IAFNS is committed to sharing the results of the research we support, regardless of the outcomes. Our publications undergo stringent peer-review by qualified experts prior to publication and include disclosure of all sources of funding.
Fat Intake Modifies the Association between Restricted Carbohydrate Diets and Prevalent Cardiometabolic Diseases among Adults in the United States: National Health and Nutrition Examination Survey, 1999–2018
Current Developments in Nutrition, 2023
Flavan-3-ols and Cardiometabolic Health: First Ever Dietary Bioactive Guideline
Advances in Nutrition, 2023
Dietary bioactives are food substances that promote health but lack quantified intake recommendations because they are not characterized as essential to prevent well characterized deficiency conditions. A newly released guideline by the Academy of Nutrition and Dietetics recommends the quantity of flavan-3-ols to help adults maintain cardiovascular health. The recommendation translates evidence from a comprehensive systematic evidence review by Raman et al. using the AND guideline development process and applying a recently released (ASN endorsed) framework for developing recommended intakes of bioactive substances. The quantified recommended intake of flavan-3-ols to promote cardiovascular health is the culmination of grants provided by IAFNS to support the evidence review, framework development, and finally the independent AND guideline development process and publication. Please contact IAFNS if your professional health organization is interested in translating evidence for additional dietary bioactives.
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Diet-Related and Gut-Derived Metabolites and Health Outcomes: A Scoping Review.
Metabolites, 2022
A scoping review to map evidence about the health impact of gut microbiota-derived metabolites is now available. The researchers found a need to conduct more prospective studies, including clinical trials. Researchers identified metabolites and conditions for which systematic reviews are warranted to characterize the direction and magnitude of metabolite-disease associations.
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Machine-Learning-Based Predictions of Polymer and Postconsumer Recycled Polymer Properties: A Comprehensive Review
ACS Applied Materials and Interfaces, 2022
Machine learning (ML) algorithms are gaining attention as cost-effective scalable solutions to exploit the physical and chemical structures of polymers. The basic steps for applying ML in polymer science such as fingerprinting, algorithms, open-source databases, representations, and polymer design are outlined in this review.
Expanding Plastics Recycling Technologies: Chemical Aspects, Technology Status and Challenges
Green Chemistry, 2022
Chemists and chemical engineers need to understand the fundamentals of emerging technologies to design improved systems for chemical recycling and upcycling of waste plastics given that less than 10 percent of plastics globally are recycled.