Ligand exchange on gold nanoparticles for drug delivery and enhanced therapeutic index evaluated in acute myeloid leukemia models
Bibliographic record
Abstract
Cancer chemotherapy is typically toxic. This problem could be addressed by using differences between cancer and normal cells for controlled delivery of drugs to cancer cells. One such difference is the ubiquitously elevated glutathione expression in cancer cells. We report a simple and versatile synthesis of water-soluble gold nanoparticles passivated with amine-containing molecules, which allow for controlled drug release via ligand exchange with bio-available glutathione. Taking methotrexate-passivated gold nanoparticles (Au:MTX) as an example, drug delivery and controlled release via glutathione-mediated ligand exchange was evaluated. Furthermore, the possibility of using Au:MTX to improve therapeutic index in acute myeloid leukemia (AML) models was examined in vitro and in vivo. Au:MTX exhibited cancer selectivity in vitro. Au:MTX had an elevated potency toward an AML cell line THP-1 in a dosage range of 1-5 nM, and therefore an enhanced delivery of drug, whereas normal hematopoietic stem/progenitor cell (HSPC) growth was minimally affected by Au:MTX and MTX treatments within the same range of dosage. In vivo efficacy and safety of Au:MTX was evaluated in a murine xenotransplant model of primary human AML. Au:MTX treatment, compared to control groups including MTX-only and Au nanoparticle-only treatments, produced better leukemia suppression without added toxicity, indicating an enhanced therapeutic index.
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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) | 0.000 | 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 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".