Quorum-sensing-negative (lasR) mutants of Pseudomonas aeruginosa avoid cell lysis and death.

In Pseudomonas aeruginosa, N-acylhomoserine lactone signals regulate the expression of several hundreds of genes, via the transcriptional regulator LasR and, in part, also via the subordinate regulator RhlR. This regulatory network termed quorum sensing contributes to the virulence of P. aeruginosa as a pathogen. The fact that two supposed PAO1 wild-type strains from strain collections were found to be defective for LasR function because of independent point mutations in the lasR gene led to the hypothesis that loss of quorum sensing might confer a selective advantage on P. aeruginosa under certain environmental conditions. A convenient plate assay for LasR function was devised, based on the observation that lasR mutants did not grow on adenosine as the sole carbon source because a key degradative enzyme, nucleoside hydrolase (Nuh), is positively controlled by LasR. The wild-type PAO1 and lasR mutants showed similar growth rates when incubated in nutrient yeast broth at pH 6.8 and 37 degrees C with good aeration. However, after termination of growth during 30 to 54 h of incubation, when the pH rose to > or = 9, the lasR mutants were significantly more resistant to cell lysis and death than was the wild type. As a consequence, the lasR mutant-to-wild-type ratio increased about 10-fold in mixed cultures incubated for 54 h. In a PAO1 culture, five consecutive cycles of 48 h of incubation sufficed to enrich for about 10% of spontaneous mutants with a Nuh(-) phenotype, and five of these mutants, which were functionally complemented by lasR(+), had mutations in lasR. The observation that, in buffered nutrient yeast broth, the wild type and lasR mutants exhibited similar low tendencies to undergo cell lysis and death suggests that alkaline stress may be a critical factor providing a selective survival advantage to lasR mutants.

Combination therapy with venlafaxine and carbamazepine in depressive patients not responding to venlafaxine: pharmacokinetic and clinical aspects.

The chiral antidepressant venlafaxine (VEN) is both a serotonin and a norepinephrine uptake inhibitor. CYP2D6 and CYP3A4 contribute to its metabolism, which has been shown to be stereoselective. Ten CYP2D6 genotyped and depressive (F32x and F33x, ICD-10) patients participated in an open study on the pharmacokinetic and pharmacodynamic consequences of a carbamazepine augmentation in VEN non-responders. After an initial 4-week treatment with VEN (195 +/- 52 mg/day), the only poor metabolizer out of 10 depressive patients had the highest plasma concentrations of S-VEN and R-VEN, respectively, whereas those of R-O-demethyl-VEN were lowest. Five non-responders completed the second 4-week study period, during which they were submitted to a combined VEN-carbamazepine treatment. In the only non-responder to this combined treatment, there was a dramatic decrease of both enantiomers of VEN, O-demethylvenlafaxine, N-desmethylvenlafaxine and N, O-didesmethylvenlafaxine in plasma, which suggests non-compliance, although metabolic induction by carbamazepine cannot entirely be excluded. The administration of carbamazepine [mean +/- SD, range: 360 +/- 89 (200-400) mg/day] over 4 weeks did not result in a significant modification of the plasma concentrations of the enantiomers of VEN and its O- and N-demethylated metabolites in the other patients. In conclusion, these preliminary observations suggest that the combination of VEN and carbamazepine represents an interesting augmentation strategy by its efficacy, tolerance and absence of pharmacokinetic modifications. However, these findings should be verified in a more comprehensive study.

Genome-wide meta-analysis for serum calcium identifies significantly associated SNPs near the calcium-sensing receptor (CASR) gene.

Calcium has a pivotal role in biological functions, and serum calcium levels have been associated with numerous disorders of bone and mineral metabolism, as well as with cardiovascular mortality. Here we report results from a genome-wide association study of serum calcium, integrating data from four independent cohorts including a total of 12,865 individuals of European and Indian Asian descent. Our meta-analysis shows that serum calcium is associated with SNPs in or near the calcium-sensing receptor (CASR) gene on 3q13. The top hit with a p-value of 6.3 x 10(-37) is rs1801725, a missense variant, explaining 1.26% of the variance in serum calcium. This SNP had the strongest association in individuals of European descent, while for individuals of Indian Asian descent the top hit was rs17251221 (p = 1.1 x 10(-21)), a SNP in strong linkage disequilibrium with rs1801725. The strongest locus in CASR was shown to replicate in an independent Icelandic cohort of 4,126 individuals (p = 1.02 x 10(-4)). This genome-wide meta-analysis shows that common CASR variants modulate serum calcium levels in the adult general population, which confirms previous results in some candidate gene studies of the CASR locus. This study highlights the key role of CASR in calcium regulation.

Combination therapy with venlafaxine and carbamazepine in depressive patients non-responding to venlafaxine : pharmacokinetic and clinical aspects

Résumé L'antidépresseur chiral venlafaxine (VEN) est à la fois un inhibiteur de la récapture de la sérotonine et de la noradrénaline. Le CYP2D6 et le CYP3A4 contribuent à son métabolisme stéreosélectif. Dix patients génotypés au CYP2D6 et dépressifs (F32x et F33x, ICD-10) ont participé à cette étude ouverte sur les conséquences pharmacocinétiques et pharmacodynamiques d'une « augmentation » avec la carbamazepine chez des non-répondeurs à la venlafaxine. Après une première période de traitement de quatre semaines avec VEN (195 - 52 mg/ jour), le seul patient qui présentait un déficience génétique de CYP2D6 (poor metaboliser), avait les taux plasmatiques de S-VEN et R-VEN les plus élevés, tandis que ceux de R-0-déméthyl-VEN étaient les plus bas dans ce groupe. Comme seulement 4 patients ont été des répondeurs après 4 semaines de traitement, 6 patients ont été inclus dans la deuxième période de traitement combiné VEN et carbamazépine. Cinq patients non-répondeurs ont complété cette deuxième période d'étude de quatre semaines. Chez l'unique non-répondeur au traitement combiné, on pouvait observer à la fin de la période d'étude une diminution importante des deux énantiomères de VEN, 0-desmethy'lvenlafaxine (ODV), N-desmethylvenlafaxine (NDV) et N, 0-didesmethylvenlafaxine (NODV) dans le plasma. Cela suggère un manque de compliance chez ce patient, mais une induction métabolique par la carbamazepine ne peut pas être exclue entièrement. L'administration de la carbamazepine (moyen ± s.d. (range) ; 360 ± 89 (200-400) mg/jour)) pendant quatre semaines n'a pas eu comme résultat une modification significative des concentrations plasmatiques des énantiomères de VEN et de ses métabolites 0- et N-démethylés chez les autres patients. En conclusion, ces observations préliminaires suggèrent qu'une combinaison de VEN et de carbamazepine représente une stratégie intéressante par son efficacité, sa tolérance et l'absence de modifications pharmcocinétiques, mais ces résultats devraient être vérifiés dans une plus grande étude.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

ROLES OF ACID-SENSING ION CHANNELS (ASICS) IN PERIPHERAL NEUROPEPTIDE SECRETION AND PAIN

Acid-sensing ion channels (ASICs) are non-voltage-gated sodium channels activated by an extracellular acidification. They are widely expressed in neurons of the central and peripheral nervous system. ASICs have a role in learning, the expression of fear, in neuronal death after cerebral ischemia, and in pain sensation. Tissue damage leads to the release of inflammatory mediators. There is a subpopulation of sensory neurons which are able to release the neuropeptides calcitonin gene-related peptide (CGRP) and substance P (SP). Neurogenic inflammation refers to the process whereby peripheral release of the neuropeptides CGRP and SP induces vasodilation and extravasation of plasma proteins, respectively. Our laboratory has previously shown that calcium-permeable homomeric ASIC1a channels are present in a majority of CGRP- or SP-expressing small diameter sensory neurons. In the first part of my thesis, we tested the hypothesis that a local acidification can produce an ASIC-mediated calcium-dependant neuropeptide secretion. We have first verified the co-expression of ASICs and CGRP/SP using immunochemistry and in-situ hybridization on dissociated rat dorsal root ganglion (DRG) neurons. We found that most CGRP/SP-positive neurons also expressed ASIC1a and ASIC3 subunits. Calcium imaging experiments with Fura-2 dye showed that an extracellular acidification can induce an increase of intracellular Ca2+ concentration, which is essential for secretion. This increase of intracellular Ca2+ concentration is, at least in some cells, ASIC-dependent, as it can be prevented by amiloride, an ASIC antagonist, and by Psalmotoxin (PcTx1), a specific ASIC1a antagonist. We identified a sub-population of neurons whose acid-induced Ca2+ entry was completely abolished by amiloride, an amiloride-resistant population which does not express ASICs, but rather another acid-sensing channel, possibly transient receptor potential vanilloïde 1 (TRPV1), and a population expressing both H+-gated channel types. Voltage-gated calcium channels (Cavs) may also mediate Ca2+ entry. Co-application of the Cavs inhibitors (ω-conotoxin MVIIC, Mibefradil and Nifedipine) reduced the Ca2+ increase in neurons expressing ASICs during an acidification to pH 6. This indicates that ASICs can depolarise the neuron and activate Cavs. Homomeric ASIC1a are Ca2+-permeable and allow a direct entry of Ca2+ into the cell; other ASICs mediate an indirect entry of Ca2+ by inducing a membrane depolarisation that activates Cavs. We showed with a secretion assay that CGRP secretion can be induced by extracellular acidification in cultured rat DRG neurons. Amiloride and PcTx1 were not able to inhibit the secretion at acidic pH, but BCTC, a TRPV1 inhibitor was able to decrease the secretion induced by an extracellular acidification in our in vitro secretion assay. In conclusion, these results show that in DRG neurons a mild extracellular acidification can induce a calcium-dependent neuropeptide secretion. Even if our data show that ASICs can mediate an increase of intracellular Ca2+ concentration, this appears not to be sufficient to trigger neuropeptide secretion. TRPV1, a calcium channel whose activation induces a sustained current - in contrary of ASICs - played in our experimental conditions a predominant role in neurosecretion. In the second part of my thesis, we focused on the role of ASICs in neuropathic pain. We used the spared nerve injury (SNI) model which consists in a nerve injury that induces symptoms of neuropathic pain such as mechanical allodynia. We have previously shown that the SNI model modifies ASIC currents in dissociated rat DRG neurons. We hypothesized that ASICs could play a role in the development of mechanical allodynia. The SNI model was performed on ASIC1a, -2, and -3 knock-out mice and wild type littermates. We measured mechanical allodynia on these mice with calibrated von Frey filaments. There were no differences between the wild-type and the ASIC1, or ASIC2 knockout mice. ASIC3 null mice were less sensitive than wild type mice at 21 day after SNI, indicating a role for ASIC3. Finally, to investigate other possible roles of ASICs in the perception of the environment, we measured the baseline heat responses. We used two different models; the tail flick model and the hot plate model. ASIC1a null mice showed increased thermal allodynia behaviour in the hot plate test at three different temperatures (49, 52, 55°C) compared to their wild type littermates. On the contrary, ASIC2 null mice showed reduced thermal allodynia behaviour in the hot plate test compared to their wild type littermates at the three same temperatures. We conclude that ASIC1a and ASIC2 in mice can play a role in temperature sensing. It is currently not understood how ASICs are involved in temperature sensing and what the reason for the opposed effects in the two knockout models is.

Caspase-3 and RasGAP: a stress-sensing survival/demise switch.

The final decision on cell fate, survival versus cell death, relies on complex and tightly regulated checkpoint mechanisms. The caspase-3 protease is a predominant player in the execution of apoptosis. However, recent progress has shown that this protease paradoxically can also protect cells from death. Here, we discuss the underappreciated, protective, and prosurvival role of caspase-3 and detail the evidence showing that caspase-3, through differential processing of p120 Ras GTPase-activating protein (RasGAP), can modulate a given set of proteins to generate, depending on the intensity of the input signals, opposite outcomes (survival vs death).

Brain glucose sensing, counterregulation, and energy homeostasis.

Neuronal circuits in the central nervous system play a critical role in orchestrating the control of glucose and energy homeostasis. Glucose, beside being a nutrient, is also a signal detected by several glucose-sensing units that are located at different anatomical sites and converge to the hypothalamus to cooperate with leptin and insulin in controlling the melanocortin pathway.

Temperature-responsive sensing regulates biocontrol factor expression in Pseudomonas fluorescens CHA0.

In the plant-beneficial, root-colonizing strain Pseudomonas fluorescens CHA0, the Gac/Rsm signal transduction pathway positively regulates the synthesis of biocontrol factors (mostly antifungal secondary metabolites) and contributes to oxidative stress response via the stress sigma factor RpoS. The backbone of this pathway consists of the GacS/GacA two-component system, which activates the expression of three small regulatory RNAs (RsmX, RsmY, RsmZ) and thereby counters translational repression exerted by the RsmA and RsmE proteins on target mRNAs encoding biocontrol factors. We found that the expression of typical biocontrol factors, that is, antibiotic compounds and hydrogen cyanide (involving the phlA and hcnA genes), was significantly lower at 35 degrees C than at 30 degrees C. The expression of the rpoS gene was affected in parallel. This temperature control depended on RetS, a sensor kinase acting as an antagonist of the GacS/GacA system. An additional sensor kinase, LadS, which activated the GacS/GacA system, apparently did not contribute to thermosensitivity. Mutations in gacS or gacA were epistatic to (that is, they overruled) mutations in retS or ladS for expression of the small RNAs RsmXYZ. These data are consistent with a model according to which RetS-GacS and LadS-GacS interactions shape the output of the Gac/Rsm pathway and the environmental temperature influences the RetS-GacS interaction in P. fluorescens CHA0.

New insight on bio-sensing by nano-fabricated memristors

We report here on a new insight for bio- sensing based on the memristive effect of functional- ized Schottky-barrier memristive silicon nanowire in dry environment. The device concept is discussed. Elec- trical measurements confirm the bio-detection by the narrowing of the memristive Ids − Vds hysteresis upon interaction of antigen with antibody-functionalized nanowire.

Sensing of mammalian IL-17A regulates fungal adaptation and virulence.

Infections by opportunistic fungi have traditionally been viewed as the gross result of a pathogenic automatism, which makes a weakened host more vulnerable to microbial insults. However, fungal sensing of a host's immune environment might render this process more elaborate than previously appreciated. Here we show that interleukin (IL)-17A binds fungal cells, thus tackling both sides of the host-pathogen interaction in experimental settings of host colonization and/or chronic infection. Global transcriptional profiling reveals that IL-17A induces artificial nutrient starvation conditions in Candida albicans, resulting in a downregulation of the target of rapamycin signalling pathway and in an increase in autophagic responses and intracellular cAMP. The augmented adhesion and filamentous growth, also observed with Aspergillus fumigatus, eventually translates into enhanced biofilm formation and resistance to local antifungal defenses. This might exemplify a mechanism whereby fungi have evolved a means of sensing host immunity to ensure their own persistence in an immunologically dynamic environment.

Chemical sensing in Drosophila.

Chemical sensing begins when peripheral receptor proteins recognise specific environmental stimuli and translate them into spatial and temporal patterns of sensory neuron activity. The chemosensory system of the fruit fly, Drosophila melanogaster, has become a dominant model to understand this process, through its accessibility to a powerful combination of molecular, genetic and electrophysiological analysis. Recent results have revealed many surprises in the biology of peripheral chemosensation in Drosophila, including novel structural and signalling properties of the insect odorant receptors (ORs), combinatorial mechanisms of chemical recognition by the gustatory receptors (GRs), and the implication of Transient Receptor Potential (TRP) ion channels as a novel class of chemosensory receptors.

Role of MyD88 and Toll-like receptors 2 and 4 in the sensing of Parachlamydia acanthamoebae.

Parachlamydia acanthamoebae is a Chlamydia-related organism whose pathogenic role in pneumonia is supported by serological and molecular clinical studies and an experimental mouse model of lung infection. Toll-like receptors (TLRs) play a seminal role in sensing microbial products and initiating innate immune responses. The aim of this study was to investigate the roles of MyD88, TLR2, and TLR4 in the interaction of Parachlamydia with macrophages. Here, we showed that Parachlamydia entered bone-marrow derived macrophages (BMDMs) in a TLR-independent manner but did not multiply intracellularly. Interestingly, compared to live bacteria, heat-inactivated Parachlamydia induced the production of substantial amounts of tumor necrosis factor alpha (TNF), interleukin-6 (IL-6), and IL-12p40 by BMDMs and of TNF and IL-6 by peritoneal macrophages as well as RAW 264.7 and J774 macrophage cell lines. Cytokine production by BMDMs, which was partially inhibited upon trypsin treatment of Parachlamydia, was dependent on MyD88, TLR4, and, to a lesser extent, TLR2. Finally, MyD88(-/-), TLR4(-/-), and TLR2(-/-) mice were as resistant as wild-type mice to lung infection following the intratracheal instillation of Parachlamydia. Thus, in contrast to Chlamydia pneumoniae, Parachlamydia acanthamoebae weakly stimulates macrophages, potentially compensating for its low replication capacity in macrophages by escaping the innate immune surveillance.