Evidence map›Paper›PMID 42461917›Full record

ArticlePloS one2026

Characterization and functional analysis of miRNAs in Salvia miltiorrhiza-isolated exosome-like nanoparticles for gastric cancer treatment.

Gang Chen, Qinjuan Zhong, Ning Tang

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Gang ChenDepartment of Spleen and Gastroenterology, Shaoxing city Keqiao District Hospital of traditional Chinese Medicine, Shaoxing, Zhejiang, People's Republic of China.ORCID https://orcid.org/0009-0007-5162-3274
Qinjuan ZhongDepartment of Spleen and Gastroenterology, Shaoxing city Keqiao District Hospital of traditional Chinese Medicine, Shaoxing, Zhejiang, People's Republic of China.
Ning TangDepartment of Spleen and Gastroenterology, Shaoxing city Keqiao District Hospital of traditional Chinese Medicine, Shaoxing, Zhejiang, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGastric cancer (GC) is a widespread global malignancy, frequently diagnosed at advanced stages owing to the subtle nature of early symptoms and low screening rates. Consequently, there is an imperative need to investigate innovative strategies for the treatment of GC. Exosomes, originating from various sources, act as natural nanocarriers enriched with numerous bioactive molecules, showcasing potential as groundbreaking treatments for GC. MATERIALS AND

methodsIn the present study, exosome-like nanoparticles (ELNs) were successfully purified from Salvia miltiorrhiza Bunge (Danshen) utilizing ultracentrifugation. The impact of these ELNs on human gastric cancer cells (HGC-27) was evaluated via a suite of viability assays, encompassing CCK-8, colony formation, flow cytometry, transwell migration, and wound healing assays. Furthermore, miRNA sequencing was conducted to identify and analyze the highly abundant miRNA within Danshen-derived ELNs, along with its potential biological functions.

resultsThe HGC-27 cells internalized Danshen-derived ELNs (DS-ELNs), which led to a decrease in cell viability. Concurrently, these ELNs exhibited significant inhibitory effects on cell migration, colony formation, and overall progression of GC in vitro. The functional analysis of the miRNAs harbored by these ELNs indicated that they may serve as a potential therapeutic target for GC.

conclusionIn summary, these findings have not only comprehensively characterized the miRNAs present in Danshen-derived exosomes but also provided invaluable insights into the molecular mechanisms by which Danshen exerts its effects in mitigating.

Indexed as

ExosomesMicroRNAsNanoparticlesSalvia miltiorrhizaStomach NeoplasmsCell Line, TumorCell MovementCell ProliferationCell SurvivalHumansMicroRNAs

Identifiers

PMID42461917
PMCPMC13375030

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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.