Tools and techniques to study ligand-receptor interactions and receptor activation by TNF superfamily members.

Ligands and receptors of the TNF superfamily are therapeutically relevant targets in a wide range of human diseases. This chapter describes assays based on ELISA, immunoprecipitation, FACS, and reporter cell lines to monitor interactions of tagged receptors and ligands in both soluble and membrane-bound forms using unified detection techniques. A reporter cell assay that is sensitive to ligand oligomerization can identify ligands with high probability of being active on endogenous receptors. Several assays are also suitable to measure the activity of agonist or antagonist antibodies, or to detect interactions with proteoglycans. Finally, self-interaction of membrane-bound receptors can be evidenced using a FRET-based assay. This panel of methods provides a large degree of flexibility to address questions related to the specificity, activation, or inhibition of TNF-TNF receptor interactions in independent assay systems, but does not substitute for further tests in physiologically relevant conditions.

GeoKernels: Modeling of Spatial Data on GeoManifolds

This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental data modeling on natural manifolds, such as complex topographies of the mountainous regions, where environmental processes are highly influenced by the relief. These relations, possibly regionalized and nonlinear, can be modeled from data with machine learning using the digital elevation models in semi-supervised kernel methods. The range of the tools and methodological issues discussed in the study includes feature selection and semisupervised Support Vector algorithms. The real case study devoted to data-driven modeling of meteorological fields illustrates the discussed approach.

Microparticles in stored red blood cells: an approach using flow cytometry and proteomic tools.

BACKGROUND AND OBJECTIVES: Microparticles (MPs) are small phospholipid vesicles of less than 1 microm, shed in blood flow by various cell types. These MPs are involved in several biological processes and diseases. MPs have also been detected in blood products; however, their role in transfused patients is unknown. The purpose of this study was to characterize those MPs in blood bank conditions. MATERIALS AND METHODS: Qualitative and quantitative experiments using flow cytometry or proteomic techniques were performed on MPs derived from erythrocytes concentrates. In order to count MPs, they were either isolated by various centrifugation procedures or counted directly in erythrocyte concentrates. RESULTS: A 20-fold increase after 50 days of storage at 4 degrees C was observed (from 3370 +/- 1180 MPs/microl at day 5 to 64 850 +/- 37 800 MPs/microl at day 50). Proteomic analysis revealed changes of protein expression comparing MPs to erythrocyte membranes. Finally, the expression of Rh blood group antigens was shown on MPs generated during erythrocyte storage. CONCLUSIONS: Our work provides evidence that storage of red blood cell is associated with the generation of MPs characterized by particular proteomic profiles. These results contribute to fundamental knowledge of transfused blood products.

Individual Classification of Mild Cognitive Impairment Subtypes by Support Vector Machine Analysis of White Matter DTI.

BACKGROUND AND PURPOSE: MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI. MATERIALS AND METHODS: Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs. RESULTS: The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI. CONCLUSIONS: Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.

Expanding molecular modeling and design tools to non-natural sidechains.

Protein-protein interactions encode the wiring diagram of cellular signaling pathways and their deregulations underlie a variety of diseases, such as cancer. Inhibiting protein-protein interactions with peptide derivatives is a promising way to develop new biological and therapeutic tools. Here, we develop a general framework to computationally handle hundreds of non-natural amino acid sidechains and predict the effect of inserting them into peptides or proteins. We first generate all structural files (pdb and mol2), as well as parameters and topologies for standard molecular mechanics software (CHARMM and Gromacs). Accurate predictions of rotamer probabilities are provided using a novel combined knowledge and physics based strategy. Non-natural sidechains are useful to increase peptide ligand binding affinity. Our results obtained on non-natural mutants of a BCL9 peptide targeting beta-catenin show very good correlation between predicted and experimental binding free-energies, indicating that such predictions can be used to design new inhibitors. Data generated in this work, as well as PyMOL and UCSF Chimera plug-ins for user-friendly visualization of non-natural sidechains, are all available at http://www.swisssidechain.ch. Our results enable researchers to rapidly and efficiently work with hundreds of non-natural sidechains.

Informing the judgments of fingerprint analysts using quality metric and statistical assessment tools

The aim of this research was to evaluate how fingerprint analysts would incorporate information from newly developed tools into their decision making processes. Specifically, we assessed effects using the following: (1) a quality tool to aid in the assessment of the clarity of the friction ridge details, (2) a statistical tool to provide likelihood ratios representing the strength of the corresponding features between compared fingerprints, and (3) consensus information from a group of trained fingerprint experts. The measured variables for the effect on examiner performance were the accuracy and reproducibility of the conclusions against the ground truth (including the impact on error rates) and the analyst accuracy and variation for feature selection and comparison.¦The results showed that participants using the consensus information from other fingerprint experts demonstrated more consistency and accuracy in minutiae selection. They also demonstrated higher accuracy, sensitivity, and specificity in the decisions reported. The quality tool also affected minutiae selection (which, in turn, had limited influence on the reported decisions); the statistical tool did not appear to influence the reported decisions.

Nuclear well logging in soils. Calibration of slim hole nuclear tools gamma-gamma and neutron-thermal neutron.

The calculation of elasticity parameters by sonic and ultra sonic wave propagation in saturated soils using Biot's theory needs the following variables : forpiation density and porosity (p, ø), compressional and shear wave velocities (Vp, Vs), fluid density, viscosity and compressibility (Pfi Ilfi Ki), matrix density and compressibility (p" K), The first four parameters can be determined in situ using logging probes. Because fluid and matrix characteristics are not modified during core extraction, they can be obtained through laboratory measurements. All parameters necessitate precise calibrations in various environments and for specific range of values encountered in soils. The slim diameter of boreholes in shallow geophysics and the high cost of petroleum equipment demand the use of specific probes, which usually only give qualitative results. The measurement 'of density is done with a gamma-gamma probe and the measurement of hydrogen index, in relation to porosity, by a neutron probe. The first step of this work has been carried out in synthetic formations in the laboratory using homogeneous media of known density and porosity. To establish borehole corrections different casings have been used. Finally a comparison between laboratory and in situ data in cored holes of known geometry and casing has been performed.