DataSheet1_Building surrogate models of nuclear density functional theory with Gaussian processes and autoencoders.pdf

From the lightest Hydrogen isotopes up to the recently synthesized Oganesson (Z = 118), it is estimated that as many as about 8,000 atomic nuclei could exist in nature. Most of these nuclei are too short-lived to be occurring on Earth, but they play an essential role in astrophysical events such as supernova explosions or neutron star mergers that are presumed to be at the origin of most heavy elements in the Universe. Understanding the structure, reactions, and decays of nuclei across the entire chart of nuclides is an enormous challenge because of the experimental difficulties in measuring properties of interest in such fleeting objects and the theoretical and computational issues of simulating strongly-interacting quantum many-body systems. Nuclear density functional theory (DFT) is a fully microscopic theoretical framework which has the potential of providing such a quantitatively accurate description of nuclear properties for every nucleus in the chart of nuclides. Thanks to high-performance computing facilities, it has already been successfully applied to predict nuclear masses, global patterns of radioactive decay like β or γ decay, and several aspects of the nuclear fission process such as, e.g., spontaneous fission half-lives. Yet, predictive simulations of nuclear spectroscopy—the low-lying excited states and transitions between them—or of nuclear fission, or the quantification of theoretical uncertainties and their propagation to basic or applied nuclear science applications, would require several orders of magnitude more calculations than currently possible. However, most of this computational effort would be spent into generating a suitable basis of DFT wavefunctions. Such a task could potentially be considerably accelerated by borrowing tools from the field of machine learning and artificial intelligence. In this paper, we review different approaches to applying supervised and unsupervised learning techniques to nuclear DFT.</p

Ezetimibe ameliorates steatohepatitis via AMP activated protein kinase-TFEB-mediated activation of autophagy and NLRP3 inflammasome inhibition

<p>Impairment in macroautophagy/autophagy flux and inflammasome activation are common characteristics of nonalcoholic steatohepatitis (NASH). Considering the lack of approved agents for treating NASH, drugs that can enhance autophagy and modulate inflammasome pathways may be beneficial. Here, we investigated the novel mechanism of ezetimibe, a widely prescribed drug for hypercholesterolemia, as a therapeutic option for ameliorating NASH. Human liver samples with steatosis and NASH were analyzed. For in vitro studies of autophagy and inflammasomes, primary mouse hepatocytes, human hepatoma cells, mouse embryonic fibroblasts with Ampk or Tsc2 knockout, and human or primary mouse macrophages were treated with ezetimibe and palmitate. Steatohepatitis and fibrosis were induced by feeding Atg7 wild-type, haploinsufficient, and knockout mice a methionine- and choline-deficient diet with ezetimibe (10 mg/kg) for 4 wk. Human livers with steatosis or NASH presented impaired autophagy with decreased nuclear TFEB and increased SQSTM1, MAP1LC3-II, and NLRP3 expression. Ezetimibe increased autophagy flux and concomitantly ameliorated lipid accumulation and apoptosis in palmitate-exposed hepatocytes. Ezetimibe induced AMPK phosphorylation and subsequent TFEB nuclear translocation, related to MAPK/ERK. In macrophages, ezetimibe blocked the NLRP3 inflammasome-IL1B pathway in an autophagy-dependent manner and modulated hepatocyte-macrophage interaction via extracellular vesicles. Ezetimibe attenuated lipid accumulation, inflammation, and fibrosis in liver-specific Atg7 wild-type and haploinsufficient mice, but not in knockout mice. Ezetimibe ameliorates steatohepatitis by autophagy induction through AMPK activation and TFEB nuclear translocation, related to an independent MTOR ameliorative effect and the MAPK/ERK pathway. Ezetimibe dampens NLRP3 inflammasome activation in macrophages by modulating autophagy and a hepatocyte-driven exosome pathway.</p