Enhancing Iron Bioavailability with Sprinkle Food Containing Steam-Blasted and Enzymatically Hydrolyzed Soybean: A Randomized Controlled Trial in Adolescent Girls
Bibliographic record
Abstract
OBJECTIVE: This study extends prior work on soy hydrolysate by developing a sprinkle food formula and evaluating its iron bioavailability and effectiveness in improving iron status among adolescent girls over an eight-week intervention. METHOD: The soybean hydrolysate was produced through sequential steam blasting and enzymatic hydrolysis. It was characterized by its molecular weight distribution-predominantly <15 kDa-and amino acid composition, with high levels of glutamic acid, aspartic acid, and arginine, known for their iron-binding properties. A randomized controlled trial (RCT) was conducted involving 106 female adolescents, comparing serum ferritin levels before and after an eight-week intervention with either the hydrolysate-fortified or control sprinkle product. RESULT: A significant increase in serum ferritin levels was observed among participants with low baseline ferritin (<11 ng/mL) who consumed the soy-hydrolysate-fortified formula, indicating enhanced iron absorption. No significant improvement was detected in participants with normal ferritin but low hemoglobin levels, suggesting that the benefit of soy hydrolysate is more pronounced in individuals with depleted iron stores. Baseline dietary intake and serum profiles were similar between groups, indicating that the benefits observed were likely due to the bioactive properties of soy hydrolysate, especially its amino acid composition and molecular weight that support iron absorption. CONCLUSION: Fortification with hydrolyzed soybean peptides represents a promising strategy to improve iron status and reduce the risk of anemia, while the applied processing method offers an effective, value-added use of agricultural resources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".