Modelització de les propietats òptiques de partícules metàl•liques en matriu dielèctrica

En el marc del projecte "Modelització de les propietats òptiques de partícules metàl•liques en matriu dielèctrica" s'han desenvolupat un conjunt d'eines numèriques que permeten avançar en l'ús de l'espectroscòpia òptica per a l'obtenció d'informació morfològica de materials compostos consistents en partícules metàl•liques en matriu dielèctrica. S'han implementat esquemes numèrics per a calcular les propietats òptiques de materials compostos on les partícules poden presentar una distribució de mides i formes i diferent graus d'ordenament espacial. Les simulacions s'han realitzat a dos nivells: i) amb l’aproximació quasi-estàtica, que permet descriure el comportament d'aquests materials en termes de constants òptiques efectives i ii) amb càlculs electrodinàmics exactes, que han servit per avaluar la validesa de l’aproximació anterior i que han permès d'estudiar la interacció de partícules amb feixos de llum focalitzats o amb polarització no homogènia. A través de l’anàlisi d'aquestes simulacions, s'han desenvolupat models senzills que permeten parametritzar la influència de diferents quantitats físiques en el comportament òptic del material. Aquests models s'han implementat en un programari de càlcul que permeten trobar el valor òptim dels paràmetres físics d'interès mitjançant l'ajust d'espectres òptics. Els models s'han avaluat amb l'anàlisi de dades experimentals subministrades per altres laboratoris.

Causality and endogeneity: Problems and solutions

Most leadership and management researchers ignore one key design and estimation problem rendering parameter estimates uninterpretable: Endogeneity. We discuss the problem of endogeneity in depth and explain conditions that engender it using examples grounded in the leadership literature. We show how consistent causal estimates can be derived from the randomized experiment, where endogeneity is eliminated by experimental design. We then review the reasons why estimates may become biased (i.e., inconsistent) in non-experimental designs and present a number of useful remedies for examining causal relations with non-experimental data. We write in intuitive terms using nontechnical language to make this chapter accessible to a large audience.

Knowledge management for systems biology a general and visually driven framework applied to translational medicine

Background: To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results: To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions: We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

Domain shuffling in a sensor protein contributed to the evolution of insect pathogenicity in plant-beneficial Pseudomonas protegens.

Pseudomonas protegens is a biocontrol rhizobacterium with a plant-beneficial and an insect pathogenic lifestyle, but it is not understood how the organism switches between the two states. Here, we focus on understanding the function and possible evolution of a molecular sensor that enables P. protegens to detect the insect environment and produce a potent insecticidal toxin specifically during insect infection but not on roots. By using quantitative single cell microscopy and mutant analysis, we provide evidence that the sensor histidine kinase FitF is a key regulator of insecticidal toxin production. Our experimental data and bioinformatic analyses indicate that FitF shares a sensing domain with DctB, a histidine kinase regulating carbon uptake in Proteobacteria. This suggested that FitF has acquired its specificity through domain shuffling from a common ancestor. We constructed a chimeric DctB-FitF protein and showed that it is indeed functional in regulating toxin expression in P. protegens. The shuffling event and subsequent adaptive modifications of the recruited sensor domain were critical for the microorganism to express its potent insect toxin in the observed host-specific manner. Inhibition of the FitF sensor during root colonization could explain the mechanism by which P. protegens differentiates between the plant and insect host. Our study establishes FitF of P. protegens as a prime model for molecular evolution of sensor proteins and bacterial pathogenicity.

A double layer model of the gas bubble/water interface

Zeta potential is a physico-chemical parameter of particular importance to describe sorption of contaminants at the surface of gas bubbles. Nevertheless, the interpretation of electrophoretic mobilities of gas bubbles is complex. This is due to the specific behavior of the gas at interface and to the excess of electrical charge at interface, which is responsible for surface conductivity. We developed a surface complexation model based on the presence of negative surface sites because the balance of accepting and donating hydrogen bonds is broken at interface. By considering protons adsorbed on these sites followed by a diffuse layer, the electrical potential at the head-end of the diffuse layer is computed and considered to be equal to the zeta potential. The predicted zeta potential values are in very good agreement with the experimental data of H-2 bubbles for a broad range of pH and NaCl concentrations. This implies that the shear plane is located at the head-end of the diffuse layer, contradicting the assumption of the presence of a stagnant diffuse layer at the gas/water interface. Our model also successfully predicts the surface tension of air bubbles in a KCl solution. (c) 2012 Elsevier Inc. All rights reserved.

Altruism, Equity, and Reciprocity in a Gift-Exchange Experiment: An Encompassing Approach

Considerable experimental evidence suggests that non-pecuniary motives must be addressed when modeling behavior in economic contexts. Recent models of non-pecuniary motives can be classified as either altruism- based, equity-based, or reciprocity-based. We estimate and compare leading approaches in these categories, using experimental data. We then offer a flexible approach that nests the above three approaches, thereby allowing for nested hypothesis testing and for determining the relative strength of each of the competing theories. In addition, the encompassing approach provides a functional form for utility in different settings without the restrictive nature of the approaches nested within it. Using this flexible form for nested tests, we find that intentional reciprocity, distributive concerns, and altruistic considerations all play a significant role in players' decisions.

Sequence determinants of a microtubule tip localization signal (MtLS).

Microtubule plus-end-tracking proteins (+TIPs) specifically localize to the growing plus-ends of microtubules to regulate microtubule dynamics and functions. A large group of +TIPs contain a short linear motif, SXIP, which is essential for them to bind to end-binding proteins (EBs) and target microtubule ends. The SXIP sequence site thus acts as a widespread microtubule tip localization signal (MtLS). Here we have analyzed the sequence-function relationship of a canonical MtLS. Using synthetic peptide arrays on membrane supports, we identified the residue preferences at each amino acid position of the SXIP motif and its surrounding sequence with respect to EB binding. We further developed an assay based on fluorescence polarization to assess the mechanism of the EB-SXIP interaction and to correlate EB binding and microtubule tip tracking of MtLS sequences from different +TIPs. Finally, we investigated the role of phosphorylation in regulating the EB-SXIP interaction. Together, our results define the sequence determinants of a canonical MtLS and provide the experimental data for bioinformatics approaches to carry out genome-wide predictions of novel +TIPs in multiple organisms.

Mécanismes cellulaires du métabolisme énergétique cérébral: implications pour l'imagerie fonctionnelle

Signals detected with functional brain imaging techniques are based on the coupling of neuronal activity with energy metabolism. Techniques such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) allow the visualization of brain areas that are activated by a variety of sensory, motor or cognitive tasks. Despite the technological sophistication of these brain imaging techniques, the precise mechanisms and cell types involved in coupling and in generating metabolic signals are still debated. Recent experimental data on the cellular and molecular mechanisms that underlie the fluorodeoxyglucose (FDG) - based PET imaging point to a critical role of a particular brain cell type, the astrocytes, in coupling neuronal activity to glucose utilization. Indeed, astrocytes possess receptors and re-uptake sites for a variety of neurotransmitters, including glutamate, the predominant excitatory neurotransmitter in the brain, In addition, astrocytic end-feet, which surround capillaries, are enriched in the specific glucose transporter GLUT-1. These features allow astrocytes to "sense" synaptic activity and to couple it with energy metabolism. In vivo and in vitro data support the following functional model: in response to glutamate released by active neurons, glucose is predominantly taken up by astrocytic end-feet; glucose is then metabolized to lactate which provides a preferred energy substrate for neurons. These data support the notion that astrocytes markedly contribute to the FDG-PET signal.

Living Snow Fences, 2006

Blowing snow can cause significant problems for mobility and safety during winter weather in three distinct ways. It may drift onto the road, thus requiring almost continuous plowing while the wind is blowing (which may occur when a given winter storm is over). Snow may drift onto wet pavement (perhaps caused by ice control chemicals) and dilute out the chemicals on the road, creating ice on the road. And sufficient blowing snow can cause a major deterioration in visibility on the road, a factor which has been shown to be significant in winter crashes. The problem of blowing snow can be very effectively addressed by creating a snow storage device upwind of the road that requires protection from snow drifting. Typically, these storage devices are fences. Extensive design guidance exists for the required height and placement of such fences for a given annual snowfall and given local topography. However, the design information on the placement of living snow fences is less complete. The purpose of this report is to present the results of three seasons of study on using standing corn as snow fences. In addition, the experience of using switch grass as a snow storage medium is also presented. On the basis of these experimental data, a design guide has been developed that makes use of the somewhat unique snow storage characteristics of standing corn snow fences. The results of the field tests on using standing corn showed that multiple rows of standing corn store snow rather differently than a traditional wooden snow fence. Specifically, while a traditional fence stores most of the snow downwind from the fence (and thus must be placed a significant distance upwind of the road to be protected, specifically at least 35 times the snow fence height) rows of standing corn store the majority of the snow within the rows. Results from the three winters of testing show that the standing corn snow fences can store as much snow within the rows of standing corn as a traditional fence of typical height for operation in Iowa (4 to 6 feet) can store. This finding is significant because it means that the snow fences can be placed at the edge of the farmer’s field closest to the road, and still be effective. This is typically much more convenient for the farmer and thus may mean that more farmers would be willing to participate in a program that uses standing corn than in traditional programs. ii On the basis of the experimental data, design guidance for the use of standing corn as a snow storage device in Iowa is given in the report. Specifically, it is recommended that if the fetch in a location to be protected is less than 5,000 feet, then 16 rows of standing corn should be used, at the edge of the field adjacent to the right of way. If the fetch is greater than 5,000 feet, then 24 rows of standing corn should be used. This is based on a row spacing of 22 inches. Further, it should be noted that these design recommendations are ONLY for the State of Iowa. Other states of course have different winter weather and without extensive further study, it cannot be said that these guidelines would be effective in other locations with other winter conditions.

Modeling of the TCR-MHC-peptide complex.

The methodology for generating a homology model of the T1 TCR-PbCS-K(d) class I major histocompatibility complex (MHC) class I complex is presented. The resulting model provides a qualitative explanation of the effect of over 50 different mutations in the region of the complementarity determining region (CDR) loops of the T cell receptor (TCR), the peptide and the MHC's alpha(1)/alpha(2) helices. The peptide is modified by an azido benzoic acid photoreactive group, which is part of the epitope recognized by the TCR. The construction of the model makes use of closely related homologs (the A6 TCR-Tax-HLA A2 complex, the 2C TCR, the 14.3.d TCR Vbeta chain, the 1934.4 TCR Valpha chain, and the H-2 K(b)-ovalbumine peptide), ab initio sampling of CDR loops conformations and experimental data to select from the set of possibilities. The model shows a complex arrangement of the CDR3alpha, CDR1beta, CDR2beta and CDR3beta loops that leads to the highly specific recognition of the photoreactive group. The protocol can be applied systematically to a series of related sequences, permitting the analysis at the structural level of the large TCR repertoire specific for a given peptide-MHC complex.

Self-serving biases: Evidence from a simulated labor relationship

Previous studies have found evidence of a self-serving bias in bargaining and dispute resolution. We use experimental data to test for this effect in a simulated labor relatonship. We finda consistent discrepancy between employer beliefs and employee actions that can only be attributed to self-serving biases. This discrepancy is evident through stated beliefs, revealed satisfaction, and actual actions. We present evidenceand discuss implications.

Umbilical venous concentrations of estradiol in infants with early-onset neonatal sepsis and chorioamnionitis.

Objective: Fetuses are exposed to high concentrations of estradiol due to placental production. Experimental data suggest that estradiol is an important modulator of the immune response. However, the role of estradiol in the pathogenesis of early-onset neonatal sepsis (EOS) is unknown. The purpose of this pilot study was to determine estradiol levels in umbilical venous blood of newborns with EOS or chorioamnionitis exposure. Methods: Estradiol concentrations were measured by enzyme immunoassay in 37 newborns with EOS, 37 newborns with chorioamnionitis and 37 controls matched for gestational age and gender. Results: Estradiol levels correlated with gestational age, birth weight, gender and mode of delivery (p < 0.05). Multivariate analysis revealed higher estradiol levels in the EOS than in the chorioamnionitis group (odds ratio 8.43, 95% CI 1.63-43.45, p = 0.01) with the highest levels in patients with proven bacteraemia (p = 0.02). No difference was found between the EOS and the control group. Exploratory analysis showed an association between lower estradiol levels and a longer duration of mechanical ventilation (n = 28, p = 0.02). Conclusions: Umbilical venous estradiol levels were similar in EOS compared to controls. Further investigation is needed to evaluate whether high estradiol levels in infants with chorioamnionitis increases the risk of developing EOS.

Protection from lethal gram-negative bacterial sepsis by targeting Toll-like receptor 4.

Toll-like receptor 4 (TLR4), the signal-transducing molecule of the LPS receptor complex, plays a fundamental role in the sensing of LPS from gram-negative bacteria. Activation of TLR4 signaling pathways by LPS is a critical upstream event in the pathogenesis of gram-negative sepsis, making TLR4 an attractive target for novel antisepsis therapy. To validate the concept of TLR4-targeted treatment strategies in gram-negative sepsis, we first showed that TLR4(-/-) and myeloid differentiation primary response gene 88 (MyD88)(-/-) mice were fully resistant to Escherichia coli-induced septic shock, whereas TLR2(-/-) and wild-type mice rapidly died of fulminant sepsis. Neutralizing anti-TLR4 antibodies were then generated using a soluble chimeric fusion protein composed of the N-terminal domain of mouse TLR4 (amino acids 1-334) and the Fc portion of human IgG1. Anti-TLR4 antibodies inhibited intracellular signaling, markedly reduced cytokine production, and protected mice from lethal endotoxic shock and E. coli sepsis when administered in a prophylactic and therapeutic manner up to 13 h after the onset of bacterial sepsis. These experimental data provide strong support for the concept of TLR4-targeted therapy for gram-negative sepsis.

Altruism, equity and reciprocity in a gift-exchange experiment: An encompassing approach

Considerable experimental evidence suggests that non-pecuniary motivesmust be addressed when modeling behavior in economic contexts. Recentmodels of non-pecuniary motives can be classified as either altruism-based, equity-based, or reciprocity-based. We estimate and compareleading approaches in these categories, using experimental data. Wethen offer a flexible approach that nests the above three approaches,thereby allowing for nested hypothesis testing and for determiningthe relative strength of each of the competing theories. In addition,the encompassing approach provides a functional form for utility in different settings without the restrictive nature of the approaches nested within it. Using this flexible form for nested tests, we findthat intentional reciprocity, distributive concerns, and altruisticconsiderations all play a significant role in players' decisions.

Systematic study of the static electrical properties of the CO molecule: influence of the basis set size and correlation energy

The influence of the basis set size and the correlation energy in the static electrical properties of the CO molecule is assessed. In particular, we have studied both the nuclear relaxation and the vibrational contributions to the static molecular electrical properties, the vibrational Stark effect (VSE) and the vibrational intensity effect (VIE). From a mathematical point of view, when a static and uniform electric field is applied to a molecule, the energy of this system can be expressed in terms of a double power series with respect to the bond length and to the field strength. From the power series expansion of the potential energy, field-dependent expressions for the equilibrium geometry, for the potential energy and for the force constant are obtained. The nuclear relaxation and vibrational contributions to the molecular electrical properties are analyzed in terms of the derivatives of the electronic molecular properties. In general, the results presented show that accurate inclusion of the correlation energy and large basis sets are needed to calculate the molecular electrical properties and their derivatives with respect to either nuclear displacements or/and field strength. With respect to experimental data, the calculated power series coefficients are overestimated by the SCF, CISD, and QCISD methods. On the contrary, perturbation methods (MP2 and MP4) tend to underestimate them. In average and using the 6-311 + G(3df) basis set and for the CO molecule, the nuclear relaxation and the vibrational contributions to the molecular electrical properties amount to 11.7%, 3.3%, and 69.7% of the purely electronic μ, α, and β values, respectively