942 resultados para Molecular processes


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While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

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The sea-surface microlayer (SML) is at the upper- most surface of the ocean, linking the hydrosphere with the atmosphere. The presence and enrichment of organic compounds in the SML have been suggested to influence air- sea gas exchange processes as well as the emission of primary organic aerosols. Here, we report on organic matter components collected from an approximately 50µm thick SML and from the underlying water (ULW), ca. 20 cm below the SML, in December 2012 during the SOPRAN METEOR 91 cruise to the highly productive, coastal upwelling regime off the coast of Peru. Samples were collected at 37 stations including coastal upwelling sites and off-shore stations with less organic matter and were analyzed for total and dissolved high molecular weight (> 1 kDa) combined carbohydrates (TCCHO, DCCHO), free amino acids (FAA), total and dissolved hydrolyzable amino acids (THAA, DHAA), transparent exopolymer particles (TEP), Coomassie stainable particles (CSPs), total and dissolved organic carbon (TOC, DOC), total and dissolved nitrogen (TN, TDN), as well as bacterial and phytoplankton abundance. Our results showed a close coupling between organic matter concentrations in the water column and in the SML for almost all components except for FAA and DHAA that showed highest enrichment in the SML on average. Accumulation of gel particles (i.e., TEP and CSP) in the SML differed spatially. While CSP abundance in the SML was not related to wind speed, TEP abundance decreased with wind speed, leading to a depletion of TEP in the SML at about 5 m s-1 . Our study provides insight to the physical and biological control of organic matter enrichment in the SML, and discusses the potential role of organic matter in the SML for air-sea exchange processes.

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Ocean acidification (OA) is believed to be a major threat for near-future marine ecosystems, and that the most sensitive organisms will be calcifying organisms and the free-living larval stages produced by most benthic marine species. In this respect, echinoderms are one of the taxa most at risk. Earlier research on the impact of near-future OA on echinoderm larval stages showed negative effects, such as a decreased growth rate, increased mortality, and developmental abnormalities. However, all the long-term studies were performed on planktotrophic larvae while alternative life-history strategies, such as nonfeeding lecithotrophy, were largely ignored. Here, we show that lecithotrophic echinoderm larvae and juveniles are positively impacted by ocean acidification. When cultured at low pH, larvae and juveniles of the sea star Crossaster papposus grow faster with no visible affects on survival or skeletogenesis. This suggests that in future oceans, lecithotrophic species may be better adapted to deal with the threat of OA compared with planktotrophic ones with potentially important consequences at the ecosystem level. For example, an increase in populations of the top predator C. papposus will likely have huge consequences for community structure. Our results also highlight the importance of taking varying life-history strategies into account when assessing the impacts of climate change, an approach that also provides insight into understanding the evolution of life-history strategies.

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Schistosomiasis is a neglected tropical disease that affects more than 200 million people worldwide. The main disease-causing agents, Schistosoma japonicum, S. mansoni and S. haematobium, are blood flukes that have complex life cycles involving a snail intermediate host. In Asia, S. japonicum causes hepatointestinal disease (schistosomiasis japonica) and is challenging to control due to a broad distribution of its snail hosts and range of animal reservoir hosts. In China, extensive efforts have been underway to control this parasite, but genetic variability in S. japonicum populations could represent an obstacle to eliminating schistosomiasis japonica. Although a draft genome sequence is available for S. japonicum, there has been no previous study of molecular variation in this parasite on a genome-wide scale. In this study, we conducted the first deep genomic exploration of seven S. japonicum populations from mainland China, constructed phylogenies using mitochondrial and nuclear genomic data sets, and established considerable variation between some of the populations in genes inferred to be linked to key cellular processes and/or pathogen-host interactions. Based on the findings from this study, we propose that verifying intraspecific conservation in vaccine or drug target candidates is an important first step toward developing effective vaccines and chemotherapies against schistosomiasis.

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BACKGROUND AND OBJECTIVES: Analysis of IgH rearrangements in B-cell malignancies has provided clinical researchers with a wide range of information during the last few years. However, only a few studies have contributed to the characterization of these features in multiple myeloma (MM), and they have been focused on the analysis of the expressed IgH allele only. Comparison between the expressed and the non-functional IgH alleles allows further characterizion of the selection processes to which pre-myeloma cells are submitted. DESIGN AND METHODS: We analyzed a cohort of 84 untreated MM patients in order to characterize their functional VDJH and non-functional DJH rearrangements. The pattern of mutations and gene segment usage for both types of rearrangements was analyzed by polymerase chain reaction and sequencing. RESULTS: VH3 and VH1 family members were over- and under-represented, respectively. VH3-30 and VH3-15 segments were the most frequently used, whereas VH4-34 was found only in non-functional or heavily mutated VDJH rearrangements. DH2 and DH3 family members were over-represented in both VDJH and DJH repertoires, while the DH1 family was under-represented only in the productive VDJH rearrangements. Finally, DH3-22 and DH2-21 gene segments were found to be over-represented in the functional repertoire while segments commonly used by less mature B-cell malignancies, such as DH6-19 or DH3-3, were under-represented. INTERPRETATION AND CONCLUSIONS: Data reported here help to identify the clonogenic MM cell as a post-germinal center B cell that has undergone selection processes during the germinal center reaction.

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This book commemorates the 25th anniversary of the International Izatt-Christensen Award in Macrocyclic and Supramolecular Chemistry. The award, one of the most prestigious of small awards in chemistry, recognizes excellence in the developing field of macrocyclic and supramolecular chemistry

Macrocyclic and Supramolecular Chemistry: How Izatt-Christensen Award Winners Shaped the Field features chapters written by the award recipients who provide unique perspectives on the spectacular growth in these expanding and vibrant fields of chemistry over the past half century, and on the role of these awardees in shaping this growth. During this time there has been an upsurge of interest in the design, synthesis and characterization of increasingly more complex macrocyclic ligands and in the application of this knowledge to understanding molecular recognition processes in host-guest chemistry in ways that were scarcely envisioned decades earlier.

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A selected ion flow tube study of the reactions of a series of gas-phase atomic cations (S+, Xe+, O+, Kr+, N+, Ar+ and Ne+) and molecular ions (SF n+ (n = 1-5), CFn+ (n = 1-3), CF2Cl+, H3O+, NO+, N 2O+, CO2+, CO+, and N2+) spanning a large range of recombination energies (6.3-21.6 eV), with acetone, 1,1,1-trifluoroacetone, and hexafluoroacetone has been undertaken with the objective of exploring the nature of the reaction ion chemistry as the methyl groups in acetone are substituted for CF3. The reaction rate coefficients and product ion branching ratios for all 66 reactions, measured at 298 K, are reported. The experimental reaction rate coefficients are compared to theoretically calculated collisional values. Several distinct reaction processes were observed among the large number of reactions studied, including charge transfer (non-dissociative and dissociative), abstraction, ion-molecule associations and, in the case of the reactions involving the reagent ion H3O+, proton transfer. 

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Microsecond long Molecular Dynamics (MD) trajectories of biomolecular processes are now possible due to advances in computer technology. Soon, trajectories long enough to probe dynamics over many milliseconds will become available. Since these timescales match the physiological timescales over which many small proteins fold, all atom MD simulations of protein folding are now becoming popular. To distill features of such large folding trajectories, we must develop methods that can both compress trajectory data to enable visualization, and that can yield themselves to further analysis, such as the finding of collective coordinates and reduction of the dynamics. Conventionally, clustering has been the most popular MD trajectory analysis technique, followed by principal component analysis (PCA). Simple clustering used in MD trajectory analysis suffers from various serious drawbacks, namely, (i) it is not data driven, (ii) it is unstable to noise and change in cutoff parameters, and (iii) since it does not take into account interrelationships amongst data points, the separation of data into clusters can often be artificial. Usually, partitions generated by clustering techniques are validated visually, but such validation is not possible for MD trajectories of protein folding, as the underlying structural transitions are not well understood. Rigorous cluster validation techniques may be adapted, but it is more crucial to reduce the dimensions in which MD trajectories reside, while still preserving their salient features. PCA has often been used for dimension reduction and while it is computationally inexpensive, being a linear method, it does not achieve good data compression. In this thesis, I propose a different method, a nonmetric multidimensional scaling (nMDS) technique, which achieves superior data compression by virtue of being nonlinear, and also provides a clear insight into the structural processes underlying MD trajectories. I illustrate the capabilities of nMDS by analyzing three complete villin headpiece folding and six norleucine mutant (NLE) folding trajectories simulated by Freddolino and Schulten [1]. Using these trajectories, I make comparisons between nMDS, PCA and clustering to demonstrate the superiority of nMDS. The three villin headpiece trajectories showed great structural heterogeneity. Apart from a few trivial features like early formation of secondary structure, no commonalities between trajectories were found. There were no units of residues or atoms found moving in concert across the trajectories. A flipping transition, corresponding to the flipping of helix 1 relative to the plane formed by helices 2 and 3 was observed towards the end of the folding process in all trajectories, when nearly all native contacts had been formed. However, the transition occurred through a different series of steps in all trajectories, indicating that it may not be a common transition in villin folding. The trajectories showed competition between local structure formation/hydrophobic collapse and global structure formation in all trajectories. Our analysis on the NLE trajectories confirms the notion that a tight hydrophobic core inhibits correct 3-D rearrangement. Only one of the six NLE trajectories folded, and it showed no flipping transition. All the other trajectories get trapped in hydrophobically collapsed states. The NLE residues were found to be buried deeply into the core, compared to the corresponding lysines in the villin headpiece, thereby making the core tighter and harder to undo for 3-D rearrangement. Our results suggest that the NLE may not be a fast folder as experiments suggest. The tightness of the hydrophobic core may be a very important factor in the folding of larger proteins. It is likely that chaperones like GroEL act to undo the tight hydrophobic core of proteins, after most secondary structure elements have been formed, so that global rearrangement is easier. I conclude by presenting facts about chaperone-protein complexes and propose further directions for the study of protein folding.

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G protein-coupled receptors (GPCRs) are seven-pass integral membrane proteins that act as transducers of extracellular signals across the lipid bilayer. Their location and involvement in basic and pathological physiological processes has secured their role as key targets for pharmaceutical intervention. GPCRs are targeted by many of the best-selling drugs on the market and there are a substantial number of GPCRs that are yet to be characterised; these could offer interest for therapeutic targeting. GPR35 is one such receptor that, as a result of gene knockout and genome wide association studies, has attracted interest through its association with cardiovascular and gastrointestinal disease. Elucidation of the basic physiological function of GPR35 has, however, been difficult due a paucity of potent and selective ligands in addition to a lack of consensus on the endogenous ligand. Herein, a focussed drug discovery effort was carried out to identify agonists of GPR35. Various in vitro cellular assays were employed in conjunction with N- or C-terminally manipulated forms of the receptor to investigate GPR35’s signalling profile and to provide an assay format suitable for the characterisation of newly identified ligands. Although GPR35 associates with both Gαi/o and Gα13 families of small heterotrimeric G proteins, the G protein-independent β-arrestin-2 recruitment format was found to be the most suited to drug screening efforts. Small molecule compound screening, carried out in conjunction with the Medical Research Council Technology, identified compound 1 as the most potent ligand of human GPR35 reported at that time. However, the lower efficacy and potency of compound 1 at the rodent species orthologues of GPR35 prevented its use in in vivo studies. A subsequent effort, carried out with Novartis, focused on mast cell stabilisers as putative agonists of GPR35, revealed lodoxamide and bufrolin as highly potent agonists that activated human and rat GPR35 with equal potency. This finding offered–for the first time–the opportunity to employ the same GPR35 ligand between species at a similar concentration, an important factor to consider when translating rodent in vivo functional studies to those in man. Additionally, using molecular modelling and site directed mutagenesis studies, these newly identified compounds were used to aid characterisation of the ligand binding pockets of human and rat GPR35 to reveal the molecular basis of species selectivity at this receptor. In summary, this research effort presents GPR35 tool compounds that can now be used to dissect the basic biology of GPR35 and investigate its contribution to disease.

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We review our work on generalisations of the Becker-Doring model of cluster-formation as applied to nucleation theory, polymer growth kinetics, and the formation of upramolecular structures in colloidal chemistry. One valuable tool in analysing mathematical models of these systems has been the coarse-graining approximation which enables macroscopic models for observable quantities to be derived from microscopic ones. This permits assumptions about the detailed molecular mechanisms to be tested, and their influence on the large-scale kinetics of surfactant self-assembly to be elucidated. We also summarise our more recent results on Becker-Doring systems, notably demonstrating that cross-inhibition and autocatalysis can destabilise a uniform solution and lead to a competitive environment in which some species flourish at the expense of others, phenomena relevant in models of the origins of life.

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The fruit is one of the most complex and important structures produced by flowering plants, and understanding the development and maturation process of fruits in different angiosperm species with diverse fruit structures is of immense interest. In the work presented here, molecular genetics and genomic analysis are used to explore the processes that form the fruit in two species: The model organism Arabidopsis and the diploid strawberry Fragaria vesca. One important basic question concerns the molecular genetic basis of fruit patterning. A long-standing model of Arabidopsis fruit (the gynoecium) patterning holds that auxin produced at the apex diffuses downward, forming a gradient that provides apical-basal positional information to specify different tissue types along the gynoecium’s length. The proposed gradient, however, has never been observed and the model appears inconsistent with a number of observations. I present a new, alternative model, wherein auxin acts to establish the adaxial-abaxial domains of the carpel primordia, which then ensures proper development of the final gynoecium. A second project utilizes genomics to identify genes that regulate fruit color by analyzing the genome sequences of Fragaria vesca, a species of wild strawberry. Shared and distinct SNPs among three F. vesca accessions were identified, providing a foundation for locating candidate mutations underlying phenotypic variations among different F. vesca accessions. Through systematic analysis of relevant SNP variants, a candidate SNP in FveMYB10 was identified that may underlie the fruit color in the yellow-fruited accessions, which was subsequently confirmed by functional assays. Our lab has previously generated extensive RNA-sequencing data that depict genome-scale gene expression profiles in F. vesca fruit and flower tissues at different developmental stages. To enhance the accessibility of this dataset, the web-based eFP software was adapted for this dataset, allowing visualization of gene expression in any tissues by user-initiated queries. Together, this thesis work proposes a well-supported new model of fruit patterning in Arabidopsis and provides further resources for F. vesca, including genome-wide variant lists and the ability to visualize gene expression. This work will facilitate future work linking traits of economic importance to specific genes and gaining novel insights into fruit patterning and development.

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An integrated analysis of naproxen adsorption on bone char in batch and packed-bed column conditions has been performed. Kinetic, thermodynamic and breakthrough parameters have been calculated using adsorption models and artificial neural networks. Results show that naproxen removal using bone char in batch conditions is a feasible and effective process, which could involve electrostatic and non-electrostatic interactions depending mainly on pH conditions. However, the application of packed-bed column for naproxen adsorption on bone char is not effective for the treatment of diluted solutions due to the low degree of adsorbent utilization (below 4%) at tested operating conditions. The proposed mechanism for naproxen removal using bone char could include a complexation process via phosphate and naproxen, hydrogen bonding and the possibility of hydrophobic interactions via π–π electron. This study highlights the relevance of performing an integrated analysis of adsorbent effectiveness in batch and dynamic conditions to establish the best process configuration for the removal of emerging water pollutants such as pharmaceuticals.

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A large proportion of human populations suffer memory impairments either caused by normal aging or afflicted by diverse neurological and neurodegenerative diseases. Memory enhancers and other drugs tested so far against memory loss have failed to produce therapeutic efficacy in clinical trials and thus, there is a need to find remedy for this mental disorder. In search for cure of memory loss, our laboratory discovered a robust memory enhancer called RGS14(414). A treatment in brain with its gene produces an enduring effect on memory that lasts for lifetime of rats. Therefore, current thesis work was designed to investigate whether RGS14(414) treatment can prevent memory loss and furthermore, explore through biological processes responsible for RGS-mediated memory enhancement. We found that RGS14(414) gene treatment prevented episodic memory loss in rodent models of normal aging and Alzheimer´s disease. A memory loss was observed in normal rats at 18 months of age; however, when they were treated with RGS14(414) gene at 3 months of age, they abrogated this deficit and their memory remained intact till the age of 22 months. In addition to normal aging rats, effect of memory enhancer treatment in mice model of Alzheimer´s disease (AD-mice) produced a similar effect. AD-mice subjected to treatment with RGS14(414) gene at the age of 2 months, a period when memory was intact, showed not only a prevention in memory loss observed at 4 months of age but also they were able to maintain normal memory after 6 months of the treatment. We posit that long-lasting effect on memory enhancement and prevention of memory loss mediated through RGS14(414) might be due to a permanent structural change caused by a surge in neuronal connections and enhanced neuronal remodeling, key processes for long-term memory formation. A neuronal arborization analysis of both pyramidal and non-pyramidal neurons in brain of RGS14(414)-treated rats exhibited robust rise in neurites outgrowth of both kind of cells, and an increment in number of branching from the apical dendrite of pyramidal neurons, reaching to almost three times of the control animals. To further understand of underlying mechanism by which RGS14(414) induces neuronal arborization, we investigated into neurotrophic factors. We observed that RGS14 treatment induces a selective increase in BDNF. Role of BDNF in neuronal arborization, as well as its implication in learning and memory processes is well described. In addition, our results showing a dynamic expression pattern of BDNF during ORM processing that overlapped with memory consolidation further support the idea of the implication of this neurotrophin in formation of long-term memory in RGS-animals. On the other hand, in studies of expression profiling of RGS-treated animals, we have demonstrated that 14-3-3ζ protein displays a coherent relationship to RGS-mediated ORM enhancement. Recent studies have demonstrated that the interaction of receptor for activated protein kinase 1 (RACK1) with 14-3-3ζ is essential for its nuclear translocation, where RACK1-14-3-3ζ complex binds at promotor IV region of BDNF and promotes an increase in BDNF gene transcription. These observations suggest that 14-3-3ζ might regulate the elevated level of BDNF seen in RGS14(414) gene treated animals. Therefore, it seems that RGS-mediated surge in 14-3-3ζ causes elevated BDNF synthesis needed for neuronal arborization and enhanced ORM. The prevention of memory loss might be mediated through a restoration in BDNF and 14-3-3ζ protein levels, which are significantly decreased in aging and Alzheimer’s disease. Additionally, our results demonstrate that RGS14(414) treatment could be a viable strategy against episodic memory loss.

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Molecular simulation provides a powerful tool for connecting molecular-level processes to physical observables. However, the facility to make those connections relies upon the application and development of theoretical methods that permit appropriate descriptions of the systems or processes to be studied. In this thesis, we utilize molecular simulation to study and predict two phenomena with very different theoretical challenges, beginning with (1) lithium-ion transport behavior in polymers and following with (2) equilibrium isotope effects with relevance to position-specific and clumped isotope studies. In the case of ion transport in polymers, there is motivation to use molecular simulation to provide guidance in polymer electrolyte design, but the length and timescales relevant for ion diffusion in polymers preclude the use of direct molecular dynamics simulation to compute ion diffusivities in more than a handful of candidate systems. In the case of equilibrium isotope effects, the thermodynamic driving forces for isotopic fractionation are often fundamentally quantum mechanical in nature, and the high precision of experimental instruments demands correspondingly accurate theoretical approaches. Herein, we describe respectively coarse-graining and path-integral strategies to address outstanding questions in these two subject areas.

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Le rétrécissement valvulaire aortique (RVA) est causé par une calcification et une fibrose progressive de la valve aortique. Le risque de développer la maladie augmente avec l’âge. À cause de l’augmentation de l’espérance de vie, le RVA est devenu un problème de santé publique. Le RVA est fatal en absence de traitement médical. Actuellement, la chirurgie est le seul traitement pour le stade sévère de la maladie, mais près de 50% des individus avec RVA n’y sont pas éligibles, principalement due à la présence de comorbidités. Plusieurs processus biologiques ont été associés à la maladie, mais les voies moléculaires spécifiques et les gènes impliqués dans le développement et la progression du RVA ne sont pas connus. Il est donc urgent de découvrir les gènes de susceptibilité pour le RVA afin d’identifier les personnes à risque ainsi que les biomarqueurs et les cibles thérapeutiques pouvant mener au développement de médicaments pour inverser ou limiter la progression de la maladie. L’objectif de cette thèse de doctorat était d’identifier la base moléculaire du RVA. Des approches modernes en génomique, incluant l’étude de gènes candidats et le criblage génomique par association (GWAS), ont été réalisées à l’aide de collections d’ADN provenant d’un grand nombre de patients bien caractérisés pour le RVA. Des études complémentaires en transciptomique ont comparé le profil d’expression global des gènes entre des valves calcifiées et non-calcifiées à l’aide de biopuces à ADN et de séquençage de l’ARN. Une première étude a identifié des variations dans le gène NOTCH1 et suggère pour la première fois la présence d’un polymorphisme commun dans ce gène conférant une susceptibilité au RVA. La deuxième étude a combiné par méta-analyse deux GWAS de patients provenant de la ville de Québec et Paris (France) aux données transcriptomiques. Cette étude de génomique intégrative a confirmé le rôle de RUNX2 dans le RVA et a permis l’identification d’un nouveau gène de susceptibilité, CACNA1C. Les troisième et quatrième études sur l’expression des gènes ont permis de mieux comprendre les bases moléculaires de la calcification des valves aortiques bicuspides et ainsi d’identifier de nouvelles cibles thérapeutiques pour le RVA. Les données générées par ce projet sont la base de futures découvertes importantes qui permettront d’améliorer les options de traitement et la qualité de vie des patients atteints du RVA.