Analysis of Degradation Data of Poly(L-lactide-co-L,D-lactic actide) and Poly(L-lactide) Obtained at Elevated and Physiological Temperatures Using Mathematical Models

The degradation of resorbable polymeric devices often takes months to years. Accelerated testing at elevated temperatures is an attractive but controversial technique. The purposes of this paper include: (a) to provide a summary of the mathematical models required to analyse accelerated degradation data and to indicate the pitfalls of using these models; (b) to improve the model previously developed by Han and Pan; (c) to provide a simple version of the model of Han and Pan with an analytical solution that is convenient to use; (d) to demonstrate the application of the improved model in two different poly(lactic acid) systems. It is shown that the simple analytical relations between molecular weight and degradation time widely used in the literature can lead to inadequate conclusions. In more general situations the rate equations are only part of a complete degradation model. Together with previous works in the literature, our study calls for care in using the accelerated testing technique.

Applications of statistical models in proportioning medium strength self-compacting concrete

Self-compacting concrete (SCC) is generally designed with a relatively higher content of finer, which includes cement, and dosage of superplasticizer than the conventional concrete. The design of the current SCC leads to high compressive strength, which is already used in special applications, where the high cost of materials can be tolerated. Using SCC, which eliminates the need for vibration, leads to increased speed of casting and thus reduces labour requirement, energy consumption, construction time, and cost of equipment. In order to obtain and gain maximum benefit from SCC it has to be used for wider applications. The cost of materials will be decreased by reducing the cement content and using a minimum amount of admixtures. This paper reviews statistical models obtained from a factorial design which was carried out to determine the influence of four key parameters on filling ability, passing ability, segregation and compressive strength. These parameters are important for the successful development of medium strength self-compacting concrete (MS-SCC). The parameters considered in the study were the contents of cement and pulverised fuel ash (PFA), water-to-powder ratio (W/P), and dosage of superplasticizer (SP). The responses of the derived statistical models are slump flow, fluidity loss, rheological parameters, Orimet time, V-funnel time, L-box, JRing combined to Orimet, JRing combined to cone, fresh segregation, and compressive strength at 7, 28 and 90 days. The models are valid for mixes made with 0.38 to 0.72 W/P ratio, 60 to 216 kg/m3 of cement content, 183 to 317 kg/m3 of PFA and 0 to 1% of SP, by mass of powder. The utility of such models to optimize concrete mixes to achieve good balance between filling ability, passing ability, segregation, compressive strength, and cost is discussed. Examples highlighting the usefulness of the models are presented using isoresponse surfaces to demonstrate single and coupled effects of mix parameters on slump flow, loss of fluidity, flow resistance, segregation, JRing combined to Orimet, and compressive strength at 7 and 28 days. Cost analysis is carried out to show trade-offs between cost of materials and specified consistency levels and compressive strength at 7 and 28 days that can be used to identify economic mixes. The paper establishes the usefulness of the mathematical models as a tool to facilitate the test protocol required to optimise medium strength SCC.

Does unidirectional vesicular transport occur in retinal vessels?

This paper challenges the hypothesis that the smooth 80 nm plasmalemmal caveolae found in abundance at the abluminal aspect of the endothelium in retinal blood vessels participate in a unidirectional vesicular transport mechanism. Evidence is presented which indicates that horseradish peroxidase, when introduced to the extracellular space of the retina via the vitreous body, may enter the intravascular compartment through junctional incompetence which occurs at or after enucleation of the eye. It is proposed that the plasmalemmal caveolae at the abluminal plasma membrane of endothelial cells in retinal blood vessels are static structures which facilitate the transport of small solutes and ions across the blood retinal barrier.

Parasites that change predator or prey behaviour can have keystone effects on community composition

Parasites play pivotal roles in structuring communities, often via indirect interactions with non-host species. These effects can be density-mediated (through mortality) or trait-mediated (behavioural, physiological and developmental), and may be crucial to population interactions, including biological invasions. For instance, parasitism can alter intraguild predation (IGP) between native and invasive crustaceans, reversing invasion outcomes. Here, we use mathematical models to examine how parasite-induced trait changes influence the population dynamics of hosts that interact via IGP. We show that trait-mediated indirect interactions impart keystone effects, promoting or inhibiting host coexistence. Parasites can thus have strong ecological impacts, even if they have negligible virulence, underscoring the need to consider trait-mediated effects when predicting effects of parasites on community structure in general and biological invasions in particular.

COP and clathrin-coated vesicle budding:different pathways, common approaches

Vesicle and tubule transport containers move proteins and lipids from one membrane system to another. Newly forming transport containers frequently have electron-dense coats. Coats coordinate the accumulation of cargo and sculpt the membrane. Recent advances have shown that components of both COP1 and clathrin-adaptor coats share the same structure and the same motif-based cargo recognition and accessory factor recruitment mechanisms, which leads to insights on conserved aspects of coat recruitment, polymerisation and membrane deformation. These themes point to the way in which evolutionarily conserved features underpin these diverse pathways.

Avoiding Overfitting in Inverse Modeling of Chloride Migration in Concrete

Inverse analysis for reactive transport of chlorides through concrete in the presence of electric field is presented. The model is solved using MATLAB’s built-in solvers “pdepe.m” and “ode15s.m”. The results from the model are compared with experimental measurements from accelerated migration test and a function representing the lack of fit is formed. This function is optimised with respect to varying amount of key parameters defining the model. Levenberg-Marquardt trust-region optimisation approach is employed. The paper presents a method by which the degree of inter-dependency between parameters and sensitivity (significance) of each parameter towards model predictions can be studied on models with or without clearly defined governing equations. Eigen value analysis of the Hessian matrix was employed to investigate and avoid over-parametrisation in inverse analysis. We investigated simultaneous fitting of parameters for diffusivity, chloride binding as defined by Freundlich isotherm (thermodynamic) and binding rate (kinetic parameter). Fitting of more than 2 parameters, simultaneously, demonstrates a high degree of parameter inter-dependency. This finding is significant as mathematical models for representing chloride transport rely on several parameters for each mode of transport (i.e., diffusivity, binding, etc.), which combined may lead to unreliable simultaneous estimation of parameters.

Unsteady Gas Dynamic Engine Simulation

This paper provides an overview of the basic theory underlying 1D unsteady gas dynamics, the computational method developed at Queen’s University Belfast (QUB), the use of CFD as an alternative and some experimental results that demonstrate the techniques used to develop the mathematical models.

Methodology for Validating Artifact Removal Techniques for Physiological Signals

Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods for this process has become particularly acute as healthcare technology deployment undergoes transition from the current hospital-centric setting toward a wearable and ubiquitous monitoring environment. Currently, determining the relative efficacy and performance of the multiple artifact removal techniques available on real world data can be problematic, due to incomplete information on the uncorrupted desired signal. The majority of techniques are presently evaluated using simulated data, and therefore, the quality of the conclusions is contingent on the fidelity of the model used. Consequently, in the biomedical signal processing community, there is considerable focus on the generation and validation of appropriate signal models for use in artifact suppression. Most approaches rely on mathematical models which capture suitable approximations to the signal dynamics or underlying physiology and, therefore, introduce some uncertainty to subsequent predictions of algorithm performance. This paper describes a more empirical approach to the modeling of the desired signal that we demonstrate for functional brain monitoring tasks which allows for the procurement of a ground truth signal which is highly correlated to a true desired signal that has been contaminated with artifacts. The availability of this ground truth, together with the corrupted signal, can then aid in determining the efficacy of selected artifact removal techniques. A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform. © 2012 IEEE.

Receptor-mediated endocytosis and intracellular trafficking of insulin and low-density lipoprotein by retinal vascular endothelial cells

PURPOSE: The authors investigated the receptor-mediated endocytosis (RME) and intracellular trafficking of insulin and low-density lipoprotein (LDL) in cultured retinal vascular endothelial cells (RVECs). METHODS: Low-density lipoprotein and insulin were conjugated to 10 nm colloidal gold, and these ligands were added to cultured bovine RVECs for 20 minutes at 4 degrees C. The cultures were then warmed to 37 degrees C and fixed after incubation times between 30 seconds and 1 hour. Control cells were incubated with unconjugated gold colloid at times and concentrations similar to those of the ligands. Additional control cells were exposed to several concentrations of anti-insulin receptor antibody or a saturating solution of unconjugated insulin before incubation with gold insulin. RESULTS: Using transmission electron microscopy, insulin gold and LDL gold were both observed at various stages of RME. Insulin-gold particles were first seen to bind to the apical plasma membrane (PM) before clustering in clathrin-coated pits and internalization in coated vesicles. Gold was later visualized in uncoated cytoplasmic vesicles, corresponding to early endosomes and multivesicular bodies (MVBs) or late endosomes. In several instances, localized regions of the limiting membrane of the MVBs appeared coated, a feature of endosomal membranes not previously described. After RME at the apical PM and passage through the endosomal system, the greater part of both insulin- and LDL-gold conjugates was seen to accumulate in large lysosome-like compartments. However, a small but significant proportion of the internalized ligands was transcytosed and released as discrete membrane-associated quanta at the basal cell surface. The uptake of LDL gold was greatly increased in highly vacuolated, late-passage RVECs. In controls, anti-insulin receptor antibody and excess unconjugated insulin caused up to 89% inhibition in gold-insulin binding and internalization. CONCLUSION: These results illustrate the internalization and intracellular trafficking by RVECs of insulin and LDL through highly efficient RME, and they provide evidence for at least two possible fates for the endocytosed ligands. This study outlines a route by which vital macromolecules may cross the inner blood-retinal barrier.

Implications of Intercellular Signaling for Radiation Therapy: A Theoretical Dose-Planning Study

Purpose
Recent in vitro results have shown significant contributions to cell killing from signaling effects at doses that are typically used in radiation therapy. This study investigates whether these in vitro observations can be reconciled with in vivo knowledge and how signaling may have an impact on future developments in radiation therapy.
Methods and Materials
Prostate cancer treatment plans were generated for a series of 10 patients using 3-dimensional conformal therapy, intensity modulated radiation therapy (IMRT), and volumetric modulated arc therapy techniques. These plans were evaluated using mathematical models of survival following modulated radiation exposures that were developed from in vitro observations and incorporate the effects of intercellular signaling. The impact on dose-volume histograms and mean doses were evaluated by converting these survival levels into "signaling-adjusted doses" for comparison.
Results
Inclusion of intercellular communication leads to significant differences between the signalling-adjusted and physical doses across a large volume. Organs in low-dose regions near target volumes see the largest increases, with mean signaling-adjusted bladder doses increasing from 23 to 33 Gy in IMRT plans. By contrast, in high-dose regions, there is a small decrease in signaling-adjusted dose due to reduced contributions from neighboring cells, with planning target volume mean doses falling from 74 to 71 Gy in IMRT. Overall, however, the dose distributions remain broadly similar, and comparisons between the treatment modalities are largely unchanged whether physical or signaling-adjusted dose is compared. Conclusions Although incorporating cellular signaling significantly affects cell killing in low-dose regions and suggests a different interpretation for many phenomena, their effect in high-dose regions for typical planning techniques is comparatively small. This indicates that the significant signaling effects observed in vitro are not contradicted by comparison with clinical observations. Future investigations are needed to validate these effects in vivo and to quantify their ranges and potential impact on more advanced radiation therapy techniques.

The effects of global climate change on the cycling and processes of persistent organic pollutants (POPs) in the North Sea

The fate and cycling of two selected legacy persistent organic pollutants (POPs), PCB 153 and gamma-HCH, in the North Sea in the 21st century have been modelled with combined hydrodynamic and fate and transport ocean models<br/>(HAMSOM and FANTOM, respectively). To investigate the impact of climate variability on POPs in the North Sea in the 21st century, future scenario model runs for three 10-year periods to the year 2100 using plausible levels of both in
situ concentrations and atmospheric, river and open boundary inputs are performed. This slice mode under a moderate scenario (A1B) is sufficient to provide a basis for further analysis. For the HAMSOM and atmospheric forcing, results of the IPCC A1B (SRES) 21st century scenario are utilized, where surface forcing is provided by the REMO downscaling of the ECHAM5 global atmospheric model, and open boundary conditions are provided by the MPIOM global ocean model.
Dry gas deposition and volatilization of gamma-HCH increase in the future relative to the present by up to 20% (in the spring and summer months for deposition and in summer for volatilization). In the water column, total mass of
gamma-HCH and PCB 153 remain fairly steady in all three runs. In sediment,
gamma-HCH increases in the future runs, relative to the present, while PCB 153 in sediment decreases exponentially in all three runs, but even faster in the future, due to the increased number of storms, increased duration of gale wind conditions and increased water and air temperatures, all of which are the result of climate change. Annual net sinks exceed sources at the ends of all periods.
Overall, the model results indicate that the climate change scenarios considered here generally have a negligible influence on the simulated fate and transport of the two POPs in the North Sea, although the increased number and magnitude of storms in the 21st century will result in POP resuspension and ensuing revolatilization events. Trends in emissions from primary and secondary sources will remain the key driver of levels of these contaminants over time.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.

Implications of FPS1 deletion and membrane ergosterol content for glycerol efflux from Saccharomyces cerevisiae

The deletion of the gene encoding the glycerol facilitator Fps1p was associated with an altered plasma membrane lipid composition in Saccharomyces cerevisiae. The S. cerevisiae fps1delta strain respectively contained 18 and 26% less ergosterol than the wild-type strain, at the whole-cell level and at the plasma membrane level. Other mutants with deficiencies in glycerol metabolism were studied to investigate any possible link between membrane ergosterol content and intracellular glycerol accumulation. In these mutants a modification in intracellular glycerol concentration, or in intra- to extracellular glycerol ratio was accompanied by a reduction in plasma membrane ergosterol content. However, there was no direct correlation between ergosterol content and intracellular glycerol concentration. Lipid composition influences the membrane permeability for solutes during adaptation of yeast cells to osmotic stress. In this study, ergosterol supplementation was shown to partially suppress the hypo-osmotic sensitivity phenotype of the fps1delta strain, leading to more efficient glycerol efflux, and improved survival. The erg-1 disruption mutant, which is unable to synthesise ergosterol, survived and recovered from the hypo-osmotic shock more successfully when the concentration of exogenously supplied ergosterol was increased. The results obtained suggest that a higher ergosterol content facilitates the flux of glycerol across the plasma membrane of S. cerevisiae cells.

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.