Development of biomimetic sensors to determine the functionality of in vitro cell models

Advances in biomedical science have enabled the development of in vitro models that mimic human tissues. Non-invasive real-time monitoring of these models would provide valuable insights without disrupting the cellular environment. This study explores the use of molecularly imprinted polymers (MIPs) for this purpose, focusing on insulin and lactate as biomarkers of cellular metabolism. MIP sensors were created by electropolymerizing pyrrole around insulin or lactate templates on carbon electrodes. The sensors showed high sensitivity and selectivity, with detection ranges of 20.0–70.0 pM for insulin (LOD: 2.41 pM) and 0.5–3.0 mM for lactate. These findings highlight MIPs’ potential for personalized diagnostics and therapy monitoring.

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Publication Details

Journal
Anali PAZU
Published
2024-12-25
DOI
https://doi.org/10.18690/analipazu.14.2.39-57.2024
Primary Topic
3D Printing in Biomedical Research
Type
article
Field-Weighted Citation Impact
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article

Development of biomimetic sensors to determine the functionality of in vitro cell models

M. Kaiser, Tanja Zidarič, Tina Maver, Noah Emil Glisik et al.
Anali PAZU
3D Printing in Biomedical Research
article

Development of biomimetic sensors to determine the functionality of in vitro cell models

M. Kaiser, Tanja Zidarič, Tina Maver, Noah Emil Glisik, Matjaž Frangež, JARO VEZJAK, JURE TERDIN, MATIC ŽNIDARŠIČ
article en

Abstract

Advances in biomedical science have enabled the development of in vitro models that mimic human tissues. Non-invasive real-time monitoring of these models would provide valuable insights without disrupting the cellular environment. This study explores the use of molecularly imprinted polymers (MIPs) for this purpose, focusing on insulin and lactate as biomarkers of cellular metabolism. MIP sensors were created by electropolymerizing pyrrole around insulin or lactate templates on carbon electrodes. The sensors showed high sensitivity and selectivity, with detection ranges of 20.0–70.0 pM for insulin (LOD: 2.41 pM) and 0.5–3.0 mM for lactate. These findings highlight MIPs’ potential for personalized diagnostics and therapy monitoring.

Anali PAZUVol. 14(2)
University of Maribor (SI)
Openalex Percentile: Top 76%
3D Printing in Biomedical Research
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