Rapid cohort generation and analysis of disease spectrum of large animal model of cone dystrophy.

Large animal models are an important resource for the understanding of human disease and for evaluating the applicability of new therapies to human patients. For many diseases, such as cone dystrophy, research effort is hampered by the lack of such models. Lentiviral transgenesis is a methodology broadly applicable to animals from many different species. When conjugated to the expression of a dominant mutant protein, this technology offers an attractive approach to generate new large animal models in a heterogeneous background. We adopted this strategy to mimic the phenotype diversity encounter in humans and generate a cohort of pigs for cone dystrophy by expressing a dominant mutant allele of the guanylate cyclase 2D (GUCY2D) gene. Sixty percent of the piglets were transgenic, with mutant GUCY2D mRNA detected in the retina of all animals tested. Functional impairment of vision was observed among the transgenic pigs at 3 months of age, with a follow-up at 1 year indicating a subsequent slower progression of phenotype. Abnormal retina morphology, notably among the cone photoreceptor cell population, was observed exclusively amongst the transgenic animals. Of particular note, these transgenic animals were characterized by a range in the severity of the phenotype, reflecting the human clinical situation. We demonstrate that a transgenic approach using lentiviral vectors offers a powerful tool for large animal model development. Not only is the efficiency of transgenesis higher than conventional transgenic methodology but this technique also produces a heterogeneous cohort of transgenic animals that mimics the genetic variation encountered in human patients.

Modelling the evolution and spread of HIV immune escape mutants.

During infection with human immunodeficiency virus (HIV), immune pressure from cytotoxic T-lymphocytes (CTLs) selects for viral mutants that confer escape from CTL recognition. These escape variants can be transmitted between individuals where, depending upon their cost to viral fitness and the CTL responses made by the recipient, they may revert. The rates of within-host evolution and their concordant impact upon the rate of spread of escape mutants at the population level are uncertain. Here we present a mathematical model of within-host evolution of escape mutants, transmission of these variants between hosts and subsequent reversion in new hosts. The model is an extension of the well-known SI model of disease transmission and includes three further parameters that describe host immunogenetic heterogeneity and rates of within host viral evolution. We use the model to explain why some escape mutants appear to have stable prevalence whilst others are spreading through the population. Further, we use it to compare diverse datasets on CTL escape, highlighting where different sources agree or disagree on within-host evolutionary rates. The several dozen CTL epitopes we survey from HIV-1 gag, RT and nef reveal a relatively sedate rate of evolution with average rates of escape measured in years and reversion in decades. For many epitopes in HIV, occasional rapid within-host evolution is not reflected in fast evolution at the population level.

Defective tumor necrosis factor-alpha-dependent control of astrocyte glutamate release in a transgenic mouse model of Alzheimer disease.

The cytokine tumor necrosis factor-alpha (TNFalpha) induces Ca2+-dependent glutamate release from astrocytes via the downstream action of prostaglandin (PG) E2. By this process, astrocytes may participate in intercellular communication and neuromodulation. Acute inflammation in vitro, induced by adding reactive microglia to astrocyte cultures, enhances TNFalpha production and amplifies glutamate release, switching the pathway into a neurodamaging cascade (Bezzi, P., Domercq, M., Brambilla, L., Galli, R., Schols, D., De Clercq, E., Vescovi, A., Bagetta, G., Kollias, G., Meldolesi, J., and Volterra, A. (2001) Nat. Neurosci. 4, 702-710). Because glial inflammation is a component of Alzheimer disease (AD) and TNFalpha is overexpressed in AD brains, we investigated possible alterations of the cytokine-dependent pathway in PDAPP mice, a transgenic model of AD. Glutamate release was measured in acute hippocampal and cerebellar slices from mice at early (4-month-old) and late (12-month-old) disease stages in comparison with age-matched controls. Surprisingly, TNFalpha-evoked glutamate release, normal in 4-month-old PDAPP mice, was dramatically reduced in the hippocampus of 12-month-old animals. This defect correlated with the presence of numerous beta-amyloid deposits and hypertrophic astrocytes. In contrast, release was normal in cerebellum, a region devoid of beta-amyloid deposition and astrocytosis. The Ca2+-dependent process by which TNFalpha evokes glutamate release in acute slices is distinct from synaptic release and displays properties identical to those observed in cultured astrocytes, notably PG dependence. However, prostaglandin E2 induced normal glutamate release responses in 12-month-old PDAPP mice, suggesting that the pathology-associated defect involves the TNFalpha-dependent control of secretion rather than the secretory process itself. Reduced expression of DENN/MADD, a mediator of TNFalpha-PG coupling, might account for the defect. Alteration of this neuromodulatory astrocytic pathway is described here for the first time in relation to Alzheimer disease.

Deciphering genetic disease in the genomic era: the model of GnRH deficiency.

Isolated gonadotropin-releasing hormone (GnRH) deficiency is a treatable albeit rare form of reproductive failure that has revealed physiological mechanisms controlling human reproduction, but despite substantial progress in discovering pathogenic single-gene defects, most of the genetic basis of GnRH deficiency remains uncharted. Although unbiased genetic investigations of affected families have identified mutations in previously unsuspected genes as causes of this disease in some cases, their application has been severely limited because of the negative effect of GnRH deficiency on fertility; moreover, relatively few of the many candidate genes nominated because of biological plausibility from in vitro or animal model experiments were subsequently validated in patients. With the advent of exciting technological platforms for sequencing, homozygosity mapping, and detection of structural variation at the whole-genome level, human investigations are again assuming the leading role for gene discovery. Using human GnRH deficiency as a paradigm and presenting original data from the screening of numerous candidate genes, we discuss the emerging model of patient-focused clinical genetic research and its complementarities with basic approaches in the near future.

Evolution of self-organized division of labor in a response threshold model.

Division of labor in social insects is determinant to their ecological success. Recent models emphasize that division of labor is an emergent property of the interactions among nestmates obeying to simple behavioral rules. However, the role of evolution in shaping these rules has been largely neglected. Here, we investigate a model that integrates the perspectives of self-organization and evolution. Our point of departure is the response threshold model, where we allow thresholds to evolve. We ask whether the thresholds will evolve to a state where division of labor emerges in a form that fits the needs of the colony. We find that division of labor can indeed evolve through the evolutionary branching of thresholds, leading to workers that differ in their tendency to take on a given task. However, the conditions under which division of labor evolves depend on the strength of selection on the two fitness components considered: amount of work performed and on worker distribution over tasks. When selection is strongest on the amount of work performed, division of labor evolves if switching tasks is costly. When selection is strongest on worker distribution, division of labor is less likely to evolve. Furthermore, we show that a biased distribution (like 3:1) of workers over tasks is not easily achievable by a threshold mechanism, even under strong selection. Contrary to expectation, multiple matings of colony foundresses impede the evolution of specialization. Overall, our model sheds light on the importance of considering the interaction between specific mechanisms and ecological requirements to better understand the evolutionary scenarios that lead to division of labor in complex systems. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00265-012-1343-2) contains supplementary material, which is available to authorized users.

RNA interference mitigates motor and neuropathological deficits in a cerebellar mouse model of machado-joseph disease.

Machado-Joseph disease or Spinocerebellar ataxia type 3 is a progressive fatal neurodegenerative disorder caused by the polyglutamine-expanded protein ataxin-3. Recent studies demonstrate that RNA interference is a promising approach for the treatment of Machado-Joseph disease. However, whether gene silencing at an early time-point is able to prevent the appearance of motor behavior deficits typical of the disease when initiated before onset of the disease had not been explored. Here, using a lentiviral-mediated allele-specific silencing of mutant ataxin-3 in an early pre-symptomatic cerebellar mouse model of Machado-Joseph disease we show that this strategy hampers the development of the motor and neuropathological phenotypic characteristics of the disease. At the histological level, the RNA-specific silencing of mutant ataxin-3 decreased formation of mutant ataxin-3 aggregates, preserved Purkinje cell morphology and expression of neuronal markers while reducing cell death. Importantly, gene silencing prevented the development of impairments in balance, motor coordination, gait and hyperactivity observed in control mice. These data support the therapeutic potential of RNA interference for Machado-Joseph disease and constitute a proof of principle of the beneficial effects of early allele-specific silencing for therapy of this disease.

Metabolic alterations and increased liver mTOR expression precede the development of autoimmune disease in a murine model of lupus erythematosus

Although metabolic syndrome (MS) and systemic lupus erythematosus (SLE) are often associated, a common link has not been identified. Using the BWF1 mouse, which develops MS and SLE, we sought a molecular connection to explain the prevalence of these two diseases in the same individuals. We determined SLE- markers (plasma anti-ds-DNA antibodies, splenic regulatory T cells (Tregs) and cytokines, proteinuria and renal histology) and MS-markers (plasma glucose, non-esterified fatty acids, triglycerides, insulin and leptin, liver triglycerides, visceral adipose tissue, liver and adipose tissue expression of 86 insulin signaling-related genes) in 8-, 16-, 24-, and 36-week old BWF1 and control New-Zealand-White female mice. Up to week 16, BWF1 mice showed MS-markers (hyperleptinemia, hyperinsulinemia, fatty liver and visceral adipose tissue) that disappeared at week 36, when plasma anti-dsDNA antibodies, lupus nephritis and a pro-autoimmune cytokine profile were detected. BWF1 mice had hyperleptinemia and high splenic Tregs till week 16, thereby pointing to leptin resistance, as confirmed by the lack of increased liver P-Tyr-STAT-3. Hyperinsulinemia was associated with a down-regulation of insulin related-genes only in adipose tissue, whereas expression of liver mammalian target of rapamicyn (mTOR) was increased. Although leptin resistance presented early in BWF1 mice can slow-down the progression of autoimmunity, our results suggest that sustained insulin stimulation of organs, such as liver and probably kidneys, facilitates the over-expression and activity of mTOR and the development of SLE.

Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease.

The failure of current strategies to provide an explanation for controversial findings on the pattern of pathophysiological changes in Alzheimer's Disease (AD) motivates the necessity to develop new integrative approaches based on multi-modal neuroimaging data that captures various aspects of disease pathology. Previous studies using [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) and structural magnetic resonance imaging (sMRI) report controversial results about time-line, spatial extent and magnitude of glucose hypometabolism and atrophy in AD that depend on clinical and demographic characteristics of the studied populations. Here, we provide and validate at a group level a generative anatomical model of glucose hypo-metabolism and atrophy progression in AD based on FDG-PET and sMRI data of 80 patients and 79 healthy controls to describe expected age and symptom severity related changes in AD relative to a baseline provided by healthy aging. We demonstrate a high level of anatomical accuracy for both modalities yielding strongly age- and symptom-severity- dependant glucose hypometabolism in temporal, parietal and precuneal regions and a more extensive network of atrophy in hippocampal, temporal, parietal, occipital and posterior caudate regions. The model suggests greater and more consistent changes in FDG-PET compared to sMRI at earlier and the inversion of this pattern at more advanced AD stages. Our model describes, integrates and predicts characteristic patterns of AD related pathology, uncontaminated by normal age effects, derived from multi-modal data. It further provides an integrative explanation for findings suggesting a dissociation between early- and late-onset AD. The generative model offers a basis for further development of individualized biomarkers allowing accurate early diagnosis and treatment evaluation.

The Besançon Galaxy Model renewed. I. Constraints on the Galactic thin disc evolution from Tycho data

Context. The understanding of Galaxy evolution can be facilitated by the use of population synthesis models, which allow to test hypotheses on the star formation history, star evolution, as well as chemical and dynamical evolution of the Galaxy. Aims. The new version of the Besanc¸on Galaxy Model (hereafter BGM) aims to provide a more flexible and powerful tool to investigate the Initial Mass Function (IMF) and Star Formation Rate (SFR) of the Galactic disc. Methods. We present a new strategy for the generation of thin disc stars which assumes the IMF, SFR and evolutionary tracks as free parameters. We have updated most of the ingredients for the star count production and, for the first time, binary stars are generated in a consistent way. We keep in this new scheme the local dynamical self-consistency as in Bienayme et al (1987). We then compare simulations from the new model with Tycho-2 data and the local luminosity function, as a first test to verify and constrain the new ingredients. The effects of changing thirteen different ingredients of the model are systematically studied. Results. For the first time, a full sky comparison is performed between BGM and data. This strategy allows to constrain the IMF slope at high masses which is found to be close to 3.0, excluding a shallower slope such as Salpeter"s one. The SFR is found decreasing whatever IMF is assumed. The model is compatible with a local dark matter density of 0.011 M pc−3 implying that there is no compelling evidence for significant amount of dark matter in the disc. While the model is fitted to Tycho2 data, a magnitude limited sample with V<11, we check that it is still consistent with fainter stars. Conclusions. The new model constitutes a new basis for further comparisons with large scale surveys and is being prepared to become a powerful tool for the analysis of the Gaia mission data.

Model of black hole evolution

We investigate a model where the quantum dynamics of black hole evaporation is determined by imposing a boundary on the apparent horizon with suitable boundary conditions. An unconventional scenario for the evolution emerges: only an insignificant fraction of energy of order (mG)-1 is radiated out; the outgoing wave carries a very small part of the quantum-mechanical information of the collapsed body, the bulk of the information remaining in the final stable black hole geometry.

The health promotion model and rare disease patients : a mixed methods study examining adherence to treatment in men with congenital hypogonadotropic hypogonadism

Rare diseases are typically chronic medical conditions of genetic etiology characterized by low prevalence and high complexity. Patients living with rare diseases face numerous physical, psychosocial and economic challenges that place them in the realm of health disparities. Congenital hypogonadotropic hypogonadism (CHH) is a rare endocrine disorder characterized by absent puberty and infertility. Little is known about the psychosocial impact of CHH on patients or their adherence to available treatments. This project aimed to examine the relationship between illness perceptions, depressive symptoms and adherence to treatment in men with CHH using the nursing-sensitive Health Promotion Model (HPM). A community based participatory research (CBPR) framework was employed as a model for empowering patients and overcoming health inequities. The study design used a sequential, explanatory mixed-methods approach. To reach dispersed CHH men, we used web-based recruitment and data collection (online survey). Subsequently, three patient focus groups were conducted to provide explanatory insights into the online survey (i.e. barriers to adherence, challenges of CHH, and coping/support) The online survey (n=101) revealed that CHH men struggle with adherence and often have long gaps in care (40% >1 year). They experience negative psychosocial consequences because of CHH and exhibit significantly increased rates of depression (p<0.001). Focus group participants (n=26) identified healthcare system, interpersonal, and personal factors as barriers to adherence. Further, CHH impacts quality of life and impedes psychosexual development in these men. The CHH men are active internet users who rely on the web forcrowdsourcing solutions and peer-to-peer support. Moreover, they are receptive to web-based interventions to address unmet health needs. This thesis contributes to nursing knowledge in several ways. First, it demonstrates the utility of the HPM as a valuable theoretical construct for understanding medication adherence and for assessing rare disease patients. Second, these data identify a range of unmet health needs that are targets for patient-centered interventions. Third, leveraging technology (high-tech) effectively extended the reach of nursing care while the CBPR approach and focus groups (high-touch) served as concurrent nursing interventions facilitating patient empowerment in overcoming health disparities. Last, these findings hold promise for developing e-health interventions to bridge identified shortfalls in care and activating patients for enhanced self- care and wellness -- Les maladies rares sont généralement de maladies chroniques d'étiologie génétique caractérisées par une faible prévalence et une haute complexité de traitement. Les patients atteints de maladies rares sont confrontés à de nombreux défis physiques, psychosociaux et économiques qui les placent dans une posture de disparité et d'inégalités en santé. L'hypogonadisme hypogonadotrope congénital (CHH) est un trouble endocrinien rare caractérisé par l'absence de puberté et l'infertilité. On sait peu de choses sur l'impact psychosocial du CHH sur les patients ou leur adhésion aux traitements disponibles. Ce projet vise à examiner la relation entre la perception de la maladie, les symptômes dépressifs et l'observance du traitement chez les hommes souffrant de CHH. Cette étude est modélisée à l'aide du modèle de la Promotion de la santé de Pender (HPM). Le cadre de l'approche communautaire de recherche participative (CBPR) a aussi été utilisé. La conception de l'étude a reposé sur une approche mixte séquentielle. Pour atteindre les hommes souffrant de CHH, un recrutement et une collecte de données ont été organisées électroniquement. Par la suite, trois groupes de discussion ont été menées avec des patients experts impliqués au sein d'organisations reliés aux maladies rares. Ils ont été invités à discuter certains éléments additionnels dont, les obstacles à l'adhésion au traitement, les défis généraux de vivre avec un CHH, et l'adaptation à la maladie en tenant compte du soutien disponible. Le sondage en ligne (n = 101) a révélé que les hommes souffrant de CHH ont souvent de longues périodes en rupture de soins (40% > 1 an). Ils vivent des conséquences psychosociales négatives en raison du CHH et présentent une augmentation significative des taux de dépression (p <0,001). Les participants aux groupes de discussion (n = 26) identifient dans l'ordre, les systèmes de soins de santé, les relations interpersonnelles, et des facteurs personnels comme des obstacles à l'adhésion. En outre, selon les participants, le CHH impacte négativement sur leur qualité de vie générale et entrave leur développement psychosexuel. Les hommes souffrant de CHH se considèrent être des utilisateurs actifs d'internet et comptent sur le web pour trouver des solutions pour trouver des ressources et y recherchent le soutien de leurs pairs (peer-to-peer support). En outre, ils se disent réceptifs à des interventions qui sont basées sur le web pour répondre aux besoins de santé non satisfaits. Cette thèse contribue à la connaissance des soins infirmiers de plusieurs façons. Tout d'abord, elle démontre l'utilité de la HPM comme une construction théorique utile pour comprendre l'adhésion aux traitements et pour l'évaluation des éléments de promotion de santé qui concernent les patients atteints de maladies rares. Deuxièmement, ces données identifient une gamme de besoins de santé non satisfaits qui sont des cibles pour des interventions infirmières centrées sur le patient. Troisièmement, méthodologiquement parlant, cette étude démontre que les méthodes mixtes sont appropriées aux études en soins infirmiers car elles allient les nouvelles technologies qui peuvent effectivement étendre la portée des soins infirmiers (« high-tech »), et l'approche CBPR par des groupes de discussion (« high-touch ») qui ont facilité la compréhension des difficultés que doivent surmonter les hommes souffrant de CHH pour diminuer les disparités en santé et augmenter leur responsabilisation dans la gestion de la maladie rare. Enfin, ces résultats sont prometteurs pour développer des interventions e-santé susceptibles de combler les lacunes dans les soins et l'autonomisation de patients pour une meilleure emprise sur les auto-soins et le bien-être.

A model for the evolution of reinforcement learning in fluctuating games

Many species are able to learn to associate behaviours with rewards as this gives fitness advantages in changing environments. Social interactions between population members may, however, require more cognitive abilities than simple trial-and-error learning, in particular the capacity to make accurate hypotheses about the material payoff consequences of alternative action combinations. It is unclear in this context whether natural selection necessarily favours individuals to use information about payoffs associated with nontried actions (hypothetical payoffs), as opposed to simple reinforcement of realized payoff. Here, we develop an evolutionary model in which individuals are genetically determined to use either trial-and-error learning or learning based on hypothetical reinforcements, and ask what is the evolutionarily stable learning rule under pairwise symmetric two-action stochastic repeated games played over the individual's lifetime. We analyse through stochastic approximation theory and simulations the learning dynamics on the behavioural timescale, and derive conditions where trial-and-error learning outcompetes hypothetical reinforcement learning on the evolutionary timescale. This occurs in particular under repeated cooperative interactions with the same partner. By contrast, we find that hypothetical reinforcement learners tend to be favoured under random interactions, but stable polymorphisms can also obtain where trial-and-error learners are maintained at a low frequency. We conclude that specific game structures can select for trial-and-error learning even in the absence of costs of cognition, which illustrates that cost-free increased cognition can be counterselected under social interactions.

Visualizing Business Model Evolution with the Business Model Canvas: Concept and Tool

The Business Model Canvas (BMC) assists in the design of companies' business models. As strategies evolve so too does the business model. Unfortunately, each BMC is a standalone representation. Thus, there is a need to be able to describe transformation from one version of a business model to the next as well as to visualize these operations. To address this issue, and to contribute to computer-assisted business model design, we propose a set of design principles for business model evolution. We also demonstrate a tool that can assist in the creation and navigation of business model versions in a visual and user-friendly way

Modelling the Evolution and Spread of HIV Immune Escape Mutants.

During infection with human immunodeficiency virus (HIV), immune pressure from cytotoxic T-lymphocytes (CTLs) selects for viral mutants that confer escape from CTL recognition. These escape variants can be transmitted between individuals where, depending upon their cost to viral fitness and the CTL responses made by the recipient, they may revert. The rates of within-host evolution and their concordant impact upon the rate of spread of escape mutants at the population level are uncertain. Here we present a mathematical model of within-host evolution of escape mutants, transmission of these variants between hosts and subsequent reversion in new hosts. The model is an extension of the well-known SI model of disease transmission and includes three further parameters that describe host immunogenetic heterogeneity and rates of within host viral evolution. We use the model to explain why some escape mutants appear to have stable prevalence whilst others are spreading through the population. Further, we use it to compare diverse datasets on CTL escape, highlighting where different sources agree or disagree on within-host evolutionary rates. The several dozen CTL epitopes we survey from HIV-1 gag, RT and nef reveal a relatively sedate rate of evolution with average rates of escape measured in years and reversion in decades. For many epitopes in HIV, occasional rapid within-host evolution is not reflected in fast evolution at the population level.