Evidence map›Paper›PMID 40297283›Full record

ArticleFrontiers in bioengineering and biotechnology2025

Transforming meat waste into sustainable corneal keratoplasty models.

Ayman Mobin, Zayd Hashem, Peter R Corridon

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ayman Mobin *Department of Biomedical Engineering and Biotechnology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
Zayd Hashem *Department of Biomedical Engineering and Biotechnology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
Peter R CorridonDepartment of Biomedical Engineering and Biotechnology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With a rapidly global population, there is a critical need to enhance food production and waste management. This necessity is driving opportunities for sustainable integrated food chains committed to biovalorization and circular bioeconomic practices. One approach that aligns with this vision relies on sustainable tissue engineering, which offers opportunities to leverage food systems in the search for natural biomaterials from agricultural waste. In this perspective, we propose utilizing common meat waste sources, often associated with a high environmental footprint, to develop tissue graft models. These models reduce agricultural waste, decrease the reliance on animal testing, and support both biovalorization and medical innovation. Specifically, we explore a unique approach to generate corneal transplantation models completely from discarded components of the meat food chain, using the eyes and bladders. This strategy involves creating keratoplasty models by reseeding the decellularized extracellular matrix (dECM), encompassing three major corneal regions: the epithelium, stroma, and endothelium. Interestingly, these scaffolds can be recellularized with cellular lineages derived from stem niches harvested from urine. This approach integrates waste management with regenerative medicine, fostering sustainable advancements in tissue engineering.

Indexed as

decellularized ECM (dECM)keratoplastymeat wasterecellularizationsustainable tissue engineeringurine-derived cells (UCs)

Identifiers

PMID40297283
PMCPMC12034655

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.