Evidence map›Paper›PMID 39282063›Full record

ReviewRSC advances2024

Magnetic nanoparticles and possible synergies with cold atmospheric plasma for cancer treatment.

Xiaofeng Dai, Yilin Dai, Yan Zheng, Yi Lv

Abstract readReview
In one paragraph

Review in RSC advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xiaofeng DaiNational Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, Shaanxi Provincial Center for Regenerative Medicine and Surgical Engineering, The First Affiliated Hospital of Xi'an Jiaotong University Xi'an 710061 PR China.ORCID https://orcid.org/0000-0001-5323-7886
Yilin DaiDepartment of Dermatology, The First Affiliated Hospital of Xi'an Jiaotong University Xi'an 710061 PR China xiaofengteam@163.com.
Yan ZhengDepartment of Dermatology, The First Affiliated Hospital of Xi'an Jiaotong University Xi'an 710061 PR China xiaofengteam@163.com.
Yi LvNational Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, Shaanxi Provincial Center for Regenerative Medicine and Surgical Engineering, The First Affiliated Hospital of Xi'an Jiaotong University Xi'an 710061 PR China.ORCID https://orcid.org/0000-0003-3636-6664

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The biomedical applications of magnetic nanoparticles (MNPs) have gained increasing attention due to their unique biological, chemical, and magnetic properties such as biocompatibility, chemical stability, and high magnetic susceptibility. However, several critical issues still remain that have significantly halted the clinical translation of these nanomaterials such as the relatively low therapeutic efficacy, hyperthermia resistance, and biosafety concerns. To identify innovative approaches possibly creating synergies with MNPs to resolve or mitigate these problems, we delineated the anti-cancer properties of MNPs and their existing onco-therapeutic portfolios, based on which we proposed cold atmospheric plasma (CAP) to be a possible synergizer of MNPs by enhancing free radical generation, reducing hyperthermia resistance, preventing MNP aggregation, and functioning as an innovative magnetic and light source for magnetothermal- and photo-therapies. Our insights on the possible facilitating role of CAP in translating MNPs for biomedical use may inspire fresh research directions that, once actualized, gain mutual benefits from both.

Identifiers

PMID39282063
PMCPMC11391930

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.