891 resultados para Complex Disease


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PURPOSE: Investigation of the incidence and distribution of congenital structural cardiac malformations among the offspring of mothers with diabetes type 1 and of the influence of periconceptional glycemic control. METHODS: Multicenter retrospective clinical study, literature review, and meta-analysis. The incidence and pattern of congenital heart disease in the own study population and in the literature on the offspring of type 1 diabetic mothers were compared with the incidence and spectrum of the various cardiovascular defects in the offspring of nondiabetic mothers as registered by EUROCAT Northern Netherlands. Medical records were, in addition, reviewed for HbA(1c) during the 1st trimester. RESULTS: The distribution of congenital heart anomalies in the own diabetic study population was in accordance with the distribution encountered in the literature. This distribution differed considerably from that in the nondiabetic population. Approximately half the cardiovascular defects were conotruncal anomalies. The authors' study demonstrated a remarkable increase in the likelihood of visceral heterotaxia and variants of single ventricle among these patients. As expected, elevated HbA(1c) values during the 1st trimester were associated with offspring fetal cardiovascular defects. CONCLUSION: This study shows an increased likelihood of specific heart anomalies, namely transposition of the great arteries, persistent truncus arteriosus, visceral heterotaxia and single ventricle, among offspring of diabetic mothers. This suggests a profound teratogenic effect at a very early stage in cardiogenesis. The study emphasizes the frequency with which the offspring of diabetes-complicated pregnancies suffer from complex forms of congenital heart disease. Pregnancies with poor 1st-trimester glycemic control are more prone to the presence of fetal heart disease.

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A total of 251 bacterial isolates were isolated from blotched mushroom samples obtained from various mushroom farms in Canada. Out of 251 stored isolates, 170 isolates were tested for pathogenicity on Agaricus bisporus through mushroom rapid pitting test with three distinct pathotypes observed: dark brown, brovm and yellow/yellow-brown blotch. Phenotypic analysis of 83 isolates showed two distinct proteinase K resistant peptide profiles. Profile group A isolates exhibited peptides with masses of 45, 18, 16 and 14 kDa and fiirther biochemical tests identified them as Pseudomonasfluorescens III and V. Profile group B isolates lacked the 16-kDa peptide and the blotch causing bacterial isolates of this group was identified as Serratia liquefaciens and Cedecea davisae. Comparative genetic analysis using Amplified Fragment Length Polymorphism (AFLP) on 50 Pseudomonas sp. isolates (Group A) showed that various blotch symptoms were caused by isolates distributed throughout the Pseudomonas sp. clusters with the exception of the Pseudomonas tolaasii group and one non-pathogenic Pseudomonas fluorescens cluster. These results show that seven distinct Pseudomonas sp. genotypes (genetic clusters) have the ability to cause various symptoms of blotch and that AFLP can discriminate blotch causing from non-blotch causing Pseudomonasfluorescens. Therefore, a complex of diverse bacterial organisms causes bacterial blotch disease

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Complex networks have recently attracted a significant amount of research attention due to their ability to model real world phenomena. One important problem often encountered is to limit diffusive processes spread over the network, for example mitigating pandemic disease or computer virus spread. A number of problem formulations have been proposed that aim to solve such problems based on desired network characteristics, such as maintaining the largest network component after node removal. The recently formulated critical node detection problem aims to remove a small subset of vertices from the network such that the residual network has minimum pairwise connectivity. Unfortunately, the problem is NP-hard and also the number of constraints is cubic in number of vertices, making very large scale problems impossible to solve with traditional mathematical programming techniques. Even many approximation algorithm strategies such as dynamic programming, evolutionary algorithms, etc. all are unusable for networks that contain thousands to millions of vertices. A computationally efficient and simple approach is required in such circumstances, but none currently exist. In this thesis, such an algorithm is proposed. The methodology is based on a depth-first search traversal of the network, and a specially designed ranking function that considers information local to each vertex. Due to the variety of network structures, a number of characteristics must be taken into consideration and combined into a single rank that measures the utility of removing each vertex. Since removing a vertex in sequential fashion impacts the network structure, an efficient post-processing algorithm is also proposed to quickly re-rank vertices. Experiments on a range of common complex network models with varying number of vertices are considered, in addition to real world networks. The proposed algorithm, DFSH, is shown to be highly competitive and often outperforms existing strategies such as Google PageRank for minimizing pairwise connectivity.

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Glutaredoxins are oxidoreductases capable of reducing protein disulfide bridges and glutathione mixed disulfides through the process of deglutathionylation and glutathionylation. Lately, redox-mediated modifications of functional cysteine residues of TGA1 and TGA8 transcription factors have been postulated. Namely, GRX480 and ROXY1 glutaredoxins have been previously shown to interact with TGA proteins and have been suggested to regulate redox state of these proteins. TGA1, together with TGA2, is involved in systemic acquired resistance (SAR) establishment in the plant Arabidopsis thaliana through PR1 (Pathogenesis related 1) gene activation. They both form an enhanceosome complex with the NPR1 protein (non-expressor of pathogenesis related gene 1) which leads to PR1 transcription. Although TGA1 is capable of activating PR1 transcription, the ability of the TGA1 NPR1 enhanceosome complex to assembly is based on the redox status of TGA1. We identified GRX480 as a glutathionylating enzyme that catalyzes the TGA1 glutathione disulfide transferase reaction with a Km of around 20μM GSSG (oxidized glutathione). Out of four cysteine residues found within TGA1, C172 and C266 were found to be glutathionylated by this enzyme. We also confirmed TGA1 glutathionylation in vivo and showed that this modification takes place while TGA1 is associated with the PR1 promoter enzymatically via GRX480. Furthermore, we show that glutathionylation via GRX480 abolishes TGA1's interaction with NPR1 and consequently prevents the TGA1-NPR1 transcription activation of PR1. When glutathionylated, TGA1 is recruited to the PR1 promoter and acts as a repressor. Therefore, glutathionylation is a mechanism that prevents TGA1 NPR1 interaction, allowing TGA1 to function as a repressor of PR1 transcription. Surprisingly, GRX480 was not able to deglutathionylate proteins demonstrating the irreversible nature of the reaction. Moreover, we demonstrate that other members of CC-class glutaredoxins, namely ROXY1 and ROXY2, can also catalyze protein glutathionylation. The TGA8 protein was previously shown to interact with NPR1 analogs, BOP1 and BOP2 proteins. However, unlike the case of TGA1 NPR1 interaction, here we demonstrate that TGA8-BOP1 interaction is not redox regulated and that TGA8 glutathionylation by ROXY1 and ROXY2 enzymes does not abolish this interaction in vitro. However, TGA8 glutathionylation results in TGA8 oligomer disassembly into smaller complexes and monomers. Our results suggest that CC-Grxs are unable to reduce mixed disulfides, instead they efficiently catalyze the opposite reaction which distinguishes them from traditional glutaredoxins. Therefore, they should not be classified as glutaredoxins but as protein glutathione disulfide transferases.

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Understanding the relationship between genetic diseases and the genes associated with them is an important problem regarding human health. The vast amount of data created from a large number of high-throughput experiments performed in the last few years has resulted in an unprecedented growth in computational methods to tackle the disease gene association problem. Nowadays, it is clear that a genetic disease is not a consequence of a defect in a single gene. Instead, the disease phenotype is a reflection of various genetic components interacting in a complex network. In fact, genetic diseases, like any other phenotype, occur as a result of various genes working in sync with each other in a single or several biological module(s). Using a genetic algorithm, our method tries to evolve communities containing the set of potential disease genes likely to be involved in a given genetic disease. Having a set of known disease genes, we first obtain a protein-protein interaction (PPI) network containing all the known disease genes. All the other genes inside the procured PPI network are then considered as candidate disease genes as they lie in the vicinity of the known disease genes in the network. Our method attempts to find communities of potential disease genes strongly working with one another and with the set of known disease genes. As a proof of concept, we tested our approach on 16 breast cancer genes and 15 Parkinson's Disease genes. We obtained comparable or better results than CIPHER, ENDEAVOUR and GPEC, three of the most reliable and frequently used disease-gene ranking frameworks.

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As a result of mutation in genes, which is a simple change in our DNA, we will have undesirable phenotypes which are known as genetic diseases or disorders. These small changes, which happen frequently, can have extreme results. Understanding and identifying these changes and associating these mutated genes with genetic diseases can play an important role in our health, by making us able to find better diagnosis and therapeutic strategies for these genetic diseases. As a result of years of experiments, there is a vast amount of data regarding human genome and different genetic diseases that they still need to be processed properly to extract useful information. This work is an effort to analyze some useful datasets and to apply different techniques to associate genes with genetic diseases. Two genetic diseases were studied here: Parkinson’s disease and breast cancer. Using genetic programming, we analyzed the complex network around known disease genes of the aforementioned diseases, and based on that we generated a ranking for genes, based on their relevance to these diseases. In order to generate these rankings, centrality measures of all nodes in the complex network surrounding the known disease genes of the given genetic disease were calculated. Using genetic programming, all the nodes were assigned scores based on the similarity of their centrality measures to those of the known disease genes. Obtained results showed that this method is successful at finding these patterns in centrality measures and the highly ranked genes are worthy as good candidate disease genes for being studied. Using standard benchmark tests, we tested our approach against ENDEAVOUR and CIPHER - two well known disease gene ranking frameworks - and we obtained comparable results.

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Contexte - La variation interindividuelle de la réponse aux corticostéroïdes (CS) est un problème important chez les patients atteints de maladies inflammatoires d’intestin. Ce problème est bien plus accentué chez les enfants avec la prévalence de la corticodépendance extrêmement (~40 %) élevée. La maladie réfractaire au CS a des répercussions sur le développement et le bien-être physique et psychologique des patients et impose des coûts médicaux élevés, particulièrement avec la maladie active comparativement à la maladie en rémission, le coût étant 2-3 fois plus élevé en ambulatoire et 20 fois plus élevé en hôpital. Il est ainsi primordial de déterminer les marqueurs prédictifs de la réponse aux CS. Les efforts précédents de découvrir les marqueurs cliniques et démographiques ont été équivoques, ce qui souligne davantage le besoin de marqueurs moléculaires. L'action des CS se base sur des processus complexes déterminés génétiquement. Deux gènes, le ABCB1, appartenant à la famille des transporteurs transmembraneaux, et le NR3C1, encodant le récepteur glucocorticoïde, sont des éléments importants des voies métaboliques. Nous avons postulé que les variations dans ces gènes ont un rôle dans la variabilité observée de la réponse aux CS et pourraient servir en tant que les marqueurs prédictifs. Objectifs - Nous avons visé à: (1) examiner le fardeau de la maladie réfractaire aux CS chez les enfants avec la maladie de Crohn (MC) et le rôle des caractéristiques cliniques et démographiques potentiellement liés à la réponse; (2) étudier l'association entre les variantes d'ADN de gène ABCB1 et la réponse aux CS; (3) étudier les associations entre les variantes d'ADN de gène NR3C1 et la réponse aux CS. Méthodes - Afin d’atteindre ces objectifs, nous avons mené une étude de cohorte des patients recrutés dans deux cliniques pédiatriques tertiaires de gastroentérologie à l’Ottawa (CHEO) et à Montréal (HSJ). Les patients avec la MC ont été diagnostiqués avant l'âge de 18 ans selon les critères standard radiologiques, endoscopiques et histopathologiques. La corticorésistance et la corticodépendance ont été définies en adaptant les critères reconnus. L’ADN, acquise soit du sang ou de la salive, était génotypée pour des variations à travers de gènes ABCB1 et NR3C1 sélectionnées à l’aide de la méthodologie de tag-SNP. La fréquence de la corticorésistance et la corticodépendance a été estimée assumant une distribution binomiale. Les associations entre les variables cliniques/démographiques et la réponse aux CS ont été examinées en utilisant la régression logistique en ajustant pour des variables potentielles de confusion. Les associations entre variantes génétiques de ABCB1 et NR3C1 et la réponse aux CS ont été examinées en utilisant la régression logistique assumant différents modèles de la transmission. Les associations multimarqueurs ont été examinées en utilisant l'analyse de haplotypes. Les variantes nongénotypées ont été imputées en utilisant les données de HAPMAP et les associations avec SNPs imputés ont été examinées en utilisant des méthodes standard. Résultats - Parmi 645 patients avec la MC, 364 (56.2%) ont reçu CS. La majorité de patients étaient des hommes (54.9 %); présentaient la maladie de l’iléocôlon (51.7%) ou la maladie inflammatoire (84.6%) au diagnostic et étaient les Caucasiens (95.6 %). Huit pourcents de patients étaient corticorésistants et 40.9% - corticodépendants. Le plus bas âge au diagnostic (OR=1.34, 95% CI: 1.03-3.01, p=0.040), la maladie cœxistante de la région digestive supérieure (OR=1.35, 95% CI: 95% CI: 1.06-3.07, p=0.031) et l’usage simultané des immunomodulateurs (OR=0.35, 95% CI: 0.16-0.75, p=0.007) ont été associés avec la corticodépendance. Un total de 27 marqueurs génotypés à travers de ABCB1 (n=14) et NR3C1 (n=13) ont été en l'Équilibre de Hardy-Weinberg, à l’exception d’un dans le gène NR3C1 (rs258751, exclu). Dans ABCB1, l'allèle rare de rs2032583 (OR=0.56, 95% CI: 0.34-0.95, p=0.029) et génotype hétérozygote (OR=0.52, 95% CI: 0.28-0.95 p=0.035) ont été négativement associes avec la dépendance de CS. Un haplotype à 3 marqueurs, comprenant le SNP fonctionnel rs1045642 a été associé avec la dépendance de CS (p empirique=0.004). 24 SNPs imputés introniques et six haplotypes ont été significativement associés avec la dépendance de CS. Aucune de ces associations n'a cependant maintenu la signification après des corrections pour des comparaisons multiples. Dans NR3C1, trois SNPs: rs10482682 (OR=1.43, 95% CI: 0.99-2.08, p=0.047), rs6196 (OR=0.55, 95% CI: 0.31-0.95, p=0.024), et rs2963155 (OR=0.64, 95% CI: 0.42-0.98, p=0.039), ont été associés sous un modèle additif, tandis que rs4912911 (OR=0.37, 95% CI: 0.13-1.00, p=0.03) et rs2963156 (OR=0.32, 95% CI: 0.07-1.12, p=0.047) - sous un modèle récessif. Deux haplotypes incluant ces 5 SNPs (AAACA et GGGCG) ont été significativement (p=0.006 et 0.01 empiriques) associés avec la corticodépendance. 19 SNPs imputés ont été associés avec la dépendance de CS. Deux haplotypes multimarqueurs (p=0.001), incluant les SNPs génotypés et imputés, ont été associés avec la dépendance de CS. Conclusion - Nos études suggèrent que le fardeau de la corticodépendance est élevé parmi les enfants avec le CD. Les enfants plus jeunes au diagnostic et ceux avec la maladie coexistante de la région supérieure ainsi que ceux avec des variations dans les gènes ABCB1 et NR3C1 étaient plus susceptibles de devenir corticodépendants.

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L’objectif principal de cette thèse est d’examiner et d’intervenir auprès des déficits de la mémoire de travail (MdeT) à l’intérieur de deux populations cliniques : la maladie d’Alzheimer (MA) et le trouble cognitif léger (TCL). La thèse se compose de trois articles empiriques. Le but de la première expérimentation était d’examiner les déficits de MdeT dans le vieillissement normal, le TCL et la MA à l’aide de deux versions de l’empan complexe : l’empan de phrases et l’empan arithmétique. De plus, l’effet de «l’oubli» (forgetting) a été mesuré en manipulant la longueur de l’intervalle de rétention. Les résultats aux tâches d’empan complexe indiquent que la MdeT est déficitaire chez les individus atteints de TCL et encore plus chez les gens ayant la MA. Les données recueillies supportent également le rôle de l’oubli à l’intérieur de la MdeT. L’augmentation de l’intervalle de rétention exacerbait le déficit dans la MA et permettait de prédire un pronostic négatif dans le TCL. L’objectif de la deuxième étude était d’examiner la faisabilité d’un programme d’entraînement cognitif à l’ordinateur pour la composante de contrôle attentionnel à l’intérieur de la MdeT. Cette étude a été réalisée auprès de personnes âgées saines et de personnes âgées avec TCL. Les données de cette expérimentation ont révélé des effets positifs de l’entraînement pour les deux groupes de personnes. Toutefois, l’absence d’un groupe contrôle a limité l’interprétation des résultats. Sur la base de ces données, la troisième expérimentation visait à implémenter une étude randomisée à double-insu avec groupe contrôle d’un entraînement du contrôle attentionnel chez des personnes TCL avec atteinte exécutive. Ce protocole impliquait un paradigme de double-tâche composé d’une tâche de détection visuelle et d’une tâche de jugement alpha-arithmétique. Alors que le groupe contrôle pratiquait simplement la double-tâche sur six périodes d’une heure chacune, le groupe expérimental recevait un entraînement de type priorité variable dans lequel les participants devaient gérer leur contrôle attentionnel en variant la proportion de ressources attentionnelles allouée à chaque tâche. Les résultats montrent un effet significatif de l’intervention sur une des deux tâches impliquées (précision à la tâche de détection visuelle) ainsi qu’une tendance au transfert à une autre tâche d’attention divisée, mais peu d’effets de généralisation à d’autres tâches d’attention. En résumé, les données originales rapportées dans la présente thèse démontrent un déficit de la MdeT dans les maladies neurodégénératives liées à l’âge, avec un gradient entre le TCL et la MA. Elles suggèrent également une préservation de la plasticité des capacités attentionnelles chez les personnes à risque de développer une démence.

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Hepatic encephalopathy (HE) is a complex neuropsychiatric syndrome that typically develops as a result of acute liver failure or chronic liver disease. Brain edema is a common feature associated with HE. In acute liver failure, brain edema contributes to an increase in intracranial pressure, which can fatally lead to brain stem herniation. In chronic liver disease, intracranial hypertension is rarely observed, even though brain edema may be present. This discrepancy in the development of intracranial hypertension in acute liver failure versus chronic liver disease suggests that brain edema plays a different role in relation to the onset of HE. Furthermore, the pathophysiological mechanisms involved in the development of brain edema in acute liver failure and chronic liver disease are dissimilar. This review explores the types of brain edema, the cells, and pathogenic factors involved in its development, while emphasizing the differences in acute liver failure versus chronic liver disease. The implications of brain edema developing as a neuropathological consequence of HE, or as a cause of HE, are also discussed.

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The overall aim of the work presented was to evaluate soil health management with a specific focus on soil borne diseases of peas. For that purpose field experiments were carried out from 2009 until 2013 to assess crop performance and pathogen occurrence in the rotation winter pea-maize-winter wheat and if the application of composts can improve system performance. The winter peas were left untreated or inoculated with Phoma medicaginis, in the presence or absence of yard waste compost at rate of 5 t dry matter ha-1. A second application of compost was made to the winter wheat. Fusarium ssp. were isolated and identified from the roots of all three crops and the Ascochyta complex pathogens on peas. Bioassays were conducted under controlled conditions to assess susceptibility of two peas to Fusarium avenaceum, F. solani, P. medicaginis and Didymella pinodes and of nine plant species to F. avenaceum. Also, effects of compost applications and temperature on pea diseases were assessed. Application of composts overall stabilized crop performance but it did not lead to significant yield increases nor did it affect pathogen composition and occurrence. Phoma medicaginis was dominating the pathogen complex on peas. F. graminearum, F. culmorum, F. proliferatum, Microdochium nivale, F. crookwellense, F. sambucinum, F. oxysporum, F. avenaceum and F. equiseti were frequently isolated species from maize and winter wheat with no obvious influence of the pre-crop on the Fusarium species composition. The spring pea Santana was considerably more susceptible to the pathogens tested than the winter pea EFB33 in both sterile sand and non-sterilized field soil. F. avenaceum was the most aggressive pathogen, followed by P. medicaginis, D. pinodes, and F. solani. Aggressiveness of all pathogens was greatly reduced in non-sterile field soil. F. avenaceum caused severe symptoms on roots of all nine plant species tested. Especially susceptible were Trifolium repens, T. subterraneum, Brassica juncea and Sinapis alba in addition to peas. Reduction of growing temperatures from 19/16°C day/night to 16/12°C and 13/10°C did not affect the efficacy of compost. It reduced plant growth and slightly increased disease on EFB33 whereas the highest disease severity on Santana was observed at the highest temperature, 19/16°C. Application of 20% v/v of compost reduced disease on peas due to all four pathogens depending on pea variety, pathogen and growing media used. Suppression was also achieved with lower application rate of 3.5% v/v. Tests with γ sterilized compost suggest that the suppression of disease caused by Fusarium spp. is biological in origin, whereas chemical and physical properties of compost are playing an additional role in the suppression of disease caused by D. pinodes and P. medicaginis.

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The increasing burden of emerging infectious diseases worldwide confronts us with numerous challenges, including the imperative to design research and responses that are commensurate to understanding the complex social and ecological contexts in which infectious diseases occur. A diverse group of scientists met in Hawaii in March 2005 to discuss the linked social and ecological contexts in which infectious diseases emerge. A subset of the meeting was a group that focused on ‘‘transdisciplinary approaches’’ to integrating knowledge across and beyond academic disciplines in order to improve prevention and control of emerging infections. This article is based on the discussions of that group. Here, we outline the epidemiological legacy that has dominated infectious disease research and control up until now, and introduce the role of new, transdisciplinary and systems-based approaches to emerging infectious diseases.Wedescribe four cases of transboundary health issues and use them to discuss the potential benefits, as well as the inherent difficulties, in understanding the social–ecological contexts in which infectious diseases occur and of using transdisciplinary approaches to deal with them.

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The development of high throughput techniques ('chip' technology) for measurement of gene expression and gene polymorphisms (genomics), and techniques for measuring global protein expression (proteomics) and metabolite profile (metabolomics) are revolutionising life science research, including research in human nutrition. In particular, the ability to undertake large-scale genotyping and to identify gene polymorphisms that determine risk of chronic disease (candidate genes) could enable definition of an individual's risk at an early age. However, the search for candidate genes has proven to be more complex, and their identification more elusive, than previously thought. This is largely due to the fact that much of the variability in risk results from interactions between the genome and environmental exposures. Whilst the former is now very well defined via the Human Genome Project, the latter (e.g. diet, toxins, physical activity) are poorly characterised, resulting in inability to account for their confounding effects in most large-scale candidate gene studies. The polygenic nature of most chronic diseases offers further complexity, requiring very large studies to disentangle relatively weak impacts of large numbers of potential 'risk' genes. The efficacy of diet as a preventative strategy could also be considerably increased by better information concerning gene polymorphisms that determine variability in responsiveness to specific diet and nutrient changes. Much of the limited available data are based on retrospective genotyping using stored samples from previously conducted intervention trials. Prospective studies are now needed to provide data that can be used as the basis for provision of individualised dietary advice and development of food products that optimise disease prevention. Application of the new technologies in nutrition research offers considerable potential for development of new knowledge and could greatly advance the role of diet as a preventative disease strategy in the 21st century. Given the potential economic and social benefits offered, funding for research in this area needs greater recognition, and a stronger strategic focus, than is presently the case. Application of genomics in human health offers considerable ethical and societal as well as scientific challenges. Economic determinants of health care provision are more likely to resolve such issues than scientific developments or altruistic concerns for human health.

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Networks are ubiquitous in natural, technological and social systems. They are of increasing relevance for improved understanding and control of infectious diseases of plants, animals and humans, given the interconnectedness of today's world. Recent modelling work on disease development in complex networks shows: the relative rapidity of pathogen spread in scale-free compared with random networks, unless there is high local clustering; the theoretical absence of an epidemic threshold in scale-free networks of infinite size, which implies that diseases with low infection rates can spread in them, but the emergence of a threshold when realistic features are added to networks (e.g. finite size, household structure or deactivation of links); and the influence on epidemic dynamics of asymmetrical interactions. Models suggest that control of pathogens spreading in scale-free networks should focus on highly connected individuals rather than on mass random immunization. A growing number of empirical applications of network theory in human medicine and animal disease ecology confirm the potential of the approach, and suggest that network thinking could also benefit plant epidemiology and forest pathology, particularly in human-modified pathosystems linked by commercial transport of plant and disease propagules. Potential consequences for the study and management of plant and tree diseases are discussed.

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This paper describes a computational and statistical study of the influence of morphological changes on the electrophysiological response of neurons from an animal model of Alzheimer's Disease (AD). We combined experimental morphological data from rat hippocampal CA1 pyramidal cells with a well-established model of active membrane properties. Dendritic morphology and the somatic response to simulated current clamp conditions were then compared for cells from the control and the AD group. The computational approach allowed us to single out the influences of neuromorphology on neuronal response by eliminating the effects of active channel variability. The results did not reveal a simple relationship between morphological changes associated with AD and changes in neural response. However, they did suggest the existence of more complex than anticipated relationships between dendritic morphology and single-cell electrophysiology.

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Mutations in leucine-rich repeat kinase 2 (LRRK2) are the most common cause of Parkinson's disease (PD). LRRK2 contains a Ras of complex proteins (ROC) domain that may act as a GTPase to regulate its protein kinase activity. The structure of ROC and the mechanism(s) by which it regulates kinase activity are not known. Here, we report the crystal structure of the LRRK2 ROC domain in complex with GDP-Mg2+ at 2.0-Å resolution. The structure displays a dimeric fold generated by extensive domain-swapping, resulting in a pair of active sites constructed with essential functional groups contributed from both monomers. Two PD-associated pathogenic residues, R1441 and I1371, are located at the interface of two monomers and provide exquisite interactions to stabilize the ROC dimer. The structure demonstrates that loss of stabilizing forces in the ROC dimer is likely related to decreased GTPase activity resulting from mutations at these sites. Our data suggest that the ROC domain may regulate LRRK2 kinase activity as a dimer, possibly via the C-terminal of ROC (COR) domain as a molecular hinge. The structure of the LRRK2 ROC domain also represents a signature from a previously undescribed class of GTPases from complex proteins and results may provide a unique molecular target for therapeutics in PD.