845 resultados para declarative, procedural, and reflective (DPR) model
                                
Resumo:
Some patients infected with human immunodeficiency virus (HIV) who are experiencing antiretroviral treatment failure have persistent improvement in CD4+ T cell counts despite high plasma viremia. To explore the mechanisms responsible for this phenomenon, 2 parameters influencing the dynamics of CD4+ T cells were evaluated: death of mature CD4+ T cells and replenishment of the CD4+ T cell pool by the thymus. The improvement in CD4+ T cells observed in patients with treatment failure was not correlated with spontaneous, Fas ligand-induced, or activation-induced T cell death. In contrast, a significant correlation between the improvement in CD4+ T cell counts and thymic output, as assessed by measurement of T cell receptor excision circles, was observed. These observations suggest that increased thymic output contributes to the dissociation between CD4+ T cell counts and viremia in patients failing antiretroviral therapy and support a model in which drug-resistant HIV strains may have reduced replication rates and pathogenicity in the thymus.
                                
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An accurate assessment of the rising ambient temperature by plant cells is crucial for the timely activation of various molecular defences before the appearance of heat damage. Recent findings have allowed a better understanding of the early cellular events that take place at the beginning of mild temperature rise, to timely express heat-shock proteins (HSPs), which will, in turn, confer thermotolerance to the plant. Here, we discuss the key components of the heat signalling pathway and suggest a model in which a primary sensory role is carried out by the plasma membrane and various secondary messengers, such as Ca(2+) ions, nitric oxide (NO) and hydrogen peroxide (H(2) O(2) ). We also describe the role of downstream components, such as calmodulins, mitogen-activated protein kinases and Hsp90, in the activation of heat-shock transcription factors (HSFs). The data gathered for land plants suggest that, following temperature elevation, the heat signal is probably transduced by several pathways that will, however, coalesce into the final activation of HSFs, the expression of HSPs and the onset of cellular thermotolerance.
                                
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The aim of this study was to calibrate the CENTURY, APSIM and NDICEA simulation models for estimating decomposition and N mineralization rates of plant organic materials (Arachis pintoi, Calopogonium mucunoides, Stizolobium aterrimum, Stylosanthes guyanensis) for 360 days in the Atlantic rainforest bioma of Brazil. The models´ default settings overestimated the decomposition and N-mineralization of plant residues, underlining the fact that the models must be calibrated for use under tropical conditions. For example, the APSIM model simulated the decomposition of the Stizolobium aterrimum and Calopogonium mucunoides residues with an error rate of 37.62 and 48.23 %, respectively, by comparison with the observed data, and was the least accurate model in the absence of calibration. At the default settings, the NDICEA model produced an error rate of 10.46 and 14.46 % and the CENTURY model, 21.42 and 31.84 %, respectively, for Stizolobium aterrimum and Calopogonium mucunoides residue decomposition. After calibration, the models showed a high level of accuracy in estimating decomposition and N- mineralization, with an error rate of less than 20 %. The calibrated NDICEA model showed the highest level of accuracy, followed by the APSIM and CENTURY. All models performed poorly in the first few months of decomposition and N-mineralization, indicating the need of an additional parameter for initial microorganism growth on the residues that would take the effect of leaching due to rainfall into account.
                                
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Toxicokinetic modeling is a useful tool to describe or predict the behavior of a chemical agent in the human or animal organism. A general model based on four compartments was developed in a previous study in order to quantify the effect of human variability on a wide range of biological exposure indicators. The aim of this study was to adapt this existing general toxicokinetic model to three organic solvents, which were methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1,-trichloroethane, and to take into account sex differences. We assessed in a previous human volunteer study the impact of sex on different biomarkers of exposure corresponding to the three organic solvents mentioned above. Results from that study suggested that not only physiological differences between men and women but also differences due to sex hormones levels could influence the toxicokinetics of the solvents. In fact the use of hormonal contraceptive had an effect on the urinary levels of several biomarkers, suggesting that exogenous sex hormones could influence CYP2E1 enzyme activity. These experimental data were used to calibrate the toxicokinetic models developed in this study. Our results showed that it was possible to use an existing general toxicokinetic model for other compounds. In fact, most of the simulation results showed good agreement with the experimental data obtained for the studied solvents, with a percentage of model predictions that lies within the 95% confidence interval varying from 44.4 to 90%. Results pointed out that for same exposure conditions, men and women can show important differences in urinary levels of biological indicators of exposure. Moreover, when running the models by simulating industrial working conditions, these differences could even be more pronounced. In conclusion, a general and simple toxicokinetic model, adapted for three well known organic solvents, allowed us to show that metabolic parameters can have an important impact on the urinary levels of the corresponding biomarkers. These observations give evidence of an interindividual variablity, an aspect that should have its place in the approaches for setting limits of occupational exposure.
                                
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A stochastic nonlinear partial differential equation is constructed for two different models exhibiting self-organized criticality: the Bak-Tang-Wiesenfeld (BTW) sandpile model [Phys. Rev. Lett. 59, 381 (1987); Phys. Rev. A 38, 364 (1988)] and the Zhang model [Phys. Rev. Lett. 63, 470 (1989)]. The dynamic renormalization group (DRG) enables one to compute the critical exponents. However, the nontrivial stable fixed point of the DRG transformation is unreachable for the original parameters of the models. We introduce an alternative regularization of the step function involved in the threshold condition, which breaks the symmetry of the BTW model. Although the symmetry properties of the two models are different, it is shown that they both belong to the same universality class. In this case the DRG procedure leads to a symmetric behavior for both models, restoring the broken symmetry, and makes accessible the nontrivial fixed point. This technique could also be applied to other problems with threshold dynamics.
                                
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Résumé : Le glioblastome (GBM, WHO grade IV) est la tumeur cérébrale primaire la plus fréquente et la plus maligne, son pronostic reste très réservé et sa réponse aux différents traitements limitée. Récemment, une étude clinique randomisée (EORTC 26981/NCIC CE.3) a démontré que le traitement combiné de temozolomide et radiothérapie (RT/TMZ) est le meilleur dans les cas de GBM nouvellement diagnostiqués [1]. Cependant, seul un sous-groupe de patients bénéficie du traitement RT/TMZ et même parmi eux, leur survie reste très limitée. Pour tenter de mieux comprendre les réponses au traitement RT/TMZ, la biologie du GBM, identifier d'autres facteurs de résistance et découvrir de nouvelles cibles aux traitements, nous avons conduit une analyse moléculaire étendue à 73 patients inclus dans cette étude clinique. Nous avons complété les résultats moléculaires déjà obtenus par un profil génomique du nombre de copies par Array Comparative Genomic Hybridization. Afin d'atteindre nos objectifs, nous avons analysé en parallèle les données cliniques des patients et leurs profils moléculaires. Nos résultats confirment des analyses connues dans le domaine des aberrations du nombre de copies (CNA) et de profils du glioblastome. Nous avons observé une bonne corrélation entre le CNA génomique et l'expression de l'ARN messager dans le glioblastome et identifié un nouveau modèle de CNA du chromosome 7 pouvant présenter un intérêt clinique. Nous avons aussi observé par l'analyse du CNA que moins de 10% des glioblastomes conservent leurs mécanismes de suppression de tumeurs p53 et Rb1. Nous avons aussi observé que l'amplification du CDK4 peut constituer un facteur supplémentaire de résistance au traitement RT/TMZ, cette observation nécessite confirmation sur un plus grand nombre d'analyses. Nous avons montré que dans notre analyse des profils moléculaires et cliniques, il n'est pas possible de différencier le GBM à composante oligodendrogliale (GBM-O) du glioblastome. En superposant les profils moléculaires et les modèles expérimentaux in vitro, nous avons identifié WIF-1 comme un gène suppresseur de tumeur probable et une activation du signal WNT dans la pathologie du glioblastome. Ces observations pourraient servir à une meilleure compréhension de cette maladie dans le futur. Abstract : Glioblastoma, (GBM, WHO grade IV) is the most malignant and most frequent primary brain tumor with a very poor prognosis and response to therapy. A recent randomized clinical trial (EORTC26981/NCIC CE.3) established RT/TMZ as the 1St effective chemo-radiation therapy in newly diagnosed GBM [1]. However only a genetic subgroup of patients benefit from RT/TMZ and even in this subgroup overall survival remains very dismal. To explain the observed response to RT/TMZ, have a better understanding of GBM biology, identify other resistance factors and discover new drugable targets a comprehensive molecular analysis was performed in 73 of these GBM trial cohort. We complemented the available molecular data with a genomic copy number profiling by Array Comparative Genomic Hybridization. We proceeded to align the molecular profiles and the Clinical data, to meet our project objectives. Our data confirm known GBM Copy Number Aberrations and profiles. We observed a good correlation of genomic CN and mRNA expression in GBM, and identified new interesting CNA pattern for chromosome 7 with a potential clinical value. We also observed that by copy number aberration data alone, less than 10% of GBM have an intact p53 and Rb1 tumor .suppressor pathways. We equally observed that CDK4 amplification might constitute an additional RT/TMZ resistant factor, an observation that will need confirmation in a larger data set. We show that the molecular and clinical profiles in our data set, does not support the identification of GBM-O as a new entity in GBM. By combining the molecular profiles and in vitro model experiments we identify WIF1 as a potential GBM TSG and an activated WNT signaling as a pathologic event in GBM worth incorporation in attempts to better understand and impact outcome in this disease.
                                
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The T cell response to major histocompatibility complex (MHC) alloantigens occurs via two main pathways. The direct pathway involves the recognition of intact allogeneic MHC:peptide complexes on donor cells and provokes uniquely high frequencies of responsive T cells. The indirect response results from alloantigens being processed like any other protein antigen and presented as peptide by autologous antigen-presenting cells. The frequencies of T cells with indirect allospecificity are orders of magnitude lower and comparable to other peptide-specific responses. In this study, we explored the contributions of naïve and memory CD4(+) T cells to these two pathways. Using an adoptive transfer and skin transplantation model we found that naive and memory CD4(+) T cells, both naturally occurring and induced by sensitization with multiple third-party alloantigens, contributed equally to graft rejection when only the direct pathway was operative. In contrast, the indirect response was predominantly mediated by the naïve subset. Elimination of regulatory CD4(+)CD25(+) T cells enabled memory cells to reject grafts through the indirect pathway, but at a much slower tempo than for naïve cells. These findings have implications for better targeting of immunosuppression to inhibit immediate and later forms of alloimmunity.
                                
                                
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In a recent paper, Traulsen and Nowak use a multilevel selection model to show that cooperation can be favored by group selection in finite populations [Traulsen A, Nowak M (2006) Proc Natl Acad Sci USA 103:10952-10955]. The authors challenge the view that kin selection may be an appropriate interpretation of their results and state that group selection is a distinctive process "that permeates evolutionary processes from the emergence of the first cells to eusociality and the economics of nations." In this paper, we start by addressing Traulsen and Nowak's challenge and demonstrate that all their results can be obtained by an application of kin selection theory. We then extend Traulsen and Nowak's model to life history conditions that have been previously studied. This allows us to highlight the differences and similarities between Traulsen and Nowak's model and typical kin selection models and also to broaden the scope of their results. Our retrospective analyses of Traulsen and Nowak's model illustrate that it is possible to convert group selection models to kin selection models without disturbing the mathematics describing the net effect of selection on cooperation.
                                
Resumo:
Capercaillie, Tetrao urogallus, is a threatened species in central Europe, and Swiss populations declined 40 to 50 % between 1970 and 1985. Capercaillie are sensitive to forest structure, and loss of habitat is a major cause of their decline. Knowledge of habitat characteristics is therefore essential for capercaillie conservation. Here, we present models predicting capercaillie probability of occurrence, based on relevant structural habitat variables. Models were built using multiple logistic regression analyses on capercaillie presence/absence data. Vegetation survey was carried out in July 1999 in a 170-km2 forested area (Jura mountains, canton de Vaud, western Switzerland) inhabited by capercaillie and presence/absence of the species was assessed according to dropping presence/absence. The survey was based on 10-m-radius sample plots each in a 1-km2 forest patch (n = 76 with capercaillie droppings, n = 80 without). A first model included seven out of 27 measured habitat variables and a second model only four. The latter model best represents practical needs. It includes three variables which had a negative impact on capercaillie presence: tree and shrub covers and spruce, Picea excelsa, shrub cover, and one which had a positive effect: bilberry, Vaccinium myrtillus, cover, highlighting that capaercaillie selected open forest with high bilberry abundance. The model can be used to map potential capercaillie habitat distribution and to manage the habitat in favour of capercaillie (protection and adapted forestry practices) in the Swiss Jura mountains.
                                
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Aims :¦Several studies have questioned the validity of separating the diagnosis of alcohol abuse from that of alcohol dependence, and the DSM-5 task force has proposed combining the criteria from these two diagnoses to assess a single category of alcohol use disorders (AUD). Furthermore, the DSM-5 task force has proposed including a new 2-symptom threshold and a severity scale based on symptom counts for the AUD diagnosis. The current study aimed to examine these modifications in a large population-based sample.¦Method :¦Data stemmed from an adult sample (N=2588 ; mean age 51.3 years (s.d.: 0.2), 44.9% female) of current and lifetime drinkers from the PsyCoLaus study, conducted in the Lausanne area in Switzerland. AUDs and validating variables were assessed using a semi-structured diagnostic interview for the assessment of alcohol¦and other major psychiatric disorders. First, the adequacy of the proposed 2- symptom threshold was tested by comparing threshold models at each possible cutoff and a linear model, in relation to different validating variables. The model with the smallest Akaike Criterion Information (AIC) value was established as the best¦model for each validating variable. Second, models with varying subsets of individual AUD symptoms were created to assess the associations between each symptom and the validating variables. The subset of symptoms with the smallest AIC value was established as the best subset for each validator.¦Results :¦1) For the majority of validating variables, the linear model was found to be the best fitting model. 2) Among the various subsets of symptoms, the symptoms most frequently associated with the validating variables were : a) drinking despite having knowledge of a physical or psychological problem, b) having had a persistent desire or unsuccessful efforts to cut down or control drinking and c) craving. The¦least frequent symptoms were : d) drinking in larger amounts or over a longer period than was intended, e) spending a great deal of time in obtaining, using or recovering from alcohol use and f) failing to fulfill major role obligations.¦Conclusions :¦The proposed DSM-5 2-symptom threshold did not receive support in our data. Instead, a linear AUD diagnosis was supported with individuals receiving an increasingly severe AUD diagnosis. Moreover, certain symptoms were more frequently associated with the validating variables, which suggests that these¦symptoms should be considered as more severe.
                                
Resumo:
Paleoclimatic reconstructions coupled with species distribution models and identification of extant spatial genetic structure have the potential to provide insights into the demographic events that shape the distribution of intra-specific genetic variation across time. Using the globeflower Trollius europaeus as a case-study, we combined (1) Amplified Fragment Length Polymorphisms, (2) suites of 1000-years stepwise hindcasted species distributions and (3) a model of diffusion through time over the last 24,000 years, to trace the spatial dynamics that most likely fits the species' current genetic structure. We show that the globeflower comprises four gene pools in Europe which, from the dry period preceding the Last Glacial Maximum, dispersed while tracking the conditions fitting its climatic niche. Among these four gene pools, two are predicted to experience drastic range retraction in the near future. Our interdisciplinary approach, applicable to virtually any taxon, is an advance in inferring how climate change impacts species' genetic structures.
                                
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In breast cancer, brain metastases are often seen as late complications of recurrent disease and represent a particularly serious condition, since there are limited therapeutic options and patients have an unfavorable prognosis. The frequency of brain metastases in breast cancer is currently on the rise. This might be due to the fact that adjuvant chemotherapeutic and targeted anticancer drugs, while they effectively control disease progression in the periphery, they only poorly cross the blood-brain barrier and do not reach effectively cancer cells disseminated in the brain. It is therefore of fundamental clinical relevance to investigate mechanisms involved in breast cancer metastasis to the brain. To date experimental models of breast cancer metastasis to the brain described in literature are based on the direct intracarotid or intracardiac injection of breast cancer cells. We recently established a brain metastasis breast cancer model in immunocompetent mice based on the orthotopic injection of 4T1 murine breast carcinoma cells in the mammary gland of syngeneic BALB/c mice. 4T1-derived tumors recapitulate the main steps of human breast cancer progression, including epithelial-to-mesenchymal transition, local invasion and metastatic spreading to lung and lymph nodes. 4T1 cells were engineered to stably express firefly Luciferase allowing noninvasive in vivo and ex vivo monitoring of tumor progression and metastatic spreading to target organs. Bioluminescence imaging revealed the appearance of spontaneous lesions to the lung and lymph nodes and, at a much lower frequency, to the brain. Brain metastases were confirmed by macroscopic and microscopic evaluation of the brains at necropsy. We then isolated brain metastatic cells, re-injected them orthotopically in new mice and isolated again lines from brain metastases. After two rounds of selection we obtained lines metastasizing to the brain with 100% penetrance (named 4T1-BM2 for Brain Metastasis, 2nd generation) compared to lines derived after two rounds of in vivo growth from primary tumors (4T1-T2) or from lung metastases (4T1-LM2). We are currently performing experiments to unravel differences in cell proliferation, adhesion, migration, invasion and survival of the 4T1-BM2 line relative to the 4T1-T2 and 4T1-LM2 lines. Initial results indicate that 4T1-BM2 cells are not more invasive or more proliferative in vitro and do not show a more mesenchymal phenotype. Our syngeneic (BALB/c) model of spontaneous breast carcinoma metastasis to the brain is a unique and clinically relevant model to unravel the mechanisms of metastatic breast cancer colonization of the brain. Genes identified in this model represent potentially clinically relevant therapeutic targets for the prevention and the treatment of brain metastases in breast cancer patients.
                                
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There is a lack of dedicated tools for business model design at a strategic level. However, in today's economic world the need to be able to quickly reinvent a company's business model is essential to stay competitive. This research focused on identifying the functionalities that are necessary in a computer-aided design (CAD) tool for the design of business models in a strategic context. Using design science research methodology a series of techniques and prototypes have been designed and evaluated to offer solutions to the problem. The work is a collection of articles which can be grouped into three parts: First establishing the context of how the Business Model Canvas (BMC) is used to design business models and explore the way in which CAD can contribute to the design activity. The second part extends on this by proposing new technics and tools which support elicitation, evaluation (assessment) and evolution of business models design with CAD. This includes features such as multi-color tagging to easily connect elements, rules to validate coherence of business models and features that are adapted to the correct business model proficiency level of its users. A new way to describe and visualize multiple versions of a business model and thereby help in addressing the business model as a dynamic object was also researched. The third part explores extensions to the business model canvas such as an intermediary model which helps IT alignment by connecting business model and enterprise architecture. And a business model pattern for privacy in a mobile environment, using privacy as a key value proposition. The prototyped techniques and proposition for using CAD tools in business model modeling will allow commercial CAD developers to create tools that are better suited to the needs of practitioners.
                                
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This report is one of two products for this project with the other being a design guide. This report describes test results and comparative analysis from 16 different portland cement concrete (PCC) pavement sites on local city and county roads in Iowa. At each site the surface conditions of the pavement (i.e., crack survey) and foundation layer strength, stiffness, and hydraulic conductivity properties were documented. The field test results were used to calculate in situ parameters used in pavement design per SUDAS and AASHTO (1993) design methodologies. Overall, the results of this study demonstrate how in situ and lab testing can be used to assess the support conditions and design values for pavement foundation layers and how the measurements compare to the assumed design values. The measurements show that in Iowa, a wide range of pavement conditions and foundation layer support values exist. The calculated design input values for the test sites (modulus of subgrade reaction, coefficient of drainage, and loss of support) were found to be different than typically assumed. This finding was true for the full range of materials tested. The findings of this study support the recommendation to incorporate field testing as part of the process to field verify pavement design values and to consider the foundation as a design element in the pavement system. Recommendations are provided in the form of a simple matrix for alternative foundation treatment options if the existing foundation materials do not meet the design intent. The PCI prediction model developed from multi-variate analysis in this study demonstrated a link between pavement foundation conditions and PCI. The model analysis shows that by measuring properties of the pavement foundation, the engineer will be able to predict long term performance with higher reliability than by considering age alone. This prediction can be used as motivation to then control the engineering properties of the pavement foundation for new or re-constructed PCC pavements to achieve some desired level of performance (i.e., PCI) with time.
 
                    