In vivo imaging of the mouse cholinergic projection system using [<sup>18</sup>F]FEOBV
Bibliographic record
Abstract
Abstract Background Positron emission tomography (PET) with the [18F]‐Fluoroethoxybenzovesamicol ([18F]FEOBV) radiotracer is a promising tool for in vivo imaging of VAChT – a protein found specifically in the cholinergic system. However, the sensitivity and specificity of [18F]FEOBV uptake to known changes in VAChT protein levels remains untested. The aim of this study is therefore to use [18F]FEOBV in mouse lines where VAChT protein expression is held under precise genetic control to determine whether [18F]FEOBV brain uptake reflects the endogenous levels of VAChT present in different genetic mouse models. Method 6‐month‐old VAChT conditional forebrain knock‐out mice (VAChTNkx2.1‐Cre‐flox/flox, n = 6), VAChT hyper expressing mice (VAChTChAT‐ChR2‐eYFP, n = 6), and littermate controls (VAChT flox/flox , n = 6; C57BL/6J, n = 6), received an intravenous injection of [18F]FEOBV and were imaged dynamically on a microPET scanner for 2 and a half hours. Result When compared to controls, VAChT conditional forebrain knock‐out mice demonstrated decreased [18F]FEOBV uptake in striatal regions of the mouse brain (Figure 1, left panel). In contrast, VAChT hyper expressing mice displayed widespread increases in brain [18F]FEOBV uptake when compared to controls (Figure 1, right panel). Conclusion Together, these findings suggest that [18F]FEOBV brain uptake is a sensitive and specific measure of known changes in VAChT protein expression.
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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 | 0.001 | 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 | 0.001 |
| 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".