Rapid temperature-dependent antibody ranking using Biacore A100

The ability to select antibodies with stable thermodynamic profiles can greatly enhance the performance of point-of-care (POC) devices allowing reproducible “on-the-spot” analysis for markers of clinical and environmental relevance. We show that by ranking antibodies based on their kinetic profiles at two different temperatures, greater information content is acquired, facilitating the selection of antibodies with desired binding characteristics. Observed binding patterns highlight the importance of temperature to assay design, which should be fully taken into consideration to ensure that the appropriate antibody is selected for the desired test.     

A mathematical algorithm for ECG signal denoising using window analysis

BACKGROUND: The presence of parasite interference signals could cause serious problems in the registration of ECG signals and many works have been done to suppress electromyogram (EMG) artifacts noises and disturbances from electrocardiogram (ECG). Recently, new developed techniques based on global and local transforms have become popular such as wavelet shrinkage approaches (1995) and time-frequency dependent threshold (1998). Moreover, other techniques such as artificial neural networks (2003), energy thresholding and Gaussian kernels (2006) are used to improve previous works. This review summarizes windowed techniques of the concerned issue. METHODS AND RESULTS: We conducted a mathematical method based on two sets of information, which are dominant scale of QRS complexes and their domain. The task is proposed by using a varying-length window that is moving over the whole signals. Both the high frequency (noise) and low frequency (base-line wandering) removal tasks are evaluated for manually corrupted ECG signals and are validated for actual recorded ECG signals. CONCLUSIONS: Although, the simplicity of the method, fast implementation, and preservation of characteristics of ECG waves represent it as a suitable algorithm, there may be some difficulties due to pre-stage detection of QRS complexes and specification of algorithm's parameters for varying morphology cases.     

Label-free primary screening and affinity ranking of fragment libraries using parallel analysis of protein panels

The authors present fragment screening data obtained using a label-free parallel analysis approach where the binding of fragment library compounds to 4 different target proteins can be screened simultaneously using surface plasmon resonance detection. They suggest this method as a first step in fragment screening to identify and select binders, reducing the demanding requirements on subsequent X-ray or nuclear magnetic resonance studies, and as a valuable "clean-up" tool to eliminate unwanted promiscuous binders from libraries. A small directed fragment library of known thrombin binders and a general 500-compound fragment library were used in this study. Thrombin, blocked thrombin, carbonic anhydrase, and glutathione-S-transferase were immobilized on the sensor chip surface, and the direct binding of the fragments was studied in real time. Only 12 microg of each protein is needed for screening of a 3000-compound fragment library. For screening, a binding site-blocked target as reference facilitates the identification of binding site-selective hits and the signals from other reference proteins for the elimination of false positives. The scope and limitations of this screening approach are discussed for both target-directed and general fragment libraries.     

Linkage analysis of alcohol dependence using both affected and discordant sib pairs

The basic idea of affected-sib-pair (ASP) linkage analysis is to test whether the inheritance pattern of a marker deviates from Mendelian expectation in a sample of ASPs. The test depends on an assumed Mendelian control distribution of the number of marker alleles shared identical by descent (IBD), i.e., 1/4, 1/2, and 1/4 for 2, 1, and 0 allele(s) IBD, respectively. However, Mendelian transmission may not always hold, for example because of inbreeding or meiotic drive at the marker or a nearby locus. A more robust and valid approach is to incorporate discordant-sib-pairs (DSPs) as controls to avoid possible false-positive results. To be robust to deviation from Mendelian transmission, here we analyzed Collaborative Study on the Genetics of Alcoholism data by modifying the ASP LOD score method to contrast the estimated distribution of the number of allele(s) shared IBD by ASPs with that by DSPs, instead of with the expected distribution under the Mendelian assumption. This strategy assesses the difference in IBD sharing between ASPs and the IBD sharing between DSPs. Further, it works better than the conventional LOD score ASP linkage method in these data in the sense of avoiding false-positive linkage evidence.     

AGRA: analysis of gene ranking algorithms

Often, the most informative genes have to be selected from different gene sets and several computer gene ranking algorithms have been developed to cope with the problem. To help researchers decide which algorithm to use, we developed the analysis of gene ranking algorithms (AGRA) system that offers a novel technique for comparing ranked lists of genes. The most important feature of AGRA is that no previous knowledge of gene ranking algorithms is needed for their comparison. Using the text mining system finding-associated concepts with text analysis. AGRA defines what we call biomedical concept space (BCS) for each gene list and offers a comparison of the gene lists in six different BCS categories. The uploaded gene lists can be compared using two different methods. In the first method, the overlap between each pair of two gene lists of BCSs is calculated. The second method offers a text field where a specific biomedical concept can be entered. AGRA searches for this concept in each gene lists' BCS, highlights the rank of the concept and offers a visual representation of concepts ranked above and below it. AVAILABILITY AND IMPLEMENTATION: Available at http://agra.fzv.uni-mb.si/, implemented in Java and running on the Glassfish server. CONTACT: simon.kocbek@uni-mb.si.     

Genetic analysis of growth curves using the SAEM algorithm

The analysis of nonlinear function-valued characters is very important in genetic studies, especially for growth traits of agricultural and laboratory species. Inference in nonlinear mixed effects models is, however, quite complex and is usually based on likelihood approximations or Bayesian methods. The aim of this paper was to present an efficient stochastic EM procedure, namely the SAEM algorithm, which is much faster to converge than the classical Monte Carlo EM algorithm and Bayesian estimation procedures, does not require specification of prior distributions and is quite robust to the choice of starting values. The key idea is to recycle the simulated values from one iteration to the next in the EM algorithm, which considerably accelerates the convergence. A simulation study is presented which confirms the advantages of this estimation procedure in the case of a genetic analysis. The SAEM algorithm was applied to real data sets on growth measurements in beef cattle and in chickens. The proposed estimation procedure, as the classical Monte Carlo EM algorithm, provides significance tests on the parameters and likelihood based model comparison criteria to compare the nonlinear models with other longitudinal methods.     

Patients' ranking of therapeutic factors in group analysis

The aim of this research is to assess which therapeutic factors are of greatest importance to patients in group analytic psychotherapy, and whether the patients' characteristics and the phase of the group process influenced their evaluation of therapeutic factors. The Yalom's group therapeutic factors questionnaire was filled out by 66 patients, members of small groups conducted according to group analytic principles. The average scores for each therapeutic factor were subsequently ranked by importance to the patients and related to their age, sex, education, previous psychotherapeutic experience and phase of group process. Self-understanding was the highest-ranking therapeutic factor for the patients (average score 21.32 +/- 0.04 out of 25 maximum), whereas identification was the lowest ranking factor (15.88 +/- 0.06 in average). Group therapeutic factors were scored higher by women, patients up to 30 years of age, high-school graduates, and those with previous psychotherapeutic experience. Self-understanding seems to be the most important therapeutic factor in group analysis, emphasizing the importance of appropriate selection of patients for group analysis in order to utilize therapeutic factors the best.     

Allosteric effectors influence the tetramer stability of both R- and T-states of hemoglobin A

The contribution of heterotropic effectors to hemoglobin allostery is still not completely understood. With the recently proposed global allostery model, this question acquires crucial significance, because it relates tertiary conformational changes to effector binding in both the R- and T-states. In this context, an important question is how far the induced conformational changes propagate from the binding site(s) of the allosteric effectors. We present a study in which we monitored the interdimeric interface when the effectors such as Cl-, 2,3-diphosphoglycerate, inositol hexaphosphate, and bezafibrate were bound. We studied oxy-Hb and a hybrid form (alphaFeO2)2-(betaZn)2 as the T-state analogue by monitoring heme absorption and Trp intrinsic fluorescence under hydrostatic pressure. We observed a pressure-dependent change in the intrinsic fluorescence, which we attribute to a pressure-induced tetramer to dimer transition with characteristic pressures in the 70-200-megapascal range. The transition is sensitive to the binding of allosteric effectors. We fitted the data with a simple model for the tetramer-dimer transition and determined the dissociation constants at atmospheric pressure. In the R-state, we observed a stabilizing effect by the allosteric effectors, although in the T-analogue a stronger destabilizing effect was seen. The order of efficiency was the same in both states, but with the opposite trend as inositol hexaphosphate > 2,3-diphosphoglycerate > Cl-. We detected intrinsic fluorescence from bound bezafibrate that introduced uncertainty in the comparison with other effectors. The results support the global allostery model by showing that conformational changes propagate from the effector binding site to the interdimeric interfaces in both quaternary states.     

A sampling algorithm for segregation analysis

Methods for detecting Quantitative Trait Loci (QTL) without markers have generally used iterative peeling algorithms for determining genotype probabilities. These algorithms have considerable shortcomings in complex pedigrees. A Monte Carlo Markov chain (MCMC) method which samples the pedigree of the whole population jointly is described. Simultaneous sampling of the pedigree was achieved by sampling descent graphs using the Metropolis-Hastings algorithm. A descent graph describes the inheritance state of each allele and provides pedigrees guaranteed to be consistent with Mendelian sampling. Sampling descent graphs overcomes most, if not all, of the limitations incurred by iterative peeling algorithms. The algorithm was able to find the QTL in most of the simulated populations. However, when the QTL was not modeled or found then its effect was ascribed to the polygenic component. No QTL were detected when they were not simulated.     

High-throughput affinity ranking of antibodies using surface plasmon resonance microarrays

A method was developed to rapidly identify high-affinity human antibodies from phage display library selection outputs. It combines high-throughput Fab fragment expression and purification with surface plasmon resonance (SPR) microarrays to determine kinetic constants (kon and koff) for 96 different Fab fragments in a single experiment. Fabs against human tissue kallikrein 1 (hK1, KLK1 gene product) were discovered by phage display, expressed in Escherichia coli in batches of 96, and purified using protein A PhyTip columns. Kinetic constants were obtained for 191 unique anti-hK1 Fabs using the Flexchip SPR microarray device. The highest affinity Fabs discovered had dissociation constants of less than 1 nM. The described SPR method was also used to categorize Fabs according to their ability to recognize an apparent active site epitope. The ability to rapidly determine the affinities of hundreds of antibodies significantly accelerates the discovery of high-affinity antibody leads.     

Feature selection for splice site prediction: A new method using EDA-based feature ranking

Background  

The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data.     

Empirical evaluation of data transformations and ranking statistics for microarray analysis

There are many options in handling microarray data that can affect study conclusions, sometimes drastically. Working with a two-color platform, this study uses ten spike-in microarray experiments to evaluate the relative effectiveness of some of these options for the experimental goal of detecting differential expression. We consider two data transformations, background subtraction and intensity normalization, as well as six different statistics for detecting differentially expressed genes. Findings support the use of an intensity-based normalization procedure and also indicate that local background subtraction can be detrimental for effectively detecting differential expression. We also verify that robust statistics outperform t-statistics in identifying differentially expressed genes when there are few replicates. Finally, we find that choice of image analysis software can also substantially influence experimental conclusions.     

A quantitative determination of multi-protein interactions by the analysis of confocal images using a pixel-by-pixel assessment algorithm

MOTIVATION: Recent advances in confocal microscopy have allowed scientists to assess the expression, and to some extent, the interaction/colocalization of multiple molecules within cells and tissues. In some instances, accurately quantifying the colocalization of two or more proteins may be critical. This can require the acquisition of multiple Z plane images (Z stacks) throughout a specimen and, as such, we report here the successful development of a freeware, open-source image analysis tool, IMAJIN_COLOC, developed in PERL (v. 5.8, build 806), using the PERLMagick libraries (ImageMagick). Using a pixel-by-pixel analysis algorithm, IMAJIN_COLOC can analyze images for antigen expression (any number of colors) and can measure all possible combinations of colocalization for up to three colors by analyzing a Z stack gallery acquired for each sample. The simultaneous (i.e. in a single pass) analysis of three-color colocalization, and batch analysis capabilities are distinctive features of this program. RESULTS: A control image, containing known individual and colocalized pixel counts, was used to validate the accuracy of IMAJIN_COLOC. As further validation, pixel counts and colocalization values from the control image were compared to those obtained with the software packaged with the Zeiss laser-scanning microscope (LSM AIM, version 3.2). The values from both programs were found to be identical. To demonstrate the applicability of this program in addressing novel biological questions, we examined the role of neurons in eliciting an immune reaction in response to viral infection. Specifically, we successfully examined expression of the chemokine RANTES in measles virus (MV) infected hippocampal neurons and quantified changes in RANTES production throughout the disease period. The resultant quantitative data were also evaluated visually, using a gif image created during the analysis. AVAILABILITY: PERL (ActivePerl, version 5.8) is available at activestate.com; the PERLMagick libraries are available at imagemagick.org, and IMAJIN_COLOC, the source code and user documentation can be downloaded from http://www.fda.gov/cber/research/imaging/imageanalysis.htm.     

Pyrolysis characteristics and kinetics of Arundo donax using thermogravimetric analysis

The increase of the price of fossil means, as well as their programmed disappearing, contributed to increase among appliances based on biomass and energy crops. The thermal behavior of Arundo donax by thermogravimetric analysis was studied under inert atmosphere at heating rates ranging from 5 to 20 °C min⁻¹ from room temperature to 750 °C. Gaseous emissions as CO₂, CO and volatile organic compounds (VOC) were measured and global kinetic parameters were determined during pyrolysis with the study of the influence of the heating rate. The thermal process describes two main phases. The first phase named active zone, characterizes the degradation of hemicellulose and cellulose polymers. It started at low temperature (200 °C) comparatively to wood samples and was finished at 350 °C. The pyrolysis of the lignin polymer occurred during the second phase from 350 to 750 °C, named passive zone. Carbon oxides are emitted during the active zone whereas VOC are mainly formed during the passive zone. Mass losses, mass loss rates and emission factors were strongly affected by the variation of the heating rate in the active zone. It was found that the global pyrolysis of A. donax can be satisfactorily described using global independent reactions model for hemicellulose and cellulose in the active zone. The activation energy for hemicellulose was not affected by a variation of the heating rate with a value close to 110 kJ mol⁻¹ and presented a reaction order close to 0.5. An increase of the heating rate decreased the activation energy of the cellulose. However, a first reaction order was observed for cellulose decomposition. The experimental results and kinetic parameters may provide useful data for the design of pyrolytic processing system using A. donax as feedstock.