ReviewBioengineering (Basel, Switzerland)2026
Next-Generation Cartilage Repair: Clinical Use of Wharton's Jelly MSCs and the Emerging Role of AI-Assisted Bioprinting.
Review in Bioengineering (Basel, 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.
What it found
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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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The treatment of articular cartilage defects remains a significant clinical challenge due to the tissue's limited intrinsic repair capacity. This paper presents a review of clinical experiences with the use of Wharton's jelly-derived mesenchymal stem cells (WJ-MSCs) as a novel therapeutic option for cartilage regeneration. WJ-MSCs offer key advantages, including high proliferative potential, strong immunomodulatory properties, and low immunogenicity, making them suitable for allogeneic applications. This review describes a single-step, dry-arthroscopic technique that was employed for the implantation of WJ-MSCs embedded in a scaffold directly into cartilage defects. Clinical follow-up, supported by MRI evaluation, demonstrated favorable outcomes with evidence of defect filling, improved cartilage surface quality, and sustained functional improvement in patients. These results suggest that WJ-MSC-based therapies, delivered through minimally invasive surgical techniques, represent a safe and effective strategy for cartilage repair, with the potential to become an important alternative to current standard treatments. Recent advances in artificial intelligence (AI) and multimodal bioprinting are opening new perspectives for standardizing regenerative therapies. Machine learning models can predict bioink performance, optimize scaffold design, and integrate real-time imaging feedback such as optical coherence tomography and photoacoustic imaging. These approaches allow closed-loop quality control and the creation of digital twins to ensure biomechanical fidelity of constructs. Incorporating AI-assisted bioprinting with Wharton's jelly MSCs could accelerate the translation of laboratory findings into reproducible, patient-specific cartilage implants. This manuscript is structured as a translational review of WJ-MSC-based cartilage repair, with AI-assisted bioprinting presented as a prospective future manufacturing direction rather than current clinical practice.
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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.