Carbocyanine-Based Optical Sensor Array for the Discrimination of Proteins and Rennet Samples Using Hypochlorite Oxidation.

Optical sensor arrays are widely used in obtaining fingerprints of samples, allowing for solutions of recognition and identification problems. An approach to extending the functionality of the sensor arrays is using a kinetic factor by conducting indicator reactions that proceed at measurable rates. In this study, we propose a method for the discrimination of proteins based on their oxidation by sodium hypochlorite with the formation of the products, which, in turn, feature oxidation properties. As reducing agents to visualize these products, carbocyanine dyes IR-783 and Cy5.5-COOH are added to the reaction mixture at pH 5.3, and different spectral characteristics are registered every several minutes (absorbance in the visible region and fluorescence under excitation by UV (254 and 365 nm) and red light). The intensities of the photographic images of the 96-well plate are processed by principal component analysis (PCA) and linear discriminant analysis (LDA). Six model proteins (bovine and human serum albumins, γ-globulin, lysozyme, pepsin, and proteinase K) and 10 rennet samples (mixtures of chymosin and pepsin from different manufacturers) are recognized by the proposed method. The method is rapid and simple and uses only commercially available reagents.

A Reaction-Based Optical Fingerprinting Strategy for the Recognition of Fat-Soluble Samples: Discrimination of Motor Oils.

Optical "fingerprints" are widely used for chemometrics-assisted recognition of samples of different types. An emerging trend in this area is the transition from obtaining "static" spectral data to reactions analyzed over time. Indicator reactions are usually carried out in aqueous solutions; in this study, we developed reactions that proceed in an organic solvent, thereby making it possible to recognize fat-soluble samples. In this capacity, we used 5W40, 10W40, and 5W30 motor oils from four manufacturers, with six samples in total. The procedure involved mixing a dye, sample, and reagents (HNO3, HCl, or tert-butyl hydroperoxide) in an ethanolic solution in a 96-well plate and measuring absorbance or near-infrared fluorescence intensity every several minutes for 20-55 min. The obtained photographic images were processed by linear discriminant analysis (LDA) and the k-nearest neighbors algorithm (kNN). Discrimination accuracy was evaluated by a validation procedure. A reaction of oxidation of a dye by nitric acid allowed us to recognize all six samples with 100% accuracy for LDA. Merging of data from the four reactions that did not provide complete discrimination ensured an accuracy of 93% for kNN. The newly developed indicator systems have good prospects for the discrimination of other fat-soluble samples. Overall, the results confirm the viability of the kinetics-based discrimination strategy.

Estimation of doses absorbed by potato tubers under electron beam or X-ray irradiation using an optical fingerprinting strategy.

High-energy electron beam and X-ray processing of foods can be used for extending their storage life and for combating pests and pathogens. Several instrumental techniques are used to estimate irradiation doses in foods, but these methods are complex and laborious, require expensive equipment, and do not always allow to determine low doses. This study was aimed at developing simple methods for detecting irradiation in potato tubers and for dose estimation. We used a "fingerprinting" strategy that does not involve quantitation of any compound; instead, the rate of indicator reactions involving carbocyanine dyes is measured. The dye content was monitored by its near-infrared fluorescence intensity and visible-light absorption. Potatoes not subjected to treatment and those irradiated with different doses (10, 100, 1000, 5000, or 10,000 Gray) could be distinguished by linear discriminant analysis. Thus, the order of magnitude of the absorbed dose can be estimated with 89% ± 3% accuracy for a mixture of tubers of two potato varieties irradiated with an electron beam or with 95% ± 8% accuracy for one variety irradiated with an X-ray source.

Aggregation-based fluorescence amplification strategy: "turn-on" sensing of aminoglycosides using near-IR carbocyanine dyes and pre-micellar surfactants.

This study is aimed at developing sensing schemes without obtaining selective receptors. A series of simple carbocyanine dyes was synthesized, whose emission was quenched in water with formation of nanoparticles in the range of 20-100 nm. Fluorescence in near-IR region is "turned on" in the presence of a drug cation of middle molecular weight (400-700 Da) and sodium dodecyl sulfate (SDS), as well as anionic drugs and a cationic surfactant (cetyltrimethylammonium bromide, CTAB). Aggregates (clusters) up to 100-200 nm in size were detected using dynamic light scattering (DLS) and Rayleigh light scattering (RLS) techniques in the systems: cationic analyte-SDS, carbocyanine dye-CTAB, and in all brightly fluorescent ternary systems dye-surfactant-analyte. Small ions (<200 Da) incapable of multi-point binding do not form the aggregates or cause the emission enhancement. The "turn-on" signal is only observed at the surfactant submicellar concentrations insufficient to solubilize the dye nanoparticles. Based on these findings, we suggest a rapid and simple method for the detection of ≥4·10-5 mol/L of neomycin in urine. The proposed strategy paves the way for developing more selective methods.