Evidence map›Paper›PMID 38791285›Full record

ArticleInternational journal of molecular sciences2024

Combinatory Nanovesicle with siRNA-Loaded Extracellular Vesicle and IGF-1 for Osteoarthritis Treatments.

Jun Yong Kim, Seung Yeon Lee, Seung-Gyu Cha, Jung Min Park, Duck Hyun Song, Sang-Hyuk Lee, Dong-Youn Hwang, Byoung Ju Kim, Seungsoo Rho, Chun Gwon Park and 2 more

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Review
  9. 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

12 authors.

Jun Yong KimDepartment of Biomedical Science, CHA University, 335 Pangyo-ro, Bundang-gu, Seongnam-si 13488, Republic of Korea.ORCID 0000-0001-8659-6623
Seung Yeon LeeDepartment of Biomedical Science, CHA University, 335 Pangyo-ro, Bundang-gu, Seongnam-si 13488, Republic of Korea.
Seung-Gyu ChaDepartment of Biomedical Science, CHA University, 335 Pangyo-ro, Bundang-gu, Seongnam-si 13488, Republic of Korea.
Jung Min ParkDepartment of Biomedical Science, CHA University, 335 Pangyo-ro, Bundang-gu, Seongnam-si 13488, Republic of Korea.
Duck Hyun SongDepartment of Biomedical Science, CHA University, 335 Pangyo-ro, Bundang-gu, Seongnam-si 13488, Republic of Korea.ORCID 0000-0003-3818-6165
Sang-Hyuk LeeDepartment of Biomedical Science, CHA University, 335 Pangyo-ro, Bundang-gu, Seongnam-si 13488, Republic of Korea.
Dong-Youn HwangDepartment of Biomedical Science, CHA University, 335 Pangyo-ro, Bundang-gu, Seongnam-si 13488, Republic of Korea.
Byoung Ju KimATEMs, Jeongui-ro 8-gil, Songpa-gu, Seoul-si 05836, Republic of Korea.
Seungsoo RhoDepartment of Ophthalmology, CHA Bundang Medical Center, CHA University, Seongnam-si 13496, Republic of Korea.
Chun Gwon ParkDepartment of Biomedical Engineering, SKKU Institute for Convergence, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon-si 16419, Republic of Korea.ORCID 0000-0002-8926-3418
Won-Kyu RhimDepartment of Biomedical Science, CHA University, 335 Pangyo-ro, Bundang-gu, Seongnam-si 13488, Republic of Korea.ORCID 0000-0002-8711-1672
Dong Keun HanDepartment of Biomedical Science, CHA University, 335 Pangyo-ro, Bundang-gu, Seongnam-si 13488, Republic of Korea.ORCID 0000-0003-4641-7883

Funding

Korean Fund for Regenerative Medicine 23A0206L1National Research Foundation of Korea 2022R1I1A1A01068486National Research Foundation of Korea 2023R1A2C3003807
6 · The paper itself

Abstract

Extracellular vesicles (EVs) have been found to have the characteristics of their parent cells. Based on the characteristics of these EVs, various studies on disease treatment using mesenchymal stem cell (MSC)-derived EVs with regenerative activity have been actively conducted. The therapeutic nature of MSC-derived EVs has been shown in several studies, but in recent years, there have been many efforts to functionalize EVs to give them more potent therapeutic effects. Strategies for functionalizing EVs include endogenous and exogenous methods. In this study, human umbilical cord MSC (UCMSC)-derived EVs were selected for optimum OA treatments with expectation via bioinformatics analysis based on antibody array. And we created a novel nanovesicle system called the IGF-si-EV, which has the properties of both cartilage regeneration and long-term retention in the lesion site, attaching positively charged insulin-like growth factor-1 (IGF-1) to the surface of the UCMSC-derived Evs carrying siRNA, which inhibits MMP13. The downregulation of inflammation-related cytokine (MMP13, NF-kB, and IL-6) and the upregulation of cartilage-regeneration-related factors (Col2, Acan) were achieved with IGF-si-EV. Moreover, the ability of IGF-si-EV to remain in the lesion site for a long time has been proven through an ex vivo system. Collectively, the final constructed IGF-si-EV can be proposed as an effective OA treatment through its successful MMP13 inhibition, chondroprotective effect, and cartilage adhesion ability. We also believe that this EV-based nanoparticle-manufacturing technology can be applied as a platform technology for various diseases.

Indexed as

Extracellular VesiclesInsulin-Like Growth Factor IMesenchymal Stem CellsOsteoarthritisRNA, Small InterferingAnimalsHumansMatrix Metalloproteinase 13IGF1 protein, humanInsulin-Like Growth Factor IMatrix Metalloproteinase 13RNA, Small Interferingbioinformaticsextracellular vesicles (EVs)IGF-1mesenchymal stem cell (MSC)osteoarthritis (OA)siRNA

Identifiers

PMID38791285
PMCPMC11121733

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.