Synthesis and Preclinical Evaluation of [<sup>18</sup>F]SiFA-PSMA Inhibitors in a Prostate Cancer Model
Bibliographic record
Abstract
Positron emission tomography (PET) imaging of prostate-specific membrane antigen (PSMA) with gallium-68 ( 68 Ga) and fluorine-18 ( 18 F) radiotracers has aroused tremendous interest over the past few years. The use of organosilicon-[ 18 F]fluoride acceptors (SiFA) conjugated to urea-based peptidomimetic PSMA inhibitors provides a “kit-like” multidose synthesis technology. Nine novel 18 F-labeled SiFA-bearing PSMA inhibitors with different linker moieties were synthesized and analyzed for their in vitro binding against [ 125 I]I-TAAG-PSMA in LNCaP cells. IC 50 values ranged from 58–570 nM. Among all compounds, [ 18 F]SiFA-Asp 2 -PEG 3 -PSMA (IC 50 = 125 nM) showed the highest tumor uptake in LNCaP tumors (SUV 60min 0.73). A substantial increase in molar activity ( A m ) (from 7.5 ± 0.5 to 86 ± 3 GBq/μmol) led to a significant increase in LNCaP tumor uptake (SUV 60min 1.18; Δ 0.45 corresponding to +62%). In vivo blocking with DCFPyL resulted in −32% uptake after 60 min. The SiFA-isotopic exchange chemistry offers a method that is readily adaptable for a “kit-type” labeling procedure and clinical translation.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".