Počet záznamů: 1
SERS-CNN approach for non-invasive and non-destructive monitoring of stem cell growth on a universal substrate through an analysis of the cultivation medium
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SYSNO ASEP 0567074 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název SERS-CNN approach for non-invasive and non-destructive monitoring of stem cell growth on a universal substrate through an analysis of the cultivation medium Tvůrce(i) Skvortsova, A. (CZ)
Trelin, A. (CZ)
Sedlář, Antonín (FGU-C) ORCID
Erzina, M. (CZ)
Trávníčková, Martina (FGU-C) RID, ORCID, SAI
Svobodová, Lucie (FGU-C) RID
Kolská, Z. (CZ)
Siegel, J. (CZ)
Bačáková, Lucie (FGU-C) RID, ORCID
Švorčík, V. (CZ)
Lyutakov, O. (CZ)Celkový počet autorů 11 Číslo článku 132812 Zdroj.dok. Sensors and Actuators B - Chemical. - : Elsevier
Roč. 375, 15 January (2023)Poč.str. 9 s. Jazyk dok. eng - angličtina Země vyd. CH - Švýcarsko Klíč. slova SERS ; artificial intelligence ; stem cells ; non-invasive detection Obor OECD Biomaterials (as related to medical implants, devices, sensors) CEP GA21-06065S GA ČR - Grantová agentura ČR Způsob publikování Omezený přístup Institucionální podpora FGU-C - RVO:67985823 UT WOS 000904973600005 EID SCOPUS 85140356459 DOI 10.1016/j.snb.2022.132812 Anotace The development of advanced methods of SERS-CNN data analysis seems to provide a perfect analytical system that is capable of solving the sophisticated task of determining the species and the behavior of microorganisms. Unlike the widely-used analytical approach, machine learning allows precise analysis even of very complex spectra of biological samples, and can provide precise decisions for a specific biochemical or microbiological task. In this article, we show for the first time the utilization of the SERS-CNN approach for remote observation of mesenchymal stem cell behavior. Our approach is based on SERS measurements of the biochemical changes taking place in the surrounding culture media due to stem cell proliferation and their biochemical activity. The cells were cultivated on various substrates supporting random or oriented cell growth, and also on „surface-toxic“ substrates. SERS-CNN analysis reveals the ability to perform „remote“ non-invasive estimation (i.e. using the surrounding medium analysis) of the degree of cell survival and the proliferation rate, using Raman measurements and advanced spectra data processing. It should be noted that the proposed approach makes it possible to analyze cell behavior without disrupting cell growth, and it can also be performed by untrained staff with the use of widely-available equipment. Pracoviště Fyziologický ústav Kontakt Lucie Trajhanová, lucie.trajhanova@fgu.cas.cz, Tel.: 241 062 400 Rok sběru 2024 Elektronická adresa https://doi.org/10.1016/j.snb.2022.132812
Počet záznamů: 1