Quantification of [ <sup>11</sup> C]yohimbine Binding to α <sub>2</sub> Adrenoceptors in Rat Brain <i>in vivo</i>
Bibliographic record
Abstract
We quantified the binding potentials (BPND) of [(11)C]yohimbine binding in rat brain to alpha-2 adrenoceptors to evaluate [(11)C]yohimbine as an in vivo marker of noradrenergic neurotransmission and to examine its sensitivity to the level of noradrenaline. Dual [(11)C]yohimbine dynamic positron emission tomography (PET) recordings were applied to five Sprague Dawley rats at baseline, followed by acute amphetamine administration (2 mg/kg) to induce elevation of the endogenous level of noradrenaline. The volume of distribution (VT) of [(11)C]yohimbine was obtained using Logan plot with arterial plasma input. Because alpha-2 adrenoceptors are distributed throughout the brain, the estimation of the BPND is complicated by the absence of an anatomic region of no displaceable binding. We used the Inhibition plot to acquire the reference volume, VND, from which we calculated the BPND. Acute pharmacological challenge with amphetamine induced a significant decline of [(11)C]yohimbine BPND of ~38% in all volumes of interest. The BPND was greatest in the thalamus and striatum, followed in descending order by, frontal cortex, pons, and cerebellum. The experimental data demonstrate that [(11)C]yohimbine binding is sensitive to a challenge known to increase the extracellular level of noradrenaline, which can benefit future PET investigations of pathologic conditions related to disrupted noradrenergic neurotransmission.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".