The prognostic value of semi-quantitative i-123 mibg scintigraphy at diagnosis in high risk neuroblastoma: validation of the siopen score method

Purpose: SIOPEN scoring of 123I mIBG imaging has been shown to predict response to induction chemotherapy and outcome at diagnosis in children with HRN.Method: Patterns of skeletal 123I mIBG uptake were assigned numerical scores (Mscore) ranging from 0 (no metastasis) to 72 (diffuse metastases) within 12 body areas as described previously. 271 anonymised, paired image data sets acquired at diagnosis and on completion of Rapid COJEC induction chemotherapy were reviewed, constituting a representative sample of 1602 children treated prospectively within the HR-NBL1/SIOPEN trial. Pre-and post-treatment Mscores were compared with bone marrow cytology (BM) and 3 year event free survival (EFS).Results: Results 224/271 patients showed skeletal MIBG-uptake at diagnosis and were evaluable forMIBG-response. Complete response (CR) on MIBG to Rapid COJEC induction was achieved by 66%, 34% and 15% of patients who had pre-treatment Mscores of <18 (n¼65, 29%), 18-44 (n¼95,42%) and Y ´ 45 (n¼64, 28.5%) respectively (chi squared test p<.0001). Mscore at diagnosis and on completion of Rapid COJEC correlated strongly with BM involvement (p<0.0001). The correlation of pre score with post scores and response was highly significant (p<0.001). Most importantly, the 3 year EFS in 47 children with Mscore 0 at diagnosis was 0.68 (A ` 0.07), by comparison with 0.42 (A` 0.06), 0.35 (A` 0.05) and 0.25 (A` 0.06) for patients in pre-treatment score groups <18, 18-44 and Y ´ 45, respectively (p<0.001). AnMscore threshold ofY ´ 45 at diagnosis was associated with significantly worse outcome by comparison with all other Mscore groups (p¼0.029). The 3 year EFS of 0.53 (A` 0.07) of patients in metastatic CR (mIBG and BM) after Rapid Cojec (33%) is clearly superior to patients not achieving metastatic CR (0.24 (A ` 0.04), p¼0.005).Conclusion: SIOPEN scoring of 123I mIBG imaging has been shown to predict response to induction chemotherapy and outcome at diagnosis in children with HRN.

MADAP, a flexible clustering tool for the interpretation of one-dimensional genome annotation data.

A recurring task in the analysis of mass genome annotation data from high-throughput technologies is the identification of peaks or clusters in a noisy signal profile. Examples of such applications are the definition of promoters on the basis of transcription start site profiles, the mapping of transcription factor binding sites based on ChIP-chip data and the identification of quantitative trait loci (QTL) from whole genome SNP profiles. Input to such an analysis is a set of genome coordinates associated with counts or intensities. The output consists of a discrete number of peaks with respective volumes, extensions and center positions. We have developed for this purpose a flexible one-dimensional clustering tool, called MADAP, which we make available as a web server and as standalone program. A set of parameters enables the user to customize the procedure to a specific problem. The web server, which returns results in textual and graphical form, is useful for small to medium-scale applications, as well as for evaluation and parameter tuning in view of large-scale applications, requiring a local installation. The program written in C++ can be freely downloaded from ftp://ftp.epd.unil.ch/pub/software/unix/madap. The MADAP web server can be accessed at http://www.isrec.isb-sib.ch/madap/.

Offer and use of complementary and alternative medicine in hospitals of the French-speaking part of Switzerland.

BACKGROUND: In 2004, complementary and alternative medicine (CAM) was offered by physicians in one-third of Swiss hospitals. Since then, CAM health policy has changed considerably. This study aimed to describe the present supply and use of CAM in hospitals in the French-speaking part of Switzerland, and to explore qualitatively the characteristics of this offer. METHODS: Between June 2011 and March 2012, a short questionnaire was sent to the medical directors of hospitals (n = 46), asking them whether CAM was offered, where and by whom. Then, a semi-directive interview was conducted with ten CAM therapists. RESULTS: Among 37 responses (return rate 80%), 19 medical directors indicated that their hospital offered at least one CAM and 18 reported that they did not. Acupuncture was the most frequently available CAM, followed by manual therapies, osteopathy and aromatherapy. The disciplines that offered CAM most frequently were rehabilitation, gynaecology and obstetrics, palliative care, psychiatry, and anaesthetics. In eight out of ten interviews, it appeared that the procedures for introducing a CAM in the hospital were not tightly supervised by the hospital and were mainly based on the goodwill of the therapists, rather than clinical/scientific evidence. CONCLUSION: The number of hospitals offering CAM in the French-speaking part of Switzerland seemed to have risen since 2004. The selection of a CAM to be offered in a hospital should be based on the same procedure of evaluation and validation as conventional therapy, and if the safety and efficiency of the CAM is evidence-based, it should receive the same resources as a conventional therapy.

Identification of different heart tissues from MRI C-SENC images using an unsupervised multi-stage fuzzy clustering technique.

PURPOSE: To objectively characterize different heart tissues from functional and viability images provided by composite-strain-encoding (C-SENC) MRI. MATERIALS AND METHODS: C-SENC is a new MRI technique for simultaneously acquiring cardiac functional and viability images. In this work, an unsupervised multi-stage fuzzy clustering method is proposed to identify different heart tissues in the C-SENC images. The method is based on sequential application of the fuzzy c-means (FCM) and iterative self-organizing data (ISODATA) clustering algorithms. The proposed method is tested on simulated heart images and on images from nine patients with and without myocardial infarction (MI). The resulting clustered images are compared with MRI delayed-enhancement (DE) viability images for determining MI. Also, Bland-Altman analysis is conducted between the two methods. RESULTS: Normal myocardium, infarcted myocardium, and blood are correctly identified using the proposed method. The clustered images correctly identified 90 +/- 4% of the pixels defined as infarct in the DE images. In addition, 89 +/- 5% of the pixels defined as infarct in the clustered images were also defined as infarct in DE images. The Bland-Altman results show no bias between the two methods in identifying MI. CONCLUSION: The proposed technique allows for objectively identifying divergent heart tissues, which would be potentially important for clinical decision-making in patients with MI.

Density-based hierarchical clustering of pyro-sequences on a large scale--the case of fungal ITS1.

MOTIVATION: Analysis of millions of pyro-sequences is currently playing a crucial role in the advance of environmental microbiology. Taxonomy-independent, i.e. unsupervised, clustering of these sequences is essential for the definition of Operational Taxonomic Units. For this application, reproducibility and robustness should be the most sought after qualities, but have thus far largely been overlooked. RESULTS: More than 1 million hyper-variable internal transcribed spacer 1 (ITS1) sequences of fungal origin have been analyzed. The ITS1 sequences were first properly extracted from 454 reads using generalized profiles. Then, otupipe, cd-hit-454, ESPRIT-Tree and DBC454, a new algorithm presented here, were used to analyze the sequences. A numerical assay was developed to measure the reproducibility and robustness of these algorithms. DBC454 was the most robust, closely followed by ESPRIT-Tree. DBC454 features density-based hierarchical clustering, which complements the other methods by providing insights into the structure of the data. AVAILABILITY: An executable is freely available for non-commercial users at ftp://ftp.vital-it.ch/tools/dbc454. It is designed to run under MPI on a cluster of 64-bit Linux machines running Red Hat 4.x, or on a multi-core OSX system. CONTACT: dbc454@vital-it.ch or nicolas.guex@isb-sib.ch.

Data-driven clustering : new methods and applications

Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.

Machine learning analysis and modeling of interest rate curves

The present research deals with the review of the analysis and modeling of Swiss franc interest rate curves (IRC) by using unsupervised (SOM, Gaussian Mixtures) and supervised machine (MLP) learning algorithms. IRC are considered as objects embedded into different feature spaces: maturities; maturity-date, parameters of Nelson-Siegel model (NSM). Analysis of NSM parameters and their temporal and clustering structures helps to understand the relevance of model and its potential use for the forecasting. Mapping of IRC in a maturity-date feature space is presented and analyzed for the visualization and forecasting purposes.

Naevus du repli semi-lunaire de la conjonctive de découverte tardive [Conjunctival semi-lunar fold nevus of presumed late onset].

Conjunctival nevi are lesions observed commonly occasionnally and can be found later in a life. Such a lesion was observed on the conjunctival semilunar fold in a 76-year-old female patient. It was oval in shape, pigmented, and was mainly visible when the affected eye was in abduction. As no accurate anterior clinical history was available, surgical resection was performed. Hitopathological study disclosed a subepithelial nevus, which was completely resected. Regular follow-up was recommended, as is usual after surgical resection of a conjunctival pigmented tumor.

Supervised injection services : what has been demonstrated? A systematic literature review

BACKGROUND: Supervised injection services (SISs) have been developed to promote safer drug injection practices, enhance health-related behaviors among people who inject drugs (PWID), and connect PWID with external health and social services. Nevertheless, SISs have also been accused of fostering drug use and drug trafficking. AIMS: To systematically collect and synthesize the currently available evidence regarding SIS-induced benefits and harm. METHODS: A systematic review was performed via the PubMed, Web of Science, and ScienceDirect databases using the keyword algorithm [("supervised" or "safer") and ("injection" or "injecting" or "shooting" or "consumption") and ("facility" or "facilities" or "room" or "gallery" or "centre" or "site")]. RESULTS: Seventy-five relevant articles were found. All studies converged to find that SISs were efficacious in attracting the most marginalized PWID, promoting safer injection conditions, enhancing access to primary health care, and reducing the overdose frequency. SISs were not found to increase drug injecting, drug trafficking or crime in the surrounding environments. SISs were found to be associated with reduced levels of public drug injections and dropped syringes. Of the articles, 85% originated from Vancouver or Sydney. CONCLUSION: SISs have largely fulfilled their initial objectives without enhancing drug use or drug trafficking. Almost all of the studies found in this review were performed in Canada or Australia, whereas the majority of SISs are located in Europe. The implementation of new SISs in places with high rates of injection drug use and associated harms appears to be supported by evidence.

Astrocytic αVβ3 integrin inhibits neurite outgrowth and promotes retraction of neuronal processes by clustering Thy-1.

Thy-1 is a membrane glycoprotein suggested to stabilize or inhibit growth of neuronal processes. However, its precise function has remained obscure, because its endogenous ligand is unknown. We previously showed that Thy-1 binds directly to α(V)β(3) integrin in trans eliciting responses in astrocytes. Nonetheless, whether α(V)β(3) integrin might also serve as a Thy-1-ligand triggering a neuronal response has not been explored. Thus, utilizing primary neurons and a neuron-derived cell line CAD, Thy-1-mediated effects of α(V)β(3) integrin on growth and retraction of neuronal processes were tested. In astrocyte-neuron co-cultures, endogenous α(V)β(3) integrin restricted neurite outgrowth. Likewise, α(V)β(3)-Fc was sufficient to suppress neurite extension in Thy-1(+), but not in Thy-1(-) CAD cells. In differentiating primary neurons exposed to α(V)β(3)-Fc, fewer and shorter dendrites were detected. This effect was abolished by cleavage of Thy-1 from the neuronal surface using phosphoinositide-specific phospholipase C (PI-PLC). Moreover, α(V)β(3)-Fc also induced retraction of already extended Thy-1(+)-axon-like neurites in differentiated CAD cells as well as of axonal terminals in differentiated primary neurons. Axonal retraction occurred when redistribution and clustering of Thy-1 molecules in the plasma membrane was induced by α(V)β(3) integrin. Binding of α(V)β(3)-Fc was detected in Thy-1 clusters during axon retraction of primary neurons. Moreover, α(V)β(3)-Fc-induced Thy-1 clustering correlated in time and space with redistribution and inactivation of Src kinase. Thus, our data indicates that α(V)β(3) integrin is a ligand for Thy-1 that upon binding not only restricts the growth of neurites, but also induces retraction of already existing processes by inducing Thy-1 clustering. We propose that these events participate in bi-directional astrocyte-neuron communication relevant to axonal repair after neuronal damage.

Large-scale clustering through functional embedding

We present a new framework for large-scale data clustering. The main idea is to modify functional dimensionality reduction techniques to directly optimize over discrete labels using stochastic gradient descent. Compared to methods like spectral clustering our approach solves a single optimization problem, rather than an ad-hoc two-stage optimization approach, does not require a matrix inversion, can easily encode prior knowledge in the set of implementable functions, and does not have an ?out-of-sample? problem. Experimental results on both artificial and real-world datasets show the usefulness of our approach.

Virosome-Formulated Plasmodium falciparum AMA-1 & CSP Derived Peptides as Malaria Vaccine: Randomized Phase 1b Trial in Semi-Immune Adults & Children.

Background: This trial was conducted to evaluate the safety and immunogenicity of two virosome formulated malaria peptidomimetics derived from Plasmodium falciparum AMA-1 and CSP in malaria semi-immune adults and children.Methods: The design was a prospective randomized, double-blind, controlled, age-deescalating study with two immunizations. 10 adults and 40 children (aged 5-9 years) living in a malaria endemic area were immunized with PEV3B or virosomal influenza vaccine Inflexal (R) V on day 0 and 90.Results: No serious or severe adverse events (AEs) related to the vaccines were observed. The only local solicited AE reported was pain at injection site, which affected more children in the Inflexal (R) V group compared to the PEV3B group (p = 0.014). In the PEV3B group, IgG ELISA endpoint titers specific for the AMA-1 and CSP peptide antigens were significantly higher for most time points compared to the Inflexal (R) V control group. Across all time points after first immunization the average ratio of endpoint titers to baseline values in PEV3B subjects ranged from 4 to 15 in adults and from 4 to 66 in children. As an exploratory outcome, we found that the incidence rate of clinical malaria episodes in children vaccinees was half the rate of the control children between study days 30 and 365 (0.0035 episodes per day at risk for PEV3B vs. 0.0069 for Inflexal (R) V; RR = 0.50 [95%-CI: 0.29-0.88], p = 0.02).Conclusion: These findings provide a strong basis for the further development of multivalent virosomal malaria peptide vaccines.

Full activation of the T cell receptor requires both clustering and conformational changes at CD3.

T cell receptor (TCR-CD3) triggering involves both receptor clustering and conformational changes at the cytoplasmic tails of the CD3 subunits. The mechanism by which TCRalphabeta ligand binding confers conformational changes to CD3 is unknown. By using well-defined ligands, we showed that induction of the conformational change requires both multivalent engagement and the mobility restriction of the TCR-CD3 imposed by the plasma membrane. The conformational change is elicited by cooperative rearrangements of two TCR-CD3 complexes and does not require accompanying changes in the structure of the TCRalphabeta ectodomains. This conformational change at CD3 reverts upon ligand dissociation and is required for T cell activation. Thus, our permissive geometry model provides a molecular mechanism that rationalizes how the information of ligand binding to TCRalphabeta is transmitted to the CD3 subunits and to the intracellular signaling machinery.