Cdc42 oscillations in yeasts.

A fundamental problem in cell biology is how cells define one or several discrete sites of polarity. Through mechanisms involving positive and negative feedback, the small Rho-family guanosine triphosphatase Cdc42 breaks symmetry in round budding yeast cells to define a single site of polarized cell growth. However, it is not clear how cells can define multiple sites of polarization concurrently. We discuss a study in which rod-shaped fission yeast cells, which naturally polarize growth at their two cell ends, exhibited oscillations of Cdc42 activity between these sites. We compare these findings with similar oscillatory behavior of Cdc42 detected in budding yeast cells and discuss the possible mechanism and functional outputs of these oscillations.

Malassezia yeasts activate the NLRP3 inflammasome in antigen-presenting cells via Syk-kinase signalling.

Although being a normal part of the skin flora, yeasts of the genus Malassezia are associated with several common dermatologic conditions including pityriasis versicolour, seborrhoeic dermatitis (SD), folliculitis, atopic eczema/dermatitis (AE/AD) and dandruff. While Malassezia spp. are aetiological agents of pityriasis versicolour, a causal role of Malassezia spp. in AE/AD and SD remains to be established. Previous reports have shown that fungi such as Candida albicans and Aspergillus fumigatus are able to efficiently activate the NLRP3 inflammasome leading to robust secretion of the pro-inflammatory cytokine IL-1β. To date, innate immune responses to Malassezia spp. are not well characterized. Here, we show that different Malassezia species could induce NLRP3 inflammasome activation and subsequent IL-1β secretion in human antigen-presenting cells. In contrast, keratinocytes were not able to secrete IL-1β when exposed to Malassezia spp. Moreover, we demonstrate that IL-1β secretion in antigen-presenting cells was dependent on Syk-kinase signalling. Our results identify Malassezia spp. as potential strong inducers of pro-inflammatory responses when taken up by antigen-presenting cells and identify C-type lectin receptors and the NLRP3 inflammasome as crucial actors in this process.

Complete DNA sequence of Kuraishia capsulata illustrates novel genomic features among budding yeasts (Saccharomycotina)

The numerous yeast genome sequences presently available provide a rich source of information for functional as well as evolutionary genomics but unequally cover the large phylogenetic diversity of extant yeasts. We present here the complete sequence of the nuclear genome of the haploid-type strain of Kuraishia capsulata (CBS1993(T)), a nitrate-assimilating Saccharomycetales of uncertain taxonomy, isolated from tunnels of insect larvae underneath coniferous barks and characterized by its copious production of extracellular polysaccharides. The sequence is composed of seven scaffolds, one per chromosome, totaling 11.4 Mb and containing 6,029 protein-coding genes, ~13.5% of which being interrupted by introns. This GC-rich yeast genome (45.7%) appears phylogenetically related with the few other nitrate-assimilating yeasts sequenced so far, Ogataea polymorpha, O. parapolymorpha, and Dekkera bruxellensis, with which it shares a very reduced number of tRNA genes, a novel tRNA sparing strategy, and a common nitrate assimilation cluster, three specific features to this group of yeasts. Centromeres were recognized in GC-poor troughs of each scaffold. The strain bears MAT alpha genes at a single MAT locus and presents a significant degree of conservation with Saccharomyces cerevisiae genes, suggesting that it can perform sexual cycles in nature, although genes involved in meiosis were not all recognized. The complete absence of conservation of synteny between K. capsulata and any other yeast genome described so far, including the three other nitrate-assimilating species, validates the interest of this species for long-range evolutionary genomic studies among Saccharomycotina yeasts.

Visual Measurement and Modelling of Tool Wear in Rough Turning

Huolimatta korkeasta automaatioasteesta sorvausteollisuudessa, muutama keskeinen ongelma estää sorvauksen täydellisen automatisoinnin. Yksi näistä ongelmista on työkalun kuluminen. Tämä työ keskittyy toteuttamaan automaattisen järjestelmän kulumisen, erityisesti viistekulumisen, mittaukseen konenäön avulla. Kulumisen mittausjärjestelmä poistaa manuaalisen mittauksen tarpeen ja minimoi ajan, joka käytetään työkalun kulumisen mittaukseen. Mittauksen lisäksi tutkitaan kulumisen mallinnusta sekä ennustamista. Automaattinen mittausjärjestelmä sijoitettiin sorvin sisälle ja järjestelmä integroitiin onnistuneesti ulkopuolisten järjestelmien kanssa. Tehdyt kokeet osoittivat, että mittausjärjestelmä kykenee mittaamaan työkalun kulumisen järjestelmän oikeassa ympäristössä. Mittausjärjestelmä pystyy myös kestämään häiriöitä, jotka ovat konenäköjärjestelmille yleisiä. Työkalun kulumista mallinnusta tutkittiin useilla eri menetelmillä. Näihin kuuluivat muiden muassa neuroverkot ja tukivektoriregressio. Kokeet osoittivat, että tutkitut mallit pystyivät ennustamaan työkalun kulumisasteen käytetyn ajan perusteella. Parhaan tuloksen antoivat neuroverkot Bayesiläisellä regularisoinnilla.

Attracting cavities for docking. Replacing the rough energy landscape of the protein by a smooth attracting landscape.

Molecular docking is a computational approach for predicting the most probable position of ligands in the binding sites of macromolecules and constitutes the cornerstone of structure-based computer-aided drug design. Here, we present a new algorithm called Attracting Cavities that allows molecular docking to be performed by simple energy minimizations only. The approach consists in transiently replacing the rough potential energy hypersurface of the protein by a smooth attracting potential driving the ligands into protein cavities. The actual protein energy landscape is reintroduced in a second step to refine the ligand position. The scoring function of Attracting Cavities is based on the CHARMM force field and the FACTS solvation model. The approach was tested on the 85 experimental ligand-protein structures included in the Astex diverse set and achieved a success rate of 80% in reproducing the experimental binding mode starting from a completely randomized ligand conformer. The algorithm thus compares favorably with current state-of-the-art docking programs. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Influence of duty factor on the die-sinking Electrical Discharge Machining of high-strength aluminum alloy under rough machining

The use of high-strength aluminium alloys as material for injection molding tools to produce small and medium batches of plastic products as well as prototyping molds is becoming of increasing demand by the tooling industry. These alloys are replacing the traditional use of steel in the cases above because they offer many advantages such as very high thermal conductivity associated with good corrosion and wear resistance presenting good machinability in milling and electrical discharge machining operations. Unfortunately there is little technological knowledge on the Electrical Discharge Machining (EDM) of high-strength aluminium alloys, especially about the AMP 8000 alloy. The duty factor, which means the ratio between pulse duration and pulse cycle time exerts an important role on the performance of EDM. This work has carried out an experimental study on the variation of the duty factor in order to analyze its influence on material removal rate and volumetric relative wear under roughing conditions of EDM process. The results showed that high values of duty factor are possible to be applied without bringing instability into the EDM process and with improvement of material removal rate and volumetric relative wear.

Genetic engineering of baker's and wine yeasts using formaldehyde hyperresistance-mediating plasmids

Yeast multi-copy vectors carrying the formaldehyde-resistance marker gene SFA have proved to be a valuable tool for research on industrially used strains of Saccharomyces cerevisiae. The genetics of these strains is often poorly understood, and for various reasons it is not possible to simply subject these strains to protocols of genetic engineering that have been established for laboratory strains of S. cerevisiae. We tested our vectors and protocols using 10 randomly picked baker's and wine yeasts all of which could be transformed by a simple protocol with vectors conferring hyperresistance to formaldehyde. The application of formaldehyde as a selecting agent also offers the advantage of its biodegradation to CO2 during fermentation, i.e., the selecting agent will be consumed and therefore its removal during down-stream processing is not necessary. Thus, this vector provides an expression system which is simple to apply and inexpensive to use

Modelling Cutting States in Rough Turning of 34CrNiMo6 Steel

Rough turning is an important form of manufacturing cylinder-symmetric parts. Thus far, increasing the level of automation in rough turning has included process monitoring methods or adaptive turning control methods that aim to keep the process conditions constant. However, in order to improve process safety, quality and efficiency, an adaptive turning control should be transformed into an intelligent machining system optimizing cutting values to match process conditions or to actively seek to improve process conditions. In this study, primary and secondary chatter and chip formation are studied to understand how to measure the effect of these phenomena to the process conditions and how to avoid undesired cutting conditions. The concept of cutting state is used to address the combination of these phenomena and the current use of the power capacity of the lathe. The measures to the phenomena are not developed based on physical measures, but instead, the severity of the measures is modelled against expert opinion. Based on the concept of cutting state, an expert system style fuzzy control system capable of optimizing the cutting process was created. Important aspects of the system include the capability to adapt to several cutting phenomena appearing at once, even if the said phenomena would potentially require conflicting control action.

Rough, tough and dependable

Some of your customers could care less what kind of zipper they find in their clothes. All they do is give it the roughest workout.

Rough sketch of butter concepts

"Roughs" of butter concepts, showing a woman preparing peas with butter

Rough draft of the script for "The Swimmer"

A draft with handwritten notes of "The Swimmer" script for use in the 1984 nutrition campaign.

Improving the Scalability of Reduct Determination in Rough Sets

Rough Set Data Analysis (RSDA) is a non-invasive data analysis approach that solely relies on the data to find patterns and decision rules. Despite its noninvasive approach and ability to generate human readable rules, classical RSDA has not been successfully used in commercial data mining and rule generating engines. The reason is its scalability. Classical RSDA slows down a great deal with the larger data sets and takes much longer times to generate the rules. This research is aimed to address the issue of scalability in rough sets by improving the performance of the attribute reduction step of the classical RSDA - which is the root cause of its slow performance. We propose to move the entire attribute reduction process into the database. We defined a new schema to store the initial data set. We then defined SOL queries on this new schema to find the attribute reducts correctly and faster than the traditional RSDA approach. We tested our technique on two typical data sets and compared our results with the traditional RSDA approach for attribute reduction. In the end we also highlighted some of the issues with our proposed approach which could lead to future research.

GA approach for finding Rough Set decision rules based on bireducts

Feature selection plays an important role in knowledge discovery and data mining nowadays. In traditional rough set theory, feature selection using reduct - the minimal discerning set of attributes - is an important area. Nevertheless, the original definition of a reduct is restrictive, so in one of the previous research it was proposed to take into account not only the horizontal reduction of information by feature selection, but also a vertical reduction considering suitable subsets of the original set of objects. Following the work mentioned above, a new approach to generate bireducts using a multi--objective genetic algorithm was proposed. Although the genetic algorithms were used to calculate reduct in some previous works, we did not find any work where genetic algorithms were adopted to calculate bireducts. Compared to the works done before in this area, the proposed method has less randomness in generating bireducts. The genetic algorithm system estimated a quality of each bireduct by values of two objective functions as evolution progresses, so consequently a set of bireducts with optimized values of these objectives was obtained. Different fitness evaluation methods and genetic operators, such as crossover and mutation, were applied and the prediction accuracies were compared. Five datasets were used to test the proposed method and two datasets were used to perform a comparison study. Statistical analysis using the one-way ANOVA test was performed to determine the significant difference between the results. The experiment showed that the proposed method was able to reduce the number of bireducts necessary in order to receive a good prediction accuracy. Also, the influence of different genetic operators and fitness evaluation strategies on the prediction accuracy was analyzed. It was shown that the prediction accuracies of the proposed method are comparable with the best results in machine learning literature, and some of them outperformed it.

Rough copy of the balance sheet to May 31, 1882

Rough copy of the balance sheet (3 pages, handwritten) to May 31, 1882.

Rough draft of a letter to John I. Mackenzie [from S.D. Woodruff]

Rough draft of a letter to John I. Mackenzie [from S.D. Woodruff]. The letter is illegible (1 doublesided page, handwritten), Dec. 6, 1881.