Cai Hongwei, Ao Zheng, Wu Zhuhao, Song Sunghwa, Mackie Ken, Guo Feng
Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN 47405, USA.
Gill Center for Biomolecular Science, and, Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA.
Lab Chip. 2021 Jun 1;21(11):2194-2205. doi: 10.1039/d1lc00145k.
Acoustofluidics, by combining acoustics and microfluidics, provides a unique means to manipulate cells and liquids for broad applications in biomedical sciences and translational medicine. However, it is challenging to standardize and maintain excellent performance of current acoustofluidic devices and systems due to a multiplicity of factors including device-to-device variation, manual operation, environmental factors, sample variability, etc. Herein, to address these challenges, we propose "intelligent acoustofluidics" - an automated system that involves acoustofluidic device design, sensor fusion, and intelligent controller integration. As a proof-of-concept, we developed intelligent acoustofluidics based mini-bioreactors for human brain organoid culture. Our mini-bioreactors consist of three components: (1) rotors for contact-free rotation via an acoustic spiral phase vortex approach, (2) a camera for real-time tracking of rotational actions, and (3) a reinforcement learning-based controller for closed-loop regulation of rotational manipulation. After training the reinforcement learning-based controller in simulation and experimental environments, our mini-bioreactors can achieve the automated rotation of rotors in well-plates. Importantly, our mini-bioreactors can enable excellent control over rotational mode, direction, and speed of rotors, regardless of fluctuations of rotor weight, liquid volume, and operating temperature. Moreover, we demonstrated our mini-bioreactors can stably maintain the rotational speed of organoids during long-term culture, and enhance neural differentiation and uniformity of organoids. Comparing with current acoustofluidics, our intelligent system has a superior performance in terms of automation, robustness, and accuracy, highlighting the potential of novel intelligent systems in microfluidic experimentation.
声流体学通过结合声学和微流体学,提供了一种独特的手段来操纵细胞和液体,在生物医学科学和转化医学中具有广泛的应用。然而,由于多种因素,包括设备间的差异、手动操作、环境因素、样品变异性等,要使当前的声流体设备和系统标准化并保持出色的性能具有挑战性。在此,为应对这些挑战,我们提出了“智能声流体学”——一种自动化系统,它涉及声流体设备设计、传感器融合和智能控制器集成。作为概念验证,我们开发了基于智能声流体学的微型生物反应器用于人类脑类器官培养。我们的微型生物反应器由三个组件组成:(1)通过声学螺旋相位涡旋方法实现无接触旋转的转子,(2)用于实时跟踪旋转动作的相机,以及(3)基于强化学习的控制器,用于对旋转操作进行闭环调节。在模拟和实验环境中对基于强化学习的控制器进行训练后,我们的微型生物反应器能够实现孔板中转子的自动旋转。重要的是,我们的微型生物反应器能够对转子的旋转模式、方向和速度实现出色的控制,而不受转子重量、液体体积和操作温度波动的影响。此外,我们证明了我们的微型生物反应器能够在长期培养过程中稳定地维持类器官的旋转速度,并增强类器官的神经分化和均匀性。与当前的声流体学相比,我们的智能系统在自动化、鲁棒性和准确性方面具有卓越的性能,突出了新型智能系统在微流体实验中的潜力。