Resveratrol inhibits the intracellular calcium increase and angiotensin/endothelin system activation induced by soluble uric acid in mesangial cells

Resveratrol (Resv) is natural polyphenol found in grapes. This study evaluated the protective effect of Resv against the effects of uric acid (UA) in immortalized human mesangial cells (ihMCs). ihMCs were preincubated with Resv (12.5 µM) for 1 h and treated with UA (10 mg/dL) for 6 or 12 h. The intracellular calcium concentration [Ca2+]i was quantified by fluorescence using flow cytometry. Angiotensinogen (AGT) and pre-pro endothelin-1 (ppET-1) mRNA were assayed by quantitative real-time RT-PCR. Angiotensin II (AII) and endothelin-1 (ET-1) were assayed by ELISA. UA significantly increased [Ca2+]i. Pre-incubation with Resv significantly reduced the change in [Ca2+]i induced by UA. Incubation with UA for 6 or 12 h also increased AGT mRNA expression and AII protein synthesis. Resv blunted these increases in AGT mRNA expression and AII protein. Incubation with UA in the ihMCs increased ppET-1 expression and ET-1 protein synthesis at 6 and 12 h. When ihMCs were pre-incubated with Resv, UA had a significantly diminished effect on ppET-1 mRNA expression and ET-1 protein synthesis at 6 and 12 h, respectively. Our results suggested that UA triggers reactions including AII and ET-1 production in mesangial cells. The renin-angiotensin system may contribute to the pathogenesis of renal function and chronic kidney disease. Resv can minimize the impact of UA on AII, ET-1 and the increase of [Ca2+]i in mesangial cells, suggesting that, at least in part, Resv can prevent the effects of soluble UA in mesangial cells.

CTLA4 enhances the osteogenic differentiation of allogeneic human mesenchymal stem cells in a model of immune activation

Allogeneic mesenchymal stem cells (allo-MSCs) have recently garnered increasing interest for their broad clinical therapy applications. Despite this, many studies have shown that allo-MSCs are associated with a high rate of graft rejection unless immunosuppressive therapy is administered to control allo-immune responses. Cytotoxic T-lymphocyte-associated protein 4 (CTLA4) is a co-inhibitory molecule expressed on T cells that mediates the inhibition of T-cell function. Here, we investigated the osteogenic differentiation potency of allo-MSCs in an activated immune system that mimics the in vivo allo-MSC grafting microenvironment and explored the immunomodulatory role of the helper T cell receptorCTLA4 in this process. We found that MSC osteogenic differentiation was inhibited in the presence of the activated immune response and that overexpression of CTLA4 in allo-MSCs suppressed the immune response and promoted osteogenic differentiation. Our results support the application of CTLA4-overexpressing allo-MSCs in bone tissue engineering.

Activation of endogenous angiotensin converting enzyme 2 prevents early injuries induced by hyperglycemia in rat retina

Diabetic retinopathy (DR) is a serious complication of diabetes mellitus that may result in blindness. We evaluated the effects of activation of endogenous angiotensin converting enzyme (ACE) 2 on the early stages of DR. Rats were administered an intravenous injection of streptozotocin to induce hyperglycemia. The ACE2 activator 1-[[2-(dimethylamino) ethyl] amino]-4-(hydroxymethyl)-7-[[(4-methylphenyl) sulfonyl] oxy]-9H-xanthone 9 (XNT) was administered by daily gavage. The death of retinal ganglion cells (RGC) was evaluated in histological sections, and retinal ACE2, caspase-3, and vascular endothelial growth factor (VEGF) expressions were analyzed by immunohistochemistry. XNT treatment increased ACE2 expression in retinas of hyperglycemic (HG) rats (control: 13.81±2.71 area%; HG: 14.29±4.30 area%; HG+XNT: 26.87±1.86 area%; P<0.05). Importantly, ACE2 activation significantly increased the RCG number in comparison with HG animals (control: 553.5±14.29; HG: 530.8±10.3 cells; HG+XNT: 575.3±16.5 cells; P<0.05). This effect was accompanied by a reduction in the expression of caspase-3 in RGC of the HG+XNT group when compared with untreated HG rats (control: 18.74±1.59; HG: 38.39±3.39 area%; HG+XNT: 27.83±2.80 area%; P<0.05). Treatment with XNT did not alter the VEGF expression in HG animals (P>0.05). Altogether, these findings indicate that activation of ACE2 reduced the death of retinal ganglion cells by apoptosis in HG rats.

Activation of locus coeruleus heme oxygenase-carbon monoxide pathway promoted an anxiolytic-like effect in rats

The heme oxygenase-carbon monoxide pathway has been shown to play an important role in many physiological processes and is capable of altering nociception modulation in the nervous system by stimulating soluble guanylate cyclase (sGC). In the central nervous system, the locus coeruleus (LC) is known to be a region that expresses the heme oxygenase enzyme (HO), which catalyzes the metabolism of heme to carbon monoxide (CO). Additionally, several lines of evidence have suggested that the LC can be involved in the modulation of emotional states such as fear and anxiety. The purpose of this investigation was to evaluate the activation of the heme oxygenase-carbon monoxide pathway in the LC in the modulation of anxiety by using the elevated plus maze test (EPM) and light-dark box test (LDB) in rats. Experiments were performed on adult male Wistar rats weighing 250-300 g (n=182). The results showed that the intra-LC microinjection of heme-lysinate (600 nmol), a substrate for the enzyme HO, increased the number of entries into the open arms and the percentage of time spent in open arms in the elevated plus maze test, indicating a decrease in anxiety. Additionally, in the LDB test, intra-LC administration of heme-lysinate promoted an increase on time spent in the light compartment of the box. The intracerebroventricular microinjection of guanylate cyclase, an sGC inhibitor followed by the intra-LC microinjection of the heme-lysinate blocked the anxiolytic-like reaction on the EPM test and LDB test. It can therefore be concluded that CO in the LC produced by the HO pathway and acting via cGMP plays an anxiolytic-like role in the LC of rats.

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.

Previsão de estabilidade de óleos vegetais através da rede de inteligência artificial

Redes Neurais Artificiais são técnicas computacionais que se utilizam de um modelo matemático capaz de adquirir conhecimentos pela experiência; esse comportamento inteligente da rede provém das interações entre unidades de processamento, denominadas de neurônios artificiais. O objetivo deste trabalho foi criar uma rede neural capaz de prever a estabilidade de óleos vegetais, a partir de dados de suas composições químicas, visando um modelo para a previsão da shelf-life de óleos vegetais, tendo como parâmetros apenas dados de suas composições químicas. Os primeiros passos do processo de desenvolvimento da rede consistiram na coleta de dados relativos ao problema e sua separação em um conjunto de treinamento e outro de testes. Estes conjuntos apresentaram como variáveis dados de composição química, que incluíram os valores totais em ácidos graxos, fenóis, tocoferóis e a composição individual em ácidos graxos. O passo seguinte foi a execução do treinamento, onde o padrão de entrada apresentado à rede como parâmetro de estabilidade foi o índice de peróxido, determinado experimentalmente por um período de 16 dias de armazenagem na ausência de luz, a 65ºC. Após o treinamento foi testada a capacidade de previsão adquirida pela rede, em função do parâmetro de estabilidade adotado, mas com um novo grupo de óleos. Seguindo o teste, foi determinada a correlação linear entre os valores de estabilidade previstos pela rede e aqueles determinados experimentalmente. Com os resultados obtidos, pode-se confirmar a viabilidade de previsão da estabilidade de óleos vegetais pela rede neural, a partir de dados de sua composição química, utilizando como parâmetro de estabilidade o índice de peróxido.

An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.

Artificial neural networks (ANN): prediction of sensory measurements from instrumental data

The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.

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.

Inteligência artificial e teoria de resolução de problemas

Este artigo é uma tentativa de delinear as principais características da pesquisa numa nova área de estudos a chamada Inteligência Artificial (AI). Os itens 1 e 2 constituem um rápido histórico da AI e seus pressupostos básicos. O item 3 trata da teoria de resolução de problemas, desenvolvida por A. Newell e H. Simon. O item 4 procura mostrar a relevância da AI para a Filosofia, em especial para a filosofia da Mente e para a Teoria do Conhecimento.

Robots, intencionalidade e inteligência artificial

O artigo aborda problemas filosóficos relativos à natureza da intencionalidade e da representação mental. A primeira parte apresenta um breve histórico dos problemas, percorrendo rapidamente alguns episódios da filosofia clássica e da filosofia contemporânea. A segunda parte examina o Chinese Room Argument (Argumento do Quarto do Chinês) formulado por J. Searle. A terceira parte desenvolve alguns argumentos visando mostrar a inadequação do modelo funcionalista de mente na construção de robots. A conclusão (quarta parte) aponta algumas alternativas ao modelo funcionalista tradicional, como, por exemplo, o conexionismo.