Postprandial zinc stable isotope response in human blood serum
Bibliographic record
Abstract
In recent years, considerable advances have been made in the field of medical isotope metallomics, but numerous fundamental physiological processes remain to be investigated. Past studies report that blood serum Zn concentrations decrease by between about 10 and 25%, depending on the size of meal, approximately three hours postprandially (i.e. after eating), before returning to baseline values if no meals are consumed over the following four to five hours. Nine participants were recruited for this study to investigate whether this postprandial Zn concentration decrease is accompanied by a stable isotope response. A baseline serum sample was collected from participants in the morning after overnight fasting. A 576 kcal meal was then provided and additional serum samples were taken 90 and 180 minutes post-meal to coincide with the postprandial response. Serum Zn concentrations decreased postprandially by an average of 21 ± 9% (1SD), but this was not accompanied by a change in stable Zn isotope composition (mean Δ66Zn180-minute-baseline = 0.01 ± 0.09‰, 2SD). We propose that hemodilution and the rapid, efficient postprandial transfer of albumin-bound Zn from serum to the liver and pancreas is responsible for the lack of postprandial serum Zn isotopic response. These results indicate that studies examining solely the distribution of Zn isotopes in serum may obtain samples without considering timing of the most recent meal. However, future studies seeking to compare serum Zn concentrations with δ66Zn values should draw blood samples in the morning after overnight fasting.
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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".