Hasil untuk "Nutrition. Foods and food supply"

M. Mahler

R. Cassada, R. Russell

Samuel Mezemir Yimenu

Junwei Wu, Runze Yan, Hanqi Luo et al.

Personalized nutrition intervention for patients with multimorbidity is critical for improving health outcomes, yet remains challenging because it requires the simultaneous integration of heterogeneous clinical conditions, medications, and dietary guidelines. Single-agent large language models (LLMs) often suffer from context overload and attention dilution when processing such high-dimensional patient profiles. We introduce NutriOrion, a hierarchical multi-agent framework with a parallel-then-sequential reasoning topology. NutriOrion decomposes nutrition planning into specialized domain agents with isolated contexts to mitigate anchoring bias, followed by a conditional refinement stage. The framework includes a multi-objective prioritization algorithm to resolve conflicting dietary requirements and a safety constraint mechanism that injects pharmacological contraindications as hard negative constraints during synthesis, ensuring clinical validity by construction rather than post-hoc filtering. For clinical interoperability, NutriOrion maps synthesized insights into the ADIME standard and FHIR R4 resources. Evaluated on 330 stroke patients with multimorbidity, NutriOrion outperforms multiple baselines, including GPT-4.1 and alternative multi-agent architectures. It achieves a 12.1 percent drug-food interaction violation rate, demonstrates strong personalization with negative correlations (-0.26 to -0.35) between patient biomarkers and recommended risk nutrients, and yields clinically meaningful dietary improvements, including a 167 percent increase in fiber and a 27 percent increase in potassium, alongside reductions in sodium (9 percent) and sugars (12 percent).

Boyu Chen, Tai Guo, Weiyu Cui et al.

Multimodal retrieval models are becoming increasingly important in scenarios such as food delivery, where rich multimodal features can meet diverse user needs and enable precise retrieval. Mainstream approaches typically employ a dual-tower architecture between queries and items, and perform joint optimization of intra-tower and inter-tower tasks. However, we observe that joint optimization often leads to certain modalities dominating the training process, while other modalities are neglected. In addition, inconsistent training speeds across modalities can easily result in the one-epoch problem. To address these challenges, we propose a staged pretraining strategy, which guides the model to focus on specialized tasks at each stage, enabling it to effectively attend to and utilize multimodal features, and allowing flexible control over the training process at each stage to avoid the one-epoch problem. Furthermore, to better utilize the semantic IDs that compress high-dimensional multimodal embeddings, we design both generative and discriminative tasks to help the model understand the associations between SIDs, queries, and item features, thereby improving overall performance. Extensive experiments on large-scale real-world Meituan data demonstrate that our method achieves improvements of 3.80%, 2.64%, and 2.17% on R@5, R@10, and R@20, and 5.10%, 4.22%, and 2.09% on N@5, N@10, and N@20 compared to mainstream baselines. Online A/B testing on the Meituan platform shows that our approach achieves a 1.12% increase in revenue and a 1.02% increase in click-through rate, validating the effectiveness and superiority of our method in practical applications.

Xinwei Ji, Lixin Wang, Pengbo Luan et al.

ObjectiveThis study aimed to evaluate the impact of enteral nutrition with dietary fiber on patients undergoing laparoscopic colorectal cancer (CRC) surgery.MethodsBetween January 2023 and August 2024, 164 CRC patients were randomly assigned to two groups at our hospital. The control group received standard nutritional intervention, while the observation group received enteral nutritional support containing dietary fiber. Both groups were subjected to intervention and continuously observed until the 14th postoperative day. An observational analysis assessed the impact of dietary fiber intake on postoperative nutritional status in CRC patients. The study compared infection stress index, inflammatory factors, nutritional status, intestinal function recovery, and complication incidence between groups. Additionally, four machine learning models—Logistic Regression (LR), Random Forest (RF), Neural Network (NN), and Support Vector Machine (SVM)—were developed based on nutritional and clinical indicators.ResultsIn the observation group, levels of procalcitonin (PCT), beta-endorphin (β-EP), C-reactive protein (CRP), interleukin-1 (IL-1), interleukin-8 (IL-8), and tumor necrosis factor-alpha (TNF-α) were significantly lower compared to the control group (p < 0.01). Conversely, levels of albumin (ALB), hemoglobin (HB), transferrin (TRF), and prealbumin (PAB) in the observation group were significantly higher than those in the control group (p < 0.01). Furthermore, LR, RF, NN, and SVM models can effectively predict the effects of dietary fiber on the immune function and inflammatory response of postoperative CRC patients, with the NN model performing the best. Through the screening of machine learning models, four key predictors for CRC patients were identified: PCT, PAB, ALB, and IL-1.ConclusionPostoperative dietary fiber administration in colorectal cancer enhances immune function, reduces disease-related inflammation, and inhibits tumor proliferation. Machine learning-based CRC prediction models hold clinical value.

Mohamed Trigui, Houda Baati, Francesco Montemurro et al.

Lucas Krusinski, Chloe Castanon, Rosalee S. Hellberg et al.

ABSTRACT The objective of this study was to use a multi‐omics (i.e., gene expression quantification, metabolomics, and fatty acid [FA] profiling) approach to separate and authenticate beef from three different dietary groups. In this 2‐year study, Red Angus steers (n = 54) were randomly allocated to one of three treatments: (1) complex biodiverse pasture (GRASS), (2) total mixed ration (TMR) in feedlot (GRAIN), or (3) TMR in feedlot supplemented with 5% (dry matter) grapeseed extract for the last 30 days (GRAPE). FAs were measured by gas chromatography‐mass spectrometry (GC–MS), secondary metabolites were identified using ultra‐high‐performance liquid chromatography tandem mass spectrometry (UPLC–MS/MS), and gene expression analysis was performed using quantitative reverse transcription polymerase chain reaction (RT–qPCR). All target genes were upregulated in beef from GRASS compared to the other two groups. Multivariate analyses showed that long‐chain n‐3 polyunsaturated FAs, the n‐6:n‐3 ratio, vitamin E, organic acids, amino acid derivatives, and the nephronectin isoform X1 (NPNT‐1) gene were the most important compounds for group separation. These compounds, considered to be beneficial for human health, showed higher concentrations in beef from GRASS. The success of beef separation by dietary treatment was highlighted by the 90.4% prediction accuracy of the random forest model, with beef from GRASS being 100% accurately predicted and beef from GRAPE being 94.4% accurately predicted. Beef from GRAIN was 76.5% accurately predicted. In conclusion, coupling gene expression analysis to metabolomics and FA profiling allowed for the separation of beef samples from varying dietary backgrounds with a high degree of confidence.

Yamamoto M, Yamamoto K, Takano-Ohmuro H et al.

Michiko Yamamoto,1,* Ken Yamamoto,2,* Hiromi Takano-Ohmuro,3 Rain Yamamoto,4 Junji Saruwatari1 1Graduate School of Pharmaceutical Sciences, Kumamoto University, Kumamoto-city, Kumamoto, Japan; 2Showa Pharmaceutical University, Machida-city, Tokyo, Japan; 3Faculty of Pharmacy, Musashino University, Nishitokyo-city, Tokyo, Japan; 4Faculty of Pharmacy, Keio University, Minato-ku, Tokyo, Japan*These authors contributed equally to this workCorrespondence: Michiko Yamamoto, Graduate School of Pharmaceutical Sciences, Kumamoto University, 5-1 Oehonmachi, Chuo-ku, Kumamoto-city, Kumamoto, Japan, Email m-yamamoto@kumamoto-u.ac.jpPurpose: The saturation of health foods in the market is coupled with inadequate information on their safe usage. Recently, health issues caused by Foods with Function Claims (FFCs) have resulted in 81 suspected deaths in Japan, where labelling precautions proved ineffective. We previously developed a Communication Index to assess usability and comprehension of FFC labelling from the perspective of healthcare professionals (HCPs). It is important to explore ways to evaluate and improve labelling usability from the consumers’ perspective to ensure safe usage.Patients and Methods: We conducted user testing from the consumers’ perspective on labels of five different FFCs, utilizing semi-structured interviews with 50 participants of diverse ages and sexes. Two levels of passing criteria were established for accessibility to correct answers: ≥ 90% of all questions within 1 min and 2 min. After the user testing, we qualitatively analyzed the participants’ feedback. Furthermore, we created a revised version of labels, which participants then evaluated against the current version using a 5-point scale.Results: Only one FFC label met the acceptance criteria within 2 min, while none did so within 1 min. The response rate for questions critical to safe use was particularly low, averaging around 70%. Participants’ feedback revealed lack of familiarity with FFCs, suggesting that the terms and text on the labels were often confusing and overly technical.Conclusion: We demonstrated that FFC label assessments from users’ perspective did not meet the passing criteria. User testing offered valuable insights into how FFC labelling can be improved to ensure safer and more appropriate use by aligning with users’ understanding and perceptions. For the first time, we developed a framework that integrates evaluations from both users and HCPs, highlighting the challenges and potential improvements with the FFC label as a source of health information.Keywords: health literacy, food with health claims, safety use, semi-structured interview, risk communication

Rushikesh Ubale, Yasar Mulani, Abhay Suresh et al.

Multi-period stock-keeping unit (SKU) allocation in supply chains is a combinatorial optimization problem that is both NP-hard and operationally critical, requiring simultaneous attention to profitability, feasibility, and diversity. Quadratic unconstrained binary optimization (QUBO) provides a principled framework for such tasks, yet prior studies often rely on simplified assumptions or omit real operational constraints. This work proposes a hybrid QUBO framework integrating three advances: (i) a quantum-derived similarity kernel, obtained from a variational RX embedding, to discourage redundant SKU selections; (ii) exact per-period capacity enforcement via slack-bit encoding to maintain feasibility; and (iii) execution on a time-multiplexed Coherent Ising Machine (CIM) benchmarked against simulated quantum annealing (SQA) and classical optimization algorithms. The resulting model, with over one million quadratic terms and about 4,100 variables, captures profit, risk, and capacity interactions within a unified formulation. On a dataset of 500 SKUs across eight planning periods, Quanfluence's CIM achieved an energy of minus 2.95 times 10 to the power of 16, producing robust solutions with 288 distinct SKUs (approximately 60 percent of the catalog), 226,813 allocated units, and 12.75 million dollars profit, all with zero capacity violations. These results demonstrate that hybrid quantum-classical QUBO methods can deliver feasible and profitable supply-chain allocations at an industrial scale.

Nirmal Gelal, Aastha Gautam, Sanaz Saki Norouzi et al.

Sustainable agricultural production aligns with several sustainability goals established by the United Nations (UN). However, there is a lack of studies that comprehensively examine sustainable agricultural practices across various products and production methods. Such research could provide valuable insights into the diverse factors influencing the sustainability of specific crops and produce while also identifying practices and conditions that are universally applicable to all forms of agricultural production. While this research might help us better understand sustainability, the community would still need a consistent set of vocabularies. These consistent vocabularies, which represent the underlying datasets, can then be stored in a global food systems datahub. The standardized vocabularies might help encode important information for further statistical analyses and AI/ML approaches in the datasets, resulting in the research targeting sustainable agricultural production. A structured method of representing information in sustainability, especially for wheat production, is currently unavailable. In an attempt to address this gap, we are building a set of ontologies and Knowledge Graphs (KGs) that encode knowledge associated with sustainable wheat production using formal logic. The data for this set of knowledge graphs are collected from public data sources, experimental results collected at our experiments at Kansas State University, and a Sustainability Workshop that we organized earlier in the year, which helped us collect input from different stakeholders throughout the value chain of wheat. The modeling of the ontology (i.e., the schema) for the Knowledge Graph has been in progress with the help of our domain experts, following a modular structure using KNARM methodology. In this paper, we will present our preliminary results and schemas of our Knowledge Graph and ontologies.

Wei Meng

This study constructs a quantifiable modelling framework to simulate non-kinetic strategic deterrence pathways in rare earth supply disruption scenarios, based on structured responses from expert interviews led by Dr. Daniel O'Connor, CEO of the Rare Earth Exchange (REE). Focusing on disruption impacts on national security systems, the study proposes four core modelling components: Security Critical Zones (SCZ), Strategic Signal Injection Function (SSIF), System-Capability Migration Function (SCIF), and Policy-Capability Transfer Function (PCTF). The framework integrates parametric ODEs, segmented function modelling, path-overlapping covariance matrices, and LSTM networks to simulate nonlinear suppression trajectories triggered by regime signals. Data is derived from expert interviews and scenario analyses centered on U.S.-China dynamics in ISR, electronic warfare, and rare earth control. Results show institutional signals have strong tempo and path-coupling effects, capable of causing rapid degradation of strategic capabilities. The model is adaptable across national resource frameworks and extendable to AI sandbox engines for situational simulation and counterfactual reasoning. This research introduces the first unified system for modelling, visualizing, and forecasting non-kinetic deterrence, offering methodological support to policymakers and analysts navigating institutionalized strategic competition.

Shabnam Hassani, Mehrdad Sabetzadeh, Daniel Amyot

Context: Laws and regulations increasingly shape software design, development, and quality assurance in regulated domains. Because legal provisions are written in technology-neutral language, deriving concrete specifications, requirements, and acceptance criteria to verify software compliance is difficult and error-prone. Recent advances in generative AI, especially large language models (LLMs), may help automate this process. Objective: We present the first systematic human-subject evaluation of LLMs' ability to derive Gherkin behavioural specifications from legal texts using a quasi-experimental design. Gherkin is a domain-specific language for scenario-based system behaviour descriptions in Given-When-Then form and is well suited to automation in software development. Methods: Ten participants evaluated 60 Gherkin specifications generated from food-safety regulations by Claude and Llama. Each participant assessed 12 specifications across five criteria: relevance, clarity, completeness, singularity, and time savings. Each specification was evaluated by two participants, yielding 120 assessments with quantitative ratings and qualitative feedback. Results: Ratings were uniformly high in the top two categories: relevance 95%, clarity 100%, completeness 94.2%, singularity 93.4%, and time savings 91.7%. No statistically reliable differences were found across participants or between LLMs. Qualitative feedback noted occasional omissions, hallucinations, and mixed intents, underscoring the need for human oversight, especially in safety-critical domains. Conclusion: In food safety, LLMs can assist in deriving Gherkin specifications from legal texts, but omissions and hallucinations require systematic human review.

Francesco Salvi, Giuseppe Russo, Adam Barla et al.

Meat consumption is a major driver of global greenhouse gas emissions. While pricing interventions have shown potential to reduce meat intake, previous studies have focused on highly constrained environments with limited consumer choice. Here, we present the first large-scale field experiment to evaluate multiple pricing interventions in a real-world, competitive setting. Using a sequential crossover design with matched menus in a Swiss university campus, we systematically compared vegetarian-meal discounts (-2.5 CHF), meat surcharges (+2.5 CHF), and a combined scheme (-1.2 CHF=+1.2 CHF) across four campus cafeterias. Only the surcharge and combined interventions led to significant increases in vegetarian meal uptake--by 26.4% and 16.6%, respectively--and reduced CO2 emissions per meal by 7.4% and 11.3%, respectively. The surcharge, while effective, triggered a 12.3% drop in sales at intervention sites and a corresponding 14.9% increase in non-treated locations, hence causing a spillover effect that completely offset environmental gains. In contrast, the combined approach achieved meaningful emission reductions without significant effects on overall sales or revenue, making it both effective and economically viable. Notably, pricing interventions were equally effective for both vegetarian-leaning customers and habitual meat-eaters, stimulating change even within entrenched dietary habits. Our results show that balanced pricing strategies can reduce the carbon footprint of realistic food environments, but require coordinated implementation to maximize climate benefits and avoid unintended spillover effects.

Asmaa Hussein Zaki, Hanaa Salem Saleh Gazwi, Moaz Mohamed Hamed et al.

The study explores the potential of orange peel extract (OPE) as a versatile natural resource, focusing on its phenolic composition, antioxidant, and antibacterial properties, as well as its application in fortifying yogurt. Analysis revealed significant concentrations of phenolic compounds in OPE. OPE exhibited notable antibacterial efficacy against pathogenic bacteria, particularly marine Escherichia coli, with synergistic effects observed when combined with Amikacin. Incorporating OPE into yogurt led to changes in chemical composition, enhancing total proteins, fat, and ash content. Fortified yogurt showed increased antioxidant activity and potential anti-cancer properties against HCT116 cell lines. In conclusion, OPE emerges as a rich source of bioactive compounds with diverse applications, from its antioxidant and antibacterial properties to its potential in fortifying functional foods like yogurt. This comprehensive exploration provides valuable insights into the multifaceted benefits of OPE, paving the way for its utilization in various industries and health-related applications.

Dan-Cristian Dabija, Cristina-Bianca Pocol, Pompei Mititean et al.

The need to use innovative packaging (active or intelligent) that extends food shelf-life and promotes sustainable production and consumption systems has become a global priority. In this context, the current research explores the consumer’s buying experience regarding food actively packed with biopolymer films. The research used a questionnaire targeting potential customers for food packed with a protein-based active film. A conceptual model was created to investigate the dependency relations between the following concepts: “superior functional packaging,” “affordable packaging,” “aesthetic packaging,” “nutritional value,” ,”spoilage prevention packaging,” “buying experience for food packed with biopolymer films,” “experiential consumption” and “informative health packaging.” The research demonstrates that affordable pricing, appealing aesthetics, functional attributes and shelf-life extension are significant elements of biopolymer films for active packaging. It validates that these incentives significantly enhance consumer awareness, shaping their experience, preference and proactive search for products packed with such materials in stores. Using biopolymer films for active packaging of foods will have social, environmental and economic benefits, both for producers and consumers.

Jong-Seok Song, Sunkyung Jung

This study investigated the effect of plasma treatment on reused water and evaluated the interactions of the plasma-treated water (PTW) with plants or microbes to determine the optimal PTW for reuse. The repeated treatment gradually accumulated nitrate (NO3−) in the PTW and lowered its pH; afterward, it led to the sprouted soybeans accumulating other inorganic ions in the PTW. The biomass of soybean sprouts was enhanced by the accumulated NO3− but decreased due to the pH effect. Meanwhile, the acidic pH reduced the microbial counts, but they increased after sprinkling the PTW over the sprouts. The optimal PTW in our study, which had a gradual increase of NO3− (≤321.8 mg·L−1) with an acceptable pH (≥pH 3), significantly enhanced the biomass by 4.2% compared to the untreated control. Additionally, it increased the total content of amino acids and isoflavones by 9% and 18% in the growing part, respectively.

Vanessa Nunes Leal, Tiago do Prado Paim, Darliane de Castro Santos et al.

Integrated crop-livestock systems play a crucial hole on sustainable intensification due simultaneous increase the land use efficiency and minimize nutrient leaching due an intensification of nutrient cycling. However, these benefits depend on a good planning and management of the production system. The main objective of this study was to investigate biomass composition, soybean yield and beef cattle performance using three distinct forage cultivars within two cropping systems: Integrated Crop-Livestock System (ICLS) and the Pure Crop System (CS). The three forage cultivars used were: Urochloa ruziziensis, Urochloa brizantha cv. Xaraés, and Megathyrsus maximus cv. BRS Quênia. The experimental area was split into 24 plots, with each plot assigned one of the cropping systems and a specific forage cultivar. The ICLS involved soybean cultivation during spring-summer followed by cattle grazing during the autumn-winter. Conversely, the CS functioned as a pure crop system, utilizing soybean cultivation alongside forage as a cover crop. Soybean yield did not differ between ICLS and CS, neither between forage cultivars (4110 ± 627.0 kg ha−1). Animal performance did not differ between forage cultivars, resulting in average daily gain equals to 0.538 ± 0.316 kg of BW day−1. Animal production per area also was not affected by forage cultivars, yielding 145.0 ± 56.8 kg of BW ha−1. For comparison between systems, beef cattle production was converted in soybean equivalent based on commodities values. ICLS proportionated an increment of 624 ± 135 kg ha−1 per year of soybean equivalent yield, representing 15% increase in land use efficiency compared to the CS system. Therefore, beef cattle grazing in off-season of cash crops can enhance the sustainable intensification of food production. The forage species choice seems not be a paramount question for this model of ICLS.

Sureka Bhola, Eleanor M. Cave, Katherine L. Prigge et al.

Polymorphisms in the vitamin D receptor (VDR) gene (BsmI (rs1544410), FokI (rs2228570), ApaI (rs7975232), TaqI (rs731236)) and low vitamin D concentrations have previously been associated with type 1 diabetes (T1D). Vitamin D is thought to mediate the switch from a pro-inflammatory Th1 response to an anti-inflammatory Th2 response which is protective against the development of T1D. These associations are inconsistent across studies and population groups. These associations have not been investigated in the South African black population. Thus, this observational, case-control study aims to address this knowledge gap. South African black participants with T1D (cases; n = 182) and healthy controls (n = 151) were genotyped for the four VDR polymorphisms using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Vitamin D levels were measured using high performance liquid chromatography (HPLC). Vitamin D levels were not significantly different between cases and controls (62.8 ± 20.7 vs. 59.5 ± 17.0 nmol/l, respectively; P = 0.122). Higher vitamin D levels were associated with the TaqI TT (P = 0.045) and FokI TT/TC (P = 0.014) genotypes in multivariate analyses. Furthermore, the TaqI TT genotype was associated with T1D status in multivariate analysis (P = 0.040). The FokI CC genotype increases the transcription of CYP24A1, resulting in vitamin D catabolism and thus decreased vitamin D concentration through the action of 24-hydroxlase. The TaqI TT genotype results in increased vitamin D potentially through calcium metabolism feedback pathways. In addition, the TaqI TT genotype is associated with T1D through a vitamin D-independent mechanism and may be in linkage disequilibrium with a true causative variant.

Xin Yin, Zhentao Ren, Ruizong Jia et al.

Wild soybeans retain many substances significantly reduced or lost in cultivars during domestication. This study utilized LC-MS to analyze metabolites in the seed coats and embryos of wild and cultivated soybeans. 866 and 815 metabolites were identified in the seed extracts of both soybean types, with 35 and 10 significantly differing metabolites in the seed coat and embryos, respectively. The upregulated metabolites in wild soybeans are linked to plant defense, stress responses, and nitrogen cycling. MALDI-MSI results further elucidated the distribution of these differential metabolites in the cotyledons, hypocotyls, and radicles. In addition to their role in physiological processes like growth and response to environmental stimuli, the prevalent terpenoids, lipids, and flavonoids present in wild soybeans exhibit beneficial bioactivities, including anti-inflammatory, antibacterial, anticancer, and cardiovascular disease prevention properties. These findings underscore the potential of wild soybeans as a valuable resource for enhancing the nutritional and ecological adaptability of cultivated soybeans.