Amplified immunoassay of human IgG using real-time biomolecular interaction analysis (BIA) technology

An automated biomolecular interaction analysis instrument (BI-Acore) based on surface plasmon resonance (SPR) has been used to determine human immunoglobulin G (IgG) in real time. Polyclonal anti-human IgG antibody was covalently immobilized to a carboxymethyldextran modified gold film surface. The samples of human IgG prepared in HBS buffer were poured over the immobilized surface. The signal amplification antibody was applied to amplify the response signal. After each measurement, the surface was regenerated with 0.1 mol/L H3PO4. The assay was rapid, requiring only 30 min for antibody immobilization and 20 min for each subsequent process of immune binding, antibody amplification and regeneration. The antibody immobilized surface had good response to human IgG in the range of 0.12-60 nmol/L with a detection limit of 60 pmol/L. The same antibody immobilized surface could be used for more than 110 cycles of binding, amplification and regeneration. The results demonstrate that the sensitivity, specificity and reproducibility of amplified immunoassay using real-time BIA technology are satisfactory.

Layer-by-layer assembly of multilayer films composed of streptavidin and biotinylated antibody by real-time biomolecular interaction analysis

Layer-by-layer assembly of multilayer films of streptavidin and biotinylated antibody was completed on the streptavidin coated surface. Real-time biomolecular interaction analysis (BIA) based on surface plasmon resonance technique was used to monitor the multilayer assembly in solution continuously. The results indicate that the uniform multilayer film can be fabricated successfully based on the strong interaction between streptavidin and biotin. The mean surface mass concentration of each adsorption layer is 1. 32 ng/mm(2) for biotinylated antibody, 2. 93 ng/mm(2) for streptavidin, according to the correlation of SPR response with surface concentration.

Fluid-structure interaction analysis of full scale vehicle-barrier impact using coupled SPH-FEA

Portable water-filled barriers (PWFB) are roadside structures used to separate moving traffic from work-zones. Numerical PWFB modelling is preferred in the design stages prior to actual testing. This paper aims to study the fluid-structure interaction of PWFB under vehicular impact using several methods. The strategy to treat water as non-structural mass was proposed and the errors were investigated. It was found that water can be treated with the FEA-NSM model for velocities higher than 80kmh-1. However, full SPH/FEA model is still the best treatment for water and necessary for lower impact velocities. The findings in this paper can be used as guidelines for modelling and designing PWFB.

Fluid-structure interaction analysis by coupled FE-SPH model based on a novel searching algorithm

Fluid–Structure Interaction (FSI) problem is significant in science and engineering, which leads to challenges for computational mechanics. The coupled model of Finite Element and Smoothed Particle Hydrodynamics (FE-SPH) is a robust technique for simulation of FSI problems. However, two important steps of neighbor searching and contact searching in the coupled FE-SPH model are extremely time-consuming. Point-In-Box (PIB) searching algorithm has been developed by Swegle to improve the efficiency of searching. However, it has a shortcoming that efficiency of searching can be significantly affected by the distribution of points (nodes in FEM and particles in SPH). In this paper, in order to improve the efficiency of searching, a novel Striped-PIB (S-PIB) searching algorithm is proposed to overcome the shortcoming of PIB algorithm that caused by points distribution, and the two time-consuming steps of neighbor searching and contact searching are integrated into one searching step. The accuracy and efficiency of the newly developed searching algorithm is studied on by efficiency test and FSI problems. It has been found that the newly developed model can significantly improve the computational efficiency and it is believed to be a powerful tool for the FSI analysis.

Genome-wide interaction analysis reveals replicated epistatic effects on brain structure

The discovery of several genes that affect the risk for Alzheimer's disease ignited a worldwide search for single-nucleotide polymorphisms (SNPs), common genetic variants that affect the brain. Genome-wide search of all possible SNP-SNP interactions is challenging and rarely attempted because of the complexity of conducting approximately 1011 pairwise statistical tests. However, recent advances in machine learning, for example, iterative sure independence screening, make it possible to analyze data sets with vastly more predictors than observations. Using an implementation of the sure independence screening algorithm (called EPISIS), we performed a genome-wide interaction analysis testing all possible SNP-SNP interactions affecting regional brain volumes measured on magnetic resonance imaging and mapped using tensor-based morphometry. We identified a significant SNP-SNP interaction between rs1345203 and rs1213205 that explains 1.9% of the variance in temporal lobe volume. We mapped the whole brain, voxelwise effects of the interaction in the Alzheimer's Disease Neuroimaging Initiative data set and separately in an independent replication data set of healthy twins (Queensland Twin Imaging). Each additional loading in the interaction effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both Alzheimer's Disease Neuroimaging Initiative and Queensland Twin Imaging samples.

Interaction analysis of strip footing resting on a non-homogeneous elastic medium

In this paper, a plane stress solution for the interaction analysis of strip footing resting on (i) a non-homogeneous elastic half-plane and (ii) a non-homogeneous elastic layer resting on a rigid stratum has been presented. The analysis has been done using a combined analytical and FEM method in which the discretization of the half-plane is not required and thereby minimizes the computational efforts considerably. The contact pressure distribution and the settlement profile for the selected cases of varying modulus half-plane, which has more relevance to foundation engineering, have been given. Experimental verification through a photoelastic method of stress analysis has been carried out for the case of footing on Gibson elastic half-plane, and the contact pressure distribution thus obtained has been compared with the theoretical results. Copyright (C) 1996 Elsevier Science Ltd

Kinetic analysis of TNF immune complex by using surface plasmon resonane

The kinetic analysis of the interaction between tumor necrosis factor(TNF) and its monoclonal antibody was performed by surface plasmon resonance(SPR) technique. The monoclonal antibody was immobilized to the surface of CM5 sensor chip by amine coupling. TNF at different concentrations was injected across the mAb immobilized surface. The interaction was recorded in real time and could be seen on the sensorgram. One cycle, including association, dissociation and regeneration, lasted no more than 15 min. The interaction results was evaluated using 1 : 1 Langmuir binding model. The kinetic rate constants were calculated to be: k =1.68 X 10(3) L (.) mol(-1) (.) s(-1), k(d) = 1.73 X 10(-4) s(-1), and the affinity constants K-A = 9. 7 X 10(3) L (.) mol(-1), K-r)= 1. 03 X 10(-7) Mol (.) L-1. The X-2 was 3.47, which showed that the interaction is consistent with the 1 : I model. We can see from the results that although there are two binding sites in one mAb molecule, TNF reacts with each site in an independent and noncooperative manner.

The development of a Flanders Interaction Analysis style instrument for use in educational computer mediated communication research

Please consult the paper edition of this thesis to read. It is available on the 5th Floor of the Library at Call Number: Z 9999 E38 D56 1992

Biomolecular interaction analysis in functional proteomics

In der funktionellen Proteomforschung werden bekannte Interaktionen eines zellulären Netzwerkes qualitativ untersucht. Diese Veröffentlichung beschreibt verschiedene biomolekulare Interaktionsanalysen, anhand des Modellsystems PKA, die zur detaillierten Charakterisierung von Bindungen herangezogen werden können. Neben den Gleichgewichtsbindungsdaten (generiert aus AlphaScreen, FP, SPR und ITC Messungen) wurden aus ITC Messungen die thermodynamischen Parameter G, H und S ermittelt. Durch Anwendung der BRET2 (Bioluminescence resonance energy transfer) Methode konnten in lebenden Zellen Aussagen über Bindungsereignisse und deren Lokalisation getroffen werden.

Structure, Dynamics, and RNA Interaction Analysis of the Human SBDS Protein

Shwachman-Bodian-Diamond syndrome is an autosomal recessive genetic syndrome with pleiotropic phenotypes, including pancreatic deficiencies, bone marrow dysfunctions with increased risk of myelodysplasia or leukemia, and skeletal abnormalities. This syndrome has been associated with mutations in the SBDS gene, which encodes a conserved protein showing orthologs in Archaea and eukaryotes. The Shwachman-Bodian-Diamond syndrome pleiotropic phenotypes may be an indication of different cell type requirements for a fully functional SBDS protein. RNA-binding activity has been predicted for archaeal and yeast SBDS orthologs, with the latter also being implicated in ribosome biogenesis. However, full-length SBDS orthologs function in a species-specific manner, indicating that the knowledge obtained from model systems may be of limited use in understanding major unresolved issues regarding SBDS function, namely, the effect of mutations in human SBDS on its biochemical function and the specificity of RNA interaction. We determined the solution structure and backbone dynamics of the human SBDS protein and describe its RNA binding site using NMR spectroscopy. Similarly to the crystal structures of Archaea, the overall structure of human SBDS comprises three well-folded domains. However, significant conformational exchange was observed in NMR dynamics experiments for the flexible linker between the N-terminal domain and the central domain, and these experiments also reflect the relative motions of the domains. RNA titrations monitored by heteronuclear correlation experiments and chemical shift mapping analysis identified a classic RNA binding site at the N-terminal FYSH (fungal, Yhr087wp, Shwachman) domain that concentrates most of the mutations described for the human SBDS. (C) 2010 Elsevier Ltd. All rights reserved.

A 2D BEM-FEM approach for time harmonic fluid-structure interaction analysis of thin elastic bodies.

[EN]This paper deals with two-dimensional time harmonic fluid-structure interaction problems when the fluid is at rest, and the elastic bodies have small thicknesses. A BEM-FEM numerical approach is used, where the BEM is applied to the fluid, and the structural FEM is applied to the thin elastic bodies.

A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

Genome-wide gene-gene interaction analysis for cardiovascular disease

Numerous studies have been carried out to try to better understand the genetic predisposition for cardiovascular disease. Although it is widely believed that multifactorial diseases such as cardiovascular disease is the result from effects of many genes which working alone or interact with other genes, most genetic studies have been focused on identifying of cardiovascular disease susceptibility genes and usually ignore the effects of gene-gene interactions in the analysis. The current study applies a novel linkage disequilibrium based statistic for testing interactions between two linked loci using data from a genome-wide study of cardiovascular disease. A total of 53,394 single nucleotide polymorphisms (SNPs) are tested for pair-wise interactions, and 8,644 interactions are found to be significant with p-values less than 3.5×10-11. Results indicate that known cardiovascular disease susceptibility genes tend not to have many significantly interactions. One SNP in the CACNG1 (calcium channel, voltage-dependent, gamma subunit 1) gene and one SNP in the IL3RA (interleukin 3 receptor, alpha) gene are found to have the most significant pair-wise interactions. Findings from the current study should be replicated in other independent cohort to eliminate potential false positive results.^