Critical reviews in food science and nutrition最新文献

Dietary health impact modeling often underpins health impact assessments - valuable decision-support tools for public health nutrition. These models depend on epidemiological evidence to quantify associations between dietary risk factors and health outcomes. However, the review and selection of evidence pose remains challenging due to a lack of systematic approaches for risk-outcome pair selection and difficulties extracting harmonized dose-response data from published literature. To address these challenges, this work aimed to 1) update the Nordic Nutrition Recommendations 2023 (NNR2023) epidemiological evidence base and suggest an approach for comparing evidence grading systems, 2) propose a streamlined method to extract non-linear dose-response curves from meta-analyses, and 3) construct an open-access database of the synthesized evidence. The NNR2023 search methodology was replicated, and risk-outcome pairs were selected using modified NNR2023 criteria. Non-linear relationships were estimated by extracting data points with an open-source graph reader and fitting piecewise constant functions. From the selected updated and original NNR2023 evidence, 159 risk-outcome associations were included, of which 51 were non-linear, and around 40% achieved levels of at least mid-range evidence certainty. The provided database and methodology contribute to increased transparency and provide a standard approach to evidence selection and use in dietary health impact modeling.

Most omega-3 supplements contain eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in defined ratios, yet their pharmacokinetic and anti-inflammatory effects are not fully understood. This systematic review and meta-analysis evaluated how EPA:DHA dosing ratios, alongside EPA+DHA daily dose, influence blood fatty acid profiles and inflammatory markers across 96 clinical trials published before February 2025. Standardized mean differences with 95% confidence intervals were calculated. EPA+DHA supplementation significantly increased EPA:DHA blood ratios and blood EPA+DHA levels, with larger effects in healthy individuals. Supplementation also reduced arachidonic acid (AA) and key inflammatory markers, C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6), particularly in participants with underlying health conditions. Ratios <1.0 produced the greatest cytokine reductions, whereas ratios ≥1.0 most effectively increased the EPA:DHA blood ratio and lowered AA. EPA+DHA doses of 1-3 g/day were associated with the most consistent reductions in CRP, TNF-α, and IL-6. Linear regression showed a strong association between the EPA:DHA dosing ratio and the EPA:DHA blood ratio and identified the EPA:DHA blood ratio as the strongest predictor of AA reduction. These findings indicate distinct ratio- and dose-dependent effects of EPA and DHA and highlight the importance of optimizing omega-3 formulations to enhance bioavailability and anti-inflammatory outcomes.

Algae-derived oligopeptides have emerged as high-value biomolecules for health and industrial applications due to their superior solubility, stability, and bioavailability compared with intact proteins. However, large-scale utilization remains constrained by low extraction yields from conventional processes, complex purification requirements, and the absence of standardized handling protocols for low-molecular-weight peptides. This review critically examines recent technological advances aimed at overcoming these limitations, with emphasis on innovative extraction approaches such as subcritical water processing and ionic liquid-based techniques. In contrast to bulk proteins that require extensive hydrolysis, oligopeptides are inherently small, readily soluble, and easily absorbed, making them well-suited for functional food, pharmaceutical, and cosmeceutical applications. Nevertheless, the structural complexity of algal proteins continues to restrict extraction efficiency and increase processing costs. Recent integration of artificial intelligence and machine learning-assisted proteomics with nanomaterial-based separation platforms has significantly improved peptide characterization, purification efficiency, and bioactivity validation. By addressing key research gaps, particularly the transition from in vitro findings to clinical relevance, this review outlines a framework for advancing algal oligopeptides as scalable next-generation bioactives. These compounds exhibit diverse therapeutic activities, including antioxidants, antihypertensives, antidiabetics, and dermatological effects, while supporting sustainable bioprocessing and responsible marine resource utilization.

Ensuring the freshness of meat is crucial for food safety and consumer trust. Traditional methods for evaluating meat freshness, such as sensory analysis and chemical assays, are time-consuming, labor-intensive, and destructive. Machine learning (ML) offers a promising alternative by providing real-time, nondestructive solutions for monitoring meat quality, rationalizing the food industry. This review examines the principles and applications of ML in meat freshness evaluation, focusing on key algorithms like Principal Component Regression (PCR), Partial Least Squares (PLS), Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and neural networks. It also details the ML-based detection pipeline, covering data acquisition, preprocessing, model selection, and fine-tuning. The paper highlights recent advancements in ML approaches tailored for meat freshness assessment, such as Convolutional Neural Networks (CNN) and ensemble learning models, which have proven effective in tackling spoilage rate, safety concerns, and the complex chemical composition of meat. However, challenges remain, including the need for high-quality datasets and model interpretability. Addressing these challenges will be crucial for the widespread adoption of ML-based solutions in meat freshness detection, ultimately leading to safer and higher-quality food products.

Fermentability is largely dictated by fiber structure, which shapes physiochemical properties and microbial accessibility. While many fibers are rapidly fermented, others are only partially degraded or remain non-fermentable yet still provide benefits such as bulking, improved motility, and altered colonic environment. Interindividual variation in gut physiology and microbiota composition adds further complexity, making it challenging to predict fiber-specific outcomes. Mechanistic studies of these resistant fibers and their interactions with other dietary polysaccharides remain relatively limited. Dietary fibers are indigestible carbohydrate polymers that are structurally and functionally diverse, encompassing natural, extracted, and synthetic forms. Their glycosidic linkages are selectively degraded by colonic bacteria that express specialized enzymes generating gases and metabolites, including short-chain fatty acids. Delaying rather than inhibiting fermentation is desirable as it delivers these beneficial metabolites to distal regions of the colon, where they exert protective and anti-carcinogenic effects. This review focuses on the physiochemical properties of fermentation-resistant and non-fermentable fibers, highlighting their role in gastrointestinal health. We emphasize magnetic resonance imaging to noninvasively monitor gut motility and regional fermentation dynamics in vivo. We discuss how structural attributes can prolong fermentation and target distal colonic metabolism, ultimately helping to guide tailored dietary interventions to maximize fiber's therapeutic potential.

Foodborne bacteria are a significant contributor to foodborne diseases worldwide, and effective prevention requires accurate early detection and continuous monitoring. Nucleic acid test (NAT)-based detection methods have been extensively studied and applied due to their high specificity and rapid turnaround time. However, most NAT-based detection systems cannot achieve ideal sensitivity or short assay times without efficient sample pretreatment. Although reviews have individually addressed methods for nucleic acid (NA) extraction and methods for increasing the concentration of foodborne bacteria at low bacterial loads such as pre-enrichment and pre-concentration, a comprehensive review that compiles and critically analyzes all pretreatment steps as an integrated process has not yet been reported. This review summarizes key considerations and advances in all pretreatment stages, including sample preparation, enhancement of bacterial abundance, and NA extraction. Particular emphasis is placed on the compatibility and potential integration of each pretreatment steps and with NAT, while critically addressing practical challenges that are often overlooked. The evaluations presented in this review aim to enable the effective application of NAT for the detection of foodborne bacteria and to facilitate the development of fully automated workflows and field-deployable diagnostic systems.

Extreme heat events are rising in frequency and duration and can have a significant impact on fetal growth and pregnancy outcomes. This review provides strong evidence that links heat stress during pregnancy and/or lactation in mammals will impair the maternal gut, immune response, hormone balance, placenta function and morphology, and alter fetal growth and birth outcomes. In addition, there are also effects to lactation and postnatally, including a change in milk production and composition, and alterations to offspring's gut, immune response, muscle, and body composition, independent of diet. In addition to the rise in extreme heat events, maternal diet composition has further effects and leads to detrimental outcomes during pregnancy and on offspring health. Yet, there are still many open questions that remain before we fully understand the mechanisms of how heat exposure during pregnancy impacts maternal and child health outcomes and how well these translate to humans. Lastly, emerging evidence supports the beneficial effects of maternal nutritional supplementation, micronutrient intake, and dietary components on maternal-child health outcomes.

Prepared aquatic foods refer to ready to eat, heat, cook, and use aquatic products. These foods are gaining popularity as a result of consumer preference for their peculiar flavor. Flavor deterioration of prepared aquatic foods directly impacts the sensory quality and consumer acceptance. Identifying the mechanisms involved in flavor development and offering strategies to regulate flavor are crucial, as the flavor of prepared aquatic foods alters under various processing and storage conditions. Microorganisms play a crucial role in flavor evolution by participating in biochemical metabolic reactions and regulating quorum sensing systems. In this review, microbial species associated with the flavor of prepared aquatic foods are summarized. The mechanisms of protein, lipid, and carbohydrate metabolism, as well as quorum sensing mediated by microorganisms in the flavor evolution of prepared aquatic foods, are also reviewed. The regulation of quorum sensing, non-thermal sterilization, antibacterial packaging, artificial intelligence colony prediction, and flavor-targeted compensation for flavor control are also discussed with current and prospective views. This review aims to provide insights into the promotion of desired flavor compounds and control of off-flavor substances in prepared aquatic foods from the perspective of metabolic mechanisms and quorum sensing in microorganisms.

Whole grains are abundant in polyphenols, phytosterols, dietary fiber β-glucan carotenoids, etc. They are highly bioavailable as intermediate metabolites processed by gut microbiota. These intermediate metabolites can enter the circulation from the gut, and then participate in the biochemical pathways that induce metabolic syndrome and improve the abnormal state of body. Metabolic syndrome is often accompanied by oxidative stress, carbonyl stress, inflammation and other abnormal states. Intermediate metabolites such as polyphenols can signal the brain. Then, under the control of the brain, it regulates the blood sugar level, blood lipid level, bile acid level, etc., and maintains the health. In this process, the brain-gut axis and liver-gut axis play a crucial part. In this review, the pathogenesis of type 2 diabetes (T2DM) mellitus, obesity, atherosclerosis and nonalcoholic liver syndrome and the role of brain-gut axis and liver-gut axis in the pathogenesis of metabolic syndrome were described in detail. The regulatory role of whole grains in these four metabolic syndromes was investigated. Dietary components have great potential for better utilization in the prevention and treatment of metabolic syndrome. The importance of a whole grain diet was explored and techniques for improving the bioavailability of functional components in whole grains were also investigated.

Wheat is a fundamental food source and drying is an important part of the process to extend storage period of wheat. Hot air drying is widely used in the wheat drying industry due to its simple system and easy operation. However, the timely incorporation of AI-driven intelligent strategies into this industry has been overlooked. This paper focuses on reviewing the recent advances of hot air drying and its integration with intelligent technologies in wheat drying. The research trends and possible limitations of applying intelligent technologies in wheat hot air drying were outlined. Different hot air-drying processes and the initial state of wheat mainly affect the product quality and energy consumption. Increasing concerns over product quality, process costs, and intelligent drying system have motivated the researchers to investigate and the industry to adopt combination technologies. Various intelligent detection technologies and clean energy sources were reported to hold great potential in advancing the wheat hot air drying industry. Future research should focus on achieving technological and equipment innovations in industrial applications through computer simulations and artificial intelligence. Research directions aimed at optimizing process parameters and enhancing product quality should also be prioritized.