Radioactive Main Group and Rare Earth Metals for Imaging and Therapy
Bibliographic record
Abstract
Radiometals possess an exceptional breadth of decay properties and have been applied to medicine with great success for several decades. The majority of current clinical use involves diagnostic procedures, which use either positron-emission tomography (PET) or single-photon imaging to detect anatomic abnormalities that are difficult to visualize using conventional imaging techniques (e.g., MRI and X-ray). The potential of therapeutic radiometals has more recently been realized and relies on ionizing radiation to induce irreversible DNA damage, resulting in cell death. In both cases, radiopharmaceutical development has been largely geared toward the field of oncology; thus, selective tumor targeting is often essential for efficacious drug use. To this end, the rational design of four-component radiopharmaceuticals has become popularized. This Review introduces fundamental concepts of drug design and applications, with particular emphasis on bifunctional chelators (BFCs), which ensure secure consolidation of the radiometal and targeting vector and are integral for optimal drug performance. Also presented are detailed accounts of production, chelation chemistry, and biological use of selected main group and rare earth radiometals.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".