Honeycomb-Inspired Surface-Enhanced Raman Scattering Microarray for Large-Area Automated Testing of Urease in Saliva Samples.

Surface-enhanced Raman scattering (SERS) technology, as an important analytical tool, has been widely applied in the field of chemical and biomedical sensing. Automated testing is often combined with biochemical analysis technologies to shorten the detection time and minimize human error. The present SERS substrates for sample detection are time-consuming and subject to high human error, which are not conducive to the combination of SERS and automated testing. Here, a novel honeycomb-inspired SERS microarray is designed for large-area automated testing of urease in saliva samples to shorten the detection time and minimize human error. The honeycomb-inspired SERS microarray is decorated with hexagonal microwells and a homogeneous distribution of silver nanostars. Compared with the other four common SERS substrates, the optimal honeycomb-inspired SERS microarray exhibits the best SERS performance. The RSD of 100 SERS spectra continuously collected from saliva samples is 6.56%, and the time of one detection is reduced from 5 min to 10 s. There is a noteworthy linear relationship with a R2 of 0.982 between SERS intensity and urease concentration, indicating the quantitative detection capability of the urease activity in saliva samples. The honeycomb-inspired SERS microarray, combined with automated testing, provides a new way in which SERS technology can be widely used in biomedical applications.

Micro-macro SERS strategy for highly sensitive paper cartridge with trace-level molecular detection.

Surface-enhanced Raman Scattering (SERS) has become a powerful spectroscopic technology for highly sensitive detection. However, SERS is still limited in the lab because it either requires complicated preparation or is limited to specific compounds, causing poor applicability for practical applications. Herein, a micro-macro SERS strategy, synergizing polymer-assisted printed process with paper-tip enrichment process, is proposed to fabricate highly sensitive paper cartridges for sensitive practical applications. The polymer-assisted printed process finely aggregates nanoparticles with a discrete degree of 1.77, and SERS results are matched with theoretical enhancement, indicating small cluster-dominated hotspots at the micro-scale and thus 41-fold SERS increase compared to other aggregation methods. The paper-tip enrichment process moves molecules in a fluid into small tips filled with plasmonic clusters, and molecular localization at hotspots is achieved by the simulation and optimization of fluidic velocity at the macro-scale, generating a 39.5-fold SERS sensibility increase in comparison with other flow methods. A highly sensitive paper cartridge contains a paper-tip and a 3D-printed cartridge, which is simple, easy-to-operate, and costs around 2 US dollars. With a detection limit of 10 -12 M for probe molecules, the application of real samples and multiple analytes achieves single-molecule level sensitivity and reliable repeatability with a 30-min standardized procedure. The micro-macro SERS strategy demonstrates its potential in practical applications that require point-of-care detection.

Usefulness of viral kinetics for early prediction of a sustained virological response in HCV-1 non-responders re-treated with pegylated interferon and ribavirin.

BACKGROUND & AIMS: Undetectable HCV RNA at 12 weeks is the stopping rule recommended in HCV patients in whom previous treatment has failed. Whether earlier virological criteria may be useful for deciding treatment discontinuation remains subject of debate. The aim of this study was to identify, in HCV-1 non-responders and relapsers to IFN or Peg-IFN and ribavirin, the earliest and most accurate predictor of failure to respond to a new treatment combining Peg-IFN and ribavirin. METHODS: Prediction of SVR was assessed using the area under the ROC (AUROC) curve of reduction in viral load at different time points. RESULTS: This study included 151 patients (32% with extensive fibrosis or cirrhosis). A SVR was reached in 34% (21% in non-responders and 59% in relapsers). In non-responders, 1 month was the most accurate time point for predicting SVR (AUROC: 0.787 ± 0.075, p = 0.0001). Thirty-seven percent of non-responders did not have a 1-log drop in viral load at 1 month. All these patients had detectable HCV RNA at 3 months (p < 0.0001) and only 4% attained a SVR (p = 0.004). The same high negative predictive value for SVR was found in sensitivity analysis restricted to non-responders to Peg-IFN and ribavirin. In contrast, in relapsers, undetectable HCV RNA at 3 months was the earliest criterion with high negative predictive value (92%, p < 0.0001). CONCLUSIONS: All HCV-1 non-responders who did not have a 1-log drop in viral load at 1 month remained HCV-RNA-detectable at 3 months, and only 4% attained a SVR. This new criterion can be used early on as a first stopping rule.