Evidence map›Paper›PMID 42999738›Full record

ReviewPhenomics (Cham, Switzerland)2026

Muscle Organoids Frontier: Construction Strategies and Applications of Multi-lineage Muscle Organoids and Multi-organoid Systems.

Dingding Wang, Lining Xu, Weijia Liu, Zitong Xie, Yuqing Sun, Mingxing Fan, Ling Wang, Quanzhong Ren, Yajun Liu, Junbo Liang and 1 more

Abstract readReview
In one paragraph

Review in Phenomics (Cham, Switzerland), 2026. 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

11 authors.

Dingding Wang *JST Sarcopenia Research Centre, Beijing Research Institute of Traumatology and Orthopaedics, National Center for Orthopaedics, Beijing Jishuitan Hospital, Capital Medical University, Beijing, 100035 China.ORCID 0000-0003-1529-3152
Lining Xu *JST Sarcopenia Research Centre, Beijing Research Institute of Traumatology and Orthopaedics, National Center for Orthopaedics, Beijing Jishuitan Hospital, Capital Medical University, Beijing, 100035 China.
Weijia LiuJST Sarcopenia Research Centre, Beijing Research Institute of Traumatology and Orthopaedics, National Center for Orthopaedics, Beijing Jishuitan Hospital, Capital Medical University, Beijing, 100035 China.
Zitong XieState Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry and Molecular Biology, Institute of Basic Medical Sciences & School of Basic Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005 China.
Yuqing SunDepartment of Spine Surgery, Beijing Jishuitan Hospital, National Center for Orthopaedics, Capital Medical University, Beijing, 100035 China.
Mingxing FanDepartment of Spine Surgery, Beijing Jishuitan Hospital, National Center for Orthopaedics, Capital Medical University, Beijing, 100035 China.
Ling WangDepartment of Radiology, Beijing Jishuitan Hospital, Capital Medical University, National Center for Orthopaedics, Beijing, 100035 China.
Quanzhong RenJST Sarcopenia Research Centre, Beijing Research Institute of Traumatology and Orthopaedics, National Center for Orthopaedics, Beijing Jishuitan Hospital, Capital Medical University, Beijing, 100035 China.
Yajun LiuJST Sarcopenia Research Centre, Beijing Research Institute of Traumatology and Orthopaedics, National Center for Orthopaedics, Beijing Jishuitan Hospital, Capital Medical University, Beijing, 100035 China.
Junbo LiangState Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry and Molecular Biology, Institute of Basic Medical Sciences & School of Basic Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005 China.ORCID 0000-0001-6230-1421
Renxian WangJST Sarcopenia Research Centre, Beijing Research Institute of Traumatology and Orthopaedics, National Center for Orthopaedics, Beijing Jishuitan Hospital, Capital Medical University, Beijing, 100035 China.ORCID 0000-0002-3330-2895

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, multi-lineage muscle organoids have rapidly emerged as transformative research tools, providing high-fidelity models for deciphering skeletal muscle development and the pathological mechanisms of muscle diseases such as sarcopenia, amyotrophic lateral sclerosis, and myasthenia gravis. Primarily derived from pluripotent stem cells, these organoids integrate multiple functional lineages, such as skeletal muscle, neural, vascular, and skeletal components, thereby addressing the limitations of conventional single-tissue muscle models. In parallel, multi-organoid systems, such as assembloids and organ-on-a-chip platforms, further integrate distinct organoids (e.g., muscle, skeletal tissue, tendon, and hindbrain/cervical spinal cord) to reconstruct inter-organ communication and systemic physiology under physiologically relevant conditions. By recapitulating in vivo-like multi-tissue interactions, they serve as critical platforms for drug screening and therapeutic development. This review summarizes recent advances in multi-lineage muscle organoids and multi-organoid systems, outlining their cellular sources, construction strategies, and major applications in basic research, disease modeling, and drug discovery, and discusses current challenges and future directions to enhance their potential in muscle research. Graphical Abstract:

Indexed as

Multi-lineage muscle organoidsMulti-organoid systemsMuscular disease modelingPluripotent stem cells

Identifiers

PMID42999738
PMCPMC13743665

What OpenQuestion holds

Textmetadata
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.