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Record W2017640674 · doi:10.1002/jlcr.1535

Automated radiosynthesis of <i>N</i>‐(4‐[<sup>18</sup>F]fluorobenzyl)‐2‐bromoacetamide: an F‐18‐labeled reagent for the prosthetic radiolabeling of oligonucleotides

2008· article· en· W2017640674 on OpenAlexaff
Ingrid L. Koslowsky, Soraya Shahhosseini, John S. Wilson, John R. Mercer

Bibliographic record

VenueJournal of Labelled Compounds and Radiopharmaceuticals · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChemistryOligonucleotideYield (engineering)RadiosynthesisReagentRadiochemistryAnhydrousCombinatorial chemistrySpecific activityOrganic chemistryPositron emission tomographyBiochemistryEnzymeNuclear medicineDNA

Abstract

fetched live from OpenAlex

Abstract The potential for radiolabeled antisense oligonucleotides to image gene expression combined with the enhanced resolution of positron‐emission tomography justifies the continued interest in the development of oligonucleotides tagged with positron‐emitting radionuclides. The radiolabeling of oligonucleotides is a multi‐step process and may require handling large amounts of radioactivity initially. A previously reported method for radiolabeling oligonucleotides with N ‐(4‐[ 18 F]fluorobenzyl)‐2‐bromoacetamide was adapted for use in a commercially available automated synthesis unit by linking two reaction trains. The yield of N ‐(4‐[ 18 F]fluorobenzyl)‐2‐bromoacetamide ranged from 3 to 18% and the synthesis was completed within 1 h. Challenges in using this unit included the maintenance of anhydrous conditions for the effective reduction of 4‐[ 18 F]fluorobenzonitrile. Preliminary results indicated that a mean yield of 36% could be obtained upon incubation of an oligonucleotide with N –(4‐[ 18 F]fluorobenzyl)‐2‐bromoacetamide. The entire synthesis could be performed within 3 h. Copyright © 2008 John Wiley &amp; Sons, Ltd.

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)0.001
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 score0.036
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.040
GPT teacher head0.311
Teacher spread0.271 · 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

Citations6
Published2008
Admission routes1
Has abstractyes

Explore more

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