Design of Safe Nanotherapeutics for the Excretion of Excess Systemic Toxic Iron
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Chronic transfusion of red blood cells (RBCs) to patients with β-thalassemia, sickle cell disease, and other acquired anemic disorders generates significant amounts of bioactive iron deposits in the body. The inactivation and excretion of redox active iron(III) from the blood pool and organs are critical to prevent organ damage, and are the focus of iron chelation therapy (ICT) using low molecular weight Fe(III) specific chelators. However, the current ICT is suboptimal because of the short circulation time of chelators, toxicity, severe side effects, difficult regime of administration, and patient noncompliance. To address this issue, we have designed long circulating and biodegradable nanoconjugates with enhanced circulation time and well-defined biodegradability to improve iron excretion and avoid nonspecific organ accumulation. A series of iron chelating nanoconjugates were generated with deferoxamine (DFO) as the iron(III) specific chelator using polymer scaffolds containing structurally different acidic pH sensitive ketal groups. The type of degradation linkages used in the polymer scaffold significantly influenced the vascular residence time, biodistribution, and mode of excretion of chelators in mice. Remarkably, the conjugate, BGD-60 (140 kDa; R h, 10.6 nm; cyclic ketal), exhibited the long circulation half-life ( t 1/2β, 64 h), a 768-fold increase compared to DFO, and showed minimal polymer accumulation in major organs. The nanoconjugates were found to be nontoxic and excreted iron significantly better than DFO in iron overloaded mice. BGD-60 showed greater iron mobilization from plasma ( p = 0.0390), spleen ( p < 0.0001), and pancreas ( p < 0.0001) whereas BDD-200 (340 kDa; R h, 13.7 nm; linear ketal) mobilized iron significantly better from the spleen, liver, and pancreas ( p < 0.0001, p < 0.0001, and p < 0.0001, respectively) compared to DFO at equivalent doses. The nanoconjugate’s favorable long blood circulation time, biodegradability, and iron excretion profiles highlight their potential for future clinical translation.
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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) | 0.000 | 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 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".