Evidence map›Paper›PMID 39725635›Full record

ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2024

[AKBA combined with doxorubicin inhibits proliferation and metastasis of triple-negative breast cancer MDA-MB-231 cells and xenograft growth in nude mice].

Youqin Zeng, Siyu Chen, Yan Liu, Yitong Liu, Ling Zhang, Jiao Xia, Xinyu Wu, Changyou Wei, Ping Leng

Abstract readEnglish Abstract
PubMed Full text at PMC Publisher
In one paragraph

Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Youqin ZengCollege of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu 611130, China.
Siyu ChenCollege of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu 611130, China.
Yan LiuCollege of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu 611130, China.
Yitong LiuCollege of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu 611130, China.
Ling ZhangCollege of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu 611130, China.
Jiao XiaCollege of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu 611130, China.
Xinyu WuCollege of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu 611130, China.
Changyou WeiSchool of Public Health, Chengdu Medical College, Chengdu 610500, China.
Ping LengCollege of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu 611130, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate the synergistic inhibitory effects of AKBA and doxorubicin on malignant phenotype of triple-negative breast cancer (TNBC) MDA-MB-231 cells.

methodsCCK-8 assay was used to determine the 48-h IC

resultsThe IC

conclusionsAKBA combined with doxorubicin inhibits proliferation, migration and invasion, promotes apoptosis of MDA-MB-231 cells and suppresses MDA-MB-231 cell xenograft growth in nude mice. The combined use of AKBA can attenuate the toxic effects of doxorubicin in nude mice.

Indexed as

ApoptosisCell MovementCell ProliferationDoxorubicinMice, NudeTriple Negative Breast NeoplasmsXenograft Model Antitumor AssaysAnimalsCell Line, TumorDrug SynergismFemaleHumansMDA-MB-231 CellsMiceDoxorubicinacetyl-11-keto‑β‑boswellic acidAKBAdoxorubicintriple-negative breast cancer

Identifiers

PMID39725635
PMCPMC11683345

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.