962 resultados para Clustering a large document collection
Resumo:
Transcription factors (TFs) are key regulators of gene expression in all organisms. In eukaryotes, TFs are often represented by functionally redundant members of large gene families. Overexpression might prove a means to unveil the biological functions of redundant TFs; however, constitutive overexpression of TFs frequently causes severe developmental defects, preventing their functional characterization. Conditional overexpression strategies help to overcome this problem. Here, we report on the TRANSPLANTA collection of Arabidopsis lines, each expressing one of 949 TFs under the control of a β–estradiol-inducible promoter. Thus far, 1636 independent homozygous lines, representing an average of 2.6 lines for every TF, have been produced for the inducible expression of 634 TFs. Along with a GUS-GFP reporter, randomly selected TRANSPLANTA lines were tested and confirmed for conditional transgene expression upon β–estradiol treatment. As a proof of concept for the exploitation of this resource, β–estradiol-induced proliferation of root hairs, dark-induced senescence, anthocyanin accumulation and dwarfism were observed in lines conditionally expressing full-length cDNAs encoding RHD6, WRKY22, MYB123/TT2 and MYB26, respectively, in agreement with previously reported phenotypes conferred by these TFs. Further screening performed with other TRANSPLANTA lines allowed the identification of TFs involved in different plant biological processes, illustrating that the collection is a powerful resource for the functional characterization of TFs. For instance, ANAC058 and a TINY/AP2 TF were identified as modulators of ABA-mediated germination potential, and RAP2.10/DEAR4 was identified as a regulator of cell death in the hypocotyl–root transition zone. Seeds of TRANSPLANTA lines have been deposited at the Nottingham Arabidopsis Stock Centre for further distribution.
Resumo:
DELLA proteins are the master negative regulators in gibberellin (GA) signaling acting in the nucleus as transcriptional regulators. The current view of DELLA action indicates that their activity relies on the physical interaction with transcription factors (TFs). Therefore, the identification of TFs through which DELLAs regulate GA responses is key to understanding these responses from a mechanistic point of view. Here, we have determined the TF interactome of the Arabidopsis (Arabidopsis thaliana) DELLA protein GIBBERELLIN INSENSITIVE and screened a collection of conditional TF overexpressors in search of those that alter GA sensitivity. As a result, we have found RELATED TO APETALA2.3, an ethylene-induced TF belonging to the group VII ETHYLENE RESPONSE FACTOR of the APETALA2/ethylene responsive element binding protein superfamily, as a DELLA interactor with physiological relevance in the context of apical hook development. The combination of transactivation assays and chromatin immunoprecipitation indicates that the interaction with GIBBERELLIN INSENSITIVE impairs the activity of RELATED TO APETALA2.3 on the target promoters. This mechanism represents a unique node in the cross regulation between the GA and ethylene signaling pathways controlling differential growth during apical hook development.
Resumo:
Automatic 2D-to-3D conversion is an important application for filling the gap between the increasing number of 3D displays and the still scant 3D content. However, existing approaches have an excessive computational cost that complicates its practical application. In this paper, a fast automatic 2D-to-3D conversion technique is proposed, which uses a machine learning framework to infer the 3D structure of a query color image from a training database with color and depth images. Assuming that photometrically similar images have analogous 3D structures, a depth map is estimated by searching the most similar color images in the database, and fusing the corresponding depth maps. Large databases are desirable to achieve better results, but the computational cost also increases. A clustering-based hierarchical search using compact SURF descriptors to characterize images is proposed to drastically reduce search times. A significant computational time improvement has been obtained regarding other state-of-the-art approaches, maintaining the quality results.
Resumo:
La última década ha sido testigo de importantes avances en el campo de la tecnología de reconocimiento de voz. Los sistemas comerciales existentes actualmente poseen la capacidad de reconocer habla continua de múltiples locutores, consiguiendo valores aceptables de error, y sin la necesidad de realizar procedimientos explícitos de adaptación. A pesar del buen momento que vive esta tecnología, el reconocimiento de voz dista de ser un problema resuelto. La mayoría de estos sistemas de reconocimiento se ajustan a dominios particulares y su eficacia depende de manera significativa, entre otros muchos aspectos, de la similitud que exista entre el modelo de lenguaje utilizado y la tarea específica para la cual se está empleando. Esta dependencia cobra aún más importancia en aquellos escenarios en los cuales las propiedades estadísticas del lenguaje varían a lo largo del tiempo, como por ejemplo, en dominios de aplicación que involucren habla espontánea y múltiples temáticas. En los últimos años se ha evidenciado un constante esfuerzo por mejorar los sistemas de reconocimiento para tales dominios. Esto se ha hecho, entre otros muchos enfoques, a través de técnicas automáticas de adaptación. Estas técnicas son aplicadas a sistemas ya existentes, dado que exportar el sistema a una nueva tarea o dominio puede requerir tiempo a la vez que resultar costoso. Las técnicas de adaptación requieren fuentes adicionales de información, y en este sentido, el lenguaje hablado puede aportar algunas de ellas. El habla no sólo transmite un mensaje, también transmite información acerca del contexto en el cual se desarrolla la comunicación hablada (e.g. acerca del tema sobre el cual se está hablando). Por tanto, cuando nos comunicamos a través del habla, es posible identificar los elementos del lenguaje que caracterizan el contexto, y al mismo tiempo, rastrear los cambios que ocurren en estos elementos a lo largo del tiempo. Esta información podría ser capturada y aprovechada por medio de técnicas de recuperación de información (information retrieval) y de aprendizaje de máquina (machine learning). Esto podría permitirnos, dentro del desarrollo de mejores sistemas automáticos de reconocimiento de voz, mejorar la adaptación de modelos del lenguaje a las condiciones del contexto, y por tanto, robustecer al sistema de reconocimiento en dominios con condiciones variables (tales como variaciones potenciales en el vocabulario, el estilo y la temática). En este sentido, la principal contribución de esta Tesis es la propuesta y evaluación de un marco de contextualización motivado por el análisis temático y basado en la adaptación dinámica y no supervisada de modelos de lenguaje para el robustecimiento de un sistema automático de reconocimiento de voz. Esta adaptación toma como base distintos enfoque de los sistemas mencionados (de recuperación de información y aprendizaje de máquina) mediante los cuales buscamos identificar las temáticas sobre las cuales se está hablando en una grabación de audio. Dicha identificación, por lo tanto, permite realizar una adaptación del modelo de lenguaje de acuerdo a las condiciones del contexto. El marco de contextualización propuesto se puede dividir en dos sistemas principales: un sistema de identificación de temática y un sistema de adaptación dinámica de modelos de lenguaje. Esta Tesis puede describirse en detalle desde la perspectiva de las contribuciones particulares realizadas en cada uno de los campos que componen el marco propuesto: _ En lo referente al sistema de identificación de temática, nos hemos enfocado en aportar mejoras a las técnicas de pre-procesamiento de documentos, asimismo en contribuir a la definición de criterios más robustos para la selección de index-terms. – La eficiencia de los sistemas basados tanto en técnicas de recuperación de información como en técnicas de aprendizaje de máquina, y específicamente de aquellos sistemas que particularizan en la tarea de identificación de temática, depende, en gran medida, de los mecanismos de preprocesamiento que se aplican a los documentos. Entre las múltiples operaciones que hacen parte de un esquema de preprocesamiento, la selección adecuada de los términos de indexado (index-terms) es crucial para establecer relaciones semánticas y conceptuales entre los términos y los documentos. Este proceso también puede verse afectado, o bien por una mala elección de stopwords, o bien por la falta de precisión en la definición de reglas de lematización. En este sentido, en este trabajo comparamos y evaluamos diferentes criterios para el preprocesamiento de los documentos, así como también distintas estrategias para la selección de los index-terms. Esto nos permite no sólo reducir el tamaño de la estructura de indexación, sino también mejorar el proceso de identificación de temática. – Uno de los aspectos más importantes en cuanto al rendimiento de los sistemas de identificación de temática es la asignación de diferentes pesos a los términos de acuerdo a su contribución al contenido del documento. En este trabajo evaluamos y proponemos enfoques alternativos a los esquemas tradicionales de ponderado de términos (tales como tf-idf ) que nos permitan mejorar la especificidad de los términos, así como también discriminar mejor las temáticas de los documentos. _ Respecto a la adaptación dinámica de modelos de lenguaje, hemos dividimos el proceso de contextualización en varios pasos. – Para la generación de modelos de lenguaje basados en temática, proponemos dos tipos de enfoques: un enfoque supervisado y un enfoque no supervisado. En el primero de ellos nos basamos en las etiquetas de temática que originalmente acompañan a los documentos del corpus que empleamos. A partir de estas, agrupamos los documentos que forman parte de la misma temática y generamos modelos de lenguaje a partir de dichos grupos. Sin embargo, uno de los objetivos que se persigue en esta Tesis es evaluar si el uso de estas etiquetas para la generación de modelos es óptimo en términos del rendimiento del reconocedor. Por esta razón, nosotros proponemos un segundo enfoque, un enfoque no supervisado, en el cual el objetivo es agrupar, automáticamente, los documentos en clusters temáticos, basándonos en la similaridad semántica existente entre los documentos. Por medio de enfoques de agrupamiento conseguimos mejorar la cohesión conceptual y semántica en cada uno de los clusters, lo que a su vez nos permitió refinar los modelos de lenguaje basados en temática y mejorar el rendimiento del sistema de reconocimiento. – Desarrollamos diversas estrategias para generar un modelo de lenguaje dependiente del contexto. Nuestro objetivo es que este modelo refleje el contexto semántico del habla, i.e. las temáticas más relevantes que se están discutiendo. Este modelo es generado por medio de la interpolación lineal entre aquellos modelos de lenguaje basados en temática que estén relacionados con las temáticas más relevantes. La estimación de los pesos de interpolación está basada principalmente en el resultado del proceso de identificación de temática. – Finalmente, proponemos una metodología para la adaptación dinámica de un modelo de lenguaje general. El proceso de adaptación tiene en cuenta no sólo al modelo dependiente del contexto sino también a la información entregada por el proceso de identificación de temática. El esquema usado para la adaptación es una interpolación lineal entre el modelo general y el modelo dependiente de contexto. Estudiamos también diferentes enfoques para determinar los pesos de interpolación entre ambos modelos. Una vez definida la base teórica de nuestro marco de contextualización, proponemos su aplicación dentro de un sistema automático de reconocimiento de voz. Para esto, nos enfocamos en dos aspectos: la contextualización de los modelos de lenguaje empleados por el sistema y la incorporación de información semántica en el proceso de adaptación basado en temática. En esta Tesis proponemos un marco experimental basado en una arquitectura de reconocimiento en ‘dos etapas’. En la primera etapa, empleamos sistemas basados en técnicas de recuperación de información y aprendizaje de máquina para identificar las temáticas sobre las cuales se habla en una transcripción de un segmento de audio. Esta transcripción es generada por el sistema de reconocimiento empleando un modelo de lenguaje general. De acuerdo con la relevancia de las temáticas que han sido identificadas, se lleva a cabo la adaptación dinámica del modelo de lenguaje. En la segunda etapa de la arquitectura de reconocimiento, usamos este modelo adaptado para realizar de nuevo el reconocimiento del segmento de audio. Para determinar los beneficios del marco de trabajo propuesto, llevamos a cabo la evaluación de cada uno de los sistemas principales previamente mencionados. Esta evaluación es realizada sobre discursos en el dominio de la política usando la base de datos EPPS (European Parliamentary Plenary Sessions - Sesiones Plenarias del Parlamento Europeo) del proyecto europeo TC-STAR. Analizamos distintas métricas acerca del rendimiento de los sistemas y evaluamos las mejoras propuestas con respecto a los sistemas de referencia. ABSTRACT The last decade has witnessed major advances in speech recognition technology. Today’s commercial systems are able to recognize continuous speech from numerous speakers, with acceptable levels of error and without the need for an explicit adaptation procedure. Despite this progress, speech recognition is far from being a solved problem. Most of these systems are adjusted to a particular domain and their efficacy depends significantly, among many other aspects, on the similarity between the language model used and the task that is being addressed. This dependence is even more important in scenarios where the statistical properties of the language fluctuates throughout the time, for example, in application domains involving spontaneous and multitopic speech. Over the last years there has been an increasing effort in enhancing the speech recognition systems for such domains. This has been done, among other approaches, by means of techniques of automatic adaptation. These techniques are applied to the existing systems, specially since exporting the system to a new task or domain may be both time-consuming and expensive. Adaptation techniques require additional sources of information, and the spoken language could provide some of them. It must be considered that speech not only conveys a message, it also provides information on the context in which the spoken communication takes place (e.g. on the subject on which it is being talked about). Therefore, when we communicate through speech, it could be feasible to identify the elements of the language that characterize the context, and at the same time, to track the changes that occur in those elements over time. This information can be extracted and exploited through techniques of information retrieval and machine learning. This allows us, within the development of more robust speech recognition systems, to enhance the adaptation of language models to the conditions of the context, thus strengthening the recognition system for domains under changing conditions (such as potential variations in vocabulary, style and topic). In this sense, the main contribution of this Thesis is the proposal and evaluation of a framework of topic-motivated contextualization based on the dynamic and non-supervised adaptation of language models for the enhancement of an automatic speech recognition system. This adaptation is based on an combined approach (from the perspective of both information retrieval and machine learning fields) whereby we identify the topics that are being discussed in an audio recording. The topic identification, therefore, enables the system to perform an adaptation of the language model according to the contextual conditions. The proposed framework can be divided in two major systems: a topic identification system and a dynamic language model adaptation system. This Thesis can be outlined from the perspective of the particular contributions made in each of the fields that composes the proposed framework: _ Regarding the topic identification system, we have focused on the enhancement of the document preprocessing techniques in addition to contributing in the definition of more robust criteria for the selection of index-terms. – Within both information retrieval and machine learning based approaches, the efficiency of topic identification systems, depends, to a large extent, on the mechanisms of preprocessing applied to the documents. Among the many operations that encloses the preprocessing procedures, an adequate selection of index-terms is critical to establish conceptual and semantic relationships between terms and documents. This process might also be weakened by a poor choice of stopwords or lack of precision in defining stemming rules. In this regard we compare and evaluate different criteria for preprocessing the documents, as well as for improving the selection of the index-terms. This allows us to not only reduce the size of the indexing structure but also to strengthen the topic identification process. – One of the most crucial aspects, in relation to the performance of topic identification systems, is to assign different weights to different terms depending on their contribution to the content of the document. In this sense we evaluate and propose alternative approaches to traditional weighting schemes (such as tf-idf ) that allow us to improve the specificity of terms, and to better identify the topics that are related to documents. _ Regarding the dynamic language model adaptation, we divide the contextualization process into different steps. – We propose supervised and unsupervised approaches for the generation of topic-based language models. The first of them is intended to generate topic-based language models by grouping the documents, in the training set, according to the original topic labels of the corpus. Nevertheless, a goal of this Thesis is to evaluate whether or not the use of these labels to generate language models is optimal in terms of recognition accuracy. For this reason, we propose a second approach, an unsupervised one, in which the objective is to group the data in the training set into automatic topic clusters based on the semantic similarity between the documents. By means of clustering approaches we expect to obtain a more cohesive association of the documents that are related by similar concepts, thus improving the coverage of the topic-based language models and enhancing the performance of the recognition system. – We develop various strategies in order to create a context-dependent language model. Our aim is that this model reflects the semantic context of the current utterance, i.e. the most relevant topics that are being discussed. This model is generated by means of a linear interpolation between the topic-based language models related to the most relevant topics. The estimation of the interpolation weights is based mainly on the outcome of the topic identification process. – Finally, we propose a methodology for the dynamic adaptation of a background language model. The adaptation process takes into account the context-dependent model as well as the information provided by the topic identification process. The scheme used for the adaptation is a linear interpolation between the background model and the context-dependent one. We also study different approaches to determine the interpolation weights used in this adaptation scheme. Once we defined the basis of our topic-motivated contextualization framework, we propose its application into an automatic speech recognition system. We focus on two aspects: the contextualization of the language models used by the system, and the incorporation of semantic-related information into a topic-based adaptation process. To achieve this, we propose an experimental framework based in ‘a two stages’ recognition architecture. In the first stage of the architecture, Information Retrieval and Machine Learning techniques are used to identify the topics in a transcription of an audio segment. This transcription is generated by the recognition system using a background language model. According to the confidence on the topics that have been identified, the dynamic language model adaptation is carried out. In the second stage of the recognition architecture, an adapted language model is used to re-decode the utterance. To test the benefits of the proposed framework, we carry out the evaluation of each of the major systems aforementioned. The evaluation is conducted on speeches of political domain using the EPPS (European Parliamentary Plenary Sessions) database from the European TC-STAR project. We analyse several performance metrics that allow us to compare the improvements of the proposed systems against the baseline ones.
Resumo:
Esta tesis, Edén: relato, imagen y proyecto. El concepto de Paraíso terrenal como generador de arquitecturas se realiza con el objetivo de estudiar los vínculos entre la idea de Edén, o Paraíso y la arquitectura. Siempre trabajando desde los tres niveles de representación, relato, imagen y proyecto. En la aproximación al objeto de estudio, se procede a estudiar el relato en sí, y se hallan, en la forma misma del relato, unas implicaciones relacionadas con el mundo mitológico y arquetípico. Estos resultados iniciales son la detección de que cada una de las partes que forman el conjunto edénico, han sido previamente objetos de culto en religiones corte pagano o chamánico, desde la prehistoria. El agua, los árboles, los animales, la tierra y los surcos del huerto, todos ellos han sido objetos de veneración desde tiempos inmemoriales. Trazando la genealogía de estos objetos de culto se acude al análisis arquetípico, que relaciona estos objetos venerados con el inconsciente y con la manifestación espontanea de los mismos en la realidad. Estos estudios arrojan resultados con implicaciones espaciales, arquitectónicas y se concluye que más que un ideal o un lugar en concreto, en el mito o en la realidad, lo que definitivamente parece (y demuestra) ser, es una tipología arquitectónica relacionada en su estructura formal y teórica con la del jardín cerrado. La manifestación en imagen de estos resultados y la investigación misma, llevan a acudir a unas de las imágenes más primitivas del Jardín del Edén, y que de hecho son previas a la “invención” del Hortus Conclusus como tal. Estas son las representaciones mozárabes del Paraíso Terrenal como lugar cierto en la tierra, que aparecen en los mappaemundi incluidos en los Códices de los Beatos. En el estudio de los mismos se comprende la estructura formal y teórica de lo que son las arquitecturas paradisíacas. Su calado en la cultura occidental hace que estos documentos sirvan como exoesqueletos del proyecto paradisíaco. Además, por su variedad arrojan gran número de resultados de índole espacial. Los resultados arrojados por el estudio de las representaciones edénicas de los Beatos llevan la investigación a otro momento e imágenes de la historia de la arquitectura donde, por su radicalidad de planteamientos y tabula rasa con las arquitecturas previas son necesarios nuevos lenguajes de aproximación al tema proyectual por el deseo globalizador que implican estas arquitecturas, esto es en el periodo de la arquitectura moderna. Se utiliza como elemento calibrador El poema del ángulo recto de Le Corbusier. Este documento gráfico no sólo nos da la clave que bullía en este periodo con respecto a una nueva aproximación a la superficie terrestre y al medio. Este instrumento también sirve de catalizador entre lo real y lo ideal y es una síntesis de operaciones arquitectónicas, que mediante la comparación y/o oposición con los resultados previos del estudio arquetípico y de los Beatos, genera grandes grupos de características que se hallan entrelazadas en los proyectos paradisíacos. Gracias a estos documentos se puede concluir con una síntesis de características que comparten los proyectos paradisiacos, que en todo caso son esto, proyectos en plural. No existe la unicidad, ya que se infiere de este estudio que son, en conjunto, una forma de hacer ciertas arquitecturas. Tienen características medibles y reproducibles y unas condiciones tipológicas y de generación de campos que permiten producir muchos tipos de proyectos, todos ellos de tipología paradisíaca. ABSTRACT This thesis, Eden: Tale, Image and Project. The Concept of Terrestrial Paradise as a Generator of Architectures, is carried out with the objective of studying the relations between the idea of Eden or Paradise and architecture. In every case working from the three levels of representation, tale, image and project. On the approximation to the object of study, the investigation is centered on the tale itself, and in the same core of it, are found some implications that relate it with the world of mythology and archetype. These initial results consist of detecting that each one of the parts that form the edenic set; have previously been objects of cult in religions of a pagan or shamanic nature, since pre-historic times. Water, animals, earth and the grooves of the orchard, have all been objects of reverence since the dawn of time. Tracing the genealogy of these objects an archetypal type of analysis is taken on, which relates the revered objects with the subconscious and with the spontaneous manifestation of these in reality. These studies also provide results with spatial and architectonic implications, and it is concluded that more than an ideal or a concrete place, in myth or reality, what it definitely seems (and shows to be) is an architectonic typology, related in its formal and theoretical structure with that of the enclosed garden. The manifestation in image of these results, and the investigation itself, lead to reach for one of the most primitive set of images of the Garden of Eden, and that are in fact previous to the “invention” of the Hortus Conclusus as such. A collection of mozárabe representations of the Terrestrial Paradise as a concrete place on Earth. These are the mappaemundi included in the Codexes of the Beatos. By their study, the formal and theoretical structure of paradisal architectures is understood. Their importance in occidental culture makes these documents bring out their side as exoskeletons of the paradisal Project. Also, for their variety, they cast a great number of results of a spatial nature. The results released by the study of the edenic representations of the Beatos take the investigation to another moment and set of images within the history of architecture, where the radicality of the approaches to architecture, and the tabula rasa in relation to previous architectures make it necessary to invent new languages of approximation to the subject of project. This happens because of the globalizing tones that imply these architectures. The lapse of time referred to would be during the general practice of modern architecture. The object of calibration would be The Poem of the Right Angle, by Le Corbusier. The graphic document not only gives us the key of what flowed during that time when a new approximation to the surface of earth and to the environment was retrieved. This instrument also serves as a catalyst between real and ideal, and it is a synthesis of architectural operations that by comparison and/or opposition with the previous results of the archetypal study, and of the Beatos, generates large groups of characteristics that are intertwined in the paradisal project. Due to these documents we can conclude the investigation with a series of characteristics that share the paradisal projects, which in any case are this, projects, in plural. There is no uniqueness. From these findings, it can be inferred that a Paradisal Project is a way to undertake a project, and certain kinds of architecture. They are measurable and are underlaid by a consistent pattern, they also have typological conditions and of field generation, that make it possible to produce many kinds of projects, all of a paradisal typology.
Resumo:
Eukaryotic genome similarity relationships are inferred using sequence information derived from large aggregates of genomic sequences. Comparisons within and between species sample sequences are based on the profile of dinucleotide relative abundance values (The profile is ρ*XY = f*XY/f*Xf*Y for all XY, where f*X denotes the frequency of the nucleotide X and f*XY denotes the frequency of the dinucleotide XY, both computed from the sequence concatenated with its inverted complement). Previous studies with respect to prokaryotes and this study document that profiles of different DNA sequence samples (sample size ≥50 kb) from the same organism are generally much more similar to each other than they are to profiles from other organisms, and that closely related organisms generally have more similar profiles than do distantly related organisms. On this basis we refer to the collection {ρ*XY} as the genome signature. This paper identifies ρ*XY extremes and compares genome signature differences for a diverse range of eukaryotic species. Interpretations on the mechanisms maintaining these profile differences center on genome-wide replication, repair, DNA structures, and context-dependent mutational biases. It is also observed that mitochondrial genome signature differences between species parallel the corresponding nuclear genome signature differences despite large differences between corresponding mitochondrial and nuclear signatures. The genome signature differences also have implications for contrasts between rodents and other mammals, and between monocot and dicot plants, as well as providing evidence for similarities among fungi and the diversity of protists.
Resumo:
In the yeast Saccharomyces cerevisiae, meiotic recombination is initiated by transient DNA double-strand breaks (DSBs) that are repaired by interaction of the broken chromosome with its homologue. To identify a large number of DSB sites and gain insight into the control of DSB formation at both the local and the whole chromosomal levels, we have determined at high resolution the distribution of meiotic DSBs along the 340 kb of chromosome III. We have found 76 DSB regions, mostly located in intergenic promoter-containing intervals. The frequency of DSBs varies at least 50-fold from one region to another. The global distribution of DSB regions along chromosome III is nonrandom, defining large (39–105 kb) chromosomal domains, both hot and cold. The distribution of these localized DSBs indicates that they are likely to initiate most crossovers along chromosome III, but some discrepancies remain to be explained.
Resumo:
Rat basophilic leukemia (RBL-2H3) cells predominantly express the type II receptor for inositol 1,4,5-trisphosphate (InsP3), which operates as an InsP3-gated calcium channel. In these cells, cross-linking the high-affinity immunoglobulin E receptor (FcεR1) leads to activation of phospholipase C γ isoforms via tyrosine kinase- and phosphatidylinositol 3-kinase-dependent pathways, release of InsP3-sensitive intracellular Ca2+ stores, and a sustained phase of Ca2+ influx. These events are accompanied by a redistribution of type II InsP3 receptors within the endoplasmic reticulum and nuclear envelope, from a diffuse pattern with a few small aggregates in resting cells to large isolated clusters after antigen stimulation. Redistribution of type II InsP3 receptors is also seen after treatment of RBL-2H3 cells with ionomycin or thapsigargin. InsP3 receptor clustering occurs within 5–10 min of stimulus and persists for up to 1 h in the presence of antigen. Receptor clustering is independent of endoplasmic reticulum vesiculation, which occurs only at ionomycin concentrations >1 μM, and maximal clustering responses are dependent on the presence of extracellular calcium. InsP3 receptor aggregation may be a characteristic cellular response to Ca2+-mobilizing ligands, because similar results are seen after activation of phospholipase C-linked G-protein-coupled receptors; cholecystokinin causes type II receptor redistribution in rat pancreatoma AR4–2J cells, and carbachol causes type III receptor redistribution in muscarinic receptor-expressing hamster lung fibroblast E36M3R cells. Stimulation of these three cell types leads to a reduction in InsP3 receptor levels only in AR4–2J cells, indicating that receptor clustering does not correlate with receptor down-regulation. The calcium-dependent aggregation of InsP3 receptors may contribute to the previously observed changes in affinity for InsP3 in the presence of elevated Ca2+ and/or may establish discrete regions within refilled stores with varying capacity to release Ca2+ when a subsequent stimulus results in production of InsP3.
Resumo:
We have undertaken an extensive screen to identify Saccharomyces cerevisiae genes whose products are involved in cell cycle progression. We report the identification of 113 genes, including 19 hypothetical ORFs, which confer arrest or delay in specific compartments of the cell cycle when overexpressed. The collection of genes identified by this screen overlaps with those identified in loss-of-function cdc screens but also includes genes whose products have not previously been implicated in cell cycle control. Through analysis of strains lacking these hypothetical ORFs, we have identified a variety of new CDC and checkpoint genes.
Resumo:
Among fruit-fly species of the genus Drosophila there is remarkable variation in sperm length, with some species producing gigantic sperm (e.g., > 10 times total male body length). These flies are also unusual in that males of some species exhibit a prolonged adult nonreproductive phase. We document sperm length, body size, and sex-specific ages of reproductive maturity for 42 species of Drosophila and, after controlling for phylogeny, test hypotheses to explain the variation in rates of sexual maturation. Results suggest that delayed male maturity is a cost of producing long sperm. A possible physiological mechanism to explain the observed relationship is discussed.
Resumo:
This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.
Resumo:
A half-page handwritten list of books with the author's surname, title, and location in the old Harvard Library, signed "Mr. Marsh." The list includes the note, "Shuckford's Connection is charged to you." The document is undated but presumably was created following the Harvard Hall Fire of 1764 as part of the College's efforts to inventory volumes that were spared because they were checked out at the time of the fire. Many of the books are listed in a charging record for Thomas Marsh recorded in a Harvard library account book (UAIII 50.15.60, Volume 1, Box 95), including "Shuckford's connection" which was charged to Marsh on September 23, 1763.