Unveiling the components of the signaling pathway between endosomes and the phagocytic uptake machinery in Dictyostelium discoideum

The soil amoebae Dictyostelium discoideum take up particles from their environment in order to obtain nutrition. The particle transits through the cell within a phagosome that fuses with organelles of different molecular compositions, undergoing a gradual degradation by different sets of hydrolytic enzymes. Griffiths’ concept of “phagosome individuality” predicts signaling from phagosomes into the cytoplasm, which might regulate many aspects of cell physiology. The finding that Dictyostelium cells depleted of the lysozyme AlyA or over-expressing the esterase Gp70 exhibit increased uptake of food particles, led to the postulation of a signaling cascade between endocytic compartments and the cytoskeletal uptake machinery at the plasma membrane. Assuming that Gp70 acts downstream of AlyA, gene-expression profiling of both mutants revealed different and overlapping sets of misregulated genes that might participate in this signaling cascade. Based on these results, we analyzed the effects of the artificial misregulation of six candidate genes by over-expression or negative genetic interference, in order to reconstruct at least part of the signaling pathway. SSB420 and SSL793 were chosen as candidates for the first signaling step, as they were up-regulated in AlyA-null cells and remained unaltered in the Gp70 over-expressing cells. The over-expression of SSB420 enhanced phagocytosis and raised the expression levels of Gp70, supporting its involvement in the signaling pathway between AlyA and Gp70 as a positive regulator of phagocytosis. However, this was not the case of cells over-expressing SSL793, as this mutation had no effects on phagocytosis. For the signaling downstream of Gp70, we studied four commonly misregulated genes in AlyA-depleted and Gp70 over-expressing cells. The expression levels of SLB350, SSB389 and TipD were lower in both mutants and therefore these were assumed as possible candidates for the negative regulation of phagocytosis. Cells depleted of SLB350 exhibited an increased phagocytic activity and no effect on Gp70 expression, proving its participation in the signaling pathway downstream of Gp70. Unlike SLB350, the disruption of the genes coding for SSB389 and TipD had no effects on particle uptake, excluding them from the pathway. The fourth candidate was Yipf1, the only gene that was commonly up-regulated in both mutants. Yet, the artificial over-expression of this protein had no effects on phagocytosis, so this candidate is also not included in the signaling pathway. Furthermore, localizing the products of the candidate genes within the cell helped unveiling several cellular organelles that receive signals from the phagosome and transduce them towards the uptake machinery.

Automatització d’una màquina de tall rotatiu

Molt sovint, a l’indústria de l’alimentació o de la cosmètica, hi ha promocions on s’afegeixen productes de regal; aquests els embalen amb un sleever (tipus de plàstic força rígid) que després retractilen. Aquestes promocions solen ser esporàdiques i canviants i això fa que no sigui factible la modificació de la línia de producció general per a realitzar-les. Per aquest motiu, moltes empreses disposen d’una petita màquina de tall rotatiu per a poder tallar els sleevers ells mateixos, i així tallar a molta velocitat i precisió aquestes petites produccions. Així doncs, esdevé molt interessant l’adquisició d’aquest tipus de maquinària. L’objectiu del projecte és fer l’automatització d’una màquina que pugui tallar aquest tipus de material ràpidament per fer-lo rentable

The automation and evaluation of nested clade phylogeographic analysis

Nested clade phylogeographic analysis (NCPA) is a popular method for reconstructing the demographic history of spatially distributed populations from genetic data. Although some parts of the analysis are automated, there is no unique and widely followed algorithm for doing this in its entirety, beginning with the data, and ending with the inferences drawn from the data. This article describes a method that automates NCPA, thereby providing a framework for replicating analyses in an objective way. To do so, a number of decisions need to be made so that the automated implementation is representative of previous analyses. We review how the NCPA procedure has evolved since its inception and conclude that there is scope for some variability in the manual application of NCPA. We apply the automated software to three published datasets previously analyzed manually and replicate many details of the manual analyses, suggesting that the current algorithm is representative of how a typical user will perform NCPA. We simulate a large number of replicate datasets for geographically distributed, but entirely random-mating, populations. These are then analyzed using the automated NCPA algorithm. Results indicate that NCPA tends to give a high frequency of false positives. In our simulations we observe that 14% of the clades give a conclusive inference that a demographic event has occurred, and that 75% of the datasets have at least one clade that gives such an inference. This is mainly due to the generation of multiple statistics per clade, of which only one is required to be significant to apply the inference key. We survey the inferences that have been made in recent publications and show that the most commonly inferred processes (restricted gene flow with isolation by distance and contiguous range expansion) are those that are commonly inferred in our simulations. However, published datasets typically yield a richer set of inferences with NCPA than obtained in our random-mating simulations, and further testing of NCPA with models of structured populations is necessary to examine its accuracy.

The automation of nested clade phylogeographic analysis

ANeCA is a fully automated implementation of Nested Clade Phylogeographic Analysis. This was originally developed by Templeton and colleagues, and has been used to infer, from the pattern of gene sequence polymorphisms in a geographically structured population, the historical demographic processes that have shaped its evolution. Until now it has been necessary to perform large parts of the procedure manually. We provide a program that will take data in Nexus sequential format, and directly output a set of inferences. The software also includes TCS v1.18 and GeoDis v2.2 as part of automation.

Targeting the cell cycle machinery for the treatment of cardiovascular disease

Cardiovascular disease represents a major clinical problem affecting a significant proportion of the world's population and remains the main cause of death in the UK. The majority of therapies currently available for the treatment of cardiovascular disease do not cure the problem but merely treat the symptoms. Furthermore, many cardioactive drugs have serious side effects and have narrow therapeutic windows that can limit their usefulness in the clinic. Thus, the development of more selective and highly effective therapeutic strategies that could cure specific cardiovascular diseases would be of enormous benefit both to the patient and to those countries where healthcare systems are responsible for an increasing number of patients. In this review, we discuss the evidence that suggests that targeting the cell cycle machinery in cardiovascular cells provides a novel strategy for the treatment of certain cardiovascular diseases. Those cell cycle molecules that are important for regulating terminal differentiation of cardiac myocytes and whether they can be targeted to reinitiate cell division and myocardial repair will be discussed as will the molecules that control vascular smooth muscle cell (VSMC) and endothelial cell proliferation in disorders such as atherosclerosis and restenosis. The main approaches currently used to target the cell cycle machinery in cardiovascular disease have employed gene therapy techniques. We will overview the different methods and routes of gene delivery to the cardiovascular system and describe possible future drug therapies for these disorders. Although the majority of the published data comes from animal studies, there are several instances where potential therapies have moved into the clinical setting with promising results.

Reprogramming the cell cycle machinery to treat cardiovascular disease

Coronary artery disease is one of the most common heart pathologies. Restriction of blood flow to the heart by atherosclerotic lesions, leading to angina pectoris and myocardial infarction, damages the heart, resulting in impaired cardiac function. Damaged myocardium is replaced by scar tissue since surviving cardiomyocytes are unable to proliferate to replace lost heart tissue. Although narrowing of the coronary arteries can be treated successfully using coronary revascularisation procedures, re-occlusion of the treated vessels remains a significant clinical problem. Cell cycle control mechanisms are key in both the impaired cardiac repair by surviving cardiomyocytes and re-narrowing of treated vessels by maladaptive proliferation of vascular smooth muscle cells. Strategies targeting the cell cycle machinery in the heart and vasculature offer promise both for the improvement of cardiac repair following MI and the prevention of restenosis and bypass graft failure following revascularisation procedures.

Integrative workflow-embedded support for process automation and management

This paper presents the on-going research performed in order to integrate process automation and process management support in the context of media production. This has been addressed on the basis of a holistic approach to software engineering applied to media production modelling to ensure design correctness, completeness and effectiveness. The focus of the research and development has been to enhance the metadata management throughout the process in a similar fashion to that achieved in Decision Support Systems (DSS) to facilitate well-grounded business decisions. The paper sets out the aims and objectives and the methodology deployed. The paper describes the solution in some detail and sets out some preliminary conclusions and the planned future work.

Multivariable cluster analysis for high-speed industrial machinery

The overall operation and internal complexity of a particular production machinery can be depicted in terms of clusters of multidimensional points which describe the process states, the value in each point dimension representing a measured variable from the machinery. The paper describes a new cluster analysis technique for use with manufacturing processes, to illustrate how machine behaviour can be categorised and how regions of good and poor machine behaviour can be identified. The cluster algorithm presented is the novel mean-tracking algorithm, capable of locating N-dimensional clusters in a large data space in which a considerable amount of noise is present. Implementation of the algorithm on a real-world high-speed machinery application is described, with clusters being formed from machinery data to indicate machinery error regions and error-free regions. This analysis is seen to provide a promising step ahead in the field of multivariable control of manufacturing systems.

Bio-inspired ant colony optimization based clustering algorithm with mobile sinks for applications in consumer home automation networks

With the fast development of wireless communications, ZigBee and semiconductor devices, home automation networks have recently become very popular. Since typical consumer products deployed in home automation networks are often powered by tiny and limited batteries, one of the most challenging research issues is concerning energy reduction and the balancing of energy consumption across the network in order to prolong the home network lifetime for consumer devices. The introduction of clustering and sink mobility techniques into home automation networks have been shown to be an efficient way to improve the network performance and have received significant research attention. Taking inspiration from nature, this paper proposes an Ant Colony Optimization (ACO) based clustering algorithm specifically with mobile sink support for home automation networks. In this work, the network is divided into several clusters and cluster heads are selected within each cluster. Then, a mobile sink communicates with each cluster head to collect data directly through short range communications. The ACO algorithm has been utilized in this work in order to find the optimal mobility trajectory for the mobile sink. Extensive simulation results from this research show that the proposed algorithm significantly improves home network performance when using mobile sinks in terms of energy consumption and network lifetime as compared to other routing algorithms currently deployed for home automation networks.