Differentiation between Ripening Stages of Iberian Dry-Cured Ham According to the Free Amino Acids Content.

In this paper, the differentiation of three ripening stages, postsalting, drying, and cellar, of Iberian dry-cured ham has been carried out according to their free amino acids contents. Eighteen L-amino acids, alanine, 2-aminobutanoic acid, aspartic acid, cysteine, glutamine, glycine, histidine, hydroxyproline, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, threonine, tyrosine, and valine have been determined by gas chromatography with derivatization with N,O-bis(trimethylsilyl)-trifluoroacetamide. Gas chromatography-mass spectrometry was used to confirm the presence of the eighteen amino acids in the ham samples, and gas chromatography using a DB-17HT column and flame ionization detector was used for quantitative determination. Extraction with a mixture methanol-acetonitrile has been carried out, achieving recoveries in the range 52-164%. Methimazole was used as internal standard. Limits of detection ranged between 7.0 and 611.7 mg·kg-1. Free amino acids have been used as chemical descriptors to differentiate between the ripening stages. Principal component analysis and linear discriminant analysis have been used as chemometric techniques, achieving complete differentiation between the ripening stages. Alanine, tyrosine, glutamine, proline, 2-aminobutanoic acid, cysteine, and valine were the most differentiating amino acids.

Geographical characterization of Spanish PDO paprika by multivariate analysis of multielemental content.

A multielemental analytical method has been proposed to determine the contents of Al, B, Ca, Cu, Fe, K, Mg, Mn, Na, Ni, P, Pb, Sr and Zn in paprika samples from the two Protected Designations of Origin recognized in Spain, such as Murcia and La Vera (Extremadura). The samples are mineralized by acid wet digestion using a mixture of perchloric and nitric acids and analyzed by means of inductively coupled plasma atomic emission spectroscopy. The method performance has been checked studying the absence of matrix effect, trueness, precision, linearity, limit of detection and limit of quantification. The proposed method has been applied to analyze samples of sweet, hot and hot/sweet paprika from the considered production areas. Differences between paprika samples from Murcia and Extremadura were found and pattern recognition methods, such as linear discriminant analysis, linear support vector machines, soft independent modeling of class analogy and multilayer perceptrons artificial neural networks, has been used to obtain classification models. Sweet and hot/sweet paprika types were differentiated by means of linear models and hot paprika was differentiated by using artificial neural networks. A model based on artificial neural networks is proposed to differentiate the geographical origin of paprika, with independence of the type, leading to an overall classification performance of 99%.

Differentiation of tea varieties using UV-Vis spectra and pattern recognition techniques.

Tea, one of the most consumed beverages all over the world, is of great importance in the economies of a number of countries. Several methods have been developed to classify tea varieties or origins based in pattern recognition techniques applied to chemical data, such as metal profile, amino acids, catechins and volatile compounds. Some of these analytical methods become tedious and expensive to be applied in routine works. The use of UV-Vis spectral data as discriminant variables, highly influenced by the chemical composition, can be an alternative to these methods. UV-Vis spectra of methanol-water extracts of tea have been obtained in the interval 250-800 nm. Absorbances have been used as input variables. Principal component analysis was used to reduce the number of variables and several pattern recognition methods, such as linear discriminant analysis, support vector machines and artificial neural networks, have been applied in order to differentiate the most common tea varieties. A successful classification model was built by combining principal component analysis and multilayer perceptron artificial neural networks, allowing the differentiation between tea varieties. This rapid and simple methodology can be applied to solve classification problems in food industry saving economic resources.

Characterisation of tequila according to their major volatile composition using multilayer perceptron neural networks.

Differentiation of silver, gold, aged and extra-aged tequila using 1-propanol, ethyl acetate, 2-methyl-1-propanol, 3-methyl-1-butanol and 2-methyl-1-butanol and furan derivatives like 5-(hydroxymethyl)-2-furaldehyde and 2-furaldehyde has been carried out. The content of 1-propanol, ethyl acetate, 2-methyl-1-propanol, 3-methyl-1-butanol and 2-methyl-1-butanol was determined by means of head space solid phase microextraction gas chromatography mass-spectrometry. 5-(Hydroxymethyl)-2-furaldehyde and 2-furaldehyde were determined by high performance liquid chromatography with diode array detection. Kruskal-Wallis test was used to highlight significant differences between types of tequila. Principal component analysis was applied as visualisation technique. Linear discriminant analysis and multilayer perceptron artificial neural networks were used to construct classification models. The best classification performance was obtained when multilayer perceptron model was applied.

Classification of Spanish DO white wines according to their elemental profile by means of support vector machines.

Spanish white wines from four production areas protected by Appellation Control laws have been analysed by inductively coupled plasma optical emission spectrometry to determine the contents of aluminium, barium, boron, calcium, chromium, copper, iron, magnesium, manganese, nickel, phosphorous, potassium, silicon, sodium, strontium, sulphur and zinc. These elements were used as chemical descriptors in order to differentiate wines from different brands certified of origin. Kruskal-Wallis test was applied to highlight significant differences between the four considered classes and pattern recognition methods were applied to construct classification models. In this way, principal component analysis was used to visualise data trends and backward stepwise linear discriminant analysis was applied in order to reduce the number of input variables. The concentrations of chromium, manganese, silicon, sodium and strontium were used to construct a support vector machine classification model, obtaining a 100% of classification performance.

El mareo como síntoma de los tumores encefálicos. Estudio de 60 casos / Dizziness as a symptom of encephalic tumors. A review of 60 cases

Se procedió a estudiar la incidencia de manifestaciones de mareos en una muestra de 60 casos de pacientes de ambos sexos, con edades entre 6 y 76 años, con tumores encefálicos de diversa localización e histopatología. La ubicación de los tumores se estableció por métodos radiológicos y se confirmaron tras la intervención quirúrgica. Se estudió especialmente la relación del síntoma mareo con la ubicación de los tumores encefálicos. Comprobamos que el mareo aparece asociado especialmente a los tumores de fosa posterior. En los casos de tumores localizados en hemisferios cerebrales el mareo se manifiesta con menor incidencia. Estos casos se ubican en áreas próximas a los centros vestibulares corticales

Cirugía de angiofibroma nasofaringeo juvenil / Surgery of of juvenile nasopharyngeal angiofibroma

En el presente trabajo, analizamos los distintos tratamientos quirúrgicos que se llevaron a cabo en 6 casos de angiofibroma nasofaríngeo juvenil (ANJ). Las vías quirúrgicas que se utilizaron fueron la nasal paralateral, la transpalatina, de Rouge-Denker, y la vía natural oral. Analizamos el criterio actual sobre la preparación prequirúrgica, la utilización de las distintas técnicas actuales, haciendo mención especial del "degloving". Se hace referencia a la relación entre los diferentes estadios del tumor: tamaño y localización, y consecuentemente las distintas técnicas a emplear