RESUMO
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.
RESUMO
The aim of this study is to assess the protective effects of Ginkgo biloba's (GB) extract against chemotherapeutic-induced reproductive toxicity using a data mining tool, namely Neural Network Clustering (NNC) on two types of data: biochemical & fertility indicators and Texture Analysis (TA) parameters. GB extract (1 g/kg/day) was given orally to male albino rats for 26 days. This period began 21 days before a single cisplatin (CIS) intraperitoneal injection (10 mg/kg body weight). GB given orally significantly restored reproductive function. Tested extract also notably reduced the CIS-induced reproductive toxicity, as evidenced by restoring normal morphology of testes. In GB, the attenuation of CIS-induced damage was associated with less apoptotic cell death both in the testicular tissue and in the sperms. CIS-induced alterations of testicular lipid peroxidation were markedly improved by the examined plant extract. NNC has been used for classifying animal groups based on the quantified biochemical & fertility indicators and microscopic image texture parameters extracted by TA. NNC showed the separation of two clusters and the distribution of groups among them in a way that signifies the dose-dependent protective effect of GB. The present study introduces the neural network as a powerful tool to assess both biochemical and histopathological data. We also show here that herbal protection against CIS-induced reproductive toxicity utilizing classic methodologies is validated using neural network analysis.
