A Machine Learning Model to Predict Risk for Hepatocellular Carcinoma in Patients With Metabolic Dysfunction-Associated Steatotic Liver Disease.

Background And Aims: Hepatocellular carcinoma (HCC) incidence is increasing and correlated with metabolic dysfunction-associated steatotic liver disease (MASLD; formerly nonalcoholic fatty liver disease), even in patients without advanced liver fibrosis who are more likely to be diagnosed with advanced disease stages and shorter survival time, and less likely to receive a liver transplant. Machine learning (ML) tools can characterize large datasets and help develop predictive models that can calculate individual HCC risk and guide selective screening and risk mitigation strategies.

Methods: Tableau and KNIME Analytics were used for descriptive analytics and ML tasks.

Accessing and utilizing clinical and genomic data from an electronic health record data warehouse.

Electronic health records (EHRs) and linked biobanks have tremendous potential to advance biomedical research and ultimately improve the health of future generations. Repurposing EHR data for research is not without challenges, however. In this paper, we describe the processes and considerations necessary to successfully access and utilize a data warehouse for research.

Intra- and Intertumoral Microglia/Macrophage Infiltration and Their Associated Molecular Signature Is Highly Variable in Canine Oligodendroglioma: A Preliminary Evaluation.

The goal of this study was to define the glioma-associated microglia/macrophage (GAM) response and associated molecular landscape in canine oligodendrogliomas. Here, we quantified the intratumoral GAM density of low- and high-grade oligodendrogliomas compared to that of a normal brain, as well as the intratumoral concentration of several known GAM-derived pro-tumorigenic molecules in high-grade oligodendrogliomas compared to that in a normal brain. Our analysis demonstrated marked intra- and intertumoral heterogeneity of GAM infiltration.

Lipoprotein(a) and diet-a challenge for a role of saturated fat in cardiovascular disease risk reduction?

In this perspective, we discuss new evidence relating to current dietary recommendations to reduce SFA intake to modulate an individual's global risk of CVD. Although it is well established that lowering dietary SFA intake has a beneficial effect on LDL cholesterol concentrations, findings increasingly indicate an opposite effect on lipoprotein(a) [Lp(a)] concentrations. In recent years, many studies have firmly established a role for an elevated Lp(a) concentration as a genetically regulated, causal, and prevalent risk factor for CVD.

Microglia-Derived Olfactomedin-like 3 Is a Potent Angiogenic Factor in Primary Mouse Brain Endothelial Cells: A Novel Target for Glioblastoma.

Neoangiogenesis, a hallmark feature of all malignancies, is robust in glioblastoma (GBM). Vascular endothelial growth factor (VEGF) has long been regarded as the primary pro-angiogenic molecule in GBM. However, anti-VEGF therapies have had little clinical efficacy, highlighting the need to explore VEGF-independent mechanisms of neoangiogenesis.