INHIBITION OF CARSINOGENESIS BY SEED AND SOYBEAN MEAL EXTRACT IN COLON OF MICE: APOPTOSIS AND DYSPLASIA

Objective: Colon cancer is a major public health problem. Soybean has demonstrated chemopreventive and anticancer. Here, we have investigatedthe effect of a standardized seed and soybean meal extract (SE) with content of lunasin, here named grobogan extract (GE) and SE. They are botanicaldrug substance in experimental models of colon cancer in vivo.Methods: The effect of GE and SE was examined on the preneoplastic lesions (aberrant crypt foci), polyps and tumors induced by the carcinogenicagent azoxymethane (10 mg/kg) and dextran sodium sulfate 2% as well as in a xenograft model of colon cancer in mice.Results: GE and SE increased apoptosis (p=0.001). GE (150 mg/kg) has the highest impact level of apoptosis (p=0.009). GE and SE decreased dysplasia(p=0.024). GE (200 mg/kg) has the highest impact level of dysplasia (p=0.002), and SE (200 mg/kg) has the second impact level of dysplasia (p=0.003).Conclusions: GE and SE inhibition of colon carcinogenesis with increased level of apoptosis and decrease level of dysplasia.Keywords:Soybean, Lunasin, Colon cancer, Azoxymethane, Dextran sodium sulfate, Apoptosis, Dysplasia

Programa virtual EDMODO en los niveles de comprensión de textos en los estudiantes de secundaria en el área de Inglés, Trujillo - 2017

La presente investigación cuya finalidad es demostrar la influencia del Programa Virtual Edmodo en los niveles de comprensión de textos en los estudiantes de secundaria en el área de inglés. Trujillo, 2017, asume retos significativos puesto que hay que mejorar los niveles. La investigación es de tipo experimental con diseño cuasi experimental con grupo al que no se aplicó programa alguno, conformado por 50 estudiantes y otro grupo de 50 participantes con los que se desarrolló el programa Edmodo, seleccionados a través de muestreo no probabilístico por conveniencia. Se administró un test para medir los niveles de comprensión de textos en el área de inglés. Los resultados del pre test indican que un gran porcentaje de los estudiantes del grupo control (48%) y del grupo experimental (74%) se encuentran en inicio en cuanto al manejo de la interpretación de textos. Al grupo experimental se aplicó el Programa Virtual Edmodo en 12 sesiones. Los resultados del post test muestran que el mayor porcentaje de los estudiantes del grupo control se ubican en inicio (66%) y el grupo experimental se ubica en logrado 80% respectivamente. Al realizar la prueba de hipótesis respectiva, se determinó diferencias significativas en las pruebas de pre y post test del grupo experimental, así como en las pruebas de post test entre los grupos experimental y de control (p<0,05), lo que indica la eficacia del programa aplicado. En conclusión el Programa virtual Edmodo influye significativamente en los niveles de comprensión de textos de los estudiantes del cuarto grado de secundaria en el área de inglés, de la Institución Educativa N° 80822 “Santa María de La Esperanza”. Trujillo

Stability control for breath analysis using GC-MS

Gas chromatography mass spectrometry (GC-MS) instruments provide researchers and clinicians with a vast amount of information on sample composition, thus these instruments are seen as gold standard in breath analysis research. However, there are many factors that can confound the data measured by GC-MS instruments. These factors will make interpretation of GC-MS data unreliable for breath analysis research. We present in this paper detailed studies of two of these factors: instrument variation over time and chemical degradation of known biomarkers during storage in sorbent tubes. We found that a single quadrupole MS showed larger variability in measurements than a quadrupole time-of-flight MS when the same mixture of chemical standards was analysed for a period of up to 8 weeks. We recommend procedures of normalising the data. Moreover, the stability studies of breath biomarkers like thioethers, previously found indicative of malaria, showed that there is a need to store the samples in sorbent tubes at low temperature, 6 °C, for no more than 20 days to avoid the total decay of the chemicals

Classifying chemical sensor data using GPU-accelerated bio-mimetic neuronal networks based on the insect olfactory system

No description supplie

Drosophila olfactory receptors as classifiers for volatiles from disparate real world applications

Olfactory receptors evolved to provide animals with ecologically and behaviourally relevant information. The resulting extreme sensitivity and discrimination has proven useful to humans, who have therefore co-opted some animals' sense of smell. One aim of machine olfaction research is to replace the use of animal noses and one avenue of such research aims to incorporate olfactory receptors into artificial noses. Here, we investigate how well the olfactory receptors of the fruit fly, Drosophila melanogaster, perform in classifying volatile odourants that they would not normally encounter. We collected a large number of in vivo recordings from individual Drosophila olfactory receptor neurons in response to an ecologically relevant set of 36 chemicals related to wine ('wine set') and an ecologically irrelevant set of 35 chemicals related to chemical hazards ('industrial set'), each chemical at a single concentration. Resampled response sets were used to classify the chemicals against all others within each set, using a standard linear support vector machine classifier and a wrapper approach. Drosophila receptors appear highly capable of distinguishing chemicals that they have not evolved to process. In contrast to previous work with metal oxide sensors, Drosophila receptors achieved the best recognition accuracy if the outputs of all 20 receptor types were used

El whatsApp y su relación con la comprensión de textos en inglés en los estudiantes del quinto grado de secundaria de la institución educativa Agropecuario Yanque provincia de Caylloma, Arequipa - 2020

El estudio tuvo como propósito determinar la relación entre el uso del whatsapp y la comprensión de textos en inglés en los estudiantes del quinto grado de secundaria de la institución educativa Agropecuario Yanque. provincia de Caylloma, Arequipa - 2020. La muestra fue de tipo no probabilístico, estuvo conformada por 30 estudiantes dividido en una sección de quinto grado de secundaria. El tipo de estudio es correlacional y el diseño no experimental. Se aplicó el instrumento de cuestionario cerrado Likert para la variable 1 y prueba escrita para la variable 2. Por validación por expertos y confiabilidad por consistencia interna, alpha de Cronbach. El estudio concluye en que el coeficiente de correlación de Rho de Spearman fue de 0.734 que nos indica el grado de relación entre nuestras dos variables, descriptivamente hablando, indica una correlación positiva media entre las variables uso del whatsapp y la comprensión de textos en inglés

Optimal feature selection for classifying a large set of chemicals using metal oxide sensors

Using linear support vector machines, we investigated the feature selection problem for the application of all-against-all classification of a set of 20 chemicals using two types of sensors, classical doped tin oxide and zeolite-coated chromium titanium oxide sensors. We defined a simple set of possible features, namely the identity of the sensors and the sampling times and tested all possible combinations of such features in a wrapper approach. We confirmed that performance is improved, relative to previous results using this data set, by exhaustive comparison of these feature sets. Using the maximal number of different sensors and all available data points for each sensor does not necessarily yield the best results, even for the large number of classes in this problem. We contrast this analysis, using exhaustive screening of simple feature sets, with a number of more complex feature choices and find that subsampled sets of simple features can perform better. Analysis of potential predictors of classification performance revealed some relevance of clustering properties of the data and of correlations among sensor responses but failed to identify a single measure to predict classification success, reinforcing the relevance of the wrapper approach used. Comparison of the two sensor technologies showed that, in isolation, the doped tin oxide sensors performed better than the zeolite-coated chromium titanium oxide sensors but that mixed arrays, combining both technologies, performed best

THE ANTIBACTERIAL ACTIVITY OF FRACTIONS OF ETHYL ACETATE GARCINIA LATISSIMA MIQ. STEM BARK EXTRACTS AGAINST BACILLUS SUBTILIS AND PSEUDOMONAS AERUGINOSA

 Objective: This research focuses on the antibacterial activities of fractions of ethyl acetate Garcinia latissima Miq. extracts against Bacillus subtilis and Pseudomonas aeruginosa.Methods: For each bacteria, the values of the inhibitory zone diameter were determined using paper discs method, while the minimum inhibitory concentration (MIC) was determined by microdilution and antibacterial assay was determined by bioautography. Fractionation was carried out using gradient elution with silica gel column as stationary phase successively increasing the separation according to the polarity (using combination of eluents; n-hexane, ethyl acetate, and methanol).Results: To determine the diameter of the inhibitory zone for each fraction, the fractions were diluted with dimethyl sulfoxide until the concentration of each fraction was 20,000 ppm. The results showed that fraction B had no inhibitory zone against B. subtilis. The inhibitory zone diameters of fractions A, C, D, E, F, and G against B. subtilis were 7.600±0.000, 6.767±0.202, 7.950±0.477, 7.883±0.901, and 9.233±0.231 mm, respectively. Only Fraction G had an inhibition zone diameter of 7.200±0.173 mm against P. aeruginosa. The active fractions were tested by contact bioautography using silica gel (60 GF254) plate and hexane:chloroform (2:3) as mobile phase for Fractions A, C, D, E, and F and chloroform:ethyl acetate (4:1) as mobile phase for Fraction G. The thin layer chromatography plates were observed under the ultraviolet light at wavelengths of 254 and 366 nm, while the others plate (using in contact bioautography) placing on agar medium that had been inoculated with the bacteria, so the compounds could be diffuse to the medium. The active compound will appeared inhibitory zones in agar medium. The determination of the MIC values using microdilution with methylthiazol tetrazolium salt showed that fractions of the ethyl acetate extracts of G. latissima Miq. stem bark inhibited the growth of B. subtilis more actively than P. aeruginosa. The highest activity of the fractions against B. subtilis was shown by fraction G, which had a MIC value of 78.125 ppm, followed by fractions F (156.25 ppm), E (312.5 ppm), D (625 ppm), C (1250 ppm), B (2500 ppm), and A (5000 ppm). The highest activity of the fractions against P. aeruginosa was Fraction G (5000 ppm), while the MIC values of other fractions were &gt;5000 ppm.Conclusion: Further investigations should be conducted to obtain the new antibacterial compounds in fractions of ethyl acetate extract of G. latissima Miq. stem bark that effective to inhibit the growth of B. subtilis and P. aeruginosa

Diurnal variation in expired breath volatiles in malaria-infected and healthy volunteers

We previously showed that thioether levels in the exhaled breath volatiles of volunteers undergoing controlled human malaria infection (CHMI) with P. falciparum increase as infection progresses. In this study, we show that thioethers have diurnal cyclical increasing patterns and their levels are significantly higher in P. falciparum CHMI volunteers compared to those of healthy volunteers. The synchronized cycle and elevation of thioethers were not present in P. vivax-infection, therefore it is likely that the thioethers are associated with unique factors in the pathology of P. falciparum. Moreover, we found that time-of-day of breath collection is important to accurately predict (98%) P. falciparum-infection. Critically, this was achieved when the disease was asymptomatic and parasitemia was below the level detectable by microscopy. Although these findings are encouraging, they show limitations because of the limited and logistically difficult diagnostic window and its utility to P. falciparum malaria only. We looked for new biomarkers in the breath of P. vivaxCHMI volunteers and found that a set of terpenes increase significantly over the course of the malaria infection. The accuracy of predicting P. vivax using breath terpenes was up to 91%. Moreover, some of the terpenes were also found in the breath of P. falciparum CHMI volunteers (accuracy up to 93.5%). The results suggest that terpenes might represent better biomarkers than thioethers to predict malaria as they were not subject to malaria pathogens diurnal changes

Feature selection for chemical sensor arrays using mutual information

We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays