Prognostics for an actuator with the combination of support vector regression and particle filter

The accurate prognostics for actuator malfunctions is a challenging task. Developing reliable prognostic methods is vital for providing reasonable preventive maintenance schedules and preventing unexpected failures. Particle filter has been proved to be a traditional approach to deal with actuator prognostic problems. However, the measurement function in the particle filter algorithm cannot be obtained in the prediction process, this paper presents a hybrid framework combining support vector regression (SVR) and particle filter (PF). The SVR output prediction results are employed as the “measurements” for the subsequent PF algorithm. To accomplish the accurate prognostics for actuator fault of civil aircraft, an improved PF based on Kendall correlation coefficient is put forward to solve the problem of particles’ degeneracy. The experimental results are presented, demonstrating that the SVR-PF hybrid approach has satisfactory performance with better prognostics accuracy and higher fault resolution than traditional approaches

A systematic investigation of Escherichia coli central carbon metabolism in response to superoxide stress

<p>Abstract</p> <p>Background</p> <p>The cellular responses of bacteria to superoxide stress can be used to model adaptation to severe environmental changes. Superoxide stress promotes the excessive production of reactive oxygen species (ROS) that have detrimental effects on cell metabolic and other physiological activities. To antagonize such effects, the cell needs to regulate a range of metabolic reactions in a coordinated way, so that coherent metabolic responses are generated by the cellular metabolic reaction network as a whole. In the present study, we have used a quantitative metabolic flux analysis approach, together with measurement of gene expression and activity of key enzymes, to investigate changes in central carbon metabolism that occur in <it>Escherichia coli </it>in response to paraquat-induced superoxide stress. The cellular regulatory mechanisms involved in the observed global flux changes are discussed.</p> <p>Results</p> <p>Flux analysis based on nuclear magnetic resonance (NMR) and mass spectroscopy (MS) measurements and computation provided quantitative results on the metabolic fluxes redistribution of the <it>E. coli </it>central carbon network under paraquat-induced oxidative stress. The metabolic fluxes of the glycolytic pathway were redirected to the pentose phosphate pathway (PP pathway). The production of acetate increased significantly, the fluxes associated with the TCA cycle decreased, and the fluxes in the glyoxylate shunt increased in response to oxidative stress. These global flux changes resulted in an increased ratio of NADPH:NADH and in the accumulation of α-ketoglutarate.</p> <p>Conclusions</p> <p>Metabolic flux analysis provided a quantitative and global picture of responses of the <it>E. coli </it>central carbon metabolic network to oxidative stress. Systematic adjustments of cellular physiological state clearly occurred in response to changes in metabolic fluxes induced by oxidative stress. Quantitative flux analysis therefore could reveal the physiological state of the cell at the systems level and is a useful complement to molecular systems approaches, such as proteomics and transcription analyses.</p

Regulation of DJ-1 by glutaredoxin 1 \u3ci\u3ein vivo – implications for Parkinson’s disease\u3c/i\u3e

Parkinson’s disease (PD) is the second most common neurodegenerative disease worldwide, caused by the degeneration of the dopaminergic neurons in the substantia nigra. Mutations in PARK7 (DJ-1) result in early onset autosomal recessive PD, and oxidative modification of DJ-1 has been reported to regulate the protective activity of DJ-1 in vitro. Glutathionylation is a prevalent redox modification of proteins resulting from the disulfide adduction of the glutathione moiety to a reactive cysteine-SH; and glutathionylation of specific proteins has been implicated in regulation of cell viability. Glutaredoxin 1 (Grx1) is the principal deglutathionylating enzyme within cells, and it has been reported to mediate protection of dopaminergic neurons in C. elegans, however many of the functional downstream targets of Grx1 in vivo remain unknown. Previously, DJ-1 protein content was shown to decrease concomitantly with diminution of Grx1 protein content in cell culture of model neurons (SH-SY5Y and Neuro-2A lines). In the current study we aimed to investigate the regulation of DJ-1 by Grx1 in vivo and characterize its glutathionylation in vitro. Here, with Grx−/− mice we provide evidence that Grx1 regulates protein levels of DJ-1 in vivo. Furthermore, with model neuronal cells (SH-SY5Y) we observed decreased DJ-1 protein content in response to treatment with known glutathionylating agents; and with isolated DJ-1 we identified two distinct sites of glutathionylation. Finally, we found that overexpression of DJ-1 in the dopaminergic neurons partly compensates for the loss of the Grx1 homolog in a C. elegans in vivo model of PD. Therefore; our results reveal a novel redox modification of DJ-1 and suggest a novel regulatory mechanism for DJ-1 content in vivo

A Plant DJ-1 Homolog Is Essential for Arabidopsis thaliana Chloroplast Development

Protein superfamilies can exhibit considerable diversification of function among their members in various organisms. The DJ-1 superfamily is composed of proteins that are principally involved in stress response and are widely distributed in all kingdoms of life. The model flowering plant Arabidopsis thaliana contains three close homologs of animal DJ-1, all of which are tandem duplications of the DJ-1 domain. Consequently, the plant DJ-1 homologs are likely pseudo-dimeric proteins composed of a single polypeptide chain. We report that one A. thaliana DJ-1 homolog (AtDJ1C) is the first DJ-1 homolog in any organism that is required for viability. Homozygous disruption of the AtDJ1C gene results in non-viable, albino seedlings that can be complemented by expression of wild-type or epitope-tagged AtDJ1C. The plastids from these dj1c plants lack thylakoid membranes and granal stacks, indicating that AtDJ1C is required for proper chloroplast development. AtDJ1C is expressed early in leaf development when chloroplasts mature, but is downregulated in older tissue, consistent with a proposed role in plastid development. In addition to its plant-specific function, AtDJ1C is an atypical member of the DJ-1 superfamily that lacks a conserved cysteine residue that is required for the functions of most other superfamily members. The essential role for AtDJ1C in chloroplast maturation expands the known functional diversity of the DJ-1 superfamily and provides the first evidence of a role for specialized DJ-1-like proteins in eukaryotic development

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery