Utilizing Gold Nanoparticles as Prospective Radiosensitizers in 3D Radioresistant Pancreatic Co-Culture Model
Bibliographic record
Abstract
Pancreatic cancer stands among the deadliest forms of cancer, and the existing treatments fall short of providing adequate efficacy. Novel and more effective treatment approaches are urgently required to address this critical medical challenge. In this study, we aimed to evaluate the anti-cancer efficacy of gold nanoparticles (GNPs) in combination with radiotherapy (RT). A 3D pancreatic cancer co-culture spheroid model of MIA PaCa-2 cancer cells and patient-derived cancer-associated fibroblasts (CAF-98) was used. The spheroids were treated with GNPs (7.5 μg/mL) and 2 Gy of RT. The spheroids’ cell viability was assessed through the CellTiter-Glo 3D assay, and an immunofluorescence assay was used to assess the DNA DSBs via the expression of the DNA damage marker 53BP1. Co-culture samples showed a 10.8% (p < 0.05) increase in proliferation and a 13.0% (p < 0.05) decrease in DNA DSB when compared to monoculture samples, However, they displayed a 175% (p < 0.001) increase in GNPs uptake when compared to monoculture spheroids. Using GNPs/RT, we were able to show a significant reduction of 6.2% (p < 0.05) in spheroid size and an increase of 14.3% (p < 0.05) in DNA DSB damage in co-culture samples. The combination of GNPs with RT demonstrated remarkable radiosensitization effects, representing a promising approach to enhance cancer treatment efficacy. These effects were particularly noteworthy in the more treatment-resistant co-culture spheroid model.
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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 | 0.001 |
| 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".