Are invasive marsh frogs (Pelophylax ridibundus) replacing the native P. lessonae /P. esculentus hybridogenetic complex in Western Europe? Genetic evidence from a field study.

The water-frog L-E system, widespread in Western Europe, comprises the pool frog Pelophylax lessonae and the hybridogenetic edible frog P. esculentus, which originated from hybridization between pool frogs and marsh frogs (P. ridibundus). In P. esculentus, the lessonae (L) genome is eliminated during meiosis and has to be gained anew each generation from a P. lessonae partner, while the ridibundus (R') genome is transmitted clonally. It therefore accumulates deleterious mutations, so that R'R' offspring from P. esculentus x P. esculentus crosses are normally unviable. This system is now threatened by invasive P. ridibundus (RR) imported from Eastern Europe and the Balkans. We investigated the genetic interactions between invasive marsh frogs and native water frogs in a Swiss wetland area, and used genetic data collected in the field to validate several components of a recently postulated mechanism of species replacement. We identified neo-ridibundus individuals derived from crosses between invasive ridibundus and native esculentus, as well as newly arisen hybridogenetic esculentus lineages stemming from crosses between invasive ridibundus (RR) and native lessonae (LL). As their ridibundus genomes are likely to carry less deleterious mutations, such lineages are expected to produce viable ridibundus offspring, contributing to species replacement. However, such crosses with invasive ridibundus only occurred at a limited scale; moreover, RR x LL crosses did not induce any introgression from the ridibundus to the lessonae genome. We did not find any ridibundus stemming from crosses between ancient esculentus lineages. Despite several decades of presence on the site, introduced ridibundus individuals only represent 15% of sampled frogs, and their spatial distribution seems shaped by specific ecological requirements rather than history of colonization. We therefore expect the three taxa to coexist stably in this area.

Gain of function mutations in CgPDR1 of Candida glabrata not only mediate antifungal resistance but also enhance virulence.

CgPdr1p is a Candida glabrata Zn(2)-Cys(6) transcription factor involved in the regulation of the ABC-transporter genes CgCDR1, CgCDR2, and CgSNQ2, which are mediators of azole resistance. Single-point mutations in CgPDR1 are known to increase the expression of at least CgCDR1 and CgCDR2 and thus to contribute to azole resistance of clinical isolates. In this study, we investigated the incidence of CgPDR1 mutations in a large collection of clinical isolates and tested their relevance, not only to azole resistance in vitro and in vivo, but also to virulence. The comparison of CgPDR1 alleles from azole-susceptible and azole-resistant matched isolates enabled the identification of 57 amino acid substitutions, each positioned in distinct CgPDR1 alleles. These substitutions, which could be grouped into three different "hot spots," were gain of function (GOF) mutations since they conferred hyperactivity to CgPdr1p revealed by constitutive high expression of ABC-transporter genes. Interestingly, the major transporters involved in azole resistance (CgCDR1, CgCDR2, and CgSNQ2) were not always coordinately expressed in presence of specific CgPDR1 GOF mutations, thus suggesting that these are rather trans-acting elements (GOF in CgPDR1) than cis-acting elements (promoters) that lead to azole resistance by upregulating specific combinations of ABC-transporter genes. Moreover, C. glabrata isolates complemented with CgPDR1 hyperactive alleles were not only more virulent in mice than those with wild type alleles, but they also gained fitness in the same animal model. The presence of CgPDR1 hyperactive alleles also contributed to fluconazole treatment failure in the mouse model. In conclusion, this study shows for the first time that CgPDR1 mutations are not only responsible for in vitro/in vivo azole resistance but that they can also confer a selective advantage under host conditions.

Calibration of high-resolution geophysical data with tracer test measurements to improve hydrological predictions

Relationships between porosity and hydraulic conductivity tend to be strongly scale- and site-dependent and are thus very difficult to establish. As a result, hydraulic conductivity distributions inferred from geophysically derived porosity models must be calibrated using some measurement of aquifer response. This type of calibration is potentially very valuable as it may allow for transport predictions within the considered hydrological unit at locations where only geophysical measurements are available, thus reducing the number of well tests required and thereby the costs of management and remediation. Here, we explore this concept through a series of numerical experiments. Considering the case of porosity characterization in saturated heterogeneous aquifers using crosshole ground-penetrating radar and borehole porosity log data, we use tracer test measurements to calibrate a relationship between porosity and hydraulic conductivity that allows the best prediction of the observed hydrological behavior. To examine the validity and effectiveness of the obtained relationship, we examine its performance at alternate locations not used in the calibration procedure. Our results indicate that this methodology allows us to obtain remarkably reliable hydrological predictions throughout the considered hydrological unit based on the geophysical data only. This was also found to be the case when significant uncertainty was considered in the underlying relationship between porosity and hydraulic conductivity.

Analysis of viral- and tumor antigen-specific CD4 T cell responses in healthy donors and melanoma patients

Résumé Des tentatives pour développer des traitements anti-cancéreux basés sur l'utilisation d'antigènes tumoraux ont commencé il y a plus de 10 ans. Depuis quelques années, un certain intérêt s'est portée sur une sous-population particulière des cellules du système immunitaire, les lymphocytes T CD4. Ces cellules jouent un rôle central dans les réponses immunitaires tant contre les virus que contre les cellules tumorales. Comme d'autres lymphocytes T, ces cellules sont activées de manière spécifique en reconnaissant un morceau d'antigène, appelé peptide. Ces peptides proviennent soit de protéines des cellules de l'hôte, soit des protéines étrangères (virus ou bactéries) soit de cellules transformées (cellules tumorales) et sont présentés aux lymphocytes T par des molécules du soi appelées CMH (complexe majeur d'histocompatibilité). Dans le cas des lymphocytes T CD4, ces molécules sont plus précisément des molécules du CMH de classe II (CMH II). Mis à part l'intérêt porté aux réponses médiées par les lymphocytes T cytotoxiques, un intérêt croissant pour les lymphocytes T CD4 s'est développé à cause de la place centrale qu'occupent ces cellules dans les réponses immunitaires. L'identification d'épitopes présentés par des molécules du CMH de classe II dérivés d'un grand nombre d'antigènes tumoraux, ainsi que le développement de techniques permettant de suivre les réponses immunitaires, offre des opportunités pour étudier de manière quantitative et qualitative les lymphocytes T CD4 spécifiques pour un antigène particulier chez des patients cancéreux. De plus, ces épitopes permettent d'induire des réponses médiées par les lymphocytes T CD4 et CD8 chez ces mêmes patients. Dans ce travail, notre premier but était de valider l'utilisation de multimères formés par des complexes peptide:molécules de CMH de class II (pCMH II) pour quantifier la réponse des cellules T CD4 dirigée contre l'épitope HA307-319 dérivé de la protéine hémaglutinine du virus de la grippe et présenté par HLA-DRB1*0401. En analysant des échantillons provenant de volontaires sains ayant reçus un vaccin contre la grippe, nous avons pu démontrer une expansion et une activation transitoires des lymphocytes T CD4 spécifiques pour le peptide HA307-319 après vaccination. De plus, les multimères pCMH II nous ont permis d'analyser plus en détails hétérogénéité des cellules T CD4 spécifiques pour le peptide HA307-319 présents dans le sang périphérique d'individus sains. Par la suite, notre but a été d'analyser les réponses des lymphocytes T CD4 spécifiques pour l'antigène Melan-A chez des patients atteints de mélanome métastatique. Nous avons tout d'abord démontré la présence de cellules T CD4 spécifiques pour l'épitope Melan-A51-73, présenté par HLA-DRBl*0401, qui avait déjà été préalablement décrit. Ensuite, nous avons décrit et caractérisé 2 nouveaux peptides issus de Melan-A qui sont présentés aux cellules T CD4 par différentes molécules du CMH de clans II. Des cellules spécifiques pour ces deux épitopes ont été trouvées chez 9/ 16 patients analysés. De plus, des multimères pCMH II chargés avec un des épitopes nous ont permis de détecter ex vivo des lymphocytes T CD4 spécifiques pour Melan-A dans le sang périphérique d'un patient atteint de mélanome. Mis ensemble, tous ces résultats suggèrent une potentielle utilisation des multimères pCMH II pour analyser en détail les lymphocytes T CD4 spécifiques d'antigènes définis. Cependant, le suivi ex vivo de telles cellules ne semble être possible que dans des cas bien particuliers. Néanmoins, les nouveaux épitopes issus de Melan-A et présentés par des molécules du CMH de classe II que nous avons décrits dans cette étude aideront à étudier plus en détails les lymphocytes T CD4 spécifiques pour Melan-A chez des patients atteints de mélanome, un sujet d'étude sur lequel peu de résultats sont à ce jour disponibles. Summary Attempts to develop cancer vaccines based on molecularly defined tumorassociated antigens were initiated more than 10 years ago. Apart from CTLmediated anti-tumor immunity, interests are. now focused on CD4 T cells that are central players of immune responses. The identification of MHC class-II-restricted epitopes from numerous tumor antigens together with the development of monitoring tools offers the opportunity to quantitatively and qualitatively study antigen-specific CD4 T lymphocytes in cancer patients and to induce both CTL and T helper responses in cancer patients. In this work, we first aimed at validating the use of peptide:MHC class II complex (pMHC II) multimers to quantitate the CD4 T cell response against the hemagglutinin-derived epitope HAso~-si9 from influenza virus presented by HLA-DRBl*0401. By analysing samples from healthy volunteers vaccinated with ananti-influenza vaccine, we could demonstrate a transient expansion and activation of HA-specific CD4 T cells after treatment. Moreover, pMHC II multimers helped us to study the heterogeneity of HAspecific CD4 T cells found in peripheral blood of healthy individuals. Then, we aimed to analyse Melan-A-specific CD4 T cell responses in metastatic melanoma patients. We first demonstrated the presence of CD4 T cells specific for the previously described Melan-A51_73 epitope presented by HLA-DRB 1 *0401 in peripheral blood of those patients. Second, we described and characterised 2 new Melan-A-derived peptides that are presented by different MHC II molecules to CD4 T cells. Specific cells for these epitopes were found in 9/ 16 rnelánoma patients analysed. In addition, pMHC II multimers loaded with one of the two epitopes allowed us to detect ex vivo Melan-A-specific CD4 T cells in peripheral blood of a melanoma patient. Together, these results suggest a potential use of pMHC II multimers in analysing in detail antigen-specific CD4 T cells. However, ex vivo monitoring of such cells will be possible only in particular conditions. Nevertheless, the new Melan-A-derived MHC II-restricted epitopes described here will help to study in more detail Melan-A-specific CD4 T cells in melanoma patients, a field where only scarce data are available.

A filtering method to correct time-lapse 3D ERT data and improve imaging of natural aquifer dynamics

We have developed a processing methodology that allows crosshole ERT (electrical resistivity tomography) monitoring data to be used to derive temporal fluctuations of groundwater electrical resistivity and thereby characterize the dynamics of groundwater in a gravel aquifer as it is infiltrated by river water. Temporal variations of the raw ERT apparent-resistivity data were mainly sensitive to the resistivity (salinity), temperature and height of the groundwater, with the relative contributions of these effects depending on the time and the electrode configuration. To resolve the changes in groundwater resistivity, we first expressed fluctuations of temperature-detrended apparent-resistivity data as linear superpositions of (i) time series of riverwater-resistivity variations convolved with suitable filter functions and (ii) linear and quadratic representations of river-water-height variations multiplied by appropriate sensitivity factors; river-water height was determined to be a reliable proxy for groundwater height. Individual filter functions and sensitivity factors were obtained for each electrode configuration via deconvolution using a one month calibration period and then the predicted contributions related to changes in water height were removed prior to inversion of the temperature-detrended apparent-resistivity data. Applications of the filter functions and sensitivity factors accurately predicted the apparent-resistivity variations (the correlation coefficient was 0.98). Furthermore, the filtered ERT monitoring data and resultant time-lapse resistivity models correlated closely with independently measured groundwater electrical resistivity monitoring data and only weakly with the groundwater-height fluctuations. The inversion results based on the filtered ERT data also showed significantly less inversion artefacts than the raw data inversions. We observed resistivity increases of up to 10% and the arrival time peaks in the time-lapse resistivity models matched those in the groundwater resistivity monitoring data.

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.

Establishment of the epithelial-specific transcriptome of normal and malignant human breast cells based on MPSS and array expression data.

INTRODUCTION: Diverse microarray and sequencing technologies have been widely used to characterise the molecular changes in malignant epithelial cells in breast cancers. Such gene expression studies to identify markers and targets in tumour cells are, however, compromised by the cellular heterogeneity of solid breast tumours and by the lack of appropriate counterparts representing normal breast epithelial cells. METHODS: Malignant neoplastic epithelial cells from primary breast cancers and luminal and myoepithelial cells isolated from normal human breast tissue were isolated by immunomagnetic separation methods. Pools of RNA from highly enriched preparations of these cell types were subjected to expression profiling using massively parallel signature sequencing (MPSS) and four different genome wide microarray platforms. Functional related transcripts of the differential tumour epithelial transcriptome were used for gene set enrichment analysis to identify enrichment of luminal and myoepithelial type genes. Clinical pathological validation of a small number of genes was performed on tissue microarrays. RESULTS: MPSS identified 6,553 differentially expressed genes between the pool of normal luminal cells and that of primary tumours substantially enriched for epithelial cells, of which 98% were represented and 60% were confirmed by microarray profiling. Significant expression level changes between these two samples detected only by microarray technology were shown by 4,149 transcripts, resulting in a combined differential tumour epithelial transcriptome of 8,051 genes. Microarray gene signatures identified a comprehensive list of 907 and 955 transcripts whose expression differed between luminal epithelial cells and myoepithelial cells, respectively. Functional annotation and gene set enrichment analysis highlighted a group of genes related to skeletal development that were associated with the myoepithelial/basal cells and upregulated in the tumour sample. One of the most highly overexpressed genes in this category, that encoding periostin, was analysed immunohistochemically on breast cancer tissue microarrays and its expression in neoplastic cells correlated with poor outcome in a cohort of poor prognosis estrogen receptor-positive tumours. CONCLUSION: Using highly enriched cell populations in combination with multiplatform gene expression profiling studies, a comprehensive analysis of molecular changes between the normal and malignant breast tissue was established. This study provides a basis for the identification of novel and potentially important targets for diagnosis, prognosis and therapy in breast cancer.

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.

Outcome and Prognostic Factors in Adenosquamous Carcinoma of the Head and Neck: A Multicenter Rare Cancer Network Study

Purpose/Objective(s): Adenosquamous carcinoma (AC) of the head and neck is a distinct entity first described in 1968. Its natural history is more aggressive than squamous cell carcinoma but this is based on very small series reported in the literature. The goal of this study was to assess the clinical profile, outcome, patterns of failure and prognostic factors in patients with AC of the head and neck treated by radiation therapy (RT) with or without chemotherapy (CT).Materials/Methods: Data from 18 patients with Stage I (n = 3), II (n = 1), III (n = 4), or IVa (n = 10) AC, treated between 1989 and 2009, were collected in a retrospective multicenter Rare Cancer Network study. Median age was 60 years (range, 48 - 73 years). Fourteen patients were male and 4 female. Risk factors, including perineural invasion, lymphangitis, vascular invasion, positive margins, were present in 83% of the patients. Tumor sites included oral cavity in 4, oropharynx in 4, hypopharynx in2, larynx in 2, salivary glands in 2, nasal vestibule in 2, nasopharynx in 1, and maxillary sinus in 1 patient. Surgery (S) was performed in all but 5 patients. S alone was performed in only 1 patient, and definitive RT alone in 3 patients. Fourteen patients received combined modality treatment (S+RT in 10, RT+CT in 2, and all of the three modalities in 2 patients). Median RT dose to the primary and to the nodes was 66 Gy (range, 50 - 72 Gy) and 53 Gy (range, 44 - 66 Gy), respectively (1.8 - 2.0 Gy/fr., 5 fr./ week). In 4 patients, the planning treatment volume included the primary tumor site only. Seven patients were treated with 2D RT, 7 with 3D conformal RT, and 2 with intensity-modulated RT.Results: After a median follow-up period of 38 months (range, 9 - 62 months), 8 patients developed distant metastases (lung, bone, mediastinum, and liver), 6 presented nodal recurrences, and only 4 had a local relapse at the primary site (all in-field recurrences). At last follow-up, 6 patients were alive without disease, 1 alive with disease, 9 died from progressive disease, and 2 died from intercurrent disease. The 3-year and median overall survival, disease-free survival (DFS) and locoregional control rates were 52% (95% confidence interval [CI]: 28 - 76%) and 39 months, 36% (95% CI: 13 - 49%) and 12 months, and 54% (95% CI: 26 - 82%) and 40 months, respectively. In multivariate analysis (Cox model), DFS was negatively influenced by the presence of extracapsular extension (p = 0.02) and advanced stage (IV versus I-III, p = 0.003).Conclusions: Overall prognosis of locoregionally advanced AC remains poor, and distant metastases and nodal relapse occur in almost half of the cases. However, local control is relatively good, and early stage AC patients had prolonged DFS when treated with combined modality treatment.

Inhibition of estrogen-responsive gene activation by the retinoid X receptor beta: evidence for multiple inhibitory pathways.

The retinoid X receptor beta (RXR beta; H-2RIIBP) forms heterodimers with various nuclear hormone receptors and binds multiple hormone response elements, including the estrogen response element (ERE). In this report, we show that endogenous RXR beta contributes to ERE binding activity in nuclear extracts of the human breast cancer cell line MCF-7. To define a possible regulatory role of RXR beta regarding estrogen-responsive transcription in breast cancer cells, RXR beta and a reporter gene driven by the vitellogenin A2 ERE were transfected into estrogen-treated MCF-7 cells. RXR beta inhibited ERE-driven reporter activity in a dose-dependent and element-specific fashion. This inhibition occurred in the absence of the RXR ligand 9-cis retinoic acid. The RXR beta-induced inhibition was specific for estrogen receptor (ER)-mediated ERE activation because inhibition was observed in ER-negative MDA-MB-231 cells only following transfection of the estrogen-activated ER. No inhibition of the basal reporter activity was observed. The inhibition was not caused by simple competition of RXR beta with the ER for ERE binding, since deletion mutants retaining DNA binding activity but lacking the N-terminal or C-terminal domain failed to inhibit reporter activity. In addition, cross-linking studies indicated the presence of an auxiliary nuclear factor present in MCF-7 cells that contributed to RXR beta binding of the ERE. Studies using known heterodimerization partners of RXR beta confirmed that RXR beta/triiodothyronine receptor alpha heterodimers avidly bind the ERE but revealed the existence of another triiodothyronine-independent pathway of ERE inhibition. These results indicate that estrogen-responsive genes may be negatively regulated by RXR beta through two distinct pathways.

Forensic intelligence for medicine anti-counterfeiting

Medicine counterfeiting is a crime that has increased in recent years and now involves the whole world. Health and economic repercussions have led pharmaceutical industries and agencies to develop many measures to protect genuine medicines and differentiate them from counterfeits. Detecting counterfeit is chemically relatively simple for the specialists, but much more information can be gained from the analyses in a forensic intelligence perspective. Analytical data can feed criminal investigation and law enforcement by detecting and understanding the criminal phenomenon. Profiling seizures using chemical and packaging data constitutes a strong way to detect organised production and industrialised forms of criminality, and is the focus of this paper. Thirty-three seizures of a commonly counterfeited type of capsule have been studied. The results of the packaging and chemical analyses were gathered within an organised database. Strong linkage was found between the seizures at the different production steps, indicating the presence of a main counterfeit network dominating the market. The interpretation of the links with circumstantial data provided information about the production and the distribution of counterfeits coming from this network. This forensic intelligence perspective has the potential to be generalised to other types of products. This may be the only reliable approach to help the understanding of the organised crime phenomenon behind counterfeiting and to enable efficient strategic and operational decision making in an attempt to dismantle counterfeit network.

Variation in the level of aggression, chemical and genetic distance among three supercolonies of the Argentine ant in Europe.

In their invasive ranges, Argentine ant populations often form one geographically vast supercolony, genetically and chemically uniform within which there is no intraspecific aggression. Here we present regional patterns of intraspecific aggression, cuticular hydrocarbons (CHCs) and population genetics of 18 nesting sites across Corsica and the French mainland. Aggression tests confirm the presence of a third European supercolony, the Corsican supercolony, which exhibits moderate to high levels of aggression, depending on nesting sites, with the Main supercolony, and invariably high levels of aggression with the Catalonian supercolony. The chemical analyses corroborated the behavioural data, with workers of the Corsican supercolony showing moderate differences in CHCs compared to workers of the European Main supercolony and strong differences compared to workers of the Catalonian supercolony. Interestingly, there were also clear genetic differences between workers of the Catalonian supercolony and the two other supercolonies at both nuclear and mitochondrial markers, but only very weak genetic differentiation between nesting sites of the Corsican and Main supercolonies (F(ST) = 0.06). A detailed comparison of the genetic composition of supercolonies also revealed that, if one of the last two supercolonies derived from the other, it is the Main supercolony that derived from the Corsican supercolony rather than the reverse. Overall, these findings highlight the importance of conducting more qualitative and quantitative analyses of the level of aggression between supercolonies, which has to be correlated with genetic and chemical data.

Integration of ground-penetrating radar and microgravimetric methods to map shallow caves

Ground-penetrating radar (GPR) and microgravimetric surveys have been conducted in the southern Jura mountains of western Switzerland in order to map subsurface karstic features. The study site, La Grande Rolaz cave, is an extensive system in which many portions have been mapped. By using small station spacing and careful processing for the geophysical data, and by modeling these data with topographic information from within the cave, accurate interpretations have been achieved. The constraints on the interpreted geologic models are better when combining the geophysical methods than when using only one of the methods, despite the general limitations of two-dimensional (2D) profiling. For example, microgravimetry can complement GPR methods for accurately delineating a shallow cave section approximately 10 X 10 mt in size. Conversely, GPR methods can be complementary in determining cavity depths and in verifying the presence of off-line features and numerous areas of small cavities and fractures, which may be difficult to resolve in microgravimetric data.

Association between white-coat effect and blunted dipping of nocturnal blood pressure.

In this study, we assessed whether the white-coat effect (difference between office and daytime blood pressure (BP)) is associated with nondipping (absence of BP decrease at night). Data were available in 371 individuals of African descent from 74 families selected from a population-based hypertension register in the Seychelles Islands and in 295 Caucasian individuals randomly selected from a population-based study in Switzerland. We used standard multiple linear regression in the Swiss data and generalized estimating equations to account for familial correlations in the Seychelles data. The prevalence of systolic and diastolic nondipping (<10% nocturnal BP decrease) and white-coat hypertension (WCH) was respectively 51, 46, and 4% in blacks and 33, 37, and 7% in whites. When white coat effect and nocturnal dipping were taken as continuous variables (mm Hg), systolic (SBP) and diastolic BP (DBP) dipping were associated inversely and independently with white-coat effect (P < 0.05) in both populations. Analogously, the difference between office and daytime heart rate was inversely associated with the difference between daytime and night-time heart rate in the two populations. These results did not change after adjustment for potential confounders. The white-coat effect is associated with BP nondipping. The similar associations between office-daytime values and daytime-night-time values for both BP and heart rate suggest that the sympathetic nervous system might play a role. Our findings also further stress the interest, for clinicians, of assessing the presence of a white-coat effect as a means to further identify patients at increased cardiovascular risk and guide treatment accordingly.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.