Bayesian Inference-Based Gaussian Mixture Models With Optimal Components Estimation Towards Large-Scale Synthetic Data Generation for Clinical Trials.

: To develop a computationally efficient and unbiased synthetic data generator for large-scale clinical trials (CTs). We propose the BGMM-OCE, an extension of the conventional BGMM (Bayesian Gaussian Mixture Models) algorithm to provide unbiased estimations regarding the optimal number of Gaussian components and yield high-quality, large-scale synthetic data at reduced computational complexity. Spectral clustering with efficient eigenvalue decomposition is applied to estimate the hyperparameters of the generator.

INT-767 prevents NASH and promotes visceral fat brown adipogenesis and mitochondrial function.

The bile acid receptors, farnesoid X receptor (FXR) and Takeda G-protein-coupled receptor 5 (TGR5), regulate multiple pathways, including glucose and lipid metabolism. In a rabbit model of high-fat diet (HFD)-induced metabolic syndrome, long-term treatment with the dual FXR/TGR5 agonist INT-767 reduces visceral adipose tissue accumulation, hypercholesterolemia and nonalcoholic steatohepatitis. INT-767 significantly improves the hallmarks of insulin resistance in visceral adipose tissue (VAT) and induces mitochondrial and brown fat-specific markers.

The microenvironment induces collective migration in -silenced mouse pheochromocytoma spheroids.

Pheochromocytomas (Pheos) and paragangliomas (PGLs) are neuroendocrine tumors. Approximately 30-40% of Pheos/PGLs are due to germline mutations in one of the susceptibility genes, including those encoding the succinate dehydrogenase subunits A-D (). Up to 2/3 of patients affected by mutated Pheo/PGL develop metastatic disease with no successful cure at present.