MétaCan
Menu
Back to cohort

Cold atmospheric plasma as novel ‘drug’ for cancer therapy

2025· preprint· en· W4406414121 on OpenAlexaff
Danni Fu, Shiyao Lin, Qingnan Xu, Fei Cao, Israr Khan, Shuhua Xu, Zhenhua Li, Zhaowei Chen, Guojun Chen, Zejun Wang, Zhitong Chen

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsMcGill University
FundersBasic and Applied Basic Research Foundation of Guangdong ProvinceNational Key Research and Development Program of China
KeywordsDrugCancerAtmospheric-pressure plasmaCancer therapyPlasmaMedicinePharmacologyInternal medicinePhysics

Abstract

fetched live from OpenAlex

Plasma with low temperature generated at atmospheric pressure is known as cold atmospheric plasma (CAP). Owing to its unique characteristics and biological effects of inducing tumor cell death without endangering the surrounding healthy tissues, CAP is regarded as an emerging potent anticancer strategy and has been extensively investigated in preclinical research. In this review, we define the reactive species that play a major role in CAP as a novel “drug” (termed as plasma drug) used in cancer therapy. Various methods of plasma drug use in tumor treatment were summarized, mainly including plasma drug direct delivery, carriers for plasma drug, plasma drug synergistic immunotherapy, plasma drug in combination with nanoparticle therapy, plasma drug delivery with other anti-tumor drugs, and biomedical devices assisted plasma drug delivery. Furthermore, we provide prospective on the future development of plasma drug for cancer therapy. Plasma drug has the potential to evolve into a novel class of cancer therapy with continued technology improvements and multidisciplinary research efforts, providing patients with effective and individualized treatment alternatives (Scheme [1](#fig-cap-0001)).

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.495
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.032
GPT teacher head0.337
Teacher spread0.305 · 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 designNot applicable
Domainnot available
GenreOther

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

Explore more

Same topicPlasma Applications and DiagnosticsFrench-language works237,207