Therapeutic enhancement effects using a lower energy 2.5 MV photon beam combined with gold nanoparticles on the BxPC-3 pancreatic cancer cell line, <i>in vitro</i>
Bibliographic record
Abstract
Abstract Objective. This study investigates the feasibility of using a clinically relevant lower energy 2.5 megavoltage (MV) photon beam in combination with gold nanoparticles (GNPs). Approach. Pancreatic cancer cell line, BxPC-3 impregnated with GNPs were exposed in vitro to 2.5 MV photon beam and compared with orthovoltage 225 kV and clinical 6 MV photon beam. Bare, 50 nm diameter, spherical GNPs were introduced in the cell culture 24 h prior to irradiation at a concentration of either 10 μg ml−1 or 50 μg ml−1. GNP uptake was determined using inductively coupled plasma optical emission spectroscopy. The cells were irradiated with doses between 0 Gy to 8 Gy. Cell survival curves were obtained via clonogenic assay using immediate or delayed plating (24 h) methods 12 d after irradiation. The terminal deoxynucleotidyl transferase dUTP nick end labeling assay was used to evaluate DNA damage at two time points post irradiation, immediate and 24 h for 1 Gy and 6 Gy. Main results. The enhancement factor (EF) in BxPC-3 cells was greatest for cells incubated with 50 μg ml−1 of GNPs analyzed immediately post irradiation. Cells irradiated with 225 kV showed greatest EF (1.57 ± 0.15), followed by 2.5 MV (1.51 ± 0.04). The lowest EF was seen for 6 MV, immediate plating (1.10 ± 0.04). A significant increase in the number of DNA double strand breaks (DSB) was observed in cells incubated with 50 μg ml−1 of GNPs irradiated at 6 Gy with 225 kV and 2.5 MV. There was no significant increase in DSBs for the cells irradiated with 6 MV. Significance. These results suggest that the 2.5 MV could be a compromise between an orthovoltage energy beam and a clinical 6 MV beam, showing comparable reduction in cell survival to the 225 kV beam. Future GNP radiation enhancement research may focus on intermediate energy beams.
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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) | 0.001 | 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 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".