Cylindrically symmetric models of gravitational collapse to black holes: a short review

We survey results about exact cylindrically symmetric models of gravitational collapse in General Relativity. We focus on models which result from the matching of two spacetimes having collapsing interiors which develop trapped surfaces and vacuum exteriors containing gravitational waves. We collect some theorems from the literature which help to decide a priori about eventual spacetime matchings. We revise, in more detail, some toy models which include some of the main mathematical and physical issues that arise in this context, and compute the gravitational energy flux through the matching boundary of a particular collapsing region. Along the way, we point out several interesting open problems.

Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.

Importance of contact lens power and thickness in oxygen transmissibility

PURPOSE: The aim of this work was to study the central and peripheral thickness of several contact lenses (CL) with different powers and analyze how thickness variation affects CL oxygen transmissibility. METHODS: Four daily disposable and five monthly or biweekly CL were studied. The powers of each CL were: the maximum negative power of each brand; -6.00 D; -3.00 D; zero power (-0.25 D or -0.50 D), +3.00 D and +6.00 D. Central and peripheral thicknesses were measured with an electronic thickness gauge. Each lens was measured five times (central and 3mm paracentral) and the mean value was considered. Using the values of oxygen permeability given by the manufacturers and the measured thicknesses, the variation of oxygen transmissibility with lens power was determined. RESULTS: For monthly or biweekly lenses, central thickness changed between 0.061 ± 0.002 mm and 0.243 ± 0.002 mm, and peripheral thickness varied between 0.084 ± 0.002 mm and 0.231 ± 0.015 mm. Daily disposable lenses showed central values ranging between 0.056 ± 0.0016 mm and 0.205 ± 0.002 mm and peripheral values between 0.108 ± 0.05 and 0.232 ± 0.011 mm. Oxygen transmissibility (in units) of monthly or biweekly CL ranged between 39.4 ± 0.3 and 246.0 ± 14.4 and for daily disposable lenses the values range between 9.5 ± 0.5 and 178.1 ± 5.1. CONCLUSIONS: The central and peripheral thicknesses change significantly when considering the CL power and this has a significant impact on the oxygen transmissibility. Eyecare practitioners must have this fact in account when high power plus or minus lenses are fitted or when continuous wear is considered.

Exploring the role of O-Mannosylation in the modulation of E-Cadherin function in Gastric Cancer cell line models

Dissertação de mestrado em Bioquímica Aplicada – Biomedicina

Level of compliance in contact lens wearing medical doctors in Nepal

PURPOSES: To determine the level of compliance and major non-compliant behaviors in contact lens (CL) wearing medical doctors (MDs) and to compare it with age matched CL wearing normal subjects with no medical background (NS). METHODS: Thirty-nine current CL wearing MDs, who were prescribed CLs in Nepal Eye Hospital, Kathmandu, Nepal, between 2007 and 2011, were interviewed on ten modifiable compliant behaviors regarding lens care and maintenance. The level of compliance and the rate of non-compliance for each behavior were determined and compared with NS. RESULTS: Level of compliance was good, average and poor in 35.9%, 48.7% and 15.4% of MDs, respectively. There was no significant difference in compliance between MDs and NS (p=0.209). Level of compliance was not associated with age, gender and duration of lens wear (p>0.05). Compliance rate varied according to different behaviors, achieving a good compliance level of 95% for hand hygiene, avoidance of water contact and not sleeping with lenses. There was poor compliance for topping up solution (53.8%) and lens case replacement (15.4%). CONCLUSION: About one third of MDs had a good level of compliance. Level of compliance and compliance rate of different behaviors were similar in MDs and NS. Periodic lens case replacement was the most neglected behavior in CL wearers for this region.

Common symptoms of Nepalese soft contact lens wearers: A pilot study

Aim: To determine the common symptoms in current soft contact lens (CL) wearers and theirassociation with other factors among Nepalese population.Methods: All the current CL wearers who started to wear soft CL in Nepal Eye Hospital between July 2007 and June 2012 were invited for the participation. Frequency of the ten most common symptoms, divided into never, occasionally, frequently and consistent were recorded. Association between degree of symptoms with other factors, e.g. age, gender, profession, cigarette smoking, ethnicity, level of education and duration and wearing modality of CL wear were analyzed.Results: Out of 129 subjects participated in this study, 67% were female; the mean age of the subjects was 23.9 ± 4.3 years. Ninety seven percent of them had at least one symptom occasionally or frequently or consistently. Discomfort was found in 88.4% of the total subjects.Other common symptoms were foreign body sensation in 73.6%, redness in 65.9%, reduced wearing time in 63.6% and dryness in 62.8%. Symptoms were found occasionally in the majority of subjects. Degree of symptoms was not associated with age, gender, profession, education status, ethnicity of subjects and duration or modality of lens wear (p > 0.05) but was positively associated with passive cigarette smoking (p < 0.001).Conclusion: Almost all of the Nepalese soft CL wearers had some types of symptoms at least occasionally. Discomfort was the most common symptom. Degree of symptoms was associated with the passive smoking but not with other factors like age, sex, profession and duration of lens wear.

Evaluating biomaterial-and microfluidic-based 3D tumor models

Cancer is a major cause of morbidity and mortality worldwide, with a disease burden estimated to increase in the coming decades. Disease heterogeneity and limited information on cancer biology and disease mechanisms are aspects that 2D cell cultures fail to address. We review the current "state-of-the-art" in 3D Tissue Engineering (TE) models developed for and used in cancer research. Scaffold-based TE models and microfluidics, are assessed for their potential to fill the gap between 2D models and clinical application. Recent advances in combining the principles of 3D TE models and microfluidics are discussed, with a special focus on biomaterials and the most promising chip-based 3D models.

Single line for assembly just-in-sequence multiple models

Programa Doutoral em Líderes para as Indústrias Tecnológicas

Metabolic engineering with multi-objective optimization of kinetic models

Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.

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.

A novel hanging spherical drop system for the generation of cellular spheroids and high throughput combinatorial drug screening

We propose a novel hanging spherical drop system for anchoring arrays of droplets of cell suspension based on the use of biomimetic superhydrophobic flat substrates, with controlled positional adhesion and minimum contact with a solid substrate. By facing down the platform, it was possible to generate independent spheroid bodies in a high throughput manner, in order to mimic in vivo tumour models on the lab-on-chip scale. To validate this system for drug screening purposes, the toxicity of the anti-cancer drug doxorubicin in cell spheroids was tested and compared to cells in 2D culture. The advantages presented by this platform, such as feasibility of the system and the ability to control the size uniformity of the spheroid, emphasize its potential to be used as a new low cost toolbox for high-throughput drug screening and in cell or tissue engineering.

Predicting SO2 pollution incidents by means of additive models with optimum variable selection

The aim of this paper is to predict time series of SO2 concentrations emitted by coal-fired power stations in order to estimate in advance emission episodes and analyze the influence of some meteorological variables in the prediction. An emission episode is said to occur when the series of bi-hourly means of SO2 is greater than a specific level. For coal-fired power stations it is essential to predict emission epi- sodes sufficiently in advance so appropriate preventive measures can be taken. We proposed a meth- odology to predict SO2 emission episodes based on using an additive model and an algorithm for variable selection. The methodology was applied to the estimation of SO2 emissions registered in sampling lo- cations near a coal-fired power station located in Northern Spain. The results obtained indicate a good performance of the model considering only two terms of the time series and that the inclusion of the meteorological variables in the model is not significant.

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.

Effect of hormonal changes on corneal biomechanical properties and anterior segment ocular perameters

Dissertação de mestrado em Optometria Avançada

Demonstrative application examples

"Series: Solid mechanics and its applications, vol. 226"