Jagged1 intracellular domain-mediated inhibition of Notch1 signalling regulates cardiac homeostasis in the postnatal heart.

AIMS: Notch1 signalling in the heart is mainly activated via expression of Jagged1 on the surface of cardiomyocytes. Notch controls cardiomyocyte proliferation and differentiation in the developing heart and regulates cardiac remodelling in the stressed adult heart. Besides canonical Notch receptor activation in signal-receiving cells, Notch ligands can also activate Notch receptor-independent responses in signal-sending cells via release of their intracellular domain. We evaluated therefore the importance of Jagged1 (J1) intracellular domain (ICD)-mediated pathways in the postnatal heart. METHODS AND RESULTS: In cardiomyocytes, Jagged1 releases J1ICD, which then translocates into the nucleus and down-regulates Notch transcriptional activity. To study the importance of J1ICD in cardiac homeostasis, we generated transgenic mice expressing a tamoxifen-inducible form of J1ICD, specifically in cardiomyocytes. Using this model, we demonstrate that J1ICD-mediated Notch inhibition diminishes proliferation in the neonatal cardiomyocyte population and promotes maturation. In the neonatal heart, a response via Wnt and Akt pathway activation is elicited as an attempt to compensate for the deficit in cardiomyocyte number resulting from J1ICD activation. In the stressed adult heart, J1ICD activation results in a dramatic reduction of the number of Notch signalling cardiomyocytes, blunts the hypertrophic response, and reduces the number of apoptotic cardiomyocytes. Consistently, this occurs concomitantly with a significant down-regulation of the phosphorylation of the Akt effectors ribosomal S6 protein (S6) and eukaryotic initiation factor 4E binding protein1 (4EBP1) controlling protein synthesis. CONCLUSIONS: Altogether, these data demonstrate the importance of J1ICD in the modulation of physiological and pathological hypertrophy, and reveal the existence of a novel pathway regulating cardiac homeostasis.

The EXS Domain of PHO1 Participates in the Response of Shoots to Phosphate Deficiency via a Root-to-Shoot Signal.

The response of shoots to phosphate (Pi) deficiency implicates long-distance communication between roots and shoots, but the participating components are poorly understood. We have studied the topology of the Arabidopsis (Arabidopsis thaliana) PHOSPHATE1 (PHO1) Pi exporter and defined the functions of its different domains in Pi homeostasis and signaling. The results indicate that the amino and carboxyl termini of PHO1 are both oriented toward the cytosol and that the protein spans the membrane twice in the EXS domain, resulting in a total of six transmembrane α-helices. Using transient expression in Nicotiana benthamiana leaf, we demonstrated that the EXS domain of PHO1 is essential for Pi export activity and proper localization to the Golgi and trans-Golgi network, although the EXS domain by itself cannot mediate Pi export. In contrast, removal of the amino-terminal hydrophilic SPX domain does not affect the Pi export capacity of the truncated PHO1 in N. benthamiana. While the Arabidopsis pho1 mutant has low shoot Pi and shows all the hallmarks associated with Pi deficiency, including poor shoot growth and overexpression of numerous Pi deficiency-responsive genes, expression of only the EXS domain of PHO1 in the roots of the pho1 mutant results in a remarkable improvement of shoot growth despite low shoot Pi. Transcriptomic analysis of pho1 expressing the EXS domain indicates an attenuation of the Pi signaling cascade and the up-regulation of genes involved in cell wall synthesis and the synthesis or response to several phytohormones in leaves as well as an altered expression of genes responsive to abscisic acid in roots.

Semantic domain and grammatical class effects in the picture-word interference paradigm

The role of grammatical class in lexical access and representation is still not well understood. Grammatical effects obtained in picture-word interference experiments have been argued to show the operation of grammatical constraints during lexicalization when syntactic integration is required by the task. Alternative views hold that the ostensibly grammatical effects actually derive from the coincidence of semantic and grammatical differences between lexical candidates. We present three picture-word interference experiments conducted in Spanish. In the first two, the semantic relatedness (related or unrelated) and the grammatical class (nouns or verbs) of the target and the distracter were manipulated in an infinitive form action naming task in order to disentangle their contributions to verb lexical access. In the third experiment, a possible confound between grammatical class and semantic domain (objects or actions) was eliminated by using action-nouns as distracters. A condition in which participants were asked to name the action pictures using an inflected form of the verb was also included to explore whether the need of syntactic integration modulated the appearance of grammatical effects. Whereas action-words (nouns or verbs), but not object-nouns, produced longer reaction times irrespective of their grammatical class in the infinitive condition, only verbs slowed latencies in the inflected form condition. Our results suggest that speech production relies on the exclusion of candidate responses that do not fulfil task-pertinent criteria like membership in the appropriate semantic domain or grammatical class. Taken together, these findings are explained by a response-exclusion account of speech output. This and alternative hypotheses are discussed.

The serine protease hepsin mediates urinary secretion and polymerisation of Zona Pellucida domain protein uromodulin.

Uromodulin is the most abundant protein in the urine. It is exclusively produced by renal epithelial cells and it plays key roles in kidney function and disease. Uromodulin mainly exerts its function as an extracellular matrix whose assembly depends on a conserved, specific proteolytic cleavage leading to conformational activation of a Zona Pellucida (ZP) polymerisation domain. Through a comprehensive approach, including extensive characterisation of uromodulin processing in cellular models and in specific knock-out mice, we demonstrate that the membrane-bound serine protease hepsin is the enzyme responsible for the physiological cleavage of uromodulin. Our findings define a key aspect of uromodulin biology and identify the first in vivo substrate of hepsin. The identification of hepsin as the first protease involved in the release of a ZP domain protein is likely relevant for other members of this protein family, including several extracellular proteins, as egg coat proteins and inner ear tectorins.

Broadening the CRM domain of application to higher educational (e-learning) environments

In this paper, we reflect about the broadening of the field of application of CRM from the business domain to a wider context of relationships in which the inclusion of non-profit making organizations seems natural. In particular, we focus on analyzing the suitability of adopting CRM processes by universities and higher educational institutions dedicated to e-learning. This is an issue that, in our opinion, has much potential but has received little attention in research so far.

An ontology to automated learning scenarios? an approach to its knowledge domain

Automation or semi-automation of learning scenariospecifications is one of the least exploredsubjects in the e-learning research area. There isa need for a catalogue of learning scenarios and atechnique to facilitate automated retrieval of stored specifications. This requires constructing anontology with this goal and is justified inthis paper. This ontology must mainlysupport a specification technique for learning scenarios. This ontology should also be useful in the creation and validation of new scenarios as well as in the personalization of learning scenarios or their monitoring. Thus, after justifying the need for this ontology, a first approach of a possible knowledge domain is presented. An example of a concrete learning scenario illustrates some relevant concepts supported by this ontology in order to define the scenario in such a way that it could be easy to automate.

Expanding the Customer Relationship Management scope to the non-profit organizations : an analysis focused on the e-university domain

Peer-reviewed

Computing the persistent homology of range images with alpha shapes

Laser scanning is becoming an increasingly popular method for measuring 3D objects in industrial design. Laser scanners produce a cloud of 3D points. For CAD software to be able to use such data, however, this point cloud needs to be turned into a vector format. A popular way to do this is to triangulate the assumed surface of the point cloud using alpha shapes. Alpha shapes start from the convex hull of the point cloud and gradually refine it towards the true surface of the object. Often it is nontrivial to decide when to stop this refinement. One criterion for this is to do so when the homology of the object stops changing. This is known as the persistent homology of the object. The goal of this thesis is to develop a way to compute the homology of a given point cloud when processed with alpha shapes, and to infer from it when the persistent homology has been achieved. Practically, the computation of such a characteristic of the target might be applied to power line tower span analysis.

Vacancy-assisted domain-growth in asymmetric binary alloys: A Monte Carlo Study

A Monte Carlo simulation study of the vacancy-assisted domain growth in asymmetric binary alloys is presented. The system is modeled using a three-state ABV Hamiltonian which includes an asymmetry term. Our simulated system is a stoichiometric two-dimensional binary alloy with a single vacancy which evolves according to the vacancy-atom exchange mechanism. We obtain that, compared to the symmetric case, the ordering process slows down dramatically. Concerning the asymptotic behavior it is algebraic and characterized by the Allen-Cahn growth exponent x51/2. The late stages of the evolution are preceded by a transient regime strongly affected by both the temperature and the degree of asymmetry of the alloy. The results are discussed and compared to those obtained for the symmetric case.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Molecular Interactions of Prodiginines with the BH3 Domain of Anti-Apoptotic Bcl-2 Family Members.

Prodigiosin and obatoclax, members of the prodiginines family, are small molecules with anti-cancer properties that are currently under preclinical and clinical trials. The molecular target(s) of these agents, however, is an open question. Combining experimental and computational techniques we find that prodigiosin binds to the BH3 domain in some BCL-2 protein families, which play an important role in the apoptotic programmed cell death. In particular, our results indicate a large affinity of prodigiosin for MCL-1, an anti-apoptotic member of the BCL-2 family. In melanoma cells, we demonstrate that prodigiosin activates the mitochondrial apoptotic pathway by disrupting MCL-1/BAK complexes. Computer simulations with the PELE software allow the description of the induced fit process, obtaining a detailed atomic view of the molecular interactions. These results provide new data to understand the mechanism of action of these molecules, and assist in the development of more specific inhibitors of anti-apoptotic BCL-2 proteins.

Photomultiplier nonlinear response in time-domain laser-induced luminescence spectroscopy

A new procedure to find the limiting range of the photomultiplier linear response of a low-cost, digital oscilloscope-based time-resolved laser-induced luminescence spectrometer (TRLS), is presented. A systematic investigation on the instrument response function with different signal input terminations, and the relationship between the luminescence intensity reaching the photomultiplier and the measured decay time are described. These investigations establish that setting the maximum intensity of the luminescence signal below 0.3V guarantees, for signal input terminations equal or higher than 99.7 ohm, a linear photomultiplier response.