Ferritin does not donate its iron for haem synthesis in macrophages
Bibliographic record
Abstract
Iron is essential for all life, yet can be dangerous under certain conditions. Iron storage by the 24-subunit protein ferritin renders excess amounts of the metal non-reactive and, consequentially, ferritin is crucial for life. Although the mechanism detailing the storage of iron in ferritin has been well characterized, little is known about the fate of ferritin-stored iron and whether it can be released and reutilized for metabolic use within a single cell. Virtually nothing is known about the use of ferritin-derived iron in non-erythroid cells. We therefore attempted to answer the question of whether iron from ferritin can be used for haem synthesis in the murine macrophage cell line RAW 264.7 cells. Cells treated with ALA (5-aminolaevulinic acid; a precursor of haem synthesis) show increased haem production as determined by enhanced incorporation of transferrin-bound 59Fe into haem. However, the present study shows that, upon the addition of ALA, 59Fe from ferritin cannot be incorporated into haem. Additionally, little 59Fe is liberated from ferritin when haem synthesis is increased upon addition of ALA. In conclusion, ferritin in cultivated macrophages is not a significant source of iron for the cell's own metabolic functions.
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 | 0.001 |
| 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) | 0.000 | 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".