Epidemiology of Orbital and Preseptal Cellulitis in the United States: A 13-Year Analysis.

Purpose: To determine the incidence rates, risk factors, and economic burden of orbital and preseptal cellulitis in the United States (US).

Methods: This retrospective longitudinal study was completed using data from the US Nationwide Emergency Department Sample dataset. An estimated 732,105 emergency department (ED) visits with a primary or secondary diagnosis of orbital and preseptal cellulitis from 2006 to 2018 were included.

Demographics in the context of health-care delivery for C1 and C2 fractures.

Introduction: Atlas and axis fractures are the most severe cervical fractures which may result in complete paralysis or death. The purpose of the current study is to identify disparities regarding length of stay (LOS), mortality, and demographic factors in patients with the most serious cervical spine fractures utilizing a nationally representative database.

Materials And Methods: The Nationwide Emergency Department Sample was utilized to provide a representative sample for patients with a primary diagnosis of C1 or C2 fracture presenting to emergency departments in years from October 2015 to December 2019.

Lack of genetic association of non-melanoma skin cancer and pseudoexfoliative glaucoma.

Background: Prior research has shown a positive association of pseudoexfoliative glaucoma (PXG) in patients with non-melanoma skin cancer (NMSC), likely due to an increase in ultraviolet exposure associated with both. However, the role of NMSC as a genetic risk factor for PXG has not been examined. Thus, the goal of this study is to utilize Mendelian randomization with genome-wide association studies to evaluate for genetic causality while controlling for environmental confounders.

A multi-resolution physics-informed recurrent neural network: formulation and application to musculoskeletal systems.

This work presents a multi-resolution physics-informed recurrent neural network (MR PI-RNN), for simultaneous prediction of musculoskeletal (MSK) motion and parameter identification of the MSK systems. The MSK application was selected as the model problem due to its challenging nature in mapping the high-frequency surface electromyography (sEMG) signals to the low-frequency body joint motion controlled by the MSK and muscle contraction dynamics. The proposed method utilizes the fast wavelet transform to decompose the mixed frequency input sEMG and output joint motion signals into nested multi-resolution signals.