H<sub>4</sub>octox: Versatile Bimodal Octadentate Acyclic Chelating Ligand for Medicinal Inorganic Chemistry
Bibliographic record
Abstract
H 4 octox, a versatile new octadentate acyclic chelating ligand, has been investigated as an alternative to the acyclic DTPA and the macrocyclic DOTA for trivalent metal ions useful in diagnostic medical imaging or therapeutic applications (Y 3+, In 3+, La 3+, Gd 3+, Lu 3+ ). The synthesis of H 4 octox is straightforward in less steps and thus more economical than those of most previously reported chelators. Complex formation equilibria in the presence of Y 3+, In 3+, La 3+, Gd 3+, and Lu 3+ revealed fast chelation and high metal-sequestering capacity. Quantitative labeling with 111 In 3+ was achieved within 15 min at room temperature at ligand concentrations as low as 10 –7 M, exactly the properties required for the development of kit-based radiopharmaceuticals. In vitro serum stability studies and in vivo SPECT imaging confirmed excellent complex stability of [ 111 In(octox)] − . Moreover, it is more lipophilic than most of the multidentate carboxylate- or picolinate-based chelators; it therefore shows more liver clearance and provides a complementary choice in the design of metal-based pharmaceuticals and in the tuning of their pharmacokinetic properties. Finally, H 4 octox showed a large fluorescence enhancement upon complexation with different metals, in particular, with Y 3+ and Lu 3+, which could be useful for non-radioactive fluorescent stability and cell studies as well as bimodal imaging. Excellent in vitro stability of [Y(octox)] − against transferrin and Fe 3+ was confirmed employing this fluorescence.
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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) | 0.002 | 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".