Dan Fan

Nanomedicine has yielded clinically useful platforms, including liposomes, albumin-bound nanoparticles, and lipid nanoparticles; yet, many systems translate poorly because of nonspecific biodistribution, limited target-site accumulation, inefficient cellular uptake and intracellular delivery, immune clearance, and off-target toxicity. These bottlenecks are often shaped at cell membrane interfaces, where therapeutic materials are recognized, retained, internalized, or cleared and may elicit unsafe responses. Here, we frame cell membrane biophysics as a therapeutic interface for nanomedicine. We examine how lipid organization and fluidity, mechanics, electrochemical state, glycocalyx architecture, and membrane protein identity shape recognition, adhesion, endocytosis, fusion, trafficking, immune responses, and drug release. We assess how disease-associated membrane remodeling can create candidate therapeutic entry points and delivery barriers across cancer, neurodegeneration, inflammation, infection, and vascular disease. We then analyze receptor-mediated targeting, lipid-domain-associated uptake, membrane-coated nanocarriers, engineered extracellular vesicles, and hybrid platforms, with explicit context-of-use definitions and design boundaries. Finally, we propose translational qualification through function-linked critical quality attributes, mechanism-relevant potency assays, context-matched models, in vivo pharmacology and immune safety, scalable manufacturing, and regulatory evaluation. Progress will depend less on descriptive membrane mimicry than on measurable, reproducible, and qualified membrane-dependent functions.

Cell sorting plays a crucial role in both medical and biological research. As a key passive sorting technique in the field of microfluidics, deterministic lateral displacement (DLD) has been widely applied to cell separation and sorting. This review aims to summarize the latest advances in the optimization of channel design for microfluidic DLD cell sorting. First, we provide an overview of the design elements of microfluidic DLD cell sorting channels, focusing on key factors that affect separation efficiency and accuracy, including channel geometry, fluid dynamics, and the interaction between cells and channel surfaces. Subsequently, we review recent innovations and progress in channel design for microfluidic DLD technology, exploring its applications in biomedical fields and its integration with machine learning. Additionally, we discuss the challenges currently faced in optimizing channel design for microfluidic DLD cell sorting. Finally, based on existing research, we make a summary and put forward prospective views on the further development of this field.