43 resultados para Epilepsia-Diagnosis-Tratamiento
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Background: Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. Methods: A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60- mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. Results: After an exhaustive process of pre-processing to ensure data quality–lost values imputation, probes quality, data smoothing and intraclass variability filtering–the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. Conclusions: We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955).
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[EUS] Matematikaren irakaskuntzaren helburuenetako bat hezkuntza maila guztietan ikasleen ahalmen intelektualen garapena da. Ahalmen espazialaren trataera eskolan urria izan da, bereziki zenbakizko ahalmenak edota arrazonamenduzko ahalmenak izan duten trataerarekin konparatzen badugu. Hezkuntza Matematikoan egindako berrikusketek ahalmen espazialaren azterketaren garrantzia azpimarratzen dute nahiz eta erreferentzi marko baten ezak sakabanatzen eta zailtzen dituen emaitzen lorpena, behin betikoak izateko erreplikagarriak izan behar dutela jakinik. Ondoren proposatzen den ikerketa-lerroak ahalmen espaziala alderdi hirukoitz batetik abiaturik aztertu nahi du: egitura, garapena eta hobetze-proposamenak kontutan harturik. Hiru arlo horietan proposaturiko ereduek bermatuko dute diagnostiko zuzen bat, ikasleen ahalmen espaziala hobetuko duena.
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617 p.: il.col., graf.
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Poster presentado al XXII Congreso Nacional de Microbiología celebrado en Sevilla los días 17 -20 septiembre de 2007
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Presentación de la la comunicación a la VII Reunión Microbiología del Medio Acuático celebradad en Bilbao del 25 al 27 de septiembre de 2008
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Presentación de la la comunicación a la VIII Reunión Microbiología del Medio Acuático celebrada en Vigo del 14 al 16 de septiembre de 2010
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Presentación de la la comunicación al IX Congreso de Microbiología del Medio Acuático celebrado en Barcelona del 13 al 15 de septiembre de 2012.
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Santamaría, José Miguel; Pajares, Eterio; Olsen, Vickie; Merino, Raquel; Eguíluz, Federico (eds.)
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Eterio Pajares, Raquel Merino y José Miguel Santamaría (eds.)
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Raquel Merino Álvarez, José Miguel Santamaría, Eterio Pajares (eds.)
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197 p. (Bibliogr. 189-197)
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Background: Primary distal renal tubular acidosis (dRTA) caused by mutations in the genes that codify for the H+ -ATPase pump subunits is a heterogeneous disease with a poor phenotype-genotype correlation. Up to now, large cohorts of dRTA Tunisian patients have not been analyzed, and molecular defects may differ from those described in other ethnicities. We aim to identify molecular defects present in the ATP6V1B1, ATP6V0A4 and SLC4A1 genes in a Tunisian cohort, according to the following algorithm: first, ATP6V1B1 gene analysis in dRTA patients with sensorineural hearing loss (SNHL) or unknown hearing status. Afterwards, ATP6V0A4 gene study in dRTA patients with normal hearing, and in those without any structural mutation in the ATP6V1B1 gene despite presenting SNHL. Finally, analysis of the SLC4A1 gene in those patients with a negative result for the previous studies. Methods: 25 children (19 boys) with dRTA from 20 families of Tunisian origin were studied. DNAs were extracted by the standard phenol/chloroform method. Molecular analysis was performed by PCR amplification and direct sequencing. Results: In the index cases, ATP6V1B1 gene screening resulted in a mutation detection rate of 81.25%, which increased up to 95% after ATP6V0A4 gene analysis. Three ATP6V1B1 mutations were observed: one frameshift mutation (c.1155dupC; p.Ile386fs), in exon 12; a G to C single nucleotide substitution, on the acceptor splicing site (c.175-1G > C; p.?) in intron 2, and one novel missense mutation (c. 1102G > A; p. Glu368Lys), in exon 11. We also report four mutations in the ATP6V0A4 gene: one single nucleotide deletion in exon 13 (c.1221delG; p. Met408Cysfs* 10); the nonsense c.16C > T; p.Arg6*, in exon 3; and the missense changes c.1739 T > C; p.Met580Thr, in exon 17 and c.2035G > T; p.Asp679Tyr, in exon 19. Conclusion: Molecular diagnosis of ATP6V1B1 and ATP6V0A4 genes was performed in a large Tunisian cohort with dRTA. We identified three different ATP6V1B1 and four different ATP6V0A4 mutations in 25 Tunisian children. One of them, c.1102G > A; p.Glu368Lys in the ATP6V1B1 gene, had not previously been described. Among deaf since childhood patients, 75% had the ATP6V1B1 gene c. 1155dupC mutation in homozygosis. Based on the results, we propose a new diagnostic strategy to facilitate the genetic testing in North Africans with dRTA and SNHL.
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The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.
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8 p.
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243 p. : il.