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Record W2026714121 · doi:10.1021/bc800413g

Kit-Like <sup>18</sup>F-Labeling of Proteins: Synthesis of 4-(Di-<i>tert</i>-butyl[<sup>18</sup>F]fluorosilyl)benzenethiol (Si[<sup>18</sup>F]FA-SH) Labeled Rat Serum Albumin for Blood Pool Imaging with PET

2009· article· en· W2026714121 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioconjugate Chemistry · 2009
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsChemistryIn vivoYield (engineering)Pet imagingRadiochemistryPositron emission tomographyNuclear medicine

Abstract

fetched live from OpenAlex

Radiosyntheses of 18F-radiopharmaceuticals for positron emission tomography (PET) normally require an extraordinarily high effort of technical equipment and specially trained personnel. We recently reported a novel method for the introduction of fluorine-18 into peptides for PET-imaging based on silicon-18F-chemistry (SiFA technique). We herewith introduce the first SiFA-based Kit-like radio-fluorination of a protein (rat serum albumin,RSA) and demonstrate its usefulness for in vivo imaging with microPET in normal rats as well as in a rat heterotropic transplanted heart model. As a labeling agent, we prepared 4-(di-tert-butyl[18F]fluorosilyl)benzenethiol (Si[18F]FASH)by simple isotopic exchange in 40-60% radiochemical yield (RCY) and coupled it directly to a Sulfo-SMCC derivatized RSA in an overall RCY of 12% within 20-30 min. The technically simple labeling procedure does not require any elaborated purification procedures and is a straightforward example of a successful application of Si-18F chemistry for in vivo imaging with PET.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
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 score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.269
Teacher spread0.253 · 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