In silico constraint-based strain optimization methods: the quest for optimal cell factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

Dielectric relaxation and ferromagnetic resonance in magnetoelectric (Polyvinylidene-fluoride)/ferrite composites

In this work the dielectric properties and ferromagnetic resonance of Polyvinylidene- uoride embedded with 10 wt. % of NiFe2O4 or Ni0.5Zn0.5Fe2O4 nanoparticles are presented. The mechanisms of the dielectric relaxation in these two composites do not differ from each other. For more precise characterization of the dielectric relaxation, a two dimensional distribution of relaxation times was calculated from the temperature dependencies of the complex dielectric permittivity. The results obtained from the 2D distribution and the mean relaxation time are found to be consistent. The dynamics of the dielectric permittivity is described by the Arrhenius law. The energy and attempt time of the dielectric relaxators lie in a narrow energy and time region thus proving that the single type chains of polymer are responsible for a dispersion. The magnetic properties of the composites were investigated using the fer- romagnetic resonance. A single resonance line was observed for both samples. From the temperature dependence (100 K - 310 K) of the resonance eld and linewidth, the origin of the observed line was attributed to the NiFe2O4 and Ni0.5Zn0.5Fe2O4 superparamagnetic nanoparticles. By measuring lms at dif- ferent orientations with respect to the external magnetic eld, the angular dependence of the resonance was observed, indicating the magnetic dipolar in-plane interactions.

Dielectric relaxation dynamics of high-temperature piezoelectric polyimide copolymers

Polyimide co-polymers have been prepared based on different diamines as co-monomers: a diamine without CN groups and a novel synthesized diamine with two CN groups prepared by polycondensation reaction followed by thermal cyclodehydration. Dielectric spectroscopy measurements were performed and the dielectric complex function, ac conductivity and electric modulus of the co-polymers were investigated as a function of CN group content in the frequency range from 0.1 Hz to 107 Hz at temperatures from 25 to 260 °C. For all samples and temperatures above 150ºC, the dielectric constant increases with increasing temperature due to increaseing conductivity. The α-relaxation is just detected for the sample without CN groups, being this relaxation overlapped by the electrical conductivity contributions in the remaining samples. For the copolymer samples and the polymer with CN groups an important Maxwell-Wagner-Sillars contribution is detected. The mechanisms responsible for the dielectric relaxation, conduction process and electric modulus response have been discussed as a function of the CN groups content present in the samples.

Project management under uncertainty: a study on solution methods

Project Management involves onetime endeavors that demand for getting it right the first time. On the other hand, project scheduling, being one of the most modeled project management process stages, still faces a wide gap from theory to practice. Demanding computational models and their consequent call for simplification, divert the implementation of such models in project management tools from the actual day to day project management process. Special focus is being made to the robustness of the generated project schedules facing the omnipresence of uncertainty. An "easy" way out is to add, more or less cleverly calculated, time buffers that always result in project duration increase and correspondingly, in cost. A better approach to deal with uncertainty seems to be to explore slack that might be present in a given project schedule, a fortiori when a non-optimal schedule is used. The combination of such approach to recent advances in modeling resource allocation and scheduling techniques to cope with the increasing flexibility in resources, as can be expressed in "Flexible Resource Constraint Project Scheduling Problem" (FRCPSP) formulations, should be a promising line of research to generate more adequate project management tools. In reality, this approach has been frequently used, by project managers in an ad-hoc way.

On the Hill estimator: a comparison of methods

Extreme value theory (EVT) deals with the occurrence of extreme phenomena. The tail index is a very important parameter appearing in the estimation of the probability of rare events. Under a semiparametric framework, inference requires the choice of a number k of upper order statistics to be considered. This is the crux of the matter and there is no definite formula to do it, since a small k leads to high variance and large values of k tend to increase the bias. Several methodologies have emerged in literature, specially concerning the most popular Hill estimator (Hill, 1975). In this work we compare through simulation well-known procedures presented in Drees and Kaufmann (1998), Matthys and Beirlant (2000), Beirlant et al. (2002) and de Sousa and Michailidis (2004), with a heuristic scheme considered in Frahm et al. (2005) within the estimation of a different tail measure but with a similar context. We will see that the new method may be an interesting alternative.

Comparing different methods to measure biofilm thickness: the techniques are: optical coherence tomography, confocal laser scanning microscopy and low load compression test

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Engenharia Clínica)

Finite integration methods for isospectral flows

In this paper we consider the approximate computation of isospectral flows based on finite integration methods( FIM) with radial basis functions( RBF) interpolation,a new algorithm is developed. Our method ensures the symmetry of the solutions. Numerical experiments demonstrate that the solutions have higher accuracy by our algorithm than by the second order Runge- Kutta( RK2) method.

Cardio-respiratory symptoms in panic disorder: a contribution from cognitive-behaviour therapy

Objective: To compare patients with panic disorder with agoraphobia treated with cognitive-behavioural therapy (CBT) associated with the medication with patients treated only with medication and verify the behaviour of the cardio-respiratory symptoms of both groups. Methods: Randomized sample in the Psychiatry Institute of the Federal University of Rio de Janeiro, divided in two groups of 25 participants each. Group 1 undertook 10 weekly sessions of CBT with one hour of duration each together with medication. Group 2, Control, were administered medication that only consisted of tricyclic anti-depressants and selective inhibitors of the re-uptake of serotonin. Evaluation instruments were applied at the beginning and to the end of the interventions. Results: According to the applied scales, group 1 showed statistically more significant results than group 2, with: reduction of panic attacks, cardio-respiratory symptoms, anticipatory anxiety, agoraphobia avoidance and fear of bodily sensations. Conclusion: Exposures (in vivo and interoceptive), especially for induction symptom exercises and relaxation, were considered essential to prepare patients with panic disorder to handle future cardio-respiratory symptoms and panic attacks with agoraphobia.

Development of computational and experimental methods for biomass composition and evaluation of its impact in genome-scale models prediction

The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.

Methods to solve the equations of motion

"Series title: Springerbriefs in applied sciences and technology, ISSN 2191-530X"

Integration methods in dynamic analysis

"Series title: Springerbriefs in applied sciences and technology, ISSN 2191-530X"

Effects of protein-calorie restriction on mechanical function of hypertrophied cardiac muscle

OBJECTIVE: To assess the effect of food restriction (FR) on hypertrophied cardiac muscle in spontaneously hypertensive rats (SHR). METHODS: Isolated papillary muscle preparations of the left ventricle (LV) of 60-day-old SHR and of normotensive Wistar-Kyoto (WKY) rats were studied. The rats were fed either an unrestricted diet or FR diet (50% of the intake of the control diet) for 30 days. The mechanical function of the muscles was evaluated through monitoring isometric and isotonic contractions. RESULTS: FR caused: 1) reduction in the body weight and LV weight of SHR and WKY rats; 2) increase in the time to peak shortening and the time to peak developed tension (DT) in the hypertrophied myocardium of the SHR; 3) diverging changes in the mechanical function of the normal cardiac muscles of WKY rats with reduction in maximum velocity of isotonic shortening and of the time for DT to decrease 50% of its maximum value, and increase of the resting tension and of the rate of tension decline. CONCLUSION: Short-term FR causes prolongation of the contraction time of hypertrophied muscles and paradoxal changes in mechanical performance of normal cardiac fibers, with worsening of the shortening indices and of the resting tension, and improvement of the isometric relaxation.

Doppler echocardiographic evaluation of HIV-positive patients in different stages of the disease

OBJETIVE: To evaluate by Doppler echocardiography (DE) early abnormalities of ventricular function in HIV-positive patients, as well as other cardiac abnormalities that can be detected by this method, with special emphasis on mitral valve flow. METHODS: 84 HIV- positive patients, 59 with CD4 cell count >500/mm³ (Group A) and 25 with CD4 cell count <500/mm³ (Group B), were analyzed. CD4 cells were counted and matched with structural data and systolic and diastolic function of the left ventricle (LV), as analyzed by DE. The results were compared with those obtained in 47 healthy individuals (Group C). RESULTS: 8% of patients in Group B had mild pericardial effusion; 31.5% showed decreased systolic function of the LV, and 12% had moderate mitral regurgitation. A wave velocity from the mitral inflow was different among the 3 groups, being higher in Group B, where the deceleration time of the E wave of the mitral inflow and the E/A ratio were significantly lower with a normal value of the isovolumic relaxation time (IVRT). CONCLUSION: HIV-positive patients with a CD4 cell count >500/mm³ had no abnormalities by DE. Patients with a more advanced infection (those with a CD4 cell count <500/mm³), had a significantly abnormal LV systolic function and a higher incidence of pericardial effusion and mitral regurgitation. Mitral valve inflow by Doppler did not indicate diastolic dysfunction.

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.