Production of human recombinant proapolipoprotein A-I in Escherichia coli: purification and biochemical characterization

A human liver cDNA library was used to isolate a clone coding for apolipoprotein A-I (Apo A-I). The clone carries the sequence for the prepeptide (18 amino acids), the propeptide (6 amino acids), and the mature protein (243 amino acids). A coding cassette for the proapo A-I molecule was reconstructed by fusing synthetic sequences, chosen to optimize expression and specifying the amino-terminal methionine and amino acids -6 to +14, to a large fragment of the cDNA coding for amino acids 15-243. The module was expressed in pOTS-Nco, an Escherichia coli expression vector carrying the regulatable X P^ promoter, leading to the production of proapolipoprotein A-I at up to 10% of total soluble proteins. The recombinant polypeptide was purified and characterized in terms of apparent molecular mass, isoelectric point, and by both chemical and enzymatic peptide mapping. In addition, it was assayed in vitro for the stimulation of the enzyme lecithin: cholesterol acyltransferase. The data show for the first time that proapo A-I can be produced efficiently in E. coli as a stable and undegraded protein having physical and functional properties indistinguishable from those of the natural product

M & L Jaargang 11/4

Jo Braeken Scholen om te leren. [Schools for learning.]Greet Plomteux Het koninklijk Atheneum te Antwerpen. [The Royal Atheneum at Antwerp.]Mario Vanroy Het Sint-Romboutscollege te Mechelen. [The Saint Rombout college at Mechelen.]Greta Paesmans De 18de-eeuwse universitaire colleges te Leuven. [The 18th century university colleges at Leuven.]Jos Gyselinck - De gemeentescholen van Bocholt en Diepenbeek. [The municipal schools of Bocholt and Diepenbeek.]Guillaume Bollen Het Heilig Hartinstituut te Maasmechelen. [The Sacred Heart insitute at Maasmechelen.]Kathleen Lanclus Het voormalige gymnasium van de Jezuïeten in Gent. [The former Jesult gymnasium in Ghent.]Chris Bogaert Het Rommelaere instituut en de instituten van de Bijloke te Gent. [The Rommelaere institute and the institutes of the Bijloke at Ghent.]Jos Stroobants De rijksnormaalschool te Brugge. [The state normal school in Bruges.]Anne-Marie Delepiere en Martine Huys De wederopbouwscholen in de Westhoek. [The post-war reconstruction schools in the Westhoek.]Jo Braeken De gemeentenscholen nr. 1 en nr. 2 te Elsene. [The municipal schools nr. 1 and nr. 2 in Elsene (Brussels).]M&L Binnenkran

Of journal editors and editorial boards: who are the trailblazers in increasing editorial board gender equality?

Female academics continue to be under-represented on the editorial boards of many, but not all, management journals. This variability is intriguing, because it is reasonable to assume that the size of the pool of female faculty available and willing to serve on editorial boards is similar for all management journals. Thus, we focus on the characteristics of the journal editors to explain this variability; journal editors or editors-in-chief are the most influential people in the selection of editorial board members. We draw on social identity and homosocial reproduction theories, and on the gender and careers literature to examine the relationship between an editor’s academic performance, professional age and gender, and editorial board gender equality. We collected longitudinal data at five points in time, using five-year intervals, from 52 management journals. To account for the nested structure of the data, a 3-level multilevel model was estimated. Overall, we found that the prospects of board membership improve for women when editors are high performing, professionally young, or female. We discuss these findings and their implications for management journals with low, stagnant, or declining representation of women in their boards

A cognitive latent variable model for the simultaneous analysis of behavioral and personality data

I describe a cognitive latent variable model, a combination of a cognitive model and a latent variable model that can be used to aggregate information regarding cognitive parameters across participants and tasks. The model is ideally suited for uncovering relationships between latent task abilities as they are expressed in experimental paradigms, but can also be used as data fusion tools to connect latent abilities with external covariates from entirely different data sources. An example application deals with the structure of cognitive abilities underlying an executive functioning task and its relation to personality traits. © 2014 Elsevier Inc

Faithful visualization of categorical data

Data is today collected in very large amounts from various kind of sources: shopping, genetic tests, etc. Given the amount of data collected, one might be interested in visualizing that data in a meaningful way. Due to their size, producing an image of such datasets is not easy as the image has to fit on the screen. Compression of the image is needed in order to have fewer elements to display. However, the quality of this compression greatly depends on the structure of the data. Given a binary matrix represented by white and black pixels, well separated groups of pixels (e.g. black and white points are respectively gathered together) gives a lower loss of information because summarizing that data concisely is easier. Moreover, reorganizing the rows and columns of a dataset can give interesting insights in structures hidden within the data. In this thesis, we introduce an innovative algorithm to reorder binary and categorical matrices using convolution. We then use the results of the algorithm to display the datasets faithfully.Master [120] : ingénieur civil en informatique, Université catholique de Louvain, 201

ConvoMap: Using Convolution to Order Boolean Data

Heatmaps, also called matrix visualisations, are a popular technique for visualising boolean data. They are easy to understand, and provide a relatively loss-free image of a given dataset. However, they are also highly dependent on the order of rows and columns chosen. We propose a novel technique, called {\em ConvoMap}, for ordering the rows and columns of a matrix such that the resulting image represents data faithfully. ConvoMap uses a novel optimisation criterion based on convolution to obtain a good column and row order. While in this paper we focus on the creation of images for exploratory data analysis in binary data, the simplicity of the ConvoMap optimisation criterion could allow for the creation of images for many other types of data as well