Differential toxicity of gold-doxorubicin in cancer cells <i>vs.</i> cardiomyocytes as measured by real-time growth assays and fluorescence lifetime imaging microscopy (FLIM)
Bibliographic record
Abstract
The kinetics of toxicity of doxorubicin (Dox) and gold nanoparticle-conjugated doxorubicin (Au-Dox) were investigated in cultured B16 melanoma cells and cardiomyocytes using real-time cell-growth imaging. Both bolus exposure and continuous exposure were used. Modeling of the growth curve dynamics suggested patterns of uptake and/or expulsion of the drug that were different for the different cell lines and exposures. Dox alone in B16 cells fit to a model of slow drug buildup, whereas Au-Dox fit to a pattern of initial high drug efficacy followed by a decrease. In cardiomyocytes, the best fit was to a model of increasing drug concentration which then began to decrease, consistent with breakdown of the doxorubicin in solution. Cardiomyocytes were more sensitive than B16 cells to Dox alone (IC50 123 ± 2 nM vs. 270 ± 2 nM with continuous exposure), but were dramatically less sensitive to Au-Dox (IC50 1 ± 0.1 μM vs. 58 ± 5 nM with continuous exposure). Bolus exposure for 40 min led to significant cell death in B16 cells but not in cardiomyocytes. Fluorescence lifetime imaging (FLIM) showed different patterns of uptake of Au-Dox in the two cell types that explained the differential toxicity. While Au-Dox concentrated in the nuclei of B16 cells, it remained endosomal in cardiomyocytes. These results suggest that stable conjugates of nanoparticles to doxorubicin may be useful for treating resistant cancers while sparing healthy tissue.
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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) | 0.001 | 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".