A single injection of pregabalin induces short- and long-term beneficial effects on fear memory and anxiety-like behavior in rats with experimental type-1 diabetes mellitus

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...     

The effect of alcohols as the third component on diffusion in mixtures of aromatics and ketones

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 J^v_i relative to a volume averaged velocity are related to gradients of molar concentration ∇C_i with four diffusion coefficients D^v_ij. Alternatively, fluxes expressed in the molar reference frame J_i are relative to a molar averaged velocity and the mole fraction gradients ∇x_i act as a driving force1with molar density ρ. The fluxes of all three components are constrained by ΣJ_i = 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 (D^v_ij to D_ij) 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 Δ_ij were obtained, associating the diffusive fluxes with the chemical potential gradients ∇μ_i2with gas constant R and temperature T. Fluxes J_i 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 γ_i, 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 Δ_ij and a thermodynamic Γ_ij. 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 (g^E) 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 g^E 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 → D_bin (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 g^E 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

HIV Infection Among People Who Inject Drugs in the United States: Geographically Explained Variance Across Racial and Ethnic Groups

Objectives. We explored how variance in HIV infection is distributed across multiple geographical scales among people who inject drugs (PWID) in the United States, overall and within racial/ethnic groups.Methods. People who inject drugs (n = 9077) were recruited via respondent-driven sampling from 19 metropolitan statistical areas (MSAs) for the Centers for Disease Control and Prevention’s 2009 National HIV Behavioral Surveillance system. We used multilevel modeling to determine the percentage of variance in HIV infection explained by zip codes, counties, and MSAs where PWID lived, overall and for specific racial/ethnic groups.Results. Collectively, zip codes, counties, and MSAs explained 29% of variance in HIV infection. Within specific racial/ethnic groups, all 3 scales explained variance in HIV infection among non-Hispanic/Latino White PWID (4.3%, 0.2%, and 7.5%, respectively), MSAs explained variance among Hispanic/Latino PWID (10.1%), and counties explained variance among non-Hispanic/Latino Black PWID (6.9%).Conclusions. Exposure to potential determinants of HIV infection at zip codes, counties, and MSAs may vary for different racial/ethnic groups of PWID, and may reveal opportunities to identify and ameliorate intraracial inequities in exposure to determinants of HIV infection at these geographical scales.Since the mid-1990s, there has been an increase in studies evaluating whether features of the social, economic, physical, and political environment (i.e., place characteristics) affect health. This focus on place characteristics is evident in the development of theories conceptualizing place characteristics as health determinants,1–3 in the use of geospatial and systematic social observation methods to measure place characteristics,4–10 in the application of multilevel modeling to assess the potential impacts of place characteristics,11–18 and in the recognition that interventions should not solely encourage individual behavior change but also modify environmental features.3,16,19Literature emerging from this field of research demonstrates that place characteristics operationalized at different geographical scales influence psychosocial processes and individual behaviors that increase vulnerability to several health outcomes. With rare exception,20–24 however, studies of place and health typically assess the potential influence of place characteristics at a single geographical scale and do not simultaneously evaluate characteristics of other geographical scales. For example, several studies, including our own,25,26 sample participants from a single metropolitan statistical area (MSA) to assess the relationships of census tract characteristics to health, without sampling participants from multiple MSAs to simultaneously assess the relationships of tract-, county-, and MSA-level characteristics to health.25–32 The decision to focus on characteristics of a single geographical scale may arise because of data availability, cost constraints, or feasibility.Studies of place and health that focus on a single geographical scale, however, may misspecify relationships and hinder the exploration of causal pathways in 2 ways. First, studies that focus on features measured at a single geographical scale may overlook potential health determinants that are operationalized at other geographical scales. For instance, research assessing the relationships of features of neighborhoods (e.g., economic deprivation, racial/ethnic composition, policing practices, and “crackdowns”) cannot determine the influence of policies, laws, and governmental expenditures that are operationalized at county, MSA, and state levels, and shape neighborhood environments. Second, studies of features of a single geographical scale cannot determine whether relationships between characteristics operating at one geographical scale are confounded, mediated, or modified by characteristics of other geographic scales.3,16,33 The possibility that at least 1 of these mechanisms can occur has been demonstrated in research conducted by Warner and Gomez, which suggests that, among Black women diagnosed with breast cancer, residing in census blocks with high concentrations of Black residents is more protective against mortality in more racially segregated metropolitan areas than less racially segregated metropolitan areas.34In addition, research assessing the association of place-based factors with health outcomes rarely highlights the extent to which variance in health outcomes is explained by place and place-based factors. Determining whether health outcomes vary geographically can generate hypotheses about inequities in exposure to potential place-based determinants of health, and thereby inform how interventions and social policies are developed and spatially concentrated.35The present study illustrates the generative possibilities of extending research beyond a single geographical scale by achieving 2 primary aims. The study’s first aim is to determine the share of total variance in HIV infection that is apportioned to zip codes, counties, and MSAs among people who inject drugs (PWID). In the United States, PWID account for 22% of people living with HIV,36 and a growing body of literature demonstrates that features of neighborhoods such as census-tract racial composition and block-level social or physical disorder are associated with HIV-related outcomes among PWID,37,38 as are features of MSAs, including drug-related law enforcement, income inequality, residential segregation, and health service access.39–41 Revealing the geographical scale to which variance in HIV infection is apportioned among PWID can stimulate hypotheses about inequities in exposure to place-based determinants of HIV and inform the development and tailoring of place-based interventions. For example, finding high MSA-level variance in HIV infection may support analyses of whether MSA-level variations in health care service access predict variance in HIV serostatus and, if they do, support interventions to increase health care access in low-access MSAs. In contrast, if little to no variance in HIV infection among PWID is apportioned to MSAs, PWID may encounter a relatively uniform exposure to health care service access.Previous studies have found that variance in some health outcomes vary across racial/ethnic groups.42,43 The second aim of this study therefore tests the hypothesis that variance in HIV infection will differ within each of 3 racial/ethnic groups of PWID: non-Hispanic/Latino Whites, non-Hispanic/Latino Blacks, and Hispanics/Latinos.     

Kinematic Analysis of a Drinking Task in Chronic Hemiparetic Patients Using Features Analysis and Statistical Parametric Mapping

Objective

To compare sitting posture and movement strategies between chronic hemiparetic and healthy subjects while performing a drinking task, using statistical parametric mapping (SPM) and feature analysis.

Intrarater and Inter-rater Reliability of Maximal Voluntary Neck Muscle Strength Assessment Using a Handheld Dynamometer in Women With Headache and Healthy Women

Objective

This study aimed to determine the inter-rater and intrarater reliability, agreement, and minimal detectable change (MDC) of the neck muscle strength test using a handheld dynamometer in healthy women and women with headaches.