Radiolabeled nanomaterials for biomedical applications: radiopharmacy in the era of nanotechnology
Bibliographic record
Abstract
BACKGROUND: Recent advances in nanotechnology have offered new hope for cancer detection, prevention, and treatment. Nanomedicine, a term for the application of nanotechnology in medical and health fields, uses nanoparticles for several applications such as imaging, diagnostic, targeted cancer therapy, drug and gene delivery, tissue engineering, and theranostics. RESULTS: Here, we overview the current state-of-the-art of radiolabeled nanoparticles for molecular imaging and radionuclide therapy. Nanostructured radiopharmaceuticals of technetium-99m, copper-64, lutetium-177, and radium-223 are discussed within the scope of this review article. CONCLUSION: Nanoradiopharmaceuticals may lead to better development of theranostics inspired by ingenious delivery and imaging systems. Cancer nano-theranostics have the potential to lead the way to more specific and individualized cancer treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".