13 research outputs found

    Development of a Novel Adaptive Soft-Sensor Using Variational Bayesian PLS with Accounting for Online Identification of Key Variables

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    Soft-sensor is the most common strategy to estimate the hard-to-measure variables in the chemical processes. Recent research has shown that accurate prediction of hard-to-measure variables can significantly improve system performance. However, deterioration of predictive ability resulting from dramatic changes in the operation conditions always renders a generic soft-sensor inadequate. This study developed an adaptive soft-sensor with Moving Window and Time Differencing technique accounting for both of long-term and short-term information for modeling. At each step of model update, the most insensitive variables were removed by VIP (Variable importance in projection). With further integrating Variational Bayesian PLS (VBPLS) as predictive model, not just prediction values are obtained but also the credibility of information for hard-to-measure quantities can be generated. The proposed methodology was first demonstrated by applying the design algorithm to a WWTP simulated with the well-established model, BSM1, then extended to a real WWTP with data collecting from the field. Results showed that the proposed strategy significantly improved the prediction performance

    Kinase Screening in <i>Pichia pastoris</i> Identified Promising Targets Involved in Cell Growth and <i>Alcohol Oxidase 1</i> Promoter (P<i><sub>AOX1</sub></i>) Regulation

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    <div><p>As one of the most commonly used eukaryotic recombinant protein expression systems, <i>P</i>. <i>pastoris</i> relies heavily on the <i>AOX1</i> promoter (P<sub><i>AOX1</i></sub>), which is strongly induced by methanol but strictly repressed by glycerol and glucose. However, the complicated signaling pathways involved in P<sub><i>AOX1</i></sub> regulation when supplemented with different carbon sources are poorly understood. Here we constructed a kinase deletion library in <i>P</i>. <i>pastoris</i> and identified 27 mutants which showed peculiar phenotypes in cell growth or P<sub><i>AOX1</i></sub> regulation. We analyzed both annotations and possible functions of these 27 targets, and then focused on the MAP kinase Hog1. In order to locate its potential downstream components, we performed the phosphoproteome analysis on glycerol cultured WT and Δ<i>hog1</i> strains and identified 157 differentially phosphorylated proteins. Our results identified important kinases involved in <i>P</i>. <i>pastoris</i> cell growth and P<sub><i>AOX1</i></sub> regulation, which could serve as valuable targets for further mechanistic studies.</p></div
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