We live in a world of glowing rectangles. Our devices emit a bluish light, akin to that from the cerulean sky. Even when they sleep, computers softly pulse tiny LEDs on and off, making their presence known through light. And where they were once uniformly black and dark gray, devices are now white, shiny, and reflective: they add light not just by emitting it, but by reflecting it. The airbrushed aluminium of Macintosh computers has a luminous flux that ranks higher on light meters than pure, snowy white.
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Background: Adverse outcome pathway (AOP) networks are versatile tools in toxicology and risk assessment that capture and visualize mechanisms driving toxicity originating from various data sources. They share a common structure consisting of a set of molecular initiating events and key events, connected by key event relationships, leading to the actual adverse outcome. AOP networks are to be considered living documents that should be frequently updated by feeding in new data. Such iterative optimization exercises are typically done manually, which not only is a time-consuming effort, but also bears the risk of overlooking critical data. The present study introduces a novel approach for AOP network optimization of a previously published AOP network on chemical-induced cholestasis using artificial intelligence to facilitate automated data collection followed by subsequent quantitative confidence assessment of molecular initiating events, key events, and key event relationships. Methods: Artificial intelligence-assisted data collection was performed by means of the free web platform Sysrev. Confidence levels of the tailored Bradford-Hill criteria were quantified for the purpose of weight-of-evidence assessment of the optimized AOP network. Scores were calculated for biological plausibility, empirical evidence, and essentiality, and were integrated into a total key event relationship confidence value. The optimized AOP network was visualized using Cytoscape with the node size representing the incidence of the key event and the edge size indicating the total confidence in the key event relationship. Results: This resulted in the identification of 38 and 135 unique key events and key event relationships, respectively. Transporter changes was the key event with the highest incidence, and formed the most confident key event relationship with the adverse outcome, cholestasis. Other important key events present in the AOP network include: nuclear receptor changes, intracellular bile acid accumulation, bile acid synthesis changes, oxidative stress, inflammation and apoptosis. Conclusions: This process led to the creation of an extensively informative AOP network focused on chemical-induced cholestasis. This optimized AOP network may serve as a mechanistic compass for the development of a battery of in vitro assays to reliably predict chemical-induced cholestatic injury.
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Production of dry encapsulated forms of anthocyanins from tulip petals with high antioxidant activity and their utilization in lipsticks.Anthocyanins (of the Greek anthos = flower and kianos = blue) are the most important pigments of the plants. These pigments are responsible of the shiny orange, pink, red, violet and blue colors in the flowers and fruits of some plants. The most interesting substances of the waste material are anthocyanins as natural water soluble antioxidants with a great health benefit besides the coloring properties. Tulip is a perennial bulbous plant which is popular worldwide and especially in the Holland due to the showy flowers of the great variety of colors and shades. It was found that for flowers of different colors biosynthesis of anthocyanins of the three anthocyanidin backbones may occur. Thus, pelargonidin (Pg), cyanidin (Cy) and delphinidin (Dp) derivatives, are responsible for tulip flowers color.
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