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정현태(Hyuntae Jeong),조영빈(Youngbin Cho),신현정(Jennifer H. Shin) 한국가시화정보학회 2018 한국가시화정보학회지 Vol.16 No.2
Cellular jamming phenomenon, defined as a kinetic arrest, is a commonly observed event in dense cell aggregates in epithelial tissues. Cells lose their motility when the density of the cell population becomes too high. Yet, not much is known about how the jamming occurs and how it influences individual cells in the population. In this study, we investigated the mechanisms during the formation of the jammed state by visualizing various dynamic components such as velocity, traction, and intercellular stress. The visualized properties exhibited interrelated features in similar time domains that can be categorized into specific stages, namely migrating, transitional and steady state. During the migrating stage, cells generated spatially correlated tractions and migrations at the collective migration step and lost these properties becoming a transitional stage. These stepwise analyses presented correlative components which are expected to adjust for explaining the detailed mechanisms of cellular jamming.
세포 운동 가시화를 통한 상처 치유 과정 내 경계 이동의 규명
정현태(Hyuntae Jeong),이재성(Jaesung Lee),신현정(Jennifer Hyunjon) 한국가시화정보학회 2020 한국가시화정보학회지 Vol.18 No.2
The curvature of wound boundaries has been identified as a key modulator that determines a type of force responsible for cell migration. While several studies report how certain curvatures of the boundary correlate with the rate at which the wound closes, it remains unclear how these curvatures are spatiotemporally formed to regulate the healing process. We investigated the dynamic changes in the boundary curvatures by visualizing cell migration patterns. Locally, cells at the convex boundary continuously move forward with transmitting kinetic responses behind to the cells away from the boundary, and cells at the concave boundary exhibit dramatic contracting motion, like a purse-string, when they accumulate enough negative curvatures to gain the thrust toward the void. Globally, the dynamics of boundary geometries are controlled by the diffusive flow of cells driven by the density gradient between the wound area and the cell layer.
암의 이질성 분류를 위한 하이브리드 학습 기반 세포 형태 프로파일링 기법
민찬홍,정현태,양세정,신현정,Min, Chanhong,Jeong, Hyuntae,Yang, Sejung,Shin, Jennifer Hyunjong 대한의용생체공학회 2021 의공학회지 Vol.42 No.5
Heterogeneity in cancer is the major obstacle for precision medicine and has become a critical issue in the field of a cancer diagnosis. Many attempts were made to disentangle the complexity by molecular classification. However, multi-dimensional information from dynamic responses of cancer poses fundamental limitations on biomolecular marker-based conventional approaches. Cell morphology, which reflects the physiological state of the cell, can be used to track the temporal behavior of cancer cells conveniently. Here, we first present a hybrid learning-based platform that extracts cell morphology in a time-dependent manner using a deep convolutional neural network to incorporate multivariate data. Feature selection from more than 200 morphological features is conducted, which filters out less significant variables to enhance interpretation. Our platform then performs unsupervised clustering to unveil dynamic behavior patterns hidden from a high-dimensional dataset. As a result, we visualize morphology state-space by two-dimensional embedding as well as representative morphology clusters and trajectories. This cell morphology profiling strategy by hybrid learning enables simplification of the heterogeneous population of cancer.