890 resultados para phylogeography, consensus approach, ensemble modeling, Pleistocene, ENM, ecological niche modeling
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Understanding the impact of geological events on diversification processes is central to evolutionary ecology. The recent amalgamation between ecological niche models (ENMs) and phylogenetic analyses has been used to estimate historical ranges of modern lineages by projecting current ecological niches of organisms onto paleoclimatic reconstructions. A critical assumption underlying this approach is that niches are stable over time. Using Notophthalmus viridescens (eastern newt), in which four ecologically diverged subspecies are recognized, we introduce an analytical framework free from the niche stability assumption to examine how refugial retreat and subsequent postglacial expansion have affected intraspecific ecological divergence. We found that the current subspecies designation was not congruent with the phylogenetic lineages. Thus, we examined ecological niche overlap between the refugial and modern populations, in both subspecies and lineage, by creating ENMs independently for modern and estimated last glacial maximum (LGM) newt populations, extracting bioclimate variables by randomly generated points, and conducting principal component analyses. Our analyses consistently showed that when tested as a hypothesis, rather than used as an assumption, the niches of N. viridescens lineages have been unstable since the LGM (both subspecies and lineages). There was greater ecological niche differentiation among the subspecies than the modern phylogenetic lineages, suggesting that the subspecies, rather than the phylogenetic lineages, is the unit of the current ecological divergence. The present study found little evidence that the LGM refugial retreat caused the currently observed ecological divergence and suggests that ecological divergence has occurred during postglacial expansion to the current distribution ranges.
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Embedded siloxane polymer waveguides have shown promising results for use in optical backplanes. They exhibit high temperature stability, low optical absorption, and require common processing techniques. A challenging aspect of this technology is out-of-plane coupling of the waveguides. A multi-software approach to modeling an optical vertical interconnect (via) is proposed. This approach utilizes the beam propagation method to generate varied modal field distribution structures which are then propagated through a via model using the angular spectrum propagation technique. Simulation results show average losses between 2.5 and 4.5 dB for different initial input conditions. Certain configurations show losses of less than 3 dB and it is shown that in an input/output pair of vias, average losses per via may be lower than the targeted 3 dB.
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Agricultural and forest productive diversification depends on multiple socioeconomic drivers—like knowledge, migration, productive capacity, and market—that shape productive strategies and influence their ecological impacts. Our comparison of indigenous and settlers allows a better understanding of how societies develop different diversification strategies in similar ecological contexts and how the related socioeconomic aspects of diversification are associated with land cover change. Our results suggest that although indigenous people cause less deforestation and diversify more, diversification is not a direct driver of deforestation reduction. A multidimensional approach linking sociocognitive, economic, and ecological patterns of diversification helps explain this contradiction.
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Anticancer drugs typically are administered in the clinic in the form of mixtures, sometimes called combinations. Only in rare cases, however, are mixtures approved as drugs. Rather, research on mixtures tends to occur after single drugs have been approved. The goal of this research project was to develop modeling approaches that would encourage rational preclinical mixture design. To this end, a series of models were developed. First, several QSAR classification models were constructed to predict the cytotoxicity, oral clearance, and acute systemic toxicity of drugs. The QSAR models were applied to a set of over 115,000 natural compounds in order to identify promising ones for testing in mixtures. Second, an improved method was developed to assess synergistic, antagonistic, and additive effects between drugs in a mixture. This method, dubbed the MixLow method, is similar to the Median-Effect method, the de facto standard for assessing drug interactions. The primary difference between the two is that the MixLow method uses a nonlinear mixed-effects model to estimate parameters of concentration-effect curves, rather than an ordinary least squares procedure. Parameter estimators produced by the MixLow method were more precise than those produced by the Median-Effect Method, and coverage of Loewe index confidence intervals was superior. Third, a model was developed to predict drug interactions based on scores obtained from virtual docking experiments. This represents a novel approach for modeling drug mixtures and was more useful for the data modeled here than competing approaches. The model was applied to cytotoxicity data for 45 mixtures, each composed of up to 10 selected drugs. One drug, doxorubicin, was a standard chemotherapy agent and the others were well-known natural compounds including curcumin, EGCG, quercetin, and rhein. Predictions of synergism/antagonism were made for all possible fixed-ratio mixtures, cytotoxicities of the 10 best-scoring mixtures were tested, and drug interactions were assessed. Predicted and observed responses were highly correlated (r2 = 0.83). Results suggested that some mixtures allowed up to an 11-fold reduction of doxorubicin concentrations without sacrificing efficacy. Taken together, the models developed in this project present a general approach to rational design of mixtures during preclinical drug development. ^
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RESUMEN El apoyo a la selección de especies a la restauración de la vegetación en España en los últimos 40 años se ha basado fundamentalmente en modelos de distribución de especies, también llamados modelos de nicho ecológico, que estiman la probabilidad de presencia de las especies en función de las condiciones del medio físico (clima, suelo, etc.). Con esta tesis se ha intentado contribuir a la mejora de la capacidad predictiva de los modelos introduciendo algunas propuestas metodológicas adaptadas a los datos disponibles actualmente en España y enfocadas al uso de los modelos en la selección de especies. No siempre se dispone de datos a una resolución espacial adecuada para la escala de los proyectos de restauración de la vegetación. Sin embrago es habitual contar con datos de baja resolución espacial para casi todas las especies vegetales presentes en España. Se propone un método de recalibración que actualiza un modelo de regresión logística de baja resolución espacial con una nueva muestra de alta resolución espacial. El método permite obtener predicciones de calidad aceptable con muestras relativamente pequeñas (25 presencias de la especie) frente a las muestras mucho mayores (más de 100 presencias) que requería una estrategia de modelización convencional que no usara el modelo previo. La selección del método estadístico puede influir decisivamente en la capacidad predictiva de los modelos y por esa razón la comparación de métodos ha recibido mucha atención en la última década. Los estudios previos consideraban a la regresión logística como un método inferior a técnicas más modernas como las de máxima entropía. Los resultados de la tesis demuestran que esa diferencia observada se debe a que los modelos de máxima entropía incluyen técnicas de regularización y la versión de la regresión logística usada en las comparaciones no. Una vez incorporada la regularización a la regresión logística usando penalización, las diferencias en cuanto a capacidad predictiva desaparecen. La regresión logística penalizada es, por tanto, una alternativa más para el ajuste de modelos de distribución de especies y está a la altura de los métodos modernos con mejor capacidad predictiva como los de máxima entropía. A menudo, los modelos de distribución de especies no incluyen variables relativas al suelo debido a que no es habitual que se disponga de mediciones directas de sus propiedades físicas o químicas. La incorporación de datos de baja resolución espacial proveniente de mapas de suelo nacionales o continentales podría ser una alternativa. Los resultados de esta tesis sugieren que los modelos de distribución de especies de alta resolución espacial mejoran de forma ligera pero estadísticamente significativa su capacidad predictiva cuando se incorporan variables relativas al suelo procedente de mapas de baja resolución espacial. La validación es una de las etapas fundamentales del desarrollo de cualquier modelo empírico como los modelos de distribución de especies. Lo habitual es validar los modelos evaluando su capacidad predictiva especie a especie, es decir, comparando en un conjunto de localidades la presencia o ausencia observada de la especie con las predicciones del modelo. Este tipo de evaluación no responde a una cuestión clave en la restauración de la vegetación ¿cuales son las n especies más idóneas para el lugar a restaurar? Se ha propuesto un método de evaluación de modelos adaptado a esta cuestión que consiste en estimar la capacidad de un conjunto de modelos para discriminar entre las especies presentes y ausentes de un lugar concreto. El método se ha aplicado con éxito a la validación de 188 modelos de distribución de especies leñosas orientados a la selección de especies para la restauración de la vegetación en España. Las mejoras metodológicas propuestas permiten mejorar la capacidad predictiva de los modelos de distribución de especies aplicados a la selección de especies en la restauración de la vegetación y también permiten ampliar el número de especies para las que se puede contar con un modelo que apoye la toma de decisiones. SUMMARY During the last 40 years, decision support tools for plant species selection in ecological restoration in Spain have been based on species distribution models (also called ecological niche models), that estimate the probability of occurrence of the species as a function of environmental predictors (e.g., climate, soil). In this Thesis some methodological improvements are proposed to contribute to a better predictive performance of such models, given the current data available in Spain and focusing in the application of the models to selection of species for ecological restoration. Fine grained species distribution data are required to train models to be used at the scale of the ecological restoration projects, but this kind of data are not always available for every species. On the other hand, coarse grained data are available for almost every species in Spain. A recalibration method is proposed that updates a coarse grained logistic regression model using a new fine grained updating sample. The method allows obtaining acceptable predictive performance with reasonably small updating sample (25 occurrences of the species), in contrast with the much larger samples (more than 100 occurrences) required for a conventional modeling approach that discards the coarse grained data. The choice of the statistical method may have a dramatic effect on model performance, therefore comparisons of methods have received much interest in the last decade. Previous studies have shown a poorer performance of the logistic regression compared to novel methods like maximum entropy models. The results of this Thesis show that the observed difference is caused by the fact that maximum entropy models include regularization techniques and the versions of logistic regression compared do not. Once regularization has been added to the logistic regression using a penalization procedure, the differences in model performance disappear. Therefore, penalized logistic regression may be considered one of the best performing methods to model species distributions. Usually, species distribution models do not consider soil related predictors because direct measurements of the chemical or physical properties are often lacking. The inclusion of coarse grained soil data from national or continental soil maps could be a reasonable alternative. The results of this Thesis suggest that the performance of the models slightly increase after including soil predictors form coarse grained soil maps. Model validation is a key stage of the development of empirical models, such as species distribution models. The usual way of validating is based on the evaluation of model performance for each species separately, i.e., comparing observed species presences or absence to predicted probabilities in a set of sites. This kind of evaluation is not informative for a common question in ecological restoration projects: which n species are the most suitable for the environment of the site to be restored? A method has been proposed to address this question that estimates the ability of a set of models to discriminate among present and absent species in a evaluation site. The method has been successfully applied to the validation of 188 species distribution models used to support decisions on species selection for ecological restoration in Spain. The proposed methodological approaches improve the predictive performance of the predictive models applied to species selection in ecological restoration and increase the number of species for which a model that supports decisions can be fitted.
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In this paper, we present a novel approach to modeling financing constraints of firms. Specifically, we adopt an approach in which firm-level investment is a nonparametric function of some relevant firm characteristics, cash flow in particular. This enables us to generate firm-year specific measures of cash flow sensitivity of investment. We are therefore able to draw conclusions about financing constraints of individual firms as well as cohorts of firms without having to split our sample on an ad hoc basis. This is a significant improvement over the stylized approach that is based on comparison of point estimates of cash flow sensitivity of investment of the average firm of ad hoc sub-samples of firms. We use firm-level data from India to highlight the advantages of our approach. Our results suggest that the estimates generated by this approach are meaningful from an economic point of view and are consistent with the literature. © 2014 © 2014 Taylor & Francis.
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Tese (doutorado)—Universidade de Brasília, Instituto de Ciências Biológicas, Programa de Pós-Graduação em Ecologia, 2016.
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Integrative taxonomy tests the validity of taxa using methods additional to traditional morphology. The existence of two different morphotypes in specimens identified as Chrysotoxum vernale Loew (Diptera: Syrphidae) prompted their taxonomic study using an integrative approach that included morphology, wing and male-surstylus geometric morphometrics, genetic and ecological analyses. As a result, a new species is recognised, Chrysotoxum montanum Nedeljković & Vujić sp. nov., and C. vernale is re-defined. A lectotype and paralectotypes are designated for C. vernale to stabilize this concept. An additional species, Chrysotoxum orthostylum Vujić sp. nov., with distinctive male genitalia is also described. The three species share an antenna with the basoflagellomere shorter than the scape plus pedicel and terga with yellow fasciae not reaching the lateral margins. This study confirms the value of integrative approach for resolving species boundaries.
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Legionella is a Gram-negative bacterium that represent a public health issue, with heavy social and economic impact. Therefore, it is mandatory to provide a proper environmental surveillance and risk assessment plan to perform Legionella control in water distribution systems in hospital and community buildings. The thesis joins several methodologies in a unique workflow applied for the identification of non-pneumophila Legionella species (n-pL), starting from standard methods as culture and gene sequencing (mip and rpoB), and passing through innovative approaches as MALDI-TOF MS technique and whole genome sequencing (WGS). The results obtained, were compared to identify the Legionella isolates, and lead to four presumptive novel Legionella species identification. One of these four new isolates was characterized and recognized at taxonomy level with the name of Legionella bononiensis (the 64th Legionella species). The workflow applied in this thesis, help to increase the knowledge of Legionella environmental species, improving the description of the environment itself and the events that promote the growth of Legionella in their ecological niche. The correct identification and characterization of the isolates permit to prevent their spread in man-made environment and contain the occurrence of cases, clusters, or outbreaks. Therefore, the experimental work undertaken, could support the preventive measures during environmental and clinical surveillance, improving the study of species often underestimated or still unknown.
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Volitional animal resistance training constitutes an important approach to modeling human resistance training. However, the lack of standardization protocol poses a frequent impediment to the production of skeletal muscle hypertrophy and the study of related physiological variables (i.e., cellular damage/inflammation or metabolic stress). Therefore, the purposes of the present study were: (1) to test whether a long-term and low frequency experimental resistance training program is capable of producing absolute increases in muscle mass; (2) to examine whether cellular damage/inflammation or metabolic stress is involved in the process of hypertrophy. In order to test this hypothesis, animals were assigned to a sedentary control (C, n = 8) or a resistance trained group (RT, n = 7). Trained rats performed 2 exercise sessions per week (16 repetitions per day) during 12 weeks. Our results demonstrated that the resistance training strategy employed was capable of producing absolute mass gain in both soleus and plantaris muscles (12%, p<0.05). Furthermore, muscle tumor necrosis factor (TNF-alpha) protein expression (soleus muscle) was reduced by 24% (p<0.01) in trained group when compared to sedentary one. Finally, serum creatine kinase (CK) activity and serum lactate concentrations were not affected in either group. Such information may have practical applications if reproduced in situations where skeletal muscle hypertrophy is desired but high mechanical stimuli of skeletal muscle and inflammation are not. Copyright (C) 2010 John Wiley & Sons, Ltd.
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Nowadays, there is a trend for industry reorganization in geographically dispersed systems, carried out of their activities with autonomy. These systems must maintain coordinated relationship among themselves in order to assure an expected performance of the overall system. Thus, a manufacturing system is proposed, based on ""web services"" to assure an effective orchestration of services in order to produce final products. In addition, it considers special functions, such as teleoperation and remote monitoring, users` online request, among others. Considering the proposed system as discrete event system (DES), techniques derived from Petri nets (PN), including the Production Flow Schema (PFS), can be used in a PFS/PN approach for modeling. The system is approached in different levels of abstraction: a conceptual model which is obtained by applying the PFS technique and a functional model which is obtained by applying PN. Finally, a particular example of the proposed system is presented.
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This review describes the current multidisciplinary management of gastrointestinal stromal tumor (GIST), which is the most common sarcoma of the gastrointestinal tract. Before 2001, surgery was the only effective therapy for GIST. The discovery of the central role of KIT proto-oncogene mutations in the pathogenesis of this tumor, and the development of specific inhibitors of KIT tyrosine kinase (TK) function, has changed the paradigm of treatment for GISTs. Imatinib and sunitinib are TK inhibitors with activity against GISTs. Their major established role in GIST is in the treatment of advanced disease. A growing body of literature and clinical experience support the potential perioperative use of these drugs. The adjuvant use of imatinib is based on retrospective series and limited prospective studies demonstrating that imatinib reduces the risk of recurrence. Ongoing studies are further defining the length of adjuvant therapy, as well as identifying the patients that could achieve the best results. Neoadjuvant treatment often decreases the tumor size, allowing a less morbid surgery, appears to be safe and beneficial for some patients, and therefore deserves further study.
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The aim of the present study was to evaluate the clinicopathological, immunohistochemical, and molecular genetic features of gastrointestinal stromal tumors in Brazil and compare them with cases from other countries. Five hundred and thirteen cases were retrospectively analyzed. HE-stained sections and clinical information were reviewed and the immunohistochemical expression of CD117, CD34, smooth-muscle actin, S-100 protein, desmin, CD44v3 adhesion molecule, p53 protein, epidermal growth factor receptor, and Ki-67 antigen was studied using tissue microarrays. Mutation analysis of KIT and platelet-derived growth factor receptor-alpha genes was also performed. There was a slight female predominance (50.3%) and the median age at diagnosis was 59 years. The tumors were mainly located in the stomach (38.4%). Immunohistochemistry showed that CD117 was expressed in 95.7% of cases. Epidermal growth factor receptor expression was observed in 84.4% of tumors. p53 protein expression was found only in 2.6% of cases but all belonged to the high-risk group for aggressive behavior according to the National Institutes of Health consensus approach. No CD44v3 adhesion molecule expression was detected. KIT exon 11 mutations were the most frequent (62.2%). The present data confirm that gastrointestinal stromal tumors in Brazilian patients do not differ from tumors occurring in other countries.
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The complex design and development of a planar multilayer phased array antenna in microstrip technology can be simplified using two commercially available design tools 1) Ansoft Ensemble and 2) HP-EEsof Touchstone. In the approach presented here, Touchstone is used to design RF switches and phase shifters whose scattering parameters are incorporated in Ensemble simulations using its black box tool. Using this approach, Ensemble is able to fully analyze the performance of radiating and beamforming layers of a phased array prior to its manufacturing. This strategy is demonstrated in a design example of a 12-element linearly-polarized circular phased array operating at L band. A comparison between theoretical and experimental results of the array is demonstrated.
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The anaerobic ammonium oxidation process is a new process for ammonia removal from wastewater. It is also a new microbial physiology that was previously believed to be impossible. The identification of Candidatus Brocadia anammoxidans and its relatives as the responsible bacteria was only possible with the development of a new experimental approach. That approach is the focus of this paper. The approach is a modernisation of the Winogradsky/Beyerinck strategy of selective enrichment and is based on the introduction of the molecular toolbox and modern bioreactor engineering to microbial ecology. It consists of five steps: (1) postulation of an ecological niche based on thermodynamic considerations and macro-ecological field data; (2) engineering of this niche into a laboratory bioreactor for enrichment culture; (3) black-box physiological characterisation of the enrichment culture as a whole; (4) phylogenetic characterisation of the enriched community using molecular tools; (5) physical separation of the dominant members of the enrichment culture using gradient centrifugation and the identification of the species of interest in accordance with Koch's postulates; (6) verification of the in situ importance of these species in the actual ecosystems. The power of this approach is illustrated with a case study: the identification of the planctomycetes responsible for anaerobic ammonium oxidation. We argue that this was impossible using molecular ecology or conventional 'cultivation based techniques' alone. We suggest that the approach might also be used for the microbiological study of many interesting microbes such as anaerobic methane oxidisers.