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Record W2155314773 · doi:10.1002/nbm.1618

<sup>13</sup>C MR reporter probe system using dynamic nuclear polarization

2010· article· en· W2155314773 on OpenAlexafffund
Albert P. Chen, Ralph E. Hurd, Yiping Gu, David M. Wilson, Charles H. Cunningham

Bibliographic record

VenueNMR in Biomedicine · 2010
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsUniversity of TorontoHealth Sciences CentreSunnybrook Health Science Centre
FundersCanadian Institutes of Health Research
KeywordsReporter geneChemistryTransfectionAcetylationHEK 293 cellsIn vivoEnzymeMolecular biologyNuclear magnetic resonanceBiochemistryGene expressionGeneBiologyPhysics

Abstract

fetched live from OpenAlex

Reporter-based cell detection and localization in vivo may become an important imaging tool with the emergence of cellular therapy. With the strong signal enhancement provided by dynamic nuclear polarization, an NMR-based reporter probe system utilizing specific enzyme expression and activity can potentially provide stable, high-resolution visualization of the cells of interest noninvasively. In this work, a proof-of-concept (13) C MR reporter system, using the aminoacylase-1 reporter gene (Acy-1) and prepolarized [1-(13) C]N-acetyl-L-methionine as the paired substrate, was developed. Using a 3-T MR scanner, the feasibility of detecting and imaging de-acetylation of the prepolarized (13) C-labeled substrate by the aminoacylase-1 enzyme was demonstrated with purified protein in solution by dynamic (13) C MRS and two-dimensional MRSI experiments. The potential to perform targeted MRI of cells using this system was also demonstrated by (13) C MR measurement of aminoacylase-1 activity in HEK 293 cells transfected with the Acy-1 gene. The de-acetylation of the substrate was not observed in control cells.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.951
Threshold uncertainty score0.566

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 head0.010
GPT teacher head0.281
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

Citations34
Published2010
Admission routes2
Has abstractyes

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