Calcium exacerbates the inhibitory effects of phytic acid on zinc bioavailability in rats
Bibliographic record
Abstract
BACKGROUND: Complementary feeding of breastfed infants with foods high in bioavailable zinc (Zn) can help meet physiological requirements for Zn. Some infant cereals contain high concentrations of phytic acid (PA) and calcium (Ca) that may reduce absorbable Zn. OBJECTIVES: This study measured PA, Zn and Ca concentrations in selected infant cereals sold in Canada and investigated the effects of dietary PA and Ca at concentrations present in infant cereals on Zn bioavailability in rats. METHODS AND RESULTS: Male Sprague-Dawley rats (36-day old) were fed a control diet containing normal Zn (29.1 mg/kg) and Ca (4.95 g/kg) or six test diets (n = 12/diet group). Test diets were low in Zn (8.91-9.74 mg/kg) and contained low (2.16-2.17 g/kg), normal (5.00-5.11 g/kg) or high (14.6-14.9 g/kg) Ca without or with added PA (8 g/kg). After 2 weeks, rats were killed and Zn status of the rats was assessed. PA, Zn and Ca concentrations in infant cereals (n = 20) differed widely. PA concentrations ranged from undetectable to 16.0 g/kg. Zn and Ca concentrations ranged from 7.0-29.1 mg/kg and 0.8-13.4 g/kg, respectively. The [PA]/[Zn] and [PA × Ca]/[Zn] molar ratios in infants cereals with detectable PA (16 of 20 cereals) ranged from 22-75 and 0.9-14.9 mol/kg, respectively, predicting low Zn bioavailability. Body weight, body composition (lean and fat mass), right femur weight and length measurements and Zn concentrations in serum and femur indicated that diets higher in Ca had a more pronounced negative effect on Zn status of rats fed a PA-supplemented diet. Addition of PA to the diet had a greater negative effect on Zn status when Ca concentration in the diet was higher. CONCLUSION: These results show that, in rats, higher concentrations of dietary Ca and PA interact to potentiate a decrease in bioavailable Zn and may suggest lower Zn bioavailability in infant cereals with higher PA and Ca concentrations.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".