Current knowledge on functionality and potential therapeutic uses of donkey milk

The increase of knowledge on the composition of donkey milk has revealed marked similarities to human milk, which led to a growing number of investigations focused on testing the potential effects of donkey milk in vitro and in vivo. This paper examines the scientific evidence regarding the beneficial effects of donkey milk on human health. Most clinical studies report a tolerability of donkey milk in 82.6–98.5% of infants with cow milk protein allergies. The average protein content of donkey milk is about 18 g/L. Caseins, which are main allergenic components of milk, are less represented compared to cow milk (56% of the total protein in donkey vs. 80% in cow milk). Donkey milk is well accepted by children due to its high concentration of lactose (about 60 g/L). Immunomodulatory properties have been reported in one study in humans and in several animal models. Donkey milk also seems to modulate the intestinal microbiota, enhance antioxidant defense mechanisms and detoxifying enzymes activities, reduce hyperglycemia and normalize dyslipidemia. Donkey milk has lower calorie and fat content compared with other milks used in human nutrition (fat ranges from 0.20% to 1.7%) and a more favourable fatty acid profile, being low in saturated fatty acids (3.02 g/L) and high in alpha-linolenic acid (about 7.25 g/100 g of fat). Until now, the beneficial properties of donkey milk have been mostly related to whey proteins, among which β-lactoglobulin is the most represented (6.06 g/L), followed by α-lactalbumin (about 2 g/L) and lysozyme (1.07 g/L). So far, the health functionality of donkey milk has been tested almost exclusively on animal models. Furthermore, in vitro studies have described inhibitory action against bacteria, viruses, and fungi. From the literature review emerges the need for new randomized clinical trials on humans to provide stronger evidence of the potential beneficial health effects of donkey milk, which could lead to new applications as an adjuvant in the treatment of cardiometabolic diseases, malnutrition, and aging

Physical origin of the power-law tailed statistical distributions

Starting from the BBGKY hierarchy, describing the kinetics of nonlinear particle system, we obtain the relevant entropy and stationary distribution function. Subsequently, by employing the Lorentz transformations we propose the relativistic generalization of the exponential and logarithmic functions. The related particle distribution and entropy represents the relativistic extension of the classical Maxwell-Boltzmann distribution and of the Boltzmann entropy respectively and define the statistical mechanics presented in [Phys. Rev. E {\bf 66}, 056125 (2002)] and [Phys. Rev. E {\bf 72}, 036108 (2005). The achievements of the present effort, support the idea that the experimentally observed power law tailed statistical distributions in plasma physics, are enforced by the relativistic microscopic particle dynamics.Comment: 6 pages. arXiv admin note: substantial text overlap with arXiv:1110.3944, arXiv:1012.390

Nonlinear evolution of the magnetized Kelvin-Helmholtz instability: from fluid to kinetic modeling

The nonlinear evolution of collisionless plasmas is typically a multi-scale process where the energy is injected at large, fluid scales and dissipated at small, kinetic scales. Accurately modelling the global evolution requires to take into account the main micro-scale physical processes of interest. This is why comparison of different plasma models is today an imperative task aiming at understanding cross-scale processes in plasmas. We report here the first comparative study of the evolution of a magnetized shear flow, through a variety of different plasma models by using magnetohydrodynamic, Hall-MHD, two-fluid, hybrid kinetic and full kinetic codes. Kinetic relaxation effects are discussed to emphasize the need for kinetic equilibriums to study the dynamics of collisionless plasmas in non trivial configurations. Discrepancies between models are studied both in the linear and in the nonlinear regime of the magnetized Kelvin-Helmholtz instability, to highlight the effects of small scale processes on the nonlinear evolution of collisionless plasmas. We illustrate how the evolution of a magnetized shear flow depends on the relative orientation of the fluid vorticity with respect to the magnetic field direction during the linear evolution when kinetic effects are taken into account. Even if we found that small scale processes differ between the different models, we show that the feedback from small, kinetic scales to large, fluid scales is negligable in the nonlinear regime. This study show that the kinetic modeling validates the use of a fluid approach at large scales, which encourages the development and use of fluid codes to study the nonlinear evolution of magnetized fluid flows, even in the colisionless regime

Relativistic kinetics and power-law tailed distributions

The present paper is devoted to the relativistic statistical theory, introduced in Phys. Rev. E {\bf 66} (2002) 056125 and Phys. Rev. E {\bf 72} (2005) 036108, predicting the particle distribution function $p(E)= \exp_{\kappa} (-\beta[E-\mu])$ with $\exp_{\kappa}(x)=(\sqrt{1+ \kappa^2 x^2}+\kappa x)^{1/\kappa}$, and $\kappa^2<1$. This, experimentally observed, relativistic distribution, at low energies behaves as the exponential, Maxwell-Boltzmann classical distribution, while at high energies presents power law tails. Here, we obtain the evolution equation, conducting asymptotically to the above distribution, by using a new deductive procedure, starting from the relativistic BBGKY hierarchy and by employing the relativistic molecular chaos hypothesis.Comment: 5 two-column page

Oxaliplatin plus irinotecan and leucovorin-modulated5-fluorouracil triplet regimen every other week:a dose-finding study in patients with advanced gastrointestinal malignancies

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Plasma Physical Parameters along CME-driven Shocks. II. Observation-Simulation Comparison

In this work, we compare the spatial distribution of the plasma parameters along the 1999 June 11 coronal mass ejection (CME)-driven shock front with the results obtained from a CME-like event simulated with the FLIPMHD3D code, based on the FLIP-MHD particle-in-cell method. The observational data are retrieved from the combination of white-light coronagraphic data (for the upstream values) and the application of the Rankine-Hugoniot equations (for the downstream values). The comparison shows a higher compression ratio X and Alfvénic Mach number MA at the shock nose, and a stronger magnetic field deflection d toward the flanks, in agreement with observations. Then, we compare the spatial distribution of MA with the profiles obtained from the solutions of the shock adiabatic equation relating MA, X, and {θ }{Bn} (the angle between the upstream magnetic field and the shock front normal) for the special cases of parallel and perpendicular shock, and with a semi-empirical expression for a generically oblique shock. The semi-empirical curve approximates the actual values of MA very well, if the effects of a non-negligible shock thickness {δ }{sh} and plasma-to magnetic pressure ratio {β }u are taken into account throughout the computation. Moreover, the simulated shock turns out to be supercritical at the nose and sub-critical at the flanks. Finally, we develop a new one-dimensional Lagrangian ideal MHD method based on the GrAALE code, to simulate the ion-electron temperature decoupling due to the shock transit. Two models are used, a simple solar wind model and a variable-γ model. Both produce results in agreement with observations, the second one being capable of introducing the physics responsible for the additional electron heating due to secondary effects (collisions, Alfvén waves, etc.)

An Arbitrary Curvilinear Coordinate Method for Particle-In-Cell Modeling

A new approach to the kinetic simulation of plasmas in complex geometries, based on the Particle-in- Cell (PIC) simulation method, is explored. In the two dimensional (2d) electrostatic version of our method, called the Arbitrary Curvilinear Coordinate PIC (ACC-PIC) method, all essential PIC operations are carried out in 2d on a uniform grid on the unit square logical domain, and mapped to a nonuniform boundary-fitted grid on the physical domain. As the resulting logical grid equations of motion are not separable, we have developed an extension of the semi-implicit Modified Leapfrog (ML) integration technique to preserve the symplectic nature of the logical grid particle mover. A generalized, curvilinear coordinate formulation of Poisson's equations to solve for the electrostatic fields on the uniform logical grid is also developed. By our formulation, we compute the plasma charge density on the logical grid based on the particles' positions on the logical domain. That is, the plasma particles are weighted to the uniform logical grid and the self-consistent mean electrostatic fields obtained from the solution of the logical grid Poisson equation are interpolated to the particle positions on the logical grid. This process eliminates the complexity associated with the weighting and interpolation processes on the nonuniform physical grid and allows us to run the PIC method on arbitrary boundary-fitted meshes.Comment: Submitted to Computational Science & Discovery December 201