Mechanistic insights into the impact of Cold Atmospheric Pressure Plasma on human epithelial cell lines
Bibliographic record
Abstract
Abstract Compelling evidence suggests that Cold Atmospheric Pressure Plasma (CAPP) has potential as a new cancer therapy. However, knowledge about cellular signaling events and toxicity subsequent to plasma treatment is still poorly documented. The aim of this study was to focus on the interaction between 3 different types of plasma (He, He-O 2 , He-N 2 ) and human epithelial cell lines to gain better insight into plasma-cell interaction. We provide evidence that reactive oxygen and nitrogen species (RONS) are inducing cell death by apoptosis and that the proteasome, a major intracellular proteolytic system which is important for tumor cell growth and survival, is a target of (He or He-N 2 ) CAPP. However, RONS are not the only actors involved in cell death; electric field and charged particles could play a significant role especially for He-O 2 CAPP. By differential label-free quantitative proteomic analysis we found that CAPP triggers antioxidant and cellular defense but is also affecting extracellular matrix in keratinocytes. Moreover, we found that malignant cells are more resistant to CAPP treatment than normal cells. Taken together, our findings provide insight into potential mechanisms of CAPP-induced proteasome inactivation and the cellular consequences of these events.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".