Detachment of cell surface-bound anticarcinoembryonic antigen immune complexes by phospholipase C.

CEA as well as normal cross-reacting antigens (NCA) are fixed to the cell membrane via phosphatidylinositol (PI). To find out whether these antigens are internalized after antibody contact, acid pH desorption was compared to phospholipase C (PLC)-mediated cleavage of the antigen anchor. With the former procedure, marked differences in the desorbability of individual MAbs were noted, while PLC was able to cleave off surface-bound immune complexes irrespective of the MAb involved. From this it is concluded that internalization of MAb complexes of CEA/NCA, if occurring at all, is a low efficiency process.

Publicizing insecurity, privatizing security: Chinese wholesalers' surveillance cameras in a Paris suburb

Since the early nineties, several hundreds of Chinese immigrants have settled in what has become known as the 'Chinese wholesalers area'. For the past two years, Chinese wholesalers in Aubervilliers have been calling on public authorities to address the problem of street robberies and violent thefts, which they experience on a daily basis. Yet, they have been encouraged by the authorities to ensure their own protection, by - amongst other things - installing surveillance cameras to film the streets. This is illegal according to French legislation on camera surveillance. Knowing this, why have surveillance cameras been adopted as a solution? This question guides the ethnographic analysis presented here of a situation where the installation of surveillance cameras was locally negotiated by the main actors involved - namely, the wholesalers' representatives and the police.

Real-time imaging of regional myocardial function using fast-SENC.

A technique for fast imaging of regional myocardial function using a spiral acquisition in combination with strain-encoded (SENC) magnetic resonance imaging (MRI) is presented in this paper. This technique, which is termed fast-SENC, enables scan durations as short as a single heartbeat. A reduced field of view (FOV) without foldover artifacts was achieved by localized SENC, which selectively excited the region around the heart. The two images required for SENC imaging (low- and high-tuning) were acquired in an interleaved fashion throughout the cardiac cycle to further shorten the scan time. Regional circumferential contraction and longitudinal shortening of both the left ventricle (LV) and right ventricle (RV) were examined in long- and short-axis views, respectively. The in vivo results obtained from five human subjects and five infarcted dogs are presented. The results of the fast-SENC technique in a single heartbeat acquisition were comparable to those obtained by conventional SENC in a long acquisition time. Therefore, fast-SENC may prove useful for imaging during stress or arrhythmia.

Preliminary regional rockfall hazard mapping using LIDAR-based slope frequency distribution and CONEFALL modeling

A factor limiting preliminary rockfall hazard mapping at regional scale is often the lack of knowledge of potential source areas. Nowadays, high resolution topographic data (LiDAR) can account for realistic landscape details even at large scale. With such fine-scale morphological variability, quantitative geomorphometric analyses become a relevant approach for delineating potential rockfall instabilities. Using digital elevation model (DEM)-based ?slope families? concept over areas of similar lithology and cliffs and screes zones available from the 1:25,000 topographic map, a susceptibility rockfall hazard map was drawn up in the canton of Vaud, Switzerland, in order to provide a relevant hazard overview. Slope surfaces over morphometrically-defined thresholds angles were considered as rockfall source zones. 3D modelling (CONEFALL) was then applied on each of the estimated source zones in order to assess the maximum runout length. Comparison with known events and other rockfall hazard assessments are in good agreement, showing that it is possible to assess rockfall activities over large areas from DEM-based parameters and topographical elements.

Sawhorse-type diruthenium tetracarbonyl complexes containing porphyrin-derived ligands as highly selective photosensitizers for female reproductive cancer cells.

Diruthenium tetracarbonyl complexes of the type [Ru2(CO)4(l2-g2-O2CR)2L2] containing a Ru-Ru backbone with four equatorial carbonyl ligands, two carboxylato bridges, and two axial two-electron ligands in a sawhorse-like geometry have been synthesized with porphyrin-derived substituents in the axial ligands [1: R is CH3, L is 5-(4-pyridyl)-10,15,20-triphenyl-21,23H-porphyrin], in the bridging carboxylato ligands [2: RCO2H is 5-(4-carboxyphenyl)-10,15,20-triphenyl-21,23H-porphyrin, L is PPh3; 3: RCO2H is 5-(4-carboxyphenyl)-10,15,20-triphenyl-21,23H-porphyrin, L is 1,3,5-triaza-7-phosphatricyclo [3.3.1.1]decane], or in both positions [4: RCO2H is 5-(4-carboxyphenyl)-10,15,20-triphenyl-21,23H-porphyrin, L is 5-(4-pyridyl)-10,15,20-triphenyl-21,23H-porphyrin]. Compounds 1-3 were assessed on different types of human cancer cells and normal cells. Their uptake by cells was quantified by fluorescence and checked by fluorescence microscopy. These compounds were taken up by human HeLa cervix and A2780 and Ovcar ovarian carcinoma cells but not by normal cells and other cancer cell lines (A549 pulmonary, Me300 melanoma, PC3 and LnCap prostate, KB head and neck, MDAMB231 and MCF7 breast, or HT29 colon cancer cells). The compounds demonstrated no cytotoxicity in the absence of laser irradiation but exhibited good phototoxicities in HeLa and A2780 cells when exposed to laser light at 652 nm, displaying an LD50 between 1.5 and 6.5 J/cm2 in these two cell lines and more than 15 J/cm2 for the others. Thus, these types of porphyric compound present specificity for cancer cell lines of the female reproductive system and not for normal cells; thus being promising new organometallic photosensitizers.

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.