Development and Clinical Application of Positron Emission Tomography Imaging Agents for Monoamine Oxidase B
Bibliographic record
Abstract
Monoamine oxidase B (MAO-B) is a high-density protein in the brain mainly found on outer mitochondrial membranes, primarily in astroglia, but additionally in serotonergic neurons and in the substantia nigra in the midbrain. It is an enzyme that participates in the oxidative metabolism of important monoamines including dopamine, norepinephrine, benzylamine, and phenylethylamine. Elevated MAO-B density may be associated with astrogliosis and inhibiting MAO-B may reduce astrogliosis. MAO-B density is elevated in postmortem sampling of pathology for many neuropsychiatric diseases including Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, amyotrophic lateral sclerosis, and alcohol use disorder. Initial development of positron emission tomography (PET) imaging agents focused on analogs of [11C]L-deprenyl, with the most commonly applied being the deuterium substituted [11C]L-deprenyl-D2. This latter radiotracer was modeled with an irreversible trapping compartment reflecting its irreversible binding to MAO-B. Subsequently, [11C]SL25.1188, a reversible binding MAO-B radioligand with outstanding properties including high specific binding and excellent reversibility was developed. [11C]SL25.1188 PET was applied to discover a substantive elevation of MAO-B binding in the prefrontal cortex in major depressive disorder (MDD) with an effect size of more than 1.5. Longer duration of MDD was associated with greater MAO-B binding throughout most gray matter regions in the brain, suggesting progressive astrogliosis. Important applications of [11C]L-deprenyl-D2 PET are detecting a 40% loss in radiotracer accumulation in cigarette smokers, and substantial occupancy of novel therapeutics like EVT301 and sembragiline. Given the number of diseases with elevations of MAO-B density and astrogliosis, and the advance of [11C]SL25.1188, clinical applications of MAO-B imaging are still at an early stage.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.002 |
| 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".