Efeitos do acido giberélico (GA) e do cloreto de clorocolina (CCC) sobre o crescimento inicial de Brachiaria plantaginea (Link) Hitch

Com o objetivo de verificar os efeitos do ácido giberélico (GA) e do cloreto de clorocolina (CCC) sobre o crescimento e desenvolvimento inicial de Brachiaria plantaginea, instalou-se a presente pesquisa em local com alta infestação dessa espécie, utilizando-se dos seguintes tratamentos: CCC nas concentrações de 1000 e 2000 ppm, GA na de 50 e 100 ppm e uma testemunha sem aplicação dos fitoreguladores. Na época de aplicação dos produtos as plantas apresentavam, em média, sete folhas e idade em torno de 25 dias. Os parâmetros avaliados foram altura do dossel, altura média das plantas, número médio de perfilhos por planta, biomassa seca da parte aérea total e por indivíduo. Os resultados foram avaliados 22 dias após a aplicação, quando se verificou que a biomassa total das plantas não foi alterada significativamente pelos tratamentos. Não ocorreram efeitos de doses e nem de interações entre fitoreguladores com dose em quaisquer dos parâmetros avaliados. Não se verificaram efeitos do CCC nos dados obtidos e todas as alterações ocorridas foram devidas à aplicação do GA que aumentou, significativamente, a altura de dossel e dos indivíduos de Brachiaria plantaginea e reduziu o perfilhamento da planta daninha.

Redução da interferência de Brachiaria plantaginea (link) hitch. em milho através de capinas e aplicação de herbicidas em diferentes épocas

O rendimento de grãos de milho é afetado pela interferência com as plantas daninhas, que pode variar em função da eficiência e da época de realização do método de controle utilizado no manejo da cultura. O objetivo deste trabalho foi determinar os efeitos da aplicação de herbicidas e de capinas em diferentes épocas sobre o controle de plantas daninhas e o rendimento de grãos na cultura do milho. O experimento foi instalado no sistema convencional de preparo do solo em Eldorado do Sul (RS), no ano agrícola 1997/98. A espécie de planta daninha predominante na área experimental foi Brachiaria plantaginea (BRAPL), em infestação média de 285 plantas por m². Os tratamentos foram constituídos pela aplicação isolada, seqüencial ou em mistura em tanque, em diferentes doses e épocas, dos herbicidas atrazine, atrazine + óleo vegetal, metolachlor e nicosulfuron. Todos os tratamentos com herbicidas foram correspondidos por tratamentos em que se utilizou capina manual com início na mesma época de aplicação dos herbicidas. O controle realizado em pré-emergência ou no início do desenvolvimento da cultura proporcionou maior rendimento de grãos, mesmo com a diminuição do controle de BRAPL no final do ciclo. As aplicações seqüenciais de herbicidas proporcionaram maior rendimento de grãos do que as misturas em tanque. Os rendimentos de grãos obtidos com a aplicação de herbicidas nas diversas épocas não foram diferentes em relação às suas respectivas capinas.

ClC-5 chloride channel and kidney stones: what is the link?

Nephrolithiasis is one of the most common diseases in the Western world. The disease manifests itself with intensive pain, sporadic infections, and, sometimes, renal failure. The symptoms are due to the appearance of urinary stones (calculi) which are formed mainly by calcium salts. These calcium salts precipitate in the renal papillae and/or within the collecting ducts. Inherited forms of nephrolithiasis related to chromosome X (X-linked hypercalciuric nephrolithiasis or XLN) have been recently described. Hypercalciuria, nephrocalcinosis, and male predominance are the major characteristics of these diseases. The gene responsible for the XLN forms of kidney stones was cloned and characterized as a chloride channel called ClC-5. The ClC-5 chloride channel belongs to a superfamily of voltage-gated chloride channels, whose physiological roles are not completely understood. The objective of the present review is to identify recent advances in the molecular pathology of nephrolithiasis, with emphasis on XLN. We also try to establish a link between a chloride channel like ClC-5, hypercalciuria, failure in urine acidification and protein endocytosis, which could explain the symptoms exhibited by XLN patients.

Early prediction of poor outcome in patients with acute asthma in the emergency room

Early identification of patients who need hospitalization or patients who should be discharged would be helpful for the management of acute asthma in the emergency room. The objective of the present study was to examine the clinical and pulmonary functional measures used during the first hour of assessment of acute asthma in the emergency room in order to predict the outcome. We evaluated 88 patients. The inclusion criteria were age between 12 and 55 years, forced expiratory volume in the first second below 50% of predicted value, and no history of chronic disease or pregnancy. After baseline evaluation, all patients were treated with 2.5 mg albuterol delivered by nebulization every 20 min in the first hour and 60 mg of intravenous methylprednisolone. Patients were reevaluated after 60 min of treatment. Sixty-five patients (73.9%) were successfully treated and discharged from the emergency room (good responders), and 23 (26.1%) were hospitalized or were treated and discharged with relapse within 10 days (poor responders). A predictive index was developed: peak expiratory flow rates after 1 h <=0% of predicted values and accessory muscle use after 1 h. The index ranged from 0 to 2. An index of 1 or higher presented a sensitivity of 74.0, a specificity of 69.0, a positive predictive value of 46.0, and a negative predictive value of 88.0. It was possible to predict outcome in the first hour of management of acute asthma in the emergency room when the index score was 0 or 2.

Prediction of exposed domains of envelope glycoprotein in Indian HIV-1 isolates and experimental confirmation of their immunogenicity in humans

We describe the impact of subtype differences on the seroreactivity of linear antigenic epitopes in envelope glycoprotein of HIV-1 isolates from different geographical locations. By computer analysis, we predicted potential antigenic sites of envelope glycoprotein (gp120 and gp4l) of this virus. For this purpose, after fetching sequences of proteins of interest from data banks, values of hydrophilicity, flexibility, accessibility, inverted hydrophobicity, and secondary structure were considered. We identified several potential antigenic epitopes in a B subtype strain of envelope glycoprotein of HIV-1 (IIIB). Solid- phase peptide synthesis methods of Merrifield and Fmoc chemistry were used for synthesizing peptides. These synthetic peptides corresponded mainly to the C2, V3 and CD4 binding sites of gp120 and some parts of the ectodomain of gp41. The reactivity of these peptides was tested by ELISA against different HIV-1-positive sera from different locations in India. For two of these predicted epitopes, the corresponding Indian consensus sequences (LAIERYLKQQLLGWG and DIIGDIRQAHCNISEDKWNET) (subtype C) were also synthesized and their reactivity was tested by ELISA. These peptides also distinguished HIV-1-positive sera of Indians with C subtype infections from sera from HIV-negative subjects.

Clinical signs of pneumonia in children: association with and prediction of diagnosis by fuzzy sets theory

The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of disease) and seven clinical signs were divided into two samples, one for analysis and other for validation. The former was used to derive relations by multi-discriminant analysis (MDA) and by fuzzy max-min compositions (fuzzy), and the latter was used to assess the predictions drawn from each type of relation. MDA and fuzzy were closely similar in terms of prediction, with correct allocation of 75.7 to 78.3% of patients in the validation sample, and displaying only a single instance of disagreement: a patient with low level of toxemia was mistaken as not diseased by MDA and correctly taken as somehow ill by fuzzy. Concerning relations, each method provided different information, each revealing different aspects of the relations between clinical signs and diagnoses. Both methods agreed on pointing X-ray, dyspnea, and auscultation as better related with pneumonia, but only fuzzy was able to detect relations of heart rate, body temperature, toxemia and respiratory rate with pneumonia. Moreover, only fuzzy was able to detect a relationship between heart rate and absence of disease, which allowed the detection of six malnourished children whose diagnoses as healthy are, indeed, disputable. The conclusion is that even though fuzzy sets theory might not improve prediction, it certainly does enhance clinical knowledge since it detects relationships not visible to stochastic models.

Fuzzy expert system in the prediction of neonatal resuscitation

In view of the importance of anticipating the occurrence of critical situations in medicine, we propose the use of a fuzzy expert system to predict the need for advanced neonatal resuscitation efforts in the delivery room. This system relates the maternal medical, obstetric and neonatal characteristics to the clinical conditions of the newborn, providing a risk measurement of need of advanced neonatal resuscitation measures. It is structured as a fuzzy composition developed on the basis of the subjective perception of danger of nine neonatologists facing 61 antenatal and intrapartum clinical situations which provide a degree of association with the risk of occurrence of perinatal asphyxia. The resulting relational matrix describes the association between clinical factors and risk of perinatal asphyxia. Analyzing the inputs of the presence or absence of all 61 clinical factors, the system returns the rate of risk of perinatal asphyxia as output. A prospectively collected series of 304 cases of perinatal care was analyzed to ascertain system performance. The fuzzy expert system presented a sensitivity of 76.5% and specificity of 94.8% in the identification of the need for advanced neonatal resuscitation measures, considering a cut-off value of 5 on a scale ranging from 0 to 10. The area under the receiver operating characteristic curve was 0.93. The identification of risk situations plays an important role in the planning of health care. These preliminary results encourage us to develop further studies and to refine this model, which is intended to implement an auxiliary system able to help health care staff to make decisions in perinatal care.

Synergistic control of forearm based on accelerometer data and artificial neural networks

In the present study, we modeled a reaching task as a two-link mechanism. The upper arm and forearm motion trajectories during vertical arm movements were estimated from the measured angular accelerations with dual-axis accelerometers. A data set of reaching synergies from able-bodied individuals was used to train a radial basis function artificial neural network with upper arm/forearm tangential angular accelerations. The trained radial basis function artificial neural network for the specific movements predicted forearm motion from new upper arm trajectories with high correlation (mean, 0.9149-0.941). For all other movements, prediction was low (range, 0.0316-0.8302). Results suggest that the proposed algorithm is successful in generalization over similar motions and subjects. Such networks may be used as a high-level controller that could predict forearm kinematics from voluntary movements of the upper arm. This methodology is suitable for restoring the upper limb functions of individuals with motor disabilities of the forearm, but not of the upper arm. The developed control paradigm is applicable to upper-limb orthotic systems employing functional electrical stimulation. The proposed approach is of great significance particularly for humans with spinal cord injuries in a free-living environment. The implication of a measurement system with dual-axis accelerometers, developed for this study, is further seen in the evaluation of movement during the course of rehabilitation. For this purpose, training-related changes in synergies apparent from movement kinematics during rehabilitation would characterize the extent and the course of recovery. As such, a simple system using this methodology is of particular importance for stroke patients. The results underlie the important issue of upper-limb coordination.

A link between sleep loss, glucose metabolism and adipokines

The present review evaluates the role of sleep and its alteration in triggering problems of glucose metabolism and the possible involvement of adipokines in this process. A reduction in the amount of time spent sleeping has become an endemic condition in modern society, and a search of the current literature has found important associations between sleep loss and alterations of nutritional and metabolic contexts. Studies suggest that sleep loss is associated with problems in glucose metabolism and a higher risk for the development of insulin resistance and type 2 diabetes mellitus. The mechanism involved may be associated with the decreased efficacy of regulation of the hypothalamus-pituitary-adrenal axis by negative feedback mechanisms in sleep-deprivation conditions. In addition, changes in the circadian pattern of growth hormone (GH) secretion might also contribute to the alterations in glucose regulation observed during sleep loss. On the other hand, sleep deprivation stress affects adipokines - increasing tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) and decreasing leptin and adiponectin -, thus establishing a possible association between sleep-debt, adipokines and glucose metabolism. Thus, a modified release of adipokines resulting from sleep deprivation could lead to a chronic sub-inflammatory state that could play a central role in the development of insulin resistance and type 2 diabetes mellitus. Further studies are necessary to investigate the role of sleep loss in adipokine release and its relationship with glucose metabolism.

Utility of a novel risk score for prediction of ventricular tachycardia and cardiac death in chronic Chagas disease - the SEARCH-RIO study

The SEARCH-RIO study prospectively investigated electrocardiogram (ECG)-derived variables in chronic Chagas disease (CCD) as predictors of cardiac death and new onset ventricular tachycardia (VT). Cardiac arrhythmia is a major cause of death in CCD, and electrical markers may play a significant role in risk stratification. One hundred clinically stable outpatients with CCD were enrolled in this study. They initially underwent a 12-lead resting ECG, signal-averaged ECG, and 24-h ambulatory ECG. Abnormal Q-waves, filtered QRS duration, intraventricular electrical transients (IVET), 24-h standard deviation of normal RR intervals (SDNN), and VT were assessed. Echocardiograms assessed left ventricular ejection fraction. Predictors of cardiac death and new onset VT were identified in a Cox proportional hazard model. During a mean follow-up of 95.3 months, 36 patients had adverse events: 22 new onset VT (mean±SD, 18.4±4‰/year) and 20 deaths (26.4±1.8‰/year). In multivariate analysis, only Q-wave (hazard ratio, HR=6.7; P<0.001), VT (HR=5.3; P<0.001), SDNN<100 ms (HR=4.0; P=0.006), and IVET+ (HR=3.0; P=0.04) were independent predictors of the composite endpoint of cardiac death and new onset VT. A prognostic score was developed by weighting points proportional to beta coefficients and summing-up: Q-wave=2; VT=2; SDNN<100 ms=1; IVET+=1. Receiver operating characteristic curve analysis optimized the cutoff value at >1. In 10,000 bootstraps, the C-statistic of this novel score was non-inferior to a previously validated (Rassi) score (0.89±0.03 and 0.80±0.05, respectively; test for non-inferiority: P<0.001). In CCD, surface ECG-derived variables are predictors of cardiac death and new onset VT.

HIGH PRESSURE PHASE EQUILIBRIUM: PREDICTION OF ESSENTIAL OIL SOLUBILITY

This work describes a method to predict the solubility of essential oils in supercritical carbon dioxide. The method is based on the formulation proposed in 1979 by Asselineau, Bogdanic and Vidal. The Peng-Robinson and Soave-Redlich-Kwong cubic equations of state were used with the van der Waals mixing rules with two interaction parameters. Method validation was accomplished calculating orange essential oil solubility in pressurized carbon dioxide. The solubility of orange essential oil in carbon dioxide calculated at 308.15 K for pressures of 50 to 70 bar varied from 1.7± 0.1 to 3.6± 0.1 mg/g. For same the range of conditions, experimental solubility varied from 1.7± 0.1 to 3.6± 0.1 mg/g. Predicted values were not very sensitive to initial oil composition.

Resistência de quatro genótipos de amendoim à produção de aflatoxina B1 após inoculação com Aspergillus flavus Link

Avaliou-se a produção de aflatoxina B1 pelo Aspergillus flavus IMI 190443, inoculado em sementes de genótipos de amendoim: Tatu Vermelho, VRR-245, 2117 e 2155, in natura e autoclavado a 1210 C por 20 minutos, previamente cultivados no Centro Experimental do Instituto Agronômico de Campinas, em 1995/96. A aflatoxina B1 foi quantificada por cromatografia em camada delgada, utilizando comparação visual com padrões. Os níveis de aflatoxina B1 das amostras autoclavadas e in natura dos genótipos Tatu Vermelho, VRR-245 e 2155 foram significativamente diferentes (p <0,05, Teste de Duncan) quando comparados aos níveis do genótipo 2117. O genótipo 2117, originário da Índia, apresentou independente do processo com e sem aquecimento os menores níveis de aflatoxina B1 em relação aos dos outros genótipos. Os resultados obtidos mostram perspectivas de exploração da resistência varietal no controle da aflatoxina.

Application of mathematical models for the prediction of adsorption isotherms in solid mixture for mango powder refreshment

Solid mixtures for refreshment are already totally integrated to the Brazilian consumers' daily routine, because of their quick preparation method, yield and reasonable price - quite lower if compared to 'ready-to-drink' products or products for prompt consumption, what makes them economically more accessible to low-income populations. Within such a context, the aim of this work was to evaluate the physicochemical and mineral composition, as well as the hygroscopic behavior of four different brands of solid mixture for mango refreshment. The BET, GAB, Oswim and Henderson mathematical models were built through the adjustment of experimental data to the isotherms of adsorption. Results from the physiochemical evaluation showed that the solid mixtures for refreshments are considerable sources of ascorbic acid and reductor sugar; and regarding mineral compounds, they are significant sources of calcium, sodium and potassium. It was also verified that the solid mixtures for refreshments of the four studied brands are considered highly hygroscopic.

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.