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Record W2096862409

Diethylenetriaminetetrahydroxamic acid: A potential chelator for labeling antibody with Zr-89 for PET imaging

2014· article· en· W2096862409 on OpenAlexaff
Gemma Dias, Zhengxing Zhang, Joseph Lau, François Bénard, Kuo‐Shyan Lin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsOxalic acidChelationChemistryYield (engineering)YttriumElutionDeferoxamineNuclear chemistryNeutralizationHEPESRadiochemistryChromatographyInorganic chemistryAntibodyMaterials scienceBiochemistryOrganic chemistryMedicine
DOInot available

Abstract

fetched live from OpenAlex

1187 Objectives Deferoxamine, the only clinically used chelator for labeling antibody with Zr-89, shows significant in vivo demetallation. One possible reason is that the three hydroxamate groups of deferoxamine are not enough to fulfill the octadentate requirement to stably complex Zr4+. Herein, we report the preparation and evaluation of DTTH-1, a diethylenetriaminetetrahydroxamic acid derivative, as a potential Zr-89 chelator for PET imaging. Methods For Zr-89 production, an yttrium disc, 10 mm diameter with 99.9% purity was bombarded with 13.9 MeV protons for 40 min (800 μA.min). The disc was dissolved and adjusted to 2M HCl and Zr-89 was extracted by hydroxamate resin. Zr-89 was eluted off the resin with 0.5 mL 1M oxalic acid. DTTH-1 was prepared via multi-step organic synthesis. Zr-89 complexation was performed at room temperature at pH 6, 7 and 8 (HEPES buffer, 0.5 M) with 200 µM DTTH-1, and at pH 7.5 with 20 µM DTTH-1 (equivalent to 0.4 mg antibody in 0.5 mL solution with on average 4 chelators/antibody). The complexation yield was determined 1 hour and 3 days later via ITLC developed using 50 mM EDTA buffer (pH 5). Results Zr-89 yield at the end of bombardment was 696 MBq of which 453 MBq was purifed and eluted in 0.5 mL 1M oxalic acid. DTTH-1 was prepared in an overall 4% yield. The Rfs of free Zr-89 and Zr-DTTH-1 complex were 1.0 and 0, respectively. Complexation of Zr-89 with 200 µM DTTH-1 at pH 7 and 8 was very efficient (>96% at 1 h), and the complexation yield remained relatively the same after 3 days (>92%). Complexation yield at pH 6 was 73% after 1 hour, and dropped to 33% 3 days later. Complexation yield with 20 µM DTTH-1 at pH 7.5 was 60% after 1 hour, and increased to 70 % 3 days later. Conclusions DTTH-1 showed high complexation yield with Zr-89 at pH 7 and 8 at both 1h and 3 day incubation. This pH is ideal for monoclonal antibody labeling. Further assessment is needed to compare in vivo stability of Zr-DTTH-1-antibody with Zr-desferroxiamine -antibody.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.012
GPT teacher head0.324
Teacher spread0.312 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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