Label-free high-throughput impedance-activated cell sorting

Cell sorting holds broad applications in fields such as early cancer diagnosis, cell differentiation studies, drug screening, and single-cell sequencing. However, achieving high-throughput and high-purity in label-free single-cell sorting is challenging. To overcome this issue, we propose a label-free, high-throughput, and high-accuracy impedance-activated cell sorting system based on impedance detection and dual membrane pumps. Leveraging the low-latency characteristics of FPGA, the system facilitates real-time dual-frequency single-cell impedance detection with high-throughput (5 × 104 cells per s) for HeLa, MDA-MB-231, and Jurkat cells. Furthermore, the system accomplishes low-latency (less than 0.3 ms), label-free, high-throughput (1000 particles per s) and high-accuracy (almost 99%) single-particle sorting using FPGA-based high-precision sort-timing prediction. In experiments with Jurkat and MDA-MB-231 cells, the system achieved a throughput of up to 1000 cells per s, maintaining a pre-sorting purity of 28.57% and increasing post-sorting purity to 97.09%. These findings indicate that our system holds significant potential for applications in label-free, high-throughput cell sorting.

iSort enables automated complex microfluidic droplet sorting in an effort to democratize technology

Fluorescence-activated droplet sorting (FADS) is a widely used microfluidic technique for high-throughput screening. However, it requires highly trained specialists to determine optimal sorting parameters, and this results in a large combinatorial space that is challenging to optimize systematically. Additionally, it is currently challenging to track every single droplet within a screen, leading to compromised sorting and "hidden" false-positive events. To overcome these limitations, we have developed a setup in which the droplet frequency, spacing, and trajectory at the sorting junction are monitored in real time using impedance analysis. The resulting data are used to continuously optimize all parameters automatically and to counteract perturbations, resulting in higher throughput, higher reproducibility, increased robustness, and a beginner-friendly character. We believe this provides a missing piece for the spreading of phenotypic single-cell analysis methods, similar to what we have seen for single-cell genomics platforms.

Microfluidics-Based Urine Biopsy for Cancer Diagnosis: Recent Advances and Future Trends

Urine biopsy, allowing for the detection, analysis and monitoring of numerous cancer-associated urinary biomarkers to provide insights into cancer occurrence, progression and metastasis, has emerged as an attractive liquid biopsy strategy with enormous advantages over traditional tissue biopsy, such as noninvasiveness, large sample volume, and simple sampling operation. Microfluidics enables precise manipulation of fluids in a tiny chip and exhibits outstanding performance in urine biopsy owing to its minimization, low cost, high integration, high throughput and low sample consumption. Herein, we review recent advances in microfluidic techniques employed in urine biopsy for cancer detection. After briefly summarizing the major urinary biomarkers used for cancer diagnosis, we provide an overview of the typical microfluidic techniques utilized to develop urine biopsy devices. Some prospects along with the major challenges to be addressed for the future of microfluidic-based urine biopsy are also discussed.