Loss of metabolites from monkey striatum during PET with FDOPA
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Bibliographic record
Abstract
The decarboxylation of 6-[(18)F]fluorodopa (FDOPA) and retention of the product [(18)F]fluorodopamine within vesicles of catecholamine fibers results in the labeling of dopamine-rich brain regions during FDOPA/PET studies. However, this metabolic trapping is not irreversible due to the eventual diffusion of [(18)F]fluorodopamine metabolites from brain. Consequently, time-radioactivity recordings of striatum are progressively influenced by metabolite loss. In linear analyses, the net blood-brain clearance of FDOPA (K(D)(i), ml g(-1) min(-1)) can be corrected for this loss by the elimination rate constant k(Lin)(cl) (min(-1)). Similarly, the DOPA decarboxylation rate constant (k(D)(3), min(-1)) calculated by compartmental analysis can also be corrected for metabolite loss by the elimination rate constant k(DA)(9) (min(-1)). To compare the two methods, we calculated the two elimination rate constants using data recorded during 240 min of FDOPA circulation in normal monkeys and in monkeys with unilateral 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) lesions. Use of the extended models increased the magnitudes of K(D)(i) and k(D)(3) in striatum; in the case of k(D)(3), variance of the estimate was substantially improved upon correction for metabolite loss. The rate constants for metabolite loss were higher in MPTP-lesioned monkey striatum than in normal striatum. The high correlation between individual estimates of k(Lin)(cl) and k(DA)(9) suggests that both rate constants reveal loss of decarboxylated metabolites from brain.
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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 | 0.000 | 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 it