ReviewCell biochemistry and biophysics2026
"Stem Cells in Regenerative Medicine: from Discovery and Molecular Mechanisms To Therapeutic Applications and Clinical Challenges".
Review in Cell biochemistry and biophysics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Organoid models: applications and research advances in gastric cancer.Frontiers in oncology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stem cells possess the unique ability to self-renew and differentiate, making them central to regenerative medicine and disease modeling. They are classified by developmental potential into totipotent, pluripotent, multipotent, oligopotent, and unipotent types, and by origin as embryonic, adult, induced pluripotent stem cells (iPSCs), mesenchymal stem cells (MSCs), and tissue-specific populations such as bronchioalveolar stem cells (BASCs). Advances in reprogramming methods—including Yamanaka factors, chemical and mRNA-based approaches, and non-integrating viral systems—have enabled the generation of iPSCs with applications in personalized therapy, immunology, and organ regeneration. Core transcriptional networks, particularly OCT4, SOX2, and NANOG, along with epigenetic regulation, govern pluripotency and lineage specification. Recent integration of artificial intelligence has further enhanced stem cell analysis, accelerating drug discovery and disease modeling. However, major challenges remain, including low survival rates post-transplantation, inaccurate differentiation, tumorigenicity, and delivery-related safety risks. Emerging strategies such as 3D bioprinting, gene editing, and advanced culture systems offer promising solutions. Continued optimization of reprogramming, differentiation protocols, and scalable production will be critical for translating stem cell research into safe and effective clinical therapies.
Indexed as
Identifiers
41171580What OpenQuestion holds
Registered trials
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.