Polygonatum cyrtonema Hua is a crucial medicinal and edible plant whose antioxidant activity is primarily attributed to its phenolic constituents. Evaluating samples from five geographical origins revealed that the Fuzhou (FZ) ecotype exhibited the strongest antioxidant capacity, significantly correlating with total phenolic content (TPC). Integrated metabolomics and co-expression network analyses identified 32 key polyphenols (flavonoids, lignans, and phenolic acids) as central contributors to this antioxidant capacity. Furthermore, network pharmacology and molecular docking predicted that 10 key polyphenols stably interact with core oxidative damage-related proteins, including prostaglandin-endoperoxide synthase 2 (PTGS2), matrix metallopeptidase 9 (MMP9), and epidermal growth factor receptor (EGFR). Transcriptomic profiling highlighted the enrichment of phenylpropanoid and flavonoid biosynthesis pathways across origins. Integrative analysis identified 14 structural genes driving polyphenol biosynthesis, with RT-qPCR confirming the upregulation of 4-coumarate: CoA ligase (4CL), Chalcone synthase (CHS), Shikimic acid/Quinic acid hydroxycinnamoyl transferase (HCT), and Dirigent protein (DIR) in the FZ samples. Ultimately, this study elucidates the gene-metabolite basis of geographical variations in P. cyrtonema antioxidant capacity, providing valuable pharmacological insights and genetic resources for breeding superior, high-polyphenol cultivars.
Monoterpenoids are key contributors to the characteristic aromas of fermented tea, but their formation by Aspergillus cristatus remains unclear. In this study, liquid-state fermentation of a tea infusion was tracked through inoculation with A. cristatus, monoterpenoid profiles, sensory analysis, and transcriptomics were generated at three fermentation stages with or without glucose supplementation. A. cristatus promoted monoterpenoid accumulation as fermentation progressed, and glucose supplementation induced earlier and stronger accumulation of key odor-active compounds. Gas chromatography–olfactometry coupled with aroma extract dilution analysis and odor activity value analyses identified linalool, α-terpineol, geranial, neral, geraniol, citronellol, β-ocimene, nerol, and β-myrcene as major odor-active monoterpenoids in TG12. Transcriptomic analysis indicated activation of the MVA pathway, and AcGal4 was identified as a putative regulatory factor associated with Acerg20 and AcTPS. AcTPS was functionally validated in vitro as a nerol synthase. These findings could assist in the targeted regulation of sensory characteristics of fermented tea.
In this work, two predominant gas-generating spoilage fungi (labeled as CQ2 and CQ5) were isolated from deteriorated roxburgh rose (Rosa roxburghii Tratt) juice and identified as Pichia nanzhaoensis and Arxiozyma slooffiae, respectively. Meanwhile, a series of novel trifluoromethylpyrimidine derivatives bearing a thiosemicarbazide group were synthesized. Biological activity evaluation demonstrated that compound 5a showed stronger antimicrobial efficacy against the isolated strains, with the EC50 values of 10.63 μg/mL (CQ2) and 8.24 μg/mL (CQ5), respectively, than potassium sorbate (both exceeded 100 μg/mL); compound 5a also exhibited superior antioxidant activity, with the IC50 values of 4.14 μg/mL (DPPH assay) and 2.95 μg/mL (ABTS assay), respectively, surpassing vitamin C (6.38 μg/mL) and trolox (8.04 μg/mL). Molecular docking and 100 ns dynamics simulations validated its stable binding to NADPH oxidase with the ΔEMMPBSA value of −36.458 kJ/mol, and ADMET analysis confirmed its desirable biosafety. In addition, application experiments confirmed that compound 5a effectively suppressed browning, conserved nutrients, and optimized the juice flavor of roxburgh rose juice during storage. Thus, these results suggest that compound 5a is a promising multifunctional preservative with integrated antimicrobial, antioxidant, and antibrowning activities for roxburgh rose juice and other fruit beverages.
Pollen identification from honey (melissopalynology) is of great economic and consumer relevance. Traditional microscopy is time-consuming and dependent on expert knowledge, thus limiting high-throughput analyses. We tested whether pollen images generated with Multispectral Imaging Flow Cytometry (MIFC) classified by machine learning (ML) (convolution neural networks (CNNs) and random forest (RF)) can serve as a fast and reproducible method for identifying pollen in honey. We examined how the classification of honey pollen is affected by images from different matrices (anther and honey samples), how results compare with traditional microscopic analysis and used a set of human-interpretable image features to better explain ML results. The study focused on the six common target pollen in honey Brassica, Castanea, Centaurea, Helianthus, Phacelia and Tilia type. A classifier trained with a combination of anther and honey brightfield and fluorescence images provided the best predictions for 13 monofloral and 10 polyfloral honeys. Yielding pollen identification results comparable to microscopy, three times more pollen can be evaluated, and a measurement time of a maximum of 10 min, the method demonstrates its high potential as a powerful screening tool in melissopalynology.
Cold-pressed apple, carrot, and celery juices retain native PR-10 allergens associated with Pollen-Food Allergy Syndrome, whereas thermal processing can alter allergen recognition while compromising heat-sensitive nutrients and sensory quality. We propose matrix-derived hypoallergenicity, a framework in which food-matrix chemistry may regulate allergen accessibility. Using beetroot (Beta vulgaris) as a model matrix, we examine two chemically plausible pathways, polyphenol-derived quinone modification and betalamic-acid-mediated carbonyl chemistry. Neither pathway has been validated in authentic juice systems. This perspective, therefore, defines a testable framework for modulating allergen behavior while preserving nutritional and sensory quality.
