Destruction of conditional insulinoma cell lines in NOD mice: a role for autoimmunity.

AIMS/HYPOTHESIS: betaTC-tet (H2(k)) is a conditional insulinoma cell line derived from transgenic mice expressing a tetracycline-regulated oncogene. Transgenic expression of several proteins implicated in the apoptotic pathways increase the resistance of betaTC-tet cells in vitro. We tested in vivo the sensitivity of the cells to rejection and the protective effect of genetic alterations in NOD mice. METHODS: betaTC-tet cells and genetically engineered lines expressing Bcl-2 (CDM3D), a dominant negative mutant of MyD88 or SOCS-1 were transplanted in diabetic female NOD mice or in male NOD mice with diabetes induced by high-dose streptozotocin. Survival of functional cell grafts in NOD-scid mice was also analyzed after transfer of splenocytes from diabetic NOD mice. Autoreactive T-cell hybridomas and splenocytes from diabetic NOD mice were stimulated by betaTC-tet cells. RESULTS: betaTC-tet cells and genetically engineered cell lines were all similarly rejected in diabetic NOD mice and in NOD-scid mice after splenocyte transfer. In 3- to 6-week-old male NOD mice treated with high-dose streptozotocin, the cells temporarily survived, in contrast with C57BL/6 mice treated with high-dose streptozotocin (indefinite survival) and untreated 3- to 6-week-old male NOD mice (rejection). The protective effect of high-dose streptozotocin was lost in older male NOD mice. betaTC-tet cells did not stimulate autoreactive T-cell hybridomas, but induced IL-2 secretion by splenocytes from diabetic NOD mice. CONCLUSION/INTERPRETATION: The autoimmune process seems to play an important role in the destruction of betaTC-tet cells in NOD mice. Genetic manipulations intended at increasing the resistance of beta cells were inefficient. Similar approaches should be tested in vivo as well as in vitro. High dose streptozotocin influences immune rejection and should be used with caution.

Dynamics of the recruitment of lateral amygdala neurons following successive fear learning to different conditional stimuli

In fear conditioning, an animal learns to associate an unconditioned stimulus (US), such as a shock, and a conditioned stimulus (CS), such as a tone, so that the presentation of the CS alone can trigger conditioned responses. Recent research on the lateral amygdala has shown that following cued fear conditioning, only a subset of higher-excitable neurons are recruited in the memory trace. Their selective deletion after fear conditioning results in a selective erasure of the fearful memory. I hypothesize that the recruitment of highly excitable neurons depends on responsiveness to stimuli, intrinsic excitability and local connectivity. In addition, I hypothesize that neurons recruited for an initial memory also participate in subsequent memories, and that changes in neuronal excitability affect secondary fear learning. To address these hypotheses, I will show that A) a rat can learn to associate two successive short-term fearful memories; B) neuronal populations in the LA are competitively recruited in the memory traces depending on individual neuronal advantages, as well as advantages granted by the local network. By performing two successive cued fear conditioning experiments, I found that rats were able to learn and extinguish the two successive short-term memories, when tested 1 hour after learning for each memory. These rats were equipped with a system of stable extracellular recordings that I developed, which allowed to monitor neuronal activity during fear learning. 233 individual putative pyramidal neurons could modulate their firing rate in response to the conditioned tone (conditioned neurons) and/or non- conditioned tones (generalizing neurons). Out of these recorded putative pyramidal neurons 86 (37%) neurons were conditioned to one or both tones. More precisely, one population of neurons encoded for a shared memory while another group of neurons likely encoded the memories' new features. Notably, in spite of a successful behavioral extinction, the firing rate of those conditioned neurons in response to the conditioned tone remained unchanged throughout memory testing. Furthermore, by analyzing the pre-conditioning characteristics of the conditioned neurons, I determined that it was possible to predict neuronal recruitment based on three factors: 1) initial sensitivity to auditory inputs, with tone-sensitive neurons being more easily recruited than tone- insensitive neurons; 2) baseline excitability levels, with more highly excitable neurons being more likely to become conditioned; and 3) the number of afferent connections received from local neurons, with neurons destined to become conditioned receiving more connections than non-conditioned neurons. - En conditionnement de la peur, un animal apprend à associer un stimulus inconditionnel (SI), tel un choc électrique, et un stimulus conditionné (SC), comme un son, de sorte que la présentation du SC seul suffit pour déclencher des réflexes conditionnés. Des recherches récentes sur l'amygdale latérale (AL) ont montré que, suite au conditionnement à la peur, seul un sous-ensemble de neurones plus excitables sont recrutés pour constituer la trace mnésique. Pour apprendre à associer deux sons au même SI, je fais l'hypothèse que les neurones entrent en compétition afin d'être sélectionnés lors du recrutement pour coder la trace mnésique. Ce recrutement dépendrait d'un part à une activation facilité des neurones ainsi qu'une activation facilité de réseaux de neurones locaux. En outre, je fais l'hypothèse que l'activation de ces réseaux de l'AL, en soi, est suffisante pour induire une mémoire effrayante. Pour répondre à ces hypothèses, je vais montrer que A) selon un processus de mémoire à court terme, un rat peut apprendre à associer deux mémoires effrayantes apprises successivement; B) des populations neuronales dans l'AL sont compétitivement recrutées dans les traces mnésiques en fonction des avantages neuronaux individuels, ainsi que les avantages consentis par le réseau local. En effectuant deux expériences successives de conditionnement à la peur, des rats étaient capables d'apprendre, ainsi que de subir un processus d'extinction, pour les deux souvenirs effrayants. La mesure de l'efficacité du conditionnement à la peur a été effectuée 1 heure après l'apprentissage pour chaque souvenir. Ces rats ont été équipés d'un système d'enregistrements extracellulaires stables que j'ai développé, ce qui a permis de suivre l'activité neuronale pendant l'apprentissage de la peur. 233 neurones pyramidaux individuels pouvaient moduler leur taux d'activité en réponse au son conditionné (neurones conditionnés) et/ou au son non conditionné (neurones généralisant). Sur les 233 neurones pyramidaux putatifs enregistrés 86 (37%) d'entre eux ont été conditionnés à un ou deux tons. Plus précisément, une population de neurones code conjointement pour un souvenir partagé, alors qu'un groupe de neurones différent code pour de nouvelles caractéristiques de nouveaux souvenirs. En particulier, en dépit d'une extinction du comportement réussie, le taux de décharge de ces neurones conditionné en réponse à la tonalité conditionnée est resté inchangée tout au long de la mesure d'apprentissage. En outre, en analysant les caractéristiques de pré-conditionnement des neurones conditionnés, j'ai déterminé qu'il était possible de prévoir le recrutement neuronal basé sur trois facteurs : 1) la sensibilité initiale aux entrées auditives, avec les neurones sensibles aux sons étant plus facilement recrutés que les neurones ne répondant pas aux stimuli auditifs; 2) les niveaux d'excitabilité des neurones, avec les neurones plus facilement excitables étant plus susceptibles d'être conditionnés au son ; et 3) le nombre de connexions reçues, puisque les neurones conditionné reçoivent plus de connexions que les neurones non-conditionnés. Enfin, nous avons constaté qu'il était possible de remplacer de façon satisfaisante le SI lors d'un conditionnement à la peur par des injections bilatérales de bicuculline, un antagoniste des récepteurs de l'acide y-Aminobutirique.

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

Policy Diffusion: An Agent-Based Approach

Methods like Event History Analysis can show the existence of diffusion and part of its nature, but do not study the process itself. Nowadays, thanks to the increasing performance of computers, processes can be studied using computational modeling. This thesis presents an agent-based model of policy diffusion mainly inspired from the model developed by Braun and Gilardi (2006). I first start by developing a theoretical framework of policy diffusion that presents the main internal drivers of policy diffusion - such as the preference for the policy, the effectiveness of the policy, the institutional constraints, and the ideology - and its main mechanisms, namely learning, competition, emulation, and coercion. Therefore diffusion, expressed by these interdependencies, is a complex process that needs to be studied with computational agent-based modeling. In a second step, computational agent-based modeling is defined along with its most significant concepts: complexity and emergence. Using computational agent-based modeling implies the development of an algorithm and its programming. When this latter has been developed, we let the different agents interact. Consequently, a phenomenon of diffusion, derived from learning, emerges, meaning that the choice made by an agent is conditional to that made by its neighbors. As a result, learning follows an inverted S-curve, which leads to partial convergence - global divergence and local convergence - that triggers the emergence of political clusters; i.e. the creation of regions with the same policy. Furthermore, the average effectiveness in this computational world tends to follow a J-shaped curve, meaning that not only time is needed for a policy to deploy its effects, but that it also takes time for a country to find the best-suited policy. To conclude, diffusion is an emergent phenomenon from complex interactions and its outcomes as ensued from my model are in line with the theoretical expectations and the empirical evidence.Les méthodes d'analyse de biographie (event history analysis) permettent de mettre en évidence l'existence de phénomènes de diffusion et de les décrire, mais ne permettent pas d'en étudier le processus. Les simulations informatiques, grâce aux performances croissantes des ordinateurs, rendent possible l'étude des processus en tant que tels. Cette thèse, basée sur le modèle théorique développé par Braun et Gilardi (2006), présente une simulation centrée sur les agents des phénomènes de diffusion des politiques. Le point de départ de ce travail met en lumière, au niveau théorique, les principaux facteurs de changement internes à un pays : la préférence pour une politique donnée, l'efficacité de cette dernière, les contraintes institutionnelles, l'idéologie, et les principaux mécanismes de diffusion que sont l'apprentissage, la compétition, l'émulation et la coercition. La diffusion, définie par l'interdépendance des différents acteurs, est un système complexe dont l'étude est rendue possible par les simulations centrées sur les agents. Au niveau méthodologique, nous présenterons également les principaux concepts sous-jacents aux simulations, notamment la complexité et l'émergence. De plus, l'utilisation de simulations informatiques implique le développement d'un algorithme et sa programmation. Cette dernière réalisée, les agents peuvent interagir, avec comme résultat l'émergence d'un phénomène de diffusion, dérivé de l'apprentissage, où le choix d'un agent dépend en grande partie de ceux faits par ses voisins. De plus, ce phénomène suit une courbe en S caractéristique, poussant à la création de régions politiquement identiques, mais divergentes au niveau globale. Enfin, l'efficacité moyenne, dans ce monde simulé, suit une courbe en J, ce qui signifie qu'il faut du temps, non seulement pour que la politique montre ses effets, mais également pour qu'un pays introduise la politique la plus efficace. En conclusion, la diffusion est un phénomène émergent résultant d'interactions complexes dont les résultats du processus tel que développé dans ce modèle correspondent tant aux attentes théoriques qu'aux résultats pratiques.

Conditional compositional biplots: theory and application

The biplot has proved to be a powerful descriptive and analytical tool in many areasof applications of statistics. For compositional data the necessary theoreticaladaptation has been provided, with illustrative applications, by Aitchison (1990) andAitchison and Greenacre (2002). These papers were restricted to the interpretation ofsimple compositional data sets. In many situations the problem has to be described insome form of conditional modelling. For example, in a clinical trial where interest isin how patients’ steroid metabolite compositions may change as a result of differenttreatment regimes, interest is in relating the compositions after treatment to thecompositions before treatment and the nature of the treatments applied. To study thisthrough a biplot technique requires the development of some form of conditionalcompositional biplot. This is the purpose of this paper. We choose as a motivatingapplication an analysis of the 1992 US President ial Election, where interest may be inhow the three-part composition, the percentage division among the three candidates -Bush, Clinton and Perot - of the presidential vote in each state, depends on the ethniccomposition and on the urban-rural composition of the state. The methodology ofconditional compositional biplots is first developed and a detailed interpretation of the1992 US Presidential Election provided. We use a second application involving theconditional variability of tektite mineral compositions with respect to major oxidecompositions to demonstrate some hazards of simplistic interpretation of biplots.Finally we conjecture on further possible applications of conditional compositionalbiplots

Conditional deletion of ferritin h in mice reduces B and T lymphocyte populations.

The immune system and iron availability are intimately linked as appropriate iron supply is needed for cell proliferation, while excess iron, as observed in hemochromatosis, may reduce subsets of lymphocytes. We have tested the effects of a ferritin H gene deletion on lymphocytes. Mx-Cre mediated conditional deletion of ferritin H in bone marrow reduced the number of mature B cells and peripheral T cells in all lymphoid organs. FACS analysis showed an increase in the labile iron pool, enhanced reactive oxygen species formation and mitochondrial depolarization. The findings were confirmed by a B-cell specific deletion using Fth(lox/lox) ; CD19-Cre mice. Mature B cells were strongly under-represented in bone marrow and spleen of the deleted mice, whereas pre-B and immature B cells were not affected. Bone marrow B cells showed increased proliferation as judged by the number of cells in S and G2/M phase as well as BrdU incorporation. Upon in vitro culture with B-cell activating factor of the tumor necrosis factor family (BAFF), ferritin H-deleted spleen B cells showed lower survival rates than wild type cells. This was partially reversed with iron-chelator deferiprone. The loss of T cells was also confirmed by a T cell-specific deletion in Fth(lox/lox) ;CD4-Cre mice. Our data show that ferritin H is required for B and T cell survival by actively reducing the labile iron pool. They further suggest that natural B and T cell maturation is influenced by intracellular iron levels and possibly deregulated in iron excess or deprivation.

Construction and analysis of a new conditional ferritin H knockout mouse strain/

Résumé Le fer joue un rôle important dans la plupart des fonctions biologiques mais sa présence excessive provoque la production de molécules réactives d'oxygène (ROS) qui peuvent contribuer à diverses maladies. La protéine de stockage du fer, la ferritine H, capte l'excès en fer et le stocke sous forme non-toxique, ce qui empêche des dommages potentiels. La délétion de la ferritine H dans des souris knock-out a été essayée antérieurement, mais ces souris mouraient au stade précoce du développement embryonnaire. Pour étudier l'importance du fer, et en particulier son stockage dans la ferritine, et pour pouvoir mieux comprendre les fonctions de la ferritine H, nous avons créé un modèle de souris knock-out conditionnelles de la ferritine H, selon le système classique de Cre-LoxP. Le premier exon et la région du promoteur du gène de la ferritine H ont été entourés de sites loxP. La mortalité embryonnaire provoquée par la délétion constitutive du gène de la ferritine H a été confirmée en croisant nos souris avec des souris exprimant nestin-Cre1. En croisant nos souris avec des souris transgéniques Mx-Cre, nous avons observé que l'induction de Cre par injection de polyI-polyC provoque la délétion presque complète de la ferritine H dans le foie (> 99%) et la rate (> 88%). Ces tissus ont également perdu une grande partie de leur réserve de fer. Cette observation apporte pour la première fois la preuve in vivo que la ferritine H est indispensable pour le stockage du fer, que les fonctions de la ferritine H et de la ferritine L ne sont pas équivalentes, et que la ferritine L ne peut pas assumer seule la fonction de stockage du fer. Dans le foie des souris knock-out, l'expression de l'ARN messager de l'hepcidine a été induite après 10 jours. En même temps, l'expression de l'ARN messager des gènes codant pour des protéines de l'absorption de fer (DMT1, ferroportin, Dcytb1 et hephaestin) a été réprimée mais dans le duodénum seulement. L'expression d'hepcidine est inversément corrélée avec celle des gènes liés à l'absorption de fer. Cette observation corrobore des études antérieures. Mais, en plus, elle montre également que cette répression se produit seulement dans l'intestin. Nous pouvons ainsi tirer la conclusion suivante : ou bien l'hepcidine a un récepteur spécifique dans le duodénum ou bien les gènes liés à l'absorption de fer dans le duodénum ont un facteur spécifique de transcription sensible à l'hepcidine. Aucune répression de DMT1 et de ferroportin n'a été observée dans les macrophages de la rate après l'induction d'hepcidine. La délétion de ferritine H a entraîné une augmentation du taux de mortalité des cellules hépatiques, ainsi que des altérations dans l'architecture normale du tissu de la rate. Vu par l'immunohistologie, le nombre de lymphocytes B et T était réduit dans la rate, tendant à démontrer que la ferritine H et l'homéostase du fer jouent un rôle dans l'immunité. En conclusion, le modèle de souris knock-out conditionnelles de la ferritine H nous fournit un outil précieux pour l'étude in vivo du rôle joué par la ferritine dans l'homéostase du fer, dans les dommages créés par les ROS, ainsi que dans l'apoptose et l'immunité. Summary Iron plays an important role in most biological functions. However, excess of iron results in production of reactive oxygen species (ROS) which could substantially contribute to pathology of various diseases. Ferritin H scavenges excess of iron and stores it in non-toxic form and potentially prevents the damage. Fenitin H targeting in mice has been attempted before, however, straight knockout was lethal in early embryonic stage. To study the role of iron and its storage protein ferritin and to further elucidate ferritin H functions, we aimed at creating a conditional ferritin H knockout mouse model by classical Cre-LoxP system. First exon along with promoter region of the ferritin H gene was foxed. Embryonic lethality of the constitutive ferritin H deletion was confirmed by crossing the foxed mice with mice expressing nestin Cre-1 as transgene. Almost complete deletion was observed in liver (> 99%) and spleen (>88%) upon induction of Cre by injecting polyI-polyC in Fth Lox/Lox; MxCre mice. These tissues also lost substantial fraction of their iron stores. This provides first in vivo evidence that ferritin H is required for iron storage, ferritin H and L functions are not redundant and that ferritin L cannot perform iron storage function alone. Hepcidin mRNA expression was induced after 10 days in the livers of deleted mice and, simultaneously, mRNA expression of iron absorption related genes (DMT 1, ferroportin, Dcytb1 and hephaestin) was repressed in duodenum only. Hepcidin expression is inversely correlated with that of duodenal iron absorption related genes. This is in agreement with previous studies. However, we also show that this repression happens only in intestine. This leads to the conclusion that either hepcidin has a specific receptor in duodenum or the iron absorption related genes have duodenum specific transcription factor that is responsive to hepcidin. No repression of DMT1 and ferroportin was observed in spleen macrophages upon hepcidin induction. Ferritin H deletion showed increased cell death in liver and disruption of normal architecture of spleen. B lymphocytes were reduced in spleen on immunohistology which point towards a role of ferritin H and iron homeostasis in immunity. In conclusion, ferritin H conditional knockout mouse model provides us with an invaluable tool to study the in vivo role of ferritin H in iron homeostasis, ROS mediated damage, apoptosis and immunity.

Modelling world investment markets using threshold conditional correlation models

In this paper we propose a parsimonious regime-switching approach to model the correlations between assets, the threshold conditional correlation (TCC) model. This method allows the dynamics of the correlations to change from one state (or regime) to another as a function of observable transition variables. Our model is similar in spirit to Silvennoinen and Teräsvirta (2009) and Pelletier (2006) but with the appealing feature that it does not suffer from the course of dimensionality. In particular, estimation of the parameters of the TCC involves a simple grid search procedure. In addition, it is easy to guarantee a positive definite correlation matrix because the TCC estimator is given by the sample correlation matrix, which is positive definite by construction. The methodology is illustrated by evaluating the behaviour of international equities, govenrment bonds and major exchange rates, first separately and then jointly. We also test and allow for different parts in the correlation matrix to be governed by different transition variables. For this, we estimate a multi-threshold TCC specification. Further, we evaluate the economic performance of the TCC model against a constant conditional correlation (CCC) estimator using a Diebold-Mariano type test. We conclude that threshold correlation modelling gives rise to a significant reduction in portfolio´s variance.

Two-sided learning in new keynesian models: dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that they observe (which may be distinct for different sets of agents) to form beliefs about unknown aspects of the true model of the economy, use their beliefs to decide on actions, and revise these beliefs through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of our model and derive its policy recommendations, particularly with respect to central bank communications. We demonstrate that two-sided learning can generate substantial increases in volatility and persistence, and alter the behavior of the variables in the model in a signifficant way. Our simulations do not converge to a symmetric rational expectations equilibrium and we highlight one source that invalidates the convergence results of Marcet and Sargent (1989). Finally, we identify a novel aspect of central bank communication in models of learning: communication can be harmful if the central bank's model is substantially mis-specified

The Voting Practice of the Fifteen in the UN General Assembly: Convergence and Divergence

The EU has, since the early days of the Community, had the ambition to speak with ‘a single voice’ in international fora, in particular in the United Nations’ General Assembly. This aspiration, which has become more pronounced since the inauguration of the CFSP, has not always been easy to achieve due to domestic or international level factors affecting the EU member states. However, in the last decade there has been a dramatic increase in convergence in the Fifteen’s voting record. This paper contemplates the underlying reasons for such a convergence

Technological convergence: a strategic perspective

The information and communication technologies (ICT) sectors are in a process of technological convergence. Determinant factors in this process are the liberalisation of the telecommunications markets and technological change. Many firms are engaged in a process of mergers and alliances to position themselves in this new framework. Technological and demand uncertainties are very important. Our objective in this paper is to study the economic determinants of the strategies of the firms. With this aim, we review some key technological and demand aspects. We shed some light on the strategic motivations of the firms by establishing a parallel with the evolution of the retailing sector

NLRP3 inflammasome activation: The convergence of multiple signalling pathways on ROS production?

The NLR family, pyrin domain-containing 3 (NLRP3) inflammasome is a multiprotein complex that activates caspase 1, leading to the processing and secretion of the pro-inflammatory cytokines interleukin-1beta (IL-1beta) and IL-18. The NLRP3 inflammasome is activated by a wide range of danger signals that derive not only from microorganisms but also from metabolic dysregulation. It is unclear how these highly varied stress signals can be detected by a single inflammasome. In this Opinion article, we review the different signalling pathways that have been proposed to engage the NLRP3 inflammasome and suggest a model in which one of the crucial elements for NLRP3 activation is the generation of reactive oxygen species (ROS).