Publications by authors named "D Moon"

Background: Leber congenital amaurosis (LCA), the most severe form of inherited retinal dystrophy, is a rare, heterogeneous, genetic eye disease associated with severe congenital visual impairment. RPE65, one of the causative genes for LCA, encodes retinoid isomerohydrolase, an enzyme that plays a critical role in regenerating visual pigment in photoreceptor cells.

Methods: Exome sequencing (ES) was performed on a patient with suspected LCA.

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Objective: This study aimed to compare morbidity of living donors and recipients after pure laparoscopic donor right hepatectomy (PLDRH) and open donor right hepatectomy (ODRH).

Background: Donor and recipient morbidity have not been sufficiently reported in large-scale comparisons of PLDRH and ODRH.

Methods: This retrospective study reviewed 3348 donors who underwent PLDRH (n=329) and ODRH (n=3019) and their corresponding recipients (n=3348) between January 2014 and August 2023.

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Organic solar cells (OSCs) have recently achieved efficiencies of >20% in single-junction unit cells owing to rapid advancements in materials and device technologies. Large-area OSCs face several challenges that adversely affect their efficiency compared to small unit cells. These challenges include increased resistance loads derived from their larger dimensions, as well as limitations related to morphology, miscibility, and crystallinity.

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Purpose: Estrogen receptor (ER) expression and heterogeneity affect endocrine therapy efficacy. F-fluoroestradiol (F-FES) PET/CT is an effective non-invasive method to analyze systemic ER expression. This study aimed to examine the predictive/prognostic value of F-FES PET/CT for patients treated with endocrine therapy plus cyclin-dependent kinase 4/6 (CDK4/6) inhibitors.

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Background/objectives: Cystoscopy is necessary for diagnosing bladder cancer, but it has limitations in identifying ambiguous lesions, such as carcinoma in situ (CIS), which leads to a high recurrence rate of bladder cancer. With the significant advancements in deep learning in the medical field, several studies have explored its application in cystoscopy. This study aimed to utilize the VGG19 and Deeplab v3+ deep learning models to classify and segment cystoscope images, respectively.

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