<sup>225</sup>Ac-H<sub>4</sub>py4pa for Targeted Alpha Therapy
Bibliographic record
Abstract
Herein, we present the syntheses and characterization of a new undecadendate chelator, H 4 py4pa, and its bifunctional analog H 4 py4pa-phenyl-NCS, conjugated to the monoclonal antibody, Trastuzumab, which targets the HER2+ cancer. H 4 py4pa possesses excellent affinity for 225 Ac (α, t 1/2 = 9.92 d) for targeted alpha therapy (TAT), where quantitative radiolabeling yield was achieved at ambient temperature, pH = 7, in 30 min at 10 –6 M chelator concentration, leading to a complex highly stable in mouse serum for at least 9 d. To investigate the chelation of H 4 py4pa with large metal ions, lanthanum (La 3+ ), which is the largest nonradioactive metal of the lanthanide series, was adopted as a surrogate for 225 Ac to enable a series of nonradioactive chemical studies. In line with the 1 H NMR spectrum, the DFT (density functional theory)-calculated structure of the [La(py4pa)] − anion possessed a high degree of symmetry, and the La 3+ ion was secured by two distinct pairs of picolinate arms. Furthermore, the [La(py4pa)] − complex also demonstrated a superb thermodynamic stability (log K [La(py4pa)] – ∼ 20.33, pLa = 21.0) compared to those of DOTA (log K [La(DOTA)] – ∼ 24.25, pLa = 19.2) or H 2 macropa (log K [La(macropa)] – = 14.99, pLa ∼ 8.5). Moreover, the functional versatility offered by the bifunctional py4pa precursor permits facile incorporation of various linkers for bioconjugation through direct nucleophilic substitution. In this work, a short phenyl-NCS linker was incorporated to tether H 4 py4pa to Trastuzumab. Radiolabeling studies, in vitro serum stability, and animal studies were performed in parallel with the DOTA-benzyl-Trastuzumab. Both displayed excellent in vivo stability and tumor specificity.
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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) | 0.003 | 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".