1.
Roles of Exosomes in Ocular Diseases.
Liu, J, Jiang, F, Jiang, Y, Wang, Y, Li, Z, Shi, X, Zhu, Y, Wang, H, Zhang, Z
International journal of nanomedicine. 2020;:10519-10538
Abstract
Exosomes, nanoscale vesicles with a diameter of 30 to 150 nm, are composed of a lipid bilayer, protein, and genetic material. Exosomes are secreted by virtually all types of cells in the human body. They have key functions in cell-to-cell communication, immune regulation, inflammatory response, and neovascularization. Mounting evidence indicates that exosomes play an important role in various diseases, such as cancer, cardiovascular diseases, and brain diseases; however, the role that exosomes play in eye diseases has not yet been rigorously studied. This review covers current exosome research as it relates to ocular diseases including diabetic retinopathy, age-related macular degeneration, autoimmune uveitis, glaucoma, traumatic optic neuropathies, corneal diseases, retinopathy of prematurity, and uveal melanoma. In addition, we discuss recent advances in the biological functions of exosomes, focusing on the toxicity of exosomes and the use of exosomes as biomarkers and drug delivery vesicles. Finally, we summarize the primary considerations and challenges to be taken into account for the effective applications of exosomes.
2.
A survey on computer aided diagnosis for ocular diseases.
Zhang, Z, Srivastava, R, Liu, H, Chen, X, Duan, L, Kee Wong, DW, Kwoh, CK, Wong, TY, Liu, J
BMC medical informatics and decision making. 2014;:80
Abstract
BACKGROUND Computer Aided Diagnosis (CAD), which can automate the detection process for ocular diseases, has attracted extensive attention from clinicians and researchers alike. It not only alleviates the burden on the clinicians by providing objective opinion with valuable insights, but also offers early detection and easy access for patients. METHOD We review ocular CAD methodologies for various data types. For each data type, we investigate the databases and the algorithms to detect different ocular diseases. Their advantages and shortcomings are analyzed and discussed. RESULT We have studied three types of data (i.e., clinical, genetic and imaging) that have been commonly used in existing methods for CAD. The recent developments in methods used in CAD of ocular diseases (such as Diabetic Retinopathy, Glaucoma, Age-related Macular Degeneration and Pathological Myopia) are investigated and summarized comprehensively. CONCLUSION While CAD for ocular diseases has shown considerable progress over the past years, the clinical importance of fully automatic CAD systems which are able to embed clinical knowledge and integrate heterogeneous data sources still show great potential for future breakthrough.