996 resultados para CLASSICAL-THEORY


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We generalize Wertheim's first order perturbation theory to account for the effect in the thermodynamics of the self-assembly of rings characterized by two energy scales. The theory is applied to a lattice model of patchy particles and tested against Monte Carlo simulations on a fcc lattice. These particles have 2 patches of type A and 10 patches of type B, which may form bonds AA or AB that decrease the energy by epsilon(AA) and by epsilon(AB) = r epsilon(AA), respectively. The angle theta between the 2 A-patches on each particle is fixed at 601, 90 degrees or 120 degrees. For values of r below 1/2 and above a threshold r(th)(theta) the models exhibit a phase diagram with two critical points. Both theory and simulation predict that rth increases when theta decreases. We show that the mechanism that prevents phase separation for models with decreasing values of theta is related to the formation of loops containing AB bonds. Moreover, we show that by including the free energy of B-rings ( loops containing one AB bond), the theory describes the trends observed in the simulation results, but that for the lowest values of theta, the theoretical description deteriorates due to the increasing number of loops containing more than one AB bond.

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Com o objetivo de conhecer a importância dos animais domésticos como reservatórios naturais dos clássicos campylobacters termotolerantes, amostras de fezes foram obtidas de mamíferos e aves do leste do Peru e imediatamente colocadas num meio de enriquecimento. Técnicas convencionais foram utilizadas para identificar C. jejuni ssp. jejuni, C. coli e C. lari. Campylobacter foi isolado em 26,5% dos animais estudados, sendo C. jejuni ssp. jejuni biovar I o mais freqüente (8,9%). O frango foi o reservatório mais importante destes microorganismos (54,0%).

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Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

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Dissertação apresentada para obtenção do Grau de Doutor em Ambiente pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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Dissertation submitted in partial fulfillment of the requirements for degree of Master in Statistics and Information Management.

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The internal impedance of a wire is the function of the frequency. In a conductor, where the conductivity is sufficiently high, the displacement current density can be neglected. In this case, the conduction current density is given by the product of the electric field and the conductance. One of the aspects the high-frequency effects is the skin effect (SE). The fundamental problem with SE is it attenuates the higher frequency components of a signal. The SE was first verified by Kelvin in 1887. Since then many researchers developed work on the subject and presently a comprehensive physical model, based on the Maxwell equations, is well established. The Maxwell formalism plays a fundamental role in the electromagnetic theory. These equations lead to the derivation of mathematical descriptions useful in many applications in physics and engineering. Maxwell is generally regarded as the 19th century scientist who had the greatest influence on 20th century physics, making contributions to the fundamental models of nature. The Maxwell equations involve only the integer-order calculus and, therefore, it is natural that the resulting classical models adopted in electrical engineering reflect this perspective. Recently, a closer look of some phenomas present in electrical systems and the motivation towards the development of precise models, seem to point out the requirement for a fractional calculus approach. Bearing these ideas in mind, in this study we address the SE and we re-evaluate the results demonstrating its fractional-order nature.

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Etnográfica, 15 (2): 313-336

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Smart Grids (SGs) have emerged as the new paradigm for power system operation and management, being designed to include large amounts of distributed energy resources. This new paradigm requires new Energy Resource Management (ERM) methodologies considering different operation strategies and the existence of new management players such as several types of aggregators. This paper proposes a methodology to facilitate the coalition between distributed generation units originating Virtual Power Players (VPP) considering a game theory approach. The proposed approach consists in the analysis of the classifications that were attributed by each VPP to the distributed generation units, as well as in the analysis of the previous established contracts by each player. The proposed classification model is based in fourteen parameters including technical, economical and behavioural ones. Depending of the VPP strategies, size and goals, each parameter has different importance. VPP can also manage other type of energy resources, like storage units, electric vehicles, demand response programs or even parts of the MV and LV distribution network. A case study with twelve VPPs with different characteristics and one hundred and fifty real distributed generation units is included in the paper.

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This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

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There is no complete overview or discussion of the literature of the economics of federalism and fiscal decentralization, even though scholarly interest in the topic has been increasing significantly over recent years. This paper provides a general, brief but comprehensive overview of the main insights from the literature on fiscal federalism and decentralization. In doing so, literature on fiscal federalism and decentralization is grouped into two main approaches: “first generation of theories” and “second generation of theories”.

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RESUMO:Introdução: Reviu-se o conhecimento epidemiológico, fisiopatológico e clínico atual sobre a doença coronária, da sua génese até ao evento agudo, o Enfarte Agudo do Miocárdio (EAM). Valorizou-se, em especial, a teoria inflamatória da aterosclerose, que foi objeto de grandes desenvolvimentos na última década. Marcadores de instabilidade da placa aterosclerótica coronária: Aprofundou-se o conhecimento da placa aterosclerótica coronária instável. Descreveram-se detalhadamente os biomarcadores clínicos e laboratoriais associados à instabilidade da placa, com particular ênfase nos mecanismos inflamatórios. Objetivos:Estão divididos em dois pontos fundamentais:(1) Estudar em doentes com EAM a relação existente entre as moléculas inflamatórias: Interleucina-6 (IL-6), Fator de Necrose Tumoral-α (TNF-α) e Metaloproteinase de Matriz-3 (MMP3), não usados em contexto clínico, com um marcador inflamatório já em uso clínico: a Proteína C-Reativa ultrassensível (hs-CRP). Avaliar a relação de todas as moléculas inflamatórias com um biomarcador de lesão miocárdica: a Troponina Cardíaca I (cTnI). (2) Avaliar, no mesmo contexto de EAM, a Resposta de Fase Aguda (RFA) . Pretende-se demonstrar o impacto deste fenómeno, com repercussão clínica generalizada, no perfil lipídico e nos biomarcadores inflamatórios dos doentes. Métodos:(1) Estudo observacional prospetivo de doentes admitidos consecutivamente por EAM (grupo EAM) numa única unidade coronária, após exclusão de trauma ou infeção. Doseamento no sangue periférico, na admissão, de IL-6, TNF-α, MMP3, hs-CRP e cTnI. Este último biomarcador foi valorizado também nos valores séricos obtidos 6-9 horas depois. Procedeu-se a correlação linear (coeficiente de Pearson, de Rho-Spearman e determinação do R2) entre os 3 marcadores estudados com os valores de hs-CRP e de cTnI (valores da admissão e 6 a 9 horas após). Efetuou-se o cálculo dos coeficientes de regressão linear múltipla entre cTnI da admissão e cTnI 6-9h após, com o conjunto dos fatores inflamatórios estudados. (2) Estudo caso-controlo entre o grupo EAM e uma população aleatória de doentes seguidos em consulta de cardiologia, após exclusão de eventos cardiovasculares de qualquer território (grupo controlo) e também sem infeção ou trauma. Foram doseados os mesmos marcadores inflamatórios no grupo controlo e no grupo EAM. Nos dois grupos dosearam-se, ainda, as lipoproteínas: Colesterol total (CT), Colesterol HDL (HDLc), com as suas subfrações 2 e 3 (HDL 2 e HDL3), Colesterol LDL oxidado (LDLox),Triglicéridos (TG), Lipoproteína (a) [Lp(a)], Apolipoproteína A1 (ApoA1), Apolipoproteína B (ApoB) e Apolipoproteína E (ApoE). Definiram-se, em cada grupo, os dados demográficos, fatores de risco clássicos, terapêutica cardiovascular e o uso de anti-inflamatórios. Procedeu-se a análise multivariada em relação aos dados demográficos, fatores de risco e à terapêutica basal. Compararam-se as distribuições destas mesmas caraterísticas entre os dois grupos, assim como os valores séricos respetivos para as lipoproteínas estudadas. Procedeu-se à correlação entre as moléculas inflamatórias e as lipoproteínas, para todos os doentes estudados. Encontraram-se os coeficientes de regressão linear múltipla entre cada marcador inflamatório e o conjunto das moléculas lipídicas, por grupo. Finalmente, efetuou-se a comparação estatística entre os marcadores inflamatórios do grupo controlo e os marcadores inflamatórios do grupo EAM. Resultados: (1) Correlações encontradas, respetivamente, Pearson, Rho-Spearman e regressão-R2: IL-6/hs-CRP 0,549, p<0,001; 0,429, p=0,001; 0,302, p<0,001; MMP 3/hsCRP 0,325, p=0,014; 0,171, p=0,202; 0,106, p=0,014; TNF-α/hs-CRP 0,261, p=0,050; 0,315, p=0,017; 0,068, p=0.050; IL-6/cTnI admissão 0,486, p<0,001; 0,483, p<0,001; 0,236, p<0,001; MMP3/cTnI admissão 0,218, p=0,103; 0,146, p=0,278; 0,048, p=0,103; TNF-α/cTnI admissão 0,444, p=0,001; 0,380, p=0,004; 0,197, p=0,001; IL-6/cTnI 6-9h 0,676, p<0,001; 0,623, p<0,001; 0,456, p<0,01; MMP3/cTnI 6-9h 0,524, p=0,001; 0,149, p=0,270; 0,275, p<0,001; TNF-α/cTnI 6-9h 0,428, p=0,001, 0,452, p<0,001, 0,183, p<0,001. A regressão linear múltipla cTnI admissão/marcadores inflamatórios produziu: (R=0,638, R2=0,407) p<0,001 e cTnI 6-9h/marcadores inflamatórios (R=0,780, R2=0,609) p<0,001. (2) Significância da análise multivariada para idade (p=0,029), IMC>30 (p=0.070), AAS (p=0,040) e grupo (p=0,002). Diferenças importantes entre as distribuições dos dados basais entre os dois grupos (grupo controlo vs EAM): idade (47,95±11,55 vs 68,53±2,70 anos) p<0.001; sexo feminino (18,18 vs 22,80%) p=0,076; diabetes mellitus (9,09% vs 36,84%) p=0,012; AAS (18,18 vs 66,66%) p<0,001; clopidogrel (4,54% vs 66,66%) p=0,033; estatinas (31,81% vs 66,14%) p=0,078; beta-bloqueadores (18,18% vs 56,14%) p=0,011; anti-inflamatórios (4,54% vs 33,33%) p=0,009. Resultados da comparação entre os dois grupos quanto ao padrão lipídico (média±dp ou mediana/intervalo interquartil, grupo controlo vs EAM): CT (208,45±35,03 vs 171,05±41,63 mg/dl) p<0,001; HDLc (51,50/18,25 vs 42,00/16,00 mg/dl) p=0,007; HDL2 (8,50/3,25 vs 10,00/6,00 mg/dl) p=0,292; HDL3 (41,75±9,82 vs 31,75±9,41 mg/dl) p<0,001; LDLox (70,00/22,0 vs 43,50/21,00 U/L) p<0,001; TG (120,00/112,50 vs 107,00/86,00 mg/dl) p=0,527; Lp(a) (0,51/0,73 vs 0,51/0,50 g/L) p=0,854; ApoA1 (1,38±0,63 vs 1,19±0,21 g/L) p=0,002; ApoB (0,96±0,19 vs 0,78±0,28 g/L) p=0,004; ApoE (38,50/10,00 vs 38,00/17,00 mg/L) p=0,574. Nas correlações lineares entre as variáveis inflamatórias e as variáveis lipídicas para todos os doentes, encontrámos uma relação negativa entre IL-6 e CT, HDLc, HDL3, LDLox, ApoA1 e ApoB. A regressão múltipla marcadores inflamatórios/perfil lipídico (grupo controlo) foi: hs-CRP (R=0,883, R2=0,780) p=0,022; IL-6 (R=0,911, R2=0,830) p=0,007; MMP3 (R=0,498, R2=0,248) p=0,943; TNF-α (R=0,680, R2=0,462) p=0,524. A regressão múltipla marcadores inflamatórios/perfil lipídico (grupo EAM) foi: hs-CRP (R=0,647, R2=0,418) p=0,004; IL-6 (R=0,544, R2=0,300), p=0,073; MMP3 (R=0,539, R2=0,290) p=0,089; TNF-α (R=0,595; R2=0,354) p=0,022. Da comparação entre os marcadores inflamatórios dos dois grupos resultou (mediana/intervalo interquartil, grupo controlo vs EAM): hs-CRP (0,19/0,27 vs 0,42/2,53 mg/dl) p=0,001, IL-6 (4,90/5,48 vs 13,07/26,41 pg/ml) p<0,001, MMP3 (19,70/13,70 vs 10,10/10,40 ng/ml) p<0,001;TNF-α (8,67/6,71 vs 8,26/7,80 pg/dl) p=0,805. Conclusões: (1) Nos doentes com EAM, existe correlação entre as moléculas inflamatórias IL-6, MMP3 e TNF-α, quer com o marcador inflamatório hs-CRP, quer com o marcador de lesão miocárdica cTnI. Esta correlação reforça-se para os valores de cTnI 6-9 horas após admissão, especialmente na correlação múltipla com o grupo dos quatro marcadores inflamatórios. (2) IL-6 está inversamente ligada às lipoproteínas de colesterol; hs-CRP e IL-6 têm excelentes correlações com o perfil lipídico valorizado no seu conjunto. No grupo EAM encontram-se níveis séricos mais reduzidos para as lipoproteínas de colesterol. Para TNF-α não foram encontradas diferenças significativas entre os grupos, as quais foram observadas para a IL-6 e hs-CRP (mais elevadas no grupo EAM). Os valores de MMP3 no grupo controlo estão mais elevados. ABSTRACT: 0,524, p=0,001; 0,149, p=0,270; 0,275, p<0,001; TNF-α/cTnI 6-9h 0,428, p=0,001, 0,452, p<0,001, 0,183, p<0,001. A regressão linear múltipla cTnI admissão/marcadores inflamatórios produziu: (R=0,638, R2=0,407) p<0,001 e cTnI 6-9h/marcadores inflamatórios (R=0,780, R2=0,609) p<0,001. (2) Significância da análise multivariada para idade (p=0,029), IMC>30 (p=0.070), AAS (p=0,040) e grupo (p=0,002). Diferenças importantes entre as distribuições dos dados basais entre os dois grupos (grupo controlo vs EAM): idade (47,95±11,55 vs 68,53±2,70 anos) p<0.001; sexo feminino (18,18 vs 22,80%) p=0,076; diabetes mellitus (9,09% vs 36,84%) p=0,012; AAS (18,18 vs 66,66%) p<0,001; clopidogrel (4,54% vs 66,66%) p=0,033; estatinas (31,81% vs 66,14%) p=0,078; beta-bloqueadores (18,18% vs 56,14%) p=0,011; anti-inflamatórios (4,54% vs 33,33%) p=0,009. Resultados da comparação entre os dois grupos quanto ao padrão lipídico (média±dp ou mediana/intervalo interquartil, grupo controlo vs EAM): CT (208,45±35,03 vs 171,05±41,63 mg/dl) p<0,001; HDLc (51,50/18,25 vs 42,00/16,00 mg/dl) p=0,007; HDL2 (8,50/3,25 vs 10,00/6,00 mg/dl) p=0,292; HDL3 (41,75±9,82 vs 31,75±9,41 mg/dl) p<0,001; LDLox (70,00/22,0 vs 43,50/21,00 U/L) p<0,001; TG (120,00/112,50 vs 107,00/86,00 mg/dl) p=0,527; Lp(a) (0,51/0,73 vs 0,51/0,50 g/L) p=0,854; ApoA1 (1,38±0,63 vs 1,19±0,21 g/L) p=0,002; ApoB (0,96±0,19 vs 0,78±0,28 g/L) p=0,004; ApoE (38,50/10,00 vs 38,00/17,00 mg/L) p=0,574. Nas correlações lineares entre as variáveis inflamatórias e as variáveis lipídicas para todos os doentes, encontrámos uma relação negativa entre IL-6 e CT, HDLc, HDL3, LDLox, ApoA1 e ApoB. A regressão múltipla marcadores inflamatórios/perfil lipídico (grupo controlo) foi: hs-CRP (R=0,883, R2=0,780) p=0,022; IL-6 (R=0,911, R2=0,830) p=0,007; MMP3 (R=0,498, R2=0,248) p=0,943; TNF-α (R=0,680, R2=0,462) p=0,524. A regressão múltipla marcadores inflamatórios/perfil lipídico (grupo EAM) foi: hs-CRP (R=0,647, R2=0,418) p=0,004; IL-6 (R=0,544, R2=0,300), p=0,073; MMP3 (R=0,539, R2=0,290) p=0,089; TNF-α (R=0,595; R2=0,354) p=0,022. Da comparação entre os marcadores inflamatórios dos dois grupos resultou (mediana/intervalo interquartil, grupo controlo vs EAM): hs-CRP (0,19/0,27 vs 0,42/2,53 mg/dl) p=0,001, IL-6 (4,90/5,48 vs 13,07/26,41 pg/ml) p<0,001, MMP3 (19,70/13,70 vs 10,10/10,40 ng/ml) p<0,001;TNF-α (8,67/6,71 vs 8,26/7,80 pg/dl) p=0,805. Conclusões: (1) Nos doentes com EAM, existe correlação entre as moléculas inflamatórias IL-6, MMP3 e TNF-α, quer com o marcador inflamatório hs-CRP, quer com o marcador de lesão miocárdica cTnI. Esta correlação reforça-se para os valores de cTnI 6-9 horas após admissão, especialmente na correlação múltipla com o grupo dos quatro marcadores inflamatórios. (2) IL-6 está inversamente ligada às lipoproteínas de colesterol; hs-CRP e IL-6 têm excelentes correlações com o perfil lipídico valorizado no seu conjunto. No grupo EAM encontram-se níveis séricos mais reduzidos para as lipoproteínas de colesterol. Para TNF-α não foram encontradas diferenças significativas entre os grupos, as quais foram observadas para a IL-6 e hs-CRP (mais elevadas no grupo EAM). Os valores de MMP3 no grupo controlo estão mais elevados. ------------- ABSTRACT: Introduction: We reviewed the epidemiology, pathophysiology and current clinical knowledge about coronary heart disease, from its genesis to the acute myocardial infarction (AMI). The inflammatory theory for atherosclerosis, which has undergone considerable development in the last decade, was especially detailed. Markers of coronary atherosclerotic vulnerable plaque: The clinical and laboratory biomarkers associated with the unstable coronary atherosclerotic plaque vulnerable plaque are detailed. An emphasis was placed on the inflammatory mechanisms. Objectives: They are divided into two fundamental points: (1) To study in AMI patients, the relationship between the inflammatory molecules: Interleukin-6 (IL-6), Tumor Necrosis Factor-α (TNF-α) and Matrix metalloproteinase-3 (MMP3), unused in the clinical setting, with an inflammatory marker in clinical use: ultrasensitive C-reactive protein (hs-CRP), as well as a biomarker of myocardial injury: cardiac troponin I (cTnI). (2) To study, in the context of AMI, the Acute Phase Response (APR). We intend to demonstrate the impact of that clinical relevant phenomenon in the lipid profile and inflammatory biomarkers of our patients. Methods: (1) Prospective observational study of patients consecutively admitted for AMI (AMI group) in a single coronary care unit, after exclusion of trauma or infection. A peripheral assay at admission for IL-6, TNF-α, MMP3, hs-CRP and cTnI was performed. The latter was also valued in assays obtained 6-9 hours after admission. Linear correlation (Pearson's correlation coefficient, Spearman Rho's correlation coefficient and R2 regression) was performed between the three markers studied and the values of hs-CRP and cTnI (on admission and 6-9 hours after admission). Multiple linear regression was also obtained between cTnI on admission and 6-9h after, with all the inflammatory markers studied. (2) Case-control study between the AMI group and a random population of patients from an outpatient cardiology setting (control group). Cardiovascular events of any kind and infection or trauma were excluded in this group. The same inflammatory molecules were assayed in control and AMI groups. The following lipoproteins were also assayed: total cholesterol (TC), HDL cholesterol (HDLc) and subfractions 2 and 3 (HDL2 and HDL 3), oxidized LDL cholesterol (oxLDL), Triglycerides (TG), Lipoprotein (a) [Lp(a)], Apolipoprotein A1 (apoA1), Apolipoprotein B (ApoB) and Apolipoprotein E (ApoE). Demographics, classical risk factors, cardiovascular therapy and the use of anti-inflammatory drugs were appreciated in each group. The authors conducted a multivariate analysis with respect to demographics, risk factors and baseline therapy. The distribution of the same baseline characteristics was compared between the two groups, as well as the lipoprotein serum values. A correlation was performed between each inflammatory molecule and each of the lipoproteins, for all the patients studied. Multiple linear regression was determined between each inflammatory marker and all the lipid molecules per group. Finally, the statistical comparison between the inflammatory markers in the two groups was performed. Results: (1) The correlation coefficients recorded, respectively, Pearson, Spearman's Rho and regression-R2, were: IL-6/hs-CRP 0.549, p <0.001; 0.429, p=0.001; 0.302, p <0.001; MMP 3/hsCRP 0.325, p=0.014; 0.171, p=0.202; 0.106, p=0.014; TNF-α/hs-CRP 0.261, p=0.050; 0.315, p=0.017; 0.068, p=0.050; IL-6/admission cTnI 0.486, p<0.001; 0.483, p<0.001; 0.236, p<0.001; MMP3/admission cTnI 0.218, p=0.103; 0.146, p=0.278; 0.048, p=0.103; TNF-α/admission cTnI 0.444, p=0.001; 0.380, p=0.004; 0.197, p=0.001; IL-6/6-9 h cTnI 0.676, p<0.001; 0.149, p<0.001; 0.456, p <0.01; MMP3/6-9h cTnI 0.428, p=0.001; 0.149, p<0.001; 0.183, p=0.001; TNF-α/6-9 h cTnI 0.676, p<0,001; 0.452, p<0.001; 0.183, p<0,001. The multiple linear regression admission cTnI/inflammatory markers produced: (R=0.638, R2=0.407) p<0.001 and 6-9 h cTnI/inflammatory markers (R=0.780, R2=0.609) p<0.001. (2) Significances of the multivariate analysis were found for age (p=0.029), IMC>30 (p=0.070), Aspirin (p=0.040) and group (p=0.002). Important differences between the baseline data of the two groups (control group vs AMI): age (47.95 ± 11.55 vs 68.53±12.70 years) p<0.001; gender (18.18 vs 22.80%) p=0.076; diabetes mellitus (9.09% vs 36. 84%) p=0.012; Aspirin (18.18 vs. 66.66%) p<0.001; Clopidogrel (4, 54% vs 66.66%) p=0.033; Statins, 31.81% vs 66.14%, p=0.078, beta-blockers 18.18% vs 56.14%, p=0.011; anti-inflammatory drugs (4.54% vs 33.33%) p=0.009. Significant differences in the lipid pattern of the two groups (mean±SD or median/interquartile range, control group vs AMI): TC (208.45±35.03 vs 171.05±41.63 mg/dl) p<0.001; HDLc (51.50/18.25 vs 42.00/16.00 mg/dl) p=0.007; HDL2 (8.50/3.25 vs 10.00/6.00 mg/dl) p=0.292; HDL3 (41.75±9.82 vs 31.75±9.82 mg/dl) p<0.01; oxLDL (70.00/22.0 vs 43.50/21.00 U/L) p <0.001; TG (120.00/112.50 vs 107.00/86.00 mg/dl) p=0.527; Lp(a) (0.51/0.73 vs 0,51/0.50 g/L) p=0.854; apoA1 (1.38±0.63 vs 1.19±0.21 g/L) p=0.002; ApoB (0.96± 0.39 vs 0.78±0.28 g/L) p=0.004; ApoE (38.50/10,00 vs 38.00 /17,00 mg/L) p=0.574. In the linear correlations between inflammatory variables and lipid variables for all patients, we found a negative relationship between IL-6 and TC, HDLc, HDL3, ApoA1 and ApoB. The multiple linear regression inflammatory markers/lipid profile (control group) was: hs-CRP (R= 0.883, R2=0.780) p=0.022; IL6 (R=0.911, R2=0.830) p=0.007; MMP3 (R=0.498, R2=0.248) p=0.943; TNF-α (R=0.680, R2=0.462) p=0.524. For the linear regression inflammatory markers/lipid profile (AMI group) we found: hs-CRP (R=0.647, R2=0.418) p=0.004; IL-6 (R=0.544, R2=0.300) p=0.073; MMP3 (R=0.539, R2 =0.290) p=0.089; TNF-α (R=0.595, R2=0.354) p=0.022. The comparison between inflammatory markers in both groups (median/interquartile range, control group vs AMI) resulted as: hs-CRP (0.19/0.27 vs 0.42/2.53 mg/dl) p=0.001; IL-6 (4.90/5.48 vs 13.07/26.41 pg/ml) p<0.001; MMP3 (19.70/13.70 vs 10.10/10.40 ng/ml) p<0.001; TNF-α (8.67/6.71 vs 8.26/7.80 pg/dl) p=0.805. Conclusions: (1) In AMI patients there is a correlation between the inflammatory molecules IL-6, TNF-α and MMP3 with both the inflammatory marker hs-CRP and the ischemic marker cTnI. This correlation is strengthened for the cTnI at 6-9h post admission, particularly in the multiple linear regression to the four inflammatory markers studied. (2) IL-6 correlates negatively with the cholesterol lipoproteins. Hs-CRP and IL-6 are strongly correlated to the whole lipoprotein profile. AMI patients display reduced serum lipid levels. For the marker TNF-α no significant differences were found between groups, which were observed for IL-6 and hs-CRP (higher in the AMI group). MMP3 values are higher in the control group.

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Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia