Management of coronary artery disease in patients with aortic stenosis in the era of transcatheter aortic valve replacement

Aortic stenosis (AS) is a common valve disorder among the elderly, and these patients frequently have concomitant coronary artery disease (CAD). Risk factors for calcific AS are similar to those for CAD. Historically, the treatment of these conditions involved simultaneous surgical replacement of the aortic valve (AV) with coronary artery bypass grafting. Since the advancement of transcatheter AV therapies, there have been tremendous advancements in the safety, efficacy, and feasibility of this procedure with expanding indications. This has led to a paradigm shift in our approach to the patient with AS and concomitant CAD. Data regarding the management of CAD in patients with AS are largely limited to single-center studies or retrospective analyses. This article aims to review available literature around the management of CAD in patients with AS and assist in the current understanding in approaches toward management

PLAS-5k: Dataset of Protein-Ligand Affinities from Molecular Dynamics for Machine Learning Applications

Computational methods and recently modern machine learning methods have played a key role in structure-based drug design. Though several benchmarking datasets are available for machine learning applications in virtual screening, accurate prediction of binding affinity for a protein-ligand complex remains a major challenge. New datasets that allow for the development of models for predicting binding affinities better than the state-of-the-art scoring functions are important. For the first time, we have developed a dataset, PLAS-5k comprised of 5000 protein-ligand complexes chosen from PDB database. The dataset consists of binding affinities along with energy components like electrostatic, van der Waals, polar and non-polar solvation energy calculated from molecular dynamics simulations using MMPBSA (Molecular Mechanics Poisson-Boltzmann Surface Area) method. The calculated binding affinities outperformed docking scores and showed a good correlation with the available experimental values. The availability of energy components may enable optimization of desired components during machine learning-based drug design. Further, OnionNet model has been retrained on PLAS-5k dataset and is provided as a baseline for the prediction of binding affinities

Diverse repertoire of human adipocyte subtypes develops from transcriptionally distinct mesenchymal progenitor cells

Single-cell sequencing technologies have revealed an unexpectedly broad repertoire of cells required to mediate complex functions in multicellular organisms. Despite the multiple roles of adipose tissue in maintaining systemic metabolic homeostasis, adipocytes are thought to be largely homogenous with only 2 major subtypes recognized in humans so far. Here we report the existence and characteristics of 4 distinct human adipocyte subtypes, and of their respective mesenchymal progenitors. The phenotypes of these distinct adipocyte subtypes are differentially associated with key adipose tissue functions, including thermogenesis, lipid storage, and adipokine secretion. The transcriptomic signature of brite/beige thermogenic adipocytes reveals mechanisms for iron accumulation and protection from oxidative stress, necessary for mitochondrial biogenesis and respiration upon activation. Importantly, this signature is enriched in human supraclavicular adipose tissue, confirming that these cells comprise thermogenic depots in vivo, and explain previous findings of a rate-limiting role of iron in adipose tissue browning. The mesenchymal progenitors that give rise to beige/brite adipocytes express a unique set of cytokines and transcriptional regulators involved in immune cell modulation of adipose tissue browning. Unexpectedly, we also find adipocyte subtypes specialized for high-level expression of the adipokines adiponectin or leptin, associated with distinct transcription factors previously implicated in adipocyte differentiation. The finding of a broad adipocyte repertoire derived from a distinct set of mesenchymal progenitors, and of the transcriptional regulators that can control their development, provides a framework for understanding human adipose tissue function and role in metabolic disease