Subject(s)
Abattoirs , Tissue Scaffolds , Tissue Engineering , Printing, Three-Dimensional , Extracellular MatrixABSTRACT
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.
ABSTRACT
Introduction: Corneal disease is a leading cause of blindness globally that stems from various etiologies. High-throughput platforms that can generate substantial quantities of corneal grafts will be invaluable in addressing the existing global demand for keratoplasty. Slaughterhouses generate substantial quantities of underutilized biological waste that can be repurposed to reduce current environmentally unfriendly practices. Such efforts to support sustainability can simultaneously drive the development of bioartificial keratoprostheses. Methods: Scores of discarded eyes from the prominent Arabian sheep breeds in our surrounding region of the United Arab Emirates (UAE) were repurposed to generate native and acellular corneal keratoprostheses. Acellular corneal scaffolds were created using a whole-eye immersion/agitation-based decellularization technique with a widely available, eco-friendly, and inexpensive 4% zwitterionic biosurfactant solution (Ecover, Malle, Belgium). Conventional approaches like DNA quantification, ECM fibril organization, scaffold dimensions, ocular transparency and transmittance, surface tension measurements, and Fourier-transform infrared (FTIR) spectroscopy were used to examine corneal scaffold composition. Results: Using this high-throughput system, we effectively removed over 95% of the native DNA from native corneas while retaining the innate microarchitecture that supported substantial light transmission (over 70%) after reversing opacity, a well-established hallmark of decellularization and long-term native corneal storage, with glycerol. FTIR data revealed the absence of spectral peaks in the frequency range 2849 cm-1 to 3075 cm-1, indicating the effective removal of the residual biosurfactant post-decellularization. Surface tension studies confirmed the FTIR data by capturing the surfactant's progressive and effectual removal through tension measurements ranging from approximately 35 mN/m for the 4% decellularizing agent to 70 mN/m for elutes highlighting the effective removal of the detergent. Discussion: To our knowledge, this is the first dataset to be generated outlining a platform that can produce dozens of ovine acellular corneal scaffolds that effectively preserve ocular transparency, transmittance, and ECM components using an eco-friendly surfactant. Analogously, decellularization technologies can support corneal regeneration with attributes comparable to native xenografts. Thus, this study presents a simplified, inexpensive, and scalable high-throughput corneal xenograft platform to support tissue engineering, regenerative medicine, and circular economic sustainability.
