ArticleJournal of tissue engineering
Liver scaffolds obtained by decellularization: A transplant perspective in liver bioengineering.
Article in Journal of tissue engineering. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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
11 citing papers in PubMed, 22 citations in OpenAlex.
- Advances and applications of organ-on-a-chip technology.Cell reports methods · 2026Review
- Mesenchymal Stromal/Stem Cell-Based Therapies for Liver Regeneration: Current Status and Future Directions.International journal of molecular sciences · 2026Review
- Pharmacological and therapeutic effects of natural products on liver regeneration-a comprehensive research.Chinese medicine · 2025Review
- Use of Decellularized Bio-Scaffolds for the Generation of a Porcine Artificial Intestine.Methods and protocols · 2024Article
- Effect of Donor Age and Liver Steatosis on Potential of Decellularized Liver Matrices to be used as a Platform for iPSC-Hepatocyte Culture.Advanced healthcare materials · 2024Article
- Liver organoids cocultured on decellularized native liver scaffolds as a bridging therapy improves survival from liver failure in rabbits.In vitro cellular & developmental biology. Animal · 2023Article
- Decellularization Techniques for Tissue Engineering: Towards Replicating Native Extracellular Matrix Architecture in Liver Regeneration.Journal of functional biomaterials · 2023Review
- Whole Liver Derived Acellular Extracellular Matrix for Bioengineering of Liver Constructs: An Updated Review.Bioengineering (Basel, Switzerland) · 2023Review
- Article
- Scaffold-mediated liver regeneration: A comprehensive exploration of current advances.Journal of tissue engineeringReview
- Decellularized extracellular matrix for organoid and engineered organ culture.Journal of tissue engineeringReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liver transplantation is the only definitive treatment for many diseases that affect this organ, however, its quantity and viability are reduced. The study of liver scaffolds based on an extracellular matrix is a tissue bioengineering strategy with great application in regenerative medicine. Collectively, recent studies suggest that liver scaffold transplantation may assist in reestablishing hepatic function in preclinical diseased animals, which represents a great potential for application as a treatment for patients with liver disease in the future. This review focuses on useful strategies to promote liver scaffold transplantation and the main open questions about this context. We outline the current knowledge about ex vivo bioengineered liver transplantation, including the surgical techniques, recipient survival time, scaffold preparation before transplantation, and liver disease models. We also highlight the current limitations and future directions regarding in vivo bioengineering techniques.
Indexed as
Identifiers
What 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.