Corneal Confocal Microscopy Identifies and Differentiates Patients With Multiple Sclerosis and Epilepsy.

Purpose: To assess whether corneal nerve analysis can identify and differentiate patients with multiple sclerosis (MS) from those with epilepsy.

Methods: Participants with MS (n = 83), participants with epilepsy (n = 50), and healthy controls (HCs) (n = 20) underwent corneal confocal microscopy (CCM) and quantification of automated corneal nerve fiber length (ACNFL), automated corneal nerve fractal dimension (ACNFrD), and ACNFrD/ACNFL ratio of the subbasal nerve plexus.

Results: ACNFL (MS: P < 0.

Automated denoising software for calcium imaging signals using deep learning.

Dynamic Ca signaling is crucial for cell survival and death, and Ca imaging approaches are commonly used to study and measure cellular Ca patterns within cells. However, the presence of image noise from instrumentation and experimentation protocols can impede the accurate extraction of Ca signals. Removing noise from Ca Spatio-Temporal Maps (STMaps) is essential for precisely analyzing Ca datasets.

A Comprehensive Analysis of Wait Times in Ambulatory Obstetrics and Gynecology Clinic at a Tertiary Care Hospital in Pakistan.

Objective Wait times are an important determinant of patient satisfaction measured objectively and associated significantly with it. It is a measure of time taken from the arrival of patients to the registration desk of a facility to the time they access service. This study focuses on current patient pathways at the Obstetrics and Gynecology Outpatient (OBGYN) Ambulatory Clinic at Shalamar Hospital and assesses wait times by stratifying it at each step of the pathway.