<i>para</i>‐Functionalized Aryl‐di‐<i>tert</i>‐butylfluorosilanes as Potential Labeling Synthons for <sup>18</sup>F Radiopharmaceuticals
Bibliographic record
Abstract
Broad spectrum: Novel para-functionalized aryl-di-tert-butylfluorosilanes, p-(tBu(2)FSi)C(6)H(4)X (X=functional group), have been made available and broaden the spectrum of silicon-based (18)F acceptors (SiFAs) for potential PET applications. For example, the [(18)F]maleimido derivative 1 has been employed for the synthesis of [(18)F]1- labeled rat serum albumin (RSA), the applicability of which for PET has been verified by in vivo experiments.The syntheses of the functionalized triorganofluorosilanes tBu(2)(p-XC(6)H(4))SiF (3 a, X=SH; 4 a, X=NCS; 4 b, X=NCO; 5, X=NC(4)H(2)O(2); 7, X=COOH; 8 a, X=COONC(4)H(4)O(2); 8 b, X=COOC(6)F(5)) are reported. These compounds display potential as silicon-based fluoride acceptors (SiFAs). The molecular structures of compounds 5, 7, and 8 a have been determined by single-crystal X-ray diffraction studies. With the exception of compounds 8 a and 8 b, all of the compounds could be (18)F-labeled by isotopic exchange in good to high radiochemical yields (RCY) with good to excellent specific activities. As proof of applicability, the maleimido-functionalized SiFA derivative 5, which is specific for thiol groups, has been used for the labeling of rat serum albumin (RSA) that had been derivatized with 2-iminothiolane. The incorporation of [(18)F]5 into the derivatized RSA reached a maximum yield after 30 min at ambient temperature. After purification, the [(18)F]RSA was evaluated in a healthy rat by means of muPET and displayed an expedient in vivo stability over 180 min.
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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) | 0.002 | 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".