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Record W45727997

A new strategy for labeling proteins using oil-in-water emulsions. Single step preparation of Tc-99m radiolabeled insulin

2011· article· en· W45727997 on OpenAlexaff
Anthony James Albina, Megan Blacker, Chitra Sundararajan, Ryan Simms, Bob Wu, John F. Valliant

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsCentre for Probe Development and CommercializationMcMaster University
Fundersnot available
KeywordsInsulinChemistryIn vivoPeptideHormoneInsulin receptorChromatographyCombinatorial chemistryBiochemistryInternal medicineInsulin resistanceBiologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

1507 Objectives Radiolabeling peptide hormones and proteins with radiometals like Tc-99m often requires multi-step indirect labeling methods because direct labeling can result in complex mixtures of products requiring extensive chromatographic purification. The objective was to develop a cost effective and efficient strategy to directly label proteins and peptide hormones using oil-in-water emulsions and insulin as the targeting vector. Insulin-derived nuclear probes are potentially valuable tools to evaluate the distribution and metabolism of insulin in vivo including dysregulation associated with diseases like diabetes, hypertension, and breast cancer. Methods Two new insulin derivatives bearing single amino acid chelates (SAACs) linked to the B1 residue of insulin through different PEG chains were prepared. The rhenium analogues were synthesized in parallel and assessed for in vitro binding to MCF-7 breast cancer cells using an I-125 insulin competition assay. The insulin derivatives were labeled with [99mTc(CO)3]+ using an oil-in-water emulsion and the products isolated by centrifugation. Results The rhenium standards were essentially indistinguishable from insulin in the competition assay and gave similar IC50 values of 4.8 nM and 7.4 nM for PEG3-SAAC II-insulin and PEG8-SAAC II-insulin, respectively. The radiolabeling procedure produced a single product in quantitative yield at room temperature in 60 min. These results are far superior to the yields obtained when performing direct solution phase labeling ( Conclusions A new paradigm for labeling targeting vectors with technetium has been developed and used to prepare 99mTc-labeled insulin in a single step. The product appears functionally indistinguishable from native insulin in vitro. The general applicability of the labeling procedure and potential uses of the Tc-insulin probes for the evaluation of insulin biochemistry in vivo will be discussed

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.138
GPT teacher head0.370
Teacher spread0.232 · 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".

Quick stats

Citations2
Published2011
Admission routes1
Has abstractyes

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