Development of [<sup>18</sup>F]AldoView as the First Highly Selective Aldosterone Synthase PET Tracer for Imaging of Primary Hyperaldosteronism
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The purpose of this study was to synthesize a fluorine-18 labeled, highly selective aldosterone synthase ( h CYP11B2) inhibitor, [ 18 F]AldoView, and to assess its potential for the detection of aldosterone-producing adenomas (APAs) with positron emission tomography in patients with primary hyperaldosteronism (PHA). Using dibenzothiophene sulfonium salt chemistry, [ 18 F]AldoView was obtained in high radiochemical yield in one step from [ 18 F]fluoride. In mice, the tracer showed a favorable pharmacokinetic profile, including rapid distribution and clearance. Imaging in the adrenal tissue from patients with PHA revealed diffuse binding patterns in the adrenal cortex, avid binding in some adenomas, and “hot spots” consistent with aldosterone-producing cell clusters. The binding pattern was in good visual agreement with the antibody staining of h CYP11B2 and distinguished areas with normal and excessive h CYP11B2 expression. Taken together, [ 18 F]AldoView is a promising tracer for the detection of APAs in patients with PHA.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".