ArticleFoods (Basel, Switzerland)2020
An Artificial Intelligence Characterised Functional Ingredient, Derived from Rice, Inhibits TNF-α and Significantly Improves Physical Strength in an Inflammaging Population.
Article in Foods (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 19 citations in OpenAlex.
- Improved Strength Recovery and Reduced Fatigue with Suppressed Plasma Myostatin Following Supplementation of aNutrients · 2023Trial
- An Artificial-Intelligence-Discovered Functional Ingredient, NRT_N0G5IJ, Derived fromNutrients · 2021Trial
- High-Value Transformation of Rice-Derived Bioactive Peptides for Multiscenario Applications: From AI-Aided Design to Molecular Modification.International journal of food science · 2026Review
- A review on the role of functional foods and derivatives for diabetes management.Journal of food science and technology · 2025Review
- Bioactive compounds for human and planetary health.Frontiers in nutrition · 2023Review
- Prediction, Discovery, and Characterization of Plant- and Food-Derived Health-Beneficial Bioactive Peptides.Nutrients · 2022Review
- Proteomics Characterization of Food-Derived Bioactive Peptides with Anti-Allergic and Anti-Inflammatory Properties.Nutrients · 2022Review
- A comprehensive review on the glucoregulatory properties of food-derived bioactive peptides.Food chemistry: X · 2022Article
- Potential Nutrients from Natural and Synthetic Sources Targeting Inflammaging-A Review of Literature, Clinical Data and Patents.Nutrients · 2021Review
- Preservatives from food-For food: Pea protein hydrolysate as a novel bio-preservative againstFood science & nutrition · 2021Article
- Discovery through Machine Learning and Preclinical Validation of Novel Anti-Diabetic Peptides.Biomedicines · 2021Article
- Artificial Intelligence in Functional Food Ingredient Discovery and Characterisation: A Focus on Bioactive Plant and Food Peptides.Frontiers in genetics · 2021Review
- Characterising the efficacy and bioavailability of bioactive peptides identified for attenuating muscle atrophy within aCurrent research in food science · 2021Article
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Food-derived bioactive peptides offer great potential for the treatment and maintenance of various health conditions, including chronic inflammation. Using in vitro testing in human macrophages, a rice derived functional ingredient natural peptide network (NPN) significantly reduced Tumour Necrosis Factor (TNF)-α secretion in response to lipopolysaccharides (LPS). Using artificial intelligence (AI) to characterize rice NPNs lead to the identification of seven potentially active peptides, the presence of which was confirmed by liquid chromatography tandem mass spectrometry (LC-MS/MS). Characterization of this network revealed the constituent peptides displayed anti-inflammatory properties as predicted in vitro. The rice NPN was then tested in an elderly "inflammaging" population with a view to subjectively assess symptoms of digestive discomfort through a questionnaire. While the primary subjective endpoint was not achieved, analysis of objectively measured physiological and physical secondary readouts showed clear significant benefits on the ability to carry out physical challenges such as a chair stand test that correlated with a decrease in blood circulating TNF-α. Importantly, the changes observed were without additional exercise or specific dietary alterations. Further health benefits were reported such as significant improvement in glucose control, a decrease in serum LDL concentration, and an increase in HDL concentration; however, this was compliance dependent. Here we provide in vitro and human efficacy data for a safe immunomodulatory functional ingredient characterized by AI.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.