Synthesis, characterisation and evaluation of a novel copper-64 complex with selective uptake in EMT-6 cells under hypoxic conditions
Bibliographic record
Abstract
The radiometal (64)Cu is now widely used in the development of diagnostic imaging agents for positron emission tomography (PET). The present study has led to the development and evaluation of a novel chelating agent for (64)Cu: the new monothiourea tripodal ligand 1-benzoyl-3-{6-[(bis-pyridin-2-ylmethyl-amino)-methyl]-pyridin-2-yl}-thiourea (MTUBo). X-ray crystallographic analysis has shown this ligand forms a mononuclear complex with copper(II) and co-ordinates via a trigonal bipyramidal N4S array of donor atoms. Promisingly, cell uptake studies revealed that (64)Cu-MTUBo selectively accumulates in EMT-6 cells incubated under hypoxic conditions which may result from its relatively high Cu(II/I) redox potential. Small-animal PET imaging and ex vivo biodistribution studies in EMT-6 tumor bearing BALB/c mice revealed significant tumor uptake after 1 h p.i., yielding tumor-to-muscle (T/M) and tumor-to-blood (T/B) ratios of 8.1 and 1.1, respectively. However, injection of (64)Cu-acetate resulted in similar uptake indicating that the observed uptake was most likely non-specific. Despite showing high in vitro stability, it is likely that in vivo the complex undergoes transchelation to proteins within the blood in a relatively short timeframe. For comparison, the hypoxia imaging agent (64)Cu-ATSM was also evaluated in the same murine tumor model and showed about 60% higher tumor uptake than (64)Cu-MTUBo.
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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) | 0.000 | 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".