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Francisco J Gómez-Pérez Carlos A Aguilar-Salinas Cuauhtémoc Vázquez-Chávez Guillermo Fangh?nel-Salmón José Gallegos-Martínez Rita A Gómez-Diaz Saul Salinas-Orozco Ismael J Chavira-López Leticia Sánchez-Reyes Evelyn M Torres-Acosta Ricardo Tamez Angelina López Luz E Guillén Gabriela Cesarman 《Metabolism: clinical and experimental》2002,51(1):44-51
The effects of troglitazone 400 or 600 mg/d on the glycemic control, very-low-density lipoprotein (VLDL), and high-density lipoprotein (HDL) subclass concentrations and plasminogen-activator inhibitor 1 (PAI-1) levels were assessed in patients with type 2 diabetes that had not been controlled with dietary treatment. This was a multicenter, open-label, parallel-groups study. It included a run-in 4-week diet period and a 24-week randomized treatment. Fifty one patients received 400 mg/d and 55 patients 600 mg. The mean HbA(1c) concentration at the end of the study was similar for both doses. Troglitazone, regardless of dose, significantly improved insulin sensitivity assessed by the homeostasis model (HOMA). PAI-1 levels were significantly decreased in both groups by 13%. Higher HDL cholesterol concentrations and lower triglycerides levels were observed at the end of treatment. Triglyceride contents were reduced only in the lighter VLDL1. The change in HDL cholesterol concentration resulted from a combination of increased HDL3 cholesterol and lower HDL2 cholesterol levels. No differences were found in the effects of both treatment groups on the evaluated parameters. Our data provide new information about the actions of the drug on the lipid profile. Troglitazone reduces triglyceride levels by lowering the triglycerides content of the VLDL1 particles and increases HDL cholesterol concentrations by increasing HDL3 cholesterol levels. 相似文献
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de Lima Silva Alvaro Henrique Bernardo Radulski Debora Rasec Pereira Gabriela Saidel Acco Alexandra Zanoveli Janaina Menezes 《Metabolic brain disease》2022,37(4):1095-1110
Metabolic Brain Disease - Anxiety Disorders and Posttraumatic Stress Disorders (PTSD) associated with type-1 diabetes mellitus (T1DM) are increasingly common comorbidities and the treatment is... 相似文献
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Tatjana Janzen Yuri Gaponenko Aliaksandr Mialdun Gabriela Guevara-Carrion Jadran Vrabec Valentina Shevtsova 《RSC advances》2018,8(18):10017
With laboratory and numerical work, we demonstrate that one of the main diffusion coefficients and the smaller eigenvalue of the Fick diffusion matrix are invariant to the number of methylene groups of the alcohol in ternary mixtures composed of an aromatic (benzene), a ketone (acetone) and one of three different alcohols (methanol, ethanol or 2-propanol). A critical analysis of the relationship between the kinetic and thermodynamic contributions to the diffusion coefficients allows us to explain this intriguing behaviour of this class of mixture. These findings are reflected by the diffusive behaviour of the according binary subsystems. Our approach provides a promising systematic framework for future investigations into the important and challenging problem of transport diffusion in multicomponent liquids.The Fick diffusion coefficient matrix of three ternary mixtures composed of an aromatic (benzene), a ketone (acetone) and one of three different alcohols (methanol, ethanol or 2-propanol) is investigated with laboratory and numerical work.Multicomponent diffusion plays a crucial role in various natural and industrial processes involving mass transfer.1–3 Liquids appearing in nature and technical applications are essentially multicomponent. However, only data on binary diffusion coefficients are relatively abundant because the diffusion behavior of ternary and higher mixtures is much more complex.4,5 Describing the isothermal–isobaric diffusion of a ternary mixture by Fick’s law requires four different diffusion coefficients that are composition dependent. The presence of cross diffusion coefficients aggravates the interpretation and data processing in experimental work, resulting in large uncertainties.6,7 Thus, efforts are being made to develop new methods for analysis of multicomponent diffusion explicitly addressing various degrees of complexity.8–10 Predictive equations for multicomponent diffusion of liquids mostly rely on extensions of the Darken relation,11–13 which is only valid for ideal mixtures.14 The underlying physical phenomena in non-ideal mixtures are not well understood and the lack of experimental data impedes the development and verification of new predictive equations.The objective of this study was not only to measure and predict the Fick diffusion coefficient matrix for a series of ternary liquid mixtures, rather, the emphasis lied on understanding common features and whether they can be related to the behavior of the pure components and binary subsystems. Three ternary mixtures that are composed of organic compounds were selected, i.e. an aromatic, a ketone and an alcohol. Throughout, the first two components were benzene (1) and acetone (2) and the third component was one of the alcohols, methanol, ethanol or 2-propanol. For each mixture, nine state points along a composition path with a constant content of benzene, x1 = 0.33 mol mol−1, were studied under ambient conditions (298.15 K and 0.1 MPa). Seven of the state points were ternary mixtures and two were binary subsystems. To obtain reliable results for the Fick diffusion coefficient matrix, two complementary approaches were used, i.e. experiments and predictive molecular simulations. This combination allows for a critical analysis and leads to a deeper understanding of the underlying phenomena.14,15The Taylor dispersion technique was utilized for the experiments.16,17 In this method, a small quantity of mixture with a slightly different composition is injected into a laminar stream. It disperses due to convection and diffusion while flowing through a capillary tube and the refractive index is measured at its end to sample the concentration distribution. We have used the same apparatus as in previous works.6,7 The Fick diffusion matrix is obtained by fitting working equations to the measured signal, i.e. the Taylor peak. The mathematical model of the Taylor dispersion technique was originally developed on the basis of Fick’s law in the volume reference frame. In a ternary mixture, two molar fluxes Jvi relative to a volume averaged velocity are related to gradients of molar concentration ∇Ci with four diffusion coefficients Dvij. Alternatively, fluxes expressed in the molar reference frame Ji are relative to a molar averaged velocity and the mole fraction gradients ∇xi act as a driving force1with molar density ρ. The fluxes of all three components are constrained by ΣJi = 0. The main diffusion coefficients D11 and D22 relate the flux of one component to its own mole fraction gradient and the cross diffusion coefficients D12 and D21 describe the coupling of the flux of one component with the gradient of the other. The third component does not appear in eqn (1) explicitly, but in general it affects all four diffusion coefficients. The transformation of experimental data from the volume to the molar reference frame (Dvij to Dij) could be done here on the basis of the pure component volumes (see the ESI†).Equilibrium molecular dynamics (MD) simulations were employed in this work, allowing for examination at the microscopic scale. The underlying molecular models were rigid, non-polarizable force fields of united atom type, consisting of a varying number of Lennard–Jones, point charge, dipole and quadrupole sites (see the ESI†). Note that the force field parameters were adjusted to pure fluid properties only so that all simulation results for the mixtures are strictly predictive. Diffusion coefficients were sampled with the Green–Kubo formalism, based on integrated correlation functions of net velocities of the contained species.11,15 Thereby, phenomenological coefficients Δij were obtained, associating the diffusive fluxes with the chemical potential gradients ∇μi2with gas constant R and temperature T. Fluxes Ji correspond to the molar reference frame as in eqn (1).The diffusion coefficients from experiment and simulation are related to different driving forces so that the chemical potential gradients have to be transformed to the mole fraction gradients for their comparison.18 This transformation is contained in the thermodynamic factor matrix Γ3with the activity coefficient of species i being γi, which expresses the non-ideality of a mixture with respect to the composition. This relationship shows that the Fick diffusion coefficients are actually the product of two contributions, a kinetic Δij and a thermodynamic Γij. The separate observation of these two contributions promotes understanding of the underlying physical phenomena. In the present study, the thermodynamic factor was calculated using the Wilson excess Gibbs energy (gE) model, using parameters fitted to experimental vapor–liquid equilibrium data of the binary subsystems (see the ESI†). This combination of MD simulation results with a gE model was successfully used in previous work to predict Fick diffusion coefficients, including several binary subsystems of the ternary mixtures studied here.19The four elements of the Fick diffusion coefficient matrix were determined for the three ternary mixtures, benzene + acetone + methanol/ethanol/2-propanol, for nine different compositions, each at ambient temperature and pressure.Results for the first main element of the diffusion matrix D11, which relates the flux of benzene to its own mole fraction gradient, are shown in Fig. 1(a). The experimental data agree quantitatively with the molecular simulation data. D11 increases with the acetone content in the ternary mixture. Since mixtures with a constant mole fraction of benzene (x1 = 0.33 mol mol−1) were studied throughout, the left edge of Fig. 1(a) corresponds to the binary limit of benzene + alcohol, while the right edge corresponds to that of benzene + acetone. Analysis of the ternary diffusive fluxes implies the following asymptotic behavior of the diffusion coefficients towards the binary limits:7 (i) at the infinite dilution limit, x2 → 0, the ternary coefficient D11 tends to the binary Fick diffusion coefficient of benzene + alcohol; (ii) at the other limit, x3 → 0, D11 − D12 = D22 − D21 → Dbin (benzene + acetone) should hold. The present experimental and simulation results for D11 are consistent with these asymptotic limits.Open in a separate windowFig. 1Top: The main Fick diffusion coefficient (molar reference frame) of benzene D11 in the three ternary mixtures benzene (1) + acetone (2) + alcohol (3) at a constant benzene mole fraction x1 = 0.33 mol mol−1 from experiment (triangles) and MD simulation combined with the Wilson gE model (circles). Both data sets were sampled at the same compositions, but are slightly shifted in the plot for visibility reasons. The symbols at the edges of this plot are the binary diffusion coefficients of benzene + alcohol (x2 → 0) and of benzene + acetone (x3 → 0). Bottom: The binary Fick diffusion coefficient of the subsystems benzene + alcohol and benzene + acetone. Most of the binary experimental data were taken from the literature.20–27An inspection of Fig. 1(a) provides an unexpected finding: the main element D11 is almost identical for all three mixtures along the examined composition path, i.e. it is independent of the contained type of alcohol. To explain this intriguing behavior of D11, the properties of the pure components are considered first (see M (g mol−1) ρ (mol l−1) ρ m (g l−1) D 0 10−9 (m2 s−1) Benzene 78.11 11.147 (2) 870.6 (1) 2.226 (4) Acetone 58.08 13.536 (3) 786.2 (2) 4.538 (8) Methanol 32.04 24.541 (6) 786.3 (2) 2.449 (6) Ethanol 46.07 17.132 (4) 789.3 (2) 0.974 (3) 2-Propanol 60.10 12.803 (1) 769.5 (1) 0.604 (7)