1,721,465 research outputs found
AMBRA1: When autophagy meets cell proliferation
No full textA growing amount of evidence reported in the literature in recent years strongly supports the relevance of the interplay between autophagy and other pathways. In this context, the study of the link between autophagy and cell proliferation regulation has been among the most challenging. In our recent publications, we finely characterize a role for the pro-autophagic protein AMBRA1 in the regulation of cell proliferation. AMBRA1 modulates autophagy and interacts with PPP2/PP2A (protein phosphatase 2), thus also modulating MYC protein levels and the cell proliferation rate. Interestingly, this pathway of regulation is controlled by the master regulator of autophagy and cell growth, MTORC1. Notably, in our study we demonstrate the relevance of the AMBRA1-mediated regulation of MYC in tumorigenesis, also identifying AMBRA1 as a tumor suppressor gene
Fanconi Anemia Genes, of Menders and Sweepers
Full text linkReporting recently in Cell, Sumpter et al. (2016) provide evidence that Fanconi anemia (FA) pathway genes, which are mutated in the homonymous disease and are tumor suppressors known as damaged nuclear DNA "menders," also act as intracellular sweepers in selective virophagy and mitophagy
Autophagic and apoptotic response to stress signals in mammalian cells
No full textAutophagy is a highly conserved catabolic programme for degrading proteins and organelles. This process has been shown to act as a pro-survival or pro-death mechanism in different physiological and pathological conditions. Several stress stimuli can induce autophagy, such as nutrient deprivation or critical steps in development of lower and higher eukaryotes. Apoptosis is an orchestrated form of cell death in which cells are actively involved in their own demise. Again, stress is a positive regulator of apoptosis and, in particular, of its apoptosome-mediated mitochondrial pathway. Besides discussing the individual roles played by the key molecules involved in autophagy in mammals in response to stress signals, we discuss here the interrelations between autophagy and apoptosis under these conditions
Autophagy up and down by outsmarting the incredible ULK
No full text: Macroautophagy/autophagy initiation is finely regulated by post-translational modifications of key proteins, to comply with the fast kinetics of the cellular response to several stress stimuli. Phosphorylation and ubiquitination play a central role in controlling autophagy by influencing the activity, recruitment and turnover of autophagic components. Recently, we found that, upon autophagy progression, ULK1 kinase is specifically ubiquitinated by the E3 ligase NEDD4L and then degraded via the proteasome. However, during prolonged autophagy, while the ULK1 protein undergoes this inhibition, ULK1 mRNA is actively transcribed, translated and then inhibited again by MTOR-dependent inhibitory phosphorylation. This regulation is essential to promptly restore the ULK1 protein to its original levels to keep autophagy under a safe and physiological threshold
Simulation Of Wind Instruments Based On A Boundary Integral Formulation For The Input Impedance Evaluation
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Data-Driven Process Mining Framework for Risk Management in Construction Projects
Full text linkConstruction Projects are exposed to numerous risks due to their complex and uncertain nature, threatening the realization of the project objectives. However, Risk Management (RM) is a less efficient realm in the industry than other knowledge areas given the manual and time-consuming nature of its processes and reliance on experience-based subjective judgments. This research proposes a Process Mining-based framework for detecting, monitoring, and analysing risks, improving the RM processes using evidence-based event logs, such as Risk Registers and Change-Logs within previous projects' documents. Process Mining (PM) is a data- driven methodology, well established in other industries, that benefits from Artificial Intelligence(AI) to identify trends and complex patterns among event logs. It performs well while intaking large amounts of data and predicting future outputs based on historical data. Therefore, this research proposes a Bayesian Network (BN)-based Process Mining framework for graphical representation of the RM processes, intaking the conditional dependence structure between Risk variables, and continuous and automated risk identification and management. A systematic literature review on RM, PM, and AI forms the framework theoretical basis and delineates the integration areas for practical implementation. The proposed framework is applied to a small database of 20 projects as the case study, the scope of which can be tailored to the enterprise requirements. It contributes to creating a holistic theoretical foundation and practical workflow applicable to construction projects and filling the knowledge gap in inefficient and discrete conventional RM methods, which ignore the interdependencies between risk variables and assess each risk isolated
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