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Record W2939132899 · doi:10.1021/acscentsci.9b00284

Design of Safe Nanotherapeutics for the Excretion of Excess Systemic Toxic Iron

2019· article· en· W2939132899 on OpenAlexafffund
Srinivas Abbina, Usama Abbasi, Arshdeep Gill, Kendrew Wong, Manu Thomas Kalathottukaren, Jayachandran N. Kizhakkedathu

Bibliographic record

VenueACS Central Science · 2019
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchMichael Smith Health Research BCCanada Foundation for Innovation
KeywordsExcretionChemistryDeferoxamineChelationPharmacologyBiodistributionConjugateThalassemiaDeferasiroxSpleenBiochemistryMedicineInternal medicineOrganic chemistryIn vitro

Abstract

fetched live from OpenAlex

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; Rh, 10.6 nm; cyclic ketal), exhibited the long circulation half-life (t1/2β, 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; Rh, 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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.139

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.260
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations41
Published2019
Admission routes2
Has abstractyes

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