous cell carcinoma (ESCC) is a malignant tumor with high heterogeneity. Research on molecular mechanisms involved in the process of tumor origination and progression is extremely limited to investigating mechanisms of molecular typing for ESCC.

Methods: After comprehensively analyzing the gene expression profiles in The Cancer Genome Atlas and Gene Expression Omnibus databases, we identified four immunotypes of ESCC (referred to as C1-C4) based on the gene sets of 28 immune cell subpopulations.

Identification of biomarkers associated with diagnosis and prognosis of gastroesophageal junction adenocarcinoma-a study based on integrated bioinformatics analysis in GEO and TCGA database.

Gastroesophageal junction adenocarcinoma (GEJAC) is a malignant tumor with high mortality. Its incidence has increased sharply all over the world in recent years. The study aims to search for potential biomarkers for the diagnosis and prognosis of GEJAC based on the Gene Expression Omnibus database (GEO) database and The Cancer Genome Atlas (TCGA) database.