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Artificial intelligence (AI) represents a valuable tool that could be used to improve the safety of care. [https://www.selleckchem.com/products/filanesib.html Filanesib supplier] Major adverse events in healthcare include healthcare-associated infections, adverse drug events, venous thromboembolism, surgical complications, pressure ulcers, falls, decompensation, and diagnostic errors. The objective of this scoping review was to summarize the relevant literature and evaluate the potential of AI to improve patient safety in these eight harm domains. A structured search was used to query MEDLINE for relevant articles. The scoping review identified studies that described the application of AI for prediction, prevention, or early detection of adverse events in each of the harm domains. The AI literature was narratively synthesized for each domain, and findings were considered in the context of incidence, cost, and preventability to make projections about the likelihood of AI improving safety. Three-hundred and ninety-two studies were included in the scoping review. The literature provided numerous examples of how AI has been applied within each of the eight harm domains using various techniques. The most common novel data were collected using different types of sensing technologies vital sign monitoring, wearables, pressure sensors, and computer vision. There are significant opportunities to leverage AI and novel data sources to reduce the frequency of harm across all domains. We expect AI to have the greatest impact in areas where current strategies are not effective, and integration and complex analysis of novel, unstructured data are necessary to make accurate predictions; this applies specifically to adverse drug events, decompensation, and diagnostic errors.Pancreatic cancer (PC) is notoriously difficult to diagnosis and properly stage resulting in incorrect primary treatment. Diagnostic and prognostic biomarkers are desperately needed to more accurately stage patients and select proper treatments. Recently, a newly discovered circulating stromal cell, i.e. cancer associated macrophage-like cell (CAML), was found to accurately identify solid cancers and predict for worse prognosis. In this pilot study, blood samples were procured from 63 PC patients prior to start of therapeutic intent. CAMLs were found in 95% of samples tested, with ≥12 CAMLs/7.5 mL and ≥50 µm CAMLs both predicting for advanced pathological stage and progression free survival. These data suggest that CAML assessment prior to treatment of PC predicts patients with under-staged disease and with more aggressive PC less likely to respond to standard of care treatment.The oleaginous yeast Yarrowia lipolytica is a potent cell factory as it is able to use a wide variety of carbon sources to convert waste materials into value-added products. Nonetheless, there are still gaps in our understanding of its central carbon metabolism. Here we present an in-depth study of Y. lipolytica hexokinase (YlHxk1), a structurally unique protein. The greatest peculiarity of YlHxk1 is a 37-amino acid loop region, a structure not found in any other known hexokinases. By combining bioinformatic and experimental methods we showed that the loop in YlHxk1 is essential for activity of this protein and through that on growth of Y. lipolytica on glucose and fructose. We further proved that the loop in YlHxk1 hinders binding with trehalose 6-phosphate (T6P), a glycolysis inhibitor, as hexokinase with partial deletion of this region is 4.7-fold less sensitive to this molecule. We also found that YlHxk1 devoid of the loop causes strong repressive effect on lipase-encoding genes LIP2 and LIP8 and that the hexokinase overexpression in Y. lipolytica changes glycerol over glucose preference when cultivated in media containing both substrates.The fruit fly, Drosophila melanogaster, has been used as a model organism for the molecular and genetic dissection of sleeping behaviors. However, most previous studies were based on qualitative or semi-quantitative characterizations. Here we quantified sleep in flies. We set up an assay to continuously track the activity of flies using infrared camera, which monitored the movement of tens of flies simultaneously with high spatial and temporal resolution. We obtained accurate statistics regarding the rest and sleep patterns of single flies. Analysis of our data has revealed a general pattern of rest and sleep the rest statistics obeyed a power law distribution and the sleep statistics obeyed an exponential distribution. Thus, a resting fly would start to move again with a probability that decreased with the time it has rested, whereas a sleeping fly would wake up with a probability independent of how long it had slept. Resting transits to sleeping at time scales of minutes. Our method allows quantitative investigations of resting and sleeping behaviors and our results provide insights for mechanisms of falling into and waking up from sleep.Metabolic plasticity enables cancer cells to switch between glycolysis and oxidative phosphorylation to adapt to changing conditions during cancer progression, whereas metabolic dependencies limit plasticity. To understand a role for the architectural environment in these processes we examined metabolic dependencies of cancer cells cultured in flat (2D) and organotypic (3D) environments. Here we show that cancer cells in flat cultures exist in a high energy state (oxidative phosphorylation), are glycolytic, and depend on glucose and glutamine for growth. In contrast, cells in organotypic culture exhibit lower energy and glycolysis, with extensive metabolic plasticity to maintain growth during glucose or amino acid deprivation. Expression of KRASG12V in organotypic cells drives glucose dependence, however cells retain metabolic plasticity to glutamine deprivation. Finally, our data reveal that mechanical properties control metabolic plasticity, which correlates with canonical Wnt signaling. In summary, our work highlights that the architectural and mechanical properties influence cells to permit or restrict metabolic plasticity.The RNA-binding protein Lin28 (Lin28a) is an important pluripotency factor that reprograms translation and promotes cancer progression. Although Lin28 blocks let-7 microRNA maturation, Lin28 also binds to a large set of cytoplasmic mRNAs directly. However, how Lin28 regulates the processing of many mRNAs to reprogram global translation remains unknown. We show here, using a structural and cellular approach, a mixing of Lin28 with YB-1 (YBX1) in the presence of mRNA owing to their cold-shock domain, a conserved β-barrel structure that binds to ssRNA cooperatively. In contrast, the other RNA binding-proteins without cold-shock domains tested, HuR, G3BP-1, FUS and LARP-6, did not mix with YB-1. Given that YB-1 is the core component of dormant mRNPs, a model in which Lin28 gains access to mRNPs through its co-association with YB-1 to mRNA may provide a means for Lin28 to reprogram translation. We anticipate that the translational plasticity provided by mRNPs may contribute to Lin28 functions in development and adaptation of cancer cells to an adverse environment.