Abstract
The precision of previous cancer research based on tumor spheroids, especially the microgel-encapsulating tumor spheroids, was limited by the high heterogeneity in the tumor spheroid size and shape. Here, we reported a user-friendly solenoid valve-based sorter to reduce this heterogeneity. The artificial intelligence algorithm was employed to detect and segmentate the tumor spheroids in real-time for the size and shape calculation. A simple off-chip solenoid valve-based sorting actuation module was proposed to sort out target tumor spheroids with the desired size and shape. Utilizing the developed sorter, we successfully uncovered the drug response variations on cisplatin of lung tumor spheroids in the same population but with different sizes and shapes. Moreover, with this sorter, the precision of drug testing on the spheroid population level was improved to a level comparable to the precise but complex single spheroid analysis. The developed sorter also exhibits significant potential for organoid morphology and sorting for precision medicine research. © 2024 Elsevier B.V.
| Original language | English |
|---|---|
| Article number | 116614 |
| Journal | Biosensors and Bioelectronics |
| Volume | 264 |
| Online published | 30 Jul 2024 |
| DOIs | |
| Publication status | Published - 15 Nov 2024 |
Funding
This work was fully supported by grants from Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone Shenzhen Park Project (HZQB-KCZYZ-2021017), and the City University of Hong Kong (project # 9610559 and # 9680217).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Research Keywords
- Artificial intelligence
- Drug testing
- Solenoid valve
- Tumor spheroid sorter
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