SARS-CoV-2 infection of human pluripotent stem cell-derived vascular cells reveals smooth muscle cells as key mediators of vascular pathology during infection.

Although respiratory symptoms are the most prevalent disease manifestation of infection by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), nearly 20% of hospitalized patients are at risk for thromboembolic events. This prothrombotic state is considered a key factor in the increased risk of stroke, which is observed clinically during both acute infection and long after symptoms clear. Here, we develop a model of SARS-CoV-2 infection using human-induced pluripotent stem cell-derived endothelial cells (ECs), pericytes (PCs), and smooth muscle cells (SMCs) to recapitulate the vascular pathology associated with SARS-CoV-2 exposure.

Overcoming ammonia inhibition via biochar-assisted anaerobic co-digestion of thermally-treated thickened waste activated sludge and food waste.

The convergence of sustainability and climate change has catalyzed the pursuit of inventive strategies for waste management and sustainable energy production. Hereby, we explored the effect of coupling biochar addition and thermal pretreatment in anaerobic mono-digestion and co-digestion of thermally pretreated thickened waste activated sludge (PTWAS) with food waste (FW). Six semi-continuous lab-scale digesters were operated for 161 days at various organic loading rates (OLR of 2, 3, 4 and 8 kgCOD/m/day) with and without biochar (BC) addition.

Current Knowledge of the Etiology and Management of Molar Incisor Hypomineralization in Children: A Narrative Review.

Molar incisor hypomineralization (MIH) is a developmental condition affecting the enamel, primarily targeting one to four permanent first molars, often with the involvement of permanent incisors. The condition is characterized by distinct white-yellow or yellow-brown opacities, with more severe cases exhibiting hypomineralized enamel that is prone to breakdown. Recent data highlights MIH as a widespread dental issue seen across the globe.

Deep learning-based multiclass segmentation in aneurysmal subarachnoid hemorrhage.

Introduction: Radiological scores used to assess the extent of subarachnoid hemorrhage are limited by intrarater and interrater variability and do not utilize all available information from the imaging. Image segmentation enables precise identification and delineation of objects or regions of interest and offers the potential for automatization of score assessments using precise volumetric information. Our study aims to develop a deep learning model that enables automated multiclass segmentation of structures and pathologies relevant for aneurysmal subarachnoid hemorrhage outcome prediction.

Congenitally Missing Lateral Incisors: Prioritizing Space Closure Whenever Feasible.

Congenital missing teeth are among the most prevalent dental malformations. Maxillary lateral incisors are particularly prone to agenesis, often missing bilaterally. This condition presented complex challenges for both patients and clinicians.