The huge potential of liquid chromatography-high-resolution mass spectrometry (LC-HRMS) still comes along with the challenges of data analysis. Regions of interest multivariate curve resolution (ROIMCR) is a valid chemometric tool when working in data-independent acquisition (DIA), since it provides a link between precursor and product ions based on chromatographic and spectral profiles. Still, the quality of the ROIMCR models should be carefully evaluated for a consequent reliable annotation of non-target chemicals. The present case study deals with the non-target analysis of extracts coming from passive samplers deployed in a wastewater treatment facility in Antarctica (Italian Research Station). The extracts, derived from polar organic chemical integrative samplers (POCIS), were analyzed by LC-DIA-HRMS/MS, resulting in a rich and complex data set. The use of a fit-for-purpose ROIMCR workflow ended in six models for a total of 770 resolved components; among them, approximately 100 compounds were tentatively identified thanks to the recently developed MSident software, including pharmaceuticals and natural substances. The chemical meaningfulness of all resolved MCR components was carefully checked and rationalized for the first time in a classification system, with 7 classes divided into 3 "goodness levels" (A, B, and C). Level A components were characterized by single chromatographic peaks and mass spectra with a reasonable appearance of precursor and product ions. Level B components presented flaws or anomalies in either the chromatographic or spectral profile, and level C components clearly showed unacceptable features. The percentage of high-quality MCR components (level A) ranged from 15 to 48%, while components of acceptable quality (levels A and B) reached percentages between 65% and 85%. Most annotated compounds were indeed associated with good-quality MCR components. The automatization of the proposed classification system may constitute a powerful additional tool to evaluate MCR models' quality and thus improve the reliability of ROIMCR results when applied to challenging case studies.
Despite the need for reliable rapid antigen tests for infectious disease diagnostics, tests that combine rapid answer-to-result times with high sensitivity and specificity remain elusive. A major challenge in developing such tests is the loss of performance of analytical assays in clinical samples. Herein, we developed a rapid antigen test based on a real-time electrochemical sandwich assay for detecting SARS-CoV-2 and Influenza A in saliva. This assay used aptamers for both target capture and signal transduction and produced limits of detection of 301 and 743 copies/mL for SARS-CoV-2 and Influenza A, respectively. When evaluating this assay with clinical saliva samples, we encountered major issues in distinguishing between positive and negative samples. In response, we developed a revised method to interrogate each clinical sample with a pair of electrochemical detectors modified, respectively, with a functional aptamer or a nonfunctional aptamer mutant. This method enabled us to normalize the signal response measured from each clinical sample with a reference signal, overcoming the previously encountered challenge and resulting in a clinical sensitivity of 100% and a specificity of 100% when analyzing 20 saliva samples that were collected and tested for COVID-19.
The well-known Fabry-Pérot (F-P) cavity serves as a crucial element of complex optical devices, offering distinctive functionalities. However, modifying reflection properties by altering the underlying optical structure remains challenging. Inspired by the optical modulation ability of plasmonic nanoparticles (NPs) and the sensitivity of reflective interferometric Fourier transform spectroscopy (RIFTS) of the F-P cavity to effective optical thickness (EOT), herein, a local surface plasmon resonance (LSPR) effect-mediated F-P interferometer with improved sensing ability is proposed. Using glucose as a model analyte, the TiO2 nanotube (NT)-based F-P interferometer is constructed by integrating a pH-responsive block copolymer (BCP) film and LSPR-mediated enzyme-like reactions in interferometric TiO2 NTs. The high-energy hotspots generated by the Au-LSPR effect can accelerate glucose oxidation in NTs, which generates gluconic acid and H2O2 as the products. By combining the experimental results with COMSOL simulations, it is found that the satisfactory response achieved in reflective interferometric Fourier transform spectroscopy (RIFTS) not only relates to the enhanced reflectivity induced by AuNPs but also depends on the EOT changes mediated by the Au-LSPR effect. The plasmon-mediated F-P interferometer offers sensitive glucose quantification with satisfactory performance in real samples, suggesting a new route to design an F-P cavity with a highly sensitive response for boosting target sensing performance.