Lab-On-Chips (LOCs) offer several advantages over traditional approaches for studying biological models and evaluating drug efficacy. Despite their small size, they present highly complex environments where significant chemical gradients are often confined to specific regions, either through intentional manipulation by researchers or generated by the cellular model itself. To address these challenges and gain deeper insights into biological mechanisms, integrating biosensors in the LOC becomes an appealing solution. In this research, we present a cost-effective, high-resolution stereolithographic technique to create small, widespread optical biosensors directly integrated into the lab-on-chip. To extract information from these sensors, we designed a custom multispectral light source, capable of capturing the optical signature of the field of view, coupled with a dedicated machine-learning algorithm. Applying this approach, we successfully measured the pH in Human Embryonic Stem Cell (hESC) 3D cell cultures, a unique cell type that lacks a pH indicator in its medium. By analyzing local temporal pH trends across various experiments and different areas within the same experiments, we advanced our comprehension of cell-scale metabolic mechanisms and their impact on tissue/organ behavior. © 2023 Elsevier B.V.

Development of integrated optical biosensors based on low-cost stereolithography fabrication and multispectral signature for Lab-On-Chip applications

Massimiani, Micol;
2024-01-01

Abstract

Lab-On-Chips (LOCs) offer several advantages over traditional approaches for studying biological models and evaluating drug efficacy. Despite their small size, they present highly complex environments where significant chemical gradients are often confined to specific regions, either through intentional manipulation by researchers or generated by the cellular model itself. To address these challenges and gain deeper insights into biological mechanisms, integrating biosensors in the LOC becomes an appealing solution. In this research, we present a cost-effective, high-resolution stereolithographic technique to create small, widespread optical biosensors directly integrated into the lab-on-chip. To extract information from these sensors, we designed a custom multispectral light source, capable of capturing the optical signature of the field of view, coupled with a dedicated machine-learning algorithm. Applying this approach, we successfully measured the pH in Human Embryonic Stem Cell (hESC) 3D cell cultures, a unique cell type that lacks a pH indicator in its medium. By analyzing local temporal pH trends across various experiments and different areas within the same experiments, we advanced our comprehension of cell-scale metabolic mechanisms and their impact on tissue/organ behavior. © 2023 Elsevier B.V.
2024
Lab-On-Chip
Machine learning
Multispectral imaging
Optical biosensors
Stereolithography
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14245/3650
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