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Biosens. Bioelectron., Nov 15 2023, 246 S0956-5663(23)00780-7 | https://doi.org/10.1016/j.bios.2023.115838 Non-intrusive quality appraisal of differentiation-induced cardiovascular stem cells using E-Nose sensor technology

Thanh Mien Nguyen ^a,1, Woong Bi Jang ^b,c,1, Yujin Lee ^d,1, You Hwan Kim ^d, Hye Ji Lim ^b,c, Eun Ji Lee ^b,c, Thu M.T. Nguyen ^d, Eun-Jung Choi ^a, Sang-Mo Kwon ^b,c, Jin-Woo Oh^a,d

^aBio-IT Fusion Technology Research Institute, Pusan National University, Busan, 46241, Republic of Korea

^bLaboratory for Vascular Medicine and Stem Cell Biology, Department of Physiology, Medical Research Institute, School of Medicine, Pusan National University, Yangsan, 50612, Republic of Korea

^cConvergence Stem Cell Research Center, Pusan National University, Yangsan, 50612, Republic of Korea

^dDepartment of Nano Fusion Technology, Pusan National University, Busan, 46214, Republic of Korea

¹These authors contributed equally to this work.

Corresponding authors: Eun-Jung Choi, Sang-Mo Kwon, Jin-Woo Oh

Abstract

Stem cell technology holds immense potential for revolutionizing medicine, particularly in regenerative treatment for heart disease. The unique capacity of stem cells to differentiate into diverse cell types offers promise in repairing damaged tissues and implanting organs. Ensuring the quality of differentiated cells, essential for specific functions, demands in-depth analysis. However, this process consumes time and incurs substantial costs while invasive methods may alter stem cell features during differentiation and deplete cell numbers. To address these challenges, we propose a non-invasive strategy, using cellular respiration, to assess the quality of differentiation-induced stem cells, notably cardiovascular stem cells. This evaluation employs an electronic nose (E-Nose) and neural pattern separation (NPS). Our goal is to assess differentiation-induced cardiac stem cells (DICs) quality through E-Nose data analysis and compare it with standard commercial human cells (SCHCs). Sensitivity and specificity were evaluated by interacting SCHCs and DICs with the E-Nose, achieving over 90% classification accuracy. Employing selective combinations optimized by NPS, E-Nose successfully classified all six cell types. Consequently, the relative similarity among DICs like cardiomyocytes, endothelial cells with SCHCs was established relied on comparing response data from the E-Nose sensor without resorting to complex evaluations.

논문정보

형식Research article
게재일2023년 11월 (BRIC 등록일 2023-12-06)
연구진국내 연구진
분야 바이오·의료융합 > 바이오센싱 및 나노바이오물질

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