Evidence map›Paper›PMID 39595531›Full record

ReviewBiomolecules2024

Advancements in Research on Mesenchymal Stem-Cell-Derived Exosomal miRNAs: A Pivotal Insight into Aging and Age-Related Diseases.

Minglei Huang, Ye Liu, Longze Zhang, Shuangmin Wang, Xianyao Wang, Zhixu He

Abstract readReview
In one paragraph

Review in Biomolecules, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Review
  6. 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

6 authors.

Minglei HuangDepartment of Immunology, Zunyi Medical University, Zunyi 563000, China.
Ye LiuDepartment of Immunology, Zunyi Medical University, Zunyi 563000, China.ORCID 0009-0004-6327-9413
Longze ZhangScientific Research Center, The First People's Hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), Zunyi 563000, China.
Shuangmin WangDepartment of Immunology, Zunyi Medical University, Zunyi 563000, China.
Xianyao WangDepartment of Immunology, Zunyi Medical University, Zunyi 563000, China.ORCID 0000-0002-1742-2045
Zhixu HeCollaborative Innovation Center of Tissue Damage Repair and Regeneration Medicine, Zunyi Medical University, Zunyi 563000, China.

Funding

Xianyao Wang 82360044Xianyao Wang Qian Ke He Ji Chu-ZK[2022]-607Xianyao Wang Qian Ke He Ji Chu-ZK[2024]-269Xianyao Wang Qian Ke Ping Tai Ren Cai 2020-032Zhixu He 2020-39Zhixu He 32270848
6 · The paper itself

Abstract

Mesenchymal stem cells (MSCs) are capable of differentiating into various cell types and play a crucial role in repairing aging tissues and diseased organs. Aging manifests as a gradual loss of cellular, tissue, and organ function, leading to the progression of pathologies. Exosomes (Exos) are extracellular vesicles secreted by cells, which maintain cellular homeostasis, clear cellular debris, and facilitate communication between cells and organs. This review provides a comprehensive summary of the mechanisms for the synthesis and sorting of MSC-Exo miRNAs and summarizes the current research status of MSCs-Exos in mitigating aging and age-related diseases. It delves into the underlying molecular mechanisms, which encompass antioxidative stress, anti-inflammatory response, and the promotion of angiogenesis. Additionally, this review also discusses potential challenges in and future strategies for advancing MSC-Exo miRNA-based therapies in the treatment of aging and age-related diseases.

Indexed as

AgingExosomesMesenchymal Stem CellsMicroRNAsAnimalsHumansMicroRNAsagingaging-related diseasesexosomesmesenchymal stem cellsmiRNAs

Identifiers

PMID39595531
PMCPMC11592330

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.