871 resultados para Classifier Generalization Ability
Resumo:
In this paper, we analyze the performance of several well-known pattern recognition and dimensionality reduction techniques when applied to mass-spectrometry data for odor biometric identification. Motivated by the successful results of previous works capturing the odor from other parts of the body, this work attempts to evaluate the feasibility of identifying people by the odor emanated from the hands. By formulating this task according to a machine learning scheme, the problem is identified with a small-sample-size supervised classification problem in which the input data is formed by mass spectrograms from the hand odor of 13 subjects captured in different sessions. The high dimensionality of the data makes it necessary to apply feature selection and extraction techniques together with a simple classifier in order to improve the generalization capabilities of the model. Our experimental results achieve recognition rates over 85% which reveals that there exists discriminatory information in the hand odor and points at body odor as a promising biometric identifier.
Resumo:
La heterogeneidad del medio geológico introduce en el proyecto de obra subterránea un alto grado de incertidumbre que debe ser debidamente gestionado a fin de reducir los riesgos asociados, que son fundamentalmente de tipo geotécnico. Entre los principales problemas a los que se enfrenta la Mecánica de Rocas moderna en el ámbito de la construcción subterránea, se encuentran la fluencia de roca en túneles (squeezing) y la rotura de pilares de carbón. Es ampliamente conocido que su aparición causa importantes perjuicios en el coste y la seguridad de los proyectos por lo que su estudio, ha estado tradicionalmente vinculado a la predicción de su ocurrencia. Entre las soluciones existentes para la determinación de estos problemas se encuentran las que se basan en métodos analíticos y numéricos. Estas metodologías son capaces de proporcionar un alto nivel de representatividad respecto del comportamiento geotécnico real, sin embargo, su utilización solo es posible cuando se dispone de una suficiente caracterización geotécnica y por tanto de una detallada definición de los parámetros que alimentan los complejos modelos constitutivos y criterios de rotura que los fenómenos estudiados requieren. Como es lógico, este nivel de definición solo es posible cuando se alcanzan etapas avanzadas de proyecto, incluso durante la propia construcción, a fin de calibrar adecuadamente los parámetros introducidos en los modelos, lo que supone una limitación de uso en etapas iniciales, cuando su predicción tiene verdadero sentido. Por su parte, los métodos empíricos permiten proporcionar soluciones a estos complejos problemas de un modo sencillo, con una baja parametrización y, dado su eminente enfoque observacional, de gran fiabilidad cuando se implementan sobre condiciones de contorno similares a las originales. La sencillez y escasez de los parámetros utilizados permiten a estas metodologías ser utilizadas desde las fases preliminares del proyecto, ya que estos constituyen en general, información habitual de fácil y económica adquisición. Este aspecto permite por tanto incorporar la predicción desde el principio del proceso de diseño, anticipando el riesgo en origen. En esta tesis doctoral, se presenta una nueva metodología empírica que sirve para proporcionar predicciones para la ocurrencia de squeezing y el fallo de pilares de carbón basada en una extensa recopilación de información de casos reales de túneles y minas en las que ambos fenómenos fueron evaluados. Esta información, recogida de referencias bibliográficas de prestigio, ha permitido recopilar una de las más extensas bases de datos existentes hasta la fecha relativa a estos fenómenos, lo que supone en sí mismo una importante contribución sobre el estado del arte. Con toda esta información, y con la ayuda de la teoría de clasificadores estadísticos, se ha implementado sobre las bases de datos un clasificador lineal de tipo regresión logística que permite hacer predicciones sobre la ocurrencia de ambos fenómenos en términos de probabilidad, y por tanto ponderar la incertidumbre asociada a la heterogeneidad incorporada por el medio geológico. Este aspecto del desarrollo es el verdadero valor añadido proporcionado por la tesis y la principal ventaja de la solución propuesta respecto de otras metodologías empíricas. Esta capacidad de ponderación probabilística permite al clasificador constituir una solución muy interesante como metodología para la evaluación de riesgo geotécnico y la toma de decisiones. De hecho, y como ejercicio de validación práctica, se ha implementado la solución desarrollada en un modelo coste-beneficio asociado a la optimización del diseño de pilares involucrados en una de mina “virtual” explotada por tajos largos. La capacidad del clasificador para cuantificar la probabilidad de fallo del diseño, junto con una adecuada cuantificación de las consecuencias de ese fallo, ha permitido definir una ley de riesgo que se ha incorporado al balance de costes y beneficios, que es capaz, a partir del redimensionamiento iterativo del sistema de pilares y de la propia configuración de la mina, maximizar el resultado económico del proyecto minero bajo unas condiciones de seguridad aceptables, fijadas de antemano. Geological media variability introduces to the subterranean project a high grade of uncertainty that should be properly managed with the aim to reduce the associated risks, which are mainly geotechnical. Among the major problems facing the modern Rock Mechanics in the field of underground construction are both, the rock squeezing while tunneling and the failure of coal pillars. Given their harmfulness to the cost and safety of the projects, their study has been traditionally linked to the determination of its occurrence. Among the existing solutions for the determination of these problems are those that are based on analytical and numerical methods. Those methodologies allow providing a high level of reliability of the geotechnical behavior, and therefore a detailed definition of the parameters that feed the complex constitutive models and failure criteria that require the studied phenomena. Obviously, this level of definition is only possible when advanced stages of the project are achieved and even during construction in order to properly calibrate the parameters entered in the models, which suppose a limited use in early stages, when the prediction has true sense. Meanwhile, empirical methods provide solutions to these complex problems in a simple way, with low parameterization and, given his observational scope, with highly reliability when implemented on similar conditions to the original context. The simplicity and scarcity of the parameters used allow these methodologies be applied in the early stages of the project, since that information should be commonly easy and cheaply to get. This aspect can therefore incorporate the prediction from the beginning of the design process, anticipating the risk beforehand. This thesis, based on the extensive data collection of case histories of tunnels and underground mines, presents a novel empirical approach used to provide predictions for the occurrence of both, squeezing and coal pillars failures. The information has been collected from prestigious references, providing one of the largest databases to date concerning phenomena, a fact which provides an important contribution to the state of the art. With all this information, and with the aid of the theory of statistical classifiers, it has been implemented on both databases, a type linear logistic regression classifier that allows predictions about the occurrence of these phenomena in terms of probability, and therefore weighting the uncertainty associated with geological variability. This aspect of the development is the real added value provided by the thesis and the main advantage of the proposed solution over other empirical methodologies. This probabilistic weighting capacity, allows being the classifier a very interesting methodology for the evaluation of geotechnical risk and decision making. In fact, in order to provide a practical validation, we have implemented the developed solution within a cost-benefit analysis associated with the optimization of the design of coal pillar systems involved in a "virtual" longwall mine. The ability of the classifier to quantify the probability of failure of the design along with proper quantification of the consequences of that failure, has allowed defining a risk law which is introduced into the cost-benefits model, which is able, from iterative resizing of the pillar system and the configuration of the mine, maximize the economic performance of the mining project under acceptable safety conditions established beforehand.
Resumo:
Multi-label classification (MLC) is the supervised learning problem where an instance may be associated with multiple labels. Modeling dependencies between labels allows MLC methods to improve their performance at the expense of an increased computational cost. In this paper we focus on the classifier chains (CC) approach for modeling dependencies. On the one hand, the original CC algorithm makes a greedy approximation, and is fast but tends to propagate errors down the chain. On the other hand, a recent Bayes-optimal method improves the performance, but is computationally intractable in practice. Here we present a novel double-Monte Carlo scheme (M2CC), both for finding a good chain sequence and performing efficient inference. The M2CC algorithm remains tractable for high-dimensional data sets and obtains the best overall accuracy, as shown on several real data sets with input dimension as high as 1449 and up to 103 labels.
Resumo:
Nonlinear analysis tools for studying and characterizing the dynamics of physiological signals have gained popularity, mainly because tracking sudden alterations of the inherent complexity of biological processes might be an indicator of altered physiological states. Typically, in order to perform an analysis with such tools, the physiological variables that describe the biological process under study are used to reconstruct the underlying dynamics of the biological processes. For that goal, a procedure called time-delay or uniform embedding is usually employed. Nonetheless, there is evidence of its inability for dealing with non-stationary signals, as those recorded from many physiological processes. To handle with such a drawback, this paper evaluates the utility of non-conventional time series reconstruction procedures based on non uniform embedding, applying them to automatic pattern recognition tasks. The paper compares a state of the art non uniform approach with a novel scheme which fuses embedding and feature selection at once, searching for better reconstructions of the dynamics of the system. Moreover, results are also compared with two classic uniform embedding techniques. Thus, the goal is comparing uniform and non uniform reconstruction techniques, including the one proposed in this work, for pattern recognition in biomedical signal processing tasks. Once the state space is reconstructed, the scheme followed characterizes with three classic nonlinear dynamic features (Largest Lyapunov Exponent, Correlation Dimension and Recurrence Period Density Entropy), while classification is carried out by means of a simple k-nn classifier. In order to test its generalization capabilities, the approach was tested with three different physiological databases (Speech Pathologies, Epilepsy and Heart Murmurs). In terms of the accuracy obtained to automatically detect the presence of pathologies, and for the three types of biosignals analyzed, the non uniform techniques used in this work lightly outperformed the results obtained using the uniform methods, suggesting their usefulness to characterize non-stationary biomedical signals in pattern recognition applications. On the other hand, in view of the results obtained and its low computational load, the proposed technique suggests its applicability for the applications under study.
Resumo:
Multi-dimensional classification (MDC) is the supervised learning problem where an instance is associated with multiple classes, rather than with a single class, as in traditional classification problems. Since these classes are often strongly correlated, modeling the dependencies between them allows MDC methods to improve their performance – at the expense of an increased computational cost. In this paper we focus on the classifier chains (CC) approach for modeling dependencies, one of the most popular and highest-performing methods for multi-label classification (MLC), a particular case of MDC which involves only binary classes (i.e., labels). The original CC algorithm makes a greedy approximation, and is fast but tends to propagate errors along the chain. Here we present novel Monte Carlo schemes, both for finding a good chain sequence and performing efficient inference. Our algorithms remain tractable for high-dimensional data sets and obtain the best predictive performance across several real data sets.
Resumo:
This paper presents a novel robust visual tracking framework, based on discriminative method, for Unmanned Aerial Vehicles (UAVs) to track an arbitrary 2D/3D target at real-time frame rates, that is called the Adaptive Multi-Classifier Multi-Resolution (AMCMR) framework. In this framework, adaptive Multiple Classifiers (MC) are updated in the (k-1)th frame-based Multiple Resolutions (MR) structure with compressed positive and negative samples, and then applied them in the kth frame-based Multiple Resolutions (MR) structure to detect the current target. The sample importance has been integrated into this framework to improve the tracking stability and accuracy. The performance of this framework was evaluated with the Ground Truth (GT) in different types of public image databases and real flight-based aerial image datasets firstly, then the framework has been applied in the UAV to inspect the Offshore Floating Platform (OFP). The evaluation and application results show that this framework is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant illumination, partial/full target occlusion, blur motion, rapid pose variation and onboard mechanical vibration, among others. To our best knowledge, this is the first work to present this framework for solving the online learning and tracking freewill 2D/3D target problems, and applied it in the UAVs.
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Sin duda, el rostro humano ofrece mucha más información de la que pensamos. La cara transmite sin nuestro consentimiento señales no verbales, a partir de las interacciones faciales, que dejan al descubierto nuestro estado afectivo, actividad cognitiva, personalidad y enfermedades. Estudios recientes [OFT14, TODMS15] demuestran que muchas de nuestras decisiones sociales e interpersonales derivan de un previo análisis facial de la cara que nos permite establecer si esa persona es confiable, trabajadora, inteligente, etc. Esta interpretación, propensa a errores, deriva de la capacidad innata de los seres humanas de encontrar estas señales e interpretarlas. Esta capacidad es motivo de estudio, con un especial interés en desarrollar métodos que tengan la habilidad de calcular de manera automática estas señales o atributos asociados a la cara. Así, el interés por la estimación de atributos faciales ha crecido rápidamente en los últimos años por las diversas aplicaciones en que estos métodos pueden ser utilizados: marketing dirigido, sistemas de seguridad, interacción hombre-máquina, etc. Sin embargo, éstos están lejos de ser perfectos y robustos en cualquier dominio de problemas. La principal dificultad encontrada es causada por la alta variabilidad intra-clase debida a los cambios en la condición de la imagen: cambios de iluminación, oclusiones, expresiones faciales, edad, género, etnia, etc.; encontradas frecuentemente en imágenes adquiridas en entornos no controlados. Este de trabajo de investigación estudia técnicas de análisis de imágenes para estimar atributos faciales como el género, la edad y la postura, empleando métodos lineales y explotando las dependencias estadísticas entre estos atributos. Adicionalmente, nuestra propuesta se centrará en la construcción de estimadores que tengan una fuerte relación entre rendimiento y coste computacional. Con respecto a éste último punto, estudiamos un conjunto de estrategias para la clasificación de género y las comparamos con una propuesta basada en un clasificador Bayesiano y una adecuada extracción de características. Analizamos en profundidad el motivo de porqué las técnicas lineales no han logrado resultados competitivos hasta la fecha y mostramos cómo obtener rendimientos similares a las mejores técnicas no-lineales. Se propone un segundo algoritmo para la estimación de edad, basado en un regresor K-NN y una adecuada selección de características tal como se propuso para la clasificación de género. A partir de los experimentos desarrollados, observamos que el rendimiento de los clasificadores se reduce significativamente si los ´estos han sido entrenados y probados sobre diferentes bases de datos. Hemos encontrado que una de las causas es la existencia de dependencias entre atributos faciales que no han sido consideradas en la construcción de los clasificadores. Nuestro resultados demuestran que la variabilidad intra-clase puede ser reducida cuando se consideran las dependencias estadísticas entre los atributos faciales de el género, la edad y la pose; mejorando el rendimiento de nuestros clasificadores de atributos faciales con un coste computacional pequeño. Abstract Surely the human face provides much more information than we think. The face provides without our consent nonverbal cues from facial interactions that reveal our emotional state, cognitive activity, personality and disease. Recent studies [OFT14, TODMS15] show that many of our social and interpersonal decisions derive from a previous facial analysis that allows us to establish whether that person is trustworthy, hardworking, intelligent, etc. This error-prone interpretation derives from the innate ability of human beings to find and interpret these signals. This capability is being studied, with a special interest in developing methods that have the ability to automatically calculate these signs or attributes associated with the face. Thus, the interest in the estimation of facial attributes has grown rapidly in recent years by the various applications in which these methods can be used: targeted marketing, security systems, human-computer interaction, etc. However, these are far from being perfect and robust in any domain of problems. The main difficulty encountered is caused by the high intra-class variability due to changes in the condition of the image: lighting changes, occlusions, facial expressions, age, gender, ethnicity, etc.; often found in images acquired in uncontrolled environments. This research work studies image analysis techniques to estimate facial attributes such as gender, age and pose, using linear methods, and exploiting the statistical dependencies between these attributes. In addition, our proposal will focus on the construction of classifiers that have a good balance between performance and computational cost. We studied a set of strategies for gender classification and we compare them with a proposal based on a Bayesian classifier and a suitable feature extraction based on Linear Discriminant Analysis. We study in depth why linear techniques have failed to provide competitive results to date and show how to obtain similar performances to the best non-linear techniques. A second algorithm is proposed for estimating age, which is based on a K-NN regressor and proper selection of features such as those proposed for the classification of gender. From our experiments we note that performance estimates are significantly reduced if they have been trained and tested on different databases. We have found that one of the causes is the existence of dependencies between facial features that have not been considered in the construction of classifiers. Our results demonstrate that intra-class variability can be reduced when considering the statistical dependencies between facial attributes gender, age and pose, thus improving the performance of our classifiers with a reduced computational cost.
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La aparición y avance de la enfermedad del marchitamiento del pino (Pine Wilt Desease, PWD), causada por Bursaphelenchus xylophilus (Nematoda; Aphelenchoididae), el nematodo de la madera del pino (NMP), en el suroeste de Europa, ha puesto de manifiesto la necesidad de estudiar la fenología y la dispersión de su único vector conocido en Europa, Monochamus galloprovincialis (Col., Cerambycidae). El análisis de 12 series de emergencias entre 2010 y 2014, registradas en Palencia, València y Teruel, con material procedente de diversos puntos de la península ibérica, demostró una alta variabilidad en la fenología de M. galloprovincialis y la divergencia térmica respecto de las poblaciones portuguesas. Para éstas, el establecimiento de los umbrales térmicos de desarrollo de las larvas post-dormantes del vector (12,2 y 33,5ºC) permitió la predicción de la emergencia mediana para la fecha en la que se acumulaban de 822 grados-día. Ninguna de las series analizadas en este trabajo necesitó de dichos grados-día estimados para la emergencia mediana. Asimismo, la emergencia se adelantó en las regiones más calurosas, mientras que se retrasó en las zonas más templadas. Más allá de la posible variabilidad entre poblaciones locales peninsulares, se detectaron indicios de que la diferencia en la acumulación de calor durante el otoño puede afectar el grado de maduración de las larvas invernantes, y su posterior patrón temporal de emergencia. Por último, también fueron observados comportamientos de protandria en las emergencias. Respecto a la fenología de su vuelo, entre los años 2010 y 2015, fueron ejecutados un total de 8 experimentos de captura de M. galloprovincialis mediante trampas cebadas con atrayentes en diferentes regiones (Castellón, Teruel, Segovia y Alicante) permitiendo el seguimiento del periodo de vuelo. Su análisis permitió constatar la disminución de las capturas y el acortamiento del periodo de vuelo con la altitud, el inicio del vuelo en el mes de mayo/junio a partir de los 14ºC de temperatura media diaria, la influencia de las altas temperaturas en la disminución de las capturas estivales (potencial causante de perfiles bimodales en las curvas de vuelo en las zonas menos frías), la evolución de la proporción de sexos a lo largo del periodo de vuelo (que muestra una mayor captura de hembras al inicio y de machos al final) y el comportamiento diurno y ligado a las altas temperaturas del vuelo circadiano del insecto. Dos redes de muestreo sistemático de insectos saproxílicos instaladas en la Comunitat Valencia (Red MUFFET, 15 parcelas, año 2013) y en Murcia (Red ESFP, 20 parcelas, años 2008-2010) permitieron el estudio de la comunidad de insectos relacionada con M. galloprovincialis. Cada una de las parcelas contaba con una trampa cebada con atrayentes y una estación meteorológica. El registro de más de 250 especies de coleópteros saproxílicos demostró el potencial que tiene el empleo de redes de trampas vigía para la detección temprana de organismos exóticos, además de permitir la caracterización y evaluación de las comunidades de entomofauna útil, representando una de las mejores herramientas de la gestión integrada de plagas. En este caso, la comunidad de saproxílicos estudiada mostró ser muy homogénea respecto a la variación ambiental de las zonas de muestreo, y que pese a las pequeñas variaciones entre las comunidades de los diferentes ecosistemas, el rol que M. galloprovincialis desempeña en ellas a lo largo de todo el gradiente estudiado es el mismo. Con todo, el análisis mediante redes de interacción mostró su relevancia ecológica al actuar de conector entre los diferentes niveles tróficos. Por último, un total de 12 experimentos de marcaje-liberación-recaptura desarrollados entre 2009 y 2012 en Castellón, Teruel, Valencia y Murcia permitieron evaluar el comportamiento dispersivo de M. galloprovincialis. Las detecciones mediante trampas cebadas de los insectos liberados se dieron por lo menos 8 días después de la emergencia. La abundancia de población pareció relacionada con la continuidad, la naturalización de la masa, y con la afección previa de incendios. La dispersión no estuvo influida por la dirección ni la intensidad de los vientos dominantes. La abundancia de material hospedante (en lo referente a las variables de masa y a los índices de competencia) influyó en la captura del insecto en paisajes fragmentados, aunque la ubicación de las trampas optimizó el número de capturas cuando se ubicaron en el límite de la masa y en zonas visibles. Por último también se constató que M. galloprovincialis posee suficiente capacidad de dispersión como para recorrer hasta 1500 m/día, llegando a alcanzar distancias máximas de 13600m o de 22100 m. ABSTRACT The detection and expansion of the Pine Wilt Desease (PWD), caused by Bursaphelenchus xylophilus (Nematoda; Aphelenchoididae), Pine Wood Nematode (PWN), in southwestern Europe since 1999, has triggered off the study of the phenology and the dispersion of its unique vector in the continent, Monochamus galloprovincialis (Coleoptera, Cerambycidae). The analysis of 12 emergence series between 2010 and 2014 registered in Palencia, Teruel and Valencia (Spain), registered from field colonized material collected at several locations of the Iberian Peninsula, showed a high variability in the emergence phenology of M. galloprovincialis. In addition, these patterns showed a very acute thermal divergence regarding a development model fitted earlier in Portugal. Such model forecasted the emergence of 50% of M. galloprovincialis individuals in the Setúbal Peninsula (Portugal) when an average of 822 degree-days (DD) were reached, based on the accumulation of heat from the 1st of March until emergence and lower and upper thresholds of 12.2 ºC and 33,5 °C respectively. In our results, all analyzed series needed less than 822 DD to complete the 50% of the emergence. Also, emergency occurred earlier in the hottest regions, while it was delayed in more temperate areas. Beyond the possible variability between local populations, the difference in the heat accumulation during the fall season may have affected the degree of maturation of overwintering larvae, and subsequently, the temporal pattern of M. galloprovincialis emergences. Therefore these results suggest the need to differentiate local management strategies for the PWN vector, depending on the location, and the climatic variables of each region. Finally, protandrous emergence patterns were observed for M. galloprovincialis in most of the studied data-sets. Regarding the flight phenology of M. galloprovincialis, a total of 8 trapping experiments were carried out in different regions of the Iberian Peninsula (Castellón, Teruel, Segovia and Alicante) between 2010 and 2015. The use of commercial lures and traps allowed monitoring of the flight period of M. galloprovincialis. The analyses of such curves, helped confirming different aspects. First, a decline in the number of catches and a shortening of the flight period was observed as the altitude increased. Flight period was recorded to start in May / June when the daily average temperature went over 14 ° C. A significant influence of high temperatures on the decrease of catches in the summer was found in many occasions, which frequently lead to a bimodal profile of the flight curves in warm areas. The evolution of sex ratio along the flight period shows a greater capture of females at the beginning of the period, and of males at the end. In addition, the circadian response of M. galloprovincialis to lured traps was described for the first time, concluding that the insect is diurnal and that such response is linked to high temperatures. Two networks of systematic sampling of saproxylic insects were installed in the Region of Valencia (Red MUFFET, 15 plots, 2013) and Murcia (Red ICPF, 20 plots, 2008-2010). These networks, intended to serve the double purpose of early-detection and long term monitoring of the saproxylic beetle assemblies, allowed the study of insect communities related to M. galloprovincialis. Each of the plots had a trap baited with attractants and a weather station. The registration of almost 300 species of saproxylic beetles demonstrated the potential use of such trapping networks for the early detection of exotic organisms, while at the same time allows the characterization and evaluation of useful entomological fauna communities, representing one of the best tools for the integrated pest management. In this particular case, the studied community of saproxylic beetles was very homogeneous with respect to environmental variation of the sampling areas, and despite small variations between communities of different ecosystems, the role that M. galloprovincialis apparently plays in them across the studied gradient seems to be the same. However, the analysis through food-webs showed the ecological significance of M. galloprovincialis as a connector between different trophic levels. Finally, 12 mark-release-recapture experiments were carried out between 2009 and 2012 in Castellón, Teruel, Valencia and Murcia (Spain) with the aim to describe the dispersive behavior of M. galloprovincialis as well as the stand and landscape characteristics that could influence its abundance and dispersal. No insects younger than 8 days were caught in lured traps. Population abundance estimates from mark-release-recapture data, seemed related to forest continuity, naturalization, and to prior presence of forest fires. On the other hand, M. galloprovincialis dispersal was not found to be significantly influenced by the direction and intensity of prevailing winds. The abundance of host material, very related to stand characteristics and spacing indexes, influenced the insect abundance in fragmented landscapes. In addition, the location of the traps optimized the number of catches when they were placed in the edge of the forest stands and in visible positions. Finally it was also found that M. galloprovincialis is able to fly up to 1500 m / day, reaching maximum distances of up to 13600 m or 22100 m.
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Autoaggregation in bacteria is the phenomenon of aggregation between cells of the same strain, whereas coaggregation is due to aggregation occurring among different species. Aggregation ability of prebiotic bacteria is related to adhesion ability, which is a prerequisite for the colonization and protection of the gastrointestinal tract in all animal species; however, coaggregation ability of prebiotic bacteria offers a possibility of close interaction with pathogenic bacteria.
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Attempted hydrogen–deuterium exchange of trimethyloxonium ion, (CH3)3O+ with excess of 1:1 2HF/SbF5 superacid at −30°C over a period of 30 days showed no exchange. Theoretical calculations at the MP2/6–31G** level are in accord with the lack of hydrogen–deuterium exchange in the methyl group of the (CH3)3O+ cation as protonation (protosolvation) prefers the oxygen lone pair of electrons, instead of a C—H bond. Methylation of aromatics with the (CH3)3O+CF3SO3− in CF3SO3H and 2CF3SO3H:B(O3SCF3)3 was also studied. Whereas in triflic acid no alkylation was observed, in triflatoboric acid, a powerful superacid, alkylation takes place, indicating protolytic activation of the trimethyloxonium ion.
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Although infection by primary HIV type 1 (HIV-1) isolates normally requires the functional interaction of the viral envelope protein with both CD4 and the CCR-5 coreceptor, a subset of such isolates also are able to use the distinct CCR-3 receptor. By analyzing the ability of a series of wild-type and chimeric HIV-1 envelope proteins to mediate CCR-3-dependent infection, we have determined that CCR-3 tropism maps to the V1 and V2 variable region of envelope. Although substitution of the V1/V2 region of a CCR-3 tropic envelope into the context of a CCR-5 tropic envelope is both necessary and sufficient to confer CCR-3 tropism, this same substitution has no phenotypic effect when inserted into a CXCR-4 tropic HIV-1 envelope context. However, this latter chimera acquires both CCR-3 and CCR-5 tropism when a CCR-5 tropic V3 loop sequence also is introduced. These data demonstrate that the V1/2 region of envelope can, like the V3 loop region, encode a particular coreceptor requirement and suggest that a functional envelope:CCR-3 interaction may depend on the cooperative interaction of CCR-3 with both the V1/V2 and the V3 region of envelope.
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Compound 1 (F), a nonpolar nucleoside analog that is isosteric with thymidine, has been proposed as a probe for the importance of hydrogen bonds in biological systems. Consistent with its lack of strong H-bond donors or acceptors, F is shown here by thermal denaturation studies to pair very poorly and with no significant selectivity among natural bases in DNA oligonucleotides. We report the synthesis of the 5′-triphosphate derivative of 1 and the study of its ability to be inserted into replicating DNA strands by the Klenow fragment (KF, exo− mutant) of Escherichia coli DNA polymerase I. We find that this nucleotide derivative (dFTP) is a surprisingly good substrate for KF; steady-state measurements indicate it is inserted into a template opposite adenine with efficiency (Vmax/Km) only 40-fold lower than dTTP. Moreover, it is inserted opposite A (relative to C, G, or T) with selectivity nearly as high as that observed for dTTP. Elongation of the strand past F in an F–A pair is associated with a brief pause, whereas that beyond A in the inverted A–F pair is not. Combined with data from studies with F in the template strand, the results show that KF can efficiently replicate a base pair (A–F/F–A) that is inherently very unstable, and the replication occurs with very high fidelity despite a lack of inherent base-pairing selectivity. The results suggest that hydrogen bonds may be less important in the fidelity of replication than commonly believed and that nucleotide/template shape complementarity may play a more important role than previously believed.
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An evolutionary process is simulated with a simple spin-glass-like model of proteins to examine the origin of folding ability. At each generation, sequences are randomly mutated and subjected to a simulation of the folding process based on the model. According to the frequency of local configurations at the active sites, sequences are selected and passed to the next generation. After a few hundred generations, a sequence capable of folding globally into a native conformation emerges. Moreover, the selected sequence has a distinct energy minimum and an anisotropic funnel on the energy surface, which are the imperative features for fast folding of proteins. The proposed model reveals that the functional selection on the local configurations leads a sequence to fold globally into a conformation at a faster rate.
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CM101, an antiangiogenic polysaccharide derived from group B streptococcus, was administered by i.v. injection 1 hr post-spinal-cord crush injury in an effort to prevent inflammatory angiogenesis and gliosis (scarring) in a mouse model. We postulated that gliosis would sterically prevent the reestablishment of neuronal connectivity; thus, treatment with CM101 was repeated every other day for five more infusions for the purpose of facilitating regeneration of neuronal function. Twenty-five of 26 mice treated with CM101 survived 28 days after surgery, and 24 of 26 recovered walking ability within 2–12 days. Only 6 of 14 mice in the control groups survived 24 hr after spinal cord injury, and none recovered function in paralyzed limbs. MRI analysis of injured untreated and treated animals showed that CM101 reduced the area of damage at the site of spinal cord compression, which was corroborated by histological analysis of spinal cord sections from treated and control animals. Electrophysiologic measurements on isolated central nervous system and neurons in culture showed that CM101 protected axons from Wallerian degeneration; reversed γ-aminobutyrate-mediated depolarization occurring in traumatized neurons; and improved recovery of neuronal conductivity of isolated central nervous system in culture.
Resumo:
Monoclonal antibodies (mAbs) that exert antitumor activity can do so by virtue of their effector function and/or their ability to signal growth arrest or cell death. In this study, we demonstrate that mAbs which have little or no signaling activity—i.e., anti-CD19, CD20, CD21, CD22 and Her-2—can become potent antitumor agents when they are converted into IgG–IgG homodimers. The homodimers exert antigrowth activity by signaling G0/G1 arrest or apoptosis, depending upon which cell surface molecule they bind. This activity is specific and, in the case of the anti-CD19 mAb, did not require an Fc portion. These results offer the possibility that homodimers of other tumor-reactive mAbs which have little antitumor activity as monomers might be potent, antitumor agents.