Thorium chelators for targeted alpha therapy: Rapid chelation of thorium‐226
Bibliographic record
Abstract
One of the main challenges in targeted alpha therapy is assuring delivery of the α‐particle dose to the targeted cells. Thus, it is critical to identify ligands for α‐emitting radiometals that will form complexes that are very stable, both in vitro and in vivo. In this investigation, thorium‐227 (t1/2 = 18.70 days) chelation of ligands containing hydroxypyridinonate (HOPO) or picolinic acid (pa) moieties and the stability of the resultant complexes were studied. Chelation reactions were followed by reversed‐phased HPLC and gamma spectroscopy. Studies revealed that high 227Th chelation yields could be obtained within 2.5 h or less with ligands containing four Me‐3,2‐HOPO moieties, 1 (83%) and 2 (65%), and also with ligands containing pa moieties, H4octapa 3 (65%) and H4py4pa 6 (87%). No reaction occurred with H4neunpa‐p‐Bn‐NO2 4, and the chelation reaction with another pa ligand H4pypa 5 gave inconsistent yields with a very broad radio‐HPLC peak. The ligands spermine‐(Me‐3,2‐HOPO)4 1, H4octapa 3, and H4py4pa 6 had high stability (i.e., 87% of 227Th still bound to the ligand) in phosphate‐buffered saline at room temperature over a 6‐day period. Preliminary studies with ligand 6 demonstrated efficient chelation of thorium‐226 (t1/2 = 30.57 min) when heated to 80°C for 5 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) | 0.001 | 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".