Ernane José Xavier Costa

Permeability of pure lipid bilayers to melatonin

Abstract: Melatonin, the chief hormone of the pineal gland, has been reported to interact with a variety of different cells. This ubiquitously acting hormone has been found to interact with protein receptors both at the cell membrane and in the nucleus. Moreover, melatonin was recently shown to be a very potent hydroxyl radical scavenger. The present work focuses on the interaction of melatonin with pure lipid bilayers. It is shown that melatonin can cross multilamellar lipid vesicles, which are used here as model systems for the lipid phase of biological membranes. Thus, the data prove that melatonin can easily pass through the cell membrane and bath every part of the cell, as previously suggested in the literature. Melatonin lipid association constant was calculated based on the change of the hormone fluorescence intensity due to its penetration into the hydrophobic lipid phase. Though melatonin was recently shown to be highly soluble in aqueous media, its lipid association constant is rather high, indicating that the biological action of the hormone is likely to be at the membrane level, either via its interaction with membrane receptors, and/or as a lipoperoxidation radical scavenger.

How melatonin interacts with lipid bilayers: a study by fluorescence and ESR spectroscopies

ESR spectra of spin labels placed at the membrane surface and at different depths of the bilayer core, and melatonin fluorescence in the presence of lipid vesicles, suggest an average shallow position for the hormone in the membrane. However, according to the melatonin ability to cross lipid bilayers, nitroxides placed deep in the bilayer were able to quench the melatonin fluorescence. Melatonin membrane partition coefficients were calculated for bilayers in different packing states, and similar and rather high values were found. The data presented here may be quite important to the understanding of melatonin physiological actions at the membrane level.

EEG-based discrimination between imagination of left and right hand movements using adaptive gaussian representation

This article uses the Adaptive Gaussian Representation (AGR) for human electroencephalogram (EEG) feature extraction aiming the discrimination among mental tasks to be used in a brain computer interface (BCI). It does not focus on the AGR time-frequency representation, but rather on their projection coefficients. Ten volunteers were asked to imagine either right or left hand movement, according to a proper visual stimulus. The features of the resulting EEG signals were characterised by extracting AGR coefficients. Classification was carried out using a Multilayer perceptron (MLP) trained with the classical backpropagation algorithm. Overall results show that AGR coefficients representation is able to reveal a significant EEG discrimination between imagination of right and left hand movement with a mean classification performance of 91%+/-5.8% achieved for female subjects and 87%+/-5.0% achieved for male subjects.

A low-cost autonomous optical sensor for water quality monitoring.

A low-cost optical sensor for monitoring the aquatic environment is presented, with the construction and design described in detail. The autonomous optical sensor is devised to be environmentally robust, easily deployable and simple to operate. It consists of a multi-wavelength light source with two photodiode detectors capable of measuring the transmission and side-scattering of the light in the detector head. This enables the sensor to give qualitative data on the changes in the optical opacity of the water. Laboratory tests to confirm colour and turbidity-related responses are described and the results given. The autonomous sensor underwent field deployments in an estuarine environment, and the results presented here show the sensors capacity to detect changes in opacity and colour relating to potential pollution events. The application of this low-cost optical sensor is in the area of environmental pollution alerts to support a water monitoring programme, where multiple such sensors could be deployed as part of a network.

Letters: EEG pattern discrimination between salty and sweet taste using adaptive Gabor transform

This article uses adaptive Gabor transform (AGR) for drawing feature information from human electroencephalogram (EEG) signals aiming at the discrimination among mental tasks during gustatory stimulation. In this study, single-channel EEG records from eight healthy humans were assessed during the application of sweet, salty and distilled water tastes. Muscular, ocular and skin potential activities were controlled. Overall results show that AGR coefficient representations are able to reveal a significant EEG discrimination among sweet, salty and water tastes.

Quantifying electrode position effects in EEG data with Lempel-Ziv complexity

Complexity measurement using Lempel and Ziv algorithm (LZ) has been used to analyze physiological data. This work shows that the Lempel and Ziv complexity measurement of EEG signals using wavelets transforms is independent of electrode position and dependent on cognitive tasks and brain activity. EEG database with 122 subjects from the public EEG dataset was used in this study. This database have spontaneous EEG and evoked potential (EP) data from a 64-multielectrode array under a variety of conditions collected at several centers in the United States, sponsored by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) project. Two experiments were performed with this database. The first experiment was to test the dependency of electrode positions into LZ complexity measures and the second experiment was to analyze if the LZ complexity was sensitive to the EEG acquired from control and alcoholic subjects. The results show that the complexity measurement is dependent on the changes of the pattern of brain dynamics and not dependent on electrode position.

An exposure assessment model of the prevalence of Salmonella spp. along the processing stages of Brazilian beef

Beef cattle carrying Salmonella spp. represents a risk for contamination of meat and meat products. This study aimed to build an exposure assessment model elucidating the changes in Salmonella prevalence in Brazilian beef along the processing stages. To this effect, the results of a number of published studies reporting Salmonella incidences were assembled in order to model conversion factors based on beta distributions representing the effect of every production stage on the Salmonella incidence on beef carcasses. A random-effects meta-analysis modelled the hide-to-carcass transfer of Salmonella contamination. The Monte Carlo simulation estimated the Salmonella prevalence in beef cuts from processing plants to be ∼6.1% (95% CI: 1.4–17.7%), which was in reasonable agreement with a pool (n = 105) of surveys’ data of Salmonella in Brazilian beef cuts (mean 4.9%; 95% CI: 1.8–11.5%) carried out in commercial establishments. The results not only underscored the significant increase in Salmonella prevalence that can occur during evisceration/splitting and boning but also reinforced that, when hygienic slaughter procedures are properly implemented, the load of Salmonella can be reduced at dehiding, rinsing and chilling. As the model was based on a systematic review and meta-analysis, it synthesised all available knowledge on the incidence of Salmonella in Brazilian beef.

A New Alternative Real-Time Method to Monitoring Dough Behavior during Processing Using Wireless Sensor Technology

Abstract Currently, food industries need rapidly available information related to food production while most lab-based instrumentation techniques are often complicated and expensive for real-time application. Studies show that the measurement of rheological characteristics of dough is a relevant control variable for the proper formulation of ingredients and bread-making additives. It is in this context that this work aims to present an alternative method for real-time monitoring of the evolution of the dough behavior during processing with telemetry form. The dough behavior is monitored through the changes in the electrical properties of the motor as affected by the properties of the machine torque that makes the mixture. Results of this work showed that it is possible to record dough deformation during mixing in real time and also demonstrated how wireless technology can contribute to the quality control of a food processing system.

Noninvasive method to assess the electrical brain activity from rats

This research presents a noninvasive method for the acquisition of brain electrical signal in rat. Was used an electroencephalography (EEG) system developed for bovine and adapted to rats. The bipolar electrode system (needle electrodes) was glued on the surface of the head of the animal without surgical procedures and the other electrode was glued to the tail, as ground. The EEG activity was sampled at 120Hz for an hour. The accuracy and precision of the EEG measurement was performed using Fourier analysis and signal energy. For this, the digital signal was divided into sections successive of 3 seconds and was decomposed into four frequency bands: delta (0.3 to 4Hz), theta (4-8Hz), alpha (8-12Hz) and beta (12-30Hz) and energy (µV²) of the series of time filtered were calculated. The method allowed the acquisition of non-invasive electrical brain signals in conscious rats and their frequency patterns were in agreement with previous studies that used surgical procedures to acquire EEG in rats. This system showed accuracy and precision and will allow further studies on behavior and to investigate the action of drugs on the central nervous system in rats without surgical procedures.

MONITORIZACIÓN DE REBAÑOS DE BOVINOS A TRAVÉS DE REDES DE SENSORES INALÁMBRICOS

Se presenta el prototipo de un sistema proyectado utilizando tecnicas de instrumentacion electronica y tecnologia de comunicacion inalambrica pudiendo ser utilizado para recolectar datos fisiologicos y monitorizar rebanos de bovinos. La necesidad de desarrollar tecnicas de adquisicion de datos, que causen menos perturbaciones al comportamiento natural de los animales, de interes en la zootecnia de precision, fue la principal motivacion de este trabajo. Para probar la aplicabilidad de la tecnologia de las redes de sensores inalambricos en este campo, se construyo una infraestructura utilizando tecnicas de instrumentacion electronica y comunicacion por radio-frecuencia. La red fue proyectada con el protocolo floating base sensor network (FBSN) que implementa una topologia adhoc con seleccion aleatoria de nodos. Los prototipos construidos fueron utilizados para efectuar colectas de datos de la actividad electrica cerebral y temperatura corporal de seis novillas de raza Holandesa. A fin de optimizar la infraestructura, fue desarrollado un software que a partir de la simulacion del desplazamiento de un rebano bovino ayuda a determinar la mejor distribucion de esa infraestructura en el area monitorizada. Los resultados alcanzados mostraron que es posible utilizar redes de sensores inalambricas como tecnicas eficientes para obtener datos fisiologicos de bovinos.