Novel Iron Chelators Alleviate Symptoms of Thalassemia.
Bibliographic record
Abstract
Abstract Thalassemia is a blood disorder requiring lifelong transfusions for survival. Erythrocytes accumulate toxic iron at their membranes, triggering an oxidative cascade that leads to their premature destruction. We hypothesized that removing this proximate iron compartment as a primary treatment using novel iron chelators, could prevent cell death and alleviate the need for transfusion. Novel, highly cell permeable iron chelators, pyridoxal isonicotinoyl hydrazone and pyridoxal ortho-chlorobenzoyl hydrazone (o-108) were compared to the present mainstay, desferrioxamine and deferiprone, in vitro and in vivo. Treatment of human model b-thalassemic erythrocytes with chelators resulted in significant depletion of membrane-associated iron (P < 0.002) and reduced oxidative stress, as indicated by methemoglobin levels (P < 0.01). When administered to β-thalassemic mice, iron chelators mobilized erythrocyte membrane iron (P < 0.05), reduced cellular oxidation (P < 0.03), and prolonged erythrocyte survival. Consistently, these mice showed substantial correction of hematological abnormalities (P < 0.05). A beneficial effect as early as the erythroid precursor stage, was also determined by normalized proportions of mature versus immature reticulocytes (P < 0.05). Remarkably, all four compounds reduced iron accumulation in target organs (P < 0.05). Most importantly, o-108 revealed superior activity compared to desferrioxamine, further decreasing iron in spleen and liver by ~2-fold and ~5-fold, respectively (P < 0.05). Our study demonstrates that iron chelators ameliorate thalassemia in a human and murine model, and validates their primary use as an alternative to transfusion therapy.
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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) | 0.000 | 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) | 0.001 | 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 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".