Synergistic enhancement of cell death by triple combination therapy of docetaxel, ultrasound and microbubbles, and radiotherapy on PC3 a prostate cancer cell line
Bibliographic record
Abstract
The application of ultrasound and microbubbles (USMB) has been shown to enhance both chemotherapy and radiotherapy. This study investigated the potential of triple combination therapy comprised of USMB, docetaxel (Taxotere: TXT) chemotherapy and XRT to enhance treatment efficacy. Prostate cancer (PC3) cells in suspension were treated with various combinations of USMB, chemotherapy and radiotherapy. Cells were treated with ultrasound and microbubbles (500 kHz pulse center frequency, 580 kPa peak negative pressure, 10 μs pulse duration, 60 s insonation time and 2% Definity microbubbles (v/v)), XRT (2 Gy), and Taxotere (TXT) at concentrations ranging from 0.001 to 0.1 nM for 5- and 120-minutes duration. Following treatment, cell viability was assessed using a clonogenic assay. Therapeutic efficiency of the combined treatments depended on chemotherapy and microbubble exposure conditions. Under the exposure conditions of the study, the triple combination therapy synergistically enhanced clonogenic cell death compared to single and double combination therapy. Cell viability of ∼2% was achieved with the triple combination therapy corresponding to ∼29, ∼37, and ∼38 folds decrease compared to XRT (57%), USMB (74%) and TXT (76%) alone conditions, respectively. In addition, the triple combination therapy decreased cell viability by ∼29, ∼19- and ∼11 folds compared to TXT 2hr + USMB (58%), TXT 2hr + XRT (37%), and USMB + XRT (22%), respectively. The in vivo PC3 tumours showed that USMB significantly enhanced cell death through detection of apoptosis (TUNEL) with both TXT and TXT + XRT. The study demonstrated that the triple combination therapy can significantly enhance cell death in prostate cancer cells both in vitro and in vivo under relatively low chemotherapy and ionizing radiation doses.
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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".