Development of Pyridothiophene Compounds for PET Imaging of α‐Synuclein
Bibliographic record
Abstract
Abstract Aggregated α‐synuclein (α‐syn) protein is a pathological hallmark of Parkinson's disease (PD) and Lewy body dementia (LBD). Development of positron emission tomography (PET) radiotracers to image α‐syn aggregates has been a longstanding goal. This work explores the suitability of a pyridothiophene scaffold for α‐syn PET radiotracers, where 47 derivatives of a potent pyridothiophene (asyn‐44; Kd=1.85 nM) were synthesized and screened against [3H]asyn‐44 in competitive binding assays using post‐mortem PD brain homogenates. Equilibrium inhibition constant (Ki) values of the most potent compounds were determined, of which three had Ki′s in the lower nanomolar range (12–15 nM). An autoradiography study confirmed that [3H]asyn‐44 is promising for imaging brain sections from multiple system atrophy and PD donors. Fluorine‐18 labelled asyn‐44 was synthesized in 6±2 % radiochemical yield (decay‐corrected, n=5) with a molar activity of 263±121 GBq/μmol. Preliminary PET imaging of [18F]asyn‐44 in rats showed high initial brain uptake (>1.5 standardized uptake value (SUV)), moderate washout (~0.4 SUV at 60 min), and low variability. Radiometabolite analysis showed 60–80 % parent tracer in the brain after 30 and 60 mins. While [18F]asyn‐44 displayed good in vitro properties and acceptable brain uptake, troublesome radiometabolites precluded further PET imaging studies. The synthesis and in vitro evaluation of additional pyridothiophene derivatives are underway, with the goal of attaining improved affinity and metabolic stability.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".