950 resultados para strategy based organization


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BACKGROUND: MYCN oncogene amplification has been defined as the most important prognostic factor for neuroblastoma (NB), the most common solid extracranial neoplasm in children. High copy numbers are strongly associated with rapid tumor progression and poor outcome, independently of tumor stage or patient age, and this has become an important factor in treatment stratification. PROCEDURE: By real-time quantitative PCR analysis, we evaluated the clinical relevance of circulating MYCN DNA of 267 patients with locoregional or metastatic NB in children less than 18 months of age. RESULTS: For patients in this age group with INSS stage 4 or 4S NB and stage 3 patients, serum-based determination of MYCN DNA sequences had good sensitivity (85%, 83%, and 75% respectively) and high specificity (100%) when compared to direct tumor gene determination. In contrast, the approach showed low sensitivity patients with stages 1 and 2 disease. CONCLUSION: Our results show that the sensitivity of the serum-based MYCN DNA sequence determination depends on the stage of the disease. However, this simple, reproducible assay may represent a reasonably sensitive and very specific tool to assess tumor MYCN status in cases with stage 3 and metastatic disease for whom a wait and see strategy is often recommended.

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PURPOSE: Few studies compare the variabilities that characterize environmental (EM) and biological monitoring (BM) data. Indeed, comparing their respective variabilities can help to identify the best strategy for evaluating occupational exposure. The objective of this study is to quantify the biological variability associated with 18 bio-indicators currently used in work environments. METHOD: Intra-individual (BV(intra)), inter-individual (BV(inter)), and total biological variability (BV(total)) were quantified using validated physiologically based toxicokinetic (PBTK) models coupled with Monte Carlo simulations. Two environmental exposure profiles with different levels of variability were considered (GSD of 1.5 and 2.0). RESULTS: PBTK models coupled with Monte Carlo simulations were successfully used to predict the biological variability of biological exposure indicators. The predicted values follow a lognormal distribution, characterized by GSD ranging from 1.1 to 2.3. Our results show that there is a link between biological variability and the half-life of bio-indicators, since BV(intra) and BV(total) both decrease as the biological indicator half-lives increase. BV(intra) is always lower than the variability in the air concentrations. On an individual basis, this means that the variability associated with the measurement of biological indicators is always lower than the variability characterizing airborne levels of contaminants. For a group of workers, BM is less variable than EM for bio-indicators with half-lives longer than 10-15 h. CONCLUSION: The variability data obtained in the present study can be useful in the development of BM strategies for exposure assessment and can be used to calculate the number of samples required for guiding industrial hygienists or medical doctors in decision-making.

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A dose-response strategy may not only allow investigation of the impact of foods and nutrients on human health but may also reveal differences in the response of individuals to food ingestion based on their metabolic health status. In a randomized crossover study, we challenged 19 normal-weight (BMI: 20-25 kg/m(2)) and 18 obese (BMI: >30 kg/m(2)) men with 500, 1000, and 1500 kcal of a high-fat (HF) meal (60.5% energy from fat). Blood was taken at baseline and up to 6 h postprandially and analyzed for a range of metabolic, inflammatory, and hormonal variables, including plasma glucose, lipids, and C-reactive protein and serum insulin, glucagon-like peptide-1, interleukin-6 (IL-6), and endotoxin. Insulin was the only variable that could differentiate the postprandial response of normal-weight and obese participants at each of the 3 caloric doses. A significant response of the inflammatory marker IL-6 was only observed in the obese group after ingestion of the HF meal containing 1500 kcal [net incremental AUC (iAUC) = 22.9 ± 6.8 pg/mL × 6 h, P = 0.002]. Furthermore, the net iAUC for triglycerides significantly increased from the 1000 to the 1500 kcal meal in the obese group (5.0 ± 0.5 mmol/L × 6 h vs. 6.0 ± 0.5 mmol/L × 6 h; P = 0.015) but not in the normal-weight group (4.3 ± 0.5 mmol/L × 6 h vs. 4.8 ± 0.5 mmol/L × 6 h; P = 0.31). We propose that caloric dose-response studies may contribute to a better understanding of the metabolic impact of food on the human organism. This study was registered at clinicaltrials.gov as NCT01446068.

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To identify malaria antigens for vaccine development, we selected alpha-helical coiled coil domains of proteins predicted to be present in the parasite erythrocytic stage. The corresponding synthetic peptides are expected to mimic structurally "native" epitopes. Indeed the 95 chemically synthesized peptides were all specifically recognized by human immune sera, though at various prevalence. Peptide specific antibodies were obtained both by affinity-purification from malaria immune sera and by immunization of mice. These antibodies did not show significant cross reactions, i.e., they were specific for the original peptide, reacted with native parasite proteins in infected erythrocytes and several were active in inhibiting in vitro parasite growth. Circular dichroism studies indicated that the selected peptides assumed partial or high alpha-helical content. Thus, we demonstrate that the bioinformatics/chemical synthesis approach described here can lead to the rapid identification of molecules which target biologically active antibodies, thus identifying suitable vaccine candidates. This strategy can be, in principle, extended to vaccine discovery in a wide range of other pathogens.

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BACKGROUND: The criteria for choosing relevant cell lines among a vast panel of available intestinal-derived lines exhibiting a wide range of functional properties are still ill-defined. The objective of this study was, therefore, to establish objective criteria for choosing relevant cell lines to assess their appropriateness as tumor models as well as for drug absorption studies. RESULTS: We made use of publicly available expression signatures and cell based functional assays to delineate differences between various intestinal colon carcinoma cell lines and normal intestinal epithelium. We have compared a panel of intestinal cell lines with patient-derived normal and tumor epithelium and classified them according to traits relating to oncogenic pathway activity, epithelial-mesenchymal transition (EMT) and stemness, migratory properties, proliferative activity, transporter expression profiles and chemosensitivity. For example, SW480 represent an EMT-high, migratory phenotype and scored highest in terms of signatures associated to worse overall survival and higher risk of recurrence based on patient derived databases. On the other hand, differentiated HT29 and T84 cells showed gene expression patterns closest to tumor bulk derived cells. Regarding drug absorption, we confirmed that differentiated Caco-2 cells are the model of choice for active uptake studies in the small intestine. Regarding chemosensitivity we were unable to confirm a recently proposed association of chemo-resistance with EMT traits. However, a novel signature was identified through mining of NCI60 GI50 values that allowed to rank the panel of intestinal cell lines according to their drug responsiveness to commonly used chemotherapeutics. CONCLUSIONS: This study presents a straightforward strategy to exploit publicly available gene expression data to guide the choice of cell-based models. While this approach does not overcome the major limitations of such models, introducing a rank order of selected features may allow selecting model cell lines that are more adapted and pertinent to the addressed biological question.

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Summary The specific CD8+ T cell immune response against tumors relies on the recognition by the T cell receptor (TCR) on cytotoxic T lymphocytes (CTL) of antigenic peptides bound to the class I major histocompatibility complex (MHC) molecule. Such tumor associated antigenic peptides are the focus of tumor immunotherapy with peptide vaccines. The strategy for obtaining an improved immune response often involves the design of modified tumor associated antigenic peptides. Such modifications aim at creating higher affinity and/or degradation resistant peptides and require precise structures of the peptide-MHC class I complex. In addition, the modified peptide must be cross-recognized by CTLs specific for the parental peptide, i.e. preserve the structure of the epitope. Detailed structural information on the modified peptide in complex with MHC is necessary for such predictions. In this thesis, the main focus is the development of theoretical in silico methods for prediction of both structure and cross-reactivity of peptide-MHC class I complexes. Applications of these methods in the context of immunotherapy are also presented. First, a theoretical method for structure prediction of peptide-MHC class I complexes is developed and validated. The approach is based on a molecular dynamics protocol to sample the conformational space of the peptide in its MHC environment. The sampled conformers are evaluated using conformational free energy calculations. The method, which is evaluated for its ability to reproduce 41 X-ray crystallographic structures of different peptide-MHC class I complexes, shows an overall prediction success of 83%. Importantly, in the clinically highly relevant subset of peptide-HLAA*0201 complexes, the prediction success is 100%. Based on these structure predictions, a theoretical approach for prediction of cross-reactivity is developed and validated. This method involves the generation of quantitative structure-activity relationships using three-dimensional molecular descriptors and a genetic neural network. The generated relationships are highly predictive as proved by high cross-validated correlation coefficients (0.78-0.79). Together, the here developed theoretical methods open the door for efficient rational design of improved peptides to be used in immunotherapy. Résumé La réponse immunitaire spécifique contre des tumeurs dépend de la reconnaissance par les récepteurs des cellules T CD8+ de peptides antigéniques présentés par les complexes majeurs d'histocompatibilité (CMH) de classe I. Ces peptides sont utilisés comme cible dans l'immunothérapie par vaccins peptidiques. Afin d'augmenter la réponse immunitaire, les peptides sont modifiés de façon à améliorer l'affinité et/ou la résistance à la dégradation. Ceci nécessite de connaître la structure tridimensionnelle des complexes peptide-CMH. De plus, les peptides modifiés doivent être reconnus par des cellules T spécifiques du peptide natif. La structure de l'épitope doit donc être préservée et des structures détaillées des complexes peptide-CMH sont nécessaires. Dans cette thèse, le thème central est le développement des méthodes computationnelles de prédiction des structures des complexes peptide-CMH classe I et de la reconnaissance croisée. Des applications de ces méthodes de prédiction à l'immunothérapie sont également présentées. Premièrement, une méthode théorique de prédiction des structures des complexes peptide-CMH classe I est développée et validée. Cette méthode est basée sur un échantillonnage de l'espace conformationnel du peptide dans le contexte du récepteur CMH classe I par dynamique moléculaire. Les conformations sont évaluées par leurs énergies libres conformationnelles. La méthode est validée par sa capacité à reproduire 41 structures des complexes peptide-CMH classe I obtenues par cristallographie aux rayons X. Le succès prédictif général est de 83%. Pour le sous-groupe HLA-A*0201 de complexes de grande importance pour l'immunothérapie, ce succès est de 100%. Deuxièmement, à partir de ces structures prédites in silico, une méthode théorique de prédiction de la reconnaissance croisée est développée et validée. Celle-ci consiste à générer des relations structure-activité quantitatives en utilisant des descripteurs moléculaires tridimensionnels et un réseau de neurones couplé à un algorithme génétique. Les relations générées montrent une capacité de prédiction remarquable avec des valeurs de coefficients de corrélation de validation croisée élevées (0.78-0.79). Les méthodes théoriques développées dans le cadre de cette thèse ouvrent la voie du design de vaccins peptidiques améliorés.

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Social organisms exhibit conspicuous intraspecific variation in all facets of their social organization. A prominent example of such variation in the highly eusocial Hymenoptera is differences in the number of reproductive queens per colony, Differences in queen number in ants are associated with differences in a host of reproductive and social traits, including queen phenotype and breeding strategy, mode of colony reproduction, and pattern of sex allocation. We examine the causes and consequences of changes in colony queen number and associated traits using the fire ant Solenopsis invicta as a principal model. Ecological constraints on mode of colony founding may act as important selective forces causing the evolution of queen number in this and many other ants, with social organization generally perpetuated across generations by means of the social environment molding appropriate queen phenotypes and reproductive strategies. Shifts in colony queen number have profound effects on genetic structure within nests and may also influence genetic structure at higher levels (aggregations of nests or local demes) because of the association of queen number with particular mating and dispersal habits. Divergence of breeding habits between populations with different social organizations has the potential to promote genetic differentiation between these social variants. Thus, evolution of social organization can be important in generating intrinsic selective regimes that channel subsequent social evolution and in initiating the development of significant population genetic structure, including barriers to gene flow important in cladogenesis.

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Cyst-based ecotoxicological tests are simple and low-cost methods for assessing acute toxicity. Nevertheless, only a few comparative studies on their sensitivity are known. In the present study, the suitability of the use of two freshwater Anostracan species, Streptocephalus rubricaudatus and S. texanus, was assessed. The impact of 16 priority pollutants (4 heavy metals, 11 organic, and 1 organometallic compounds) on these two species, as well as on Artemia salina (Artoxkit M), Daphnia magna (International Organization for Standardization 6341), and S. proboscideus (Streptoxkit F) was assessed. For indicative comparison, bioassays using Brachionus calyciflorus (Rotoxkit F) and Photobacterium phosphoreum (Microtox) were also performed. For heavy metals (K2Cr2O7, Cd2+, Zn2+, Cu2+), the sensitivity of the two studied Streptocephalus species was slightly higher than that of D. magna. It was significantly more elevated than for the marine A. salina. For organic and organometallic micropollutants [phenol, 3,5-dichlorophenol, pentachlorophenol (PCP), hydroquinone, linear alkylbenzene sulfonate, sodium dodecyl sulfate, tributylphosphate, dimethylphthalate, atrazine, lindane, malathion, tributyltin chloride (TBT-Cl)], the sensitivity of the 4 anostracan species was of the same order of magnitude as that of D. magna. Artemia salina was slightly less sensitive to some organic compounds (PCP, hydroquinone, TBT-Cl). The sensitivity of S. rubricaudatus to organic solvents was low. On the other hand, this anostracan was quite sensitive to NaCl. Thus, its use is restricted to freshwater samples. The evaluation of global practicability of these two tests confirms that cyst-based freshwater anostracans may be used to perform low-cost tests at a sensitivity comparable to that of D. magna (24 h immobilization test).

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PURPOSE: To assess how different diagnostic decision aids perform in terms of sensitivity, specificity, and harm. METHODS: Four diagnostic decision aids were compared, as applied to a simulated patient population: a findings-based algorithm following a linear or branched pathway, a serial threshold-based strategy, and a parallel threshold-based strategy. Headache in immune-compromised HIV patients in a developing country was used as an example. Diagnoses included cryptococcal meningitis, cerebral toxoplasmosis, tuberculous meningitis, bacterial meningitis, and malaria. Data were derived from literature and expert opinion. Diagnostic strategies' validity was assessed in terms of sensitivity, specificity, and harm related to mortality and morbidity. Sensitivity analyses and Monte Carlo simulation were performed. RESULTS: The parallel threshold-based approach led to a sensitivity of 92% and a specificity of 65%. Sensitivities of the serial threshold-based approach and the branched and linear algorithms were 47%, 47%, and 74%, respectively, and the specificities were 85%, 95%, and 96%. The parallel threshold-based approach resulted in the least harm, with the serial threshold-based approach, the branched algorithm, and the linear algorithm being associated with 1.56-, 1.44-, and 1.17-times higher harm, respectively. Findings were corroborated by sensitivity and Monte Carlo analyses. CONCLUSION: A threshold-based diagnostic approach is designed to find the optimal trade-off that minimizes expected harm, enhancing sensitivity and lowering specificity when appropriate, as in the given example of a symptom pointing to several life-threatening diseases. Findings-based algorithms, in contrast, solely consider clinical observations. A parallel workup, as opposed to a serial workup, additionally allows for all potential diseases to be reviewed, further reducing false negatives. The parallel threshold-based approach might, however, not be as good in other disease settings.

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The induction of fungal metabolites by fungal co-cultures grown on solid media was explored using multi-well co-cultures in 2 cm diameter Petri dishes. Fungi were grown in 12-well plates to easily and rapidly obtain the large number of replicates necessary for employing metabolomic approaches. Fungal culture using such a format accelerated the production of metabolites by several weeks compared with using the large-format 9 cm Petri dishes. This strategy was applied to a co-culture of a Fusarium and an Aspergillus strain. The metabolite composition of the cultures was assessed using ultra-high pressure liquid chromatography coupled to electrospray ionisation and time-of-flight mass spectrometry, followed by automated data mining. The de novo production of metabolites was dramatically increased by nutriment reduction. A time-series study of the induction of the fungal metabolites of interest over nine days revealed that they exhibited various induction patterns. The concentrations of most of the de novo induced metabolites increased over time. However, interesting patterns were observed, such as with the presence of some compounds only at certain time points. This result indicates the complexity and dynamic nature of fungal metabolism. The large-scale production of the compounds of interest was verified by co-culture in 15 cm Petri dishes; most of the induced metabolites of interest (16/18) were found to be produced as effectively as on a small scale, although not in the same time frames. Large-scale production is a practical solution for the future production, identification and biological evaluation of these metabolites.

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The increasing popularity of evidence-based practice (EBP) requires that nurses take a stand regarding this type of practice. This positioning rests on knowledge of EBP, however this notion varies by discipline and many definitions exist even within the nursing discipline. An improved understanding of the basic tenets of this type of practice is thus essential. This first, of a series of two articles describes the origin of EBP as well as various definitions, it also presents the major criticisms raised and takes a look at the impact of the increased tendency towards EBP on professional practice.

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This paper presents the segmentation of bilateral parotid glands in the Head and Neck (H&N) CT images using an active contour based atlas registration. We compare segmentation results from three atlas selection strategies: (i) selection of "single-most-similar" atlas for each image to be segmented, (ii) fusion of segmentation results from multiple atlases using STAPLE, and (iii) fusion of segmentation results using majority voting. Among these three approaches, fusion using majority voting provided the best results. Finally, we present a detailed evaluation on a dataset of eight images (provided as a part of H&N auto segmentation challenge conducted in conjunction with MICCAI-2010 conference) using majority voting strategy.

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Evidence-based (EBP) aims for a new distribution of power centered on scientific evidence rather than clinical expertise. The present article describes the operational process of EBP by describing the implementation stages of this type of practise. This stage presentation is essential given that there are many conceptions end models of EBP and that some nurses have a limited knowledge of its rules ans implications. Given that number and formulation of the stages varies by author, the process presented here attempts to integrate the different stages reviewed.

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The discipline of Enterprise Architecture Management (EAM) deals with the alignment of business and information systems architectures. While EAM has long been regarded as a discipline for IT managers this book takes a different stance: It explains how top executives can use EAM for leveraging their strategic planning and controlling processes and how EAM can contribute to sustainable competitive advantage. Based on the analysis of best practices from eight leading European companies from various industries the book presents crucial elements of successful EAM. It outlines what executives need to do in terms of governance, processes, methodologies and culture in order to bring their management to the next level. Beyond this, the book points how EAM might develop in the next decade allowing today's managers to prepare for the future of architecture management.

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This article has been written as a comment to Dr Thomas and Dr Baker's article "Teaching an adult brain new tricks: A critical review of evidence for training-dependent structural plasticity in humans". We deliberately expand on the key question about the biological substrates underlying use-dependent brain plasticity rather than reiterating the authors' main points of criticism already addressed in more general way by previous publications in the field. The focus here is on the following main issues: i) controversial brain plasticity findings in voxel-based morphometry studies are partially due to the strong dependency of the widely used T1-weighted imaging protocol on varying magnetic resonance contrast contributions; ii) novel concepts in statistical analysis allow one to directly infer topological specificity of structural brain changes associated with plasticity. We conclude that iii) voxel-based quantification of relaxometry derived parameter maps could provide a new perspective on use-dependent plasticity by characterisation of brain tissue property changes beyond the estimation of volume and cortical thickness changes. In the relevant sections we respond to the concerns raised by Dr Thomas and Dr Baker from the perspective of the proposed data acquisition and analysis strategy.