Effects of Anesthesia and Species on the Uptake or Binding of Radioligands In Vivo in the Göttingen Minipig
Bibliographic record
Abstract
Progress in neuroscience research often involves animals, as no adequate alternatives exist to animal models of living systems. However, both the physiological characteristics of the species used and the effects of anesthesia raise questions of common concern. Here, we demonstrate the confounding influences of these effects on tracer binding in positron emission tomography (PET). We determined the effects of two routinely used anesthetics (isoflurane and propofol) on the binding of two tracers of monoamine function, [(11)C]SCH23390, a tracer of the dopamine D1 and D5 receptors, and the alpha2-adrenoceptor antagonist, [(11)C]yohimbine, in Göttingen minipigs. The kinetics of SCH23390 in the pigs differed from those of our earlier studies in primates. With two different graphical analyses of uptake of SCH23390, the initial clearance values of this tracer were higher with isoflurane than with propofol anesthesia, indicative of differences in blood flow, whereas no significant differences were observed for the volumes of distribution of yohimbine. The study underscores the importance of differences of anesthesia and species when the properties of radioligands are evaluated under different circumstances that may affect blood flow and tracer uptake. These differences must be considered in the choice of a particular animal species and mode of anesthesia for a particular application.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".