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Record W1590350170 · doi:10.1002/cmmi.1497

<i>In vivo</i> magnetic resonance imaging of glucose – initial experience

2012· article· en· W1590350170 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

VenueContrast Media & Molecular Imaging · 2012
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsWestern University
FundersBrainWatch
KeywordsHyperpolarization (physics)Positron emission tomographyIn vivoMagnetic resonance imagingChemistryNuclear magnetic resonanceNuclear medicinePreclinical imagingMedicineRadiologyNuclear magnetic resonance spectroscopy

Abstract

fetched live from OpenAlex

A new noninvasive, nonradioactive approach for glucose imaging using spin hyperpolarization technology and stable isotope labeling is presented. A glucose analog labeled with (13)C at all six positions increased the overall hyperpolarized imaging signal; deuteration at all seven directly bonded proton positions prolonged the spin-lattice relaxation time. High-bandwidth (13)C imaging overcame the large glucose carbon chemical shift dispersion. Hyperpolarized glucose images in the live rat showed time-dependent organ distribution patterns. At 8 s after the start of bolus injection, the inferior vena cava was demonstrated at angiographic quality. Distribution of hyperpolarized glucose in the kidneys, vasculature, and heart was demonstrated at 12 and 20 s. The heart-to-vasculature intensity ratio at 20 s suggests myocardial uptake. Cancer imaging, currently performed with (18)F-deoxyglucose positron emission tomography (FDG-PET), warrants further investigation, and glucose imaging could be useful in a vast range of clinical conditions and research fields where the radiation associated with the FDG-PET examination limits its use.

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)0.000
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 score0.131
Threshold uncertainty score0.878

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 head0.007
GPT teacher head0.276
Teacher spread0.269 · 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