Evidence map›Paper›PMID 38891683›Full record

ArticleAnimals : an open access journal from MDPI2024

Enhancing the Anti-Tumor Efficacy of NK Cells on Canine Mammary Tumors through Resveratrol Activation.

Tingting Zhu, Shengzi Jin, Danning Tong, Xingyao Liu, Yun Liu, Jiasan Zheng

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

6 authors.

Tingting ZhuCollege of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China.
Shengzi JinCollege of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China.
Danning TongCollege of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China.
Xingyao LiuCollege of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China.
Yun LiuCollege of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China.
Jiasan ZhengCollege of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing 163000, China.

Funding

National Natural Resources Foundation of China 32172931National Natural Resources Foundation of China 32373083
6 · The paper itself

Abstract

In order to explore the therapeutic effect of Resveratrol (Res)-activated Natural Killer (NK) cells on canine mammary tumors, this study employed a range of assays, including wound healing, colony formation, Transwell, flow cytometry, and Western blot experiments, to investigate the impact of Res-pretreated NK cells on canine mammary tumor cells in vitro. Additionally, a tumor-bearing mouse model was utilized to further analyze the therapeutic effects of Res-pretreated NK cells in vivo. The results showed that Res enhances the capacity of NK cells to induce apoptosis, pyroptosis, and ferroptosis in canine breast tumor cells, while also augmenting their influence on the migration, invasion, and epithelial-mesenchymal transition of these cells. Furthermore, pretreatment of NK cells with Res significantly amplified their inhibitory effect on breast tumor growth in vivo and promoted tumor tissue apoptosis. Additionally, Res enhanced the recruitment of NK cells to other immune cells in the body. In summary, Res has been shown to enhance the anti-breast-tumor effect of NK cells both in vitro and in vivo, offering a new avenue for optimizing immunotherapy for canine breast tumors.

Indexed as

apoptosiscanine mammary tumorimmunotherapyNK cellsresveratrol

Identifiers

PMID38891683
PMCPMC11171074

What OpenQuestion holds

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Registered trials

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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.