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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985823%3A_____%2F23%3A00567074" target="_blank" >RIV/67985823:_____/23:00567074 - isvavai.cz</a>

Alternative codes found

RIV/60461373:22310/23:43925032 RIV/44555601:13440/23:43897699

Result on the web

<a href="https://doi.org/10.1016/j.snb.2022.132812" target="_blank" >https://doi.org/10.1016/j.snb.2022.132812</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.snb.2022.132812" target="_blank" >10.1016/j.snb.2022.132812</a>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

30404 - Biomaterials (as related to medical implants, devices, sensors)

Project

<a href="/en/project/GA21-06065S" target="_blank" >GA21-06065S: New functionalized plasmon-based sensors as tools for cell monitoring and advanced tissue engineering</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Sensors and Actuators B - Chemical

ISSN

0925-4005

e-ISSN

0925-4005

Volume of the periodical

375

Issue of the periodical within the volume

15 January

Country of publishing house

CH - SWITZERLAND

Number of pages

9

Pages from-to

132812

UT code for WoS article

000904973600005

EID of the result in the Scopus database

2-s2.0-85140356459