Chelation in One Fell Swoop: Optimizing Ligands for Smaller Radiometal Ions
Bibliographic record
Abstract
[ 44/47 Sc]Sc 3+, [ 68 Ga]Ga 3+, and [ 111 In]In 3+ are the three most attractive trivalent smaller radiometalnuclides, offering a wide range of distinct properties (emission energies and types) in the toolbox of nuclear medicine. In this study, all three of the metal ions are successfully chelated using a new oxine-based hexadentate ligand, H 3 glyox, which forms thermodynamically stable neutral complexes with exceptionally high pM values [pIn (34) > pSc (26) > pGa (24.9)]. X-ray diffraction single crystal structures with stable isotopes revealed that the ligand is highly preorganized and has a perfect fit to size cavity to form [Sc(glyox)(H 2 O)] and [In(glyox)(H 2 O)] complexes. Quantitative radiolabeling with gallium-68 (RCY > 95%, [L] = 10 –5 M) and indium-111 (RCY > 99%, [L] = 10 –8 M) was achieved under ambient conditions (RT, pH 7, and 15 min) with very high apparent molar activities of 750 MBq/μmol and 650 MBq/nmol, respectively. Preliminary quantitative radiolabeling of [ 44 Sc]ScCl 3 (RCY > 99%, [L] = 10 –6 M) was fast at room temperature (pH 7 and 10 min). In vitro experiments revealed exceptional stability of both [ 68 Ga]Ga(glyox) and [ 111 In]In(glyox) complexes against human serum (transchelation <2%) and its suitability for biological applications. Additionally, on chelation with metal ions, H 3 glyox exhibits enhanced fluorescence, which was employed to determine the stability constants for Sc(glyox) in addition to the in-batch UV–vis spectrophotometric titrations; as a proof-of-concept these complexes were used to obtain fluorescence images of live HeLa cells using Sc(glyox) and Ga(glyox), confirming the viability of the cells. These initial investigations suggest H 3 glyox to be a valuable chelator for radiometal-based diagnosis (nuclear and optical imaging) and therapy.
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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".