In Vitro Release from Reverse Poloxamine/alpha-Cyclodextrin Matrices: Modelling and Comparison of Dissolution Profiles

Gels obtained by complexation of octablock star polyethylene oxide/polypropylene oxide copolymers (Tetronic 90R4) with -cyclodextrin (-CD) were evaluated as matrices for drug release. Both molecules are biocompatible so they can be potentially applied to drug delivery systems. Two different types of matrices of Tetronic 90R4 and -CD were evaluated: gels and tablets. These gels are capable to gelifying in situ and show sustained erosion kinetics in aqueous media. Tablets were prepared by freeze-drying and comprising the gels. Using these two different matrices, the release of two model molecules, L-tryptophan (Trp), and a protein, bovine serum albumin (BSA), was evaluated. The release profiles of these molecules from gels and tablets prove that they are suitable for sustained delivery. Mathematical models were applied to the release curves from tablets to elucidate the drug delivery mechanism. Good correlations were found for the fittings of the release curves to different equations. The results point that the release of Trp from different tablets is always governed by Fickian diffusion, whereas the release of BSA is governed by a combination of diffusion and tablet erosion. 

A Lagrangian approach for modeling road collisions using second-order models of traffic flow

In [M. Herty, A. Klein, S. Moutari, V. Schleper, and G. Steinaur, IMA J. Appl. Math., 78(5), 1087–1108, 2013] and [M. Herty and V. Schleper, ZAMM J. Appl. Math. Mech., 91, 763–776, 2011], a macroscopic approach, derived from fluid-dynamics models, has been introduced to infer traffic conditions prone to road traffic collisions along highways’ sections. In these studies, the governing equations are coupled within an Eulerian framework, which assumes fixed interfaces between the models. A coupling in Lagrangian coordinates would enable us to get rid of this (not very realistic) assumption. In this paper, we investigate the well-posedness and the suitability of the coupling of the governing equations within the Lagrangian framework. Further, we illustrate some features of the proposed approach through some numerical simulations.

Pattern Recognition Approach for Road Collision Hotspots Analysis: Case Study of Northern Ireland

In order to address road safety effectively, it is essential to understand all the factors, which
attribute to the occurrence of a road collision. This is achieved through road safety
assessment measures, which are primarily based on historical crash data. Recent advances
in uncertain reasoning technology have led to the development of robust machine learning
techniques, which are suitable for investigating road traffic collision data. These techniques
include supervised learning (e.g. SVM) and unsupervised learning (e.g. Cluster Analysis).
This study extends upon previous research work, carried out in Coll et al. [3], which
proposed a non-linear aggregation framework for identifying temporal and spatial hotspots.
The results from Coll et al. [3] identified Lisburn area as the hotspot, in terms of road safety,
in Northern Ireland. This study aims to use Cluster Analysis, to investigate and highlight any
hidden patterns associated with collisions that occurred in Lisburn area, which in turn, will
provide more clarity in the causation factors so that appropriate countermeasures can be put
in place.

Ranking Spatial and Temporal Hotspots for Road Safety Interventions Using a Nonlinear Aggregation Approach

In recent years, the concept of a composite performance index, brought from economic and business statistics, has gained popularity in the field of road safety. The construction of the Composite Safety Performance Index (CSPI) involves the following key steps: the selection of the most appropriate indicators to be aggregated and the method used to aggregate them.

Over the last decade, various aggregation methods for estimating the CSPI have been suggested in the literature. However, recent studies indicates that most of these methods suffer from many deficiencies at both the theoretical and operational level; these include the correlation and compensability between indicators, as well as their high “degree of freedom” which enables one to readily manipulate them to produce desired outcomes.

The purpose of this study is to introduce an alternative aggregation method for the estimation of the CSPI, which is free from the aforementioned deficiencies. In contrast with the current aggregation methods, which generally use linear combinations of road safety indicators to estimate a CSPI, the approach advocated in this study is based on non-linear combinations of indicators and can be summarized into the following two main steps: the pairwise comparison of road safety indicators and the development of marginal and composite road safety performance functions. The introduced method has been successfully applied to identify and rank temporal and spatial hotspots for Northern Ireland, using road traffic collision data recorded in the UK STATs19 database. The obtained results highlight the promising features of the proposed approach including its stability and consistency, which enables significantly reduced deficiencies associated with the current aggregation methods. Progressively, the introduced method could evolve into an intelligent support system for road safety assessment.

Cytokine and C-reactive protein profiles induced by porcine circovirus type 2 experimental infection in 3-week-old piglets

The purpose of this study was to determine serum profiles of cytokines at a protein level and Creactive protein (CRP) during the development of postweaning multisystemic wasting syndrome (PMWS) in experimentally inoculated pigs. Levels of serum IFN-alpha, IL-6, IL-10, and CRP were examined for a 35-day period in 10 piglets experimentally infected with PCV2 at 3 weeks of age. Four of the infected piglets developed severe PMWS at 14 to 21 days post-infection (d.p.i.) and died prior to termination of the experiment. The remaining six PCV2-infected piglets experienced transient fever, but did not display overt clinical signs of PMWS and were considered as subclinically infected. A bioassay was used to detect IL-6 and ELISAs were used to detect IFN-alpha, IL-10, and CRP. There were no significant differences in cytokine or CRP expression from 0 to 7 d.p.i. between the PMWS-affected and the subclinically infected piglets. Levels of IL-10 and CRP were elevated from 10 and 14 d.p.i. respectively in the PMWS-affected piglets compared to the subclinically infected piglets. There were no significant differences in IFN-alpha and IL-6 expression between the PMWS-affected piglets and the subclinically infected piglets. The present study shows that elevated levels of serum CRP and IL-10 were associated with PCV2-infected piglets that subsequently developed severe PMWS. This may help to provide further insight into the immunoaetiogenesis of this syndrome.

Beam profiles of proton and carbon ions in the relativistic transparency regime

Ion acceleration from relativistic laser solid interactions has been of particular interest over the last decade. While beam profiles have been studied for target normal sheath acceleration (TNSA), such profiles have yet to be described for other mechanisms. Here, experimental data is presented, investigating ion beam profiles from acceleration governed by relativistic transparent laser plasma interaction. The beam shape of carbon C6+ ions and protons has been measured simultaneously with a wide angle spectrometer. It was found that ion beams deviate from the typical Gaussian-like shape found with TNSA and that the profile is governed by electron dynamics in the volumetric laser-plasma interaction with a relativistically transparent plasma; due to the ponderomotive force electrons are depleted from the center of the laser axis and form lobes affecting the ion beam structure. The results are in good agreement with high resolution three-dimensional-VPIC simulations and can be used as a new tool to experimentally distinguish between different acceleration mechanisms.

Plasma properties and Stokes profiles during the lifetime of a photospheric magnetic bright point

Aims: In this paper we aim to investigate the evolution of plasmaproperties and Stokes parameters in photospheric magnetic bright pointsusing 3D magneto-hydrodynamical simulations and radiative diagnostics ofsolar granulation.

Methods: Simulated time-dependent radiationparameters and plasma properties were investigated throughout theevolution of a bright point. Synthetic Stokes profiles for the FeI630.25 nm line were calculated, which also allowed the evolution of theStokes-I line strength and Stokes-V area and amplitude asymmetries to beinvestigated.

Results: Our results are consistent withtheoretical predictions and published observations describing convectivecollapse, and confirm this as the bright point formation process.Through degradation of the simulated data to match the spatialresolution of SOT, we show that high spatial resolution is crucial forthe detection of changing spectro-polarimetric signatures throughout amagnetic bright point's lifetime. We also show that the signaturedownflow associated with the convective collapse process tends towardszero as the radiation intensity in the bright point peaks, because ofthe magnetic forces present restricting the flow of material in the fluxtube.

Genetics of Diabetic Nephropathy: a Long Road of Discovery

The global prevalence of diabetic nephropathy is rising in parallel with the increasing incidence of diabetes in most countries. Unfortunately, up to 40 % of persons diagnosed with diabetes may develop kidney complications. Diabetic nephropathy is associated with substantially increased risks of cardiovascular disease and premature mortality. An inherited susceptibility to diabetic nephropathy exists, and progress is being made unravelling the genetic basis for nephropathy thanks to international research collaborations, shared biological resources and new analytical approaches. Multiple epidemiological studies have highlighted the clinical heterogeneity of nephropathy and the need for better phenotyping to help define important subgroups for analysis and increase the power of genetic studies. Collaborative genome-wide association studies for nephropathy have reported unique genes, highlighted novel biological pathways and suggested new disease mechanisms, but progress towards clinically relevant risk prediction models for diabetic nephropathy has been slow. This review summarises the current status, recent developments and ongoing challenges elucidating the genetics of diabetic nephropathy.