Multivariate spectroscopic methods for the analysis of solutions

In this thesis some multivariate spectroscopic methods for the analysis of solutions are proposed. Spectroscopy and multivariate data analysis form a powerful combination for obtaining both quantitative and qualitative information and it is shown how spectroscopic techniques in combination with chemometric data evaluation can be used to obtain rapid, simple and efficient analytical methods. These spectroscopic methods consisting of spectroscopic analysis, a high level of automation and chemometric data evaluation can lead to analytical methods with a high analytical capacity, and for these methods, the term high-capacity analysis (HCA) is suggested. It is further shown how chemometric evaluation of the multivariate data in chromatographic analyses decreases the need for baseline separation. The thesis is based on six papers and the chemometric tools used are experimental design, principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), partial least squares regression (PLS) and parallel factor analysis (PARAFAC). The analytical techniques utilised are scanning ultraviolet-visible (UV-Vis) spectroscopy, diode array detection (DAD) used in non-column chromatographic diode array UV spectroscopy, high-performance liquid chromatography with diode array detection (HPLC-DAD) and fluorescence spectroscopy. The methods proposed are exemplified in the analysis of pharmaceutical solutions and serum proteins. In Paper I a method is proposed for the determination of the content and identity of the active compound in pharmaceutical solutions by means of UV-Vis spectroscopy, orthogonal signal correction and multivariate calibration with PLS and SIMCA classification. Paper II proposes a new method for the rapid determination of pharmaceutical solutions by the use of non-column chromatographic diode array UV spectroscopy, i.e. a conventional HPLC-DAD system without any chromatographic column connected. In Paper III an investigation is made of the ability of a control sample, of known content and identity to diagnose and correct errors in multivariate predictions something that together with use of multivariate residuals can make it possible to use the same calibration model over time. In Paper IV a method is proposed for simultaneous determination of serum proteins with fluorescence spectroscopy and multivariate calibration. Paper V proposes a method for the determination of chromatographic peak purity by means of PCA of HPLC-DAD data. In Paper VI PARAFAC is applied for the decomposition of DAD data of some partially separated peaks into the pure chromatographic, spectral and concentration profiles.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

Perceptual maps analysis for organic food consumers in China: a study on Shanghai consumers

Although in Europe and in the USA many studies focus on organic, little is known on the topic in China. This research provides an insight on Shanghai consumers’ perception of organic, aiming at understanding and representing in graphic form the network of mental associations that stems from the organic concept. To acquire, process and aggregate the individual networks it was used the “Brand concept mapping” methodology (Roedder et al., 2006), while the data analysis was carried out also using analytic procedures. The results achieved suggest that organic food is perceived as healthy, safe and costly. Although these attributes are pretty much consistent with the European perception, some relevant differences emerged. First, organic is not necessarily synonymous with natural product in China, also due to a poor translation of the term in the Chinese language that conveys the idea of a manufactured product. Secondly, the organic label has to deal with the competition with the green food label in terms of image and positioning on the market, since they are easily associated and often confused. “Environmental protection” also emerged as relevant association, while the ethical and social values were not mentioned. In conclusion, health care and security concerns are the factors that influence most the food consumption in China (many people are so concerned about food safety that they found it difficult to shop), and the associations “Safe”, “Pure and natural”, “without chemicals” and “healthy” have been identified as the best candidates for leveraging a sound image of organic food .

Il linguaggio degli ambienti virtuali culturali: comunicare la storia di Bologna attraverso il progetto Nu.M.E.

The contemporary media landscape is characterized by the emergence of hybrid forms of digital communication that contribute to the ongoing redefinition of our societies cultural context. An incontrovertible consequence of this phenomenon is the new public dimension that characterizes the transmission of historical knowledge in the twenty-first century. Awareness of this new epistemic scenario has led us to reflect on the following methodological questions: what strategies should be created to establish a communication system, based on new technology, that is scientifically rigorous, but at the same time engaging for the visitors of museums and Internet users? How does a comparative analysis of ancient documentary sources form a solid base of information for the virtual reconstruction of thirteenth century Bologna in the Metaverse? What benefits can the phenomenon of cross-mediality give to the virtual heritage? The implementation of a new version of the Nu.M.E. project allowed for answering many of these instances. The investigation carried out between 2008 and 2010 has shown that, indeed, real-time 3D graphics and collaborative virtual environments can be feasible tools for representing philologically the urban medieval landscape and for communicating properly validated historical data to the general public. This research is focused on the study and implementation of a pipeline that permits mass communication of historical information about an area of vital importance in late medieval Bologna: Piazza di Porta Ravegnana. The originality of the developed project is not limited solely to the methodological dimension of historical research. Adopted technological perspective is an excellent example of innovation that digital technologies can bring to the cultural heritage. The main result of this research is the creation of Nu.ME 2010, a cross-media system of 3D real-time visualization based on some of the most advanced free software and open source technologies available today free of charge.

Pyrolysis-Gas Chromatography-Mass Spectometry and Chemometric Analysis for the Characterization of Complex Matrices

The present PhD thesis was focused on the development and application of chemical methodology (Py-GC-MS) and data-processing method by multivariate data analysis (chemometrics). The chromatographic and mass spectrometric data obtained with this technique are particularly suitable to be interpreted by chemometric methods such as PCA (Principal Component Analysis) as regards data exploration and SIMCA (Soft Independent Models of Class Analogy) for the classification. As a first approach, some issues related to the field of cultural heritage were discussed with a particular attention to the differentiation of binders used in pictorial field. A marker of egg tempera the phosphoric acid esterified, a pyrolysis product of lecithin, was determined using HMDS (hexamethyldisilazane) rather than the TMAH (tetramethylammonium hydroxide) as a derivatizing reagent. The validity of analytical pyrolysis as tool to characterize and classify different types of bacteria was verified. The FAMEs chromatographic profiles represent an important tool for the bacterial identification. Because of the complexity of the chromatograms, it was possible to characterize the bacteria only according to their genus, while the differentiation at the species level has been achieved by means of chemometric analysis. To perform this study, normalized areas peaks relevant to fatty acids were taken into account. Chemometric methods were applied to experimental datasets. The obtained results demonstrate the effectiveness of analytical pyrolysis and chemometric analysis for the rapid characterization of bacterial species. Application to a samples of bacterial (Pseudomonas Mendocina), fungal (Pleorotus ostreatus) and mixed- biofilms was also performed. A comparison with the chromatographic profiles established the possibility to: • Differentiate the bacterial and fungal biofilms according to the (FAMEs) profile. • Characterize the fungal biofilm by means the typical pattern of pyrolytic fragments derived from saccharides present in the cell wall. • Individuate the markers of bacterial and fungal biofilm in the same mixed-biofilm sample.

Patterns of regional differentiation in post-Soviet Russia

This doctoral thesis aims at contributing to the literature on transition economies focusing on the Russian Federations and in particular on regional income convergence and fertility patterns. The first two chapter deal with the issue of income convergence across regions. Chapter 1 provides an historical-institutional analysis of the period between the late years of the Soviet Union and the last decade of economic growth and a presentation of the sample with a description of gross regional product composition, agrarian or industrial vocation, labor. Chapter 2 contributes to the literature on exploratory spatial data analysis with a application to a panel of 77 regions in the period 1994-2008. It provides an analysis of spatial patterns and it extends the theoretical framework of growth regressions controlling for spatial correlation and heterogeneity. Chapter 3 analyses the national demographic patterns since 1960 and provides a review of the policies on maternity leave and family benefits. Data sources are the Statistical Yearbooks of USSR, the Statistical Yearbooks of the Russian Soviet Federative Socialist Republic and the Demographic Yearbooks of Russia. Chapter 4 analyses the demographic patterns in light of the theoretical framework of the Becker model, the Second Demographic Transition and an economic-crisis argument. With national data from 1960, the theoretically issue of the pro or countercyclical relation between income and fertility is graphically analyzed and discussed, together with female employment and education. With regional data after 1994 different panel data models are tested. Individual level data from the Russian Longitudinal Monitoring Survey are employed using the logit model. Chapter 5 employs data from the Generations and Gender Survey by UNECE to focus on postponement and second births intentions. Postponement is studied through cohort analysis of mean maternal age at first birth, while the methodology used for second birth intentions is the ordered logit model.

Hydrogeochemical characterization of Seehausen territory - Bremen

The aim of this thesis is to provide a geochemical characterization of the Seehausen territory (a neighborhood) of Bremen, Germany. In this territory it is hosted a landfill of dredged sediments coming both from Bremerhaven (North See) and Bremen harbor (directly on the river Weser). For this reason this work has been focused also on possible impacts of the landfill on the groundwaters (shallow and deep aquifer). The Seehausen landfill uses the dewatering technique to manage the dredged sediments: incoming sediments are put into dewatering fields until they are completely dried (it takes almost a year). Then they are randomly sampled and analyzed: if the pollutants content is acceptable, sediments are treated with other materials and used instead of raw material for embankment, bricks, etc., otherwise they are disposed in the landfill. During this work it has been made a study of the natural geology and hydrogeology of the whole area of interest, especially because it is characterized by ancient natural salt deposits. Then, together with the Geological Survey of Bremen and the Harbor Authority of Bremen there have been identified all useful piezometers for a monitoring net around the landfill. During the sampling campaign there have been collected data of the principal anions and cations, physical parameters and stable water isotopes. Data analysis has been focused particularly on Cl, Na, SO4 and EC because these parameters might be helpful to attribute geochemical trends to the landfill or to a natural background. Furthermore dataloggers have been installed for a month in some piezometers and EC, pressure, dissolved oxygen and temperature data have been collected. Finally there has been made a deep comparison between current and historical data (1996 – 2011) and between old interpolation maps and current ones in order to see time trends of the aquifer geochemistry.

Essays on geography and diseases

This dissertation explores how diseases contributed to shape historical institutions and how health and diseases are still affecting modern comparative development. The overarching goal of this investigation is to identify the channels linking geographic suitability to diseases and the emergence of historical and modern insitutions, while tackling the endogenenity problems that traditionally undermine this literature. I attempt to do so by taking advantage of the vast amount of newly available historical data and of the richness of data accessible through the geographic information system (GIS). The first chapter of my thesis, 'Side Effects of Immunities: The African Slave Trade', proposes and test a novel explanation for the origins of slavery in the tropical regions of the Americas. I argue that Africans were especially attractive for employment in tropical areas because they were immune to many of the diseases that were ravaging those regions. In particular, Africans' resistance to malaria increased the profitability of slaves coming from the most malarial parts of Africa. In the second chapter of my thesis, 'Caste Systems and Technology in Pre-Modern Societies', I advance and test the hypothesis that caste systems, generally viewed as a hindrance to social mobility and development, had been comparatively advantageous at an early stage of economic development. In the third chapter, 'Malaria as Determinant of Modern Ethnolinguistic Diversity', I conjecture that in highly malarious areas the necessity to adapt and develop immunities specific to the local disease environment historically reduced mobility and increased isolation, thus leading to the formation of a higher number of different ethnolinguistic groups. In the final chapter, 'Malaria Risk and Civil Violence: A Disaggregated Analysis for Africa', I explore the relationship between malaria and violent conflicts. Using georeferenced data for Africa, the article shows that violent events are more frequent in areas where malaria risk is higher.

Stock boundaries of Parapenaeus longirostris (Lucas, 1846) populations in the Italian seas: Development of genomic 2b-RAD markers and biological variation analysis.

This thesis is developed in the contest of Ritmare project WP1, which main objective is the development of a sustainable fishery through the identification of populations boundaries in commercially important species in Italian Seas. Three main objectives are discussed in order to help reach the main purpose of identification of stock boundaries in Parapenaeus longirostris: 1 -Development of a representative sampling design for Italian seas; 2 -Evaluation of 2b-RAD protocol; 3 -Investigation of populations through biological data analysis. First of all we defined and accomplished a sampling design which properly represents all Italian seas. Then we used information and data about nursery areas distribution, abundance of populations and importance of P. longirostris in local fishery, to develop an experimental design that prioritize the most important areas to maximize the results with actual project funds. We introduced for the first time the use of 2b-RAD on this species, a genotyping method based on sequencing the uniform fragments produced by type IIB restriction endonucleases. Thanks to this method we were able to move from genetics to the more complex genomics. In order to proceed with 2b-RAD we performed several tests to identify the best DNA extraction kit and protocol and finally we were able to extract 192 high quality DNA extracts ready to be processed. We tested 2b-RAD with five samples and after high-throughput sequencing of libraries we used the software “Stacks” to analyze the sequences. We obtained positive results identifying a great number of SNP markers among the five samples. To guarantee a multidisciplinary approach we used the biological data associated to the collected samples to investigate differences between geographical samples. Such approach assures continuity with other project, for instance STOCKMED, which utilize a combination of molecular and biological analysis as well.

Towards the 3D attenuation imaging of active volcanoes: methods and tests on real and simulated data

The purpose of my PhD thesis has been to face the issue of retrieving a three dimensional attenuation model in volcanic areas. To this purpose, I first elaborated a robust strategy for the analysis of seismic data. This was done by performing several synthetic tests to assess the applicability of spectral ratio method to our purposes. The results of the tests allowed us to conclude that: 1) spectral ratio method gives reliable differential attenuation (dt*) measurements in smooth velocity models; 2) short signal time window has to be chosen to perform spectral analysis; 3) the frequency range over which to compute spectral ratios greatly affects dt* measurements. Furthermore, a refined approach for the application of spectral ratio method has been developed and tested. Through this procedure, the effects caused by heterogeneities of propagation medium on the seismic signals may be removed. The tested data analysis technique was applied to the real active seismic SERAPIS database. It provided a dataset of dt* measurements which was used to obtain a three dimensional attenuation model of the shallowest part of Campi Flegrei caldera. Then, a linearized, iterative, damped attenuation tomography technique has been tested and applied to the selected dataset. The tomography, with a resolution of 0.5 km in the horizontal directions and 0.25 km in the vertical direction, allowed to image important features in the off-shore part of Campi Flegrei caldera. High QP bodies are immersed in a high attenuation body (Qp=30). The latter is well correlated with low Vp and high Vp/Vs values and it is interpreted as a saturated marine and volcanic sediments layer. High Qp anomalies, instead, are interpreted as the effects either of cooled lava bodies or of a CO2 reservoir. A pseudo-circular high Qp anomaly was detected and interpreted as the buried rim of NYT caldera.

Ancient Greek harbours used as geo-archives for palaeotsunami research : case studies from Krane (Cefalonia), Lechaion (Gulf of Corinth) and Kyllini (Peloponnese)

Since historical times, coastal areas throughout the eastern Mediterranean are exposed to tsunami hazard. For many decades the knowledge about palaeotsunamis was solely based on historical accounts. However, results from timeline analyses reveal different characteristics affecting the quality of the dataset (i.e. distribution of data, temporal thinning backward of events, local periodization phenomena) that emphasize the fragmentary character of the historical data. As an increasing number of geo-scientific studies give convincing examples of well dated tsunami signatures not reported in catalogues, the non-existing record is a major problem to palaeotsunami research. While the compilation of historical data allows a first approach in the identification of areas vulnerable to tsunamis, it must not be regarded as reliable for hazard assessment. Considering the increasing economic significance of coastal regions (e.g. for mass tourism) and the constantly growing coastal population, our knowledge on the local, regional and supraregional tsunami hazard along Mediterranean coasts has to be improved. For setting up a reliable tsunami risk assessment and developing risk mitigation strategies, it is of major importance (i) to identify areas under risk and (ii) to estimate the intensity and frequency of potential events. This approach is most promising when based on the analysis of palaeotsunami research seeking to detect areas of high palaeotsunami hazard, to calculate recurrence intervals and to document palaeotsunami destructiveness in terms of wave run-up, inundation and long-term coastal change. Within the past few years, geo-scientific studies on palaeotsunami events provided convincing evidence that throughout the Mediterranean ancient harbours were subject to strong tsunami-related disturbance or destruction. Constructed to protect ships from storm and wave activity, harbours provide especially sheltered and quiescent environments and thus turned out to be valuable geo-archives for tsunamigenic high-energy impacts on coastal areas. Directly exposed to the Hellenic Trench and extensive local fault systems, coastal areas in the Ionian Sea and the Gulf of Corinth hold a considerably high risk for tsunami events, respectively.Geo-scientific and geoarcheaological studies carried out in the environs of the ancient harbours of Krane (Cefalonia Island), Lechaion (Corinth, Gulf of Corinth) and Kyllini (western Peloponnese) comprised on-shore and near-shore vibracoring and subsequent sedimentological, geochemical and microfossil analyses of the recovered sediments. Geophysical methods like electrical resistivity tomography and ground penetrating radar were applied in order to detect subsurface structures and to verify stratigraphical patterns derived from vibracores over long distances. The overall geochronological framework of each study area is based on radiocarbon dating of biogenic material and age determination of diagnostic ceramic fragments. Results presented within this study provide distinct evidence of multiple palaeotsunami landfalls for the investigated areas. Tsunami signatures encountered in the environs of Krane, Lechaion and Kyllini include (i) coarse-grained allochthonous marine sediments intersecting silt-dominated quiescent harbour deposits and/or shallow marine environments, (ii) disturbed microfaunal assemblages and/or (iii) distinct geochemical fingerprints as well as (iv) geo-archaeological destruction layers and (v) extensive units of beachrock-type calcarenitic tsunamites. For Krane, geochronological data yielded termini ad or post quem (maximum ages) for tsunami event generations dated to 4150 ± 60 cal BC, ~ 3200 ± 110 cal BC, ~ 650 ± 110 cal BC, and ~ 930 ± 40 cal AD, respectively. Results for Lechaion suggest that the harbour was hit by strong tsunami impacts in the 8th-6th century BC, the 1st-2nd century AD and in the 6th century AD. At Kyllini, the harbour site was affected by tsunami impact in between the late 7th and early 4th cent. BC and between the 4th and 6th cent. AD. In case of Lechaion and Kyllini, the final destruction of the harbour facilities also seems to be related to the tsunami impact. Comparing the tsunami signals obtained for each study areas with geo-scientific data from palaeotsunami events from other sites indicates that the investigated harbour sites represent excellent geo-archives for supra-regional mega-tsunamis.

Progettazione e realizzazione di un'applicazione per l'estrazione, l'analisi e l'integrazione di social data e linked open data.

Studio ed analisi delle principali tecniche in ambito di Social Data Analysis. Progettazione e Realizzazione di una soluzione software implementata con linguaggio Java in ambiente Eclipse. Il software realizzato permette di integrare differenti servizi di API REST, per l'estrazione di dati sociali da Twitter, la loro memorizzazione in un database non-relazionale (realizzato con MongoDB), e la loro gestione. Inoltre permette di effettuare operazioni di classificazione di topic, e di analizzare dati complessivi sulle collection di dati estratti. Infine permette di visualizzare un albero delle "ricondivisioni", partendo da singoli tweet selezionati, ed una mappa geo-localizzata, contenente gli utenti coinvolti nella catena di ricondivisioni, e i relativi archi di "retweet".

Dynamic characterisation of four nine-story large-panel R.C. buildings in Bishkek (Kyrgyzstan): A comparison between experimental ambient vibration analysis and numerical finite element modeling

With the outlook of improving seismic vulnerability assessment for the city of Bishkek (Kyrgyzstan), the global dynamic behaviour of four nine-storey r.c. large-panel buildings in elastic regime is studied. The four buildings were built during the Soviet era within a serial production system. Since they all belong to the same series, they have very similar geometries both in plan and in height. Firstly, ambient vibration measurements are performed in the four buildings. The data analysis composed of discrete Fourier transform, modal analysis (frequency domain decomposition) and deconvolution interferometry, yields the modal characteristics and an estimate of the linear impulse response function for the structures of the four buildings. Then, finite element models are set up for all four buildings and the results of the numerical modal analysis are compared with the experimental ones. The numerical models are finally calibrated considering the first three global modes and their results match the experimental ones with an error of less then 20%.

Mining tissue microarray data to uncover combinations of biomarker expression patterns that improve intermediate staging and grading of clear cell renal cell cancer

PURPOSE: Tumor stage and nuclear grade are the most important prognostic parameters of clear cell renal cell carcinoma (ccRCC). The progression risk of ccRCC remains difficult to predict particularly for tumors with organ-confined stage and intermediate differentiation grade. Elucidating molecular pathways deregulated in ccRCC may point to novel prognostic parameters that facilitate planning of therapeutic approaches. EXPERIMENTAL DESIGN: Using tissue microarrays, expression patterns of 15 different proteins were evaluated in over 800 ccRCC patients to analyze pathways reported to be physiologically controlled by the tumor suppressors von Hippel-Lindau protein and phosphatase and tensin homologue (PTEN). Tumor staging and grading were improved by performing variable selection using Cox regression and a recursive bootstrap elimination scheme. RESULTS: Patients with pT2 and pT3 tumors that were p27 and CAIX positive had a better outcome than those with all remaining marker combinations. A prolonged survival among patients with intermediate grade (grade 2) correlated with both nuclear p27 and cytoplasmic PTEN expression, as well as with inactive, nonphosphorylated ribosomal protein S6. By applying graphical log-linear modeling for over 700 ccRCC for which the molecular parameters were available, only a weak conditional dependence existed between the expression of p27, PTEN, CAIX, and p-S6, suggesting that the dysregulation of several independent pathways are crucial for tumor progression. CONCLUSIONS: The use of recursive bootstrap elimination, as well as graphical log-linear modeling for comprehensive tissue microarray (TMA) data analysis allows the unraveling of complex molecular contexts and may improve predictive evaluations for patients with advanced renal cancer.

Auditory verbal hallucinations: imaging, analysis, and intervention

In this article, we will link neuroimaging, data analysis, and intervention methods in an important psychiatric condition: auditory verbal hallucinations (AVH). The clinical and phenomenological background as well as neurophysiological findings will be covered and discussed with respect to noninvasive brain stimulation. Additionally, methods of noninvasive brain stimulation will be presented as ways to intervene with AVH. Finally, preliminary conclusions and possible future perspectives will be proposed.