CERKL Knockdown Causes Retinal Degeneration in Zebrafish

The human CERKL gene is responsible for common and severe forms of retinal dystrophies. Despite intense in vitro studies at the molecular and cellular level and in vivo analyses of the retina of murine knockout models, CERKL function remains unknown. In this study, we aimed to approach the developmental and functional features of cerkl in Danio rerio within an Evo-Devo framework. We show that gene expression increases from early developmental stages until the formation of the retina in the optic cup. Unlike the high mRNA-CERKL isoform multiplicity shown in mammals, the moderate transcriptional complexity in fish facilitates phenotypic studies derived from gene silencing. Moreover, of relevance to pathogenicity, teleost CERKL shares the two main human protein isoforms. Morpholino injection has been used to generate a cerkl knockdown zebrafish model. The morphant phenotype results in abnormal eye development with lamination defects, failure to develop photoreceptor outer segments, increased apoptosis of retinal cells and small eyes. Our data support that zebrafish Cerkl does not interfere with proliferation and neural differentiation during early developmental stages but is relevant for survival and protection of the retinal tissue. Overall, we propose that this zebrafish model is a powerful tool to unveil CERKL contribution to human retinal degeneration

Wnt-3a and Wnt-3 differently stimulate proliferation and neurogenesis of spinal neural precursors and promote neurite outgrowth by canonical signaling

Wnt factors regulate neural stem cell development and neuronal connectivity. Here we investigated whether Wnt-3a and Wnt-3, expressed in the developing spinal cord, regulate proliferation and the neuronal differentiation of spinal cord neural precursors (SCNP). Wnt-3a promoted a sustained increase of SCNP proliferation, whereas Wnt-3 enhanced SCNP proliferation transiently and increased neurogenesis through β-catenin signaling. Consistent with this, Wnt-3a and Wnt-3 differently regulate the expression of Cyclin-dependent kinase inhibitors. Furthermore, Wnt-3a and Wnt-3 stimulated neurite outgrowth in SCNP-derived neurons through ß-catenin and TCF4-dependent transcription. GSK-3ß inhibitors mimicked Wnt signaling and promoted neurite outgrowth in established cultures. We conclude that Wnt-3a and Wnt-3 signal through the canonical Wnt/β-catenin pathway to regulate different aspects of SCNP development. These findings may be of therapeutic interest for the treatment of neurodegenerative diseases and nerve injury.

Maximal operators and differentiation theorems for sparse sets

"Vegeu el resum a l'inici del document del fitxer adjunt."

Product differentiation, competitive pressure and the effects of innovation on the success and survivability of firms in oligopoly markets

In a recent paper Tishler and Milstein (2009) fi…nd that increased competition may increase aggregate R&D spending while market output decreases. Therefore, they obtain the surprising result that R&D spending is excessive when competition becomes intense. Their result is based on the standard linear demand function for differentiated products introduced by Bowley (1924) where decreased product differentiation is interpreted as more competitive pressure. In this paper I show that at an aggregate level this interpretation is problematic because equilibrium effects are dominated by a demand reduction effect. A slight modifi…cation of the standard demand function eliminates this effect. For the Tishler and Milstein (2009) setting it is shown that then increased competition increases both R&D spending and aggregate market output. Therefore, at least for consumers, more intense competition increases welfare. Journal of Economic Literature Classi…fication Numbers: D43, L1, O3. Keywords: Oligopoly markets, Product differentiation, Competitive pressure.

Implementación y entrenamiento de un modelo clasificatorio de red neural sobre la base de datos IGBADAT para la clasificación de las rocas basálticas de acuerdo a las clases del sistema de clasificación tradicional de Yoder and Tiller.

Aquest treball vol implementar un projecte de mineria de dades en l'àrea de la petrologia ígnia, especialitat englobada dins la geologia clàssica.

Efficient learning of reactive robot behaviors with a Neural-Q_learning approach

The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

Volatility smile extrapolation with an artificial neural network

I use a multi-layer feedforward perceptron, with backpropagation learning implemented via stochastic gradient descent, to extrapolate the volatility smile of Euribor derivatives over low-strikes by training the network on parametric prices.

Distribution of events of positive selection and population differentiation in a metabolic pathway: the case of asparagine N-glycosylation

Background: Asparagine N-Glycosylation is one of the most important forms of protein post-translational modification in eukaryotes. This metabolic pathway can be subdivided into two parts: an upstream sub-pathway required for achieving proper folding for most of the proteins synthesized in the secretory pathway, and a downstream sub-pathway required to give variability to trans-membrane proteins, and involved in adaptation to the environment andinnate immunity. Here we analyze the nucleotide variability of the genes of this pathway in human populations, identifying which genes show greater population differentiation and which genes show signatures of recent positive selection. We also compare how these signals are distributed between the upstream and the downstream parts of the pathway, with the aim of exploring how forces of population differentiation and positive selection vary among genes involved in the same metabolic pathway but subject to different functional constraints. Results:Our results show that genes in the downstream part of the pathway are more likely to show a signature of population differentiation, while events of positive selection are equally distributed among the two parts of the pathway. Moreover, events of positive selection arefrequent on genes that are known to be at bifurcation points, and that are identified as beingin key position by a network-level analysis such as MGAT3 and GCS1.Conclusions: These findings indicate that the upstream part of the Asparagine N-Glycosylation pathway has lower diversity among populations, while the downstream part is freer to tolerate diversity among populations. Moreover, the distribution of signatures of population differentiation and positive selection can change between parts of a pathway, especially between parts that are exposed to different functional constraints. Our results support the hypothesis that genes involved in constitutive processes can be expected to show lower population differentiation, while genes involved in traits related to the environment should show higher variability. Taken together, this work broadens our knowledge on how events of population differentiation and of positive selection are distributed among different parts of a metabolic pathway.

Cannabinoid addiction: behavioral models and neural correlates

The use of cannabis sativa preparations as recreational drugs can be traced back to the earliest civilizations. However, animal models of cannabinoid addiction allowing the exploration of neural correlates of cannabinoid abuse have been developed only recently. We review these models and the role of the CB1 cannabinoid receptor, the main target of natural cannabinoids, and its interaction with opioid and dopamine transmission in reward circuits. Extensive reviews on the molecular basis of cannabinoid action are available elsewhere (Piomelli et al., 2000;Schlicker and Kathmann, 2001).

Origin and genetic differentiation of Three Mexican Native Groups (Purépechas, Triquis and Mayas): contribution of CODIS-STRs to the history of human populations of Mesoamerica

BACKGROUND: CODIS-STRs in Native Mexican groups have rarely been analysed for human identification and anthropological purposes. AIM:To analyse the genetic relationships and population structure among three Native Mexican groups from Mesoamerica.SUBJECTS AND METHODS: 531 unrelated Native individuals from Mexico were PCR-typed for 15 and 9 autosomal STRs (Identifiler™ and Profiler™ kits, respectively), including five population samples: Purépechas (Mountain, Valley and Lake), Triquis and Yucatec Mayas. Previously published STR data were included in the analyses. RESULTS:Allele frequencies and statistical parameters of forensic importance were estimated by population. The majority of Native groups were not differentiated pairwise, excepting Triquis and Purépechas, which was attributable to their relative geographic and cultural isolation. Although Mayas, Triquis and Purépechas-Mountain presented the highest number of private alleles, suggesting recurrent gene flow, the elevated differentiation of Triquis indicates a different origin of this gene flow. Interestingly, Huastecos and Mayas were not differentiated, which is in agreement with the archaeological hypothesis that Huastecos represent an ancestral Maya group. Interpopulation variability was greater in Natives than in Mestizos, both significant.CONCLUSION: Although results suggest that European admixture has increased the similarity between Native Mexican groups, the differentiation and inconsistent clustering by language or geography stresses the importance of serial founder effect and/or genetic drift in showing their present genetic relationships.

What can spike train distances tell us about the neural code?

Time scale parametric spike train distances like the Victor and the van Rossum distancesare often applied to study the neural code based on neural stimuli discrimination.Different neural coding hypotheses, such as rate or coincidence coding,can be assessed by combining a time scale parametric spike train distance with aclassifier in order to obtain the optimal discrimination performance. The time scalefor which the responses to different stimuli are distinguished best is assumed to bethe discriminative precision of the neural code. The relevance of temporal codingis evaluated by comparing the optimal discrimination performance with the oneachieved when assuming a rate code.We here characterize the measures quantifying the discrimination performance,the discriminative precision, and the relevance of temporal coding. Furthermore,we evaluate the information these quantities provide about the neural code. Weshow that the discriminative precision is too unspecific to be interpreted in termsof the time scales relevant for encoding. Accordingly, the time scale parametricnature of the distances is mainly an advantage because it allows maximizing thediscrimination performance across a whole set of measures with different sensitivitiesdetermined by the time scale parameter, but not due to the possibility toexamine the temporal properties of the neural code.

Overeducation among European university graduates : a comparative analysis ot its incidence and the importance of higher education differentiation

The incidence of over-education is here assessed by applying some standard subjective and objective indicators and a new skill-based indicator of over-education to the national samples of eight European countries in the REFLEX survey. With the exception of Spain, the results reveal that over-education is a minor risk amongst European tertiary graduates. Yet, the contrast between the standard indicators and the skill-based indicator reveals the existence of an over-education of a moderate kind in countries with high tertiary attainment rates (Norway, Finland and Netherlands). Such a type of over-education does not come to the surface when applying the standard indicators. Our results also reveal the importance of higher education differentiation (i.e. field of study and branch of higher education) for understanding the risk of over-education. Graduates from humanistic fields, bachelor courses and vocational colleges are more exposed to over-education, though their disadvantage varies across-nationally to a significant extent.

Pharmaceutical Generics, Vertical Product Differentiation, and Public Policy

This paper studies oligopolistic competition in off-patent pharmaceutical markets using a vertical product differentiation model. This model can explain the observation that countries with stronger regulations have smaller generic market shares. It can also explain the differences in observed regulatory regimes. Stronger regulation may be due to a higher proportion of production that is done by foreign firms. Finally, a closely related model can account for the observed increase in prices by patent owners after entry of generic producers.

Pharmaceutical generics, vertical product differentiation and public policy

This paper studies oligopolistic competition in off-patent pharmaceuticalmarkets using a vertical product differentiation model. This model canexplain the observation that countries with stronger regulations havesmaller generic market shares. It can also explain the differences inobserved regulatory regimes. Stronger regulation may be due to a higherproportion of production that is done by foreign firms. Finally, a closelyrelated model can account for the observed increase in prices by patentowners after entry of generic producers.