Tissue Aspiration and Inverse Finite Element Characterisation of Soft Tissues

In this work we examined the determination of soft tissue parameters via tissue aspiration experiments and inverse finite element characterisation. An aspiration tube was put against the target tissue. The deformation of the tissue inside the tube caused by weak suction was tracked with a video based system. A strain energy function was employed to model the elastic behaviour of soft tissue and viscoelasticity was accounted for by means of a quasi-linear viscoelastic formulation. Friction between the aspiration tube and the aspirated tissue was included in the model. Based on the assumed material model, an optimal set of material parameters was found, in order to best fit the experimental data obtained from ex-vivo experiments on pig kidney cortex. The inverse method resulted in robust determination of the unknown material parameters.     

Molecular dynamic studies of the compatibility of some cellulose derivatives with selected ionic liquids

Molecular dynamics techniques were used to study oligomers that mimic cellulose and various derivatives in the amorphous phase, including cellulose (C), methyl cellulose (MC), hydroxypropyl cellulose (HPC), and carboxymethyl cellulose (CMC). Densities and solubility parameters were determined for a series of oligomers with increasing chain length. Both properties were found to change linearly with the degree of polymerization (from monomers to dodecamers). Extrapolated predictions of the densities (g/cm³) for long chain polymers are: C, 1.42; MC, 1.33; HPC, 1.30; and CMC, 1.42. Computed values for the solubility parameter (MPa^1/2) are: C, 25.39; MC, 21.43; HPC, 21.70; and CMC, 24.35. We also evaluated the sensitivity of the solubility parameter to changes in the calculated density and found the dependence to be significant. The calculated solubility parameters were evaluated against experimental and other theoretical values as well as against selected ionic liquids comprised of cations in the imidazolium family and the chloride and trifluoroacetate anions.     

Application of Axial-haloketone Rule to Lactones

Antifungal activities were examined and compared for some 40 kinds of aliphatic and aromatic aldehydes, alcohols, phenolic compounds, ether compounds and hydrocarbons from essential oils and for some related compounds, using seven fungi.     

Population genetic characterisation of dominant Cryptosporidium parvum subtype IIaA15G2R1

The subtype IIaA15G2R1 at the 60 kDa glycoprotein (gp60) gene locus is the most dominant Cryptosporidium parvum infecting dairy cattle and humans in industrialised nations. The reasons for its high transmissibility are not clear, and it remains to be determined whether this subtype represents a homogeneous parasite population. In this study, we sequence-characterised 26 IIaA15G2R subtype specimens and 26 non-IIaA15G2R subtype specimens from the United States, Canada, United Kingdom and Spain at seven other known polymorphic loci, including CP47, CP56, DZ-HRGP, MSC6-5, MSC6-7, RPGR and ZPT. Extensive heterogeneity within IIaA15G2R1 and discordance in typing results between gp60 and other genetic markers were observed. Results of inter-locus and intra-ZPT linkage disequilibrium and recombination analyses indicated that the heterogeneity within IIaA15G2R1 and discordance in typing results among genetic loci were largely due to the occurrence of genetic recombination, mostly within the gp60 subtype IIaA15G2R1. Although there was no clear population diversion between IIaA15G2R and non-IIaA15G2R subtypes, results of STRUCTURE and F_ST analyses suggested the presence of at least two subpopulations; subpopulation 1 had an epidemic population structure and was widely distributed, whereas subpopulation 2 had a clonal population structure and consisted of geographically segregated multilocus subtypes. Genetic recombination between epidemic and geographically segregated C. parvum populations appeared to be a driving force in the emergence of a hyper-transmissible IIaA15G2R1 subtype. Genetic recombination was observed even between the zoonotic IIa subtype family and anthroponotic subtype family IIc at CP56, MSC6-7 and ZPT. Thus, the IIaA15G2R1 subtype at gp60 is likely a fitness marker for C. parvum and the wide spread of IIaA15G2R1 subtype around the world is probably independent of the sequence characteristics at other genetic loci.     

An SEI model for sarcoptic mange among chamois

We consider a simple model to study the dynamics of sarcoptic mange in a population of chamois. The epidemiological patterns observed during an epidemic in Italy are reconstructed and key parameters of the model are estimated from field data. In particular, we calculate the basic reproductive ratio R ₀, a threshold value for chamois density for the occurrence of an epidemic and the speed of propagation of the epidemic wave. The model is then used to obtain indications on the effect of culling as a possible control measure in a closed population and extended to analyse the spatial diffusion of the epidemic. Our results are in agreement with mange epidemiology and observations, and suggest that intervention could be efficacious in reducing the impact of an epidemic.     

An evolutionary computing approach for parameter estimation investigation of a model for cholera

We consider the problem of using time-series data to inform a corresponding deterministic model and introduce the concept of genetic algorithms (GA) as a tool for parameter estimation, providing instructions for an implementation of the method that does not require access to special toolboxes or software. We give as an example a model for cholera, a disease for which there is much mechanistic uncertainty in the literature. We use GA to find parameter sets using available time-series data from the introduction of cholera in Haiti and we discuss the value of comparing multiple parameter sets with similar performances in describing the data.     

Coupling-induced population synchronization in an excitatory population of subthreshold Izhikevich neurons

We consider an excitatory population of subthreshold Izhikevich neurons which exhibit noise-induced firings. By varying the coupling strength J, we investigate population synchronization between the noise-induced firings which may be used for efficient cognitive processing such as sensory perception, multisensory binding, selective attention, and memory formation. As J is increased, rich types of population synchronization (e.g., spike, burst, and fast spike synchronization) are found to occur. Transitions between population synchronization and incoherence are well described in terms of an order parameter $\mathcal{O}$ . As a final step, the coupling induces oscillator death (quenching of noise-induced spikings) because each neuron is attracted to a noisy equilibrium state. The oscillator death leads to a transition from firing to non-firing states at the population level, which may be well described in terms of the time-averaged population spike rate $\overline{R}$ . In addition to the statistical-mechanical analysis using $\mathcal{O}$ and $\overline{R}$ , each population and individual state are also characterized by using the techniques of nonlinear dynamics such as the raster plot of neural spikes, the time series of the membrane potential, and the phase portrait. We note that population synchronization of noise-induced firings may lead to emergence of synchronous brain rhythms in a noisy environment, associated with diverse cognitive functions.     

Lichenicolous fungi show population subdivision by host species but do not share population history with their hosts

Lichenicolous fungi are a species-rich biological group growing on lichen thalli. Here, we analyze the genetic structure of the lichenicolous basidiomycete Tremella lobariacearum and three host species (Lobaria pulmonaria, Lobaria macaronesica, and Lobaria immixta) in Macaronesia. We used ordination and analysis of molecular variance to investigate the structuring of genetic variation, and a simulation test to investigate whether rDNA haplotypes of T. lobariacearum were significantly associated with host species. To investigate the evolutionary and demographic history of the lichenicolous fungus and its hosts, we used coalescent samplers to generate trees, and Bayesian skyline plots. We found that the hosts were most important in structuring populations of the lichenicolous species. Despite their wide geographic distribution, the same haplotypes of T. lobariacearum consistently associated with a given host species. Our results suggest that the Lobaria hosts create a selective environment for the lichenicolous fungus. Both the pathogen and the host populations exhibited substantial genetic structure. However, evolutionary and demographic histories differed between the parasite and its hosts, as evidenced by different divergence times and tree topologies.     

Process model comparison and transferability across bioreactor scales and modes of operation for a mammalian cell bioprocess

A Monod kinetic model, logistic equation model, and statistical regression model were developed for a Chinese hamster ovary cell bioprocess operated under three different modes of operation (batch, bolus fed‐batch, and continuous fed‐batch) and grown on two different bioreactor scales (3 L bench‐top and 15 L pilot‐scale). The Monod kinetic model was developed for all modes of operation under study and predicted cell density, glucose glutamine, lactate, and ammonia concentrations well for the bioprocess. However, it was computationally demanding due to the large number of parameters necessary to produce a good model fit. The transferability of the Monod kinetic model structure and parameter set across bioreactor scales and modes of operation was investigated and a parameter sensitivity analysis performed. The experimentally determined parameters had the greatest influence on model performance. They changed with scale and mode of operation, but were easily calculated. The remaining parameters, which were fitted using a differential evolutionary algorithm, were not as crucial. Logistic equation and statistical regression models were investigated as alternatives to the Monod kinetic model. They were less computationally intensive to develop due to the absence of a large parameter set. However, modeling of the nutrient and metabolite concentrations proved to be troublesome due to the logistic equation model structure and the inability of both models to incorporate a feed. The complexity, computational load, and effort required for model development has to be balanced with the necessary level of model sophistication when choosing which model type to develop for a particular application. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2013