Browsing by Author "Corridon, Peter R. (55359441300)"

Corneal diseases and injuries, with their substantial global prevalence and adverse effects on quality of life, demographics, occupations, and lifestyles, pose a pressing healthcare challenge worldwide. Limited treatment options are unable to halt the progression of end-stage conditions, where transplantation is the ideal solution. Unfortunately, the high demand and low supply of corneal tissues, donor-recipient mismatches, and host rejections leading to graft failure limit this ideal option. As a result, there is a critical need for alternative interventions. This article aims to establish a bioengineered corneal model generated from the cadaveric decellularized extracellular matrix (dECM) that can repurpose discarded human corneal tissues to potentially increase the supply of transplantable tissues. Comparable studies have primarily focused on reendothelialization and re-epithelialization. Therefore, we hypothesize devising a method to support scaffold reinnervation emanating from prominent nerve plexi spanning the stroma to the epithelium in a patient-centered manner, using peripheral blood mononuclear cells. © 2024 The Author(s)

There is no cure for kidney failure, but a bioartificial kidney may help address this global problem. Decellularization provides a promising platform to generate transplantable organs. However, maintaining a viable vasculature is a significant challenge to this technology. Even though angiography offers a valuable way to assess scaffold structure/function, subtle changes are overlooked by specialists. In recent years, various image analysis methods in radiology have been suggested to detect and identify subtle changes in tissue architecture. The aim of our research was to apply one of these methods based on a gray level co-occurrence matrix (Topalovic et al.) computational algorithm in the analysis of vascular architecture and parenchymal damage generated by hypoperfusion in decellularized porcine. Perfusion decellularization of the whole porcine kidneys was performed using previously established protocols. We analyzed and compared angiograms of kidneys subjected to pathophysiological arterial perfusion of whole blood. For regions of interest Santos et al. covering kidney medulla and the main elements of the vascular network, five major GLCM features were calculated: angular second moment as an indicator of textural uniformity, inverse difference moment as an indicator of textural homogeneity, GLCM contrast, GLCM correlation, and sum variance of the co-occurrence matrix. In addition to GLCM, we also performed discrete wavelet transform analysis of angiogram ROIs by calculating the respective wavelet coefficient energies using high and low-pass filtering. We report statistically significant changes in GLCM and wavelet features, including the reduction of the angular second moment and inverse difference moment, indicating a substantial rise in angiogram textural heterogeneity. Our findings suggest that the GLCM method can be successfully used as an addition to conventional fluoroscopic angiography analyses of micro/macrovascular integrity following in vitro blood perfusion to investigate scaffold integrity. This approach is the first step toward developing an automated network that can detect changes in the decellularized vasculature. Copyright © 2022 Pantic, Shakeel, Petroianu and Corridon.

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. Copyright © 2023 Pantic, Cumic, Valjarevic, Shakeel, Wang, Vurivi, Daoud, Chan, Petroianu, Shibru, Ali, Nesic, Salih, Butt and Corridon.

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. Copyright © 2023 Pantic, Cumic, Valjarevic, Shakeel, Wang, Vurivi, Daoud, Chan, Petroianu, Shibru, Ali, Nesic, Salih, Butt and Corridon.