63 research outputs found

    Energy Model for the Design of Ultra-Low Power Nodes for Wireless Sensor Networks

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    AbstractThis article describes the modeling of a microsensor node for wireless sensor network applications. Considering the heterogeneous aspect of a sensor node, the developed model allows comparing different node configurations in order to make the best choice of components according to the specifications of the application. Therefore, our model allows identifying the need to design specific element or to use Components Of the Shelf

    Regulation of downstream neuronal genes by proneural transcription factors during initial neurogenesis in the vertebrate brain

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    International audienceBACKGROUND: Neurons arise in very specific regions of the neural tube, controlled by components of the Notch signalling pathway, proneural genes, and other bHLH transcription factors. How these specific neuronal areas in the brain are generated during development is just beginning to be elucidated. Notably, the critical role of proneural genes during differentiation of the neuronal populations that give rise to the early axon scaffold in the developing brain is not understood. The regulation of their downstream effectors remains poorly defined. RESULTS: This study provides the first overview of the spatiotemporal expression of proneural genes in the neuronal populations of the early axon scaffold in both chick and mouse. Overexpression studies and mutant mice have identified a number of specific neuronal genes that are targets of proneural transcription factors in these neuronal populations. CONCLUSION: Together, these results improve our understanding of the molecular mechanisms involved in differentiation of the first neuronal populations in the brain

    Novel genes upregulated when NOTCH signalling is disrupted during hypothalamic development.

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    International audienceBACKGROUND: The generation of diverse neuronal types and subtypes from multipotent progenitors during development is crucial for assembling functional neural circuits in the adult central nervous system. It is well known that the Notch signalling pathway through the inhibition of proneural genes is a key regulator of neurogenesis in the vertebrate central nervous system. However, the role of Notch during hypothalamus formation along with its downstream effectors remains poorly defined. RESULTS: Here, we have transiently blocked Notch activity in chick embryos and used global gene expression analysis to provide evidence that Notch signalling modulates the generation of neurons in the early developing hypothalamus by lateral inhibition. Most importantly, we have taken advantage of this model to identify novel targets of Notch signalling, such as Tagln3 and Chga, which were expressed in hypothalamic neuronal nuclei. CONCLUSIONS: These data give essential advances into the early generation of neurons in the hypothalamus. We demonstrate that inhibition of Notch signalling during early development of the hypothalamus enhances expression of several new markers. These genes must be considered as important new targets of the Notch/proneural network

    Local retinoic acid signaling directs emergence of the extraocular muscle functional unit

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    Coordinated development of muscles, tendons, and their attachment sites ensures emergence of functional musculoskeletal units that are adapted to diverse anatomical demands among different species. How these different tissues are patterned and functionally assembled during embryogenesis is poorly understood. Here, we investigated the morphogenesis of extraocular muscles (EOMs), an evolutionary conserved cranial muscle group that is crucial for the coordinated movement of the eyeballs and for visual acuity. By means of lineage analysis, we redefined the cellular origins of periocular connective tissues interacting with the EOMs, which do not arise exclusively from neural crest mesenchyme as previously thought. Using 3D imaging approaches, we established an integrative blueprint for the EOM functional unit. By doing so, we identified a developmental time window in which individual EOMs emerge from a unique muscle anlage and establish insertions in the sclera, which sets these muscles apart from classical muscle-to-bone type of insertions. Further, we demonstrate that the eyeballs are a source of diffusible all-trans retinoic acid (ATRA) that allow their targeting by the EOMs in a temporal and dose-dependent manner. Using genetically modified mice and inhibitor treatments, we find that endogenous local variations in the concentration of retinoids contribute to the establishment of tendon condensations and attachment sites that precede the initiation of muscle patterning. Collectively, our results highlight how global and site-specific programs are deployed for the assembly of muscle functional units with precise definition of muscle shapes and topographical wiring of their tendon attachments

    Conception multidisciplinaire de microsystĂšmes autonomes

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    Any natural action creates lost energy which could be exploited to supply our electrical and mobile appliance. Our physical environments have a high number of micro-energy sources. Admittedly, each one provides low power but their multiplicity could be significant, in particular within the framework of the microsystem operation. The previous observation guided our works towards the problematic of autonomous microsystem design. Thus, to be innovative, microsystems engineering must lean on electronic, mechanical and energy domains. The design process is highly multidisciplinary and its efficiency depends on the ability to implement methods and tools: - of collaborative design - of capitalization of technical knowledge - of multiphysic engineering - of integrated design. Based on these fundamentals, we developed a design support tool. The underlying methodology enables: 6- the design problem analysis and structuring of an autonomous microsystem: this phase leads to the identification and functional and environmental description of the system and its environment 7- the knowledge modelling: an architectural analysis gives the description of components and interactions related to the microsystem (directly or indirectly). Then, it leads to a behaviour modelling. 8- the energy qualification and physical coupling: the structured reuse of knowledge models is guided to couple physical models and describe the sources, sinks and the energy mechanism of the environment. 9- the control of innovative concept search: the knowledge base, qualification criteria and functional description, previously constructed, are combined in an unique virtual design approach dedicated to search innovative concepts as a solution 10- the predimensioning: this phase ensures the integration of specific simulation tools (finite elements method and functional simulation). The predimensioning of autonomous microsystems is supported by a synthetic scheme based on an abductive reasoning (bottom-up). The combination of physical reasoning, the integration of methods and engineering domains, the virtual exploration of solution spaces and the modelling represent a new way to support autonomous microsystem design. This approach was applied to the design of an autonomous piezoelectric sensor.Toute action naturelle crĂ©e de l'Ă©nergie perdue qui pourrait ĂȘtre exploitĂ©e pour alimenter nos appareils Ă©lectriques et mobiles. Nos environnements physiques disposent d'un nombre Ă©levĂ© de micro-sources d'Ă©nergies ; certes chacune est de faible puissance, mais leur multiplicitĂ© pourrait s'avĂ©rer significative, notamment dans le cadre du fonctionnement de microsystĂšmes. C'est le principe prĂ©cĂ©dent qui a conduit nos travaux sur la problĂ©matique de la conception de microsystĂšmes autonomes. Ainsi, pour ĂȘtre innovante, l'ingĂ©nierie de microsystĂšmes doit Ă  la fois s'appuyer sur la culture de l'Ă©lectronique, de la mĂ©canique mais aussi de l'Ă©nergĂ©tique. Le processus de conception est fortement pluridisciplinaire et son efficacitĂ© rĂ©side dans la capacitĂ© Ă  mettre en oeuvre des mĂ©thodologies et des outils : - de conception collaborative, - de capitalisation des connaissances techniques, - d'ingĂ©nierie multi-physique, - d'ingĂ©nierie intĂ©grĂ©e. Sur le base de ces fondamentaux, nous avons dĂ©veloppĂ© un outil d'aide Ă  la conception. La mĂ©thodologie sous-jacente permet : 1- l'analyse et la structuration d'un problĂšme de conception d'un microsystĂšme autonome : cette phase conduit l'identification, la description fonctionnelle et environnementale du systĂšme et de son environnement. 2- la modĂ©lisation des connaissances : une analyse architecturale conduit Ă  la description des composants et des interactions liĂ©es au microsystĂšme (directement ou indirectement) puis Ă  la modĂ©lisation des comportements, 3- la qualification Ă©nergĂ©tique et le couplage physique : la rĂ©utilisation structurĂ©e des modĂšles de connaissances est pilotĂ©e pour coupler les modĂšles physiques et dĂ©crire les sources, les puits et les mĂ©canismes Ă©nergĂ©tiques des environnements, 4- la conduite de la recherche de concepts innovants : la base de connaissances, les critĂšres de qualification et la description fonctionnelle prĂ©alablement construits sont agencĂ©s dans une seule mĂ©thode de conception virtuelle pour rechercher des concepts de solutions innovants, 5- le prĂ©-dimensionnement : tout en assurant l'intĂ©gration des outils spĂ©cialisĂ©s de simulation (mĂ©thode des Ă©lĂ©ments finis et simulation fonctionnelle), le prĂ©dimensionnement de microsystĂšmes autonomes est supportĂ©e selon un schĂ©ma synthĂ©tique, assurant un raisonnement abductif (ou bottom-up). La conjonction des raisonnements physiques, l'intĂ©gration des mĂ©thodes et des cultures mĂ©tiers, l'exploration virtuelle des espaces de solutions et la modĂ©lisation constituent les bases d'un nouveau moyen d'aide Ă  la conception de microsystĂšmes autonomes. Cette approche a Ă©tĂ© dĂ©ployĂ©e pour la conception d'un capteur piĂ©zoĂ©lectrique autonome

    Multidisciplinary design of autonomous microsystems

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    Toute action naturelle crĂ©e de l’énergie perdue qui pourrait ĂȘtre exploitĂ©e pour alimenter nos appareils Ă©lectriques et mobiles. Nos environnements physiques disposent d’un nombre Ă©levĂ© de micro-sources d’énergies ; certes chacune est de faible puissance, mais leur multiplicitĂ© pourrait s’avĂ©rer significative, notamment dans le cadre du fonctionnement de microsystĂšmes.C’est le principe prĂ©cĂ©dent qui a conduit nos travaux sur la problĂ©matique de la conception de microsystĂšmes autonomes. Ainsi, pour ĂȘtre innovante, l’ingĂ©nierie de microsystĂšmes doit Ă  la fois s’appuyer sur la culture de l’électronique, de la mĂ©canique mais aussi de l’énergĂ©tique. Le processus de conception est fortement pluridisciplinaire et son efficacitĂ© rĂ©side dans la capacitĂ© Ă  mettre en Ɠuvre des mĂ©thodologies et des outils :- de conception collaborative,- de capitalisation des connaissances techniques, - d’ingĂ©nierie multi-physique,- d’ingĂ©nierie intĂ©grĂ©e.Sur le base de ces fondamentaux, nous avons dĂ©veloppĂ© un outil d’aide Ă  la conception. La mĂ©thodologie sous-jacente permet :1- l’analyse et la structuration d’un problĂšme de conception d’un microsystĂšme autonome : cette phase conduit l’identification, la description fonctionnelle et environnementale du systĂšme et de son environnement.2- la modĂ©lisation des connaissances : une analyse architecturale conduit Ă  la description des composants et des interactions liĂ©es au microsystĂšme (directement ou indirectement) puis Ă  la modĂ©lisation des comportements,3- la qualification Ă©nergĂ©tique et le couplage physique : la rĂ©utilisation structurĂ©e des modĂšles de connaissances est pilotĂ©e pour coupler les modĂšles physiques et dĂ©crire les sources, les puits et les mĂ©canismes Ă©nergĂ©tiques des environnements,4- la conduite de la recherche de concepts innovants : la base de connaissances, les critĂšres de qualification et la description fonctionnelle prĂ©alablement construits sont agencĂ©s dans une seule mĂ©thode de conception virtuelle pour rechercher des concepts de solutions innovants,5- le prĂ©-dimensionnement : tout en assurant l’intĂ©gration des outils spĂ©cialisĂ©s de simulation (mĂ©thode des Ă©lĂ©ments finis et simulation fonctionnelle), le prĂ©-dimensionnement de microsystĂšmes autonomes est supportĂ©e selon un schĂ©ma synthĂ©tique, assurant un raisonnement abductif (ou bottom-up)La conjonction des raisonnements physiques, l’intĂ©gration des mĂ©thodes et des cultures mĂ©tiers, l’exploration virtuelle des espaces de solutions et la modĂ©lisation constituent les bases d’un nouveau moyen d’aide Ă  la conception de microsystĂšmes autonomes. Cette approche a Ă©tĂ© dĂ©ployĂ©e pour la conception d’un capteur piĂ©zoĂ©lectrique autonome.Any natural action creates lost energy which could be exploited to supply our electrical and mobile appliance. Our physical environments have a high number of micro-energy sources. Admittedly, each one provides low power but their multiplicity could be significant, in particular within the framework of the microsystem operation.The previous observation guided our works towards the problematic of autonomous microsystem design. Thus, to be innovative, microsystems engineering must lean on electronic, mechanical and energy domains. The design process is highly multidisciplinary and its efficiency depends on the ability to implement methods and tools:- of collaborative design- of capitalization of technical knowledge- of multiphysic engineering- of integrated design.Based on these fundamentals, we developed a design support tool. The underlying methodology enables:1- the design problem analysis and structuring of an autonomous microsystem: this phase leads to the identification and functional and environmental description of the system and its environment2- the knowledge modelling: an architectural analysis gives the description of components and interactions related to the microsystem (directly or indirectly). Then, it leads to a behaviour modelling.3- the energy qualification and physical coupling: the structured reuse of knowledge models is guided to couple physical models and describe the sources, sinks and the energy mechanism of the environment.4- the control of innovative concept search: the knowledge base, qualification criteria and functional description, previously constructed, are combined in an unique virtual design approach dedicated to search innovative concepts as a solution5- the predimensioning: this phase ensures the integration of specific simulation tools (finite elements method and functional simulation). The predimensioning of autonomous microsystems is supported by a synthetic scheme based on an abductive reasoning (bottom-up).The combination of physical reasoning, the integration of methods and engineering domains, the virtual exploration of solution spaces and the modelling represent a new way to support autonomous microsystem design. This approach was applied to the design of an autonomous piezoelectric sensor

    Multidisciplinary design of autonomous microsystems

    No full text
    Toute action naturelle crĂ©e de l’énergie perdue qui pourrait ĂȘtre exploitĂ©e pour alimenter nos appareils Ă©lectriques et mobiles. Nos environnements physiques disposent d’un nombre Ă©levĂ© de micro-sources d’énergies ; certes chacune est de faible puissance, mais leur multiplicitĂ© pourrait s’avĂ©rer significative, notamment dans le cadre du fonctionnement de microsystĂšmes.C’est le principe prĂ©cĂ©dent qui a conduit nos travaux sur la problĂ©matique de la conception de microsystĂšmes autonomes. Ainsi, pour ĂȘtre innovante, l’ingĂ©nierie de microsystĂšmes doit Ă  la fois s’appuyer sur la culture de l’électronique, de la mĂ©canique mais aussi de l’énergĂ©tique. Le processus de conception est fortement pluridisciplinaire et son efficacitĂ© rĂ©side dans la capacitĂ© Ă  mettre en Ɠuvre des mĂ©thodologies et des outils :- de conception collaborative,- de capitalisation des connaissances techniques, - d’ingĂ©nierie multi-physique,- d’ingĂ©nierie intĂ©grĂ©e.Sur le base de ces fondamentaux, nous avons dĂ©veloppĂ© un outil d’aide Ă  la conception. La mĂ©thodologie sous-jacente permet :1- l’analyse et la structuration d’un problĂšme de conception d’un microsystĂšme autonome : cette phase conduit l’identification, la description fonctionnelle et environnementale du systĂšme et de son environnement.2- la modĂ©lisation des connaissances : une analyse architecturale conduit Ă  la description des composants et des interactions liĂ©es au microsystĂšme (directement ou indirectement) puis Ă  la modĂ©lisation des comportements,3- la qualification Ă©nergĂ©tique et le couplage physique : la rĂ©utilisation structurĂ©e des modĂšles de connaissances est pilotĂ©e pour coupler les modĂšles physiques et dĂ©crire les sources, les puits et les mĂ©canismes Ă©nergĂ©tiques des environnements,4- la conduite de la recherche de concepts innovants : la base de connaissances, les critĂšres de qualification et la description fonctionnelle prĂ©alablement construits sont agencĂ©s dans une seule mĂ©thode de conception virtuelle pour rechercher des concepts de solutions innovants,5- le prĂ©-dimensionnement : tout en assurant l’intĂ©gration des outils spĂ©cialisĂ©s de simulation (mĂ©thode des Ă©lĂ©ments finis et simulation fonctionnelle), le prĂ©-dimensionnement de microsystĂšmes autonomes est supportĂ©e selon un schĂ©ma synthĂ©tique, assurant un raisonnement abductif (ou bottom-up)La conjonction des raisonnements physiques, l’intĂ©gration des mĂ©thodes et des cultures mĂ©tiers, l’exploration virtuelle des espaces de solutions et la modĂ©lisation constituent les bases d’un nouveau moyen d’aide Ă  la conception de microsystĂšmes autonomes. Cette approche a Ă©tĂ© dĂ©ployĂ©e pour la conception d’un capteur piĂ©zoĂ©lectrique autonome.Any natural action creates lost energy which could be exploited to supply our electrical and mobile appliance. Our physical environments have a high number of micro-energy sources. Admittedly, each one provides low power but their multiplicity could be significant, in particular within the framework of the microsystem operation.The previous observation guided our works towards the problematic of autonomous microsystem design. Thus, to be innovative, microsystems engineering must lean on electronic, mechanical and energy domains. The design process is highly multidisciplinary and its efficiency depends on the ability to implement methods and tools:- of collaborative design- of capitalization of technical knowledge- of multiphysic engineering- of integrated design.Based on these fundamentals, we developed a design support tool. The underlying methodology enables:1- the design problem analysis and structuring of an autonomous microsystem: this phase leads to the identification and functional and environmental description of the system and its environment2- the knowledge modelling: an architectural analysis gives the description of components and interactions related to the microsystem (directly or indirectly). Then, it leads to a behaviour modelling.3- the energy qualification and physical coupling: the structured reuse of knowledge models is guided to couple physical models and describe the sources, sinks and the energy mechanism of the environment.4- the control of innovative concept search: the knowledge base, qualification criteria and functional description, previously constructed, are combined in an unique virtual design approach dedicated to search innovative concepts as a solution5- the predimensioning: this phase ensures the integration of specific simulation tools (finite elements method and functional simulation). The predimensioning of autonomous microsystems is supported by a synthetic scheme based on an abductive reasoning (bottom-up).The combination of physical reasoning, the integration of methods and engineering domains, the virtual exploration of solution spaces and the modelling represent a new way to support autonomous microsystem design. This approach was applied to the design of an autonomous piezoelectric sensor

    : Retinoic acid receptors in cranial and branchial arch neural crest cells

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    International audiencePrevious work has emphasized the crucial role of retinoic acid (RA) in the ontogenesis of the vast majority of mesenchymal structures derived from the neural crest cells (NCC), which migrate through, or populate, the frontonasal process and branchial arches. Using somatic mutagenesis in the mouse, we have selectively ablated two or three retinoic acid receptors (i.e., RARalpha/RARbeta, RARalpha/RARgamma and RARalpha/RARbeta/RARgamma) in NCC. By rigorously analyzing these mutant mice, we found that survival and migration of NCC is normal until gestational day 10.5, suggesting that RAR-dependent signaling is not intrinsically required for the early steps of NCC development. However, ablation of Rara and Rarg genes in NCC yields an agenesis of the median portion of the face, demonstrating that RARalpha and RARgamma act cell-autonomously in postmigratory NCC to control the development of structures derived from the frontonasal process. In contrast, ablation of the three Rar genes in NCC leads to less severe defects of the branchial arches derived structures compared with Rar compound null mutants. Therefore, RARs exert a function in the NCC as well as in a separated cell population. This work demonstrates that RARs use distinct mechanisms to pattern cranial NCC

    Evolutionary Conservation of the Early Axon Scaffold in the Vertebrate Brain

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    International audienceThe early axon scaffold is the first axonal structure to appear in the rostral brain of vertebrates, paving the way for later, more complex connections. Several early axon scaffold components are conserved between all vertebrates; most notably two main ventral longitudinal tracts, the tract of the postoptic commissure and the medial longitudinal fascicle. While the overall structure is remarkably similar, differences both in the organization and the development of the early tracts are apparent. This review will bring together extensive data from the last 25 years in different vertebrates and for the first time, the timing and anatomy of these early tracts have been directly compared. Representatives of major vertebrate clades, including cat shark, Xenopus, chick, and mouse embryos, will be compared using immunohistochemistry staining based on previous results. There is still confusion over the nomenclature and homology of these tracts which this review will aim to address. The discussion here is relevant both for understanding the evolution of the early axon scaffold and for future studies into the molecular regulation of its formation. Developmental Dynamics, 2015. © 2015 Wiley Periodicals, In

    Notch signaling and proneural genes work together to control the neural building blocks for the initial scaffold in the hypothalamus.

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    International audienceThe vertebrate embryonic prosencephalon gives rise to the hypothalamus, which plays essential roles in sensory information processing as well as control of physiological homeostasis and behavior. While patterning of the hypothalamus has received much attention, initial neurogenesis in the developing hypothalamus has mostly been neglected. The first differentiating progenitor cells of the hypothalamus will give rise to neurons that form the nucleus of the tract of the postoptic commissure (nTPOC) and the nucleus of the mammillotegmental tract (nMTT). The formation of these neuronal populations has to be highly controlled both spatially and temporally as these tracts will form part of the ventral longitudinal tract (VLT) and act as a scaffold for later, follower axons. This review will cumulate and summarize the existing data available describing initial neurogenesis in the vertebrate hypothalamus. It is well-known that the Notch signaling pathway through the inhibition of proneural genes is a key regulator of neurogenesis in the vertebrate central nervous system. It has only recently been proposed that loss of Notch signaling in the developing chick embryo causes an increase in the number of neurons in the hypothalamus, highlighting an early function of the Notch pathway during hypothalamus formation. Further analysis in the chick and mouse hypothalamus confirms the expression of Notch components and Ascl1 before the appearance of the first differentiated neurons. Many newly identified proneural target genes were also found to be expressed during neuronal differentiation in the hypothalamus. Given the critical role that hypothalamic neural circuitry plays in maintaining homeostasis, it is particularly important to establish the targets downstream of this Notch/proneural network
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