Call Center como forma organizacional de implementação de serviços de Brokering para empresas virtuais

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Polymicrobial interactions in infections: the case Pseudomonas aeruginosa and Candida albicans in ventilator-associated pneumonia

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

Hind limb ischemia in type 1 diabetic mice as useful tool to evaluate the neovascularization of tissue engineering constructs

Hind-limb ischemia has been used in type 1 diabetic mice to evaluate treatments for peripheral arterial disease or mechanisms of vascular impairment in diabetes [1]. Vascular deficiency is not only a pathophysiological condition, but also an obvious circumstance in tissue regeneration and in tissue engineering and regenerative medicine (TERM) strategies. We performed a pilot experiment of hind-limb ischemia in streptozotocin(STZ)-induced type 1 diabetic mice to hypothesise whether diabetes influences neovascularization induced by biomaterials. The dependent variables included blood flow and markers of arteriogenesis and angiogenesis. Type 1 diabetes was induced in 8-week-old C57BL/6 mice by an i.p. injection of STZ (50 mg/kg daily for 5 days). Hind-limb ischemia was created under deep anaesthesia and the left femoral artery and vein were isolated, ligated, and excised. The contralateral hind limb served as an internal control within each mouse. Non-diabetic ischaemic mice were used as experiment controls. At the hind-limb ischemia surgical procedure, different types of biomaterials were placed in the blood vessels gap. Blood flow was estimated by Laser Doppler perfusion imager, right after surgery and then weekly. After 28 days of implantation, surrounding muscle was excised and evaluated by histological analysis for arteriogenesis and angiogenesis. The results showed that implanted biomaterials were promote faster restoration of blood flow in the ischemic limbs and improved neovascularization in the diabetic mice. Therefore, we herein demonstrate that the combined model of hind-limb ischemia in type 1 diabetes mice is suitable to evaluate the neovascularization potential of biomaterials and eventually tissue engineering constructs.  

End-systolic pressure-diameter relation of the left ventricle during transient and sustained elevations of blood pressure

OBJECTIVE: To assess the effect of transient and sustained variations in cardiac load on the values of the end-systolic pressure-diameter relation (ESPDR) of the left ventricle. METHODS: We studied 13 dogs under general anesthesia and autonomic blockade. Variations of cardiac loads were done by elevation of blood pressure by mechanical constriction of the aorta. Two protocols were used in each animal: gradual peaking and decreasing pressure variation, the "transient arterial hypertension protocol" (TAH), and a quick and 10 min sustained elevation, the "sustained arterial hypertension protocol"(SAH). Then, we compared the ESDR in these two situations. RESULTS: Acute elevation of arterial pressure, being it "transitory" or "sustained", did not alter the heart frequency and increased similarly the preload and after load. However, they acted differently in end systolic pressure-diameter relation. It was greater in the SAH than TAH protocol, 21.0±7.3mmHg/mm vs. 9.2±1.2mmHg/mm (p<0.05). CONCLUSION: The left ventricular ESPDR values determined during sustained pressure elevations were higher than those found during transient pressure elevations. The time-dependent activation of myocardial contractility associated with the Frank-Starling mechanism is the major factor in inotropic stimulation during sustained elevations of blood pressure, determining an increase in the ESPDR values.

Candida tropicalis biofilms: biomass, metabolic activity and secreted aspartyl proteinase production

According to epidemiological data, Candida tropicalis has been related to urinary tract infections and haematological malignancy. Several virulence factors seem to be responsible for C. tropicalis infections, for example: their ability to adhere and to form biofilms onto different indwelling medical devices; their capacity to adhere, invade and damage host human tissues due to enzymes production such as proteinases. The main aim of this work was to study the behaviour of C. tropicalis biofilms of different ages (24120 h) formed in artificial urine (AU) and their ability to express aspartyl proteinase (SAPT) genes. The reference strain C. tropicalis ATCC 750 and two C. tropicalis isolates from urine were used. Biofilms were evaluated in terms of culturable cells by colony-forming units enumeration; total biofilm biomass was evaluated using the crystal violet staining method; metabolic activity was evaluated by XTT assay; and SAPT gene expression was determined by real-time PCR. All strains of C. tropicalis were able to form biofilms in AU, although with differences between strains. Candida tropicalis biofilms showed a decrease in terms of the number of culturable cells from 48 to 72 h. Generally, SAPT3 was highly expressed. C. tropicalis strains assayed were able to form biofilms in the presence of AU although in a strain- and time-dependent way, and SAPT genes are expressed during C. tropicalis biofilm formation.

Development of a water-in-oil-in-water multiple emulsion system integrating biomimetic aqueous-core lipid nanodroplets for protein entity stabilization. Part I: experimental factorial design

Lipid nanoballoons integrating multiple emulsions of the type water-in-oil-in-water enclose, at least in theory, a biomimetic aqueous-core suitable for housing hydrophilic biomolecules such as proteins, peptides and bacteriophage particles. The research effort entertained in this paper reports a full statistical 23x31 factorial design study (three variables at two levels and one variable at three levels) to optimize biomimetic aqueous-core lipid nanoballoons for housing hydrophilic protein entities. The concentrations of protein, lipophilic and hydrophilic emulsifiers, and homogenization speed were set as the four independent variables, whereas the mean particle hydrodynamic size (HS), zeta potential (ZP) and polydispersity index (PI) were set as the dependent variables. The V23x31 factorial design constructed led to optimization of the higher (+1) and lower (-1) levels, with triplicate testing for the central (0) level, thus producing thirty three experiments and leading to selection of the optimized processing parameters as 0.015% (w/w) protein entity, 0.75% (w/w) lipophilic emulsifier (soybean lecithin) and 0.50% (w/w) hydrophilic emulsifier (poloxamer 188). In the present research effort, statistical optimization and production of protein derivatives encompassing full stabilization of their three-dimensional structure, has been attempted via housing said molecular entities within biomimetic aqueous-core lipid nanoballoons integrating a multiple (W/O/W) emulsion.

Subclinical Ventricular Dysfunction Detected by Speckle Tracking Two Years after Use of Anthracycline

Background: Heart failure is a severe complication associated with doxorubicin (DOX) use. Strain, assessed by two-dimensional speckle tracking (2D-STE), has been shown to be useful in identifying subclinical ventricular dysfunction. Objectives: a) To investigate the role of strain in the identification of subclinical ventricular dysfunction in patients who used DOX; b) to investigate determinants of strain response in these patients. Methods: Cross-sectional study with 81 participants: 40 patients who used DOX ±2 years before the study and 41 controls. All participants had left ventricular ejection fraction (LVEF) ≥55%. Total dose of DOX was 396mg (242mg/ms2). The systolic function of the LV was evaluated by LVEF (Simpson), as well as by longitudinal (εLL), circumferential (εCC), and radial (εRR) strains. Multivariate linear regression (MLR) analysis was performed using εLL (model 1) and εCC (model 2) as dependent variables. Results: Systolic and diastolic blood pressure values were higher in the control group (p < 0.05). εLL was lower in the DOX group (-12.4 ±2.6%) versus controls (-13.4 ± 1.7%; p = 0.044). The same occurred with εCC: -12.1 ± 2.7% (DOX) versus -16.7 ± 3.6% (controls; p < 0.001). The S’ wave was shorter in the DOX group (p = 0.035). On MLR, DOX was an independent predictor of reduced εCC (B = -4.429, p < 0.001). DOX (B = -1.289, p = 0.012) and age (B = -0.057, p = 0.029) were independent markers of reduced εLL. Conclusion: a) εLL, εCC and the S’ wave are reduced in patients who used DOX ±2 years prior to the study despite normal LVEF, suggesting the presence of subclinical ventricular dysfunction; b) DOX was an independent predictor of reduced εCC; c) prior use of DOX and age were independent markers of reduced εLL.

Long-term citalopram administration reduces responsiveness of HPA axis in patients with major depression: relationship with S-citalopram concentrations in plasma and cerebrospinal fluid (CSF) and clinical response.

RATIONALE: A dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is a well-documented neurobiological finding in major depression. Moreover, clinically effective therapy with antidepressant drugs may normalize the HPA axis activity. OBJECTIVE: The aim of this study was to test whether citalopram (R/S-CIT) affects the function of the HPA axis in patients with major depression (DSM IV). METHODS: Twenty depressed patients (11 women and 9 men) were challenged with a combined dexamethasone (DEX) suppression and corticotropin-releasing hormone (CRH) stimulation test (DEX/CRH test) following a placebo week and after 2, 4, and 16 weeks of 40 mg/day R/S-CIT treatment. RESULTS: The results show a time-dependent reduction of adrenocorticotrophic hormone (ACTH) and cortisol response during the DEX/CRH test both in treatment responders and nonresponders within 16 weeks. There was a significant relationship between post-DEX baseline cortisol levels (measured before administration of CRH) and severity of depression at pretreatment baseline. Multiple linear regression analyses were performed to identify the impact of psychopathology and hormonal stress responsiveness and R/S-CIT concentrations in plasma and cerebrospinal fluid (CSF). The magnitude of decrease in cortisol responsivity from pretreatment baseline to week 4 on drug [delta-area under the curve (AUC) cortisol] was a significant predictor (p<0.0001) of the degree of symptom improvement following 16 weeks on drug (i.e., decrease in HAM-D21 total score). The model demonstrated that the interaction of CSF S-CIT concentrations and clinical improvement was the most powerful predictor of AUC cortisol responsiveness. CONCLUSION: The present study shows that decreased AUC cortisol was highly associated with S-CIT concentrations in plasma and CSF. Therefore, our data suggest that the CSF or plasma S-CIT concentrations rather than the R/S-CIT dose should be considered as an indicator of the selective serotonergic reuptake inhibitors (SSRIs) effect on HPA axis responsiveness as measured by AUC cortisol response.

Effort, reward and self-reported mental health: a simulation study on negative affectivity bias.

Background : In the present article, we propose an alternative method for dealing with negative affectivity (NA) biases in research, while investigating the association between a deleterious psychosocial environment at work and poor mental health. First, we investigated how strong NA must be to cause an observed correlation between the independent and dependent variables. Second, we subjectively assessed whether NA can have a large enough impact on a large enough number of subjects to invalidate the observed correlations between dependent and independent variables.Methods : We simulated 10,000 populations of 300 subjects each, using the marginal distribution of workers in an actual population that had answered the Siegrist's questionnaire on effort and reward imbalance (ERI) and the General Health Questionnaire (GHQ).Results : The results of the present study suggested that simulated NA has a minimal effect on the mean scores for effort and reward. However, the correlations between the effort and reward imbalance (ERI) ratio and the GHQ score might be important, even in simulated populations with a limited NA.Conclusions : When investigating the relationship between the ERI ratio and the GHQ score, we suggest the following rules for the interpretation of the results: correlations with an explained variance of 5% and below should be considered with caution; correlations with an explained variance between 5% and 10% may result from NA, although this effect does not seem likely; and correlations with an explained variance of 10% and above are not likely to be the result of NA biases. [Authors]

Three essays on bankruptcy risk

Abstract Market prices of corporate bond spreads and of credit default swap (CDS) rates do not match each other. In this paper, we argue that the liquidity premium, the cheapest-to-deliver (CTD) option and actual market segmentation explain the pricing differences. Using the European transaction data from Reuters and Bloomberg, we estimate the liquidity premium that is time- varying and firm-specific. We show that when time-dependent liquidity premiums are considered, corporate bond spreads and CDS rates behave in a much closer way than previous studies have shown. We find that high equity volatility drives pricing differences that can be explained by the CTD option.

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?

Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting models as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output growth and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

Where is the economics in spatial econometrics?

Spatial econometrics has been criticized by some economists because some model specifications have been driven by data-analytic considerations rather than having a firm foundation in economic theory. In particular this applies to the so-called W matrix, which is integral to the structure of endogenous and exogenous spatial lags, and to spatial error processes, and which are almost the sine qua non of spatial econometrics. Moreover it has been suggested that the significance of a spatially lagged dependent variable involving W may be misleading, since it may be simply picking up the effects of omitted spatially dependent variables, incorrectly suggesting the existence of a spillover mechanism. In this paper we review the theoretical and empirical rationale for network dependence and spatial externalities as embodied in spatially lagged variables, arguing that failing to acknowledge their presence at least leads to biased inference, can be a cause of inconsistent estimation, and leads to an incorrect understanding of true causal processes.

Forecasting with Medium and Large Bayesian VARs

This paper is motivated by the recent interest in the use of Bayesian VARs for forecasting, even in cases where the number of dependent variables is large. In such cases, factor methods have been traditionally used but recent work using a particular prior suggests that Bayesian VAR methods can forecast better. In this paper, we consider a range of alternative priors which have been used with small VARs, discuss the issues which arise when they are used with medium and large VARs and examine their forecast performance using a US macroeconomic data set containing 168 variables. We nd that Bayesian VARs do tend to forecast better than factor methods and provide an extensive comparison of the strengths and weaknesses of various approaches. Our empirical results show the importance of using forecast metrics which use the entire predictive density, instead of using only point forecasts.

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?

Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting model as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

Optimal exponent heat balance and refined integral methods applied to Stefan problems

When using a polynomial approximating function the most contentious aspect of the Heat Balance Integral Method is the choice of power of the highest order term. In this paper we employ a method recently developed for thermal problems, where the exponent is determined during the solution process, to analyse Stefan problems. This is achieved by minimising an error function. The solution requires no knowledge of an exact solution and generally produces significantly better results than all previous HBI models. The method is illustrated by first applying it to standard thermal problems. A Stefan problem with an analytical solution is then discussed and results compared to the approximate solution. An ablation problem is also analysed and results compared against a numerical solution. In both examples the agreement is excellent. A Stefan problem where the boundary temperature increases exponentially is analysed. This highlights the difficulties that can be encountered with a time dependent boundary condition. Finally, melting with a time-dependent flux is briefly analysed without applying analytical or numerical results to assess the accuracy.