Biosensors

Rare-earth-doped upconversion nanoparticles (UCNPs) exhibit upconversion luminescence upon excitation with infrared light and have been extensively utilized in the field of biosensing. In this study, a UCNPs-based biosensor with porous silicon (PSi) as the substrate was developed for the first time, enabling the detection of target DNA molecule concentration. First, a PSi substrate was prepared via electrochemical etching and subsequently functionalized to enable target DNA molecules to immobilize onto the inner walls of the PSi substrate’s pores. Then, UCNPs-labeled probe DNA molecules hybridized with the target DNA molecules, enabling indirect attachment of UCNPs to the inner walls of the PSi substrate. Subsequently, the sample surface is irradiated with a 980 nm laser. Upconversion fluorescence images of the sample, both before and after the biological reaction, are captured using an image acquisition device. Image processing software is employed to calculate the average change in grayscale values, enabling the determination of the molecular concentration of target DNA. The limit of detection (LOD) of this method for target DNA molecular concentration is 86 pM, demonstrating that it enables low-cost, highly sensitive, rapid, and convenient biological detection of target DNA molecules.

Microfluidic chip technologies, also known as lab-on-a-chip systems, have profoundly transformed laboratory medicine by enabling the miniaturization, automation, and rapid processing of complex diagnostic assays using minimal sample volumes. Recent advances in chip design, fabrication methods—including 3D printing, modular and flexible substrates—and biosensor integration have significantly enhanced the performance, sensitivity, and clinical applicability of these devices. Integration of advanced biosensors allows for real-time detection of circulating tumor cells, nucleic acids, and exosomes, supporting innovative applications in cancer diagnostics, infectious disease detection, point-of-care testing (POCT), personalized medicine, and therapeutic monitoring. Notably, the convergence of microfluidics with artificial intelligence (AI) and machine learning has amplified device automation, reliability, and analytical power, resulting in “smart” diagnostic platforms capable of self-optimization, automated analysis, and clinical decision support. Emerging applications in fields such as neuroscience diagnostics and microbiome profiling further highlight the broad potential of microfluidic technology. Here, we present findings from a comprehensive review of recent innovations in microfluidic chip design and fabrication, advances in biosensor and AI integration, and their clinical applications in laboratory medicine. We also discuss current challenges in manufacturing, clinical validation, and system integration, as well as future directions for translating next-generation microfluidic technologies into routine clinical and public health practice.

Sulfamethazine (SMZ) is widely used in livestock production, and its residues can enter water and soil environments, posing potential risks to human health and ecosystems. This study focuses on environmental samples and constructs an AuNP-based colorimetric aptasensor using the SMZ1S aptamer for the rapid visual detection of SMZ. Under optimized conditions, the aptasensor showed a wide linear range from 0.05 to 0.4 µg/mL and a limit of detection of 0.039 µg/mL. Molecular dynamics simulations have demonstrated that the aptamer’s binding to SMZ is stable, providing a theoretical basis for the high selectivity of the aptasensor. Spike-and-recovery experiments yielded recoveries of 87.3–105.5%, 88.6–102.8%, and 87.5–103.4% for SMZ in lake water, tap water, and soil samples, respectively, with relative standard deviations of 5.9–8.3%, 8.0–10.6%, and 4.8–9.6%, showing good agreement with high-performance liquid chromatography (HPLC) results (R² ≥ 0.981). Overall, the proposed aptasensor provides a simple and effective approach for rapid detection of SMZ in environmental samples.