Interaction of Fas(Apo-1/CD95) with proteins implicated in the ubiquitination pathway.

Fas(Apo-1/CD95), a receptor belonging to the tumor necrosis factor receptor family, induces apoptosis when triggered by Fas ligand. Upon its activation, the cytoplasmic domain of Fas binds several proteins which transmit the death signal. We used the yeast two-hybrid screen to isolate Fas-associated proteins. Here we report that the ubiquitin-conjugating enzyme UBC9 binds to Fas at the interface between the death domain and the membrane-proximal region of Fas. This interaction is also seen in vivo. UBC9 transiently expressed in HeLa cells bound to the co-expressed cytoplasmic segment of Fas. FAF1, a Fas-associated protein that potentiates apoptosis (Chu et al. (1996) Proc. Natl. Acad. Sci. USA 92, 11894-11898), was found to contain sequences similar to ubiquitin. These results suggest that proteins related to the ubiquitination pathway may modulate the Fas signaling pathway.

Probable metabolic interaction between methadone and fluvoxamine in addict patients.

We report five cases where fluvoxamine (FLVX) was added to maintenance treatment with methadone (MTD) in addict patients with affective disorders. In view of the implication of FLVX in several metabolic drug interactions, MTD plasma levels were measured before and after treatment with FLVX. A slight increase (approximately 20% of the MTD plasma level/dose ratio) occurred in two cases. In the remaining three patients, the interaction was more pronounced (40-100% increase of the MTD plasma level/dose ratio), with clinical manifestations of opiate withdrawal after stopping FLVX therapy in one case. Caution is needed when starting or stopping treatment with FLVX in patients receiving maintenance treatment with methadone.

Interaction of antigenic peptides with MHC class I molecules on living cells studied by photoaffinity labeling.

Using a direct binding assay based on photoaffinity labeling, we have studied the interaction of antigenic peptides with murine MHC class I molecules on living cells. Photoreactive derivatives were prepared by N-terminal amidation with iodo, 4-azido salicylic acid of the Kd restricted Plasmodium berghei circumsporozoite (P.b. CS) peptide 253-260 (YIPSAEKI) and the Db-restricted Adenovirus 5 early region 1A (Ad5 E1A) peptide 234-243 (SGPSNTPPEI). As assessed in functional competition experiments, both peptide derivatives retained the specific binding activity of the parental peptides for Kd or Dd, respectively. The P.b. CS photoprobe specifically labeled Kd molecules on P815 (H-2d) cells, but failed to label RMA (H-2b) cells. Conversely, the Ad5 E1A photoprobe specifically labeled Db molecules on RMA cells, but failed to label P815 cells. When the two photoprobes were tested on a panel of Con A-activated spleen cells expressing 10 different H-2 haplotypes, significant photoaffinity labeling was observed only on H-2d cells with the P.b. CS photoprobe and on H-2b cells with the Ad5 E1A photoprobe. Labeling of cell-associated Kd or Db molecules with the photoprobes was specifically inhibited by antigenic peptides known to be presented by the same class I molecule. Photoaffinity labeling of Kd with the P.b. CS photoprobe was used to study the dynamics of peptide binding on living P815 cells. Binding increased steadily with the incubation period (up to 8 h) at 37 degrees C and at ambient temperature, but was greatly reduced (greater than 95%) at 0 to 4 degrees C or in the presence of ATP synthesis inhibitors. The magnitude of the labeling was twofold higher at room temperature than at 37 degrees C. In contrast, binding to isolated Kd molecules in solution rapidly reached maximal binding, particularly at 37 degrees C. Dissociation of the photoprobe from either cell-associated or soluble Kd molecules was similar, with a half time of approximately 1 h at 37 degrees C, whereas the complexes were long-lived at 4 degrees C in both instances.

Human-Computer Interaction with older people through ethnographical lenses: everyday interactions with ICT

Report for the scientific sojourn carried out at the School of Computing of the University of Dundee, United Kingdom, from 2010 to 2012. This document is a scientific report of the work done, main results, publications and accomplishment of the objectives of the 2-year post-doctoral research project with reference number BP-A 00239. The project has addressed the topic of older people (60+) and Information and Communication Technologies (ICT), which is a topic of growing social and research interest, from a Human-Computer Interaction perspective. Over a 2-year period (June 2010-June 2012), we have conducted classical ethnography of ICT use in a computer clubhouse in Scotland, addressing interaction barriers and strategies, social sharing practices in Social Network Sites, and ICT learning, and carried out rapid ethnographical studies related to geo-enabled ICT and e-government services towards supporting independent living and active ageing. The main results have provided a much deeper understanding of (i) the everyday use of Computer-Mediated Communication tools, such as video-chats and blogs, and its evolution as older people’s experience with ICT increases over time, (ii) cross-cultural aspects of ICT use in the north and south of Europe, (iii) the relevance of cognition over vision in interacting with geographical information and a wide range of ICT tools, despite common stereotypes (e.g. make things bigger), (iv) the important relationship offline-online to provide older people with socially inclusive and meaningful eservices for independent living and active ageing, (v) how older people carry out social sharing practices in the popular YouTube, (vi) their user experiences and (vii) the challenges they face in ICT learning and the strategies they use to become successful ICT learners over time. The research conducted in this project has been published in 17 papers, 4 in journals – two of which in JCR, 5 in conferences, 4 in workshops and 4 in magazines. Other public output consists of 10 invited talks and seminars.

Multi-scale label interaction to improve object detection and segmentation

The project aims at advancing the state of the art in the use of context information for classification of image and video data. The use of context in the classification of images has been showed of great importance to improve the performance of actual object recognition systems. In our project we proposed the concept of Multi-scale Feature Labels as a general and compact method to exploit the local and global context. The feature extraction from the discriminative probability or classification confidence label field is of great novelty. Moreover the use of a multi-scale representation of the feature labels lead to a compact and efficient description of the context. The goal of the project has been also to provide a general-purpose method and prove its suitability in different image/video analysis problem. The two-year project generated 5 journal publications (plus 2 under submission), 10 conference publications (plus 2 under submission) and one patent (plus 1 pending). Of these publications, a relevant number make use of the main result of this project to improve the results in detection and/or segmentation of objects.

A positive interaction between inhibitors of protein synthesis and cefepime in the fight against methicillin-resistant Staphylococcus aureus.

Quinupristin-dalfopristin (Q-D) synergizes with cefepime for the treatment of methicillin-resistant Staphylococcus aureus (MRSA). Here, we studied whether the synergism was restricted to MRSA and if it extended to non-beta-lactam cell wall inhibitors or to other inhibitors of protein synthesis. Three MRSA and two methicillin-susceptible S. aureus (MSSA) strains were tested, including an isogenic pair of mecA (-)/mecA (+) S. aureus Newman. The drug interactions were determined by fractional inhibitory concentration (FIC) indices and population analysis profiles. The antibacterial drugs that we used included beta-lactam (cefepime) and non-beta-lactam cell wall inhibitors (D-cycloserine, fosfomycin, vancomycin, teicoplanin), inhibitors of protein synthesis (Q-D, erythromycin, chloramphenicol, tetracycline, linezolid, fusidic acid), and polynucleotide inhibitors (cotrimoxazole, ciprofloxacin). The addition of each protein inhibitor to cefepime was synergistic (FIC ≤ 0.5) or additive (FIC > 0.5 but < 1) against MRSA, but mostly indifferent against MSSA (FIC ≥ 1 but ≤ 4). This segregation was not observed after adding cotrimoxazole or ciprofloxacin to cefepime. Population analysis profiles were performed on plates in the presence of increasing concentrations of the cell wall inhibitors plus 0.25 × minimum inhibitory concentration (MIC) of Q-D. Cefepime combined with Q-D was synergistic against MRSA, but D-cycloserine and glycopeptides were not. Thus, the synergism was specific to beta-lactam antibiotics. Moreover, the synergism was not lost against fem mutants, indicating that it acted at another level. The restriction of the beneficial effect to MRSA suggests that the functionality of penicillin-binding protein 2A (PBP2A) was affected, either directly or indirectly. Further studies are necessary in order to provide a mechanism for this positive interaction.

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.

Association of NTRK3 and its interaction with NGF suggest an altered cross-regulation of the neurotrophin signaling pathway in eating disorders

Eating disorders (EDs) are complex psychiatric diseases that include anorexia nervosa and bulimia nervosa, and have higher than 50% heritability. Previous studies have found association of BDNF and NTRK2 to ED, while animal models suggest that other neurotrophin genes might also be involved in eating behavior. We have performed a family-based association study with 151 TagSNPs covering 10 neurotrophin signaling genes: NGFB, BDNF, NTRK1, NGFR/p75, NTF4/5, NTRK2, NTF3, NTRK3, CNTF and CNTFR in 371 ED trios of Spanish, French and German origin. Besides several nominal associations, we found a strong significant association after correcting for multiple testing (P = 1.04 × 10−4) between ED and rs7180942, located in the NTRK3 gene, which followed an overdominant model of inheritance. Interestingly, HapMap unrelated individuals carrying the rs7180942 risk genotypes for ED showed higher levels of expression of NTRK3 in lymphoblastoid cell lines. Furthermore, higher expression of the orthologous murine Ntrk3 gene was also detected in the hypothalamus of the anx/anx mouse model of anorexia. Finally, variants in NGFB gene appear to modify the risk conferred by the NTRK3 rs7180942 risk genotypes (P = 4.0 × 10−5) showing a synergistic epistatic interaction. The reported data, in addition to the previous reported findings for BDNF and NTRK2, point neurotrophin signaling genes as key regulators of eating behavior and their altered cross-regulation as susceptibility factors for EDs.

Development and validation of AMANDA, a new algorithm for selecting highly relevant regions in Molecular Interaction Fields

Descriptors based on Molecular Interaction Fields (MIF) are highly suitable for drug discovery, but their size (thousands of variables) often limits their application in practice. Here we describe a simple and fast computational method that extracts from a MIF a handful of highly informative points (hot spots) which summarize the most relevant information. The method was specifically developed for drug discovery, is fast, and does not require human supervision, being suitable for its application on very large series of compounds. The quality of the results has been tested by running the method on the ligand structure of a large number of ligand-receptor complexes and then comparing the position of the selected hot spots with actual atoms of the receptor. As an additional test, the hot spots obtained with the novel method were used to obtain GRIND-like molecular descriptors which were compared with the original GRIND. In both cases the results show that the novel method is highly suitable for describing ligand-receptor interactions and compares favorably with other state-of-the-art methods.

Monitoring of illicit pill distribution networks using an image collection exploration framework

This paper proposes a novel approach for the analysis of illicit tablets based on their visual characteristics. In particular, the paper concentrates on the problem of ecstasy pill seizure profiling and monitoring. The presented method extracts the visual information from pill images and builds a representation of it, i.e. it builds a pill profile based on the pill visual appearance. Different visual features are used to build different image similarity measures, which are the basis for a pill monitoring strategy based on both discriminative and clustering models. The discriminative model permits to infer whether two pills come from the same seizure, while the clustering models groups of pills that share similar visual characteristics. The resulting clustering structure allows to perform a visual identification of the relationships between different seizures. The proposed approach was evaluated using a data set of 621 Ecstasy pill pictures. The results demonstrate that this is a feasible and cost effective method for performing pill profiling and monitoring.

Minimizing recombinations in consensus networks for phylogeographic studies

Background: We address the problem of studying recombinational variations in (human) populations. In this paper, our focus is on one computational aspect of the general task: Given two networks G1 and G2, with both mutation and recombination events, defined on overlapping sets of extant units the objective is to compute a consensus network G3 with minimum number of additional recombinations. We describe a polynomial time algorithm with a guarantee that the number of computed new recombination events is within ϵ = sz(G1, G2) (function sz is a well-behaved function of the sizes and topologies of G1 and G2) of the optimal number of recombinations. To date, this is the best known result for a network consensus problem.Results: Although the network consensus problem can be applied to a variety of domains, here we focus on structure of human populations. With our preliminary analysis on a segment of the human Chromosome X data we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. These results have been verified independently using traditional manual procedures. To the best of our knowledge, this is the first recombinations-based characterization of human populations. Conclusion: We show that our mathematical model identifies recombination spots in the individual haplotypes; the aggregate of these spots over a set of haplotypes defines a recombinational landscape that has enough signal to detect continental as well as population divide based on a short segment of Chromosome X. In particular, we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. The agreement with mutation-based analysis can be viewed as an indirect validation of our results and the model. Since the model in principle gives us more information embedded in the networks, in our future work, we plan to investigate more non-traditional questions via these structures computed by our methodology.

Kinship in entrepreneur networks: Performance effects of resource assembly in Africa

We examine the relationship between structural social capital, resource assembly, and firm performance of entrepreneurs in Africa. We posit that social capital primarily composed of kinship or family ties helps the entrepreneur to raise resources, but it does so at a cost. Using data drawn from small firms in Kampala, Uganda, we explore how shared identity among the entrepreneur's social network moderates this relationship. A large network contributed a higher quantity of resources raised, but at a higher cost when shared identity was high. We discuss the implications of these findings for the role of family ties and social capital in resource assembly, with an emphasis on developing economies.