Deep Learning-Assisted Analysis of GO-Reinforcing Effects on the Interfacial Transition Zone of CWRB.

Understanding the enhancing mechanisms of graphene oxide (GO) on the pore structure characteristics in the interfacial transition zone (ITZ) plays a crucial role in cemented waste rock backfill (CWRB) nanoreinforcement. In the present work, an innovative method based on metal intrusion techniques, backscattered electron (BSE) images, and deep learning is proposed to analyze the micro/nanoscale characteristics of microstructures in the GO-enhanced ITZ. The results showed that the addition of GO reduced the interpore connectivity and the porosity at different pore throats by 53.

Diagnosis and Molecular Characterization of Potential RNA Binding Protein Involved in the Pathogenesis of Liver Ischemia Reperfusion Injury.

Background: Liver ischemia-reperfusion is one of the common complications after liver surgery. Uncontrolled liver ischemia-reperfusion will lead to many serious consequences such as surgical failure. It is an urgent clinical problem to search for diagnostic markers and explore its potential pathogenesis.

Analysis of clinical significance and molecular characteristics of methionine metabolism and macrophage-related patterns in hepatocellular carcinoma based on machine learning.

Background: Increasing evidence has indicated that abnormal methionine metabolic activity and tumour-associated macrophage infiltration are correlated with hepatocarcinogenesis. However, the relationship between methionine metabolic activity and tumour-associated macrophage infiltration is unclear in hepatocellular carcinoma, and it contributes to the occurrence and clinical outcome of hepatocellular carcinoma (HCC). Thus, we systematically analysed the expression patterns of methionine metabolism and macrophage infiltration in hepatocellular carcinoma using bioinformatics and machine learning methods and constructed novel diagnostic and prognostic models of HCC.

Construction and validation of a prediction model of extrahepatic metastasis for hepatocellular carcinoma based on common clinically available data.

Objective: This study aimed to investigate the clinical characteristics and risk factors of patients with hepatocellular carcinoma (HCC) with extrahepatic metastases (EHM) and to establish an effective predictive nomogram.

Methods: Clinical and pathological data from 607 patients with hepatocellular carcinoma admitted to the Affiliated Hospital of Qinghai University between 1 January 2015 and 31 May 2018 were documented, as well as demographics, clinical pathological characteristics, and tumor-related parameters to clarify clinical risk factors for HCC EHM. These risks were selected to build an R-based clinical prediction model.

Metabolism-Relevant Molecular Classification Identifies Tumor Immune Microenvironment Characterization and Immunotherapeutic Effect in Cervical Cancer.

Cervical cancer (CESC) is a gynecologic malignant tumor associated with high incidence and mortality rates because of its distinctive management complexity. Herein, we characterized the molecular features of CESC based on the metabolic gene expression profile by establishing a novel classification system and a scoring system termed as METAscore. Integrative analysis was performed on human CESC samples from TCGA dataset.

MT1JP-mediated miR-24-3p/BCL2L2 axis promotes Lenvatinib resistance in hepatocellular carcinoma cells by inhibiting apoptosis.

Purpose: Lenvatinib is a long-awaited alternative to Sorafenib for first-line targeted therapy of patients with advanced hepatocellular carcinoma (HCC). However, resistance to Lenvatinib results in tumor progression and has become a major obstacle to improving the prognosis of HCC patients. Exploring the mechanisms underlying Lenvatinib resistance is considered essential for the treatment of advanced HCC.

Characterization of murine mammary stem/progenitor cells in a D-galactose-induced aging model.

Aging plays an important role in many diseases, including breast cancer. Aged mammary stem/progenitor cells are perceived to be the cells of origin in breast tumorigenesis; however, the extensive use of mice who have aged naturally for research is hampered by cost, time, disease complications, and high mortality. In this study, we characterized murine mammary stem/progenitor cells in a D-galactose-induced accelerated aging model and compared them with findings from our earlier study on mice from natural aging.

Developmental co-exposure of TBBPA and titanium dioxide nanoparticle induced behavioral deficits in larval zebrafish.

Both tetrabromobisphenol A (TBBPA) and titanium dioxide nanoparticle (TiO NP) have widespread commercial applications, resulting in their ubiquitous co-presence in the environment and biota. Although environmental chemicals exist as mixtures, toxicity studies are nearly always conducted with single chemicals. Few studies explore potential interactions of different chemical mixtures.

Identification of Biomarkers Related to Atrial Fibrillation With Mitral Regurgitation.

Background: We aimed to explore the biomarkers associated with atrial fibrillation (AF) with mitral regurgitation (MR).

Methods: The gene expression profile data GSE115574 were downloaded from Gene Expression Omnibus database, which were obtained from patients with degenerative MR with AF and sinus rhythm (SR). The differentially expressed genes (DEGs) in samples of AF with MR compared with those of SR with MR were selected, followed by functional enrichment analysis, protein-protein interaction (PPI) network analysis, transcription factor (TF) prediction, and drug-gene interaction prediction.