RESUMEN

OBJECTIVE: Genome studies have shown that the genes encoding paraoxonase 1 (PON1) and PON2 are associated with glucose metabolism. The goal of this study was to simultaneously evaluate the association between functional variants in PON1 and PON2 genes and susceptibility for type 2 diabetes (T2D) and determine whether they can affect glycemic control. METHODS: We performed a case-control study with 145 newly diagnosed patients with T2D and 148 controls. The common variants including PON1-Q192R, PON1-L55M and PON2-S311C were genotyped by PCR-based RFLP. A mismatch-PCR/RFLP was applied for genotyping the PON2-A148G variant. RESULTS: The variant PON1-Q192R in males (OR = 2.55, 95%CI 1.16-5.69, p = 0.023) and PON2-A148G in females (OR = 1.56, 95%CI 1.00-2.44, p = 0.059) were associated with T2D. Compared with the LL genotypes of PON1-L55M, HbA1c levels were significantly lower in the LM genotypes (p = 0.01) and MM genotypes (p = 0.032) in patients. Multiple linear regression analyses showed that among the study variants only the PON1-L55M variant as an independent variable significantly associated with glycemic control. This variant significantly influenced glycemic control in patients with poor glycemic control so that it was better with the following order: LL < LM < MM. Based on gamma correlation, there was a significant inverse association between the number of M alleles of the PON1-L55M and HbA1c levels (r = -0.261, p = 0.001). CONCLUSIONS: Sex should be considered a confounding variable in association studies on the variants PON1-Q192R and PON2-A148G in T2D. Patients sharing the 55 M allele were prone to having good glycemic control. Our findings provide genetic evidence that the PON1-L55M variant may be a factor contributing to glycemic control.

Asunto(s)

Arildialquilfosfatasa/genética , Glucemia/genética , Diabetes Mellitus Tipo 2/genética , Femenino , Perfilación de la Expresión Génica , Código Genético/genética , Predisposición Genética a la Enfermedad/genética , Variación Genética/genética , Humanos , Masculino , Persona de Mediana Edad

RESUMEN

Shape and movement features of sperms are important parameters for infertility study and treatment. In this article, a new method is introduced for characterization sperms in microscopic videos. In this method, first a hypothesis framework is defined to distinguish sperms from other particles in captured video. Then decision about each hypothesis is done in following steps: Selecting some primary regions as candidates for sperms by watershed-based segmentation, pruning of some false candidates during successive frames using graph theory concept and finally confirming correct sperms by using their movement trajectories. Performance of the proposed method is evaluated on real captured images belongs to semen with high density of sperms. The obtained results show the proposed method may detect 97% of sperms in presence of 5% false detections and track 91% of moving sperms. Furthermore, it can be shown that better characterization of sperms in proposed algorithm doesn't lead to extracting more false sperms compared to some present approaches.