Janus particles with an anisotropic structure have emerged as a focus of intensive research due to their diverse composition and surface chemistry, which show excellent performance in various fields, especially in biomedical applications. In this review, we briefly introduce the structures, composition, and properties of Janus particles, followed by a summary of their biomedical applications. Then we review several design strategies including morphology, particle size, composition, and surface modification, that will affect the performance of Janus particles. Subsequently, we explore the synthetic methodologies of Janus particles, with an emphasis on the most prevalent synthetic method (surface nucleation and seeded growth). Following this, we highlight Janus particles in biomedical applications, especially in drug delivery, bio-imaging, and bio-sensing. Finally, we will consider the current challenges the materials face with perspectives in the future directions.

Early cancer detection greatly increases the chances for successful treatment, but available diagnostics for some tumours, including lung adenocarcinoma (LA), are limited. An ideal early-stage diagnosis of LA for large-scale clinical use must address quick detection, low invasiveness, and high performance. Here, we conduct machine learning of serum metabolic patterns to detect early-stage LA. We extract direct metabolic patterns by the optimized ferric particle-assisted laser desorption/ionization mass spectrometry within 1 s using only 50 nL of serum. We define a metabolic range of 100–400 Da with 143 m/z features. We diagnose early-stage LA with sensitivity~70–90% and specificity~90–93% through the sparse regression machine learning of patterns. We identify a biomarker panel of seven metabolites and relevant pathways to distinguish early-stage LA from controls (p < 0.05). Our approach advances the design of metabolic analysis for early cancer detection and holds promise as an efficient test for low-cost rollout to clinics.

In-vitro metabolite and drug detection rely on designed materials-based analytical platforms, which are universally used in biomedical research and clinical practice. However, metabolic analysis in bio-samples needs tedious sample preparation, due to the sample complexity and low molecular abundance. A further challenge is to construct diagnostic tools. Herein, we developed a platform using silver nanoshells. We synthesized SiO₂@Ag with tunable shell structures by multi-cycled silver mirror reactions. Optimized nanoshells achieved direct laser desorption/ionization mass spectrometry in 0.5 μL of bio-fluids. We applied these nanoshells for disease diagnosis and therapeutic evaluation. We identified patients with postoperative brain infection through daily monitoring and glucose quantitation in cerebrospinal fluid. We measured drug distribution in blood and cerebrospinal fluid systems and validated the function of blood-brain/cerebrospinal fluid-barriers for pharmacokinetics. Our work sheds light on the design of materials for advanced metabolic analysis and precision diagnostics.

Delicate α-Fe₂O₃ multi-shelled hollow spheres have been prepared by a simple and scalable spray drying method followed by annealing in air. The resulting material shows high specific capacity, good cycling stability, and excellent rate performance in lithium ion battery applications.