A novel dominant mutation of the Nav1.4 alpha-subunit domain I leading to sodium channel myotonia.

BACKGROUND: Mutations in SCN4A may lead to myotonia. METHODS: Presentation of a large family with myotonia, including molecular studies and patch clamp experiments using human embryonic kidney 293 cells expressing wild-type and mutated channels. RESULTS: In a large family with historic data on seven generations and a clear phenotype, including myotonia at movement onset, with worsening by cold temperature, pregnancy, mental stress, and especially after rest after intense physical activity, but without weakness, the phenotype was linked with the muscle sodium channel gene (SCN4A) locus, in which a novel p.I141V mutation was found. This modification is located within the first transmembrane segment of domain I of the Na(v)1.4 alpha subunit, a region where no mutation has been reported so far. Patch clamp experiments revealed a mutation-induced hyperpolarizing shift (-12.9 mV) of the voltage dependence of activation, leading to a significant increase (approximately twofold) of the window current amplitude. In addition, the mutation shifted the voltage dependence of slow inactivation by -8.7 mV and accelerated the entry to this state. CONCLUSIONS: We propose that the gain-of-function alteration in activation leads to the observed myotonic phenotype, whereas the enhanced slow inactivation may prevent depolarization-induced paralysis.

Steady-state equilibrium phase inversion recovery ON-resonant water suppression (IRON) MR angiography in conjunction with superparamagnetic nanoparticles. A robust technique for imaging within a wide range of contrast agent dosages.

PURPOSE: To investigate the ability of inversion recovery ON-resonant water suppression (IRON) in conjunction with P904 (superparamagnetic nanoparticles which consisting of a maghemite core coated with a low-molecular-weight amino-alcohol derivative of glucose) to perform steady-state equilibrium phase MR angiography (MRA) over a wide dose range. MATERIALS AND METHODS: Experiments were approved by the institutional animal care committee. Rabbits (n = 12) were imaged at baseline and serially after the administration of 10 incremental dosages of 0.57-5.7 mgFe/Kg P904. Conventional T1-weighted and IRON MRA were obtained on a clinical 1.5 Tesla (T) scanner to image the thoracic and abdominal aorta, and peripheral vessels. Contrast-to-noise ratios (CNR) and vessel sharpness were quantified. RESULTS: Using IRON MRA, CNR and vessel sharpness progressively increased with incremental dosages of the contrast agent P904, exhibiting constantly higher contrast values than T1 -weighted MRA over a very wide range of contrast agent doses (CNR of 18.8 ± 5.6 for IRON versus 11.1 ± 2.8 for T1 -weighted MRA at 1.71 mgFe/kg, P = 0.02 and 19.8 ± 5.9 for IRON versus -0.8 ± 1.4 for T1-weighted MRA at 3.99 mgFe/kg, P = 0.0002). Similar results were obtained for vessel sharpness in peripheral vessels, (Vessel sharpness of 46.76 ± 6.48% for IRON versus 33.20 ± 3.53% for T1-weighted MRA at 1.71 mgFe/Kg, P = 0.002, and of 48.66 ± 5.50% for IRON versus 19.00 ± 7.41% for T1-weighted MRA at 3.99 mgFe/Kg, P = 0.003). CONCLUSION: Our study suggests that quantitative CNR and vessel sharpness after the injection of P904 are consistently higher for IRON MRA when compared with conventional T1-weighted MRA. These findings apply for a wide range of contrast agent dosages.

RF pulse concatenation for spatially selective inversion

It is shown that spatially selective inversion and saturation can be achieved by concatenation of RF pulses with lower flip angles. A concatenation rule which enables global doubling of the flip angle of any given excitation pulse applied to initial z magnetization is proposed. In this fashion, the selectivity of the single pulse is preserved, making the high selectivity achievable in the low flip-angle regime available for inversion and large flip-angle saturation purposes. The profile quality achievable with exemplary concatenated pulses is investigated in comparison with adiabatic inversion. It is verified that by using concatenated inversion in the transfer insensitive labeling technique (TILT), the MT artifact is suppressed. Copyright 2000 Academic Press.

Kitcher's Revolutionary Reasoning Inversion in Ethics

This paper examines three specific issues raised by The Ethical Project. First, I discuss the varieties of altruism and spell out the differences between the definitions proposed by Kitcher and the ways altruism is usually conceived in biology, philosophy, psychology, and economics literature. Second, with the example of Kitcher's account, I take a critical look at evolutionary stories of the emergence of human ethical practices. Third, I point to the revolutionary implications of the Darwinian methodology when it is thoughtfully applied to ethics.

Transcription factor CTF1 acts as a chromatin domain boundary that shields human telomeric genes from silencing.

Telomeres are associated with chromatin-mediated silencing of genes in their vicinity. However, how epigenetic markers mediate mammalian telomeric silencing and whether specific proteins may counteract this effect are not known. We evaluated the ability of CTF1, a DNA- and histone-binding transcription factor, to prevent transgene silencing at human telomeres. CTF1 was found to protect a gene from silencing when its DNA-binding sites were interposed between the gene and the telomeric extremity, while it did not affect a gene adjacent to the telomere. Protein fusions containing the CTF1 histone-binding domain displayed similar activities, while mutants impaired in their ability to interact with the histone did not. Chromatin immunoprecipitation indicated the propagation of a hypoacetylated histone structure to various extents depending on the telomere. The CTF1 fusion protein was found to recruit the H2A.Z histone variant at the telomeric locus and to restore high histone acetylation levels to the insulated telomeric transgene. Histone lysine trimethylations were also increased on the insulated transgene, indicating that these modifications may mediate expression rather than silencing at human telomeres. Overall, these results indicate that transcription factors can act to delimit chromatin domain boundaries at mammalian telomeres, thereby blocking the propagation of a silent chromatin structure.

p53-induced protein with a death domain (PIDD) isoforms differentially activate nuclear factor-kappaB and caspase-2 in response to genotoxic stress

Cells respond to DNA damage in a complex way and the fate of damaged cells depends on the balance between pro- and antiapoptotic signals. This is of crucial importance in cancer as genotoxic stress is implied both in oncogenesis and in classical tumor therapies. p53-induced protein with a death domain (PIDD), initially described as a p53-inducible gene, is one of the molecular switches able to activate a survival or apoptotic program. Two isoforms of PIDD, PIDD (isoform 1) and LRDD (isoform 2), have already been reported and we describe here a third isoform. These three isoforms are differentially expressed in tissues and cell lines. Genotoxic stress only affects PIDD isoform 3 mRNA levels, whereas isoforms 1 and 2 mRNA levels remain unchanged. All isoforms are capable of activating nuclear factor-kappaB in response to genotoxic stress, but only isoform 1 interacts with RIP-associated ICH-1/CED-3 homologous protein with a death domain and activates caspase-2. Isoform 2 counteracts the pro-apoptotic function of isoform 1, whereas isoform 3 enhances it. Thus, the differential splicing of PIDD mRNA leads to the formation of at least three proteins with antagonizing/agonizing functions, thereby regulating cell fate in response to DNA damage

Experimental cerebral malaria develops independently of caspase recruitment domain-containing protein 9 signaling.

The outcome of infection depends on multiple layers of immune regulation, with innate immunity playing a decisive role in shaping protection or pathogenic sequelae of acquired immunity. The contribution of pattern recognition receptors and adaptor molecules in immunity to malaria remains poorly understood. Here, we interrogate the role of the caspase recruitment domain-containing protein 9 (CARD9) signaling pathway in the development of experimental cerebral malaria (ECM) using the murine Plasmodium berghei ANKA infection model. CARD9 expression was upregulated in the brains of infected wild-type (WT) mice, suggesting a potential role for this pathway in ECM pathogenesis. However, P. berghei ANKA-infected Card9(-/-) mice succumbed to neurological signs and presented with disrupted blood-brain barriers similar to WT mice. Furthermore, consistent with the immunological features associated with ECM in WT mice, Card9(-/-) mice revealed (i) elevated levels of proinflammatory responses, (ii) high frequencies of activated T cells, and (iii) CD8(+) T cell arrest in the cerebral microvasculature. We conclude that ECM develops independently of the CARD9 signaling pathway.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

Identification of novel and cell type enriched cofactors of the transcription activation domain of RelA (p65 NF-kappaB).

RelA (NF-kappaB) is a transcription factor inducible by distinct stimuli in many different cell types. To find new cell type specific cofactors of NF-kappaB dependent transcription, we isolated RelA transcription activation domain binding proteins from the nuclear extracts of three different cell types. Analysis by electrophoresis and liquid chromatography tandem mass spectrometry identified several novel putative molecular partners. Some were strongly enriched in the complex formed from the nuclear extracts of specific cell types.

Mass conservative three-dimensional water tracer distribution from Markov chain Monte Carlo inversion of time-lapse ground-penetrating radar data

Time-lapse geophysical measurements are widely used to monitor the movement of water and solutes through the subsurface. Yet commonly used deterministic least squares inversions typically suffer from relatively poor mass recovery, spread overestimation, and limited ability to appropriately estimate nonlinear model uncertainty. We describe herein a novel inversion methodology designed to reconstruct the three-dimensional distribution of a tracer anomaly from geophysical data and provide consistent uncertainty estimates using Markov chain Monte Carlo simulation. Posterior sampling is made tractable by using a lower-dimensional model space related both to the Legendre moments of the plume and to predefined morphological constraints. Benchmark results using cross-hole ground-penetrating radar travel times measurements during two synthetic water tracer application experiments involving increasingly complex plume geometries show that the proposed method not only conserves mass but also provides better estimates of plume morphology and posterior model uncertainty than deterministic inversion results.

The role of MMP-9 and its fibronectin-like domain in tumor growth & invasion : certainties, controversies & discrepancies

Tumors are often compared to wounds that do not heal, where the crosstalk between tumor cells and their surrounding stroma is crucial at all stages of development, from the initial primary growth to metastasis. Similar to wound healing, fibroblasts in the tumor stroma differentiate into myofibroblasts, also referred to as "cancer-associated fibroblasts" (CAFs), primarily, but not exclusively, in response to transforming growth factor-ß (TGF-ß). Myofibroblasts in turn enhance tumor progression by remodeling the stroma. Among molecules implicated in stroma remodeling, matrix metalloproteinases (MMPs), and MMP-g in particular, play a prominent role. However, the mechanisms that regulate MMP-g activation and function remain poorly understood. Recent evidence indicates that tumor cell surface association of MMP-g is an important event in its activation, and more generally in tumor growth and invasion. In the present work we address the potential association of MMP-g activity with cell-surface recruitment to human fibroblasts. We show for the first time that recruitment of MMP-g to the MRC-5 fibroblast cell surface occurs through the fibronectin-like (FN) domain, shared only by MMP-g and MMP-2 among all the MMPs. Functional assays suggest that both the pro- and active form of MMP-g trigger a-smooth muscle actin (aSMA) expression in resting fibroblasts that reflects myofibroblast differentiation, possibly through TGF-ß activation. Moreover, the FN domain of MMP-g inhibits both MMP-g-induced TGF-ß activation and aSMA expression by sequestering MMP-g. Xenograft experiments in NOD/SCID mice using HT1080 fibrosarcoma or MDA-MD231 breast adenocarcinoma cells stably expressing the FN domain of MMP-g revealed no changes in primary tumor growth. However, in the context of metastasis, expression of the FN domain by these same tumor cells dramatically increased their metastatic proclivity whereas expression of wt MMP-g either promoted no change or actually reduced the number of metastases. We observed a decrease of an active form of MMP-g in MDA-MB231 cells overexpressing the FN domain suggesting that the FN domain may inhibit MMP-g activity in Tumors are often compared to wounds that do not heal, where the crosstalk between tumor cells and their surrounding stroma is crucial at all stages of development, from the initial primary growth to metastasis. Similar to wound healing, fibroblasts in the tumor stroma differentiate into myofibroblasts, also referred to as "cancer-associated fibroblasts" (CAFs), primarily, but not exclusively, in response to transforming growth factor-ß (TGF-ß). Myofibroblasts in turn enhance tumor progression by remodeling the stroma. Among molecules implicated in stroma remodeling, matrix metalloproteinases (MMPs), and MMP-g in particular, play a prominent role. However, the mechanisms that regulate MMP-g activation and function remain poorly understood. Recent evidence indicates that tumor cell surface association of MMP-g is an important event in its activation, and more generally in tumor growth and invasion. In the present work we address the potential association of MMP-g activity with cell-surface recruitment to human fibroblasts. We show for the first time that recruitment of MMP-g to the MRC-5 fibroblast cell surface occurs through the fibronectin-like (FN) domain, shared only by MMP-g and MMP-2 among all the MMPs. Functional assays suggest that both the pro- and active form of MMP-g trigger a-smooth muscle actin (aSMA) expression in resting fibroblasts that reflects myofibroblast differentiation, possibly through TGF-ß activation. Moreover, the FN domain of MMP-g inhibits both MMP-g-induced TGF-ß activation and aSMA expression by sequestering MMP-g. Xenograft experiments in NOD/SCID mice using HT1080 fibrosarcoma or MDA-MD231 breast adenocarcinoma cells stably expressing the FN domain of MMP-9 revealed no changes in primary tumor growth. However, in the context of metastasis, expression of the FN domain by these same tumor cells dramatically increased their metastatic proclivity whereas expression of wt MMP-g either promoted no change or actually reduced the number of metastases. We observed a decrease of an active form of MMP-9 in MDA-MB231 cells overexpressing the FN domain suggesting that the FN domain may inhibit MMP-9 activity in those cells and therefore prevent MMP-9-induced activation of TGF-b, which results in increased invasion. Curiously, xenografts of SW480 colorectal adenocarcinoma cells stably expressing the FN domain of MMP-9 displayed reduced growth at both the primary (subcutaneous) injection site and the lungs of NOD/SCID mice, in experimental metastasis assays, whilst the same cells overexpressing wt MMP-9 showed enhanced growth and dissemination. Gelatin zymography of conditioned medium revealed that these effects may be due to the FN domain, which displaces MMP-9 from SW480 cell surface. These observations suggest a dual role of MMP-9 and its FN domain in primary tumor growth and metastasis, underscoring the notion that the effect of MMP-9 on tumor cells may depend on the cell type and highlighting possible protective effects of MMPs in tumor progression.

Semantic domains and supersens tagging for domain-specific ontology learning

In this paper we propose a novel unsupervised approach to learning domain-specific ontologies from large open-domain text collections. The method is based on the joint exploitation of Semantic Domains and Super Sense Tagging for Information Retrieval tasks. Our approach is able to retrieve domain specific terms and concepts while associating them with a set of high level ontological types, named supersenses, providing flat ontologies characterized by very high accuracy and pertinence to the domain.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

c-Jun N-terminal kinase binding domain-dependent phosphorylation of mitogen-activated protein kinase kinase 4 and mitogen-activated protein kinase kinase 7 and balancing cross-talk between c-Jun N-terminal kinase and extracellular signal-regulated kinase pathways in cortical neurons

The c-Jun N-terminal kinase (JNK) is a mitogen-activated protein kinase (MAPK) activated by stress-signals and involved in many different diseases. Previous results proved the powerful effect of the cell permeable peptide inhibitor d-JNKI1 (d-retro-inverso form of c-Jun N-terminal kinase-inhibitor) against neuronal death in CNS diseases, but the precise features of this neuroprotection remain unclear. We here performed cell-free and in vitro experiments for a deeper characterization of d-JNKI1 features in physiological conditions. This peptide works by preventing JNK interaction with its c-Jun N-terminal kinase-binding domain (JBD) dependent targets. We here focused on the two JNK upstream MAPKKs, mitogen-activated protein kinase kinase 4 (MKK4) and mitogen-activated protein kinase kinase 7 (MKK7), because they contain a JBD homology domain. We proved that d-JNKI1 prevents MKK4 and MKK7 activity in cell-free and in vitro experiments: these MAPKK could be considered not only activators but also substrates of JNK. This means that d-JNKI1 can interrupt downstream but also upstream events along the JNK cascade, highlighting a new remarkable feature of this peptide. We also showed the lack of any direct effect of the peptide on p38, MEK1, and extracellular signal-regulated kinase (ERK) in cell free, while in rat primary cortical neurons JNK inhibition activates the MEK1-ERK-Ets1/c-Fos cascade. JNK inhibition induces a compensatory effect and leads to ERK activation via MEK1, resulting in an activation of the survival pathway-(MEK1/ERK) as a consequence of the death pathway-(JNK) inhibition. This study should hold as an important step to clarify the strong neuroprotective effect of d-JNKI1.