Development of a PET radioligand for potassium channels to image CNS demyelination
Bibliographic record
Abstract
Abstract Central nervous system (CNS) demyelination represents the pathological hallmark of multiple sclerosis (MS) and contributes to other neurological conditions. Quantitative and specific imaging of demyelination would thus provide critical clinical insight. Here, we investigated the possibility of targeting axonal potassium channels to image demyelination by positron emission tomography (PET). These channels, which normally reside beneath the myelin sheath, become exposed upon demyelination and are the target of the MS drug, 4-aminopyridine (4-AP). We demonstrate using autoradiography that 4-AP has higher binding in non-myelinated and demyelinatedversuswell-myelinated CNS regions, and describe a fluorine-containing derivative, 3-F-4-AP, that has similar pharmacological properties and can be labeled with18F for PET imaging. Additionally, we demonstrate that [18F]3-F-4-AP can be used to detect demyelination in rodents by PET. Further evaluation in Rhesus macaques shows higher binding in non-myelinatedversusmyelinated areas and excellent properties for brain imaging. Together, these data indicate that [18F]3-F-4-AP may be a valuable PET tracer for detecting CNS demyelination noninvasively.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".