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Revisiting the mouse model of oxygen-induced retinopathy

Overview of attention for article published in Eye and brain, May 2016
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Title
Revisiting the mouse model of oxygen-induced retinopathy
Published in
Eye and brain, May 2016
DOI 10.2147/eb.s94447
Pubmed ID
Authors

Clifford Kim, Patricia D'Amore, Kip Connor

Abstract

Abnormal blood vessel growth in the retina is a hallmark of many retinal diseases, such as retinopathy of prematurity (ROP), proliferative diabetic retinopathy, and the wet form of age-related macular degeneration. In particular, ROP has been an important health concern for physicians since the advent of routine supplemental oxygen therapy for premature neonates more than 70 years ago. Since then, researchers have explored several animal models to better understand ROP and retinal vascular development. Of these models, the mouse model of oxygen-induced retinopathy (OIR) has become the most widely used, and has played a pivotal role in our understanding of retinal angiogenesis and ocular immunology, as well as in the development of groundbreaking therapeutics such as anti-vascular endothelial growth factor injections for wet age-related macular degeneration. Numerous refinements to the model have been made since its inception in the 1950s, and technological advancements have expanded the use of the model across multiple scientific fields. In this review, we explore the historical developments that have led to the mouse OIR model utilized today, essential concepts of OIR, limitations of the model, and a representative selection of key findings from OIR, with particular emphasis on current research progress.

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Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Brazil 1 1%
Unknown 65 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 27%
Researcher 13 19%
Student > Master 8 12%
Student > Doctoral Student 7 10%
Student > Bachelor 6 9%
Other 7 10%
Unknown 8 12%
Readers by discipline Count As %
Medicine and Dentistry 18 27%
Biochemistry, Genetics and Molecular Biology 12 18%
Agricultural and Biological Sciences 9 13%
Neuroscience 7 10%
Engineering 3 4%
Other 5 7%
Unknown 13 19%