Potential of Food Hydrolyzed Proteins and Peptides to Chelate Iron or Calcium and Enhance their Absorption
Bibliographic record
Abstract
Iron and calcium are two essential micronutrients that have strong effects on nutrition and human health because of their involvement in several biological and redox processes. Iron is responsible for electron and oxygen transport, cell respiration, and gene expression, whereas calcium is responsible for intracellular metabolism, muscle contraction, cardiac function, and cell proliferation. The bioavailability of these nutrients in the body is dependent on enhancers and inhibitors, some of which are found in consumed foods. Hydrolyzed proteins and peptides from food proteins can bind these essential minerals in the body and facilitate their absorption and bioavailability. The binding is also important because excess free iron will increase oxidative stress and the risks of developing chronic diseases. This paper provides an overview of the function of calcium and iron, and strategies to enhance their absorption with an emphasis on hydrolyzed proteins and peptides from foods. It also discusses the relationship between the structure of peptides and their potential to act as transition metal ligands.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".