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Record W1988760858 · doi:10.1039/c4dt01928h

Synthesis and characterisation of zirconium complexes for cell tracking with Zr-89 by positron emission tomography

2014· article· en· W1988760858 on OpenAlexaff
Trevor J. Ferris, Putthiporn Charoenphun, Levente K. Meszaros, Gregory Mullen, Philip J. Blower, Michael J. Went

Bibliographic record

VenueDalton Transactions · 2014
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsSt. Thomas Hospital
FundersEngineering and Physical Sciences Research CouncilMedical Research CouncilCancer Research UKWellcome TrustWellcome
KeywordsTropoloneOxalic acidLabellingZirconiumChemistryNuclear chemistryRadiochemistryPositron emission tomographyYield (engineering)PositronLigand (biochemistry)Hydrochloric acidHigh-performance liquid chromatographyChromatographyMaterials scienceInorganic chemistryOrganic chemistryNuclear medicineBiochemistry

Abstract

fetched live from OpenAlex

The increasing availability of the long half-life positron emitter Zr-89 (half life 78.4 h) suggests that it is a strong candidate for cell labelling and hence cell tracking using positron emission tomography. The aim was to produce a range of neutral ZrL4 lipophilic complexes for cell labelling which could be prepared under radiopharmaceutical conditions. This was achieved when the ligand was oxine, tropolone or ethyl maltol. The complexes can be prepared in high yield from zirconium(iv) precursors in hydrochloric or oxalic acid solution. The oxinate and tropolonate complexes were the most amenable to chromatographic characterisation, and HPLC and ITLC protocols have been established to monitor their radiochemical purity. The radiochemical synthesis and quality control of (89)Zr(oxinate)4 is reported as well as preliminary cell labelling data for the oxinate, tropolonate and ethyl maltolate complexes which indicates that (89)Zr(oxinate)4 is the most promising candidate for further evaluation.

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 score0.236
Threshold uncertainty score0.336

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 head0.015
GPT teacher head0.266
Teacher spread0.251 · 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

Citations32
Published2014
Admission routes1
Has abstractyes

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