Radiosynthesis and Characterization of <sup>11</sup>C-GSK215083 as a PET Radioligand for the 5-HT6 Receptor
Bibliographic record
Abstract
UNLABELLED: The development of a PET radioligand for imaging 5-hydroxytryptamine (5-HT) 6 receptors in the brain would, for the first time, enable in vivo imaging of this target along with assessment of its involvement in disease pathophysiology. In addition, such a tool would assist in the development of novel drugs targeting the 5-HT6 receptor. METHODS: On the basis of in vitro data, GSK215083 was identified as a promising 5-HT6 radioligand candidate and was radiolabeled with (11)C via methylation. The in vivo properties of (11)C-GSK215083 were evaluated first in pigs (to investigate brain penetration and specific binding), second in nonhuman primates (to confirm brain penetration, specific binding, selectivity, and kinetics), and third in human subjects (to confirm brain penetration and biodistribution). RESULTS: (11)C-GSK215083 readily entered the brain in all 3 species, leading to a heterogeneous distribution (striatum > cortex > cerebellum) consistent with reported 5-HT6 receptor densities and distribution determined by tissue-section autoradiography in preclinical species and humans. In vivo saturation studies using escalating doses of GSK215083 in primates demonstrated saturable, dose-dependent binding to the 5-HT6 receptor in the striatum. Importantly, (11)C-GSK215083 also exhibited affinity for the 5-HT2A receptor; however, given the differential localization of these 2 receptors in the central nervous system, the discrete 5-HT6 binding properties of this radioligand were able to be determined. CONCLUSION: These data demonstrate the utility of (11)C-GSK215083 as a promising PET radioligand for probing the 5-HT6 receptor in vivo in both preclinical and clinical species.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".