Total zinc absorption in young women, but not fractional zinc absorption, differs between vegetarian and meat-based diets with equal phytic acid content
Bibliographic record
Abstract
Zn bioavailability is often lower in vegetarian diets mainly due to low Zn and high phytic acid contents. The objective of the present study was to determine the fractional and total absorption of Zn from a vegetarian diet in comparison with meat diets with equal concentrations of phytic acid. A randomized cross-over design, comprising three whole-day diet periods of 5 d each, with a vegetarian diet or diets containing Polish-produced meat or Danish-produced meat, was conducted. Twelve healthy female subjects completed the study. All diets had a high content of phytic acid (1250 micromol/d) and in the meat diets the main meals contained 60 g pork meat. All main meals were extrinsically labelled with the radioactive isotope 65Zn and absorption of Zn was measured in a whole-body counter. The mean Zn content of the whole-day diet was: Polish meat diet 9.9 (SE 0.14) mg, Danish meat diet 9.4 (SE 0.19) mg and vegetarian diet 7.5 (SE 0.18) mg. No difference was observed in the fractional absorption of Zn (Polish meat diet: 27 (SE 1.2) %, Danish meat diet: 27 (SE 1.9) % and vegetarian diet: 23 (SE 2.6) %). A significantly lower amount of total Zn was absorbed from the vegetarian diet (mean Zn absorption of Polish meat diet: 2.7 (SE 0.12) mg/d (P<0.001), Danish meat diet: 2.6 (SE 0.17) mg/d (P=0.006) and vegetarian diet: 1.8 (SE 0.20) mg/d). In conclusion, the vegetarian diet compared with the meat-based diets resulted in lower amounts of absorbed Zn due to a higher content of Zn in the meat diets, but no difference was observed in the fractional absorption of Zn.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".