ArticleAnnals of biomedical engineering2024
Decellularized Tissue-Induced Cellular Recruitment for Tissue Engineering and Regenerative Medicine.
Article in Annals of biomedical engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- A multifunctional DECM/PLMA hydrogel incorporated with engineered PRP-derived exosomes enabling PHD2 silencing for skin wound repair.Bioactive materials · 2027Article
- Comparative proteomic analysis of the composition of dECM and dECM-based inks compared to native tissues.iScience · 2026Article
- Engineered Osteochondral Scaffolds with Bioactive Cartilage Zone for Enhanced Articular Cartilage Regeneration.Annals of biomedical engineering · 2025Article
- Decellularized cartilage tissue bioink formulation for osteochondral graft development.Biomedical materials (Bristol, England) · 2025Article
- Decellularized extracellular matrix biomaterials for regenerative therapies: Advances, challenges and clinical prospects.Bioactive materials · 2024Review
- Extracellular Matrix-Based and Electrospun Scaffolding Systems for Vaginal Reconstruction.Bioengineering (Basel, Switzerland) · 2023Review
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.
Funding
Abstract
Biomaterials that recapitulate the native in vivo microenvironment are promising to facilitate tissue repair and regeneration when used in combination with relevant growth factors (GFs), chemokines, cytokines, and other small molecules and cell sources. However, limitations with the use of exogenous factors and ex vivo cell expansion has prompted cell-/GF-free tissue engineering strategies. Additionally, conventional chemotaxis assays for studying cell migration behavior provide limited information, lack long-term stability, and fail to recapitulate physiologically relevant conditions. In this study, articular cartilage tissue-based biomaterials were developed via a rapid tissue decellularization protocol. The decellularized tissue was further processed into a hydrogel through solubilization and self-assembly. Chemotactic activity of the tissue-derived gel was investigated using sophisticated cellular migration assays. These tissue-derived extracellular matrix (ECM) biomaterials retain biochemical cues of native tissue and stimulate the chemotactic migration of hBMSCs in 2D and 3D cell migration models using a real-time chemotaxis assay. This strategy, in a way, developed a new paradigm in tissue engineering where cartilage tissue repair and regeneration can be approached with decellularized cartilage tissue in the place of an engineered matrix. This strategy can be further expanded for other tissue-based ECMs to develop cell-/GF-free tissue engineering and regenerative medicine strategies for recruiting endogenous cell populations to facilitate tissue repair and regeneration.
Indexed as
Identifiers
36952144What 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.