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Record W4414287535 · doi:10.14740/wjon2579

Liquid Plasma Induces Necroptosis Without Inflammatory Responses in Head and Neck Cancer Cells

2025· article· en· W4414287535 on OpenAlexvenueno aff
Jae Hoon Choi, Sungryeal Kim, Yun Sang Lee, Young Suk You, Jeon Yeob Jang, Yoo Seob Shin, Chul‐Ho Kim

Bibliographic record

VenueWorld Journal of Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsnot available
FundersKorea Health Industry Development InstituteMinistry of Education, IndiaMinistry of Environment
KeywordsNecroptosisHead and neck cancerInflammationLiquid biopsyNecrosisHead and neckCancer cell

Abstract

fetched live from OpenAlex

Background: Several types of regulated cell deaths are known, including apoptosis, necroptosis, autophagy, ferroptosis, and pyroptosis. Among these types of cell deaths, apoptosis is induced by many cancer therapeutic agents. In the case of resistance, however, induction of other regulated cell death, such as necroptosis, are required. Liquid plasma, which is prepared by treatment of non-thermal plasma to solution, induces various types of regulated cell death via reactive oxygen and nitrogen species. Methods: Liquid plasma was generated by N2/Ar plasma treatment in culture medium (minimum essential medium (MEM), Dulbecco’s modified Eagle medium (DMEM), or Roswell Park Memorial Institute (RPMI)-1640) for 120 s per milliliter of medium (2 cm). Cell viability was determined using Cell Counting Kit-8 (CCK8), and apoptosis was determined by terminal deoxynucleotidyl transferase deoxyuridine triphosphate (dUTP) nick end labeling (TUNEL) assay. Tumor necrosis factor alpha (TNF-α), cycloheximide (CHX), and zVAD-fmk were used to induce necroptosis in head and neck squamous cell carcinoma (HNSCC) cells, and necroptosis inhibitors, such as necrostatin-1 (Nec-1, 50 µM), GSK872 (10 µM), and necrosulfonamide (NSA, 2 µM) were used to inhibit necroptosis. Statistical comparisons between groups were carried out using the Student’s t-test. Results: Here, we determined the type of cell death induced by liquid plasma in head and neck cancer (HNC) cells. Our results show that liquid plasma caused necroptosis in HNC cells, and peroxynitrite in the liquid plasma might be involved in the cell death. The expression of inflammation-related molecules, including nuclear factor kappa B (NF-κB), interleukin (IL)-6, and mitochondrial antiviral signaling proteins, were detected in HNC cells, and treatment of HNC cells with liquid plasma decreased their expression. Conclusions: These results suggest that liquid plasma could be used to treat HNC by inducing necroptosis without inflammatory responses. In this study, we demonstrated that liquid plasma treatment may kill HNC cells without causing necroptosis-induced inflammation and inflammation-mediated diseases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.346
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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