Iron trafficking in the mitochondrion: novel pathways revealed by disease
Bibliographic record
Abstract
It is well known that iron (Fe) is transported to the mitochondrion for heme synthesis. However, only recently has the importance of this organelle for many other facets of Fe metabolism become widely appreciated. Indeed, this was stimulated by the description of human disease states that implicate mitochondrial Fe metabolism. In particular, studies assessing various diseases leading to mitochondrial Fe loading have produced intriguing findings. For instance, the disease X-linked sideroblastic anemia with ataxia (XLSA/A) is due to a mutation in the ATP-binding cassette protein B7 (ABCB7) transporter that is thought to transfer [Fe-S] clusters from the mitochondrion to the cytoplasm. This and numerous other findings suggest the mitochondrion is a dynamo of Fe metabolism, being vital not only for heme synthesis but also for playing a critical role in the genesis of [Fe-S] clusters. Studies examining the disease Friedreich ataxia have suggested that a mutation in the gene encoding frataxin leads to mitochondrial Fe loading. Apart from these findings, the recently discovered mitochondrial ferritin that may store Fe in ring sideroblasts could also regulate the level of Fe needed for heme and [Fe-S] cluster synthesis. In this review, we suggest a model of mitochondrial Fe processing that may account for the pathology observed in these disease states.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".