The quantitative analysis of respiratory viruses is of great importance for rapid diagnosis, precision medicine, and prognosis. Several current quantitative analysis systems have been proposed and commercialized. Although they have been proven in trials, quantitative analyzes based on real samples are still complex, time-consuming, and expensive. Therefore, they are not able to directly quantify real samples. In this work, we presented a lab-on-a-chip platform combined with an automated control system to achieve quantitative analysis from samples to results. We developed a multilayer integrated chip to rapidly extract and quantify RNA of coronavirus disease 2019 (COVID-19) pseudovirus from large-volume nasal swab samples. The dependence of the magnetic bead size and the interfacial effect was studied for the first time, and the conditions of immiscible filtration assisted by surface tension (IFAST) method for nucleic acid extraction were optimized to increase the nucleic acid recovery rate up to 85%. Inside the chip, a pneumatic valve was developed for automatic opening and closing of the liquid channel. The integrated chip platform and automatic control system presented here are advantageous for use in resource-limited settings (RLS). In addition, our method can be extended to other respiratory viruses and other sample types.

Single-cell measurements routinely demonstrate high levels of variation between cells, but fewer studies provide insight into the analytical and biological sources of this variation. This is particularly true of chemical cytometry, in which individual cells are lysed and their contents separated, compared to more established single-cell measurements of the genome and transcriptome. To characterize population-level variation and its sources, we analyzed oxidative stress levels in 1278 individual Dictyostelium discoideum cells as a function of exogenous stress level and cell cycle position. Cells were exposed to varying levels of oxidative stress via singlet oxygen generation using the photosensitizer Rose Bengal. Single-cell data reproduced the dose-response observed in ensemble measurements by CE-LIF, superimposed with high levels of heterogeneity. Through experiments and data analysis, we explored possible biological sources of this heterogeneity. No trend was observed between population variation and oxidative stress level, but cell cycle position was a major contributor to heterogeneity in oxidative stress. Cells synchronized to the same stage of cell division were less heterogeneous than unsynchronized cells (RSD of 37-51% vs 93%), and mitotic cells had higher levels of reactive oxygen species than interphase cells. While past research has proposed changes in cell size during the cell cycle as a source of biological noise, the measurements presented here use an internal standard to normalize for effects of cell volume, suggesting a more complex contribution of cell cycle to heterogeneity of oxidative stress.

Pesticides, chemical substances extensively employed in agriculture to optimize crop yields, pose potential risks to human and environmental health. Consequently, regulatory frameworks are in place to restrict pesticide residue concentrations in water intended for human consumption. These regulations are implemented to safeguard consumer safety and mitigate any adverse effects on the environment and public health. Although gas chromatography- and liquid chromatography-mass spectrometry (GC-MS and LC-MS) are highly efficient techniques for pesticide quantification, their use is not suitable for real-time monitoring due to the need for sophisticated laboratory pretreatment of samples prior to analysis. Since they would enable analyte detection with selectivity and sensitivity without sample pretreatment, biosensors appear as a promising alternative. These consist of a bioreceptor allowing for specific recognition of the target and of a detection platform, which translates the biological interaction into a measurable signal. As early detection systems remain urgently needed to promptly alert and act in case of pollution, we review here the biosensors described in the literature for pesticide detection to advance their development for use in the field.

An ultrasensitive dual-signal ratiometric electrochemical sensor was developed for creatinine detection utilizing silver nanoparticles (Ag) with intrinsic self-calibration afforded by iron-nickel bimetallic Prussian blue (FeNiPBA) analogues. The Ag@FeNiPBA exhibits two redox signals corresponding to the Ag+/Ag and Fe3+/Fe2+ systems. Adding chloride (Cl-) solution increases the anodic current of the Ag/Ag system significantly due to the formation of silver chloride through solid-state electrochemistry. While the anodic current of the Ag/Ag system decreases in the presence of creatinine due to the competitive reaction, the Fe/Fe system's anodic current remains the same, which enables a ratiometric response. Under optimized conditions, the response ratio (IAg/IFe) decreases while the creatinine concentration increases linearly between 0.015 and 140 μM, with 0.004 μM as a good detection limit (S/N = 3). These results demonstrate superior performance over previously reported methods for electrochemical creatinine determination. The high sensitivity arises from the signal amplification of the Ag/AgCl solid-state electrochemistry, while the selectivity originates from the specific interaction between Ag+ and creatinine. The Ag@FeNiPBA hybrid can quantify creatinine in real samples with good recoveries. This work opens up new opportunities for applying dual-signal nanostructures to develop electrochemical sensors for (bio)molecule detection.

This study investigated the colorimetric response of standard glucose, serum glucose, and nucleic acid assays on various paper surfaces with different wettability, including hydrophilic, hydrophobic, and nearly superhydrophobic surfaces. Water contact angles (WCA) formed by water droplets on each surface were measured using ImageJ software. The hydrophilic surface showed no contact angle, while the hydrophobic and nearly superhydrophobic surfaces exhibited contact angles of 115.667° and 133.933°, respectively. The colorimetric sensitivity of the standard glucose assay was analyzed on these surfaces, revealing enhanced sensitivity on the nearly superhydrophobic surface due to the high molecular crowding effect owing to its non-wetting behavior and eventually confined reaction product at the sample loading zone. The hydrophobic nature of the surface restricts the spreading and diffusion of the reaction product, leading to a controlled and localized concentration of the assay product leading to moderate colorimetric intensity. On the other hand, the hydrophilic surface showed the least enhancement in colorimetric sensitivity; this is attributed to the high wettability of the hydrophilic surface causing the reaction product to spread extensively, resulting in a larger area of dispersion and consequently a lower colorimetric intensity. The measured limit of detection (LOD) for nucleic acid on nearly superhydrophobic surfaces was found to be 16.15 ng/µL, which was almost four-fold lower than on hydrophilic surfaces (60.08 ng/µL). Additionally, the LODs of standard glucose and clinical serum samples were two-fold lower on nearly superhydrophobic surfaces compared to hydrophilic surfaces. Our findings clearly highlight the promising potential of utilizing superhydrophobic surfaces to significantly enhance colorimetric sensitivity in paper-based diagnostic applications. This innovative approach holds promise for advancing point-of-care diagnostics and improving disease detection in resource-limited settings.

The evaluation of aroma properties of beverages, both analytically as well as with human sensory studies, is a challenging task and most often related to time- and cost-intensive analyses. Whisky is a spirit offering a wide variety of aroma impressions caused by a complex mixture of aroma active compounds. In the present study, methods for the efficient evaluation of aroma characteristics are evaluated for 16 whisky samples of different origins (Scotch and American). Rate all that apply (RATA) was applied as a rapid method for the sensory evaluation of whiskies. Sensory evaluation of the samples led to the determination of eight significant aroma attributes: caramel-/cream caramel-/toffee-like, vanilla-like, (canned) peach-like, phenolic, smoky, fruity, flowery and (fermented) apple-/cider-like. Chemical analysis was conducted by stir bar sorptive extraction (SBSE) coupled to gas chromatography-mass spectrometry in combination with an in-house data processing tool for semi-automated analyte detection. Through chemical analysis of the whisky samples and automated compound detection, we report over 200 mostly aroma-active volatiles. To test both approaches for their potential for sample classification, a simple classification problem (Scotch vs. American) was applied. Linear discriminant analysis (LDA) indicates both that sensory evaluation by RATA (97.86%) and the applied analytical procedure (96.94%) are suitable for the distinction between the two whisky types. In both approaches, potential markers were determined for the classification. These investigations build a solid foundation for the implementation of a versatile platform facilitating rapid and efficient aroma evaluation in various foodstuffs and beverages.

Spices such as paprika, curry, turmeric, dry chilli, and black pepper are grown in various geographic locations and widely used by consumers across the world. Pesticides applied during crop production practices could contaminate the produce, affecting the quality and posing a health risk for consumers. The complexity of the spice matrix and the wide range of target pesticides potentially present require special sample extraction and clean-up treatments to overcome matrix interference and ion suppression. In this study, sample extracts from spice matrices (paprika/curry/turmeric/dry chilli/black pepper) were cleaned up by an automated µSPE clean-up method for multi-residue analysis of pesticides using LC-MS/MS. The automated µSPE clean-up method involves pre-filled cartridges containing various sorbent materials suitable for numerous co-extractives and the automated clean-up process was carried out using an autosampler. The regulatory limit for pesticides in spices varies with type, with a low MRL of 0.05 mg kg-1 or higher for 99% of the analytes. At spiking concentrations of 0.05 and 0.1 mg kg-1, good recoveries between 70 and 120% with RSD values below 20% were achieved for more than 98% of the compounds. With automatic clean-up of samples that takes 5 min/sample, 20% increased output per day shows an important advantage achieved compared to manual clean-up.

Sinapic acid (SA) is ubiquitously distributed in the plant kingdom as a free organic acid and more frequently as a biosynthetic pioneer for SA derivatives, e.g., SA esters. Broad biological and pharmacological activities have been disclosed for SA. Because of the metabolism lability property, metabolites instead of the parent compound should be the primary forms after oral treatment of SA, and those metabolites should also be rapidly observed from SA following administration of SA derivative. Hence, the metabolites might provide a primary contribution to the pharmacological properties of SA; however, the metabolite profile remains unclear. Here, our efforts were devoted to addressing this issue through deploying online energy-resolved mass spectrometry (ER-MS) to accomplish isomer identification which is the key issue hindering metabolite identification, notably those conjugated metabolites. After recording breakdown graphs of concerned fragment ions with online ER-MS, the positive correlations between optimal collision energy (OCE) and bond dissociation energy (BDE) were applied to assign candidate structures to isomeric signals. Moreover, in vitro metabolism with liver cellular subfractions, UV-triggered cis-/trans-configuration transformation, and wet-chemistry hydrogenation were carried out to justify the structures. As a result, sixteen metabolites (M1-M16) were found and confirmatively identified in rat plasma and urine following SA administration, and sulfation, glucuronidation, demethylation, reduction, and dihydroxylation served as the primary metabolic channels. Noteworthily, greater distribution occurred for sulfation and glucuronidation products while inferior distributions were observed for phase I metabolites, and the half-life (T1/2) of most metabolites was greater than that of SA. This study provides a comprehensive insight into the metabolic fate of SA. More importantly, the fortification of online ER-MS and quantum structure calculation to the conventional LC-MS program is eligible to achieve unambiguous identification of isomeric metabolites.

Cooking oil is a critical component of human food and its main component, lipid, is influential to health, but assessing its authenticity and quality can be challenging due to its complex chemical composition. In this study, we introduce a novel application of time-resolved coherent anti-Stokes Raman scattering (T-CARS) spectroscopy for detecting adulteration and understanding the mechanisms of lipid oxidation in various cooking oils. Our research surpasses the limitations of conventional spontaneous Raman spectroscopy, demonstrating that intra-molecular interactions from unsaturated bonds in triglycerides significantly influence vibrational dephasing time. We observed that these dephasing times, although diverse initially, converge to a similar value after heating cycles. Notably, a longer vibrational dephasing of the CH2 symmetric stretching mode was found to correlate with a higher lipid oxidation rate. These findings underscore the potential of T-CARS in identifying and characterizing subtle molecular interactions, offering a transformative approach to understanding molecular dynamics. This research paves the way for broader applications of T-CARS across fields such as chemistry, biomedicine, and material science, marking a significant advancement in the development of innovative analytical techniques.