Characterisation of combinatorial libraries of mucin-2 antigen peptides by high-resolution mass spectrometry

An epitope motif, TX(1)TX(2)T, of mucin-2 glycoprotein was identified by means of a mucin-2-specific monoclonal antibody, mAb 994, raised against a synthetic mucin-derived 15-mer peptide conjugate. For determination of the epitope sequence recognised with highest affinity by mAb 994, a combinatorial approach was applied using the portioning-mixing technique excluding Cys. Antibody binding of libraries was most profound when Gln was at the X(1) position. Analytical characterisation of the TQTX(2)T library was conducted by amino acid analysis and matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) and electrospray ionisation Fourier transform ion cyclotron resonance (ESI-FTICR) mass spectrometric methods. Control libraries were prepared by mixing 19 individual peptides corresponding to the TQTX(2)T sequence. Thus, mixtures of 6, 10 and 19 pentapeptides were analysed and compared with the combinatorial mixture. MALDI-TOFMS was able to detect only partially the components in the 6- and 10-member mixtures, but failed to characterise a more complex 19-member mixture. In contrast, ESI-FTICRMS resolved all mixtures of higher complexity and provided direct identification at monoisotopic resolution, such as for a peptide library containing 'isobaric' lysine and glutamine (Delta m = 0.0364 Da). The results of this study suggest that ESI-FTICRMS is a powerful tool for characterisation of combinatorial peptide libraries of higher complexity.     

Dynamics of self-assembled chaining in magnetorheological fluids

The aggregation dynamics of paramagnetic spherical particles embedded in a viscous fluid is investigated via numerical simulations using a fully coupled three-dimensional model. Particles experience simultaneously Brownian motion, dipolar magnetic attraction, and multibody hydrodynamic interactions. When the dipole strength characterizing the ratio of magnetic attraction to random diffusion exceeds a critical value, particles join together forming supraparticle structures. As time evolves, particle/chain and chain/ chain interactions lead to a continuous increase of the cluster size. The mean length of particle chains has a power-law dependence with respect to time, as predicted by the theory of diffusion-limited aggregation. Both the exponent and the characteristic time scale agree very well with the experimental results of Promislow et al.     

Planar Chromatographic and Electrophoretic Study of Thermally Induced Conformational Modifications of Protein Structure

JPC – Journal of Planar Chromatography – Modern TLC -     

A convergence study of a new partitioned fluid–structure interaction algorithm based on fictitious mass and damping

We develop, analyze and validate a new method for simulating fluid–structure interactions (FSIs), which is based on fictitious mass and fictitious damping in the structure equation. We employ a partitioned method for the fluid and structure motions in conjunction with sub-iteration and Aitken relaxation. In particular, the use of such fictitious parameters requires sub-iterations in order to reduce the induced error in addition to the local temporal truncation error. To this end, proper levels of tolerance for terminating the sub-iteration procedure have been obtained in order to recover the formal order of temporal accuracy. For the coupled FSI problem, these fictitious terms have a significant effect, leading to better convergence rate and hence substantially smaller number of sub-iterations. Through analysis we identify the proper range of these parameters, which we then verify by corresponding numerical tests. We implement the method in the context of spectral element discretization, which is more sensitive than low-order methods to numerical instabilities arising in the explicit FSI coupling. However, the method we present here is simple and general and hence applicable to FSI based on any other discretization. We demonstrate the effectiveness of the method in applications involving 2D vortex-induced vibrations (VIV) and in 3D flexible arteries with structural density close to blood density. We also present 3D results for a patient-specific aneurysmal flow under pulsatile flow conditions examining, in particular, the sensitivity of the results on different values of the fictitious parameters.     

Adaptive ANOVA decomposition of stochastic incompressible and compressible flows

Realistic representation of stochastic inputs associated with various sources of uncertainty in the simulation of fluid flows leads to high dimensional representations that are computationally prohibitive. We investigate the use of adaptive ANOVA decomposition as an effective dimension–reduction technique in modeling steady incompressible and compressible flows with nominal dimension of random space up to 100. We present three different adaptivity criteria and compare the adaptive ANOVA method against sparse grid, Monte Carlo and quasi-Monte Carlo methods to evaluate its relative efficiency and accuracy. For the incompressible flow problem, the effect of random temperature boundary conditions (modeled as high-dimensional stochastic processes) on the Nusselt number is investigated for different values of correlation length. For the compressible flow, the effects of random geometric perturbations (simulating random roughness) on the scattering of a strong shock wave is investigated both analytically and numerically. A probabilistic collocation method is combined with adaptive ANOVA to obtain both incompressible and compressible flow solutions. We demonstrate that for both cases even draconian truncations of the ANOVA expansion lead to accurate solutions with a speed-up factor of three orders of magnitude compared to Monte Carlo and at least one order of magnitude compared to sparse grids for comparable accuracy.     

Dynamic and rheological properties of soft biological cell suspensions

Quantifying dynamic and rheological properties of suspensions of soft biological particles such as vesicles, capsules, and red blood cells (RBCs) is fundamentally important in computational biology and biomedical engineering. In this review, recent studies on dynamic and rheological behavior of soft biological cell suspensions by computer simulations are presented, considering both unbounded and confined shear flow. Furthermore, the hemodynamic and hemorheological characteristics of RBCs in diseases such as malaria and sickle cell anemia are highlighted.     

Evaluation of Pesticide Contamination of Ground Water in Two Agricultural Areas of Portugal

In two Portuguese agricultural areas, "Beira Litoral" and "Ribatejo e Oeste", several pesticides regularly applied in vineyards, maize, potato, tomato for industry, apple, pear and rice were detected in ground water. Atrazine was the most frequently detected, being found in 70% of the total of 79 sites selected in the year 2000, followed by its metabolites desethylatrazine and desisopropylatrazine with frequencies of detection, respectively, of 56% and 48% and by simazine (37%), alachlor (25%), metolachlor (24%) and metribuzin (15%). Other pesticides and metabolites i.e. 3,4-dichloroaniline, dimethoate, f and g -endosulfan, lindane, molinate and prometryn were also detected but at lower occurrences. Pesticides were detected mainly in ground water wells used for irrigation purposes, although in some locations they were also found in water wells used for human consumption. In this study, it was also observed a seasonal variation of pesticide residues in ground water of shallow and deep wells.