Cardiac metabolic imaging using hyperpolarized [1-13C]lactate as a substrate
Bibliographic record
Abstract
Abstract Hyperpolarized [1- 13 C]lactate is an attractive alternative to [1-13C]pyruvate as a substrate to investigate cardiac metabolism in vivo; it can be administered safely at a higher dose and can be polarized to a similar degree as pyruvate via dynamic nuclear polarization. While 13 C cardiac experiments using HP lactate have been performed in small animal models, it has not been demonstrated in large animal models or humans. Utilizing the same hardware and data acquisition methods used in the first human HP 13 C cardiac study, 13C metabolic images were acquired following injections of HP [1- 13 C]lactate in porcine hearts. Data were also acquired using HP [1- 13 C]pyruvate for comparison. The 13 C bicarbonate signal was localized to the myocardium and had a similar appearance with both substrates for all animals. No 13 C pyruvate signal was detected in the experiments following injection of hyperpolarized 13 C lactate. The SNR of injected lactate was 88 +/-14% of the SNR of injected pyruvate, and the SNR of bicarbonate in the experiments using lactate as the substrate was 52+/-19% of the SNR in the experiments using pyruvate as the substrate. The lower SNR was likely due to the shorter T1 of [1- 13 C]lactate as compared to [1- 13 C]pyruvate and the additional enzyme-catalyzed metabolic conversion step before the 13C nuclei from [1-13C]lactate were detected as 13 C bicarbonate. While challenges remain, the potential of HP lactate as a substrate for clinical metabolic imaging of human heart was demonstrated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".