Combined In Vivo Microdialysis and PET Studies to Validate [11C]Yohimbine Binding as a Marker of Noradrenaline Release
Bibliographic record
Abstract
The noradrenaline system attracts attention for its role in mood disorders and neurodegenerative diseases but the lack of well-validated methods impairs our understanding when assessing its function and release in vivo. This study combines simultaneous positron emission tomography (PET) and microdialysis to explore if [11C]yohimbine, a selective antagonist radioligand of the α2 adrenoceptors, may be used to assess in vivo changes in synaptic noradrenaline during acute pharmacological challenges. Anesthetised Göttingen minipigs were positioned in a head holder in a PET/CT device. Microdialysis probes were placed in the thalamus, striatum and cortex and dialysis samples were collected every 10 min. Three 90 min [11C]yohimbine scans were acquired: at baseline and at two timepoints after the administration of amphetamine (1–10 mg/kg), a non-specific releaser of dopamine and noradrenaline, or nisoxetine (1 mg/kg), a specific noradrenaline transporter inhibitor. [11C]yohimbine volumes of distribution (VT) were obtained using the Logan kinetic model. Both challenges induced a significant decrease in yohimbine VT, with time courses reflecting their different mechanisms of action. Dialysis samples revealed a significant increase in noradrenaline extracellular concentrations after challenge and an inverse correlation with changes in yohimbine VT. These data suggest that [11C]yohimbine can be used to evaluate acute variations in synaptic noradrenaline concentrations after pharmacological challenges.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".