Synthesis of DOTA-pyridine chelates for 64Cu coordination and radiolabeling of αMSH peptide
Bibliographic record
Abstract
Abstract Background 64 Cu is one of the few radioisotopes that can be used for both imaging and therapy, enabling theranostics with identical chemical composition. Development of stable chelators is essential to harness the potential of this isotope, challenged by the presence of endogenous copper chelators. Pyridyl type chelators show good coordination ability with copper, prompting the present study of a series of chelates DOTA-xPy (x = 1–4) that sequentially substitute carboxyl moieties with pyridyl moieties on a DOTA backbone. Results We found that the presence of pyridyl groups significantly increases 64 Cu labeling conversion yield, with DOTA-2Py, −3Py and -4Py quantitatively complexing 64 Cu at room temperature within 5 min (1 × 10 − 4 M). [ 64 Cu]Cu-DOTA-xPy (x = 2–4) exhibited good stability in human serum up to 24 h. When challenged with 1000 eq. of NOTA, no transmetallation was observed for all three 64 Cu complexes. DOTA-xPy (x = 1–3) were conjugated to a cyclized α-melanocyte-stimulating hormone (αMSH) peptide by using one of the pendant carboxyl groups as a bifunctional handle. [ 64 Cu]Cu-DOTA-xPy-αMSH retained good serum stability (> 96% in 24 h) and showed high binding affinity (Ki = 2.1–3.7 nM) towards the melanocortin 1 receptor. Conclusion DOTA-xPy (x = 1–3) are promising chelators for 64 Cu. Further in vivo evaluation is necessary to assess the full potential of these chelators as a tool to enable further theranostic radiopharmaceutical development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".