Modelling molecular and inorganic data of Amanita ponderosa mushrooms using artificial neural networks

Amanita ponderosa are wild mushroom eatable, growing spontaneously in some Mediterranean microclimates, namely in Alentejo and Andaluzia, in the Iberian Peninsula, due to its Mediterranean characteristics. The aim of this study was to evaluate inorganic composition of mycorrhizal Amanita ponderosa collected from different regions of the southwest of the Iberian Peninsula and to access molecular biomarkers using artificial neural networks. Fruiting bodies of the A. ponderosa mushrooms were collected in Spring from different locations area, in the southwest of the Iberian Peninsula. Three individuals were sampled per location. The inorganic analyses showed that mineral composition of these mushrooms depends on the ecosystem where they grow. Levels of trace metals are considerably lower, acceptable to human consumption at nutritional and low toxic levels. Molecular approach using the microsatellite primer M13-PCR allowed to distinguish the mushrooms at specie level and to differentiate the A. ponderosa strains according to their location. Data mining tools were used in order to correlate inorganic and molecular results. In order to obtain the best prediction of the M13 PCR DNA band profile, different network structures and architectures were elaborated and evaluated. In the present work the error metric used was the mean squared error. The neural network selected for modelling the data has a 6-7-14 topology, i.e. an input layer with six nodes, a hidden layer with seven nodes and a fourteen nodes output layer. A good match between the experimental and predicted values can be observed

A Data Mining Approach to Characterize Amanita ponderosa Mushrooms Using Inorganic Profile and M13-PCR Molecular Data

Wild eatable mushrooms Amanita ponderosa are very appreciated in gastronomy, showing high export potential. This specie grows spontaneously in some microclimates, namely in the southwest of the Iberian Peninsula. The aim of this study is to find inorganic and molecular markers that allow to characterize the wild A. ponderosa strains collected from different geographical locations in the Iberian Peninsula. Molecular approach using the microsatellite primer M13-PCR allowed to distinguish the mushrooms at specie level and to differentiate the A. ponderosa strains according to their location. Data mining tools were used in order to correlate inorganic and molecular results. A. ponderosa strains showed different inorganic composition according to their habitat. It was developed a segmentation model based on the molecular analysis, which allow relating the clusters obtained with the geographical site of sampling. There were also developed explanatory models of the segmentation, using decision trees, by following two different strategies. One of them based on the bands of DNA and, the other one, based on the mineral composition. The results show that it may be possible to relate the molecular and inorganic data. The present findings are wide potential application and both health and economical benefits arise from this study

Aroma Compounds Prevision using Artificial Neural Networks Influence of Newly Indigenous Saccharomyces SPP in White Wine Produced with Vitis Vinifera Cv Siria

Commercial yeasts strains of Saccharomyces cerevisae are frequently used in white wine production as starters in fermentation process, however, these strains can affect the wine characteristics. The aim of this study was to evaluate the effect of three strains of Saccharomyces spp. (var. 1, 2 and 3) on wine aroma compounds produced in microvinification assays. Microvinification assays were carried out with Vitis vinifera cv Síria grapes using the strains in study as starters. Aroma compounds were identified and quantified by GC-FID and GC-MS. At the end of fermentation process and during the first three months of maturation some aroma compounds were detected, namely propanol, isobutanol, isoamyl acetate, isoamylic alcohol, ethyl hexanoate, ethyl lactate, hexanol, ethyl octanoate, 3-ethylhydroxibutirate, benzaldehyde, 3-methyl-2-butanol, 2,3-butanediol, g-butyrolactone, ethyl decanoate, diethyl succinate, methionol, 4-hydroxi-2-butyrolactone, heptanoic acid, phenylethyl acetate, ethyl dodecanoate, phenylethanol, octanoic acid, 2-methoxy-4- vinylphenol and decanoic acid. Artificial Neural Networks (ANNs) were used to predict the concentration of twelve wine aroma compounds from the phenyl ethanol, propanol, isobutanol, hexanol, heptanoic acid, octanoic acid and decanoic acid concentrations. Results showed that, either, maturation time and Saccharomyces strain used as starter influence the aroma compounds produced. Wines produced with S. cerevisae var. 1 and S. cerevisae var. 2 showed a similar composition in aroma compounds, relatively to the wines produced with the strain S. cerevisae var. 3. However, for S. cerevisae var. 1 and S. cerevisae var. 2 the time of maturation influence the aroma composition of wines. From a technological approach, the choice of yeast strain and maturation time has decisive influence on the aroma compounds produced

Redução de compostos fenólicos de resíduos de lagares de azeite utilizando culturas de Coriolus versicolor

In this study, C. versicolor cultures were performed during 20 days with different RLA (olive mill wastes)subtracts, 50%, 75% and 100%. During this assay, samples were collected in regular time intervals, cell growth were evaluated and broth decolorization was observed. The organic matter and total phenolic compounds level in the culture broth showed a decrease in all RLA ratios. 50% and 75% RLA presented high total phenolic removal, 85% and 90% respectively. In the end of the assay, toxicological evaluation of the culture broth was performed against Artemia salina. These results showed a toxicological decrease of these residues after biological treatment with C. Versicolor

Prediction of bioactive compounds activity against wood contaminant fungi using artificial neural networks

Biopesticides based on natural endophytic bacteria to control plant diseases are an ecological alternative to the chemical treatments. Bacillus species produce a wide variety of metabolites with biological activity like iturinic lipopeptides. This work addresses the production of biopesticides based on natural endophytic bacteria, isolated from Quercus suber. Artificial Neural Networks were used to maximize the percentage of inhibition triggered by antifungal activity of bioactive compounds produced by Bacillus amyloliquefaciens. The active compounds, produced in liquid cultures, inhibited the growth of fifteen fungi and exhibited a broader spectrum of antifungal activity against surface contaminant fungi, blue stain fungi and phytopathogenic fungi. A 19-7-6-1 neural network was selected to predict the percentage of inhibition produced by antifungal bioactive compounds. A good match among the observed and predicted values was obtained with the R2 values varying between 0.9965 – 0.9971 and 0.9974 – 0.9989 for training and test sets. The 19-7-6-1 neural network was used to establish the dilution rates that maximize the production of antifungal bioactive compounds, namely 0.25 h-1 for surface contaminant fungi, 0.45 h-1 for blue stain fungi and between 0.30 and 0.40 h-1 for phytopathogenic fungi. Artificial neural networks show great potential in the modelling and optimization of these bioprocesses.Les biopesticides à base de bactéries endophytes naturelles pour lutter contre les maladies des plantes constituent une alternative écologique aux traitements chimiques. Les espèces de Bacillus produisent une grande variété de métabolites biologiquement actifs tels que les lipopeptides ituriniques. Cette étude porte sur la production de biopesticides par des bactéries endophytes naturelles isolées du Quercus suber L. Des réseaux neuronaux artificiels ont été utilisés pour maximiser le pourcentage d’inhibition provoquée par l’activité antifongique des composés bioactifs produits par Bacillus amyloliquefaciens. Les composés actifs, produits en culture liquide, ont inhibé la croissance de 15 champignons et avaient un spectre d’activé antifongique plus large contre les contaminants fongiques de surface, les champignons de bleuissement et les champignons phytopathogènes. Un réseau neuronal 19-7-6-1 a été choisi pour prédire le pourcentage d’inhibition produit par les composés bioactifs antifongiques. Une bonne concordance entre les valeurs observées et prédites a été obtenue; les valeurs de R2 variaient de 0,9965 a` 0,9971 et de 0,9974 a` 0,9989 pour les bases d’apprentissage et de test. Le réseau neuronal 19-7-6-1 a été utilisé pour établir les taux de dilution qui maximisent la production des composés bioactifs antifongiques, nommément 0,25 h−1 pour les contaminants fongiques de surface, 0,45 h−1 pour les champignons de bleuissement et entre 0,30 et 0,40 h−1 pour les champignons phytopathogènes. Les réseaux neuronaux artificiels ont un potentiel élevé pour modéliser et optimiser ces processus biologiques

Terapêutica da Diabetes Tipo1 com Bomba Infusora de Insulina

[resumo][abstract

Tvådimensionella och tredimensionella figurer som undervisningsinnehåll i geometriundervisning på lågstadiet : En jämförelseanalys av hur lärare organiserar och genomför geometriundervisning i årskurs 1-3 i relation till van Hiele ́s teori

Ämnesområdet för den här studien är matematik, mer specificerat mot området geometri. Syftet är att undersöka hur lärare beskriver att de arbetar med det matematiska området geometri för att möjliggöra och utveckla elevers geometriska kunskaper. Sociokulturell teori ligger till grund för studien, eftersom social interaktion kan leda till kunskapsutveckling inom geometri. Studien genomfördes genom intervjuer med fem lärare med varierande lång yrkeserfarenhet. Analys av material gjordes genom en kvalitativ innehållsanalys och lärares resonemang ställs mot varandra för att urskilja likheter och skillnader i organisering av undervisning och arbetssätt. Lärares resonemang ställs också i relation till van Hiele ́s teori, för att urskilja likheter och skillnader av empiri och teori. Resultatet visade att geometriundervisning är ett återkommande område på lågstadiet och det ska därför inte ska ta upp för mycket tid. Undervisning baseras på läromedel och dess struktur följs genomgående i arbetsområdet. Genomförande av undervisning föredras att göra i mindre elevgrupper och konkret material och digitala verktyg inkluderas som stöd för elevers kunskapsutveckling gällande tvådimensionella och tredimensionella figurer. Avslutningsvis diskuteras föregående innehåll i relation till van Hiele ́s teori, sociokulturellt perspektiv och läroplan för grundskolan, förskoleklass och fritidshem.The subject area for this study in mathematics, specified geometry. The purpose of the study is to investigate how teachers describe how they work with the mathematical field of geometry to enable and develop students' geometric skills. The underline theory is socio-cultural perspective, since social interaction can result in geometric concept understanding. The study was conducted through interviews with five teachers with varied long professional experience. Analysis of material was done through qualitative content analysis and teacher reasoning against each other in order to distinguish similarities and differences in the organization of teaching and working methods. Teachers' reasoning is also made in relation to Van Hiele's theory, in order to distinguish similarities and differences of empirical and theory. The result showed that geometry education is a recurring area at the lower stage and therefore should not take too much time. Teaching is based on teaching materials and its structure is monitored throughout the work area. Implementation of teaching is preferred to do in smaller student groups and concrete materials and digital tools are included as support for pupils' knowledge development regarding two- dimensional and three-dimensional figures'. Previous content is discussed in relation to Van Hiele's theory, socio-cultural perspective and curriculum

Phylogenetic and Inorganic Profile of Mediterranean Mycorrhizal Amanita ponderosa Mushrooms: A Data Mining Approach

Amanita ponderosa are wild edible mushrooms, growing in some Mediterranean microclimates, namely in Alentejo and Andaluzia, in the Iberian Peninsula. The nutritional values of these fungi make them highly exportable. Due to the wide diversity of mushrooms in nature, it is essential to differentiate and to identify the various edible species. Mushrooms can accumulate high concentrations of some elements, namely toxic metals, because the symbiotic relation between these macrofungi and some plants in its habitats. The aim of this study is to find inorganic and molecular markers that allow to characterize the wild A. ponderosa strains collected from different geographical locations in the Iberian Peninsula. Molecular approach using the microsatellite primer M13-PCR allowed to distinguish the mushrooms at specie level and to differentiate the A. ponderosa strains according to their location. Trace metals concentrations are considerably lower, acceptable to human consumption at nutritional and low toxic levels. Data mining tools were used in order to correlate inorganic and molecular results. A. ponderosa strains showed different inorganic composition according to their habitat. It was developed a segmentation model based on the molecular analysis, which allow relating the clusters obtained with the geographical site of sampling. There were also developed explanatory models of the segmentation, using decision trees, by following two different strategies. One of them based on the bands of DNA and, the other one, based on the mineral composition. The results show that it may be possible to relate the molecular and inorganic data. The present findings are wide potential application and both health and economical benefits arise from this study

Molecular Biomarkers to characterize Amanita ponderosa mushrooms

Amanita ponderosa strains are wild mushroom, edible, with a high exportation potential. This specie grows spontaneously in some microclimates in Iberian Peninsula, due to its Mediterranean characteristics, namely in Alentejo and Andaluzia. Due to the great diversity of wild mushrooms, it is essential be able to differentiate and identify the several edible mushrooms species. RAPD markers have been used as a valuable tool to distinguish different genotypes in edible mushrooms; however, it’s a new approach, for Amanita ponderosa strains. In the present study six Amanita ponderosa strains were compared with others Basidiomycetes (Pleurotus ostreatus, Lactarius deliciosus and Coriolus versicolor) and one Ascomycete strain (Tuber sp.) in order to establish different genetic fingerprintings profiles between strains. Molecular profiles were analyzed by RAPD-PCR using eight micosatelites primers and by MSP-PCR using the M13. Results showed that different patterns were generated for each nine strains tested. RAPD analysis enabled to differentiate at species and strain level, however, the degree of discrimination by means of RAPD-PCR depends highly on the primers used. The MSP-PCR is a fast method to amplified DNA polymorphic sequences, with high reproducibility and similarity for the same specie that allow to characterise the genetic profile of the edible mushrooms Tuber sp., Lactarius deliciosus, Pleurotus ostreatus and Amanita ponderosa. Moreover, constitute a valuable tool to distinguish the different genotypes of Amanita ponderosa strains, allowing to identify at specie level and to differentiate A. ponderosa strains from each origin sites

AVALIAÇÃO TOXICOLÓGICA E EFEITO HEPATOPROTECTOR DE COMPLEXOS PROTEÍNA-POLISSACÁRIDO PRODUZIDOS POR CULTURAS DE TRAMETES VERSICOLOR

As propriedades medicinais de vários cogumelos são amplamente conhecidas, no entanto, apenas nas últimas décadas, foi possível isolar e caracterizar alguns metabolitos biologicamente activos. Os efeitos terapêuticos de alguns fungos, tais como o Trametes versicolor, são maioritariamente atribuídos ao seu conteúdo em polissacáridos. O objectivo deste trabalho é estudar as propriedades hepatoprotectoras dos complexos proteína-polissacárido, produzidos por culturas líquidas de Trametes versicolor, utilizando ratos com intoxicação aguda pelo etanol, e comparar com uma droga padrão (silimarina)