Determination of a pharmacokinetic model for [11C]-acetate in brown adipose tissue
Bibliographic record
Abstract
BACKGROUND: C]-acetate positron emission tomography is used to assess oxidative metabolism in various tissues including the heart, tumor, and brown adipose tissue. For brown adipose tissue, a monoexponential decay model is commonly employed. However, no systematic assessment of kinetic models has been performed to validate this model or others. The monoexponential decay model and various compartmental models were applied to data obtained before and during brown adipose tissue activation by cold exposure in healthy men. Quality of fit was assessed visually and by analysis of residuals, including the Akaike information criterion. Stability and accuracy of compartmental models were further assessed through simulations, along with sensitivity and identifiability of kinetic parameters. RESULTS: Differences were noted in the arterial input function between the warm and cold conditions. These differences are not taken into account by the monoexponential decay model. They are accounted for by compartmental models, but most models proved too complex to be stable. Two and three-tissue models with no more than four distinct kinetic parameters, including blood volume fraction, provided the best compromise between fit quality and stability/accuracy. CONCLUSION: C]-acetate pathways in BAT cells. Further studies are required to validate this model in women and people with metabolic disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".