High-Precision Viral Detection Using Electrochemical Kinetic Profiling of Aptamer-Antigen Recognition in Clinical Samples and Machine Learning.

High-precision viral detection at point of need with clinical samples plays a pivotal role in the diagnosis of infectious diseases and the control of a global pandemic. However, the complexity of clinical samples that often contain very low viral concentrations makes it a huge challenge to develop simple diagnostic devices that do not require any sample processing and yet are capable of meeting performance metrics such as very high sensitivity and specificity. Herein we describe a new single-pot and single-step electrochemical method that uses real-time kinetic profiling of the interaction between a high-affinity aptamer and an antigen on a viral surface. This method generates many data points per sample, which when combined with machine learning, can deliver highly accurate test results in a short testing time. We demonstrate this concept using both SARS-CoV-2 and Influenza A viruses as model viruses with specifically engineered high-affinity aptamers. Utilizing this technique to diagnose COVID-19 with 37 real human saliva samples results in a sensitivity and specificity of both 100 % (27 true negatives and 10 true positives, with 0 false negative and 0 false positive), which showcases the superb diagnostic precision of this method.

Analysis and Discrimination of Canadian Honey Using Quantitative NMR and Multivariate Statistical Methods.

To address the growing concern of honey adulteration in Canada and globally, a quantitative NMR method was developed to analyze 424 honey samples collected across Canada as part of two surveys in 2018 and 2019 led by the Canadian Food Inspection Agency. Based on a robust and reproducible methodology, NMR data were recorded in triplicate on a 700 MHz NMR spectrometer equipped with a cryoprobe, and the data analysis led to the identification and quantification of 33 compounds characteristic of the chemical composition of honey. The high proportion of Canadian honey in the library provided a unique opportunity to apply multivariate statistical methods including PCA, PLS-DA, and SIMCA in order to differentiate Canadian samples from the rest of the world. Through satisfactory model validation, both PLS-DA as a discriminant modeling technique and SIMCA as a class modeling method proved to be reliable at differentiating Canadian honey from a diverse set of honeys with various countries of origins and floral types. The replacement method of optimization was successfully applied for variable selection, and trigonelline, proline, and ethanol at a lower extent were identified as potential chemical markers for the discrimination of Canadian and non-Canadian honeys.

Economically Motivated Adulteration of Lemon Juice: Cavity Ring Down Spectroscopy in Comparison with Isotope Ratio Mass Spectrometry: Round-Robin Study.

Background: Economically motivated adulteration (EMA) of foods has become an increasing concern in recent years, with lemon juice as a popular target. Objective and Method: In this work, an optimized preparation procedure for the isolation of citric acid from lemon juice was validated using elemental analyzer-isotope ratio MS (EA-IRMS) to detect adulteration with exogenous citric acid. Additionally, 69 imported lemon juice samples were evaluated using combustion module-cavity ring down spectrometry (CM-CRDS) and compared with the well-established EA-IRMS. Equivalency of CM-CRDS to EA-IRMS was further demonstrated by conducting a round-robin study involving eight laboratories throughout the United States, Canada, and New Zealand. Results: Overall, the results obtained for CM-CRDS were statistically indistinguishable from the results obtained using EA-IRMS for EMA lemon juice analysis. Conclusions: Therefore, CM-CRDS is a viable option for this application. Highlights: The CM-CRDS instrumentation is easy to operate, robust, and provides δ13C values comparable to EA-IRMS for citrate analysis. Through a multi-laboratory exercise, CM-CRDS was shown to be an alternative to EA-IRMS in the detection of economic adulteration of lemon juice.

Spectrofluorimetric determination of formaldehyde in maple syrup.

A quick and simple method was developed for determination of formaldehyde in maple syrup. In this method, formaldehyde reacts with Fluoral P to form a complex which is chemically extracted by isobutanol and determined by spectrofluorimetry. Performance, as gauged by the limits of detection (0.16 mg/kg) and quantitation (0.21 mg/kg), recovery (>79%), and variability (1.9-16.1%, depending on fortification level and class of syrup) were superior to the current official AOAC standard method.