Sorting specific cells from heterogeneous samples is important for research and clinical applications. In this work, a novel label‐free cell sorting method is presented that integrates deep learning image recognition with microfluidic manipulation to differentiate cells based on morphology. Using an Active‐Matrix Digital Microfluidics (AM‐DMF) platform, the YOLOv8 object detection model ensures precise droplet classification, and the Safe Interval Path Planning algorithm manages multi‐target, collision‐free droplet path planning. Simulations and experiments revealed that detection model precision, concentration ratios, and sorting cycles significantly affect recovery rates and purity. With HeLa cells and polystyrene beads as samples, the method achieved 98.5% sorting precision, 96.49% purity, and an 80% recovery over three cycles. After a series of experimental validations, this method can also be used to sort HeLa cells from red blood cells, cancer cells from white blood cells (represented by HeLa and Jurkat cells), and differentiate white blood cell subtypes (represented by HL‐60 cells and Jurkat cells). Cells sorted using this method can be lysed directly on chip within their hosting droplets, ensuring minimal sample loss and suitability for downstream bioanalysis. This innovative AM‐DMF cell sorting technique holds significant potential to advance diagnostics, therapeutics, and fundamental research in cell biology.

Most electrospray based ambient ionization techniques, e.g., laser ablation electrospray ionization (LAESI), utilize a fixed spray solution composition. Complex samples often contain compounds of different polarity that exhibit a wide range of solubilities in the electrospray solvent. Thus, the fixed spray solution composition limits the molecular coverage of these approaches. Two-barrel theta glass capillaries have been used for the rapid mixing of two solutions for manipulating fast reactions including protein folding, unfolding, and charge state distributions. Here, we present a new variant of LAESI mass spectrometry (MS) by scanning the high voltages applied to the two barrels of a theta glass capillary containing two different solvents. In the resulting gradient LAESI (g-LAESI), the composition of the spray solution is ramped between the two solvents in the barrels to facilitate the detection of compounds of diverse polarity and solubility. Dynamic ranges and limits of detection achieved for g-LAESI-MS were comparable to conventional LAESI-MS. We have demonstrated simultaneous detection of different types of chemical standards, and polar and less polar compounds from Escherichia coli cell pellets using g-LAESI-MS. Varying the spray solution composition in a gradient electrospray can benefit from the enhanced solubilities of different analytes in polar and less polar solvents, ultimately improving the molecular coverage in the direct analysis of biological samples.

Extracellular vesicles were successfully extracted from mouse liver tissue using kit combined with TiO₂.