Estudi dels models de veu cantada de l'alumnat de mestre en Educació Musical

Desde el año 1992, en que se crea la nueva diplomatura de maestro en Educación Musical, las escuelas y facultades de formación del profesorado empiezan a formar a los especialistas responsables de impartir la educación musical en la escuela primaria. Partiendo de la hipótesis de que el ejemplo de voz cantada que presenta el alumnado de la nueva diplomatura no es el más apropiado para ser imitado por niños y niñas de la escuela primaria, el autor de este artículo nos describe el estudio exploratorio practicado al alumnado que finaliza la diplomatura de maestro en educación musical en la Facultat de Formació del Professorat de la Universitat de Barcelona. Este estudio, que ha contado con dos instrumentos de recogida de la información, una observación y un cuestionario, plantea como objetivo principal detectar las dificultades básicas planteadas por el alumnado, y al mismo tiempo conocer las causas que las originan. Una vez analizados en profundidad los datos y las informaciones recogidas, el autor aporta soluciones encaminadas a resolver las problemáticas, así como a mejorar el ejemplo de voz cantada de los futuros maestros.

Models teòrics explicatius de l'aprenentatge motor

En este artículo se repasan los principales modelos teóricos explicativos del aprendizaje motor. En un primer apartado se comentan las aportaciones propias de la psicología cognitiva y más concretamente del corriente del procesamiento de la información: la Teoría del bucle cerrado de Jack Adams y la Teoría del esquema de Richard Schmidt. Posteriormente, se exponen las críticas que han recibido estos modelos y, para hacerlo, se introducen las principales aportaciones que el científico ruso Nikolai Bernstein hizo al estudio del aprendizaje y el control motor. A partir de estas aportaciones, se introducen las formulaciones teóricas que, surgidas desde la perspectiva dinámica-ecológica, pretenden superar las limitaciones de los modelos cognitivos. Finalmente, se comparan las dos perspectivas y se sugieren algunas posibles vías de desarrollo futuro del campo que nos ocupa.

Geostatistical prediction of clay percentage based on soil survey data

Selostus: Viljelymaiden savespitoisuuden alueellistaminen geostatistiikan ja pistemäisen tiedon avulla

Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula.

The major intention of the present study was to investigate whether an approach combining the use of niche-based palaeodistribution modeling and phylo-geography would support or modify hypotheses about the Quaternary distributional history derived from phylogeographic methods alone. Our study system comprised two closely related species of Alpine Primula. We used species distribution models based on the extant distribution of the species and last glacial maximum (LGM) climate models to predict the distribution of the two species during the LGM. Phylogeographic data were generated using amplified fragment length polymorphisms (AFLPs). In Primula hirsuta, models of past distribution and phylogeographic data are partly congruent and support the hypothesis of widespread nunatak survival in the Central Alps. Species distribution models (SDMs) allowed us to differentiate between alpine regions that harbor potential nunatak areas and regions that have been colonized from other areas. SDMs revealed that diversity is a good indicator for nunataks, while rarity is a good indicator for peripheral relict populations that were not source for the recolonization of the inner Alps. In P. daonensis, palaeo-distribution models and phylogeographic data are incongruent. Besides the uncertainty inherent to this type of modeling approach (e.g., relatively coarse 1-km grain size), disagreement of models and data may partly be caused by shifts of ecological niche in both species. Nevertheless, we demonstrate that the combination of palaeo-distribution modeling with phylogeographical approaches provides a more differentiated picture of the distributional history of species and partly supports (P. hirsuta) and partly modifies (P. daonensis and P. hirsuta) hypotheses of Quaternary distributional history. Some of the refugial area indicated by palaeodistribution models could not have been identified with phylogeographic data.

Phenotypic and molecular characterization of the onset of neuropathy in rodent models of diabetes mellitus

Abstract : The principal focus of this work was to study the molecular changes leading to the development of diabetic peripheral neuropathy (DPN). DPN is the most common complication associated with both type I and II diabetes mellitus (DM). This pathology is the leading cause of non-traumatic amputations. Even though the pathological and morphological changes underlying DPN are relatively well described, the implicated molecular mechanisms remain poorly understood. The following two approaches were developed to study the development of DPN in a rodent model of DM type I. As a first approach, we studied the implication of lipid metabolism in DPN phenotype, concentrating on Sterol Response Element Binding Protein (SREBP)-lc which is the key regulator of storage lipid metabolism. We showed that SREBP-1c was expressed in peripheral nerves and that its expression profile followed the expression of genes involved in storage lipid metabolism. In addition, the expression of SREBP-1c in the endoneurium of peripheral nerves was dependant upon nutritional status and this expression was also perturbed in type I diabetes. In line with this, we showed that insulin elevated the expression of SREBP-1c in primary cultured Schwann cells by activating the SREBP-1c promoter. Taken together, these findings reveal that SREBP-1c expression in Schwann cells responds to metabolic stimuli including insulin and that this response is affected in type I diabetes mellitus. This suggests that disturbed SREBP-1c regulated lipid metabolism may contribute to the pathophysiology of DPN. As a second approach, we performed a comprehensive analysis of the molecular changes associated with DPN in the Akital~1~+ mouse which is a model of spontaneous early-onset type I diabetes mellitus. This mouse expresses a mutated non-functional isoform of insulin, leading to hypoinsulinemia and hyperglycaemia. To determine the onset of DPN, weight, blood glucose and motor nerve conduction velocity (MNCV) were measured in Akital+/+ mice during the first three months of life. A decrease in MNCV was evident akeady one week after the onset of hyperglycemia. To explore the molecular changes associated with the development of DPN in these mice, we performed gene expression profiling using sciatic nerve endoneurium and dorsal root ganglia (DRG) isolated from early diabetic male Akita+/+ mice and sex-matched littermate controls. No major transcriptional changes were detected either in the DRG or in the sciatic nerve endoneurium. This experiment indicates that the phenotypic changes observed during the development of DPN are not correlated with major transcriptional alterations, but mainly with alterations at the protein level. Résumé Lors ce travail, nous nous sommes intéressés aux changements moléculaires aboutissant aux neuropathies périphériques dues au diabète (NPD). Les NPD sont la complication la plus commune du diabète de type I et de type II. Cette pathologie est une cause majeure d'amputations. Même si les changements pathologiques et morphologiques associés aux NPD sont relativement bien décrits, les mécanismes moléculaires provoquant cette pathologie sont mal connus. Deux approches ont principalement été utilisées pour étudier le développement des NPD dans des modèles murins du diabète de type I. Nous avons d'abord étudié l'impact du métabolisme des lipides sur le développement des NPD en nous concentrant sur Sterol Response Element Binding Protein (SREBP)-1 c qui est un régulateur clé des lipides de stockage. Nous avons montré que SREBP-1 c est exprimé dans les nerfs périphériques et que son profil d'expression suit celui de gènes impliqués dans le métabolisme des lipides de stockage. De plus, l'expression de SREBP-1c dans l'endoneurium des nerfs périphériques est dépendante du statut nutritionnel et est dérégulée lors de diabète de type I. Nous avons également pu montrer que l'insuline augmente l'expression de SREBP-1c dans des cultures primaires de cellules de Schwann en activant le promoteur de SREBP-1c. Ses résultats démontrent que l'expression de SREBP-1c dans les cellules de Schwann est contrôlée par des stimuli métaboliques comme l'insuline et que cette réponse est affectée dans le cas d'un diabète de type I. Ces données suggèrent que la dérégulation de l'expression de SREBP-1c lors du diabète pourrait affecter le métabolisme des lipides et ainsi contribuer à la pathophysiologie des NPD. Comme seconde approche, nous avons réalisé une analyse globale des changements moléculaires associés au développement des NPD chez les souris Akita+/+, un modèle de diabète de type I. Cette souris exprime une forme mutée et non fonctionnelle de l'insuline provoquant une hypoinsulinémie et une hyperglycémie. Afin de déterminer le début du développement de la NPD, le poids, le niveau de glucose sanguin et la vitesse de conduction nerveuse (VCN) ont été mesurés durant les 3 premiers mois de vie. Une diminution de la VCN a été détectée une semaine seulement après le développement de l'hyperglycémie. Pour explorer les changements moléculaires associés avec le développement des NPD, nous avons réalisé un profil d'expression de l'endoneurium du nerf sciatique et des ganglions spinaux isolés à partir de souris Akital+/+ et de souris contrôles Akita+/+. Aucune altération transcriptionnelle majeure n'a été détectée dans nos échantillons. Cette expérience suggère que les changements phénotypiques observés durant le développement des NPD ne sont pas corrélés avec des changements importants au niveau transcriptionnel, mais plutôt avec des altérations au niveau protéique. Résumé : Lors ce travail, nous nous sommes intéressés aux changements moléculaires aboutissant aux neuropathies périphériques dues au diabète (NPD). Les NPD sont la complication la plus commune du diabète de type I et de type II. Cette pathologie est une cause majeure d'amputations. Même si les changements pathologiques et morphologiques associés aux NPD sont relativement bien décrits, les mécanismes moléculaires provoquant cette pathologie sont mal connus. Deux approches ont principalement été utilisées pour étudier le développement des NPD dans des modèles murins du diabète de type I. Nous avons d'abord étudié l'impact du métabolisme des lipides sur le développement des NPD en nous concentrant sur Sterol Response Element Binding Protein (SREBP)-1c qui est un régulateur clé des lipides de stockage. Nous avons montré que SREBP-1 c est exprimé dans les nerfs périphériques et que son profil d'expression suit celui de gènes impliqués dans le métabolisme des lipides de stockage. De plus, l'expression de SREBP-1c dans l'endoneurium des nerfs périphériques est dépendante du statut nutritionnel et est dérégulée lors de diabète de type I. Nous avons également pu montrer que l'insuline augmente l'expression de SREBP-1c dans des cultures primaires de cellules de Schwann en activant le promoteur de SREBP-1c. Ses résultats démontrent que l'expression de SREBP-1c dans les cellules de Schwann est contrôlée par des stimuli métaboliques comme l'insuline et que cette réponse est affectée dans le cas d'un diabète de type I. Ces données suggèrent que la dérégulation de l'expression de SREBP-1c lors du diabète pourrait affecter le métabolisme des lipides et ainsi contribuer à la pathophysiologie des NPD. Comme seconde approche, nous avons réalisé une analyse globale des changements moléculaires associés au développement des NPD chez les souris Akita~~Z~+, un modèle de diabète de type I. Cette souris exprime une forme mutée et non fonctionnelle de l'insuline provoquant une hypoinsulinémie et une hyperglycémie. Afin de déterminer le début du développement de la NPD, le poids, le niveau de glucose sanguin et la vitesse de conduction nerveuse (VCN) ont été mesurés durant les 3 premiers mois de vie. Une diminution de la VCN a été détectée une semaine seulement après le développement de l'hyperglycémie. Pour explorer les changements moléculaires associés avec le développement des NPD, nous avons réalisé un profil d'expression de l'endoneurium du nerf sciatique et des ganglions spinaux isolés à partir de souris Akital+/+ et de souris contrôles Akita+/+. Aucune altération transcriptionnelle majeure n'a été détectée dans nos échantillons. Cette expérience suggère que les changements phénotypiques observés durant le développement des NPD ne sont pas corrélés avec des changements importants au niveau transcriptionnel, mais plutôt avec des altérations au niveau protéique.

Effects of alternative sets of climatic predictors on species distribution models and associated estimates of extinction risk: a test with plants in an arid environment

Aim To evaluate the effects of using distinct alternative sets of climatic predictor variables on the performance, spatial predictions and future projections of species distribution models (SDMs) for rare plants in an arid environment. . Location Atacama and Peruvian Deserts, South America (18º30'S - 31º30'S, 0 - 3 000 m) Methods We modelled the present and future potential distributions of 13 species of Heliotropium sect. Cochranea, a plant group with a centre of diversity in the Atacama Desert. We developed and applied a sequential procedure, starting from climate monthly variables, to derive six alternative sets of climatic predictor variables. We used them to fit models with eight modelling techniques within an ensemble forecasting framework, and derived climate change projections for each of them. We evaluated the effects of using these alternative sets of predictor variables on performance, spatial predictions and projections of SDMs using Generalised Linear Mixed Models (GLMM). Results The use of distinct sets of climatic predictor variables did not have a significant effect on overall metrics of model performance, but had significant effects on present and future spatial predictions. Main conclusion Using different sets of climatic predictors can yield the same model fits but different spatial predictions of current and future species distributions. This represents a new form of uncertainty in model-based estimates of extinction risk that may need to be better acknowledged and quantified in future SDM studies.

Integrating nuclear receptor mobility in models of gene regulation.

The mode of action of nuclear receptors in living cells is an actively investigated field but much remains hypothetical due to the lack, until recently, of methods allowing the assessment of molecular mechanisms in vivo. However, these last years, the development of fluorescence microscopy methods has allowed initiating the dissection of the molecular mechanisms underlying gene regulation by nuclear receptors directly in living cells or organisms. Following our analyses on peroxisome proliferator activated receptors (PPARs) in living cells, we discuss here the different models arising from the use of these tools, that attempt to link mobility, DNA binding or chromatin interaction, and transcriptional activity.

Evolutionarily stable learning schedules and cumulative culture in discrete generation models.

Individual learning (e.g., trial-and-error) and social learning (e.g., imitation) are alternative ways of acquiring and expressing the appropriate phenotype in an environment. The optimal choice between using individual learning and/or social learning may be dictated by the life-stage or age of an organism. Of special interest is a learning schedule in which social learning precedes individual learning, because such a schedule is apparently a necessary condition for cumulative culture. Assuming two obligatory learning stages per discrete generation, we obtain the evolutionarily stable learning schedules for the three situations where the environment is constant, fluctuates between generations, or fluctuates within generations. During each learning stage, we assume that an organism may target the optimal phenotype in the current environment by individual learning, and/or the mature phenotype of the previous generation by oblique social learning. In the absence of exogenous costs to learning, the evolutionarily stable learning schedules are predicted to be either pure social learning followed by pure individual learning ("bang-bang" control) or pure individual learning at both stages ("flat" control). Moreover, we find for each situation that the evolutionarily stable learning schedule is also the one that optimizes the learned phenotype at equilibrium.

Global habitat suitability models of terrestrial mammals.

Detailed large-scale information on mammal distribution has often been lacking, hindering conservation efforts. We used the information from the 2009 IUCN Red List of Threatened Species as a baseline for developing habitat suitability models for 5027 out of 5330 known terrestrial mammal species, based on their habitat relationships. We focused on the following environmental variables: land cover, elevation and hydrological features. Models were developed at 300 m resolution and limited to within species' known geographical ranges. A subset of the models was validated using points of known species occurrence. We conducted a global, fine-scale analysis of patterns of species richness. The richness of mammal species estimated by the overlap of their suitable habitat is on average one-third less than that estimated by the overlap of their geographical ranges. The highest absolute difference is found in tropical and subtropical regions in South America, Africa and Southeast Asia that are not covered by dense forest. The proportion of suitable habitat within mammal geographical ranges correlates with the IUCN Red List category to which they have been assigned, decreasing monotonically from Least Concern to Endangered. These results demonstrate the importance of fine-resolution distribution data for the development of global conservation strategies for mammals.

Quantitative integration of high-resolution hydrogeophysical data through Monte-Carlo-type conditional simulations

Geophysical techniques can help to bridge the inherent gap with regard to spatial resolution and the range of coverage that plagues classical hydrological methods. This has lead to the emergence of the new and rapidly growing field of hydrogeophysics. Given the differing sensitivities of various geophysical techniques to hydrologically relevant parameters and their inherent trade-off between resolution and range the fundamental usefulness of multi-method hydrogeophysical surveys for reducing uncertainties in data analysis and interpretation is widely accepted. A major challenge arising from such endeavors is the quantitative integration of the resulting vast and diverse database in order to obtain a unified model of the probed subsurface region that is internally consistent with all available data. To address this problem, we have developed a strategy towards hydrogeophysical data integration based on Monte-Carlo-type conditional stochastic simulation that we consider to be particularly suitable for local-scale studies characterized by high-resolution and high-quality datasets. Monte-Carlo-based optimization techniques are flexible and versatile, allow for accounting for a wide variety of data and constraints of differing resolution and hardness and thus have the potential of providing, in a geostatistical sense, highly detailed and realistic models of the pertinent target parameter distributions. Compared to more conventional approaches of this kind, our approach provides significant advancements in the way that the larger-scale deterministic information resolved by the hydrogeophysical data can be accounted for, which represents an inherently problematic, and as of yet unresolved, aspect of Monte-Carlo-type conditional simulation techniques. We present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on pertinent synthetic data and then applied to corresponding field data collected at the Boise Hydrogeophysical Research Site near Boise, Idaho, USA.

Using niche-based models to improve the sampling of rare species

Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution models can be used to stratify the sampling and increase sampling efficiency. New data sampled are then used to improve the initial model. Applying this approach repeatedly is an adaptive process that may allow increasing the number of new occurrences found. We illustrate the approach with a case study of a rare and endangered plant species in Switzerland and a simulation experiment. Our field survey confirmed that the method helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high. In our simulations the model-based approach provided a significant improvement (by a factor of 1.8 to 4 times, depending on the measure) over simple random sampling. In terms of cost this approach may save up to 70% of the time spent in the field.