Modeling pulmonary fibrosis by abnormal expression of telomerase/apoptosis/collagen V in experimental usual interstitial pneumonia

Limitations on tissue proliferation capacity determined by telomerase/apoptosis balance have been implicated in pathogenesis of idiopathic pulmonary fibrosis. In addition, collagen V shows promise as an inductor of apoptosis. We evaluated the quantitative relationship between the telomerase/apoptosis index, collagen V synthesis, and epithelial/fibroblast replication in mice exposed to butylated hydroxytoluene (BHT) at high oxygen concentration. Two groups of mice were analyzed: 20 mice received BHT, and 10 control mice received corn oil. Telomerase expression, apoptosis, collagen I, III, and V fibers, and hydroxyproline were evaluated by immunohistochemistry, in situ detection of apoptosis, electron microscopy, immunofluorescence, and histomorphometry. Electron microscopy confirmed the presence of increased alveolar epithelial cells type 1 (AEC1) in apoptosis. Immunostaining showed increased nuclear expression of telomerase in AEC type 2 (AEC2) between normal and chronic scarring areas of usual interstitial pneumonia (UIP). Control lungs and normal areas from UIP lungs showed weak green birefringence of type I and III collagens in the alveolar wall and type V collagen in the basement membrane of alveolar capillaries. The increase in collagen V was greater than collagens I and III in scarring areas of UIP. A significant direct association was found between collagen V and AEC2 apoptosis. We concluded that telomerase, collagen V fiber density, and apoptosis evaluation in experimental UIP offers the potential to control reepithelization of alveolar septa and fibroblast proliferation. Strategies aimed at preventing high rates of collagen V synthesis, or local responses to high rates of cell apoptosis, may have a significant impact in pulmonary fibrosis.

HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.

Influência da adição de íons Ca++ e Mg++ na dureza de géis de concentrado proteíco de soro de leite bovino

Inúmeros estudos vêm sendo realizados com o objetivo de compreender o comportamento das proteínas do Concentrado Protéico de Soro (CPS). A capacidade destas proteínas em formar géis estáveis a temperaturas entre 70ºC e 90ºC, é uma propriedade funcional importante para a confecção de vários produtos alimentícios, tais como: produtos de padaria, cárneos, texturizados e lácteos. A concentração protéica, pH, composição iônica e temperatura podem ser controladas para obter um gel com as características desejadas. Neste trabalho foi investigado o efeito dos íons metálicos bivalentes Ca++ e Mg++, na propriedade de dureza de géis de CPS induzidos termicamente. Dispersões protéicas a 6; 7 e 8% de proteína do CPS a pH 6,3 com 0; 7,5; 15; 30 e 75mm de CaCl2 ou MgCl2 foram aquecidas a 75ºC por 45 min, resfriadas a 4ºC por 12 horas, e os géis avaliados em um texturômetro TA-XT2. Os géis formados com maiores concentrações do sal adicionado obtiveram maiores valores de dureza na faixa estudada. Nas concentrações de 15 a 75mM os valores de dureza dos géis com a adição de CaCl2 foram significativamente maiores (p<0,05) do que com adição de MgCl2. Na concentração de 8% de proteínas do CPS ambos os tratamentos atingem o maior valor de dureza (p<0,05) a 30mM do sal adicionado. O cálcio iônico mostrou ter um importante papel na formação do gel de proteínas do soro.

Perfil de textura e capacidade de retenção de água de géis ácidos de concentrado protéico de soro de leite

A capacidade dos concentrados protéicos de soro de leite (CPS) de formar géis é importante propriedade funcional. O objetivo deste estudo foi avaliar a influência das variáveis concentração de proteína, pH, temperatura e tempo de desnaturação, nos intervalos de 8 a 12%; 4,0 a 5,2; 81 a 89ºC e 15 a 27 minutos, respectivamente, no perfil de textura e capacidade de retenção de água de géis ácidos de CPS. O perfil de textura foi determinado em texturômetro TAXT2 e a capacidade de retenção de água avaliada através da umidade espremível dos géis. O delineamento estatístico foi um planejamento fatorial 2(4) completo. Os géis de CPS apresentaram os maiores valores de firmeza, coesividade, elasticidade e capacidade de retenção de água, de maneira geral, nas maiores faixas de concentração protéica, tempo e temperatura de desnaturação. Com relação a variável pH, géis formados em pH 4,0 apresentaram-se mais elásticos e com maior capacidade de retenção de água, enquanto que os géis formados em pH 4,9 a 5,2 mostraram-se mais firmes e coesos.

Perfil de textura e umidade espremível de géis do albume de ovos recobertos com soro de leite

A gelatinização é uma importante propriedade funcional das proteínas alimentares, devido ao seu grande potencial de uso nos alimentos estruturados. As proteínas da clara do ovo de galinha têm sido extensivamente usadas como ingredientes em alimentos processados. O objetivo deste trabalho foi avaliar as mudanças no pH, no perfil de textura e na umidade espremível de géis de clara de ovos de galinha com e sem cobertura de concentrado protéico de soro de leite, armazenados a 25ºC, por 3, 7, 10, 14, 21 e 28 dias. A dureza do gel do albume de ovos sem cobertura foi maior do que a de ovos recobertos, durante todos os períodos de armazenamento. Não houve efeito do tempo de armazenamento na dureza dos géis dos ovos sem cobertura. Em ovos cobertos, a regressão linear explicou 60% do comportamento da dureza em relação ao período de armazenamento. No caso da elasticidade, não houve interação entre período de armazenamento e a cobertura. Houve diferença entre as médias dentro de cada período, mas não durante o armazenamento. A maior elasticidade foi dos géis de ovos sem cobertura, comparados com os géis de ovos recobertos. O índice de coesividade e a mastigabilidade de géis de ovos sem cobertura foi maior que o de géis de ovos recobertos, em todos os períodos de armazenamento. A percentagem de umidade espremível (UE) de géis de clara de ovos recobertos foi maior do que a de ovos sem cobertura em todo o período de estocagem.

Estudo reológico da gelificação induzida pelo calor de proteínas do soro do leite e dos géis resultantes sob condições variadas de pH

Medidas reólogicas sob cisalhamento oscilatório foram realizadas em reômetro de tensão e deformação controladas com suspensões de concentrado de proteínas do soro do leite (WPC) a 10% (m/m) em água e a diferentes condições de pH (pH 4,0, 4,6 e 7,0). O processo de gelificação induzida pelo calor foi investigado, assim como as propriedades viscoelásticas dos géis formados a 80°C e daqueles formados após o decréscimo da temperatura a 20°C. Foi verificado que, em presença de teores significativos de sais, procedentes do próprio soro, a concentração usada nos experimentos foi suficiente para a formação de géis macroscópicos, e que o pH exerce papel importante na formação e na natureza estrutural dos géis.

Estabilidade de géis de amido de milho normal, ceroso e com alto teor de amilose adicionados de gomas guar e xantana durante os processos de congelamento e descongelamento

O objetivo do presente trabalho foi estudar os efeitos das gomas guar e xantana sobre a estabilidade dos géis de amido de milho normal, ceroso e com alto teor de amilose submetidos aos processos de congelamento e descongelamento. Os géis desses amidos, com concentração total de sólidos de 10% e adicionados das gomas (0,15; 0,50; 0,85 e 1%), foram submetidos a 5 ciclos de congelamento (20 horas a -18 °C) e descongelamento (4 horas a 25 °C), com exceção dos géis com alto teor de amilose, que foram submetidos a apenas 1 ciclo, devido à perda da estrutura de gel. A determinação da sinérese (porcentagem de água liberada) foi realizada pela diferença entre a massa inicial e a massa final das amostras. O gel de amido de milho normal liberou 74,45% de água, sendo que a adição de 1% da goma xantana reduziu significativamente a sinérese para 66,43%. A adição de 0,85 e 1% da goma xantana também reduziu a sinérese dos géis de amido ceroso. O menor teor de sinérese foi obtido com a utilização de 1% de goma xantana ao gel de amido de milho com alto teor de amilose, evidenciando a ação crioprotetora desta goma.

Experimental results and modeling of poultry carcass cooling by water immersion

Poultry carcasses have to be chilled to reduce the central breast temperatures from approximately 40 to 4 °C, which is crucial to ensure safe products. This work investigated the cooling of poultry carcasses by water immersion. Poultry carcasses were taken directly from an industrial processing plant and cooled in a pilot chiller, which was built to investigate the influence of the method and the water stirring intensity on the carcasses cooling. A simplified empiric mathematical model was used to represent the experimental results. These results indicated clearly that the understanding and quantification of heat transfer between the carcass and the cooling water is crucial to improve processes and equipment. The proposed mathematical model is a useful tool to represent the dynamics of carcasses cooling, and it can be used to compare different chiller operational conditions in industrial plants. Therefore, this study reports data and a simple mathematical tool to handle an industrial problem with little information available in the literature.

Multicomponent diffusion during Prato cheese ripening: mathematical modeling using the finite element method

The partial replacement of NaCl by KCl is a promising alternative to produce a cheese with lower sodium content since KCl does not change the final quality of the cheese product. In order to assure proper salt proportions, mathematical models are employed to control the product process and simulate the multicomponent diffusion during the reduced salt cheese ripening period. The generalized Fick's Second Law is widely accepted as the primary mass transfer model within solid foods. The Finite Element Method (FEM) was used to solve the system of differential equations formed. Therefore, a NaCl and KCl multicomponent diffusion was simulated using a 20% (w/w) static brine with 70% NaCl and 30% KCl during Prato cheese (a Brazilian semi-hard cheese) salting and ripening. The theoretical results were compared with experimental data, and indicated that the deviation was 4.43% for NaCl and 4.72% for KCl validating the proposed model for the production of good quality, reduced-sodium cheeses.

Modeling the water uptake by chicken carcasses during cooling by immersion

In this study, water uptake by poultry carcasses during cooling by water immersion was modeled using artificial neural networks. Data from twenty-five independent variables and the final mass of the carcass were collected in an industrial plant to train and validate the model. Different network structures with one hidden layer were tested, and the Downhill Simplex method was used to optimize the synaptic weights. In order to accelerate the optimization calculus, Principal Component Analysis (PCA) was used to preprocess the input data. The obtained results were: i) PCA reduced the number of input variables from twenty-five to ten; ii) the neural network structure 4-6-1 was the one with the best result; iii) PCA gave the following order of importance: parameters of mass transfer, heat transfer, and initial characteristics of the carcass. The main contributions of this work were to provide an accurate model for predicting the final content of water in the carcasses and a better understanding of the variables involved.

Mathematical modeling of dehydration of 'Fuji' and 'Gala' apples slices using infrared

The objective of this work was to determine and model the infrared dehydration curves of apple slices - Fuji and Gala varieties. The slices were dehydrated until constant mass, in a prototype dryer with infrared heating source. The applied temperatures ranged from 50 to 100 °C. Due to the physical characteristics of the product, the dehydration curve was divided in two periods, constant and falling, separated by the critical moisture content. A linear model was used to describe the constant dehydration period. Empirical models traditionally used to model the drying behavior of agricultural products were fitted to the experimental data of the falling dehydration period. Critical moisture contents of 2.811 and 3.103 kgw kgs-1 were observed for the Fuji and Gala varieties, respectively. Based on the results, it was concluded that the constant dehydration rates presented a direct relationship with the temperature; thus, it was possible to fit a model that describes the moisture content variation in function of time and temperature. Among the tested models, which describe the falling dehydration period, the model proposed by Midilli presented the best fit for all studied conditions.

Mathematical modeling of microbial growth in milk

A mathematical model to predict microbial growth in milk was developed and analyzed. The model consists of a system of two differential equations of first order. The equations are based on physical hypotheses of population growth. The model was applied to five different sets of data of microbial growth in dairy products selected from Combase, which is the most important database in the area with thousands of datasets from around the world, and the results showed a good fit. In addition, the model provides equations for the evaluation of the maximum specific growth rate and the duration of the lag phase which may provide useful information about microbial growth.

Modeling of allergen proteins found in sea food products

Shellfish are a source of food allergens, and their consumption is the cause of severe allergic reactions in humans. Tropomyosins, a family of muscle proteins, have been identified as the major allergens in shellfish and mollusks species. Nevertheless, few experimentally determined three-dimensional structures are available in the Protein Data Base (PDB). In this study, 3D models of several homologous of tropomyosins present in marine shellfish and mollusk species (Chaf 1, Met e1, Hom a1, Per v1, and Pen a1) were constructed, validated, and their immunoglobulin E binding epitopes were identified using bioinformatics tools. All protein models for these allergens consisted of long alpha-helices. Chaf 1, Met e1, and Hom a1 had six conserved regions with sequence similarities to known epitopes, whereas Per v1 and Pen a1 contained only one. Lipophilic potentials of identified epitopes revealed a high propensity of hydrophobic amino acids in the immunoglobulin E binding site. This information could be useful to design tropomyosin-specific immunotherapy for sea food allergies.

Mathematical modeling of microwave dried celery leaves and determination of the effective moisture diffusivities and activation energy

Celery (Apium graveolens L. var. secalinum Alef) leaves with 50±0.07 g weight and 91.75±0.15% humidity (~11.21 db) were dried using 8 different microwave power densities ranging between 1.8-20 W g-1, until the humidity fell down to 8.95±0.23% (~0.1 db). Microwave drying processes were completed between 5.5 and 77 min depending on the microwave power densities. In this study, measured values were compared with predicted values obtained from twenty thin layer drying theoretical, semi-empirical and empirical equations with a new thin layer drying equation. Within applied microwave power density; models whose coefficient and correlation (R²) values are highest were chosen as the best models. Weibull distribution model gave the most suitable predictions at all power density. At increasing microwave power densities, the effective moisture diffusivity values ranged from 1.595 10-10 to 6.377 10-12 m2 s-1. The activation energy was calculated using an exponential expression based on Arrhenius equation. The linear relationship between the drying rate constant and effective moisture diffusivity gave the best fit.