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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6

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    PublicationOpen Access
    Applications of augmented reality in ophthalmology [invited]
    (Optical Society of America (OSA), 2021) Artal, Pablo; Department of Physics; Department of Electrical and Electronics Engineering; Aydındoğan, Güneş; Kavaklı, Koray; Ürey, Hakan; Şahin, Afsun; Faculty Member; Faculty Member; Department of Physics; Department of Electrical and Electronics Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); Graduate School of Sciences and Engineering; College of Engineering; School of Medicine; N/A; N/A; 8579; 171267
    Throughout the last decade, augmented reality (AR) head-mounted displays (HMDs) have gradually become a substantial part of modern life, with increasing applications ranging from gaming and driver assistance to medical training. Owing to the tremendous progress in miniaturized displays, cameras, and sensors, HMDs are now used for the diagnosis, treatment, and follow-up of several eye diseases. In this review, we discuss the current state-of-the-art as well as potential uses of AR in ophthalmology. This review includes the following topics: (i) underlying optical technologies, displays and trackers, holography, and adaptive optics; (ii) accommodation, 3D vision, and related problems such as presbyopia, amblyopia, strabismus, and refractive errors; (iii) AR technologies in lens and corneal disorders, in particular cataract and keratoconus; (iv) AR technologies in retinal disorders including age-related macular degeneration (AMD), glaucoma, color blindness, and vision simulators developed for other types of low-vision patients.
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    PublicationOpen Access
    Machine learning helps identify CHRONO as a circadian clock component
    (Public Library of Science, 2014) Anafi, Ron C.; Lee, Yoo; Sato, Trey K.; Venkataraman, Anand; Ramanathan, Chidambaram; Hughes, Michael E.; Baggs, Julie E.; Growe, Jacqueline; Liu, Andrew C.; Kim, Junhyong; Hogenesch, John B.; Kavaklı, İbrahim Halil; Faculty Member; College of Engineering; 40319
    Over the last decades, researchers have characterized a set of ‘‘clock genes’’ that drive daily rhythms in physiology and behavior. This arduous work has yielded results with far-reaching consequences in metabolic, psychiatric, and neoplastic disorders. Recent attempts to expand our understanding of circadian regulation have moved beyond the mutagenesis screens that identified the first clock components, employing higher throughput genomic and proteomic techniques. In order to further accelerate clock gene discovery, we utilized a computer-assisted approach to identify and prioritize candidate clock components. We used a simple form of probabilistic machine learning to integrate biologically relevant, genome-scale data and ranked genes on their similarity to known clock components. We then used a secondary experimental screen to characterize the top candidates. We found that several physically interact with known clock components in a mammalian two-hybrid screen and modulate in vitro cellular rhythms in an immortalized mouse fibroblast line (NIH 3T3). One candidate, Gene Model 129, interacts with BMAL1 and functionally represses the key driver of molecular rhythms, the BMAL1/CLOCK transcriptional complex. Given these results, we have renamed the gene CHRONO (computationally highlighted repressor of the network oscillator). Bi-molecular fluorescence complementation and co-immunoprecipitation demonstrate that CHRONO represses by abrogating the binding of BMAL1 to its transcriptional co-activator CBP. Most importantly, CHRONO knockout mice display a prolonged free-running circadian period similar to, or more drastic than, six other clock components. We conclude that CHRONO is a functional clock component providing a new layer of control on circadian molecular dynamics.