Rearmed Bifunctional Chelating Ligand for <sup>225</sup>Ac/<sup>155</sup>Tb Precision-Guided Theranostic Radiopharmaceuticals─H<sub>4</sub>noneunpaX
Bibliographic record
Abstract
Superior bifunctional chelating ligands, which can sequester both α-emitting radionuclides ( 225 Ac, 213 Bi) and their diagnostic companions ( 155 Tb, 111 In), remain a formidable challenge to translating targeted alpha therapy, with complementary diagnostic imaging, to the clinic. H 4 noneupaX, a chelating ligand with an unusual diametrically opposed arrangement of pendant donor groups, has been developed to this end. H 4 noneunpaX preferentially complexes Ln 3+ and An 3+ ions, forming thermodynamically stable (pLa = 17.8, pLu = 21.3) and kinetically inert complexes─single isomeric species by nuclear magnetic resonance and density functional theory. Metal binding versatility demonstrated in radiolabeling [ 111 In]In 3+, [ 155 Tb]Tb 3+, [ 177 Lu]Lu 3+, and [ 225 Ac]Ac 3+ achieved high molar activities under mild conditions. Efficient, scalable synthesis enabled in vivo evaluation of bifunctional H 4 noneunpaX conjugated to two octreotate peptides targeting neuroendocrine tumors. Single photon emission computed tomography/CT and biodistribution studies of 155 Tb-radiotracers in AR42J tumor-bearing mice showed excellent image contrast, good tumor uptake, and high in vivo stability. H 4 noneunpaX shows significant potential for theranostic applications involving 225 Ac/ 155 Tb or 177 Lu/ 155 Tb.
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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".