• Title/Summary/Keyword: Release profile

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A plasma circulating miRNAs profile predicts type 2 diabetes mellitus and prediabetes: from the CORDIOPREV study

  • Jimenez-Lucena, Rosa;Camargo, Antonio;Alcala-Diaz, Juan Francisco;Romero-Baldonado, Cristina;Luque, Raul Miguel;van Ommen, Ben;Delgado-Lista, Javier;Ordovas, Jose Maria;Perez-Martinez, Pablo;Rangel-Zuniga, Oriol Alberto;Lopez-Miranda, Jose
    • Experimental and Molecular Medicine
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    • v.50 no.12
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    • pp.13.1-13.12
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    • 2018
  • We aimed to explore whether changes in circulating levels of miRNAs according to type 2 diabetes mellitus (T2DM) or prediabetes status could be used as biomarkers to evaluate the risk of developing the disease. The study included 462 patients without T2DM at baseline from the CORDIOPREV trial. After a median follow-up of 60 months, 107 of the subjects developed T2DM, 30 developed prediabetes, 223 maintained prediabetes and 78 remained disease-free. Plasma levels of four miRNAs related to insulin signaling and beta-cell function were measured by RT-PCR. We analyzed the relationship between miRNAs levels and insulin signaling and release indexes at baseline and after the follow-up period. The risk of developing disease based on tertiles (T1-T2-T3) of baseline miRNAs levels was evaluated by COX analysis. Thus, we observed higher miR-150 and miR-30a-5p and lower miR-15a and miR-375 baseline levels in subjects with T2DM than in disease-free subjects. Patients with high miR-150 and miR-30a-5p baseline levels had lower disposition index (p = 0.047 and p = 0.007, respectively). The higher risk of disease was associated with high levels (T3) of miR-150 and miR-30a-5p ($HR_{T3-T1}=4.218$ and $HR_{T3-T1}=2.527$, respectively) and low levels (T1) of miR-15a and miR-375 ($HR_{T1-T3}=3.269$ and $HR_{T1-T3}=1.604$, respectively). In conclusion, our study showed that deregulated plasma levels of miR-150, miR-30a-5p, miR-15a, and miR-375 were observed years before the onset of T2DM and pre-DM and could be used to evaluate the risk of developing the disease, which may improve prediction and prevention among individuals at high risk for T2DM.

The Simulation of Pore Size Distribution from Unsaturated Hydraulic Conductivity Data Using the Hydraulic Functions (토양 수리학적 함수를 이용한 불포화 수리전도도로부터 공극크기분포의 모사)

  • Yoon, Young-Man;Kim, Jeong-Gyu;Shin, Kook-Sik
    • Korean Journal of Soil Science and Fertilizer
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    • v.43 no.4
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    • pp.407-414
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    • 2010
  • Until now, the pore size distribution, PSD, of soil profile has been calculated from soil moisture characteristic data by water release method or mercury porosimetry using the capillary rise equation. But the current methods are often difficult to use and time consuming. Thus, in this work, theoretical framework for an easy and fast technique was suggested to estimate the PSD from unsaturated hydraulic conductivity data in an undisturbed field soil profile. In this study, unsaturated hydraulic conductivity data were collected and simulated by the variation of soil parameters in the given boundary conditions (Brooks and Corey soil parameters, ${\alpha}_{BC}=1-5L^{-1}$, b = 1 - 10; van Genuchten soil parameters, ${\alpha}_{VG}=0.001-1.0L^{-1}$, m = 0.1 - 0.9). Then, $K_s$ (1.0 cm $h^{-1})$ was used as the fixed input parameter for the simulation of each models. The PSDs were estimated from the collected K(h) data by model simulation. In the simulation of Brooks-Corey parameter, the saturated hydraulic conductivity, $K_s$, played a role of scaling factor for unsaturated hydraulic conductivity, K(h) Changes of parameter b explained the shape of PSD curve of soil intimately, and a ${\alpha}_{BC}$ affected on the sensitivity of PSD curve. In the case of van Genuchten model, $K_s$ and ${\alpha}_{VG}$ played the role of scaling factor for a vertical axis and a horizontal axis, respectively. Parameter m described the shape of PSD curve and K(h) systematically. This study suggests that the new theoretical technique can be applied to the in situ prediction of PSD in undisturbed field soil.