Biology subjects

Chun, J. Y.

Publications and source records attributed to Chun, J. Y..

3 recordsLinked to original sources

bioRxiv2024

Visualizing Functional Network Connectivity Differences Using an Explainable Machine-learning Method

Functional network connectivity (FNC) estimated from resting-state functional magnetic resonance imaging showed great information about the neural mechanism in different brain disorders. But previous research has mainly focused on standard statistical learning approaches to find FNC features separating patients from control. Although machine learning approaches provide better models separating controls from patients, it is not straightforward for these approaches to provide intuition on the model and the underlying neural process of each disorder. Explainable machine learning offers a solution to this problem by applying machine learning to understand the neural process behind brain disorders. In this study, we introduce a novel framework leveraging SHapley Additive exPlanations (SHAP) to identify crucial Functional Network Connectivity (FNC) features distinguishing between two distinct population classes. Initially, we validate our approach using synthetic data. Subsequently, applying our framework, we ascertain FNC biomarkers distinguishing between, controls and schizophrenia patients with accuracy of 81.04% as well as middle aged adults and old aged adults with accuracy 71.38%, respectively, employing Random Forest (RF), XGBoost, and CATBoost models. Our analysis underscores the pivotal role of the cognitive control network (CCN), subcortical network (SCN), and somatomotor network (SMN) in discerning individuals with schizophrenia from controls. In addition, our platform found CCN and SCN as the most important networks separating young adults from older.

neuroscience↗

bioRxiv2020

Single cell transcriptome analysis defines novel heterogeneity within the pancreatic ductal tree

Lineage tracing using genetically engineered mouse models is an essential tool for investigating cell-fate decisions of progenitor cells and biology of mature cell types, with relevance to physiology and disease progression. To study disease development, an inventory of an organs cell types and understanding of physiologic function is paramount. Here, we performed single-cell RNA sequencing to examine heterogeneity of murine pancreatic duct cells, pancreatobiliary cells, and intrapancreatic bile duct cells. We describe an epithelial-mesenchymal transitory axis in our three pancreatic duct subpopulations and identify SPP1 as a regulator of this fate decision as well as human duct cell de-differentiation. Our results further identify functional heterogeneity within pancreatic duct subpopulations by elucidating a role for Geminin in accumulation of DNA damage in the setting of chronic pancreatitis. Our findings implicate diverse functional roles for subpopulations of pancreatic duct cells in maintenance of duct cell identity and disease progression and establish a comprehensive road map of murine pancreatic duct cell, pancreatobiliary cell, and intrapancreatic bile duct cell homeostasis. SIGNIFICANCEMurine models are extensively used for pancreatic lineage tracing experiments and investigation of pancreatic disease progression. Here, we describe the transcriptome of murine pancreatic duct cells, intrapancreatic bile duct cells, and pancreatobiliary cells at single cell resolution. Our analysis defines novel heterogeneity within the pancreatic ductal tree and supports the paradigm that more than one population of pancreatic duct cells harbors progenitor capacity. We identify and validate unique functional properties of subpopulations of pancreatic duct cells including an epithelial-mesenchymal transcriptomic axis and roles in chronic pancreatic inflammation.

bioinformatics↗

bioRxiv2018

An anti-Gn glycoprotein antibody from a convalescent patient potently inhibits the infection of severe fever with thrombocytopenia syndrome virus

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease localized to China, Japan, and Korea that is characterized by severe hemorrhage and a high fatality rate. Currently, no specific vaccine or treatment has been approved for this disease. To develop a therapeutic agent for SFTS, we isolated antibodies from a phage-displayed antibody library that was constructed from a patient who recovered from SFTS virus (SFTSV) infection. One antibody, designated as Ab10, was reactive to the Gn envelope glycoprotein of SFTSV and protected host cells and A129 mice from infection in both in vitro and in vivo experiments. Notably, Ab10 protected 80% of mice, even when injected 5 days after inoculation with a lethal dose of SFTSV. Using cross-linker assisted mass spectrometry and alanine scanning, we located the non-linear epitope of Ab10 on the Gn glycoprotein domain II and an unstructured stem region, suggesting that Ab10 may inhibit a conformational alteration that is critical for cell membrane fusion between the virus and host cell. Ab10 reacted to recombinant Gn glycoprotein in Gangwon/Korea/2012, HB28, and SD4 strains. Additionally, based on its epitope, we predict that Ab10 binds the Gn glycoprotein in 247 of 272 reported SFTSV isolates previously reported. Together, these data suggest that Ab10 has potential to be developed into a therapeutic agent that could protect against more than 90% of reported SFTSV isolates.\n\nAuthor summarySevere fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease localized to China, Japan, and Korea. This tick-borne virus has infected more than 5,000 humans with a 6.4% to 20.9% fatality rate. Currently, there are no prophylactic or therapeutic measures against this virus. Historically, antibodies from patients who recovered from viral infection have been used to treat new patients. Until now, one recombinant monoclonal antibody was approved for the prophylaxis of respiratory syntial virus infection. We selected 10 antibodies from a patient who recovered from SFTS and found that one antibody potently inhibited SFTS viral infection in both test tube and animal studies. We determined the binding site of this antibody to SFTS virus, which allowed us to predict that this antibody could bind 247 out of 272 SFTS virus isolates reported up to now. We anticipate that this antibody could be developed into a therapeutic measure against SFTS.

biochemistry↗