As a global public health challenge, food allergy affects hundreds of millions of individuals worldwide. This review provides a recent advance in the field of food allergy, including developments in diagnostic techniques, allergy evaluation methods, and management strategies. In addition, the modulation of food allergies by natural active substances in foods is also emphasized. Combining bioinformatics diagnostics with regulation of dietary actives holds great promise for allergy prevention. Furthermore, evaluation methods that combine dynamic gastrointestinal digestion modeling with bioinformatics provides new ideas for revealing the structural stability of allergens. Finally, enhanced food allergy management has further improved the effectiveness of allergy prevention. This review provides a better understanding and novel insights into the prevention and control of food allergies, as well as explores the potential applications of natural bioactive substances in food allergy management strategies.

Propolis is a resinous complex mixture made from plant resins collected by worker bees and mixed with their own secretions. It is rich in polyphenols and flavonoids and thus has a wide range of biological activities and is considered a functional source for promoting human health. However, propolis and its bioactive compounds have poor water solubility, rapid and intense metabolism, and low oral bioavailability, which limits their wide application. In this paper, the main bioactive substances in propolis were summarized, and the biological characteristics and therapeutic potential of propolis and its bioactive substances were discussed. In addition, this paper discussed the factors affecting the bioavailability of propolis and its functional ingredients, focusing on the research progress in improving the bioavailability and bioactivity of propolis and its functional ingredients using nanoencapsulation technology. Finally, the current situation of the global propolis market and the applications of propolis products in the pharmaceutical, food, cosmetic and other industrial fields were discussed, providing useful references for promoting the development of the propolis industry.

In this study, the effect of ultrasonic on the decrystallisation rate and physicochemical properties (crystal microstructure, rheological properties, textural properties, color, enzyme activities, total phenols, total flavonoids, 5-hydroxymethylfurfural, antioxidant and antibacterial capacity) of loquat honey was investigated, and the action mechanism was revealed using an online real-time temperature monitoring system. The results showed that ultrasonic cavitation and thermal effects worked together to decompose the cluster crystal structure in loquat honey. After 80 min of ultrasonic decrystallisation at 400 W and 40 kHz, the temperature of loquat honey increased to 55.9 ℃ , and the decrystallisation rate reached up to (98.2 ± 0.65)%. In addition, ultrasonic decrystallisation effectively changed loquat honey from a pseudoplasticfluid into a Newtonian fluid, leading to a decrease in hardness and gumminess and an increase in chewiness. Furthermore, ultrasonic decrystallisation facilitated the release of total phenols and flavonoids in loquat honey, thereby enhancing its antioxidant activity. However, the thermal effect and free radicals generated by ultrasonic treatment resulted in the accumulation of 5-hydroxymethylfurfural (5-HMF) and the consumption of reducing sugar by accelerating the Maillard reaction, and led to a decrease in the antibacterial capacity by inhibiting the glucose oxidase activity of loquat honey. The objective of this study is to provide a feasible non-thermal decrystallisation method for honey and technical guidance for promoting the industrial application of efficient decrystallisation technology.

To shorten the complex and time-consuming process of the identification method of the traditional food angiotensin-I-converting enzyme (ACE-I) inhibitory peptides, we propose AHTPeptideFusion based on a segmented fusion with the protein language model and deep learning. The statistical analysis found that hydrophobic amino acids, N-terminal valine is a dominant amino acid in the activity of ACE-I inhibitory peptides. In 12 machine learning (ML) algorithms, the transformer outperformed the other 11 models, with the best performance in predicting short and medium peptides. In the external dataset, AHTPeptideFusion fused by transformer and random forest (RF) showed excellent performance (accuracy > 0.9) in predicting ACE-I inhibitory peptides with lengths ranging from 2 to 15 amino acid residues and different activity distributions, and the reliability and accuracy of AHTPeptideFusion was demonstrated by synthetic peptide and ACE-I inhibition experiments. In addition, hydrogen bonding and electrostatic interaction between 4 synthetic peptides and active residues of ACE-I were found by molecular docking. To further explore the ACE-I inhibitory peptides from animal-derived foods, we established an automated pipeline consisting of the trinity of proteomics, virtual enzymatic digestion and AHTPeptideFusion, and tapped the ACE-I inhibitory peptide released from royal jelly after digestion in the gastrointestinal tract. In conclusion, this computational pipeline will become a powerful screening tool for active peptides from animal-derived foods, which can help food scientists accelerate the mining and design of active peptides from animal-derived foods. Overall, AHTPeptideFusion will be a powerful ACE-I inhibitor peptide prediction tool, it can help food scientists accelerate the mining and design of ACE-I inhibitory peptides.

The significant demand for high quality food has motivated us to adopt appropriate processing methods to improve the food nutritional quality and flavors. In this study, the effects of five drying methods, namely, pulsed vacuum drying (PVD), freeze drying (FD), infrared drying (IRD), hot-air drying (HAD) and sun drying (SD) on free amino acids (FAAs), α-dicarbonyl compounds (α-DCs) and volatile compounds (VOCs) in rape bee pollen (RBP) were determined. The results showed that FD significantly released the essential amino acids (EAAs) compared with fresh samples while SD caused the highest loss. Glucosone was the dominant α-DCs in RBP and the highest loss was observed after PVD. Aldehydes were the dominant volatiles of RBP and SD samples contained more new volatile substances (especially aldehydes) than the other four drying methods. Comprehensively, FD and PVD would be potential methods to effectively reduce the quality deterioration of RBP in the drying process.