Thio-glucose bound gold nanoparticles enhance radio-cytotoxic targeting of ovarian cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The treatment of ovarian cancer has traditionally been intractable, and required novel approaches to improve therapeutic efficiency. This paper reports that thio-glucose bound gold nanoparticles (Glu-GNPs) can be used as a sensitizer to enhance ovarian cancer radiotherapy. The human ovarian cancer cells, SK-OV-3, were treated by gold nanoparticles (GNPs) alone, irradiation alone, or GNPs in addition to irradiation. Cell uptake was assayed using inductively coupled plasma atomic emission spectroscopy (ICP-AES), while cytotoxicity induced by radiotherapy was measured using both 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di-phenytetrazoliumromide and clonogenic assays. The presence of reactive oxygen species (ROS) was determined using CM-H2-DCFDA confocal microscopy and cell apoptosis was determined by an Annexin V-FITC/propidium iodide (PI) kit with flow cytometry. The cells treated by Glu-GNPs resulted in an approximate 31% increase in nanoparticle uptake compared to naked GNPs (p < 0.005). Compared to the irradiation alone treatment, the intracellular uptake of Glu-GNPs resulted in increased inhibition of cell proliferation by 30.48% for 90 kVp and 26.88% for 6 MV irradiation. The interaction of x-ray radiation with GNPs induced elevated levels of ROS production, which is one of the mechanisms by which GNPs can enhance radiotherapy on ovarian cancer.
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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 | 0.000 | 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) | 0.001 | 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 it