Weihua He

would not substantially affect the cell property. We envision that the NN-enhanced real-time IFC will provide a new platform for high-throughput, real-time and online cell intrinsic electrical characterization.

Imaging flow cytometry allows image-activated cell sorting (IACS) with enhanced feature dimensions in cellular morphology, structure, and composition. However, existing IACS frameworks suffer from the challenges of 3D information loss and processing latency dilemma in real-time sorting operation. Herein, we establish a neuromorphic-enabled video-activated cell sorter (NEVACS) framework, designed to achieve high-dimensional spatiotemporal characterization content alongside high-throughput sorting of particles in wide field of view. NEVACS adopts event camera, CPU, spiking neural networks deployed on a neuromorphic chip, and achieves sorting throughput of 1000 cells/s with relatively economic hybrid hardware solution (~$10 K for control) and simple-to-make-and-use microfluidic infrastructures. Particularly, the application of NEVACS in classifying regular red blood cells and blood-disease-relevant spherocytes highlights the accuracy of using video over a single frame (i.e., average error of 0.99% vs 19.93%), indicating NEVACS’ potential in cell morphology screening and disease diagnosis. Existing image-activated cell sorting tools suffer from the challenges of 3D information loss and processing latency in real-time sorting operations. Here, the authors propose a neuromorphic-enabled video-activated cell sorter (NEVACS) framework, which achieves high-dimensional spatiotemporal characterization content and high-throughput sorting of particles.

Abstract Reflecting various physiological states and phenotypes of single cells, intrinsic biophysical characteristics (e.g., mechanical and electrical properties) are reliable and important, label‐free biomarkers for characterizing single cells. However, single‐modal mechanical or electrical properties alone are not specific enough to characterize single cells accurately, and it has been long and challenging to couple the conventionally image‐based mechanical characterization and impedance‐based electrical characterization. In this work, the spatial‐temporal characteristics of impedance sensing signal are leveraged, and an impedance‐based multimodal electrical‐mechanical flow cytometry framework for on‐the‐fly high‐dimensional intrinsic measurement is proposed, that is, Young's modulus E , fluidity β , radius r , cytoplasm conductivity σ i , and specific membrane capacitance C sm , of single cells. With multimodal high‐dimensional characterization, the electrical‐mechanical flow cytometry can better reveal the difference in cell types, demonstrated by the experimental results with three types of cancer cells (HepG2, MCF‐7, and MDA‐MB‐468) with 93.4% classification accuracy and pharmacological perturbations of the cytoskeleton (fixed and Cytochalasin B treated cells) with 95.1% classification accuracy. It is envisioned that multimodal electrical‐mechanical flow cytometry provides a new perspective for accurate label‐free single‐cell intrinsic characterization.

Microfluidic-based portable devices for stool analysis are important for detecting established biomarkers for gastrointestinal disorders and understanding the relationship between gut microbiota imbalances and various health conditions, ranging from digestive disorders to neurodegenerative diseases. However, the challenge of processing stool samples in microfluidic devices hinders the development of a standalone platform. Here, we present the first microfluidic chip that can liquefy stool samples via acoustic streaming. With an acoustic transducer actively generating strong micro-vortex streaming, stool samples and buffers in microchannel can be homogenized at a flow rate up to 30 μL min-1. After homogenization, an array of 100 μm wide micropillars can further purify stool samples by filtering out large debris. A favorable biocompatibility was also demonstrated for our acoustofluidic-based stool liquefaction chip by examining bacteria morphology and viability. Moreover, stool samples with different consistencies were liquefied. Our acoustofluidic chip offers a miniaturized, robust, and biocompatible solution for stool sample preparation in a microfluidic environment and can be potentially integrated with stool analysis units for designing portable stool diagnostics platforms.