Evidence map›Paper›PMID 40519684›Full record

ArticleRSC advances2025

Nano-delivery of miRNA inhibiting CENPF combined with cisplatin for bladder cancer treatment.

Ruixiang Song, Xin Chen, Zhensheng Zhang, Huiqing Wang, Guanghua Chen, Jinshan Xu, Shuxiong Zeng, Wentao Zhang, Xudong Yao

Abstract read
In one paragraph

Article in RSC advances, 2025. 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. 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

9 authors.

Ruixiang SongDepartment of Urology, Shanghai Tenth People's Hospital, Tongji University Shanghai 200072 China.ORCID https://orcid.org/0009-0008-6368-8814
Xin ChenDepartment of Urology, Zhejiang Qiushi Cardiovascular Hospital Hangzhou 310011 China.
Zhensheng ZhangDepartment of Urology, Changhai Hospital, Naval Medical University Shanghai 200433 China.
Huiqing WangDepartment of Urology, Changhai Hospital, Naval Medical University Shanghai 200433 China.
Guanghua ChenDepartment of Urology, Changhai Hospital, Naval Medical University Shanghai 200433 China.
Jinshan XuDepartment of Urology, Changhai Hospital, Naval Medical University Shanghai 200433 China.
Shuxiong ZengDepartment of Urology, Changhai Hospital, Naval Medical University Shanghai 200433 China.
Wentao ZhangDepartment of Urology, Shanghai Tenth People's Hospital, Tongji University Shanghai 200072 China.
Xudong YaoDepartment of Urology, Shanghai Tenth People's Hospital, Tongji University Shanghai 200072 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bladder cancer (BCa) presents a substantial global health burden, with high rates of recurrence and metastasis that limit the effectiveness of current therapies. New therapeutic strategies are urgently needed. This study introduces a novel nanotherapeutic approach utilizing polydopamine (PDA) nanoparticles to co-deliver cisplatin and miR-205-5p for BCa treatment. Combination therapy reduces the dose-dependent toxicity of cisplatin while enhancing tumor cell cytotoxicity. miR-205-5p targets centromere protein F (CENPF), a key regulator of cancer progression. Overexpression of CENPF in BCa correlates with poor prognosis, and miR-205-5p-mediated suppression of CENPF expression inhibits tumor growth. The PDA-based system combines the DNA-damaging effects of cisplatin with the gene-silencing properties of miR-205-5p, resulting in synergistic antitumor activity. This multimodal strategy enhances therapeutic precision and efficacy, providing a promising solution for BCa treatment with significant clinical potential.

Identifiers

PMID40519684
PMCPMC12163902

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.