Increasing and maintaining rates of standardized depression screening in youth with childhood-onset systemic lupus erythematosus in a pediatric rheumatology clinic.

Background: Depression adversely affects health outcomes in patients with childhood-onset systemic lupus erythematous (cSLE). By identifying patients with depressive symptoms, we can intervene early with referrals to mental health resources and improve outcomes. The aim of our quality improvement project was to increase and maintain rates of standardized depression screening for youth with cSLE seen within our pediatric rheumatology clinic.

Cardiac fibroblast BAG3 regulates TGFBR2 signaling and fibrosis in dilated cardiomyopathy.

Loss of Bcl2-associated athanogene 3 (BAG3) is associated with dilated cardiomyopathy (DCM). BAG3 regulates sarcomere protein turnover in cardiomyocytes; however, the function of BAG3 in other cardiac cell types is understudied. In this study, we used an isogenic pair of BAG3-knockout and wild-type human induced pluripotent stem cells (hiPSCs) to interrogate the role of BAG3 in hiPSC-derived cardiac fibroblasts (CFs).

Using induced pluripotent stem cells for drug discovery in arrhythmias.

Introduction: Arrhythmias are disturbances in the normal rhythm of the heart and account for significant cardiovascular morbidity and mortality worldwide. Historically, preclinical research has been anchored in animal models, though physiological differences between these models and humans have limited their clinical translation. The discovery of human induced pluripotent stem cells (iPSC) and subsequent differentiation into cardiomyocyte has led to the development of new models of arrhythmias with the hope of a new pathway for both exploration of pathogenic variants and novel therapeutic discovery.

BeatProfiler: Multimodal In Vitro Analysis of Cardiac Function Enables Machine Learning Classification of Diseases and Drugs.

Contractile response and calcium handling are central to understanding cardiac function and physiology, yet existing methods of analysis to quantify these metrics are often time-consuming, prone to mistakes, or require specialized equipment/license. We developed BeatProfiler, a suite of cardiac analysis tools designed to quantify contractile function, calcium handling, and force generation for multiple in vitro cardiac models and apply downstream machine learning methods for deep phenotyping and classification. We first validate BeatProfiler's accuracy, robustness, and speed by benchmarking against existing tools with a fixed dataset.