Machine learning approaches to identifying social determinants of health in electronic health record clinical notes

Social determinants of health (SDH) represent the complex set of circumstances in which individuals are born, or with which they live, that impact health. Relatively little attention has been given to processes needed to extract SDH data from electronic health records. Despite their importance, SDH data in the EHR remains sparse, typically collected only in clinical notes and thus largely unavailable for clinical decision making. I focus on developing and validating more efficient information extraction approaches to identifying and classifying SDH in clinical notes. In this dissertation, I have three goals: First, I develop a word embedding model to expand SDH terminology in the context of identifying SDH clinical text. Second, I examine the effectiveness of different machine learning algorithms and a neural network model to classify the SDH characteristics financial resource strain and poor social support. Third, I compare the highest performing approaches to simpler text mining techniques and evaluate the models based on performance, cost, and generalizability in the task of classifying SDH in two distinct data sources.Doctor of Philosoph

Immediate-early gene expression in human saphenous veins harvested during coronary artery bypass graft operations

Saphenous vein graft occlusion is a common late complication of coronary bypass grafting. Intimal smooth muscle cell hyperplasia is a component of this pathobiology, but the underlying molecular events are poorly understood. Immediate-early genes are activated shortly after growth stimulation and subserve cellular functions, which may contribute to intimal smooth muscle cell accumulation. In the present study, human saphenous vein grafts were harvested with minimal manipulation during coronary bypass and processed for isolation of total ribonucleic acid to examine changes in immediate-early gene expression of messenger ribonucleic acid by Northern blotting techniques. Thirty saphenous vein grafts were incubated at 4° C in Dulbecco's modified Eagle media from 30 minutes to 10 hours. The messenger ribonucleic acids for immediate-early genes c-fos and c-myc were weak or undetectable in controls but were increased (>10 times controls) within 1 hour (c-fos) and persisted for at least 6 hours (c-myc) after harvest. Our results demonstrate, for the first time in human vascular tissue, incipient immediate-early gene induction. This information may lead to molecular therapies to control saphenous vein graft disease

Neuropilin-1 Modulates p53/Caspases Axis to Promote Endothelial Cell Survival

Vascular permeability factor/vascular endothelial growth factor (VPF/VEGF), one of the crucial pro-angiogenic factors, functions as a potent inhibitor of endothelial cell (EC) apoptosis. Previous progress has been made towards delineating the VPF/VEGF survival signaling downstream of the activation of VEGFR-2. Here, we seek to define the function of NRP-1 in VPF/VEGF-induced survival signaling in EC and to elucidate the concomitant molecular signaling events that are pivotal for our understanding of the signaling of VPF/VEGF. Utilizing two different in vitro cell culture systems and an in vivo zebrafish model, we demonstrate that NRP-1 mediates VPF/VEGF-induced EC survival independent of VEGFR-2. Furthermore, we show here a novel mechanism for NRP-1-specific control of the anti-apoptotic pathway in EC through involvement of the NRP-1-interacting protein (NIP/GIPC) in the activation of PI-3K/Akt and subsequent inactivation of p53 pathways and FoxOs, as well as activation of p21. This study, by elucidating the mechanisms that govern VPF/VEGF-induced EC survival signaling via NRP-1, contributes to a better understanding of molecular mechanisms of cardiovascular development and disease and widens the possibilities for better therapeutic targets