Background: Adiponectin (ADIPOQ) is a hormone primarily synthesized by adipocytes and encoded by the ADIPOQ gene, which exerts anti-inflammatory, antiatheratogenic and insulin sensitizing functions. It has been shown that its plasma concentrations are decreased in individuals with metabolic syndrome (MS) and type 2 diabetes mellitus (DM2), which could be due to variations in the gene coding for this protein. The aim of this study was to detect the +45 T>G polymorphism of the ADIPOQ gene in subjects with DM2 and MS in Maracaibo municipality, Zulia state, Venezuela. Methods: A total of 90 subjects who attended the Center for Metabolic Endocrine Research "Dr. Félix Gómez" were enrolled for this study, 46 of which had MS-DM2 and 44 of which were healthy control individuals. Genomic DNA was extracted from blood samples and PCR-restriction fragment length polymorphism analysis was carried out for the promoter region of the ADIPOQ gene. Likewise, the +45 T> G polymorphism was identified and correlated with MS and DM2 in the studied population. Results: The most frequent allele in both groups was the T allele, and the predominant genotype was homozygous T/T (79%). Genotypes with heterozygous T/G and G/G homozygous polymorphism were more frequent in the control group than in the MS-DM2 group. Regarding the individuals with T/G and G/G genotypes, statistically significant lower mean values were found for fasting glucose, total cholesterol, triacylglycerides, abdominal circumference, and for the medians of systolic and diastolic blood pressure. Odds ratio were calculated for the presence or absence of MS and DM2. Conclusions: The results suggested that the presence of the G allele exerts a protective effect on the carrier individuals, thus avoiding the appearance of the aforementioned metabolic alterations.
The multi-slice computerized tomography (MSCT) is a medical Background: imaging modality that has been used to determine the size and location of the stomach cancer. Additionally, MSCT is considered the best modality for the staging of gastric cancer. One way to assess the type 2 cancer of stomach is by detecting the pathological structure with an image segmentation approach. The tumor segmentation of MSCT gastric cancer images enables the diagnosis of the disease condition, for a given patient, without using an invasive method as surgical intervention.This approach consists of three stages. The initial stage, an image Methods: enhancement, consists of a method for correcting non homogeneities present in the background of MSCT images. Then, a segmentation stage using a clustering method allows to obtain the adenocarcinoma morphology. In the third stage, the pathology region is reconstructed and then visualized with a three-dimensional (3-D) computer graphics procedure based on marching cubes algorithm. In order to validate the segmentations, the Dice score is used as a metric function useful for comparing the segmentations obtained using the proposed method with respect to ground truth volumes traced by a clinician.A total of 8 datasets available for patients diagnosed, from the cancer Results: data collection of the project, Cancer Genome Atlas Stomach Adenocarcinoma (TCGASTAD) is considered in this research. The volume of the type 2 stomach tumor is estimated from the 3-D shape computationally segmented from the each dataset. These 3-D shapes are computationally reconstructed and then used to assess the morphopathology macroscopic features of this cancer.The segmentations obtained are useful for assessing Conclusions:qualitatively and quantitatively the stomach type 2 cancer. In addition, this type
Background: The multi–slice computerized tomography (MSCT) is a medical imaging modality that has been used to determine the size and location of the stomach cancer. Additionally, MSCT is considered the best modality for the staging of gastric cancer. One way to assess the type 2 cancer of stomach is by detecting the pathological structure with an image segmentation approach. The tumor segmentation of MSCT gastric cancer images enables the diagnosis of the disease condition, for a given patient, without using an invasive method as surgical intervention. Methods: This approach consists of three stages. The initial stage, an image enhancement, consists of a method for correcting non homogeneities present in the background of MSCT images. Then, a segmentation stage using a clustering method allows to obtain the adenocarcinoma morphology. In the third stage, the pathology region is reconstructed and then visualized with a three–dimensional (3–D) computer graphics procedure based on marching cubes algorithm. In order to validate the segmentations, the Dice score is used as a metric function useful for comparing the segmentations obtained using the proposed method with respect to ground truth volumes traced by a clinician. Results: A total of 8 datasets available for patients diagnosed, from the cancer data collection of the project, Cancer Genome Atlas Stomach Adenocarcinoma (TCGASTAD) is considered in this research. The volume of the type 2 stomach tumor is estimated from the 3–D shape computationally segmented from the each dataset. These 3–D shapes are computationally reconstructed and then used to assess the morphopathology macroscopic features of this cancer. Conclusions: The segmentations obtained are useful for assessing qualitatively and quantitatively the stomach type 2 cancer. In addition, this type of segmentation allows the development of computational models that allow the planning of virtual surgical processes related to type 2 cancer.
La Encuesta Nacional de Examen de Salud y Nutrición es un programa de estudios diseñado para evaluar el estado de salud y nutrición de los adultos y de los niños en Estados Unidos. Esta encuesta es un importante estudio del Centro Nacional de Estadísticas de Salud. Realizar investigaciones sobre la salud de los adolescentes y la salud de personas de mayor edad que permita producir estadísticas confiables para estos grupos es un tema relevante para Colombia y el mundo. Tomar este estudio como referencia y replicarlo después en la población de Colombia se considera relevante como área de investigación. El objetivo de esta investigación es desarrollar un software interactivo para el proceso de integración automática de bases de datos médicas mostradas por NHANES, de manera que permita de forma sencilla y rápida la descarga de datas y la realización de fusiones automáticas entre ellas. La validación del se realiza con base a la fusión de 2 datas correspondientes los años 2016 y 2017 de forma manual comparándola con la realizada por el software. La metodología para el desarrollo es una adaptación de la metodología Programación Extrema (XP) por ser esta ágil y flexible, en ella destacan las fases de interacción constante entre el usuario y el equipo de desarrollo, planificación flexible abierta y rápida respuesta a cambios. El lenguaje de desarrollo es PHYTON por ser software libre y haberse convertido en uno de los movimientos tecnológicos de mayor auge en el siglo XXI.
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