Bioinspired Superhydrophobic SERS Substrates for Machine Learning Assisted miRNA Detection in Complex Biomatrix Below Femtomolar Limit

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22310%2F23%3A43927109" target="_blank" >RIV/60461373:22310/23:43927109 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1016/j.aca.2023.341708" target="_blank" >https://doi.org/10.1016/j.aca.2023.341708</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.aca.2023.341708" target="_blank" >10.1016/j.aca.2023.341708</a>

Result language

angličtina

Original language name

Bioinspired Superhydrophobic SERS Substrates for Machine Learning Assisted miRNA Detection in Complex Biomatrix Below Femtomolar Limit

Original language description

Surface-enhanced Raman spectroscopy (SERS) is an analytical method with high potential in the field of medicine. The design of SERS substrates, based on specific morphology and/or chemical modification, allow the recognition of the presence of specific analytes with precision close to a single-molecule detection limit. However, the SERS analysis of real samples is significantly complicated by the presence of a large number of “minor” molecules that can shield the signal from the target analyte and make it impossible to determine it in practice. In this work, an advanced SERS approach was used for the detection of cancer-related miRNA-21 in blood plasma, used as a molecular model background. The approach was based on the combination of the biomimetic plasmon-active SERS substrate, its tuned surface chemistry and advanced SERS data analysis, making use of artificial machine learning. In the first step, biomimetic SERS substrates were created using a butterfly wing as a starting template. The substrates were covered by thin Au layer and covalently grafted with hydrophobic chemical moieties to introduce superhydrophobic and water-adhesive properties. The self-concentration of the analyte on the substrates was achieved by minimizing the contact area between the analyte drop and the substrate, which is facilitated by surface superhydrophobicity and additionally enhanced by drop evaporation on the flipped over substrate. Due to the presence of cancer miRNA and blood plasma background, the measured SERS spectra represent a complex of interfering peaks. Thus, their interpretation was carried out using a specially trained machine learning model. As a result, reliable and repeatable quantitative detection of miRNAs below the femtomolar level (up to 10−16 M) on the background of human blood plasma becomes possible.

Czech name

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Czech description

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Type

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

CEP classification

—

OECD FORD branch

20501 - Materials engineering

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

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

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

Name of the periodical

Analytica Chimica Acta

ISSN

0003-2670

e-ISSN

—

Volume of the periodical

1278

Issue of the periodical within the volume

OCT 16 2023

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

24

Pages from-to

"341708/1"-24

UT code for WoS article

001076457700001

EID of the result in the Scopus database

2-s2.0-85169050550