Fluorescent Copper Nanoclusters for Highly Sensitive Monitoring of Hypoxanthine in Fish

Integrating hypoxanthine and K value for reliable and rapid freshness assessment in marine fish

This study aimed to explore the relationship between hypoxanthine (Hx) levels and freshness indicators in three kinds of fish samples during storage for 7 days at 4 °C to determine the Hx levels indicating freshness. The total volatile basic nitrogen (TVBN) was tested using the semi-micro Kjeldahl method, and Hx level and K value were measured using high-performance liquid chromatography (HPLC). During storage, Hx levels, TVBN, and K values increased, and distinct patterns were observed between Hx and TVBN in three fish samples. The Hx level highly correlated with K value (Adj-R2 = 0.998, 0.986, and 0.986) when K value was below 40 %. A paper biosensor was applied for Hx determination, the color of which correlated well with the K value, offering an easy, rapid and visual tool for predicting fish freshness. Thus, Hx can be used to predict K value and indicate freshness in some application scenario prior to spoilage.

Freshness in Salmon by Hand-Held Devices: Methods in Feature Selection and Data Fusion for Spectroscopy

Salmon fillet was analyzed via hand-held optical devices: fluorescence (@340 nm) and absorption spectroscopy across the visible and near-infrared (NIR) range (400-1900 nm). Spectroscopic measurements were benchmarked with nucleotide assays and potentiometry in an exploratory set of experiments over 11 days, with changes to spectral profiles noted. A second enlarged spectroscopic data set, over a 17 day period, was then acquired, and fillet freshness was classified ±1 day via four machine learning (ML) algorithms: linear discriminant analysis, Gaussian naïve, weighted K-nearest neighbors, and an ensemble bagged tree method. Dual-mode data fusion returned almost perfect accuracies (mean = 99.5 ± 0.51%), while single-mode ML analyses (fluorescence, visible absorbance, and NIR absorbance) returned lower mean accuracies at greater spread (77.1 ± 10.1%). Single-mode fluorescence accuracy was especially poor; however, via principal component analysis, we found that a truncated fluorescence data set of four variables (wavelengths) could predict "fresh" and "spoilt" salmon fillet based on a subtle peak redshift as the fillet aged, albeit marginally short of statistical significance (95% confidence ellipse). Thus, whether by feature selection of one spectral data set, or the combination of multiple data sets through different modes, this study lays the foundation for better determination of fish freshness within the context of rapid spectroscopic analyses.

Sensing materials for fresh food quality deterioration measurement: a review of research progress and application in supply chain

Fresh food are consumed in large quantities worldwide. During the supply chain, microbial growth in fresh food can lead to the production of a number of metabolites, which make food highly susceptible to spoilage and contamination. The quality of fresh food changes in terms of smell, tenderness, color and texture, which causes a decrease in freshness and consumers acceptance. Therefore, the quality monitoring of fresh food has become an essential part in the supply chain. As traditional analysis methods are highly specialized, expensive and have a small scope of application, which cannot be applied to the supply chain to realize real-time monitoring. Recently, sensing materials have received a lot of attention from researchers due to the low price, high sensitivity and high speed. However, the progress of research on sensing materials has not been critically evaluated. The study examines the progress of research in the application of sensing materials for fresh food quality monitoring. Meanwhile, indicator compounds for spoilage of fresh food are analyzed. Moreover, some suggestions for future research directions are given.

Assessing Meat Freshness via Nanotechnology Biosensors: Is the World Prepared for Lightning-Fast Pace Methods?

In the rapidly evolving field of food science, nanotechnology-based biosensors are one of the most intriguing techniques for tracking meat freshness. Purine derivatives, especially hypoxanthine and xanthine, are important signs of food going bad, especially in meat and meat products. This article compares the analytical performance parameters of traditional biosensor techniques and nanotechnology-based biosensor techniques that can be used to find purine derivatives in meat samples. In the introduction, we discussed the significance of purine metabolisms as analytes in the field of food science. Traditional methods of analysis and biosensors based on nanotechnology were also briefly explained. A comprehensive section of conventional and nanotechnology-based biosensing techniques is covered in detail, along with their analytical performance parameters (selectivity, sensitivity, linearity, and detection limit) in meat samples. Furthermore, the comparison of the methods above was thoroughly explained. In the last part, the pros and cons of the methods and the future of the nanotechnology-based biosensors that have been created are discussed.

Determination of the critical micelle concentration of surfactants using fluorescence strategies

The increasing importance of surfactants in various fields has led to growing interest in the comprehensive characterization of surfactants. The critical micelle concentration (CMC), the most fundamental property of surfactants, is a parameter that must be measured. In particular, with the continuous expansion of the molecular structure of surfactants, numerous novel amphiphilic molecules have been developed that are capable of forming ordered aggregates in various solvent systems. Fluorescence spectroscopy, based on the differences in fluorescence intensity and wavelength of the fluorescent probe in the solvent phase and micellar phase, can sensitively detect the CMC of surfactants. This review aims to summarize the various fluorescence methods used to determine the CMC, including aggregation-induced emission (AIE), excimer formation, intramolecular charge transfer (ICT), and other miscellaneous strategies. The difficulties and limitations in the CMC determination process are also described. Further suggestions are provided to guide the existing fluorescence probes and the corresponding fluorescence methods to detect critical aggregation concentrations of amphiphilic molecules.

Advances in Accurate Quantification Methods in Food Analysis

Food safety is an important topic, and with the perfection of regulations and technologies, food safety is improving [...]

Visualization of Polymer–Surfactant Interaction by Dual-Emissive Gold Nanocluster Labeling

Polymer-surfactant interaction decides the performance of corresponding complexes, making its rapid and intuitionistic visualization important for enhancing the performance of products and/or processing in related fields. In this study, the fluorescence visualization of the interaction between cationic hyperbranched polyethyleneimine and anionic sodium dodecyl sulfonate surfactant was realized by dual-emissive gold nanocluster labeling. The sensing mechanism was due to the interaction-induced polymer conformation change, which regulated the molecular structure and subsequent photoradiation process of the gold nanoclusters. All three inflection points of the interactions between the polymers and the surfactants were obtained by the change in fluorescence emission ratio of the designed dual-emissive gold nanoclusters. Moreover, these inflection points are verified by the hydrodynamic diameter and zeta potential measurements.

Catechin-inspired gold nanocluster nanoprobe for selective and ratiometric dopamine detection via forming azamonardine

The sensitive and selective perception of dopamine (DA, a typical neurotransmitter) is important to evaluate the biological environment. In this study, a catechin-functionalized gold nanocluster (C-Au NC) nanoprobe has been explored for the ratiometric DA sensing. The detection mechanism is based on the formation of azamonardine via selective DA-catechin chemical reaction and subsequent enhanced fluorescence emission. Using Au NC emission as the internal reference, ratiometric fluorescence variation is realized, which allows sensitive DA analysis with a limit of detection of 1.0 nM (S/N = 3) and linear response concentration range from 0 to 500 nM. The characteristic chemical reaction between catechin and DA affords favorable selectivity over other amino acids, metal ions and small molecules. In addition, the practical application of the proposed nanoprobe is validated by the accurate detection of DA content in urea and cell lysate samples.

Peptide-Derived Biosensors and Their Applications in Tumor Immunology-Related Detection

Small-molecular targeting peptides possess features of biocompatibility, affinity, and specificity, which is widely applied in molecular recognition and detection. Moreover, peptides can be developed into highly ordered supramolecular assemblies with boosting binding affinities, diverse functions, and enhanced stabilities suitable for biosensors construction. In this Review, we summarize recent progress of peptide-based biosensors for precise detection, especially on tumor-related analysis, as well as further provide a brief overview of the progress in tumor immune-related detection. Also, we are looking forward to the prospective future of peptide-based biosensors.