Histology-driven data mining of lipid signatures from multiple imaging mass spectrometry analyses: application to human colorectal cancer liver metastasis biopsies.

Imaging mass spectrometry (IMS) represents an innovative tool in the cancer research pipeline, which is increasingly being used in clinical and pharmaceutical applications. The unique properties of the technique, especially the amount of data generated, make the handling of data from multiple IMS acquisitions challenging. This work presents a histology-driven IMS approach aiming to identify discriminant lipid signatures from the simultaneous mining of IMS data sets from multiple samples. The feasibility of the developed workflow is evaluated on a set of three human colorectal cancer liver metastasis (CRCLM) tissue sections. Lipid IMS on tissue sections was performed using MALDI-TOF/TOF MS in both negative and positive ionization modes after 1,5-diaminonaphthalene matrix deposition by sublimation. The combination of both positive and negative acquisition results was performed during data mining to simplify the process and interrogate a larger lipidome into a single analysis. To reduce the complexity of the IMS data sets, a sub data set was generated by randomly selecting a fixed number of spectra from a histologically defined region of interest, resulting in a 10-fold data reduction. Principal component analysis confirmed that the molecular selectivity of the regions of interest is maintained after data reduction. Partial least-squares and heat map analyses demonstrated a selective signature of the CRCLM, revealing lipids that are significantly up- and down-regulated in the tumor region. This comprehensive approach is thus of interest for defining disease signatures directly from IMS data sets by the use of combinatory data mining, opening novel routes of investigation for addressing the demands of the clinical setting.

Cross-species and cross-platform gene expression studies with the Bioconductor-compliant R package 'annotationTools'.

Background: The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cross-species studies, in particular, have the power of identifying conserved, functionally important molecular processes. Validation of discoveries can now often be performed in readily available public data which frequently requires cross-platform studies.Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models ( e. g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles.Results: We provide annotationTools, a Bioconductor-compliant R package to annotate microarray experiments and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file databases. First, annotationTools contains a specialized set of functions for mining this widely used database format in a systematic manner. It thus offers a straightforward solution for annotating microarray experiments. Second, building on these basic functions and relying on the combination of information from several databases, it provides tools to easily perform cross-species analyses of gene expression data.Here, we present two example applications of annotationTools that are of direct relevance for the analysis of heterogeneous gene expression profiles, namely a cross-platform mapping of probes and a cross-species mapping of orthologous probes using different orthology databases. We also show how to perform an explorative comparison of disease-related transcriptional changes in human patients and in a genetic mouse model.Conclusion: The R package annotationTools provides a simple solution to handle microarray annotation and orthology tables, as well as other flat molecular biology databases. Thereby, it allows easy integration and analysis of heterogeneous microarray experiments across different technological platforms or species.

Biogeochemical evolution of a marine shore tailings deposit during bioremediation

Summary : Mining activities produce enormous amounts of waste material known as tailings which are composed of fine to medium size particles. These tailings often contain sulfides, which oxidation can lead to acid and metal contamination of water; therefore they need to be remediated. In this work a tailings bioremediation approach was investigated by an interdisciplinary study including geochemistry, mineralogy and microbiology. The aim of the work was to study the effect of the implementation of wetland above oxidizing tailings on the hydrogeology and the biogeochemical element cycles, and to assess the system evolution over time. To reach these goals, biogeochemical processes occurring in a marine shore tailings deposit were investigated. The studied tailings deposit is located at the Bahìa de Ite, Pacific Ocean, southern Peru, where between 1940 and 1996 the tailings were discharged from the two porphyry copper mines Cuajone and Toquepala. After the end of deposition, a remediation approach was initiated in 1997 with a wetland implementation above the oxidizing tailings. Around 90% of the tailings deposits (total 16 km2) were thus remediated, except the central delta area and some areas close to the shoreline. The multi-stable isotope study showed that the tailings were saturated with fresh water in spite of the marine setting, due to the high hydraulic gradient resulting from the wetland implementation. Submarine groundwater discharge (SGD) was the major source of SO4 2-, C1-, Na+, Fe2+, and Mn2+ input into the tailings at the original shelf-seawater interface. The geochemical study (aquatic geochemistry and X-Ray diffraction (XRD) and sequential extractions from the solid fraction) showed that iron and sulfur oxidation were the main processes in the non-remediated tailings, which showed a top a low-pH oxidation zone with strong accumulation of efflorescent salts at the surface due to capillary upward transport of heavy metals (Fe, Cu, Zn, Mn, Cd, Co, and Ni) in the arid climate. The study showed also that the implementation of the wetland resulted in very low concentrations of heavy metals in solution (mainly under the detection limit) due to the near neutral pH and more reducing conditions (100-150 mV). The heavy metals, which were taken from solution, precipitated as hydroxides and sulfides or were bound to organic matter. The bacterial community composition analysis by Terminal Restriction Fragment Length Polymorphism (T-RFLP) and cloning and sequencing of 16S rRNA genes combined with a detailed statistical analysis revealed a high correlation between the bacterial distribution and the geochemical variables. Acidophilic autotrophic oxidizing bacteria were dominating the oxidizing tailings, whereas neutrophilic and heterotrophic reducing bacteria were driving the biogeochemical processes in the remediated tailings below the wetland. At the subsurface of the remediated tailings, an iron cycling was highlighted with oxidation and reduction processes due to micro-aerophilic niches provided by the plant rhizosphere in this overall reducing environment. The in situ bioremediation experiment showed that the main parameter to take into account for the effectiveness was the water table and chemistry which controls the system. The constructed remediation cells were more efficient and rapid in metal removal when saturation conditions were available. This study showed that the bioremediation by wetland implementation could be an effective and rapid treatment for some sulfidic mine tailings deposits. However, the water saturation of the tailings has to be managed on a long-term basis in order to guarantee stability. Résumé : L'activité minière produit d'énormes quantités de déchets géologiques connus sous le nom de « tailings » composées de particules de taille fine à moyenne. Ces déchets contiennent souvent des sulfures dont l'oxydation conduit à la formation d'effluents acides contaminés en métaux, d'où la nécessité d'effectuer une remédiation des sites de stockage concernés. Le but de ce travail est dans un premier temps d'étudier l'effet de la bio-remédiation d'un dépôt de tailings oxydés sur l'hydrogéologie du système et les cycles biogéochimiques des éléments et en second lieu, d'évaluer l'évolution du processus de remédiation dans le temps. Le site étudié dans ce travail est situé dans la Bahía de Ite, au sud du Pérou, au bord de l'Océan Pacifique. Les déchets miniers en question sont déposés dans un environnement marin. De 1940 à 1996, les déchets de deux mines de porphyre cuprifère - Cuajone et Toquepala - ont été acheminés sur le site via la rivière Locumba. En 1997, une première remédiation a été initiée avec la construction d'une zone humide sur les tailings. Depuis, environ 90% de la surface du dépôt (16 km2) a été traité, les parties restantes étant la zone centrale du delta du Locumba et certaines zones proches de la plage. Malgré la proximité de l'océan, les études isotopiques menées dans le cadre de ce travail ont montré que les tailings étaient saturés en eau douce. Cette saturation est due à la pression hydraulique résultant de la mise en place des zones humides. Un écoulement d'eau souterrain sous-marin a été à détecté à l'interface entre les résidus et l'ancien fond marin. En raison de la géologie locale, il constitue une source d'entrée de SO4 2-, Cl-, Na+, FeZ+, et Mn2+ dans le système. L'analyse de la géochimie aquatique, la Diffraction aux Rayons X (XRD) et l'extraction séquentielle ont montré que l'oxydation du fer et .des sulfures est le principal processus se produisant dans les déchets non remédiés. Ceci a entraîné le développement d'une zone d'oxydation à pH bas induisant une forte accumulation des sels efflorescents, conséquence de la migration capillaire des métaux lourds (Fe, Cu, Zn, Mn, Cd, Co et Ni) de la solution vers la surface dans ce climat aride. Cette étude a montré également que la construction de la zone humide a eu comme résultats une précipitation des métaux dans des phases minérales en raison du pH neutre et des conditions réductrices (100-150mV). Les métaux lourds ont précipité sous la forme d'hydroxydes et de sulfures ou sont adsorbés à la matière organique. L'analyse de la composition de la communauté bactérienne à l'aide la technique T-RFLP (Terminal Restriction Fragment Length Polymorphism) et par le clonage/séquençage des gènes de l'ARNr 16S a été combinée à une statistique détaillée. Cette dernière a révélé une forte corrélation entre la distribution de bactéries spécifiques et la géochimie : Les bactéries autotrophes acidophiles dominent dans les déchets oxydés non remédiés, tandis que des bactéries hétérotrophes neutrophiles ont mené les processus microbiens dans les déchets remédiés sous la zone humide. Sous la surface de la zone humide, nos analyses ont également mis en évidence un cycle du fer par des processus d'oxydoréduction rendus possibles par la présence de niches micro-aérées par la rhizosphère dans cet environnement réducteur. L'expérience de bio-remédiation in situ a montré que les paramètres clés qui contrôlent l'efficacité du traitement sont le niveau de la nappe aquifère et la chimie de l'eau. Les cellules de remédiation se sont montrées plus efficaces et plus rapides lorsque le système a pu être saturé en eau. Finalement, cette étude a montré que la bio-remédiation de déchets miniers par la construction de zones humides est un moyen de traitement efficace, rapide et peu coûteux. Cependant, la saturation en eau du système doit être gérée sur le long terme afin de garantir la stabilité de l'ensemble du système.

Intégration de méthodes de data mining dans le renseignement criminel : analyse par des structures issues de la théorie des graphes dans le profilage des stupéfiants

Data mining can be defined as the extraction of previously unknown and potentially useful information from large datasets. The main principle is to devise computer programs that run through databases and automatically seek deterministic patterns. It is applied in different fields of application, e.g., remote sensing, biometry, speech recognition, but has seldom been applied to forensic case data. The intrinsic difficulty related to the use of such data lies in its heterogeneity, which comes from the many different sources of information. The aim of this study is to highlight potential uses of pattern recognition that would provide relevant results from a criminal intelligence point of view. The role of data mining within a global crime analysis methodology is to detect all types of structures in a dataset. Once filtered and interpreted, those structures can point to previously unseen criminal activities. The interpretation of patterns for intelligence purposes is the final stage of the process. It allows the researcher to validate the whole methodology and to refine each step if necessary. An application to cutting agents found in illicit drug seizures was performed. A combinatorial approach was done, using the presence and the absence of products. Methods coming from the graph theory field were used to extract patterns in data constituted by links between products and place and date of seizure. A data mining process completed using graphing techniques is called ``graph mining''. Patterns were detected that had to be interpreted and compared with preliminary knowledge to establish their relevancy. The illicit drug profiling process is actually an intelligence process that uses preliminary illicit drug classes to classify new samples. Methods proposed in this study could be used \textit{a priori} to compare structures from preliminary and post-detection patterns. This new knowledge of a repeated structure may provide valuable complementary information to profiling and become a source of intelligence.

Direct visualization of supercoiled DNA molecules in solution.

The shape of supercoiled DNA molecules in solution is directly visualized by cryo-electron microscopy of vitrified samples. We observe that: (i) supercoiled DNA molecules in solution adopt an interwound rather than a toroidal form, (ii) the diameter of the interwound superhelix changes from about 12 nm to 4 nm upon addition of magnesium salt to the solution and (iii) the partition of the linking deficit between twist and writhe can be quantitatively determined for individual molecules.

The development of a stable oral solution of captopril for paediatric patients

Study objectives: Many major drugs are not available in paediatric form. The aim of this study was to develop a stable liquid solution of captopril for oral paediatric use allowing individualised dosage and easy administration to newborn and young patients. Methods: A specific HPLC-UV method was developed. In a pilot study, a number of formulations described in the literature as affording one-month stability were examined. In the proper long-term study, the formulation that gave the best results was then prepared in large batches and its stability monitored for two years at 5°C and room temperature, and for one year at 40°C. Results: Most formulations described in the literature were found wanting in our pilot study. A simple solution of the drug (1 mg/mL) in purified water (European Pharmacopeia) containing 0.1% disodium edetate (EDTA-Na) as preservative proved chemically and microbiologically stable at 5°C and room temperature for two years. Conclusion: The proposed in-house formulation fulfils stringent criteria of purity and stability and is fully acceptable for oral administration to newborn and young patients.

The case for resequencing studies of Arabidopsis thaliana accessions: mining the dark matter of natural genetic variation.

Ultra-high-throughput sequencing (UHTS) techniques are evolving rapidly and may soon become an affordable and routine tool for sequencing plant DNA, even in smaller plant biology labs. Here we review recent insights into intraspecific genome variation gained from UHTS, which offers a glimpse of the rather unexpected levels of structural variability among Arabidopsis thaliana accessions. The challenges that will need to be addressed to efficiently assemble and exploit this information are also discussed.

Community Policing in Switzerland's Major Urban Areas: An Observational Study of the Implementation and Impact Using Geospatial Data Mining

La présente étude est à la fois une évaluation du processus de la mise en oeuvre et des impacts de la police de proximité dans les cinq plus grandes zones urbaines de Suisse - Bâle, Berne, Genève, Lausanne et Zurich. La police de proximité (community policing) est à la fois une philosophie et une stratégie organisationnelle qui favorise un partenariat renouvelé entre la police et les communautés locales dans le but de résoudre les problèmes relatifs à la sécurité et à l'ordre public. L'évaluation de processus a analysé des données relatives aux réformes internes de la police qui ont été obtenues par l'intermédiaire d'entretiens semi-structurés avec des administrateurs clés des cinq départements de police, ainsi que dans des documents écrits de la police et d'autres sources publiques. L'évaluation des impacts, quant à elle, s'est basée sur des variables contextuelles telles que des statistiques policières et des données de recensement, ainsi que sur des indicateurs d'impacts construit à partir des données du Swiss Crime Survey (SCS) relatives au sentiment d'insécurité, à la perception du désordre public et à la satisfaction de la population à l'égard de la police. Le SCS est un sondage régulier qui a permis d'interroger des habitants des cinq grandes zones urbaines à plusieurs reprises depuis le milieu des années 1980. L'évaluation de processus a abouti à un « Calendrier des activités » visant à créer des données de panel permettant de mesurer les progrès réalisés dans la mise en oeuvre de la police de proximité à l'aide d'une grille d'évaluation à six dimensions à des intervalles de cinq ans entre 1990 et 2010. L'évaluation des impacts, effectuée ex post facto, a utilisé un concept de recherche non-expérimental (observational design) dans le but d'analyser les impacts de différents modèles de police de proximité dans des zones comparables à travers les cinq villes étudiées. Les quartiers urbains, délimités par zone de code postal, ont ainsi été regroupés par l'intermédiaire d'une typologie réalisée à l'aide d'algorithmes d'apprentissage automatique (machine learning). Des algorithmes supervisés et non supervisés ont été utilisés sur les données à haute dimensionnalité relatives à la criminalité, à la structure socio-économique et démographique et au cadre bâti dans le but de regrouper les quartiers urbains les plus similaires dans des clusters. D'abord, les cartes auto-organisatrices (self-organizing maps) ont été utilisées dans le but de réduire la variance intra-cluster des variables contextuelles et de maximiser simultanément la variance inter-cluster des réponses au sondage. Ensuite, l'algorithme des forêts d'arbres décisionnels (random forests) a permis à la fois d'évaluer la pertinence de la typologie de quartier élaborée et de sélectionner les variables contextuelles clés afin de construire un modèle parcimonieux faisant un minimum d'erreurs de classification. Enfin, pour l'analyse des impacts, la méthode des appariements des coefficients de propension (propensity score matching) a été utilisée pour équilibrer les échantillons prétest-posttest en termes d'âge, de sexe et de niveau d'éducation des répondants au sein de chaque type de quartier ainsi identifié dans chacune des villes, avant d'effectuer un test statistique de la différence observée dans les indicateurs d'impacts. De plus, tous les résultats statistiquement significatifs ont été soumis à une analyse de sensibilité (sensitivity analysis) afin d'évaluer leur robustesse face à un biais potentiel dû à des covariables non observées. L'étude relève qu'au cours des quinze dernières années, les cinq services de police ont entamé des réformes majeures de leur organisation ainsi que de leurs stratégies opérationnelles et qu'ils ont noué des partenariats stratégiques afin de mettre en oeuvre la police de proximité. La typologie de quartier développée a abouti à une réduction de la variance intra-cluster des variables contextuelles et permet d'expliquer une partie significative de la variance inter-cluster des indicateurs d'impacts avant la mise en oeuvre du traitement. Ceci semble suggérer que les méthodes de géocomputation aident à équilibrer les covariables observées et donc à réduire les menaces relatives à la validité interne d'un concept de recherche non-expérimental. Enfin, l'analyse des impacts a révélé que le sentiment d'insécurité a diminué de manière significative pendant la période 2000-2005 dans les quartiers se trouvant à l'intérieur et autour des centres-villes de Berne et de Zurich. Ces améliorations sont assez robustes face à des biais dus à des covariables inobservées et covarient dans le temps et l'espace avec la mise en oeuvre de la police de proximité. L'hypothèse alternative envisageant que les diminutions observées dans le sentiment d'insécurité soient, partiellement, un résultat des interventions policières de proximité semble donc être aussi plausible que l'hypothèse nulle considérant l'absence absolue d'effet. Ceci, même si le concept de recherche non-expérimental mis en oeuvre ne peut pas complètement exclure la sélection et la régression à la moyenne comme explications alternatives. The current research project is both a process and impact evaluation of community policing in Switzerland's five major urban areas - Basel, Bern, Geneva, Lausanne, and Zurich. Community policing is both a philosophy and an organizational strategy that promotes a renewed partnership between the police and the community to solve problems of crime and disorder. The process evaluation data on police internal reforms were obtained through semi-structured interviews with key administrators from the five police departments as well as from police internal documents and additional public sources. The impact evaluation uses official crime records and census statistics as contextual variables as well as Swiss Crime Survey (SCS) data on fear of crime, perceptions of disorder, and public attitudes towards the police as outcome measures. The SCS is a standing survey instrument that has polled residents of the five urban areas repeatedly since the mid-1980s. The process evaluation produced a "Calendar of Action" to create panel data to measure community policing implementation progress over six evaluative dimensions in intervals of five years between 1990 and 2010. The impact evaluation, carried out ex post facto, uses an observational design that analyzes the impact of the different community policing models between matched comparison areas across the five cities. Using ZIP code districts as proxies for urban neighborhoods, geospatial data mining algorithms serve to develop a neighborhood typology in order to match the comparison areas. To this end, both unsupervised and supervised algorithms are used to analyze high-dimensional data on crime, the socio-economic and demographic structure, and the built environment in order to classify urban neighborhoods into clusters of similar type. In a first step, self-organizing maps serve as tools to develop a clustering algorithm that reduces the within-cluster variance in the contextual variables and simultaneously maximizes the between-cluster variance in survey responses. The random forests algorithm then serves to assess the appropriateness of the resulting neighborhood typology and to select the key contextual variables in order to build a parsimonious model that makes a minimum of classification errors. Finally, for the impact analysis, propensity score matching methods are used to match the survey respondents of the pretest and posttest samples on age, gender, and their level of education for each neighborhood type identified within each city, before conducting a statistical test of the observed difference in the outcome measures. Moreover, all significant results were subjected to a sensitivity analysis to assess the robustness of these findings in the face of potential bias due to some unobserved covariates. The study finds that over the last fifteen years, all five police departments have undertaken major reforms of their internal organization and operating strategies and forged strategic partnerships in order to implement community policing. The resulting neighborhood typology reduced the within-cluster variance of the contextual variables and accounted for a significant share of the between-cluster variance in the outcome measures prior to treatment, suggesting that geocomputational methods help to balance the observed covariates and hence to reduce threats to the internal validity of an observational design. Finally, the impact analysis revealed that fear of crime dropped significantly over the 2000-2005 period in the neighborhoods in and around the urban centers of Bern and Zurich. These improvements are fairly robust in the face of bias due to some unobserved covariate and covary temporally and spatially with the implementation of community policing. The alternative hypothesis that the observed reductions in fear of crime were at least in part a result of community policing interventions thus appears at least as plausible as the null hypothesis of absolutely no effect, even if the observational design cannot completely rule out selection and regression to the mean as alternative explanations.

Multi-well fungal co-culture for de novo metabolite-induction in time-series studies based on untargeted metabolomics.

The induction of fungal metabolites by fungal co-cultures grown on solid media was explored using multi-well co-cultures in 2 cm diameter Petri dishes. Fungi were grown in 12-well plates to easily and rapidly obtain the large number of replicates necessary for employing metabolomic approaches. Fungal culture using such a format accelerated the production of metabolites by several weeks compared with using the large-format 9 cm Petri dishes. This strategy was applied to a co-culture of a Fusarium and an Aspergillus strain. The metabolite composition of the cultures was assessed using ultra-high pressure liquid chromatography coupled to electrospray ionisation and time-of-flight mass spectrometry, followed by automated data mining. The de novo production of metabolites was dramatically increased by nutriment reduction. A time-series study of the induction of the fungal metabolites of interest over nine days revealed that they exhibited various induction patterns. The concentrations of most of the de novo induced metabolites increased over time. However, interesting patterns were observed, such as with the presence of some compounds only at certain time points. This result indicates the complexity and dynamic nature of fungal metabolism. The large-scale production of the compounds of interest was verified by co-culture in 15 cm Petri dishes; most of the induced metabolites of interest (16/18) were found to be produced as effectively as on a small scale, although not in the same time frames. Large-scale production is a practical solution for the future production, identification and biological evaluation of these metabolites.