41 resultados para Hierarchical dynamic models
em Université de Lausanne, Switzerland
Resumo:
The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling.
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PURPOSE OF REVIEW: HIV targets primary CD4(+) T cells. The virus depends on the physiological state of its target cells for efficient replication, and, in turn, viral infection perturbs the cellular state significantly. Identifying the virus-host interactions that drive these dynamic changes is important for a better understanding of viral pathogenesis and persistence. The present review focuses on experimental and computational approaches to study the dynamics of viral replication and latency. RECENT FINDINGS: It was recently shown that only a fraction of the inducible latently infected reservoirs are successfully induced upon stimulation in ex-vivo models while additional rounds of stimulation make allowance for reactivation of more latently infected cells. This highlights the potential role of treatment duration and timing as important factors for successful reactivation of latently infected cells. The dynamics of HIV productive infection and latency have been investigated using transcriptome and proteome data. The cellular activation state has shown to be a major determinant of viral reactivation success. Mathematical models of latency have been used to explore the dynamics of the latent viral reservoir decay. SUMMARY: Timing is an important component of biological interactions. Temporal analyses covering aspects of viral life cycle are essential for gathering a comprehensive picture of HIV interaction with the host cell and untangling the complexity of latency. Understanding the dynamic changes tipping the balance between success and failure of HIV particle production might be key to eradicate the viral reservoir.
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In dynamic models of energy allocation, assimilated energy is allocated to reproduction, somatic growth, maintenance or storage, and the allocation pattern can change with age. The expected evolutionary outcome is an optimal allocation pattern, but this depends on the environment experienced during the evolutionary process and on the fitness costs and benefits incurred by allocating resources in different ways. Here we review existing treatments which encompass some of the possibilities as regards constant or variable environments and their predictability or unpredictability, and the ways in which production rates and mortality rates depend on body size and composition and age and on the pattern of energy allocation. The optimal policy is to allocate resources where selection pressures are highest, and simultaneous allocation to several body subsystems and reproduction can be optimal if these pressures are equal. This may explain balanced growth commonly observed during ontogeny. Growth ceases at maturity in many models; factors favouring growth after maturity include non-linear trade-offs, variable season length, and production and mortality rates both increasing (or decreasing) functions of body size. We cannot yet say whether these are sufficient to account for the many known cases of growth after maturity and not all reasonable models have yet been explored. Factors favouring storage are also reviewed.
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A review of extinction risk analysis and viability methods is presented. The importance of environmental, demographic and genetic uncertainties, as well as the role of catastrophes are successively considered, and different approaches aiming at the integration of these risk factors in predictive population dynamic models are discussed.
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The present dissertation analyzed the construct of attachment at different time points, specifically focusing on two phases of adoptive family life that have so far received little attention from investigators. Study 1 focused on the first months of adoption, and analyzed the development of the attachment relationship to new caregivers. The sample was composed of a small but homogeneous group (n=6) of Korean-born children, adopted by Italian parents. The Parent Attachment Diary (Dozier & Stovall, 1997) was utilized to assess the child's attachment behavior. We assessed these behavior for the first 3 months after placement into adoption. Results showed a double variability of attachment behavior: within subjects during the 3-months, and between subjects, with just half of the children developing a stable pattern of attachment. In order to test the growth trajectories of attachment behavior, Hierarchical Linear Models (Bryk & Raudenbush, 1992) were also applied, but no significant population trend was identified. Study 2 analyzed attachment among adoptees during the sensitive period of adolescence. Data was derived from an international collection (n= 104, from Belgium Italy, and Romania) of semi-structured clinical interviews (with adolescents and with their adoptive parents), as well as from questionnaires. The purpose of this study was to detect the role played by risk and protective factors on the adoptee's behavioral and socio-emotional outcomes. In addition, we tested the possible interactions between the different attachment representations within the adoptive family. Results showed that pre-adoptive risk predicted the adolescent's adjustment; however, parental representations constituted an important moderator of this relationship. Moreover, the adolescent's security of attachment partially mediated the relationship between age at placement and later behavioral problems. In conclusion, the two present attachment studies highlighted the notable rate of change of attachment behavior over time, which showed its underlying plasticity, and thus the possible reparatory value of the adoption practice. Since parents have been proven to play an important role, especially in adolescence, the post-adoption support acquires even more importance in order to help parents promoting a positive and stable relational environment over time. - L'objectif de cette thèse est de décrire la formation des relations d'attachement chez les enfants et les adolescents adoptés, lors de deux phases particulières de la vie de la famille adoptive, qui ont été relativement peu étudiées. L'Étude 1 analyse les premiers mois après l'adoption, avec le but de comprendre si, et comment, une relation d'attachement aux nouveaux parents se développe. L'échantillon est composé d'un petit groupe (n = 6) d'enfants provenant de Corée du Sud, adoptés par des parents Italiens. A l'aide du Parent Attachment Diary (Dozier & Stovall, 1997), des observations des comportements d'attachement de l'enfant ont été recueillies chaque jour au cours des 3 premiers mois après l'arrivée. Les résultats montrent une double variabilité des comportements d'attachement: au niveau inter- et intra-individuel ; au premier de ces niveaux, seuleme la moitié des enfants parvient à développer un pattern stable d'attachement ; au niveau intra-individuel, les trajectoires de développement des comportements d'attachement ont été testées à l'aide de Modèles Linéaires Hiérarchiques (Bryk et Raudenbush, 1992), mais aucune tendance significative n'a pu être révélée. L'Étude 2 vise à analyser l'attachement chez des enfants adoptés dans l'enfance, lors de la période particulièrement sensible de l'adolescence. Les données sont issues d'un base de données internationale (n = 104, Belgique, Italie et Roumanie), composée d' entretiens cliniques semi-structurées (auprès de l'adolescents et des ses parents adoptifs), ainsi que de questionnaires. Les analyses statistiques visent à détecter la présence de facteurs de risque et de protection relativement à l'attachement et aux problèmes de comportement de l'enfant adopté. En outre, la présence d'interactions entre les représentations d'attachement des membres de la famille adoptive est évaluée. Les résultats montrent que les risques associés à la période pré-adoptive prédisent la qualité du bien-être de l'adolescent, mais les représentations parentales constituent un modérateur important de cette relation. En outre, la sécurité de l'attachement du jeune adopté médiatise partiellement la relation entre l'âge au moment du placement et les problèmes de comportement lors de l'adolescence. En conclusion, à l'aide de multiples données relatives à l'attachement, ces deux études soulignent son évolution notable au fil du temps, ce qui sous-tend la présence d'une certaine plasticité, et donc la possible valeur réparatrice de la pratique de l'adoption. Comme les parents semblent jouer un rôle important de ce point de vue, surtout à l'adolescence, cela renforce la notion d'un soutien post-adoption, en vue d'aider les parents à la promotion d'un environnement relationnel favorable et stable. - Il presente lavoro è volto ad analizzare l'attaccamento durante le due fasi della vita della famiglia adottiva che meno sono state indagate dalla letteratura. Lo Studio 1 aveva l'obiettivo di analizzare i primi mesi che seguono il collocamento del bambino, al fine di capire se e come una relazione di attaccamento verso i nuovi genitori si sviluppa. Il campione è composto da un piccolo gruppo (n = 6) di bambini provenienti dalla Corea del Sud e adottati da genitori italiani. Attraverso il Parent Attachment Diary (Stovall e Dozier, 1997) sono stati osservati quotidianamente, e per i primi tre mesi, i comportamenti di attaccamento del bambino. I risultati hanno mostrato una duplice variabilità: a livello intraindividuale (nell'arco dei 3 mesi), ed interindividuale, poiché solo la metà dei bambini ha sviluppato un pattern stabile di attaccamento. Per verificare le traiettorie di sviluppo di tali comportamenti, sono stati applicati i Modelli Lineari Gerarchici (Bryk & Raudenbush, 1992), che però non hanno stimato una tendenza significativa all'interno della popolazione. Obiettivo dello Studio 2 è stato quello di esaminare l'attaccamento nelle famiglie i cui figli adottivi si trovavano nella delicata fase adolescenziale. I dati, provenienti da una raccolta internazionale (n = 104, Belgio, Italia e Romania), erano costituiti da interviste cliniche semi-strutturate (con gli adolescenti e i propri genitori adottivi) e da questionari. Le analisi hanno indagato il ruolo dei fattori di rischio sullo sviluppo socio-emotivo e sugli eventuali problemi comportamentali dei ragazzi. Inoltre, sono state esaminate le possibili interazioni tra le diverse rappresentazioni di attaccamento dei membri della famiglia adottiva. I risultati hanno mostrato che il rischio pre-adottivo predice l'adattamento dell'adolescente, sebbene le rappresentazioni genitoriali costituiscano un importante moderatore di questa relazione. Inoltre, la sicurezza dell'attaccamento dell'adolescente media parzialmente la relazione tra età al momento dell'adozione e problemi comportamentali in adolescenza. In conclusione, attraverso i molteplici dati relativi all'attaccamento, i due studi ne hanno evidenziato il cambiamento nel tempo, a riprova della sua plasticità, e pertanto sottolineano il possibile valore riparativo dell'adozione. Dal momento che i genitori svolgono un ruolo importante, soprattutto in adolescenza, il supporto nel post- adozione diventa centrale per aiutarli a promuovere un ambiente relazionale favorevole e stabile nel tempo.
Resumo:
BACKGROUND AND PURPOSE: We compared among young patients with ischemic stroke the distribution of vascular risk factors among sex, age groups, and 3 distinct geographic regions in Europe. METHODS: We included patients with first-ever ischemic stroke aged 15 to 49 years from existing hospital- or population-based prospective or consecutive young stroke registries involving 15 cities in 12 countries. Geographic regions were defined as northern (Finland, Norway), central (Austria, Belgium, France, Germany, Hungary, The Netherlands, Switzerland), and southern (Greece, Italy, Turkey) Europe. Hierarchical regression models were used for comparisons. RESULTS: In the study cohort (n=3944), the 3 most frequent risk factors were current smoking (48.7%), dyslipidemia (45.8%), and hypertension (35.9%). Compared with central (n=1868; median age, 43 years) and northern (n=1330; median age, 44 years) European patients, southern Europeans (n=746; median age, 41 years) were younger. No sex difference emerged between the regions, male:female ratio being 0.7 in those aged <34 years and reaching 1.7 in those aged 45 to 49 years. After accounting for confounders, no risk-factor differences emerged at the region level. Compared with females, males were older and they more frequently had dyslipidemia or coronary heart disease, or were smokers, irrespective of region. In both sexes, prevalence of family history of stroke, dyslipidemia, smoking, hypertension, diabetes mellitus, coronary heart disease, peripheral arterial disease, and atrial fibrillation positively correlated with age across all regions. CONCLUSIONS: Primary preventive strategies for ischemic stroke in young adults-having high rate of modifiable risk factors-should be targeted according to sex and age at continental level.
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Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.
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AIM: To determine the extent drinking patterns (at the individual and country level) are associated with alcohol-related consequences over and above the total alcohol the person consumes. METHODS: Hierarchical linear models were estimated based on general population surveys conducted in 18 countries participating in the GENACIS project. RESULTS: In general, the positive association between drinking pattern scores and alcohol-related consequences was found at both the individual and country levels, independent of volume of drinking. In addition, a significant interaction effect indicated that the more detrimental the country's drinking pattern, the less steep the association between the volume of drinking and its consequences. CONCLUSION: Drinking patterns have an independent impact on consequences over and above the relationship between volume and consequences.
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Motivation: Hormone pathway interactions are crucial in shaping plant development, such as synergism between the auxin and brassinosteroid pathways in cell elongation. Both hormone pathways have been characterized in detail, revealing several feedback loops. The complexity of this network, combined with a shortage of kinetic data, renders its quantitative analysis virtually impossible at present.Results: As a first step towards overcoming these obstacles, we analyzed the network using a Boolean logic approach to build models of auxin and brassinosteroid signaling, and their interaction. To compare these discrete dynamic models across conditions, we transformed them into qualitative continuous systems, which predict network component states more accurately and can accommodate kinetic data as they become available. To this end, we developed an extension for the SQUAD software, allowing semi-quantitative analysis of network states. Contrasting the developmental output depending on cell type-specific modulators enabled us to identify a most parsimonious model, which explains initially paradoxical mutant phenotypes and revealed a novel physiological feature.
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MOTIVATION: Combinatorial interactions of transcription factors with cis-regulatory elements control the dynamic progression through successive cellular states and thus underpin all metazoan development. The construction of network models of cis-regulatory elements, therefore, has the potential to generate fundamental insights into cellular fate and differentiation. Haematopoiesis has long served as a model system to study mammalian differentiation, yet modelling based on experimentally informed cis-regulatory interactions has so far been restricted to pairs of interacting factors. Here, we have generated a Boolean network model based on detailed cis-regulatory functional data connecting 11 haematopoietic stem/progenitor cell (HSPC) regulator genes. RESULTS: Despite its apparent simplicity, the model exhibits surprisingly complex behaviour that we charted using strongly connected components and shortest-path analysis in its Boolean state space. This analysis of our model predicts that HSPCs display heterogeneous expression patterns and possess many intermediate states that can act as 'stepping stones' for the HSPC to achieve a final differentiated state. Importantly, an external perturbation or 'trigger' is required to exit the stem cell state, with distinct triggers characterizing maturation into the various different lineages. By focusing on intermediate states occurring during erythrocyte differentiation, from our model we predicted a novel negative regulation of Fli1 by Gata1, which we confirmed experimentally thus validating our model. In conclusion, we demonstrate that an advanced mammalian regulatory network model based on experimentally validated cis-regulatory interactions has allowed us to make novel, experimentally testable hypotheses about transcriptional mechanisms that control differentiation of mammalian stem cells. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.
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In occupational exposure assessment of airborne contaminants, exposure levels can either be estimated through repeated measurements of the pollutant concentration in air, expert judgment or through exposure models that use information on the conditions of exposure as input. In this report, we propose an empirical hierarchical Bayesian model to unify these approaches. Prior to any measurement, the hygienist conducts an assessment to generate prior distributions of exposure determinants. Monte-Carlo samples from these distributions feed two level-2 models: a physical, two-compartment model, and a non-parametric, neural network model trained with existing exposure data. The outputs of these two models are weighted according to the expert's assessment of their relevance to yield predictive distributions of the long-term geometric mean and geometric standard deviation of the worker's exposure profile (level-1 model). Bayesian inferences are then drawn iteratively from subsequent measurements of worker exposure. Any traditional decision strategy based on a comparison with occupational exposure limits (e.g. mean exposure, exceedance strategies) can then be applied. Data on 82 workers exposed to 18 contaminants in 14 companies were used to validate the model with cross-validation techniques. A user-friendly program running the model is available upon request.
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Axial deflection of DNA molecules in solution results from thermal motion and intrinsic curvature related to the DNA sequence. In order to measure directly the contribution of thermal motion we constructed intrinsically straight DNA molecules and measured their persistence length by cryo-electron microscopy. The persistence length of such intrinsically straight DNA molecules suspended in thin layers of cryo-vitrified solutions is about 80 nm. In order to test our experimental approach, we measured the apparent persistence length of DNA molecules with natural "random" sequences. The result of about 45 nm is consistent with the generally accepted value of the apparent persistence length of natural DNA sequences. By comparing the apparent persistence length to intrinsically straight DNA with that of natural DNA, it is possible to determine both the dynamic and the static contributions to the apparent persistence length.
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Inconsistencies about dynamic asymmetry between the on- and off-transient responses in VO2 are found in the literature. Therefore the purpose of this study was to examine VO2 on- and off-transients during moderate- and heavy-intensity cycling exercise in trained subjects. Ten men underwent an initial incremental test for the estimation of ventilatory threshold (VT) and, on different days, two bouts of square-wave exercise at moderate (<VT) and heavy (>VT) intensities. VO2 kinetics in exercise and recovery were better described by a single exponential model (<VT), or by a double exponential with two time delays (>VT). For moderate exercise, we found a symmetry of VO2 kinetics between the on- and off-transients (i.e., fundamental component), consistent with a system manifesting linear control dynamics. For heavy exercise, a slow component superimposed on the fundamental phase was expressed in both the exercise and recovery, with similar parameter estimates. But the on-transient values of the time constant were appreciably faster than the associated off-transient, and independent of the work rate imposed (<VT and >VT). Our results do not support a dynamically linear system model of VO2 during cycling exercise in the heavy-intensity domain.