Evidence map›Paper›PMID 41625361›Full record

ReviewMaterials today. Bio2025

Nanotechnology-driven strategies for gene therapy of arthritis.

Shuo Wang, Yuequan Wang, Qin Chen

Abstract readReview
In one paragraph

Review in Materials today. Bio, 2025. 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
0cells of the map it votes in
0citing 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

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.

Shuo WangDepartment of Pharmacy, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, No. 44 Xiaoheyan Road, Dadong District, Shenyang, 110042, Liaoning Province, China.
Yuequan WangDepartment of Pharmaceutics, Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, Liaoning, 110016, China.
Qin ChenDepartment of Pharmacy, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, No. 44 Xiaoheyan Road, Dadong District, Shenyang, 110042, Liaoning Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Arthritis remains a major global health burden, driven by chronic inflammation and irreversible joint damage, with current treatments often failing to achieve sustained remission. Gene therapy offers a promising strategy to address the root molecular causes by reprogramming dysregulated immune responses and promoting tissue regeneration. However, clinical translation is limited by delivery inefficiency, off-target effects, and immunogenicity. Recent advances in genetic technologies, including RNA-based therapies, DNA-based strategies, and CRISPR-Cas9 gene editing, have broadened the therapeutic toolkit for precise and durable gene modulation. Concurrently, the integration of nanotechnology has enabled the development of smart delivery platforms, such as lipid nanoparticles, polymeric carriers, inorganic nanostructures, extracellular vesicles, membrane-coated systems, and DNA nanoframeworks, to overcome biological barriers and enhance gene transfection. Moreover, emerging therapeutic strategies targeting immune modulation, synovial macrophage reprogramming, inflammatory signaling, cartilage preservation and regeneration, and pain relief further expand the clinical potential. This review provides a comprehensive overview of the key genetic tools, nanoplatforms, and therapeutic approaches driving next-generation gene therapy for arthritis, highlighting a multidisciplinary path toward precise, effective, and long-lasting treatment.

Indexed as

ArthritisCRISPR-Cas9Gene therapyNanotechnologyTargeted drug delivery

Identifiers

PMID41625361
PMCPMC12859592

What OpenQuestion holds

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LicenceCC BY
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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.