Aptamer‐Mediated Artificial Synapses for Neuromorphic Modulation of Inflammatory Signaling via Organic Electrochemical Transistor

• Published in: Advanced science p. e09545
• Main Authors: Ding, Yuqing, Kuai, You, Li, Rongpei, Xu, Xinzhao, Wang, Bo, Wang, Zhihui, Liu, Yanfang, Dong, Yuchao, Chen, Shunjie, Guo, Meng, Liu, Yunqi, Zhao, Yan
• Format: Journal Article
• Language: English
• Published: Germany 04.08.2025
• Subjects: neuromorphic interface; synaptic plasticity; interleukin‐6 sensing; aptamer‐based biosensor; organic electrochemical transistor
• ISSN: 2198-3844; 2198-3844
• DOI: 10.1002/advs.202509545

Artificial synaptic devices that mimic neuromorphic signal processing hold great promise for bioelectronic interfaces. However, most systems remain limited to physical stimuli or electroactive small molecules, lacking the ability to transduce biologically relevant protein signals. To address this limitation, an aptamer‐mediated aqueous artificial synaptic transistor is developed capable of selectively responding to the interleukin‐6 (IL‐6) signal, a specifically expressed protein of inflammatory stress, via gate‐voltage‐induced synaptic modulation in biologically relevant electrolyte environments. Guided by molecular docking simulations, high‐affinity aptamer sequences are identified for robust recognition of IL‐6. The device demonstrates precise IL‐6 capture and translation into neuromorphic electrical signals across various biological electrolytes (PBS, albumin, serum), with linear detection from 0.5 p m to 50 n m . Moreover, the device can convert IL‐6 binding events into time and concentration‐dependent electrical outputs, exhibiting significant synaptic plasticity and memory retention. When implanted into the caudal vein of sepsis mice, the device stably monitors IL‐6 level and maintains reliable synaptic response to inflammatory‐triggered elevations. Machine learning analysis enables accurate discrimination between normal and pathological states from device‐generated signals. By bridging biochemical signals with neuromorphic encoding, this system outlines a conceptual framework for future integration between artificial and biological neural units, contributing to the hybrid neurosensory systems.