Young and embedded clusters in Cygnus-X: evidence for building up the IMF?

We provide a new view on the Cygnus-X north complex by accessing for the first time the low mass content of young stellar populations in the region. CFHT/WIRCam camera was used to perform a deep near-IR survey of this complex, sampling stellar masses down to ~0.1 M$_\odot$. Several analysis tools, including a extinction treatment developed in this work, were employed to identify and uniformly characterise a dozen unstudied young star clusters in the area. Investigation of their mass distributions in low-mass domain revealed a relatively uniform log-normal IMF with a characteristic mass of 0.32$\pm$0.08 M$_\odot$ and mass dispersion of 0.40$\pm$0.06. In the high mass regime, their derived slopes showed that while the youngest clusters (age < 4 Myr) presented slightly shallower values with respect to the Salpeter's, our older clusters (4 Myr < age < 18 Myr) showed IMF compliant values and a slightly denser stellar population. Although possibly evidencing a deviation from an 'universal' IMF, these results also supports a scenario where these gas dominated young clusters gradually 'build up' their IMF by accreting low-mass stars formed in their vicinity during their first ~3 Myr, before the gas expulsion phase, emerging at the age of ~4 Myr with a fully fledged IMF. Finally, the derived distances to these clusters confirmed the existence of at least 3 different star forming regions throughout Cygnus-X north complex, at distances of 500-900 pc, 1.4-1.7 kpc and 3.0 kpc, and revealed evidence of a possible interaction between some of these stellar populations and the Cygnus-OB2 association.Comment: 20 pages, 19 figures. Contains an appendix with 10 extra figure

An integrated framework for strain optimization

The identification of genetic modifications leading to mutant strains able to overproduce compounds of industrial interest is a challenging task in Metabolic Engineering (ME). Several methods have been proposed but, to some extent, none of them is suitable for all the specificities of each particular strain optimization problem. This work proposes an integrated framework that allows its users to configure and fine tune all the various steps involved in a strain optimization strategy, including the loading of models in distinct formats, the definition of a suitable phenotype simulation method and the choice and configuration of the strain optimization engine. Moreover, it is designed to suit the needs of users skilled at programming, as well as less advanced users. The framework includes a GUI implemented as the strain optimization plug-in for the OptFlux workbench (version 3), a reference platform for ME (http://www.optflux.org). All the code is distributed under the GPLv3 licence and it is fully available (http://sourceforge.net/projects/optflux/).This work is partially funded by ERDF- European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within projects ref. COMPETE FCOMP- 01-0124-FEDER-015079 and PTDC/EBB-EBI/104235/2008. This work is also funded by National Funds through the FCT within project PEst-OE/EEI/UI0752/2011. The work of PM was supported by the FCT through the Ph.D. grant SFRH/BD/61465/2009

On the effects of phenotype prediction methods over strain design algorithms. A multi-objective approach

The past two decades have witnessed great advances in the computational modeling and systems biology fields. Soon after the first models of metabolism were developed, several methods for the prediction of phenotypes were also put forward. With the ever-growing information provided by such methods, new questions arose. Metabolic Engineering in particular posed some interesting questions. Recently, Schuetz and co-workers proposed that the metabolism of bacteria operates close to the Pareto-optimal surface of a three-dimensional space definedned by competing objectives and demonstrated the validity of their claims for various environmental perturbations. However, phenotype prediction methods have all been developed to operate based on the assumption of a given single-objective, as an example Flux Balance Analysis (FBA) often assumes that the organisms are evolutionarily optimized towards optimal growth. On the other hand, Minimization of Metabolic Adjustment (MOMA) proposes that after a perturbation, the goal of the organisms shifts from optimal growth to the minimization of the global metabolic adjustment relative to the wild-type. Albeit multi-objective approaches focused on the bio-engineering objectives have been proposed, none tackles the multi-objective nature of the cellular objectives. In this work we analyze the inuence of several phenotype prediction methods on the strainsdesigned by metaheuristic algorithms and suggest a multi-objective approach capable of finding designs compliant with the cellular objectives assumed by the various phenotype prediction methods. Using a recent model of Escherichia coli K12, we observed the effect of different phenotype prediction methods in the convergence of metaheuristic algorithms performing strain optimization, evolving growth-coupled production mutants in aerobic and anaerobic conditions. A critical analysis of the different mutant ux distributions was performed, and we concluded that, for a selected phenotype prediction method, the strain designs proposed by the optimization algorithms were generally not robust when another method was used to predict their phenotypes. There is variation in the Biomass-product coupled yield (BPCY) of aerobically succinate producing mutants with glucose as carbon source, when solutions generated with either pFBA (a variation of FBA that minimizes the overall use of enzyme-associated flux) or LMOMA (a linear implementation of MOMA) (box colors) are simulated with the other (x-axis). Besides the great variation in fitness for the different phenotype simulation methods, we veri_ed that in some cases less than 10% of the solutions generated by pFBA are valid in LMOMA (BPCY _ 0:0001). Assumptions regarding the cellular objectives of an organism when subjected to distinct conditions (environmental, genetic, etc.) are still the object of active discussion. This fact motivated us to develop a method capable of suggesting designs compliant with more than one phenotype prediction method. Solutions generated by our method are simulated using pFBA and LMOMA and plotted by BPCY for both phenotype simulation methods. The ad-hoc clusters reveal a group of interesting solutions (cluster 2). An analysis on the flux distribution of the solutions presented in these clusters is also provided and a rational for robust solution design is derived

A generic multi-criterion approach for mutant strain optimization

Motivation: The identification of genetic modifications that can lead to mutant strains that overproduce compounds of industrial interest is a challenging task in Metabolic Engineering. Evolutionary Algorithms and other metaheuristics have provided successful methods for solving the underlying in silico bi-level optimization problems (e.g. to find the best set of gene knockouts) [1]. Although these algorithms perform well in some criteria, they lose sense of the inner multi-objective nature of these problems. Results: In this work, these tasks are viewed as multi-objective optimization problems and algorithms based on multi-objective EAs are proposed. The objectives include maximizing the production of the compound of interest, maximizing biomass and minimizing the number of knockouts. Furthermore, a generalization to integrate multiple-criterion capabilities into single-objective algorithms is proposed and implemented as an ensemble method. This new approach allows taking advantage of the solution space sampling capabilities of some algorithms (e.g. Simulated Annealing), while generating the set of solutions (Pareto-front) according to the multiobjective premises. The algorithms are validated with two case studies, where E. coli is used to produce succinate and lactate. Results show that this option provides an efficient alternative to the previous approaches, returning not a single solution, but rather sets of solutions that are trade-offs among the distinct objective functions. Availability: Algorithms are implemented as a plug-in for the open-source OptFlux [2] platform available in the site http://www.optflux.org

The mathematical description of the electrosynthesis of composites of oxy-hydroxycompounds cobalt with polypyrrole overooxidazed

The electrosynthesis of the composite with of the overoxidized polypyrrole with cobalt oxy-hydroxide in strongly acidic media has been described mathematically, using linear stability theory and bifurcation analysis. The steadystates stability conditions and oscillatory and monotonic instability requirements have been described too. The system´s behavior was compared with behavior of other systems with overoxidation, electropolymerization of heterocyclic compounds and electrosynthesis of the cobalt oxy-hydroxides

Diffusive epidemic process: theory and simulation

We study the continuous absorbing-state phase transition in the one-dimensional diffusive epidemic process via mean-field theory and Monte Carlo simulation. In this model, particles of two species (A and B) hop on a lattice and undergo reactions B -> A and A + B -> 2B; the total particle number is conserved. We formulate the model as a continuous-time Markov process described by a master equation. A phase transition between the (absorbing) B-free state and an active state is observed as the parameters (reaction and diffusion rates, and total particle density) are varied. Mean-field theory reveals a surprising, nonmonotonic dependence of the critical recovery rate on the diffusion rate of B particles. A computational realization of the process that is faithful to the transition rates defining the model is devised, allowing for direct comparison with theory. Using the quasi-stationary simulation method we determine the order parameter and the survival time in systems of up to 4000 sites. Due to strong finite-size effects, the results converge only for large system sizes. We find no evidence for a discontinuous transition. Our results are consistent with the existence of three distinct universality classes, depending on whether A particles diffusive more rapidly, less rapidly, or at the same rate as B particles.Comment: 19 pages, 5 figure

Food insecurity is associated with an unhealthy lifestyle score in middle- and older-aged adults: findings from the EPIPorto cohort

The association of food insecurity with the combined effect of lifestyles is still limited. This study evaluated the association between food insecurity and a lifestyle score in middle- and older-aged adults. A cross-sectional study (2013-2016) was performed among 595 individuals (>= 50 years) from the EPIPorto cohort (Porto, Portugal). Food security status was assessed using the US Household Food Security Survey Module: Six-Item Short Form. Information on fruit and vegetable consumption (F&V), physical activity (PA) practice, tobacco smoking, and alcohol consumption were included in a lifestyle score. Those with F&V one drink of alcoholic beverages in women, and > two in men were assigned with one point; all the others had nil points. The score could range from 0 to 4, and was further categorised into three categories. Food insecurity was positively associated with an unhealthy lifestyle profile (OR = 2.272; 95%CI:1.079-4.782), independently of the adjustment variables. Analysing each lifestyle component, food insecurity was associated with low PA practice (OR = 2.365; 95%CI:1.020-5.485). Individuals from food insecure households were more likely to have an unhealthy lifestyle profile. Public health strategies should be developed among food insecure individuals to promote healthy lifestyles

Portal Vein Aneurysm Mimicking a Liver Nodule

info:eu-repo/semantics/publishedVersio

Prolonged Thrombocytopenia in a Child with Severe Neonatal Alloimmune Reaction and Noonan Syndrome

Fetomaternal alloimmune thrombocytopenia (FMAIT) caused by maternal antibodies is the leading cause of severe neonatal thrombocytopenia. A 1-month-old Caucasian girl was referred to our Hematology Clinic for persistent thrombocytopenia diagnosed after a bleeding episode. Diagnostic tests suggested FMAIT. Mild thrombocytopenia persisted for 18 months, and subsequent findings of dysmorphic facies, short stature and mild pulmonary stenosis led to the hypothesis of Noonan syndrome (NS), which was confirmed by genetic test. Other hematological abnormalities were excluded and she had no further bleeding episodes. This case illustrates the possibility of different diagnoses with the same clinical manifestations. The persistence of thrombocytopenia longer than expected associated with typical physical features led to the diagnosis of NS.info:eu-repo/semantics/publishedVersio

OptFerm - a computational platform for the optimization of fermentation processes

We present OptFerm, a computational platform for the simulation and optimization of fermentation processes. The aim of this project is to offer a platform-independent, user-friendly, open-source and extensible environment for Bioengineering process optimization that can be used to increase productivity. This tool is focused in optimizing a feeding trajectory to be fed into a fed-batch bioreactor and to calculate the best concentration of nutrients to initiate the fermentation. Also, a module for the estimation of kinetic and yield parameters has been developed, allowing the use of experimental data obtained from batch or fed-batch fermentations to reach the best possible model setup. The software was built using a component-based modular development methodology, using Java as the programming language. AlBench. a Model-View-Control based application framework was used as the basis to implement the different data objects and operations, as well as their graphical user interfaces. Also, this allows the tool to be easily extended with new modules, currently being developed