Publications by authors named "G Zacharias Holland"
Purpose: To validate automated counts of presumed anterior chamber (AC) cells in eyes with histories of uveitis involving the anterior segment using swept-source (SS) anterior segment optical coherence tomography (AS-OCT) against manual counts and compare automated counts against Standardized Uveitis Nomenclature (SUN) criteria.
Methods: Eyes were imaged with the ANTERION SS AS-OCT device (Heidelberg Engineering). A fully automated custom algorithm quantified the number of hyper-reflective foci (HRF) in line-scan images.
Background: A multicentre European randomized control trial - European Uncomplicated Type B Aortic Repair (EU-TBAR) is being developed to compare pre-emptive thoracic endovascular aortic repair (TEVAR) with custom-made devices versus conventional optimal medical therapy. The pretrial set-up is confluent on different pillars, including evaluation of 1) European activity, trends, and governance; 2) outcome reporting; and 3) cost evaluation. This article aimed to demonstrate the observational cross-sectional survey results from participating centers and highlight the risk assessment, activity, practices, and governance of uncomplicated type B aortic dissection (uTBAD).
View Article and Find Full Text PDFPurpose: To report a case of hydroxychloroquine (HCQ) retinopathy after long-term exposure in a 23-year-old male.
Methods: Multimodal imaging including fundus photography, fundus autofluorescence (FAF), spectral domain optical coherence tomography (SD-OCT), and en face OCT were performed, in addition to functional testing with full-field electroretinography (ERG) and Humphrey visual field (HVF).
Results: A 23-year-old man with a history of juvenile systemic lupus erythematosus and HCQ treatment for 13 years at a dosage of 200 mg/d (cumulative dose: 949 grams) presented to the retinal clinic (DS).
Article Synopsis
- Building large-scale quantum computers requires effective error-correction strategies to manage the issues that arise in quantum systems.
- Quantum error-correction codes, particularly the surface code, rely on accurately decoding noisy information to recover correct data, which is a significant challenge.
- A new recurrent neural network decoder has been developed that learns to decode the surface code, outperforming existing decoders and showcasing machine learning's potential to enhance quantum computing through direct data learning.
Article Synopsis
- Hydroxyapatite (HAP) is crucial for biological hard tissues, and its formation involves interactions with biomineralization proteins rich in acidic residues, such as aspartic acid (Asp).
- Experiments show that Asp binds most strongly to short HAP nanorods, which have specific lattice planes, compared to other forms like nanosheets and nanowires, indicating a relationship between HAP structure and Asp affinity.
- Advanced techniques, including solid-state NMR and molecular dynamics simulations, reveal how Asp interacts with HAP surfaces, identifying carboxyl sites as key binding groups, and confirming that binding strength varies based on the HAP morphology.