Technetium Nitrido Complexes of Tetradentate Thiosemicarbazones: Kit-Based Radiolabeling, Characterization, and <i>In Vivo</i> Evaluation
Bibliographic record
Abstract
Bis(thiosemicarbazone) and pyridylhydrazone-thiosemicarbazone chelators have demonstrated utility in nuclear medicine. In particular, the 64 Cu 2+ complexes have been extensively developed for hypoxia imaging and molecular imaging of peptide and protein markers of disease. However, the chemistry and application of bis(thiosemicarbazone) and pyridylhydrazone-thiosemicarbazone chelators in combination with 99m Tc, the most widely used radionuclide in nuclear medicine, is underexplored. Herein, a series of bis(thiosemicarbazone) and pyridylhydrazone-thiosemicarbazone chelators were radiolabeled with nitrido-technetium-99m in an optimized one-pot synthesis from [ 99m Tc]TcO 4 – . Optimization of the radiochemical syntheses allowed for production of the complexes in >90% radiochemical conversion with apparent molar activities of 3.3–5 GBq/μmol. Competition experiments demonstrated the excellent stability of the complexes. The nitrido-technetium-99 complexes were synthesized, and the chemical identities were investigated using mass spectrometry, spectroscopy, and density functional theory calculations. Complexation of nitrido-rhenium(V) was achieved with the N 4 -dialkylated bis(thiosemicarbazones). Planar imaging and ex vivo biodistribution studies of the five 99m Tc complexes were conducted on healthy BALB/c mice to determine in vivo behavior. The lipophilic nature of the complexes resulted in uptake of 1.6–5.7% ID g –1 in the brain at 2 min postinjection and retention of 0.4–1.7% ID g –1 at 15 min postinjection. The stability of the complexes and the biodistribution data demonstrate that these chelators are ideal platforms for future production of radiopharmaceutical candidates.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".