Analyses of [<sup>18</sup>F]altanserin bolus injection PET data. II: Consideration of radiolabeled metabolites in humans
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Bibliographic record
Abstract
Imaging serotonin-2A (5-HT(2A)) neuroreceptors with positron emission tomography (PET) and [(18)F]altanserin has been the focus of a series of PET studies, as [(18)F]altanserin is one of the most selective 5-HT(2A) antagonist radiotracers. Previous animal studies showed that radiolabeled metabolites (radiometabolites) of [(18)F]altanserin crossed the blood-brain barrier (BBB) to localize nonspecifically in brain, consistent with a constant radioactivity "background." In this work, we evaluated human bolus injection [(18)F]altanserin PET data with detailed consideration of the impact of BBB-permeable metabolites on the specific binding parameters. Data were quantified using either single (parent radiotracer), dual (parent radiotracer and radiometabolites), or no arterial input function(s) (cerebellum as reference tissue input function). A step-gradient high-performance liquid chromatography (HPLC) analysis provided distinct separation of [(18)F]altanserin and four radiolabeled components in plasma. After [(18)F]altanserin injection, the step-gradient data showed that the major BBB-permeable radiometabolites approached constant levels in plasma (>50 min), consistent with a constant metabolite "background." The single-input Logan graphical results were highly correlated with the dual-input results and its bias was fairly constant across regions and subjects, as similarly observed for a nongraphical reference tissue method. The most comprehensive and quantitatively valid analysis for bolus [(18)F]altanserin PET data was the dual-input method that specifically accounted for BBB-permeable metabolites, although the Logan analysis was preferred because it provided a good compromise between validity, sensitivity, and reliability of implementation. Further study is needed to better understand how the cerebellar kinetics of [(18)F]altanserin and its radiometabolites impact the reference tissue measures.
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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 | 0.001 |
| 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 | 0.000 | 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