Morphological and functional convergence of visual projection neurons from diverse neurogenic origins in Drosophila.

The Drosophila visual system is a powerful model to study the development of neural circuits. Lobula columnar neurons-LCNs are visual output neurons that encode visual features relevant to natural behavior. There are ~20 classes of LCNs forming non-overlapping synaptic optic glomeruli in the brain.

Experimental investigation on the carob extraction using arrhenius approach and response surface.

Environmental problems have increased the need for sustainable agricultural practices that conserve water and energy. Carob, an eco-friendly crop with multiple health benefits, holds the potential for economic evaluation. This study investigates the carob molasses extraction process, focusing on the influence of temperature and water quantity on the diffusion coefficient.

Comparative Analysis of Burn Injuries in Toddler and Preschool Children: Implications for Triage and Outcome Assessment.

Objective: This study aims to compare the demographic, clinical characteristics, and outcomes of burn injuries in toddler and preschool children, and to validate the American Burn Association (ABA) Burn Triage Decision Matrix in the Turkish pediatric population.

Methods: A retrospective analysis was conducted on 684 pediatric burn patients (494 toddlers, 190 preschoolers) admitted to our burn center over a 5-year period. Variables including gender, burn etiology, burn area, depth, treatment modalities, complications, length of hospital stay, and mortality were analyzed.

Alterations in visible light exposure modulate platelet function and regulate thrombus formation.

Background: Variations in light exposure are associated with changes in inflammation and coagulation. The impact of light spectra on venous thrombosis (VT) and arterial thrombosis is largely unexplored.

Objectives: To investigate the impact of altering light spectrum on platelet function in thrombosis.

Profile Photograph Classification Performance of Deep Learning Algorithms Trained Using Cephalometric Measurements: A Preliminary Study.

Extraoral profile photographs are crucial for orthodontic diagnosis, documentation, and treatment planning. The purpose of this study was to evaluate classifications made on extraoral patient photographs by deep learning algorithms trained using grouped patient pictures based on cephalometric measurements. Cephalometric radiographs and profile photographs of 990 patients from the archives of Kocaeli University Faculty of Dentistry Department of Orthodontics were used for the study.