Rapid, Label‐free Optical Spectroscopy Platform for Diagnosis of Heparin‐Induced Thrombocytopenia

Unraveling surface-enhanced Raman spectroscopy results through chemometrics and machine learning: principles, progress, and trends

Surface-enhanced Raman spectroscopy (SERS) has gained increasing attention because it provides rich chemical information and high sensitivity, being applicable in many scientific fields including medical diagnosis, forensic analysis, food control, and microbiology. Although SERS is often limited by the lack of selectivity in the analysis of samples with complex matrices, the use of multivariate statistics and mathematical tools has been demonstrated to be an efficient strategy to circumvent this issue. Importantly, since the rapid development of artificial intelligence has been promoting the implementation of a wide variety of advanced multivariate methods in SERS, a discussion about the extent of their synergy and possible standardization becomes necessary. This critical review comprises the principles, advantages, and limitations of coupling SERS with chemometrics and machine learning for both qualitative and quantitative analytical applications. Recent advances and trends in combining SERS with uncommonly used but powerful data analysis tools are also discussed. Finally, a section on benchmarking and tips for selecting the suitable chemometric/machine learning method is included. We believe this will help to move SERS from an alternative detection strategy to a general analytical technique for real-life applications.

Printed Nanochain-Based Colorimetric Assay for Quantitative Virus Detection

Fast and ultrasensitive detection of pathogens is very important for efficient monitoring and prevention of viral infections. Here, we demonstrate a label-free optical detection approach that uses a printed nanochain assay for colorimetric quantitative testing of viruses. The antibody-modified nanochains have high activity and specificity which can rapidly identify target viruses directly from biofluids in 15 min, as well as differentiate their subtypes. Arising from the resonance induced near-field enhancement, the color of nanochains changes with the binding of viruses that are easily observed by a smartphone. We achieve the detection limit of 1 PFU μL^-1 through optimizing the optical response of nanochains in visible region. Besides, it allows for real-time response to virus concentrations ranging from 0 to 1.0×10⁵  PFU mL^-1 . This low-cost and portable platform is also applicable to rapid detection of other biomarkers, making it attractive for many clinical applications.