In Vitro and In Vivo Radiotoxicity and Biodistribution of Thallium-201 Delivered to Cancer Cells by Prussian Blue Nanoparticles
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Thallium-201 ( t 1/2 = 73 h) emits around 37 Auger and other secondary electrons per decay and is highly radiotoxic when internalized into cancer cells. However, the lack of effective chelators hinders its application in molecular radiotherapy. This study evaluates Prussian blue nanoparticles, coated with citric acid ( 201 Tl-caPBNPs) or chitosan ( 201 Tl-chPBNPs), as a 201 Tl delivery vehicle compared with unbound 201 Tl + . Cellular uptake and efflux kinetics and radiotoxicity using clonogenic and γH2AX DNA damage assays were evaluated in vitro for both nanoparticle types. Subcellular localization was also assessed using electron microscopy with energy-dispersive X-ray spectroscopy. Biodistribution of 201 Tl-chPBNPs was evaluated in vivo in mice bearing subcutaneous A549 tumor xenografts, using single photon computed tomography imaging and ex vivo tissue counting. Compared with unbound 201 Tl +, 201 Tl-chPBNPs showed higher cellular uptake, while 201 Tl-caPBNP uptake was reduced. Both showed delayed efflux of 201 Tl from cancer cells. PBNPs prelocalized within cells enhanced the capture and retention of 201 Tl + ions. Both types of PBNPs accumulated in cytoplasmic vesicular compartments and were not visible in the nuclei. Furthermore, 201 Tl-radiolabeled chPBNPs but not 201 Tl-caPBNPs showed significantly greater radiotoxicity than unbound 201 Tl + per Becquerel of radiotoxicity provided in media, resulting from their higher uptake and delayed efflux. However, when corrected for the greater activity accumulated in cells and delayed efflux, the radiotoxicity of 201 Tl-chPBNPs was lower than that of unbound 201 Tl +, possibly due to differences in subcellular localization. These findings highlight the potential of chPBNPs for enhancing the uptake and retention of 201 Tl in cancer cells and development of targeted radionuclide therapy.
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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) | 0.000 | 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 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".