Kinetics of (R)-[11C] rolipram and (S)-[11C] rolipram In the Dog Heart: Investigation of Four Compartment Models
Bibliographic record
Abstract
The PET tracers (R)-[11C]rolipram and (S)-[11C]rolipram have been proposed to measure phosphodiesterase-4 (PDE4) density as an indirect index of cAMP-mediated cell signaling, which is altered in many cardiac pathologies. The aim of this study was to determine which of the following models (if any) describe the kinetics of these tracers in normal dog hearts: a one-compartment model, a two-compartment model, and dual-input models comprising one or two compartments for rolipram and one compartment for labeled metabolites. Dynamic PET data were acquired from 6 healthy dogs with (R)-[11C]rolipram (10 studies) and (S)-[11C]rolipram (6 studies). Parameter estimates were obtained for 648 ROI's and median values determined. Distribution volumes were estimated from the parameter estimates. The one-compartment model did not fit the data acquired with either tracer adequately. Both the two-compartment model and the model comprising one compartment for the unchanged tracer and a parallel compartment to account for labeled metabolites provided good fits to the data obtained with (S)-[11C]rolipram (R-square: 0.99-1). The two-compartment model, with or without a parallel compartment to account for metabolites, described the kinetics of (R)-[11C]rolipram very well (R-square: 0.98-0.99). Estimates of the distribution volumes obtained with models that provided good fits to the data were very reproducible (CV: 10%-21%), suggesting that reliable measurement of PDE4 density in the heart may be possible.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".