A steroidomic approach for biomarkers discovery in doping control.

Anti-doping authorities have high expectations of the athlete steroidal passport (ASP) for anabolic-androgenic steroids misuse detection. However, it is still limited to the monitoring of known well-established compounds and might greatly benefit from the discovery of new relevant biomarkers candidates. In this context, steroidomics opens the way to the untargeted simultaneous evaluation of a high number of compounds. Analytical platforms associating the performance of ultra-high pressure liquid chromatography (UHPLC) and the high mass-resolving power of quadrupole time-of-flight (QTOF) mass spectrometers are particularly adapted for such purpose. An untargeted steroidomic approach was proposed to analyse urine samples from a clinical trial for the discovery of relevant biomarkers of testosterone undecanoate oral intake. Automatic peak detection was performed and a filter of reference steroid metabolites mass-to-charge ratio (m/z) values was applied to the raw data to ensure the selection of a subset of steroid-related features. Chemometric tools were applied for the filtering and the analysis of UHPLC-QTOF-MS(E) data. Time kinetics could be assessed with N-way projections to latent structures discriminant analysis (N-PLS-DA) and a detection window was confirmed. Orthogonal projections to latent structures discriminant analysis (O-PLS-DA) classification models were evaluated in a second step to assess the predictive power of both known metabolites and unknown compounds. A shared and unique structure plot (SUS-plot) analysis was performed to select the most promising unknown candidates and receiver operating characteristic (ROC) curves were computed to assess specificity criteria applied in routine doping control. This approach underlined the pertinence to monitor both glucuronide and sulphate steroid conjugates and include them in the athletes passport, while promising biomarkers were also highlighted.

On the Schoenberg transformations in data analysis: theory and illustrations

The class of Schoenberg transformations, embedding Euclidean distances into higher dimensional Euclidean spaces, is presented, and derived from theorems on positive definite and conditionally negative definite matrices. Original results on the arc lengths, angles and curvature of the transformations are proposed, and visualized on artificial data sets by classical multidimensional scaling. A distance-based discriminant algorithm and a robust multidimensional centroid estimate illustrate the theory, closely connected to the Gaussian kernels of Machine Learning.

Breast cancer and melanoma cell line identification by FTIR imaging after formalin-fixation and paraffin-embedding.

Over the past few decades, Fourier transform infrared (FTIR) spectroscopy coupled to microscopy has been recognized as an emerging and potentially powerful tool in cancer research and diagnosis. For this purpose, histological analyses performed by pathologists are mostly carried out on biopsied tissue that undergoes the formalin-fixation and paraffin-embedding (FFPE) procedure. This processing method ensures an optimal and permanent preservation of the samples, making FFPE-archived tissue an extremely valuable source for retrospective studies. Nevertheless, as highlighted by previous studies, this fixation procedure significantly changes the principal constituents of cells, resulting in important effects on their infrared (IR) spectrum. Despite the chemical and spectral influence of FFPE processing, some studies demonstrate that FTIR imaging allows precise identification of the different cell types present in biopsied tissue, indicating that the FFPE process preserves spectral differences between distinct cell types. In this study, we investigated whether this is also the case for closely related cell lines. We analyzed spectra from 8 cancerous epithelial cell lines: 4 breast cancer cell lines and 4 melanoma cell lines. For each cell line, we harvested cells at subconfluence and divided them into two sets. We first tested the "original" capability of FTIR imaging to identify these closely related cell lines on cells just dried on BaF2 slides. We then repeated the test after submitting the cells to the FFPE procedure. Our results show that the IR spectra of FFPE processed cancerous cell lines undergo small but significant changes due to the treatment. The spectral modifications were interpreted as a potential decrease in the phospholipid content and protein denaturation, in line with the scientific literature on the topic. Nevertheless, unsupervised analyses showed that spectral proximities and distances between closely related cell lines were mostly, but not entirely, conserved after FFPE processing. Finally, PLS-DA statistical analyses highlighted that closely related cell lines are still successfully identified and efficiently distinguished by FTIR spectroscopy after FFPE treatment. This last result paves the way towards identification and characterization of cellular subtypes on FFPE tissue sections by FTIR imaging, indicating that this analysis technique could become a potential useful tool in cancer research.

Effect of n-3 fatty acids on cerebral markers and the inflammatory response in sepsis

Introduction ICM+ software encapsulates our 20 years' experience in brain monitoring. It collects data from a variety of bedside monitors and produces time trends of parameters defi ned using confi gurable mathematical formulae. To date it is being used in nearly 40 clinical research centres worldwide. We present its application for continuous monitoring of cerebral autoregulation using near-infrared spectroscopy (NIRS). Methods Data from multiple bedside monitors are processed by ICM+ in real time using a large selection of signal processing methods. These include various time and frequency domain analysis functions as well as fully customisable digital fi lters. The fi nal results are displayed in a variety of ways including simple time trends, as well as time window based histograms, cross histograms, correlations, and so forth. All this allows complex information from bedside monitors to be summarized in a concise fashion and presented to medical and nursing staff in a simple way that alerts them to the development of various pathological processes. Results One hundred and fi fty patients monitored continuously with NIRS, arterial blood pressure (ABP) and intracranial pressure (ICP), where available, were included in this study. There were 40 severely headinjured adult patients, 27 SAH patients (NCCU, Cambridge); 60 patients undergoing cardiopulmonary bypass (John Hopkins Hospital, Baltimore) and 23 patients with sepsis (University Hospital, Basel). In addition, MCA fl ow velocity (FV) was monitored intermittently using transcranial Doppler. FV-derived and ICP-derived pressure reactivity indices (PRx, Mx), as well as NIRS-derived reactivity indices (Cox, Tox, Thx) were calculated and showed signifi cant correlation with each other in all cohorts. Errorbar charts showing reactivity index PRx versus CPP (optimal CPP chart) as well as similar curves for NIRS indices versus CPP and ABP were also demonstrated. Conclusions ICM+ software is proving to be a very useful tool for enhancing the battery of available means for monitoring cerebral vasoreactivity and potentially facilitating autoregulation guided therapy. Complexity of data analysis is also hidden inside loadable profi les, thus allowing investigators to take full advantage of validated protocols including advanced processing formulas.

Development of a two-step screening ESI-TOF-MS method for rapid determination of significant stress-induced metabolome modifications in plant leaf extracts: the wound response in Arabidopsis thaliana as a case study.

To study the stress-induced effects caused by wounding under a new perspective, a metabolomic strategy based on HPLC-MS has been devised for the model plant Arabidopsis thaliana. To detect induced metabolites and precisely localise these compounds among the numerous constitutive metabolites, HPLC-MS analyses were performed in a two-step strategy. In a first step, rapid direct TOF-MS measurements of the crude leaf extract were performed with a ballistic gradient on a short LC-column. The HPLC-MS data were investigated by multivariate analysis as total mass spectra (TMS). Principal components analysis (PCA) and hierarchical cluster analysis (HCA) on principal coordinates were combined for data treatment. PCA and HCA demonstrated a clear clustering of plant specimens selecting the highest discriminating ions given by the complete data analysis, leading to the specific detection of discrete-induced ions (m/z values). Furthermore, pool constitution with plants of homogeneous behaviour was achieved for confirmatory analysis. In this second step, long high-resolution LC profilings on an UPLC-TOF-MS system were used on pooled samples. This allowed to precisely localise the putative biological marker induced by wounding and by specific extraction of accurate m/z values detected in the screening procedure with the TMS spectra.

Identification and validation of copy number variants using SNP genotyping arrays from a large clinical cohort.

BACKGROUND: Genotypes obtained with commercial SNP arrays have been extensively used in many large case-control or population-based cohorts for SNP-based genome-wide association studies for a multitude of traits. Yet, these genotypes capture only a small fraction of the variance of the studied traits. Genomic structural variants (GSV) such as Copy Number Variation (CNV) may account for part of the missing heritability, but their comprehensive detection requires either next-generation arrays or sequencing. Sophisticated algorithms that infer CNVs by combining the intensities from SNP-probes for the two alleles can already be used to extract a partial view of such GSV from existing data sets. RESULTS: Here we present several advances to facilitate the latter approach. First, we introduce a novel CNV detection method based on a Gaussian Mixture Model. Second, we propose a new algorithm, PCA merge, for combining copy-number profiles from many individuals into consensus regions. We applied both our new methods as well as existing ones to data from 5612 individuals from the CoLaus study who were genotyped on Affymetrix 500K arrays. We developed a number of procedures in order to evaluate the performance of the different methods. This includes comparison with previously published CNVs as well as using a replication sample of 239 individuals, genotyped with Illumina 550K arrays. We also established a new evaluation procedure that employs the fact that related individuals are expected to share their CNVs more frequently than randomly selected individuals. The ability to detect both rare and common CNVs provides a valuable resource that will facilitate association studies exploring potential phenotypic associations with CNVs. CONCLUSION: Our new methodologies for CNV detection and their evaluation will help in extracting additional information from the large amount of SNP-genotyping data on various cohorts and use this to explore structural variants and their impact on complex traits.

A novel in vitro metabolomics approach for neurotoxicity testing, proof of principle for methyl mercury chloride and caffeine

There is a need for more efficient methods giving insight into the complex mechanisms of neurotoxicity. Testing strategies including in vitro methods have been proposed to comply with this requirement. With the present study we aimed to develop a novel in vitro approach which mimics in vivo complexity, detects neurotoxicity comprehensively, and provides mechanistic insight. For this purpose we combined rat primary re-aggregating brain cell cultures with a mass spectrometry (MS)-based metabolomics approach. For the proof of principle we treated developing re-aggregating brain cell cultures for 48h with the neurotoxicant methyl mercury chloride (0.1-100muM) and the brain stimulant caffeine (1-100muM) and acquired cellular metabolic profiles. To detect toxicant-induced metabolic alterations the profiles were analysed using commercial software which revealed patterns in the multi-parametric dataset by principal component analyses (PCA), and recognised the most significantly altered metabolites. PCA revealed concentration-dependent cluster formations for methyl mercury chloride (0.1-1muM), and treatment-dependent cluster formations for caffeine (1-100muM) at sub-cytotoxic concentrations. Four relevant metabolites responsible for the concentration-dependent alterations following methyl mercury chloride treatment could be identified using MS-MS fragmentation analysis. These were gamma-aminobutyric acid, choline, glutamine, creatine and spermine. Their respective mass ion intensities demonstrated metabolic alterations in line with the literature and suggest that the metabolites could be biomarkers for mechanisms of neurotoxicity or neuroprotection. In addition, we evaluated whether the approach could identify neurotoxic potential by testing eight compounds which have target organ toxicity in the liver, kidney or brain at sub-cytotoxic concentrations. PCA revealed cluster formations largely dependent on target organ toxicity indicating possible potential for the development of a neurotoxicity prediction model. With such results it could be useful to perform a validation study to determine the reliability, relevance and applicability of this approach to neurotoxicity screening. Thus, for the first time we show the benefits and utility of in vitro metabolomics to comprehensively detect neurotoxicity and to discover new biomarkers.

Foxm1 expression in prostate epithelial cells is essential for prostate carcinogenesis.

The treatment of advanced prostate cancer (PCa) remains a challenge. Identification of new molecular mechanisms that regulate PCa initiation and progression would provide targets for the development of new cancer treatments. The Foxm1 transcription factor is highly up-regulated in tumor cells, inflammatory cells, and cells of tumor microenvironment. However, its functions in different cell populations of PCa lesions are unknown. To determine the role of Foxm1 in tumor cells during PCa development, we generated two novel transgenic mouse models, one exhibiting Foxm1 gain-of-function and one exhibiting Foxm1 loss-of-function under control of the prostate epithelial-specific Probasin promoter. In the transgenic adenocarcinoma mouse prostate (TRAMP) model of PCa that uses SV40 large T antigen to induce PCa, loss of Foxm1 decreased tumor growth and metastasis. Decreased prostate tumorigenesis was associated with a decrease in tumor cell proliferation and the down-regulation of genes critical for cell proliferation and tumor metastasis, including Cdc25b, Cyclin B1, Plk-1, Lox, and Versican. In addition, tumor-associated angiogenesis was decreased, coinciding with reduced Vegf-A expression. The mRNA and protein levels of 11β-Hsd2, an enzyme playing an important role in tumor cell proliferation, were down-regulated in Foxm1-deficient PCa tumors in vivo and in Foxm1-depleted TRAMP C2 cells in vitro. Foxm1 bound to, and increased transcriptional activity of, the mouse 11β-Hsd2 promoter through the -892/-879 region, indicating that 11β-Hsd2 was a direct transcriptional target of Foxm1. Without TRAMP, overexpression of Foxm1 either alone or in combination with inhibition of a p19(ARF) tumor suppressor caused a robust epithelial hyperplasia, but was insufficient to induce progression from hyperplasia to PCa. Foxm1 expression in prostate epithelial cells is critical for prostate carcinogenesis, suggesting that inhibition of Foxm1 is a promising therapeutic approach for prostate cancer chemotherapy.

Tire traces: discrimination and classification of pyrolysis-GC/MS profiles

Tire traces can be observed on several crime scenes as vehicles are often used by criminals. The tread abrasion on the road, while braking or skidding, leads to the production of small rubber particles which can be collected for comparison purposes. This research focused on the statistical comparison of Py-GC/MS profiles of tire traces and tire treads. The optimisation of the analytical method was carried out using experimental designs. The aim was to determine the best pyrolysis parameters regarding the repeatability of the results. Thus, the pyrolysis factor effect could also be calculated. The pyrolysis temperature was found to be five time more important than time. Finally, a pyrolysis at 650 °C during 15 s was selected. Ten tires of different manufacturers and models were used for this study. Several samples were collected on each tire, and several replicates were carried out to study the variability within each tire (intravariability). More than eighty compounds were integrated for each analysis and the variability study showed that more than 75% presented a relative standard deviation (RSD) below 5% for the ten tires, thus supporting a low intravariability. The variability between the ten tires (intervariability) presented higher values and the ten most variant compounds had a RSD value above 13%, supporting their high potential of discrimination between the tires tested. Principal Component Analysis (PCA) was able to fully discriminate the ten tires with the help of the first three principal components. The ten tires were finally used to perform braking tests on a racetrack with a vehicle equipped with an anti-lock braking system. The resulting tire traces were adequately collected using sheets of white gelatine. As for tires, the intravariability for the traces was found to be lower than the intervariability. Clustering methods were carried out and the Ward's method based on the squared Euclidean distance was able to correctly group all of the tire traces replicates in the same cluster than the replicates of their corresponding tire. Blind tests on traces were performed and were correctly assigned to their tire source. These results support the hypothesis that the tested tires, of different manufacturers and models, can be discriminated by a statistical comparison of their chemical profiles. The traces were found to be not differentiable from their source but differentiable from all the other tires present in the subset. The results are promising and will be extended on a larger sample set.

Reflections on Partial Least Squares Path Modeling

The purpose of the present article is to take stock of a recent exchange in Organizational Research Methods between critics (Rönkkö & Evermann, 2013) and proponents (Henseler et al., 2014) of partial least squares path modeling (PLS-PM). The two target articles were centered around six principal issues, namely whether PLS-PM: (1) can be truly characterized as a technique for structural equation modeling (SEM); (2) is able to correct for measurement error; (3) can be used to validate measurement models; (4) accommodates small sample sizes; (5) is able to provide null hypothesis tests for path coefficients; and (6) can be employed in an exploratory, model-building fashion. We summarize and elaborate further on the key arguments underlying the exchange, drawing from the broader methodological and statistical literature in order to offer additional thoughts concerning the utility of PLS-PM and ways in which the technique might be improved. We conclude with recommendations as to whether and how PLS-PM serves as a viable contender to SEM approaches for estimating and evaluating theoretical models.

Role of Staphylococcus aureus surface proteins in experimental endocarditis

Résumé Le staphylocoque doré est un pathogène responsable d'une grande variété de maladies chez l'être humain. Il est extrêmement bien équipé de facteurs de virulence, dont les adhésines. Jusqu'à présent, 21 protéines liant des composants de tissus de l'hôte ("microbial surface components reacting with adherence matrix molecules, MSCRAMM") ont été identifiées, par exemple le "clumping factor" A (CIfA) ou la "fibronectin-binding protein" A (FnBPA). Néanmoins, pour la plupart de ces protéines, leur rôle dans la pathogénie des infections à staphylocoque doré reste à être élucidé. Le but de cette thèse est de contribuer à ce processus. Premièrement, les "MSCRAMM" CIfA, CIfB, FnBPA, FnBPB, Cna, SpA, Pls, SdrC, SdrD, SdrE, SasD, SasE, SasF, SasG, Sasl, SasJ et SasK ont été exprimés dans une bactérie substitut, Lactococcus lactis, et testés pour leurs propriétés adhésives et leur pathogénicité dans un modèle d'endocardite expérimentale (voir chapitre 1). Cette technique a préalablement été utilisée avec succès et a l'avantage d'éviter le contexte complexe des redondances et systèmes de régulations propres au staphylocoque doré. Les résultats montrent que, de tous les facteurs de virulence testés, seuls CIfA et FnBPA sont d'importance primordiale dans le développement d'endocardite expérimentale. En ce qui concerne l'internalisation dans les cellules endothéliales, seulement FnPBA et FnBPB en sont capables. En outre, l'adhérence à chacun des ligands testés (fibrinogène, fibronectine, kératine, élastine, collagène, et les caillots de fibrine et plaquettes) est très spécifique et est médiée par une ou plusieures adhésines provenant du staphylocoque doré. Par conséquence, ces protéines pourraient représenter des cibles potentielles pour de futures thérapies anti-adhésives contre le staphylocoque doré. Deuxièmement, l'expression des facteurs de virulence décrits dans le chapitre 1 par les souches recombinantes de lactocoques a été vérifiée par une nouvelle méthode utilisant la spectrométrie de masse (voir chapitre 2). L'expression de toutes ces protéines par les souches recombinantes a pu être confirmée. Cette méthode pourrait être de grande valeur dans la vérification de la présence de protéines quelconques dans toutes sortes d'applications. Troisièmement, deux facteurs de virulence du staphylocoque, CIfA et une forme tronquée de FnBPA, ont été exprimés de façon simultanée dans une souche recombinante de lactocoque (voir chapitre 3}. Contrairement à une souche exprimant la FnBPA entière, une souche exprimant la forme tronquée de FnPBA, qui ne contient plus le domaine capable de lier le fibrinogène, perd complètement sa capacité d'infecter dans le modèle d'endocardite expérimentale. Par contre, il est montré que, en cas de complémentation de la forme tronquée de FnPBA avec le domaine de liaison au fibrinogène de CIfA dans la souche double recombinante, le phénotype intégral de FnBPA est récupéré. En conséquence, les facteurs de virulence sont capables de coopérer dans le but de la pathogénie des infections à staphylocoque doré. Summary Staphylococcus aureus is a human pathogen causing a wide variety of disease. It is extremely well equipped with both secreted and surface-attached virulence factors, which can act as adhesins to host tissues. In total, twenty-one microbial surface components reacting with adherence matrix molecules (MSCRAMMs) have been identified, so far. These include well-characterized adhesins such as clumping factor A (CIfA) or fibronectin-binding protein A (FnBPA). However, for most of them their potential role in the pathogenesis of staphylococcal infections remains to be elucidated. This has been attempted in this thesis work. Firstly, the staphylococcal MSCRAMMs CIfA, CIfB, FnBPA, FnBPB, Cna, SpA, Pls, SdrC, SdrD, SdrE, SasD, SasE, SasF, SasG, Sasl, SasJ, and SasK have been expressed in a surrogate bacterium, Lactococcus lactis, and tested for their in vitro adherence properties and their pathogenicity in the rat model of experimental endocarditis (see chapter 1). This model has successfully been used previously, and has the advantage of bypassing the complex S. aureus background of redundancies and differential regulation. Here, it is shown that of the seventeen tested potential virulence factors, only CIfA and FnBPA are critical for the pathogenesis of experimental endocarditis in rats, while internalization into bovine endothelial cells is mediated exclusively by FnBPA and FnBPB. In addition, the adherence to specific host ligands (fibrinogen, fibronectin, keratin, elastin, collagen, and fibrin-platelet clots) is highly specific and mediated by one or few staphylococcal adhesins, respectively. Thus, these surface proteins may represent potential targets for an anti-adhesive strategy against S. aureus infections. Secondly, the expression of the staphylococcal proteins by L. lactis recombinants described in chapter 1 was tested by a novel method using mass spectrometry (see chapter 2). The expression of all the staphylococcal proteins by the respective recombinant lactococcal strain could be confirmed. This method may prove to be of great value in the confirmation of the presence of any given protein in various experimental settings. Thirdly, two staphylococcal virulence factors, CIfA and a truncated form of FnBPA, were expressed simultaneously in one recombinant lactococcal strain (see chapter 3). In contrast to a recombinant strain expressing full-length FnPBA, a recombinant strain expressing a truncated FnPBA, lacking the domain capable of binding fibrinogen, completely lost infectivity in experimental endocarditis. However, it is shown that the complementation of the truncated form of FnBPA with the fibrinogenbinding domain of CIfA in a double recombinant strain results in the recovery of the complete phenotype of full-length FnBPA. Thus, virulence factors can cooperate in the pathogenesis of staphylococcal infections.