Evidence map›Paper›PMID 41836719›Full record

ReviewInternational journal of nanomedicine2026

Nanoparticles in the Treatment of Renal Fibrosis.

Ying Wu, Wen Zhang, Li'ou Zhu, Lili Liu

Abstract readReview
In one paragraph

Review in International journal of nanomedicine, 2026. 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

4 authors.

Ying WuDepartment of Pathology, Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430016, People's Republic of China.
Wen ZhangDepartment of Pathology, Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430016, People's Republic of China.
Li'ou ZhuDepartment of Pathology, Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430016, People's Republic of China.
Lili LiuDepartment of Pathology, Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430016, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Renal fibrosis represents a key pathological hallmark of chronic kidney disease (CKD), a prevalent condition worldwide that currently lacks effective therapies. Nanotechnology offers transformative potential for renal fibrosis treatments. Engineered nanoparticles (NPs), with tunable physicochemical properties such as size, surface charge, and shape, enable targeted and controlled drug delivery. Furthermore, active targeting strategies can increase nanoparticle uptake by specific cell types or structures in kidneys. Although nanomedicine-based strategies for renal fibrosis remain at an early, predominantly preclinical stage, accumulating evidence from experimental models suggests substantial potential for improving therapeutic precision and efficacy in fibrotic kidney disease. This review integrates recent insights into the pathogenesis of renal fibrosis, NP design strategies, along with advances in NP-based therapeutics, highlighting nanomedicine as a promising approach for precise and effective intervention in CKD-associated renal fibrosis.

Indexed as

Nanoparticle Drug Delivery SystemNanoparticlesRenal Insufficiency, ChronicAnimalsDrug Delivery SystemsFibrosisHumansKidneyNanomedicineNanoparticle Drug Delivery Systemchronic kidney diseasedrug deliverynanomedicineNPsrenal fibrosis

Identifiers

PMID41836719
PMCPMC12988763

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.