Response to: Dietary and pharmacological factors affecting iron absorption in mice and man
Bibliographic record
Abstract
We agree with the comments of Kontoghiorghe et al. l on the effects of various dietary and pharmacological factors in iron absorption. There is no doubt that lipophilic iron compounds can be relatively efficiently absorbed by the gastrointestinal tract, while hydrophilic iron complexes are impermeable to cellular membranes. Nevertheless, even though heme shares some physicochemical similarities to other lipophilic iron-binding compounds, it is a molecule with distinct and unique biological properties. Thus, gastrointestinal absorption, 2 intracellular transport 3 and extracellular neutralization 4 of heme are mediated by specific pathways. Moreover, heme can only release iron in cells following its enzymatic degradation by heme oxygenases. s Kontoghiorghe et al. point out, and as is also demonstrated by epidemiological data, 6 iron deficiency anemia is quite common in vegetarian and malnourished populations of developing countries, but is not frequently observed in Western populations consuming heme-rich diets. Consistently, nutritional studies have suggested that heme iron is more bioavailable to humans than inorganic iron. We showed that heme is a poor dietary iron source for mice. 8 which is in line with the fact that these animals are not predators and rarely have access to hemerich sources of nutrition. We identified the rate-limiting step in the transport of luminal heme across the apical membrane of murine enterocytes. Based on these findings, we speculated that efficient heme absorption mechanisms may have evolved preferentially in carnivores and omnivores, and not in de facto vegetarian species. Future identification of the long-sought intestinal heme transporter(s) could provide experimental support to this hypothesis, if this molecule is differentially expressed in human and murine enterocytes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".