研究目的
To achieve a quality-controlled production of brain organoids and to provide readout capabilities for assays development by realizing active micro-scale devices for in-tissue wireless sensing and monitoring of biosignals.
研究成果
The proposed μRadio module is feasible for integrating all necessary circuits in a small area with low power consumption, and preliminary experiments show that micro-devices can be internalized into 3D cell assemblies without cytotoxicity. This approach supports the development of bionic organoids for real-time in-tissue monitoring.
研究不足
The study is based on simulations and preliminary in vitro experiments with dummy devices; actual CMOS device prototypes are under production and not yet tested. Potential limitations include impact of aluminum contacts on coil efficiency, alignment mismatches, and need for optimization in 3D cell cultures with human-derived neurons.
1：Experimental Design and Method Selection:
The study involves designing a low-power CMOS micro-device (μRadio) for wireless biosensing in 3D cell assemblies, using circuit simulations and preliminary in vitro experiments. Theoretical models include RF wireless power delivery, data transmission, and bioelectrical signal amplification.
2：Sample Selection and Data Sources:
Human glioblastoma cell line U-87mg was used for cell culture experiments. Dummy silicon micro-devices of similar size to the μRadio were fabricated and integrated into 3D spheroids.
3：List of Experimental Equipment and Materials:
Equipment includes a 96-wells Ultra-Low Attachment plate from Corning, inverted Leica DMI 6000 CS microscope, MTT assay kit from Sigma-Aldrich, and fabricated Si-dummy devices. Materials include serum-free neurobasal medium, GFP-expressing virus, and IPA for dissolving formazan crystals.
4：Experimental Procedures and Operational Workflow:
For cell culture, 4000 cells were plated with a dummy device in each well, incubated for 7 days, and monitored with microscopy. Viability was assessed using MTT assay. Circuit simulations were performed using post-layout simulations on a 130nm RF-CMOS technology.
5：Data Analysis Methods:
Data from simulations included power consumption, gain, noise, and frequency response analyzed using montecarlo simulations. Cell viability data were analyzed by measuring absorbance at 575 nm.
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