DEVELOPMENT OF A DUAL TRACER PET METHOD FOR IMAGING DOPAMINERGIC NEUROMODULATION
Bibliographic record
Abstract
The modulatory neurotransmitter dopamine (DA) is involved in movement and reward behaviors, and malfunctions in the dopamine system are implicated in a variety of prevalent and debilitating pathologies including Parkinson's disease, attention deficit/hyperactivity disorder, schizophrenia, and addiction. Positron emission tomography (PET) has been used to separately measure changes in DA receptor occupancy and blood flow in response to various interventions. Here we describe a dual tracer PET method to simultaneously measure both responses with the aim of comparing DA release in particular areas of the brain and associated alterations in neural activity throughout the brain. Significant correlations between reductions in DA receptor occupancy and blood flow alterations would be potential signs of dopaminergic modulation, i.e. modifications in signal processing due to increased levels of extracellular DA. Methodological development has begun with rats undergoing an amphetamine challenge while being scanned with the blood flow tracer [ 17 F]fluoromethane and the dopamine D2 receptor tracer [ 18 F]desmethoxyfallypride.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.002 | 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".