The synergistic effect of Canady Helios cold atmospheric plasma and a FOLFIRINOX regimen for the treatment of cholangiocarcinoma in vitro
Bibliographic record
Abstract
Cholangiocarcinoma (CCA) is a rare biliary tract cancer with a low five-year survival rate and high recurrence rate after surgical resection. Currently treatment approaches include systemic chemotherapeutics such as FOLFIRINOX, a chemotherapy regimen is a possible treatment for severe CCA cases. A limitation of this chemotherapy regimen is its toxicity to patients and adverse events. There exists a need for therapies to alleviate the toxicity of a FOLFIRINOX regimen while enhancing or not altering its anticancer properties. Cold atmospheric plasma (CAP) is a technology with a promising future as a selective cancer treatment. It is critical to know the potential interactions between CAP and adjuvant chemotherapeutics. In this study the aim is to characterize the efficacy of FOLFIRINOX and CAP in combination to understand potential synergetic effect on CCA cells. FOLFIRINOX treatment alone at the highest dose tested (53.8 µM fluorouracil, 13.7 µM Leucovorin, 5.1 µM Irinotecan, and 3.7 µM Oxaliplatin) reduced CCA cell viability to below 20% while CAP treatment alone for 7 min reduced viability to 3% (p < 0.05). An analysis of cell viability, proliferation, and cell cycle demonstrated that CAP in combination with FOLFIRINOX is more effective than either treatment alone at a lower FOLFIRINOX dose of 6.7 µM fluorouracil, 1.7 µM leucovorin, 0.6 µM irinotecan, and 0.5 µM oxaliplatin and a shorter CAP treatment of 1, 3, or 5 min. In conclusion, CAP has the potential to reduce the toxicity burden of FOLFIRINOX and warrants further investigation as an adjuvant therapy.
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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".