Thermal-annealing-regulated plasmonic enhanced fluorescence platform enables accurate detection of antigen/antibody against infectious diseases

Neural Network Enables High Accuracy for Hepatitis B Surface Antigen Detection with a Plasmonic Platform

The detection of hepatitis B surface antigen (HBsAg) is critical in diagnosing hepatitis B virus (HBV) infection. However, existing clinical detection technologies inevitably cause certain inaccuracies, leading to delayed or unwarranted treatment. Here, we introduce a label-free plasmonic biosensing method based on the thickness-sensitive plasmonic coupling, combined with supervised deep learning (DL) using neural networks. The strategy of utilizing neural networks to process output data can reduce the limit of detection (LOD) of the sensor and significantly improve the accuracy (from 93.1%-97.4% to 99%-99.6%). Compared with widely used emerging clinical technologies, our platform achieves accurate decisions with higher sensitivity in a short assay time (∼30 min). The integration of DL models considerably simplifies the readout procedure, resulting in a substantial decrease in processing time. Our findings offer a promising avenue for developing high-precision molecular detection tools for point-of-care (POC) applications.

Unraveling the Activity and Mechanism of TM@g-C4N3 Electrocatalysts in the Oxygen Reduction Reaction

In this work, a high-throughput screening strategy and density functional theory (DFT) are jointly employed to identify high-performance TM@g-C4N3 (TM = 3d, 4d, 5d transition metals) single-atom catalysts (SACs) for the oxygen reduction reaction (ORR). Comprehensive studies demonstrated that Cu@, Zn@, and Ag@g-C4N3 show high ORR catalytic activities under both acidic and alkaline conditions with favorable overpotentials (ηORR) of 0.70, 0.89, and 0.89 V, respectively; among them, Cu@g-C4N3 is the best candidate. The ORR follows a four-electron mechanism with the final product H2O/OH-. Cu@, Zn@, and Ag@g-C4N3 catalysts also exhibit good thermal (500 K) and electrochemical (0.93-3.14 V) stabilities. Cu@, Zn@, and Ag@g-C4N3 demonstrate superior activities with low ηORR due to its moderate adsorption strength of *OH. The ηORR and the Gibbs free energy changes of *OH (ΔG4(acidic)/ΔG4(alkaline)) resemble a volcano-type relationship under acidic/alkaline conditions, respectively. Additionally, the O-O bond length in *OOH emerged as an effective structural descriptor for rapidly identifying the promising electrocatalysts. This research provides valuable insights into the origin of the ORR activity on TM@g-C4N3 and offers useful guidance for the efficient exploration of high-performance catalyst candidates.

Naked-Eye Readable Microarray for Rapid Profiling of Antibodies against Multiple SARS-CoV-2 Variants

Novel high-throughput protein detection technologies are critically needed for population-based large-scale SARS-CoV-2 antibody detection as well as for monitoring quality and duration of immunity against virus variants. Current protein microarray techniques rely heavily on labeled transduction methods that require sophisticated instruments and complex operations, limiting their clinical potential, particularly for point-of-care (POC) applications. Here, we developed a label-free and naked-eye readable microarray (NRM) based on a thickness-sensing plasmon ruler, enabling antibody profiling within 30 min. The NRM chips provide 100% accuracy for neutralizing antibody detection by efficiently screening antigen types and experimental conditions and allow for the profiling of antibodies against multiple SARS-CoV-2 variants in clinical samples. We further established a flexible "barcode" NRM assay with a simple tape-based operation, enabling an effective smartphone-based readout and analysis. These results demonstrate new strategies for high-throughput protein detection and highlight the potential of novel protein microarray techniques for realistic clinical applications.