Food research international (Ottawa, Ont.)最新文献

The colonic mucus layer is the primary interface between the host and the gut microbiota. It serves both as an ecological niche for bacteria and a barrier protecting the host from microbial exposure. Disruption of the mucus layer, particularly under Western-style diet (WSD) feeding, increases the risk of infection and inflammation. Here, we identify casein glycomacropeptide (CGMP), a milk-derived glycopeptide, as a novel dietary supplement capable of preserving mucus function under WSD consumption. Notably, we demonstrate that the sialylation level of CGMP is a key determinant of its protective effects. Supplementation of highly sialylated CGMP not only prevented WSD-induced mucus defects but also altered the gut microbiota composition, enhancing beneficial bacterial genera, particularly Bifidobacterium. Mechanistically, bacterial shifts were associated with increased production of the short-chain fatty acid propionate, which can induce mucus growth. Our findings thus reveal sialylated CGMP as a promising prebiotic supplement to counteract diet-induced mucus dysfunction, highlighting the importance of protein-bound glycan structures in modulating host-microbiota interaction.

Olive (Olea europaea) leaves are a valuable source of bioactive compounds with numerous associated health benefits. These beneficial effects may arise from metabolites generated in vivo rather than from the native constituents of the extract. However, the human metabolism of these compounds remains underexplored. This study profiles urinary metabolites of olive leaves in humans, demonstrating extensive metabolism and identifying key derivatives. Urine samples from seventeen healthy volunteers were collected pre- and post-supplementation with an olive leaf extract and analyzed using an untargeted metabolomics workflow based on HPLC-ESI-qTOF-MS. Over 18,500 molecular features were detected, which were subsequently filtered and examined using a combination of R-based data processing packages and both supervised and unsupervised statistical analyses. Results revealed 513 significant features related to olive leaf extract intake, 176 of which were successfully annotated. Key metabolites included 28 oleuropein conjugates (e.g., hydroxyoleuropein) and 48 compounds derived from oleuropein degradation and attributed to hydroxytyrosol and elenolic acid metabolism (e.g., homovanillic acid and oleoside), along with several flavonoids and phenolic acids. Both phase I and phase II modifications dominated, while intact parent compounds were scarcely detected, highlighting extensive biotransformation and rapid urinary excretion, predominantly within the first 6 h. Moreover, 19 metabolites overlapped with those previously identified in plasma from the same volunteers, underscoring coordinated systemic processing. These findings emphasize the power of untargeted metabolomics to uncover novel bioactive structures and metabolic pathways, and provide a basis for future research on the health potential of olive-derived metabolites, which remains limitedly studied.

The globalization of food systems has heightened the risk of foodborne pathogens such as Salmonella, Listeria monocytogenes, and Campylobacter, exacerbated by rising antimicrobial resistance (AMR). Traditional pathogen identification and AMR risk surveillance methods are often labor-intensive and low-throughput, while single-omics approaches fail to capture microbial complexity. Moreover, reliance on individual machine learning (ML) models limits predictive robustness, posing challenges to food safety and public health. This systematic review evaluates ML-based predictive modeling integrated with omics techniques (genomics, metagenomics, and transcriptomics) for foodborne pathogen and AMR risk surveillance. Following PRISMA guidelines, 1245 articles from PubMed, Scopus, and other databases (2015-2025) were screened, selecting 13 relevant studies. These studies applied ML algorithms, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machines (SVM), to enhance predictive accuracy. The selected studies demonstrated predictive accuracies up to 99 % and AUROC scores above 0.90. Key discoveries include genetic markers for Salmonella virulence, Listeria attribution to fruits and dairy, and 145 mobile antimicrobial resistance genes (ARGs) in poultry. Despite these advancements, limitations such as small sample sizes, inconsistent metadata, overfitting, and computational scalability hinder real-world implementation. This review underscores the potential of ML-driven omics frameworks to revolutionize foodborne pathogen and AMR risk monitoring, paving the way for smarter, more resilient food safety systems. However, methodological inconsistencies necessitate standardized protocols, larger datasets, and explainable AI (XAI) to improve reliability and applicability in global food safety monitoring.

Although in the literature it is referred to as a Non-Conventional Food Plant, ora-pro-nóbis is a traditional food plant that has been incorporated into the diet and culture of various communities in different regions of the planet. Their leaves have a high protein content and contain high levels of amino acids, dietary fiber, minerals, fatty acids, volatile compounds, and bioactive compounds, including phenolic compounds, flavonoids, and carotenoids. This study aims to provide a systematic review of the literature on ora-pro-nóbis, addressing its chemical composition, bioactive compounds, biological activities, and its applications in different areas, carried out with the aid of bibliometric tools to identify influential publications and research trends in this field. Using different bibliometric tools, it was possible to observe that studies on ora-pro-nóbis showed an increase, highlighting the importance of this topic in the food and pharmaceutical industry. The bibliometric analysis showed that studies involving the leaves of ora-pro-nóbis focus on the evaluation of chemical composition, including proximal composition, phenolic and flavonoid compounds, and applications with biological activity, including antioxidant activity. Research trends highlight studies evaluating the extraction of ora-pro-nóbis mucilage in the development of new materials carrying bioactive compounds, such as films, hydrogels, and microcapsules. The article highlights the importance of the application of ora-pro-nóbis in different industry segments, especially in the areas of food science and technology, and pharmaceuticals.