Iron transport: emerging roles in health and disease
Bibliographic record
Abstract
In the theater of cellular life, iron plays an ambiguous and yet undoubted lead role. Iron is a ubiquitous core element of the earth and plays a central role in countless biochemical pathways. It is integral to the catalysis of the redox reactions of oxidative phosphorylation in the respiratory chain, and it provides a specific binding site for oxygen in the heme binding moiety of hemoglobin, which allows oxygen transport in the blood. Its biological utility depends upon its ability to readily accept or donate electrons, interconverting between its ferric (Fe3+) and ferrous (Fe2+) forms. In contrast to these beneficial features, free iron can assume a dangerous aspect catalyzing the formation of highly reactive compounds such as cytotoxic hydroxyl radicals that cause damage to the macromolecular components of cells, including DNA and proteins, and thereby cellular destruction. The handling of iron in the body must therefore be very carefully regulated. Most environmental iron is in the Fe3+ state, which is almost insoluble at neutral pH. To overcome the virtual insolubility and potential toxicity of iron, a myriad of specialized transport systems and associated proteins have evolved to mediate regulated acquisition, transport, and storage of iron in a soluble, biologically useful, non-toxic form. We are gradually beginning to understand how these proteins individually and in concert serve to maintain cellular and whole body homeostasis of this crucial yet potentially harmful metal ion. Furthermore, studies are increasingly implicating iron and its associated transport in specific pathologies of many organs. Investigation of the transport proteins and their functions is beginning to unravel the detailed mechanisms underlying the diseases associated with iron deficiency, iron overload, and other dysfunctions of iron metabolism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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".