Artificial Intelligence (AI) has become of increasing interest over the past decade. While digital image analysis (DIA) is already being used in radiology, it is still in its infancy in pathology. One of the reasons is that large-scale digitization of glass slides has only recently become available. With the advent of digital slide scanners, that digitize glass slides into whole slide images, many labs are now in a transition phase towards digital pathology. However, only few departments worldwide are currently fully digital. Digital pathology provides the ability to annotate large datasets and train computers to develop and validate robust algorithms, similar to radiology. In this opinionated overview, we will give a brief introduction into AI in pathology, discuss the potential positive and negative implications and speculate about the future role of AI in the field of pediatric pathology.
Despite the ubiquitous use of glasses, their simultaneous susceptibility toward scratch-induced defects and atmospheric hydration deteriorates their mechanical and chemical durability. Here, it is demonstrated that the deposition of a few-layer graphene provides unprecedented wear resistance to silica glass in aqueous conditions. To this extent, nanoscale scratch tests are carried out on graphene-glass surfaces via contact-mode atomic force microscopy with chemically inert and reactive tips.
Background: Corona virus disease 2019 (COVID-19) reinfection, particularly short-term reinfection, poses challenges to the management of rheumatic diseases and may increase adverse clinical outcomes. This study aims to develop machine learning models to predict and identify the risk of short-term COVID-19 reinfection in patients with rheumatic diseases.
Methods: We developed four prediction models using explainable machine learning to assess the risk of short-term COVID-19 reinfection in 543 patients with rheumatic diseases.
Background: The simultaneous differentiation of human pluripotent stem cells (hPSCs) into both endodermal and mesodermal lineages is crucial for developing complex, vascularized tissues, yet poses significant challenges. This study explores a method for co-differentiation of mesoderm and endoderm, and their subsequent differentiation into pancreatic progenitors (PP) with endothelial cells (EC).
Alzheimer's Disease (AD) is a debilitating neurodegenerative disease that affects 47.5 million people worldwide. AD is characterised by the formation of plaques containing extracellular amyloid-β (Aβ) and neurofibrillary tangles composed of hyper-phosphorylated tau proteins (pTau).
Engineering Research Center of Edible and Medicinal Fungi, Ministry of Education, Jilin Agricultural University, No. 2888 Xincheng Street, Changchun , Jilin Province, 130118, China.
Background: Hericium coralloides is a traditional edible and medicinal mushroom. Light is a key factor in forming fruiting bodies of fungi; however, the effects of different light on the yield and morphogenesis of H. coralloides are still unknown.
