Purpose: To develop and validate a deep learning (DL) model to differentiate ocular surface squamous neoplasia (OSSN) from pterygium and pinguecula using high resolution anterior segment optical coherence tomography (AS-OCT).
Design: Retrospective Diagnostic Accuracy Study METHODS: xxx.
Setting: Single Center STUDY POPULATION: All eyes with a clinical or biopsy-proven diagnosis of OSSN, pterygium, or pinguecula that received AS-OCT imaging.
Antibiotic resistance, driven by the rise of pathogens like VRE and MRSA, poses a global health threat, prompting the exploration of antimicrobial peptides (AMPs) as alternatives to traditional antibiotics. AMPs, known for their broad-spectrum activity and structural flexibility, share characteristics with intrinsically disordered proteins, which lack a rigid structure and play diverse roles in cellular processes. This study aims to quantify the intrinsic disorder and liquid-liquid phase separation (LLPS) propensity in AMPs, advancing our understanding of their antimicrobial mechanisms and potential therapeutic applications.
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