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Record W4390943282 · doi:10.1002/mrm.29919

Evidence of <sup>13</sup> C‐lactate oxidation in the human brain from hyperpolarized <sup>13</sup> C‐MRI

2024· article· en· W4390943282 on OpenAlexafffund
Biranavan Uthayakumar, Hany Soliman, Albert P. Chen, Nadia Bragagnolo, Nicole Cappelletto, Ruby Endre, William J. Perks, Nathan Ma, Chris Heyn, Kayvan R. Keshari, Charles H. Cunningham

Bibliographic record

VenueMagnetic Resonance in Medicine · 2024
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersNational Institute of Biomedical Imaging and BioengineeringCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchOntario Research FoundationNational Cancer InstituteNational Institutes of HealthMemorial Sloan-Kettering Cancer Center
KeywordsBicarbonateNuclear magnetic resonanceChemistryHuman brainNuclear medicineMedicinePhysics

Abstract

fetched live from OpenAlex

Abstract Purpose To test the hypothesis that lactate oxidation contributes to the C‐bicarbonate signal observed in the awake human brain using hyperpolarized C MRI. Methods Healthy human volunteers ( N = 6) were scanned twice using hyperpolarized C‐MRI, with increased radiofrequency saturation of C‐lactate on one set of scans. C‐lactate, C‐bicarbonate, and C‐pyruvate signals for 132 brain regions across each set of scans were compared using a clustered Wilcoxon signed‐rank test. Results Increased C‐lactate radiofrequency saturation resulted in a significantly lower C‐bicarbonate signal ( p = 0.04). These changes were observed across the majority of brain regions. Conclusion Radiofrequency saturation of C‐lactate leads to a decrease in C‐bicarbonate signal, demonstrating that the C‐lactate generated from the injected C‐pyruvate is being converted back to C‐pyruvate and oxidized throughout the human brain.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.628
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.320
Teacher spread0.292 · 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.

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

Citations11
Published2024
Admission routes2
Has abstractyes

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