Artificial neural networks as auxiliary tools for the improvement of bean plant architecture

Classification using a scale of visual notes is a strategy used to select erect bean plants in order to improve bean plant architectures. Use of morphological traits associated with the phenotypic expression of bean architecture in classification procedures may enhance selection. The objective of this study was to evaluate the potential of artificial neural networks (ANNs) as auxiliary tools in the improvement of bean plant architecture. Data from 19 lines were evaluated for 22 traits, in 2007 and 2009 winter crops. Hypocotyl diameter and plant height were selected for analysis through ANNs. For classification purposes, these lines were separated into two groups, determined by the plant architecture notes. The predictive ability of ANNs was evaluated according to two scenarios to predict the plant architecture - training with 2007 data and validating in 2009 data (scenario 1), and vice versa (scenario 2). For this, ANNs were trained and validated using data from replicates of the evaluated lines for hypocotyl diameter individually, or together with the mean height of plants in the plot. In each scenario, the use of data from replicates or line means was evaluated for prediction through previously trained and validated ANNs. In both scenarios, ANNs based on hypocotyl diameter and mean height of plants were superior, since the error rates obtained were lower than those obtained using hypocotyl diameter only. Lower apparent error rates were verified in both scenarios for prediction when data on the means of the evaluated traits were submitted to better trained and validated ANNs

Evaluation of the efficiency of artificial neural networks for genetic value prediction

Artificial neural networks have shown great potential when applied to breeding programs. In this study, we propose the use of artificial neural networks as a viable alternative to conventional prediction methods. We conduct a thorough evaluation of the efficiency of these networks with respect to the prediction of breeding values. Therefore, we considered eight simulated scenarios, and for the purpose of genetic value prediction, seven statistical parameters in addition to the phenotypic mean in a network designed as a multilayer perceptron. After an evaluation of different network configurations, the results demonstrated the superiority of neural networks compared to estimation procedures based on linear models, and indicated high predictive accuracy and network efficiency

Sambucus australis Modulates Inflammatory Response via Inhibition of Nuclear Factor Kappa B (NF-kB) in vitro

Abstract: Medicinal plants have long been used as an alternative to traditional drugs for the treatment of inflammatory conditions due to the classical side effects and restricted access of various commercially available drugs, such as steroids (GCs) and nonsteroidal anti-inflammatory drugs (NSAIDs). Sambucus australis is a Brazilian herb that is commonly used to treat inflammatory diseases; however, few studies have examined the use of this species in the treatment of inflammatory conditions. The present study aims to evaluate the potential anti-inflammatory activity of S. australis in vitro. We established spleen cell cultures stimulated with pokeweed mitogen (PWM) to evaluate the production of proinflammatory cytokines, such as IL-4, IL-5, IFN-y, and IL-10 (by ELISA), and the expression of the transcription factor NF-kB (by RT-PCR). In addition, we evaluated the levels of nitric oxide in macrophage cultures and the membrane-stabilizing activity of S. australis methanolic extract (EMSA). Treatment with EMSA at concentrations of 100, 50, 25 and 12.5 µg/ml significantly decreased IL-4 (p<0.001) and IL-5 (p<0.001) levels. Treatment with 100 µg/ml EMSA reduced IFN-у (p<0.001) levels. Moreover, at 100 mg/ml, EMSA also increased IL-10 production and reduced NF-kB expression (p<0.01). In macrophage cultures stimulated with LPS, EMSA decreased nitric oxide levels (p<0.001) at all concentrations tested (100, 50, 25 and 12.5 µg/ml). Additionally, EMSA had a protective effect in the erythrocyte membrane stabilization assay. Taken together, these results suggest that S. australis has anti-inflammatory potential in vitro, characterized by the reduction of both inflammatory cytokines and the expression of NF-kB along with the up-regulation of IL-10