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Record W4310610876 · doi:10.1186/s41181-022-00183-y

A simple and automated method for 161Tb purification and ICP-MS analysis of 161Tb

2022· article· en· W4310610876 on OpenAlexafffund
Scott McNeil, Michiel Van de Voorde, Chengcheng Zhang, Maarten Ooms, François Bénard, Valery Radchenko, Hua Yang

Bibliographic record

VenueEJNMMI Radiopharmacy and Chemistry · 2022
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsSimon Fraser UniversityUniversity of British ColumbiaTRIUMF
FundersNatural Sciences and Engineering Research Council of CanadaTRIUMF
KeywordsSolid phase extractionChromatographyChemistryExtraction (chemistry)ChelationNeutron activation analysisIon chromatographyMass spectrometryInductively coupled plasma mass spectrometryRadiochemistryInorganic chemistry

Abstract

fetched live from OpenAlex

Abstract Background 161 Tb is a radiolanthanide with the potential to replace 177 Lu in targeted radionuclide therapy. 161 Tb is produced via the neutron irradiation of [ 160 Gd]Gd 2 O 3 targets, and must be purified from 160 Gd and the decay product 161 Dy prior to use. Established purification methods require complex conditions or high-pressure ion chromatography (HPIC) which are inconvenient to introduce in a broad user community. This study aims to find a simpler small solid-phase extraction (SPE) column method for 161 Tb purification that is more suitable for automation with commercially available systems like TRASIS. Results We first tested the distribution coefficients on TK211 and TK212 resins for the separation of Gd, Tb, and Dy, and subsequently developed a method to separate these metal ions, with an additional TK221 resin to concentrate the final product. A side-by-side comparison of the products purified using this new method with the HPIC method was undertaken, assessing the radionuclidic purity, chemical purity regarding Gd and Dy, and labeling efficiency with a standard chelate (DOTA) and a novel chelate (crown). The two methods have comparable radionuclidic purity and labeling efficiency. The small SPE column method reduced Gd content to nanogram level, although still higher than the HPIC method. An ICP-MS method to quantify 161 Tb, 159 Tb, 160 Gd, and 161 Dy was developed with the application of mass-shift by ammonia gas. Last, 161 Tb produced from the small SPE column method was used to assess the biodistribution of [ 161 Tb]Tb-crown-αMSH, and the results were comparable to the HPIC produced 161 Tb. Conclusions 161 Tb was successfully purified by a semi-automated TRASIS system using a combination of TrisKem extraction resins. The resulting product performed well in radiolabelling and in vivo experiments. However, improvement can be made in the form of further reduction of 160 Gd target material in the final product. An ICP-MS method to analyze the radioactive product was developed. Combined with gamma spectroscopy, this method allows the purity of 161 Tb being assessed before the decay of the product, providing a useful tool for quality control.

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 score0.320
Threshold uncertainty score0.716

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 head0.023
GPT teacher head0.372
Teacher spread0.348 · 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

Citations26
Published2022
Admission routes2
Has abstractyes

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