Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Suitability, success and sinks: how do predictions of nesting distributions relate to fitness parameters in high arctic waders?

AimAlthough habitat suitability maps derived from species distribution models (SDMs) are often assumed to highlight locations that can sustain healthy populations over time, the relationship between suitability scores and fitness parameters has rarely been tested thoroughly. LocationZackenberg Valley, north-east Greenland. MethodsUsing 14years of data (1997-2010) representing three wader species (dunlin Calidris alpina, sanderling Calidris alba and ruddy turnstone Arenaria interpres), we tested the relationships between modelled suitability and fitness parameters at nesting locations. ResultsAmong the three species examined, only the ruddy turnstone exhibited significant relationships between suitability and nest success, but over time rather than space. During years with extensive snow cover in the landscape, the nesting sites of ruddy turnstone occurred in different habitats than were typically used across years. Moreover, in years with extensive snow cover, the ruddy turnstone initiated nests later and suffered from higher egg predation rates. Main conclusionOur results suggest that SDMs derived from species occurrences that include years of low reproductive success may over-estimate the potential suitable habitat in the landscape. Whenever possible, variation in reproductive success should be considered when building models to inform species' response to environmental change. species' response to environmental change.

Use of DNA profiles for investigation using a simulated national DNA database: Part II. Statistical and ethical considerations on familial searching.

Familial searching consists of searching for a full profile left at a crime scene in a National DNA Database (NDNAD). In this paper we are interested in the circumstance where no full match is returned, but a partial match is found between a database member's profile and the crime stain. Because close relatives share more of their DNA than unrelated persons, this partial match may indicate that the crime stain was left by a close relative of the person with whom the partial match was found. This approach has successfully solved important crimes in the UK and the USA. In a previous paper, a model, which takes into account substructure and siblings, was used to simulate a NDNAD. In this paper, we have used this model to test the usefulness of familial searching and offer guidelines for pre-assessment of the cases based on the likelihood ratio. Siblings of "persons" present in the simulated Swiss NDNAD were created. These profiles (N=10,000) were used as traces and were then compared to the whole database (N=100,000). The statistical results obtained show that the technique has great potential confirming the findings of previous studies. However, effectiveness of the technique is only one part of the story. Familial searching has juridical and ethical aspects that should not be ignored. In Switzerland for example, there are no specific guidelines to the legality or otherwise of familial searching. This article both presents statistical results, and addresses criminological and civil liberties aspects to take into account risks and benefits of familial searching.

Probability distribution of the radionuclide half-lives

Power law distributions, a well-known model in the theory of real random variables, characterize a wide variety of natural and man made phenomena. The intensity of earthquakes, the word frequencies, the solar ares and the sizes of power outages are distributed according to a power law distribution. Recently, given the usage of power laws in the scientific community, several articles have been published criticizing the statistical methods used to estimate the power law behaviour and establishing new techniques to their estimation with proven reliability. The main object of the present study is to go in deep understanding of this kind of distribution and its analysis, and introduce the half-lives of the radioactive isotopes as a new candidate in the nature following a power law distribution, as well as a \canonical laboratory" to test statistical methods appropriate for long-tailed distributions.

JULIDE: a software tool for 3D reconstruction and statistical analysis of autoradiographic mouse brain sections.

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

Statistical discrimination of steroid profiles in doping control with support vector machines.

Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society. To screen for misuse with these compounds, drug testing laboratories monitor the urinary concentrations of endogenous steroid metabolites and their ratios, which constitute the steroid profile and compare them with reference ranges to detect unnaturally high values. However, the interpretation of the steroid profile is difficult due to large inter-individual variances, various confounding factors and different endogenous steroids marketed that influence the steroid profile in various ways. A support vector machine (SVM) algorithm was developed to statistically evaluate urinary steroid profiles composed of an extended range of steroid profile metabolites. This model makes the interpretation of the analytical data in the quest for deviating steroid profiles feasible and shows its versatility towards different kinds of misused endogenous steroids. The SVM model outperforms the current biomarkers with respect to detection sensitivity and accuracy, particularly when it is coupled to individual data as stored in the Athlete Biological Passport.

A temporal hierarchy for conspecific vocalization discrimination in humans.

Introduction: Discrimination of species-specific vocalizations is fundamental for survival and social interactions. Its unique behavioral relevance has encouraged the identification of circumscribed brain regions exhibiting selective responses (Belin et al., 2004), while the role of network dynamics has received less attention. Those studies that have examined the brain dynamics of vocalization discrimination leave unresolved the timing and the inter-relationship between general categorization, attention, and speech-related processes (Levy et al., 2001, 2003; Charest et al., 2009). Given these discrepancies and the presence of several confounding factors, electrical neuroimaging analyses were applied to auditory evoked-potential (AEPs) to acoustically and psychophysically controlled non-verbal human and animal vocalizations. This revealed which region(s) exhibit voice-sensitive responses and in which sequence. Methods: Subjects (N=10) performed a living vs. man-made 'oddball' auditory discrimination task, such that on a given block of trials 'target' stimuli occurred 10% of the time. Stimuli were complex, meaningful sounds of 500ms duration. There were 120 different sound files in total, 60 of which represented sounds of living objects and 60 man-made objects. The stimuli that were the focus of the present investigation were restricted to those of living objects within blocks where no response was required. These stimuli were further sorted between human non-verbal vocalizations and animal vocalizations. They were also controlled in terms of their spectrograms and formant distributions. Continuous 64-channel EEG was acquired through Neuroscan Synamps referenced to the nose, band-pass filtered 0.05-200Hz, and digitized at 1000Hz. Peri-stimulus epochs of continuous EEG (-100ms to 900ms) were visually inspected for artifacts, 40Hz low-passed filtered and baseline corrected using the pre-stimulus period . Averages were computed from each subject separately. AEPs in response to animal and human vocalizations were analyzed with respect to differences of Global Field Power (GFP) and with respect to changes of the voltage configurations at the scalp (reviewed in Murray et al., 2008). The former provides a measure of the strength of the electric field irrespective of topographic differences; the latter identifies changes in spatial configurations of the underlying sources independently of the response strength. In addition, we utilized the local auto-regressive average distributed linear inverse solution (LAURA; Grave de Peralta Menendez et al., 2001) to visualize and statistically contrast the likely underlying sources of effects identified in the preceding analysis steps. Results: We found differential activity in response to human vocalizations over three periods in the post-stimulus interval, and this response was always stronger than that to animal vocalizations. The first differential response (169-219ms) was a consequence of a modulation in strength of a common brain network localized into the right superior temporal sulcus (STS; Brodmann's Area (BA) 22) and extending into the superior temporal gyrus (STG; BA 41). A second difference (291-357ms) also followed from strength modulations of a common network with statistical differences localized to the left inferior precentral and prefrontal gyrus (BA 6/45). These two first strength modulations correlated (Spearman's rho(8)=0.770; p=0.009) indicative of functional coupling between temporally segregated stages of vocalization discrimination. A third difference (389-667ms) followed from strength and topographic modulations and was localized to the left superior frontal gyrus (BA10) although this third difference did not reach our spatial criterion of 12 continuous voxels. Conclusions: We show that voice discrimination unfolds over multiple temporal stages, involving a wide network of brain regions. The initial stages of vocalization discrimination are based on modulations in response strength within a common brain network with no evidence for a voice-selective module. The latency of this effect parallels that of face discrimination (Bentin et al., 2007), supporting the possibility that voice and face processes can mutually inform one another. Putative underlying sources (localized in the right STS; BA 22) are consistent with prior hemodynamic imaging evidence in humans (Belin et al., 2004). Our effect over the 291-357ms post-stimulus period overlaps the 'voice-specific-response' reported by Levy et al. (Levy et al., 2001) and the estimated underlying sources (left BA6/45) were in agreement with previous findings in humans (Fecteau et al., 2005). These results challenge the idea that circumscribed and selective areas subserve con-specific vocalization processing.

HLA and non-HLA genes in Behçet's disease: a multicentric study in the Spanish population.

INTRODUCTION According to genome wide association (GWA) studies as well as candidate gene approaches, Behçet's disease (BD) is associated with human leukocyte antigen (HLA)-A and HLA-B gene regions. The HLA-B51 has been consistently associated with the disease, but the role of other HLA class I molecules remains controversial. Recently, variants in non-HLA genes have also been associated with BD. The aims of this study were to further investigate the influence of the HLA region in BD and to explore the relationship with non-HLA genes recently described to be associated in other populations. METHODS This study included 304 BD patients and 313 ethnically matched controls. HLA-A and HLA-B low resolution typing was carried out by PCR-SSOP Luminex. Eleven tag single nucleotide polymorphisms (SNPs) located outside of the HLA-region, previously described associated with the disease in GWA studies and having a minor allele frequency in Caucasians greater than 0.15 were genotyped using TaqMan assays. Phenotypic and genotypic frequencies were estimated by direct counting and distributions were compared using the χ(2) test. RESULTS In addition to HLA-B*51, HLA-B*57 was found as a risk factor in BD, whereas, B*35 was found to be protective. Other HLA-A and B specificities were suggestive of association with the disease as risk (A*02 and A*24) or protective factors (A*03 and B*58). Regarding the non-HLA genes, the three SNPs located in IL23R and one of the SNPs in IL10 were found to be significantly associated with susceptibility to BD in our population. CONCLUSION Different HLA specificities are associated with Behçet's disease in addition to B*51. Other non-HLA genes, such as IL23R and IL-10, play a role in the susceptibility to the disease.

In vitro heat exposure induces a redistribution of nuclear matrix proteins in human K562 erythroleukemia cells.

By using both conventional and confocal laser scanning microscopy with three monoclonal antibodies recognizing nuclear matrix proteins we have investigated by means of indirect fluorescence whether an incubation of isolated nuclei at the physiological temperature of 37 degrees C induces a redistribution of nuclear components in human K562 erythroleukemia cells. Upon incubation of isolated nuclei for 45 min at 37 degrees C, we have found that two of the antibodies, directed against proteins of the inner matrix network (M(r) 125 and 160 kDa), gave a fluorescent pattern different from that observed in permeabilized cells. By contrast, the fluorescent pattern did not change if nuclei were kept at 0 degrees C. The difference was more marked in case of the 160-kDa polypeptide. The fluorescent pattern detected by the third antibody, which recognizes the 180-kDa nucleolar isoform of DNA topoisomerase II, was unaffected by heat exposure of isolated nuclei. When isolated nuclear matrices prepared from heat-stabilized nuclei were stained by means of the same three antibodies, it was possible to see that the distribution of the 160-kDa matrix protein no longer corresponded to that observable in permeabilized cells, whereas the fluorescent pattern given by the antibody to the 125-kDa polypeptide resembled that detectable in permeabilized cells. The 180-kDa isoform of topoisomerase II was still present in the matrix nucleolar remnants. We conclude that a 37 degrees C incubation of isolated nuclei induces a redistribution of some nuclear matrix antigens and cannot prevent the rearrangement in the spatial organization of one of these antigens that takes place during matrix isolation in human erythroleukemia cells. The practical relevance of these findings is discussed.

Rank estimation of trajectory matrix in motion segmentation

A novel technique for estimating the rank of the trajectory matrix in the local subspace affinity (LSA) motion segmentation framework is presented. This new rank estimation is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built with LSA. The result is an enhanced model selection technique for trajectory matrix rank estimation by which it is possible to automate LSA, without requiring any a priori knowledge, and to improve the final segmentation

Statistical Analysis of Eco-Toxicologic Data of Mammals from a Polluted Area

Several eco-toxicological studies have shown that insectivorous mammals, due to theirfeeding habits, easily accumulate high amounts of pollutants in relation to other mammal species. To assess the bio-accumulation levels of toxic metals and their in°uenceon essential metals, we quantified the concentration of 19 elements (Ca, K, Fe, B, P,S, Na, Al, Zn, Ba, Rb, Sr, Cu, Mn, Hg, Cd, Mo, Cr and Pb) in bones of 105 greaterwhite-toothed shrews (Crocidura russula) from a polluted (Ebro Delta) and a control(Medas Islands) area. Since chemical contents of a bio-indicator are mainly compositional data, conventional statistical analyses currently used in eco-toxicology can givemisleading results. Therefore, to improve the interpretation of the data obtained, weused statistical techniques for compositional data analysis to define groups of metalsand to evaluate the relationships between them, from an inter-population viewpoint.Hypothesis testing on the adequate balance-coordinates allow us to confirm intuitionbased hypothesis and some previous results. The main statistical goal was to test equalmeans of balance-coordinates for the two defined populations. After checking normality,one-way ANOVA or Mann-Whitney tests were carried out for the inter-group balances

Monitoring procedures in environmental geochemistry and compositional data analysis theory

First discussion on compositional data analysis is attributable to Karl Pearson, in 1897. However, notwithstanding the recent developments on algebraic structure of the simplex, more than twenty years after Aitchison’s idea of log-transformations of closed data, scientific literature is again full of statistical treatments of this type of data by using traditional methodologies. This is particularly true in environmental geochemistry where besides the problem of the closure, the spatial structure (dependence) of the data have to be considered. In this work we propose the use of log-contrast values, obtained by asimplicial principal component analysis, as LQGLFDWRUV of given environmental conditions. The investigation of the log-constrast frequency distributions allows pointing out the statistical laws able togenerate the values and to govern their variability. The changes, if compared, for example, with the mean values of the random variables assumed as models, or other reference parameters, allow definingmonitors to be used to assess the extent of possible environmental contamination. Case study on running and ground waters from Chiavenna Valley (Northern Italy) by using Na+, K+, Ca2+, Mg2+, HCO3-, SO4 2- and Cl- concentrations will be illustrated

MDCT Arthrography of the Hip: Value of the Adaptive Statistical Iterative Reconstruction Technique and Potential for Radiation Dose Reduction

Au cours des deux dernières décennies, la technique d'imagerie arthro-scanner a bénéficié de nombreux progrès technologiques et représente aujourd'hui une excellente alternative à l'imagerie par résonance magnétique (IRM) et / ou arthro-IRM dans l'évaluation des pathologies de la hanche. Cependant, elle reste limitée par l'exposition aux rayonnements ionisants importante. Les techniques de reconstruction itérative (IR) ont récemment été mis en oeuvre avec succès en imagerie ; la littérature montre que l'utilisation ces dernières contribue à réduire la dose d'environ 40 à 55%, comparativement aux protocoles courants utilisant la rétroprojection filtrée (FBP), en scanner de rachis. A notre connaissance, l'utilisation de techniques IR en arthro-scanner de hanche n'a pas été évaluée jusqu'à présent. Le but de notre étude était d'évaluer l'impact de la technique ASIR (GE Healthcare) sur la qualité de l'image objective et subjective en arthro-scanner de hanche, et d'évaluer son potentiel en terme de réduction de dose. Pour cela, trente sept patients examinés par arthro-scanner de hanche ont été randomisés en trois groupes : dose standard (CTDIvol = 38,4 mGy) et deux groupes de dose réduite (CTDIvol = 24,6 ou 15,4 mGy). Les images ont été reconstruites en rétroprojection filtrée (FBP) puis en appliquant différents pourcentages croissants d'ASIR (30, 50, 70 et 90%). Le bruit et le rapport contraste sur bruit (CNR) ont été mesurés. Deux radiologues spécialisés en imagerie musculo-squelettique ont évalué de manière indépendante la qualité de l'image au niveau de plusieurs structures anatomiques en utilisant une échelle de quatre grades. Ils ont également évalué les lésions labrales et du cartilage articulaire. Les résultats révèlent que le bruit augmente (p = 0,0009) et le CNR diminue (p = 0,001) de manière significative lorsque la dose diminue. A l'inverse, le bruit diminue (p = 0,0001) et le contraste sur bruit augmente (p < 0,003) de manière significative lorsque le pourcentage d'ASIR augmente ; on trouve également une augmentation significative des scores de la qualité de l'image pour le labrum, le cartilage, l'os sous-chondral, la qualité de l'image globale (au delà de ASIR 50%), ainsi que le bruit (p < 0,04), et une réduction significative pour l'os trabuculaire et les muscles (p < 0,03). Indépendamment du niveau de dose, il n'y a pas de différence significative pour la détection et la caractérisation des lésions labrales (n=24, p = 1) et des lésions cartilagineuses (n=40, p > 0,89) en fonction du pourcentage d'ASIR. Notre travail a permis de montrer que l'utilisation de plus de 50% d'ASIR permet de reduire de manière significative la dose d'irradiation reçue par le patient lors d'un arthro-scanner de hanche tout en maintenant une qualité d'image diagnostique comparable par rapport à un protocole de dose standard utilisant la rétroprojection filtrée.

Overcoming the rare species modelling paradox: test of a novel hierarchical framework with an Iberian endemic plant

Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.