Qingyi Wei

Freshness prediction of starch-coated snakehead fish fillets across different storage times remains challenging due to complex quality deterioration and spectral distribution shifts. In the current research, hyperspectral imaging (HSI) combined with transfer learning (TL) was developed to predict the freshness of starch-coated snakehead fish fillets during short-term refrigerated and long-term frozen storage. The results showed that storage led to texture deterioration, pH increase, TVB-N accumulation, and lipid oxidation, while starch coating effectively delayed quality degradation. Compared with models based only on short-term or long-term data, the domain transfer convolutional neural network (DT-CNN) model improved the robustness of freshness prediction across storage stages. The DT-CNN model based on VIS spectra achieved the best performance for TBA prediction in the starch coating treatment group, with an R_P² of 0.76 and RMSE_P of 0.13, and showed strong performance for TVB-N prediction in the starch coating treatment group, with an R_P² of 0.85 and RMSE_P of 8.66. These results demonstrate that HSI combined with TL is a promising non-destructive method for freshness evaluation of starch-coated snakehead fish fillets during storage.

Background: Inhibition of α-glucosidase activity is recognized as an effective strategy for managing type 2 diabetes. Methods: The inhibitory mechanisms of two kinds of mulberry flavonoids, namely sanggenone D and kuwanon G, on α-glucosidase were investigated and the hypoglycemic pathways were explored in the current study. Results: The outcomes indicate that sanggenone D (IC₅₀: 4.51 × 10⁻⁵ mol/L) and kuwanon G (IC₅₀: 3.83 × 10⁻⁵ mol/L) inhibited α-glucosidase activity by non-competition/anti-competition mixed inhibition and competitive inhibition, respectively. Moreover, the secondary structure of α-glucosidase was altered by static quenching and exhibited a decrease in α-helix and β-antiparallel content, and an increase in β-sheet content. Furthermore, the interaction forces between sanggenone D/kuwanon G and α-glucosidase were hydrophobic interactions and hydrogen bonds, as evidenced by molecular docking. The binding affinity, stability, and binding energy aligned with the results of IC₅₀. Notably, the cyclization in sanggenone D structure resulted in a decrease in the number of phenolic hydroxyl groups and thus a reduction in the formation of hydrogen bonds, which ultimately diminished the binding affinity of sanggenone D to α-glucosidase. In addition, Western blot analysis further indicated that sanggenone D and kuwanon G regulated glucose metabolism by activating the GLUT4 pathway. Conclusions: The results provided useful reference for the application of sanggenone D and kuwanon G in hypoglycemic functional components.

Inhibition of α-glucosidase activity is considered to be an effective treatment for type 2 diabetes. The inhibitory mechanisms of sanggenone D and kuwanon G on α-glucosidase were investigated and the pathways for hypoglycemic effects were explored in the current study. The outcomes indicated that sanggenone D (IC50: 4.51 × 10-5 mol/L) and kuwanon G (IC50: 3.83 × 10-5 mol/L) inhibited α-glucosidase activity by non-competition/anti-competition mixed inhibition and competitive inhibition, respectively. Besides, the secondary structure of α-glucosidase were altered by static quenching, and exhibited the decrease in α-helix, β-antiparallel content, while increase in β-sheet content. Furthermore, the interaction forces between sanggenone D/kuwanon G and α-glucosidase were hydrophobic interactions and hydrogen bonds as evidenced by molecular docking. The binding affinity, stability and binding energy aligned with the results of IC50. Cyclization in sanggenone D structure resulted in a decrease in the number of phenolic hydroxyl groups and thus a reduction in the formation of hydrogen bonds, which ultimately diminished the binding affinity of sanggenone D to α-glucosidase. In addition, western blot results showed that sanggenone D and kuwanon G regulated glucose metabolism by activating of GLUT4 pathway.

Dimethoate contaminants in food pose a threat to human health. Rapid and sensitive trace detection methods are required to keep food safe. In this study, a novel fluorescent aptasensor was developed for the sensitive detection of dimethoate based on carbon quantum dots labeled with double-stranded DNA (CQDs−apt−cDNA) and Ti₃C₂T_x flakes. Under optimal conditions, the aptasensor showed a good linear range of 1 × 10⁻⁹ to 5 × 10⁻⁵ M for dimethoate with a coefficient of determination (R²) of 0.996. Besides, a low detection limit of 2.18 × 10⁻¹⁰ M was obtained. The aptasensor showed high selectivity in interference samples and good reproducibility with an RSD of 3.06% (<5%) for dimethoate detection. Furthermore, the proposed aptasensor was applied to the detection of dimethoate in apple juice and tap water with satisfactory recoveries from 96.2 to 104.4%. Because of these benefits, this aptasensor has the potential and promise for detecting food contaminants in the food industry.

Efficient detection and degradation of fungicides are greatly concerned with aquatic food safety. Herein, a multifunction CoFe₂O₄/MoS₂@Au (ACMS) composite was synthesized for crystal violet (CV) and malachite green (MG) photocatalytic degradation and SERS determination. As the construction of the Z-scheme heterostructure of ACMS, which enhanced the light absorption capability and the separation efficiency of photoexcited carrier significantly, ACMS possessed an excellent photocatalytic performance with a degradation rate of 94.76% for CV under simulated solar light irradiation. Furthermore, the multifunction ACMS exhibited superior SERS capability with a detection limit (LOD) of 4.309 × 10⁻² μg L⁻¹ for MG residues in water. And the ACMS substrates could be utilized to determine the MG residues in crucian carp extract, resulting in a recovery rate of 96.00~116.00%. In addition, such multifunction heterojunctions were performed for in situ monitoring of the photodegradation process. This research opened up a novel perspective on the applications of heterojunction-based multifunction materials for food safety control.

For survival and quality of human life, the search for better ways to ensure food safety is constant. However, food contaminants still threaten human health throughout the food chain. In particular, food systems are often polluted with multiple contaminants simultaneously, which can cause synergistic effects and greatly increase food toxicity. Therefore, the establishment of multiple food contaminant detection methods is significant in food safety control. The surface-enhanced Raman scattering (SERS) technique has emerged as a potent candidate for the detection of multicomponents simultaneously. The current review focuses on the SERS-based strategies in multicomponent detection, including the combination of chromatography methods, chemometrics, and microfluidic engineering with the SERS technique. Furthermore, recent applications of SERS in the detection of multiple foodborne bacteria, pesticides, veterinary drugs, food adulterants, mycotoxins and polycyclic aromatic hydrocarbons are summarized. Finally, challenges and future prospects for the SERS-based detection of multiple food contaminants are discussed to provide research orientation for further.