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Dietary Connections01:23

Dietary Connections

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In biological systems, most metabolic pathways are interconnected. The cellular respiration processes that convert glucose to ATP—such as glycolysis, pyruvate oxidation, and the citric acid cycle—tie into those that break down other organic compounds. As a result, various foods—from apples to cheese to guacamole—end up as ATP. In addition to carbohydrates, food also contains proteins and lipids—such as cholesterol and fats. All of these organic compounds are used...
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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Protein digestion begins in the stomach, where the highly acidic environment can easily disrupt protein structure by exposing the peptide bonds of polypeptide chains. After polypeptide chains are broken into individual amino acids by a series of digestive enzymes, the amino acids are transported to the liver via the bloodstream to produce energy.
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Correction: Pramesthi et al. Evaluating the Impact of Indonesia's National School Feeding Program (ProGAS) on Children's Nutrition and Learning Environment: A Mixed-Methods Approach. <i>Nutrients</i> 2025, <i>17</i>, 3575.

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PROTEIN AI Advisor: A Knowledge-Based Recommendation Framework Using Expert-Validated Meals for Healthy Diets.

Kiriakos Stefanidis1, Dorothea Tsatsou1, Dimitrios Konstantinidis1

  • 1Information Technologies Institute, Centre for Research and Technology Hellas, GR 57001 Thessaloniki, Greece.

Nutrients
|October 27, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces an AI-powered framework for personalized nutrition, offering accurate diet plans for diverse user groups. The system achieves 92% accuracy in nutrient recommendations, promoting healthier lifestyles.

Keywords:
artificial intelligencemeal plan recommendationsontologypersonalized nutrition

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Area of Science:

  • Artificial Intelligence in Health
  • Nutritional Science
  • Computational Biology

Background:

  • Personalized nutrition is crucial for healthy lifestyles.
  • AI-based software applications are increasingly used for dietary guidance.
  • Existing systems may lack accuracy and personalization for specific health conditions.

Purpose of the Study:

  • To present a knowledge-based recommendation framework for personalized nutrition.
  • To develop an AI advisor offering accurate diet plans for ten distinct user groups.
  • To enhance user adherence to healthy lifestyles through tailored meal suggestions.

Main Methods:

  • A novel architecture with qualitative (ingredient verification) and quantitative (meal plan synthesis) layers.
  • An expert system using fuzzy inference and a nutrition ontology for ingredient appropriateness.
  • An optimization method for generating daily meal plans based on target nutrient values.

Main Results:

  • High precision and recall in recommending appropriate ingredients across user categories.
  • A total recommendation accuracy of 92% for nutrient recommendations in meal plans.
  • Demonstrated effectiveness in meal appropriateness, meal plan appropriateness, and meal variety.

Conclusions:

  • The AI-based framework provides highly accurate and personalized nutrition recommendations.
  • The system effectively supports both healthy individuals and those with health conditions.
  • This approach advances the application of AI in promoting healthier eating habits.