ArticleFrontiers in bioengineering and biotechnology2023
Computational approaches for evaluating morphological changes in the corneal stroma associated with decellularization.
Article in Frontiers in bioengineering and biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 23 citations in OpenAlex.
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- Integrated environmental and health economic assessments of novel xeno-keratografts addressing a growing public health crisis.Scientific reports · 2024Article
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- Machine learning approaches to detect hepatocyte chromatin alterations from iron oxide nanoparticle exposure.Scientific reports · 2024Article
- A sustainable approach to derive sheep corneal scaffolds from stored slaughterhouse waste.Regenerative medicine · 2024Article
- Capturing effects of blood flow on the transplanted decellularized nephron with intravital microscopy.Scientific reports · 2023Article
- From waste to wealth: Repurposing slaughterhouse waste for xenotransplantation.Frontiers in bioengineering and biotechnology · 2023Article
- A proposed model of xeno-keratoplasty using 3D printing and decellularization.Frontiers in pharmacology · 2023Article
- Enhancing the expression of a key mitochondrial enzyme at the inception of ischemia-reperfusion injury can boost recovery and halt the progression of acute kidney injury.Frontiers in physiology · 2023Article
- A scalable corneal xenograft platform: simultaneous opportunities for tissue engineering and circular economic sustainability by repurposing slaughterhouse waste.Frontiers in bioengineering and biotechnology · 2023Article
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Authors and funding
15 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Decellularized corneas offer a promising and sustainable source of replacement grafts, mimicking native tissue and reducing the risk of immune rejection post-transplantation. Despite great success in achieving acellular scaffolds, little consensus exists regarding the quality of the decellularized extracellular matrix. Metrics used to evaluate extracellular matrix performance are study-specific, subjective, and semi-quantitative. Thus, this work focused on developing a computational method to examine the effectiveness of corneal decellularization. We combined conventional semi-quantitative histological assessments and automated scaffold evaluations based on textual image analyses to assess decellularization efficiency. Our study highlights that it is possible to develop contemporary machine learning (ML) models based on random forests and support vector machine algorithms, which can identify regions of interest in acellularized corneal stromal tissue with relatively high accuracy. These results provide a platform for developing machine learning biosensing systems for evaluating subtle morphological changes in decellularized scaffolds, which are crucial for assessing their functionality.
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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.