Improved longevity and in vivo performance of neurotransmitter detection using 30 µm cone-shaped carbon fiber microelectrode.

使用 30 µm 锥形碳纤维微电极提高神经递质检测的寿命和体内性能

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作者:Kwon Haeun, Cho Hyun-U, Sim Jeongeun, Boo Kyung-Jun, Kang Yumin, Hwang Sangmun, Kwak Youngjong, Jang Jaehyun, Kim Kyung Min, Jeon Se Jin, Shin Chan Young, Bennet Kevin E, Oh Yoonbae, Shin Hojin, Lee Kendall H, Jang Dong Pyo
Fast Scan Cyclic Voltammetry (FSCV) is a widely used electrochemical technique to detect rapid extracellular dopamine transients in vivo. It employs carbon fiber microelectrodes (CFMEs), but conventional 7 µm diameter CFMEs often suffer from limited mechanical durability and reduced lifespan, hindering their use in chronic monitoring. To improve mechanical robustness and long-term functionality, we fabricated 30 µm diameter CFMEs and modified their geometry via electrochemical etching to form cone-shaped tips. We compared the in vitro and in vivo performance of 7 µm, 30 µm bare, and 30 µm cone-shaped CFMEs using FSCV. Electrode longevity was assessed, and biocompatibility was evaluated via immunofluorescence analysis of brain tissue. In vitro, the 30 µm bare CFMEs showed 2.7-fold higher sensitivity (33.3 ± 5.9 pA/µm(2), n = 5) compared to 7 µm CFMEs (12.2 ± 4.9 pA/µm(2), n = 5). However, in vivo dopamine detection was significantly reduced in 30 µm bare CFMEs (12.9 ± 8.1 nA, n = 5) relative to 7 µm CFMEs (24.6 ± 8.5 nA, n = 5), likely due to tissue damage. Cone-shaped modification of 30 µm CFMEs resulted in a 3.7-fold improvement in vivo dopamine signals (47.5 ± 19.8 nA, n = 5) and significantly lower glial activation based on Iba1 and GFAP markers. Furthermore, erosion tests revealed a 4.7-fold increase in lifespan compared to 7 µm CFMEs. These results suggest that while increasing CFME diameter improves sensitivity, it also increases tissue damage in vivo. The cone-shaped geometry effectively mitigates insertion-induced damage, enhancing in vivo performance and biocompatibility. This design offers a promising approach for long-term neurotransmitter monitoring and potential integration into closed-loop neuromodulation systems.

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