Tissue engineering of retina and Bruch's membrane: a review of cells, materials and processes.

The biological, structural and functional configuration of Bruch's membrane (BM) is significantly relevant to age-related macular degeneration (AMD) and other chorioretinal diseases, and AMD is one of the leading causes of blindness in the elderly worldwide. The configuration may worsen along with the ageing of retinal pigment epithelium and BM that finally leads to AMD. Thus, the scaffold-based tissue-engineered retina provides an innovative alternative for retinal tissue repair. The cell and material requirements for retinal repair are discussed including cell sheet engineering, decellularised membrane and tissue-engineered membranes. Further, the challenges and potential in realising a whole tissue model construct for retinal regeneration are highlighted herein. This review article provides a framework for future development of tissue-engineered retina as a preclinical model and possible treatments for AMD.

A bilayer photoreceptor-retinal tissue model with gradient cell density design: A study of microvalve-based bioprinting.

ARPE-19 and Y79 cells were precisely and effectively delivered to form an in vitro retinal tissue model via 3D cell bioprinting technology. The samples were characterized by cell viability assay, haematoxylin and eosin and immunofluorescent staining, scanning electrical microscopy and confocal microscopy, and so forth. The bioprinted ARPE-19 cells formed a high-quality cell monolayer in 14 days. Manually seeded ARPE-19 cells were poorly controlled during and after cell seeding, and they aggregated to form uneven cell layer. The Y79 cells were subsequently bioprinted on the ARPE-19 cell monolayer to form 2 distinctive patterns. The microvalve-based bioprinting is efficient and accurate to build the in vitro tissue models with the potential to provide similar pathological responses and mechanism to human diseases, to mimic the phenotypic endpoints that are comparable with clinical studies, and to provide a realistic prediction of clinical efficacy.