Iron Chelator Research: Past, Present, and Future
Bibliographic record
Abstract
The occurrence of in vivo iron toxicity in the human body can be categorized into iron overload and non-iron overload conditions. Iron overload conditions are common in beta-thalassemia and hereditary hemochromatosis patients, and anthracycline mediated cardiotoxicity is an example of a non-iron overload condition in cancer patients, in which the toxicity is iron-dependent. While hundreds of iron chelators have been evaluated in animal studies, only a few have been studied in humans. Examples of iron chelator drugs are desferrioxamine (DFO), deferiprone (L1), and dexrazoxane (ICRF 187). The compound ICL670 has completed phase II clinical trials and a phase III trial is planned in 2003. Triapine is currently in phase II clinical trial as an anticancer agent. CP502, GT56-252, NaHBED, and MPB0201 are examples of new chelators in preclinical/clinical development. In the past decade, many new viable utilities for iron chelators have been reported. This includes the use of iron chelators as antiviral, photoprotective, antiproliferative, and antifibrotic agents. This review will focus on the status of drug development for the treatment of iron overload in patients with beta-thalassemia and the potential use of iron chelators in the prevention and treatment of other diseases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".