Diabetes mellitus increased integrins gene expression in rat endometrium at the time of embryo implantation

Background: Diabetes mellitus deeply changes the genes expression of integrin (Itg) subunits in several cells and tissues such as monocytes, arterial endothelium, kidney glomerular cells, retina. Furthermore, hyperglycemia could impress and reduce the rate of successful assisted as well as non-assisted pregnancy. Endometrium undergoes thorough changes in normal menstrual cycle and the question is: What happens in the endometrium under diabetic condition? Objective: The aim of the current study was to investigate the endometrial gene expression of α3, α4, αv, Itg β1 and β3 subunits in diabetic rat models at the time of embryo implantation. Materials and Methods: Twenty-eight rats were randomly divided into 4 groups: control group, diabetic group, pioglitazone-treated group, and metformin-treated group. Real-time PCR was performed to determine changes in the expression of Itg α3, α4, αv, β1, and β3 genes in rat’s endometrium. Results: The expression of all Itg subunits increased significantly in diabetic rats’ endometrium compared with control group. Treatment with pioglitazone significantly reduced the level of Itg subunits gene expression compared with diabetic rats. While metformin had a different effect on α3 and α4 and elevated these two subunits gene expression. Conclusion: Diabetes mellitus significantly increased the expression of studied Itg subunits, therefore untreated diabetes could be potentially assumed as one of the preliminary elements in embryo implantation failure

Design and Implementation of a Real-Time Fingering Detection System for Contrabass Using Musical Rules

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Датчики интегральной поглощенной дозы ионизирующего излучения на основе МОП-транзисторов

Определены требования к конструкции технологии изготовления р- и n-канальных МОП-транзисторов с толстым слоем оксида, предназначенных для применения в качестве интегральных дозиметров поглощенной дозы ионизирующего излучения.Визначено вимоги до конструкції та технології виготов лення р-канальних та n-канальних МОП-транзисторів із тоѕстим шаром оксиду, призначених для вжитку як інтегральні дозиметри поглинутої дози іонізуючого випромінення. Розроблено технологію створення радіаційно-чутливих МОП-транзисторів з товстим шаром оксиду в р-канальному и в n-канальному вариантах.The requirements to technology and design of p-channel and n-channel MOS transistors with a thick oxide layer designed for use in the capacity of integral dosimeters of absorbed dose of ionizing radiation are defined. The technology of radiation-sensitive MOS transistors with a thick oxide in the p-channel and n-channel version is created

The mediating effect of immune markers on the association between ambient air pollution and adult-onset asthma

We aim to investigate to what extent a set of immune markers mediate the association between air pollution and adult-onset asthma. We considered long-term exposure to multiple air pollution markers and a panel of 13 immune markers in peripheral blood samples collected from 140 adult cases and 199 controls using a nested-case control design. We tested associations between air pollutants and immune markers and adult-onset asthma using mixed-effects (logistic) regression models, adjusted for confounding variables. In order to evaluate a possible mediating effect of the full set of immune markers, we modelled the relationship between asthma and air pollution with a partial least square path model. We observed a strong positive association of IL-1RA [OR 1.37; 95% CI (1.09, 1.73)] with adult-onset asthma. Univariate models did not yield any association between air pollution and immune markers. However, mediation analyses indicated that 15% of the effect of air pollution on risk of adult-onset asthma was mediated through the immune system when considering all immune markers as a latent variable (path coefficient (β) = 0.09; 95% CI: (-0.02, 0.20)). This effect appeared to be stronger for allergic asthma (22%; β = 0.12; 95% CI: (-0.03, 0.27)) and overweight subjects (27%; β = 0.19; 95% CI: (-0.004, 0.38)). Our results provides supportive evidence for a mediating effect of the immune system in the association between air pollution and adult-onset asthma

Omics biomarkers to study the internal exposome: the case of air pollution

The majority of chronic diseases are likely to be the result of the combination of environmental exposures and human genetics. The exposome concept was proposed to increase our knowledge regarding the potential role of environment in the causation of disease. The exposome is a paradigm involving the study of all environmental exposures (e.g., air pollutants, chemical contaminants, diet or life style factors) and associated biological responses from conception until death. Once environmental exposures enter the human body they and their biological consequences become part of the internal exposome, which can be measured by OMICS technologies. Investigating perturbations in the internal exposome can provide information on direct measures of exposure or on physiological perturbations that are indicative of a certain exposure. Studying the internal exposome can provide biological underpinnings for empirically observed exposure-disease associations. In this thesis, we focused on air pollution, a high priority environmental pollutant responsible for 7 million premature deaths worldwide each year. Air pollution is recognized as a human carcinogen associated with lung cancer. It is also a major risk factor for other acute and chronic diseases including cardiovascular disease and chronic respiratory diseases, such as asthma and chronic obstructive pulmonary disease. The overall aim of this thesis is to study three OMICS platforms (proteomics, transcriptomics, and DNA-methylomics) in relation to exposure to air pollution in order to have a better understanding of the biological processes that link air pollution exposure to health effects. When successful such analyses might contribute to generating insights on air pollution induced health effects, identifying air pollutant specific biological pathways, and detecting biomarkers of early disease

Omics biomarkers to study the internal exposome: the case of air pollution

The majority of chronic diseases are likely to be the result of the combination of environmental exposures and human genetics. The exposome concept was proposed to increase our knowledge regarding the potential role of environment in the causation of disease. The exposome is a paradigm involving the study of all environmental exposures (e.g., air pollutants, chemical contaminants, diet or life style factors) and associated biological responses from conception until death. Once environmental exposures enter the human body they and their biological consequences become part of the internal exposome, which can be measured by OMICS technologies. Investigating perturbations in the internal exposome can provide information on direct measures of exposure or on physiological perturbations that are indicative of a certain exposure. Studying the internal exposome can provide biological underpinnings for empirically observed exposure-disease associations. In this thesis, we focused on air pollution, a high priority environmental pollutant responsible for 7 million premature deaths worldwide each year. Air pollution is recognized as a human carcinogen associated with lung cancer. It is also a major risk factor for other acute and chronic diseases including cardiovascular disease and chronic respiratory diseases, such as asthma and chronic obstructive pulmonary disease. The overall aim of this thesis is to study three OMICS platforms (proteomics, transcriptomics, and DNA-methylomics) in relation to exposure to air pollution in order to have a better understanding of the biological processes that link air pollution exposure to health effects. When successful such analyses might contribute to generating insights on air pollution induced health effects, identifying air pollutant specific biological pathways, and detecting biomarkers of early disease

Persistence of endothelial cell damage late after Kawasaki disease in patients without coronary artery complications

Background: Recent studies proposed an increased risk of atherosclerosis in patients with a history of Kawasaki disease. This study aimed to investigate the persistence of vascular injury after an acute phase of the Kawasaki disease. Materials and Methods: We determined the number of circulating endothelial cells (CEC) in the peripheral blood of 13 patients with a history of Kawasaki disease within four to ten years, in comparison with 13 healthy relative controls. The CECs were counted as CD146+/CD34 + cells by the standard flow cytometry technique, and the independent t-test was employed to compare the mean number of CECs in the two groups. Results: The mean number of CECs was significantly higher in patients than in controls (12 ± 3.03 vs. 2.38 ± 0.87, respectively, P < 0.001). Conclusion: This study elucidates the persistence of vascular injury late after Kawasaki disease. This finding suggests that prolonged administration of vascular anti-inflammatory agents might be beneficial for preventing atherosclerosis in the subsequent years, in these patients

GWAS with longitudinal phenotypes : performance of approximate procedures

Analysis of genome-wide association studies with longitudinal data using standard procedures, such as linear mixed model (LMM) fitting, leads to discouragingly long computation times. There is a need to speed up the computations significantly. In our previous work (Sikorska et al: Fast linear mixed model computations for genome-wide association studies with longitudinal data. Stat Med 2012; 32.1: 165-180), we proposed the conditional two-step (CTS) approach as a fast method providing an approximation to the P-value for the longitudinal single-nucleotide polymorphism (SNP) effect. In the first step a reduced conditional LMM is fit, omitting all the SNP terms. In the second step, the estimated random slopes are regressed on SNPs. The CTS has been applied to the bone mineral density data from the Rotterdam Study and proved to work very well even in unbalanced situations. In another article (Sikorska et al: GWAS on your notebook: fast semi-parallel linear and logistic regression for genome-wide association studies. BMC Bioinformatics 2013; 14: 166), we suggested semi-parallel computations, greatly speeding up fitting many linear regressions. Combining CTS with fast linear regression reduces the computation time from several weeks to a few minutes on a single computer. Here, we explore further the properties of the CTS both analytically and by simulations. We investigate the performance of our proposal in comparison with a related but different approach, the two-step procedure. It is analytically shown that for the balanced case, under mild assumptions, the P-value provided by the CTS is the same as from the LMM. For unbalanced data and in realistic situations, simulations show that the CTS method does not inflate the type I error rate and implies only a minimal loss of power.European Journal of Human Genetics advance online publication, 25 February 2015; doi:10.1038/ejhg.2015.1

GWAS with longitudinal phenotypes: performance of approximate procedures

Analysis of genome-wide association studies with longitudinal data using standard procedures, such as linear mixed model (LMM) fitting, leads to discouragingly long computation times. There is a need to speed up the computations significantly. In our previous work (Sikorska et al: Fast linear mixed model computations for genome-wide association studies with longitudinal data. Stat Med 2012; 32.1: 165-180), we proposed the conditional two-step (CTS) approach as a fast method providing an approximation to the P-value for the longitudinal single-nucleotide polymorphism (SNP) effect. In the first step a reduced conditional LMM is fit, omitting all the SNP terms. In the second step, the estimated random slopes are regressed on SNPs. The CTS has been applied to the bone mineral density data from the Rotterdam Study and proved to work very well even in unbalanced situations. In another article (Sikorska et al: GWAS on your notebook: fast semi-parallel linear and logistic regression for genome-wide association studies. BMC Bioinformatics 2013; 14: 166), we suggested semi-parallel computations, greatly speeding up fitting many linear regressions. Combining CTS with fast linear regression reduces the computation time from several weeks to a few minutes on a single computer. Here, we explore further the properties of the CTS both analytically and by simulations. We investigate the performance of our proposal in comparison with a related but different approach, the two-step procedure. It is analytically shown that for the balanced case, under mild assumptions, the P-value provided by the CTS is the same as from the LMM. For unbalanced data and in realistic situations, simulations show that the CTS method does not inflate the type I error rate and implies only a minimal loss of power.European Journal of Human Genetics advance online publication, 25 February 2015; doi:10.1038/ejhg.2015.1