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).

Classification of sags according to their origin based on the waveform similarity

A statistical method for classification of sags their origin downstream or upstream from the recording point is proposed in this work. The goal is to obtain a statistical model using the sag waveforms useful to characterise one type of sags and to discriminate them from the other type. This model is built on the basis of multi-way principal component analysis an later used to project the available registers in a new space with lower dimension. Thus, a case base of diagnosed sags is built in the projection space. Finally classification is done by comparing new sags against the existing in the case base. Similarity is defined in the projection space using a combination of distances to recover the nearest neighbours to the new sag. Finally the method assigns the origin of the new sag according to the origin of their neighbours

AIDS defining opportunistic infections in patients with high CD4 counts in the combination antiretroviral therapy (cART) era: things ain't what they used to be.

INTRODUCTION: According to reports from observational databases, classic AIDS-defining opportunistic infections (ADOIs) occur in patients with CD4 counts above 500/µL on and off cART. Adjudication of these events is usually not performed. However, ADOIs are often used as endpoints, for example, in analyses on when to start cART. MATERIALS AND METHODS: In the database, Swiss HIV Cohort Study (SHCS) database, we identified 91 cases of ADOIs that occurred from 1996 onwards in patients with the nearest CD4 count >500/µL. Cases of tuberculosis and recurrent bacterial pneumonia were excluded as they also occur in non-immunocompromised patients. Chart review was performed in 82 cases, and in 50 cases we identified CD4 counts within six months before until one month after ADOI and had chart review material to allow an in-depth review. In these 50 cases, we assessed whether (1) the ADOI fulfilled the SHCS diagnostic criteria (www.shcs.ch), and (2) HIV infection with CD4 >500/µL was the main immune-compromising condition to cause the ADOI. Adjudication of cases was done by two experienced clinicians who had to agree on the interpretation. RESULTS: More than 13,000 participants were followed in SHCS in the period of interest. Twenty-four (48%) of the chart-reviewed 50 patients with ADOI and CD4 >500/µL had an HIV RNA <400 copies/mL at the time of ADOI. In the 50 cases, candida oesophagitis was the most frequent ADOI in 30 patients (60%) followed by pneumocystis pneumonia and chronic ulcerative HSV disease (Table 1). Overall chronic HIV infection with a CD4 count >500/µL was the likely explanation for the ADOI in only seven cases (14%). Other reasons (Table 1) were ADOIs occurring during primary HIV infection in 5 (10%) cases, unmasking IRIS in 1 (2%) case, chronic HIV infection with CD4 counts <500/µL near the ADOI in 13 (26%) cases, diagnosis not according to SHCS diagnostic criteria in 7 (14%) cases and most importantly other additional immune-compromising conditions such as immunosuppressive drugs in 14 (34%). CONCLUSIONS: In patients with CD4 counts >500/ µL, chronic HIV infection is the cause of ADOIs in only a minority of cases. Other immuno-compromising conditions are more likely explanations in one-third of the patients, especially in cases of candida oesophagitis. ADOIs in HIV patients with high CD4 counts should be used as endpoints only with much caution in studies based on observational databases.

Risk factors associated with Trypanosoma cruziexposure in domestic dogs from a rural community in Panama

Chagas disease, caused by Trypanosoma cruzi infection, is a zoonosis of humans, wild and domestic mammals, including dogs. In Panama, the main T. cruzi vector is Rhodnius pallescens, a triatomine bug whose main natural habitat is the royal palm, Attalea butyracea. In this paper, we present results from three T. cruzi serological tests (immunochromatographic dipstick, indirect immunofluorescence and ELISA) performed in 51 dogs from 24 houses in Trinidad de Las Minas, western Panama. We found that nine dogs were seropositive (17.6% prevalence). Dogs were 1.6 times more likely to become T. cruziseropositive with each year of age and 11.6 times if royal palms where present in the peridomiciliary area of the dog’s household or its two nearest neighbours. Mouse-baited-adhesive traps were employed to evaluate 12 peridomestic royal palms. All palms were found infested with R. pallescens with an average of 25.50 triatomines captured per palm. Of 35 adult bugs analysed, 88.6% showed protozoa flagellates in their intestinal contents. In addition, dogs were five times more likely to be infected by the presence of an additional domestic animal species in the dog’s peridomiciliary environment. Our results suggest that interventions focused on royal palms might reduce the exposure to T. cruzi infection.

A Factor analysis of hidrochemical composition of Llobregat river basin

Hydrogeological research usually includes some statistical studies devised to elucidate mean background state, characterise relationships among different hydrochemical parameters, and show the influence of human activities. These goals are achieved either by means of a statistical approach or by mixing modelsbetween end-members. Compositional data analysis has proved to be effective with the first approach, but there is no commonly accepted solution to the end-member problem in a compositional framework.We present here a possible solution based on factor analysis of compositions illustrated with a case study.We find two factors on the compositional bi-plot fitting two non-centered orthogonal axes to the most representative variables. Each one of these axes defines a subcomposition, grouping those variables thatlay nearest to it. With each subcomposition a log-contrast is computed and rewritten as an equilibrium equation. These two factors can be interpreted as the isometric log-ratio coordinates (ilr) of three hiddencomponents, that can be plotted in a ternary diagram. These hidden components might be interpreted as end-members.We have analysed 14 molarities in 31 sampling stations all along the Llobregat River and its tributaries, with a monthly measure during two years. We have obtained a bi-plot with a 57% of explained totalvariance, from which we have extracted two factors: factor G, reflecting geological background enhanced by potash mining; and factor A, essentially controlled by urban and/or farming wastewater. Graphicalrepresentation of these two factors allows us to identify three extreme samples, corresponding to pristine waters, potash mining influence and urban sewage influence. To confirm this, we have available analysisof diffused and widespread point sources identified in the area: springs, potash mining lixiviates, sewage, and fertilisers. Each one of these sources shows a clear link with one of the extreme samples, exceptfertilisers due to the heterogeneity of their composition.This approach is a useful tool to distinguish end-members, and characterise them, an issue generally difficult to solve. It is worth note that the end-member composition cannot be fully estimated but only characterised through log-ratio relationships among components. Moreover, the influence of each endmember in a given sample must be evaluated in relative terms of the other samples. These limitations areintrinsic to the relative nature of compositional data

Model d'adequació de l'hàbitat del llop a Catalunya

Des de l’any 2000 es té constància de la presencia del llop a Catalunya. Des de llavors, com a mínim 14 llops diferents han entrat i sortit del territori català, encara que cap d’ells s’ha assentat de manera permanent. L’estudi analitza l’entorn català utilitzant GIS, creant un model d’adequació de l’hàbitat tenint en compte les següents variables: la distància a la carretera més propera, la biomassa disponible a la zona, l’altitud i el tipus i tant per cent de recobriment. El model es basa en la informació obtinguda mitjançant la consulta a experts tant del llop com del territori català, així com en una recerca bibliogràfica sobre l’adequació de l’hàbitat del llop. L’enquesta que es dirigí als experts té en compte els valors que cada variable pot prendre dins l’àrea d’estudi, estableix rangs dels valors de cada variable i pregunta als experts com cada rang pot afectar a l’adequació de l’hàbitat pel llop. Els resultats mostren com bona part de la zona Nord de Catalunya té unes condicions adequades perquè el llop pugui arribar a reproduir-s’hi. Es desenvolupa també una anàlisi dels possibles punts de conflicte humà-llop i una superposició dels espais protegits amb les zones més adequades per l’establiment del llop.

Detection of millimetric deformation using a terrestrial laser scanner: experiment and application to a rockfall event

Abstract. Terrestrial laser scanning (TLS) is one of the most promising surveying techniques for rockslope characteriza- tion and monitoring. Landslide and rockfall movements can be detected by means of comparison of sequential scans. One of the most pressing challenges of natural hazards is com- bined temporal and spatial prediction of rockfall. An outdoor experiment was performed to ascertain whether the TLS in- strumental error is small enough to enable detection of pre- cursory displacements of millimetric magnitude. This con- sists of a known displacement of three objects relative to a stable surface. Results show that millimetric changes cannot be detected by the analysis of the unprocessed datasets. Dis- placement measurement are improved considerably by ap- plying Nearest Neighbour (NN) averaging, which reduces the error (1σ ) up to a factor of 6. This technique was ap- plied to displacements prior to the April 2007 rockfall event at Castellfollit de la Roca, Spain. The maximum precursory displacement measured was 45 mm, approximately 2.5 times the standard deviation of the model comparison, hampering the distinction between actual displacement and instrumen- tal error using conventional methodologies. Encouragingly, the precursory displacement was clearly detected by apply- ing the NN averaging method. These results show that mil- limetric displacements prior to failure can be detected using TLS.

Exploring the conditions for a mortality crisis: bringing context back into the debate

This study engages with the debate over the mortality crises in the former Soviet Union and Central and Eastern Europe by 1) considering at length and as complementary to each other the two most prominent explanations for the post-communist mortality crisis, stress and alcohol consumption; 2) emphasizing the importance of context by exploiting systematic similarities and differences across the region. Differential mortality trajectories reveal three country groups that cluster both spatially and in terms of economic transition experiences. The first group are the countries furthest west in which mortality rates increased minimally after the transition began. The second group experienced a severe increase in mortality rates in the early 1990s, but recovered previous levels within a few years. These countries are located peripherally to Russia and its nearest neighbours. The final group consists of countries that experienced two mortality increases or in which mortality levels had not recovered to pre-transition levels well into the 21st century. Cross-sectional time-series data analyses of men’s and women’s age and cause-specific death rates reveal that the clustering of these countries and their mortality trajectories can be partially explained by the economic context, which is argued to be linked to stress and alcohol consumption. Above and beyond many basic differences in the country groups that are held constant—including geographically and historically shared cultural, lifestyle and social characteristics—poor economic conditions account for a remarkably consistent share of excess age-specific and cause-specific deaths.

Regulation of Spermatogenesis: Differentiation of GFP-labeled Stem Cells and the Function of Cytoplasmic Bridges

During spermatogenesis, different genes are expressed in a strictly coordinated fashion providing an excellent model to study cell differentiation. Recent identification of testis specific genes and the development of green fluorescence protein (GFP) transgene technology and an in vivo system for studying the differentiation of transplanted male germ cells in infertile testis has opened new possibilities for studying the male germ cell differentiation at molecular level. We have employed these techniques in combination with transillumination based stage recognition (Parvinen and Vanha-Perttula, 1972) and squash preparation techniques (Parvinen and Hecht, 1981) to study the regulation of male germ cell differentiation. By using transgenic mice expressing enhanced-(E)GFP as a marker we have studied the expression and hormonal regulation of beta-actin and acrosin proteins in the developmentally different living male germ cells. Beta-actin was demonstrated in all male germ cells, whereas acrosin was expressed only in late meiotic and in postmeiotic cells. Follicle stimulating hormone stimulated b-actin-EGFP expression at stages I-VI and enhanced the formation of microtubules in spermatids and this way reduced the size of the acrosomic system. When EGFP expressing spermatogonial stem cells were transplanted into infertile mouse testis differentiation and the synchronized development of male germ cells could be observed during six months observation time. Each colony developed independently and maintained typical stage-dependent cell associations. Furthermore, if more than two colonies were fused, each of them was adjusted to one stage and synchronized. By studying living spermatids we were able to demonstrate novel functions for Golgi complex and chromatoid body in material sharing between neighbor spermatids. Immunosytochemical analyses revealed a transport of haploid cell specific proteins in spermatids (TRA54 and Shippo1) and through the intercellular bridges (TRA54). Cytoskeleton inhibitor (nocodazole) demonstrated the importance of microtubules in material sharing between spermatids and in preserving the integrity of the chromatoid body. Golgi complex inhibitor, brefeldin A, revealed the great importance of Golgi complex i) in acrosomic system formation ii) TRA54 translation and in iii) granule trafficking between spermatids.

The rate-limiting step for glucose transport into the hypothalamus is across the blood-hypothalamus interface.

Specialized glucosensing neurons are present in the hypothalamus, some of which neighbor the median eminence, where the blood-brain barrier has been reported leaky. A leaky blood-brain barrier implies high tissue glucose levels and obviates a role for endothelial glucose transporters in the control of hypothalamic glucose concentration, important in understanding the mechanisms of glucose sensing We therefore addressed the question of blood-brain barrier integrity at the hypothalamus for glucose transport by examining the brain tissue-to-plasma glucose ratio in the hypothalamus relative to other brain regions. We also examined glycogenolysis in hypothalamus because its occurrence is unlikely in the potential absence of a hypothalamus-blood interface. Across all regions the concentration of glucose was comparable at a given plasma glucose concentration and was a near linear function of plasma glucose. At steady-state, hypothalamic glucose concentration was similar to the extracellular hypothalamic glucose concentration reported by others. Hypothalamic glycogen fell at a rate of approximately 1.5 micromol/g/h and remained present in substantial amounts. We conclude for the hypothalamus, a putative primary site of brain glucose sensing that: the rate-limiting step for glucose transport into brain cells is at the blood-hypothalamus interface, and that glycogenolysis is consistent with a substantial blood -to- intracellular glucose concentration gradient.

Genetic variability of a population of Aedes aegypti from Paraná, Brazil, using the mitochondrial ND4 gene

Genetic variability of a population of Aedes aegypti from Paraná, Brazil, using the mitochondrial ND4 gene. To analyze the genetic variability of populations of Aedes aegypti, 156 samples were collected from 10 municipalities in the state of Paraná, Brazil. A 311 base pairs (bp) region of the NADH dehydrogenase subunit 4 (ND4) mitochondrial gene was examined. An analysis of this fragment identified eight distinct haplotypes. The mean genetic diversity was high (h = 0.702; p = 0.01556). AMOVA analysis indicated that most of the variation (67%) occurred within populations and the F ST value (0.32996) was highly significant. F ST values were significant in most comparisons among cities. The isolation by distance was not significant (r = -0.1216 and p = 0, 7550), indicating that genetic distance is not related to geographic distance. Neighbor-joining analysis showed two genetically distinct groups within Paraná. The DNA polymorphism and AMOVA data indicate a decreased gene flow in populations from Paraná, which can result in increased vectorial competence.

Local-scale spatial variation in diversity of social wasps in an Amazonian rain forest in Caxiuanã, Pará, Brazil (Hymenoptera, Vespidae, Polistinae)

Polistine wasps are important in Neotropical ecosystems due to their ubiquity and diversity. Inventories have not adequately considered spatial attributes of collected specimens. Spatial data on biodiversity are important for study and mitigation of anthropogenic impacts over natural ecosystems and for protecting species. We described and analyzed local-scale spatial patterns of collecting records of wasp species, as well as spatial variation of diversity descriptors in a 2500-hectare area of an Amazon forest in Brazil. Rare species comprised the largest fraction of the fauna. Close range spatial effects were detected for most of the more common species, with clustering of presence-data at short distances. Larger spatial lag effects could also be identified in some species, constituting probably cases of exogenous autocorrelation and candidates for explanations based on environmental factors. In a few cases, significant or near significant correlations were found between five species (of Agelaia, Angiopolybia, and Mischocyttarus) and three studied environmental variables: distance to nearest stream, terrain altitude, and the type of forest canopy. However, association between these factors and biodiversity variables were generally low. When used as predictors of polistine richness in a linear multiple regression, only the coefficient for the forest canopy variable resulted significant. Some level of prediction of wasp diversity variables can be attained based on environmental variables, especially vegetation structure. Large-scale landscape and regional studies should be scheduled to address this issue.

Profiling of counterfeit medicines by vibrational spectroscopy

Counterfeit pharmaceutical products have become a widespread problem in the last decade. Various analytical techniques have been applied to discriminate between genuine and counterfeit products. Among these, Near-infrared (NIR) and Raman spectroscopy provided promising results.The present study offers a methodology allowing to provide more valuable information fororganisations engaged in the fight against counterfeiting of medicines.A database was established by analyzing counterfeits of a particular pharmaceutical product using Near-infrared (NIR) and Raman spectroscopy. Unsupervised chemometric techniques (i.e. principal component analysis - PCA and hierarchical cluster analysis - HCA) were implemented to identify the classes within the datasets. Gas Chromatography coupled to Mass Spectrometry (GC-MS) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to determine the number of different chemical profiles within the counterfeits. A comparison with the classes established by NIR and Raman spectroscopy allowed to evaluate the discriminating power provided by these techniques. Supervised classifiers (i.e. k-Nearest Neighbors, Partial Least Squares Discriminant Analysis, Probabilistic Neural Networks and Counterpropagation Artificial Neural Networks) were applied on the acquired NIR and Raman spectra and the results were compared to the ones provided by the unsupervised classifiers.The retained strategy for routine applications, founded on the classes identified by NIR and Raman spectroscopy, uses a classification algorithm based on distance measures and Receiver Operating Characteristics (ROC) curves. The model is able to compare the spectrum of a new counterfeit with that of previously analyzed products and to determine if a new specimen belongs to one of the existing classes, consequently allowing to establish a link with other counterfeits of the database.

Batch effect confounding leads to strong bias in performance estimates obtained by cross-validation.

BACKGROUND: With the large amount of biological data that is currently publicly available, many investigators combine multiple data sets to increase the sample size and potentially also the power of their analyses. However, technical differences ("batch effects") as well as differences in sample composition between the data sets may significantly affect the ability to draw generalizable conclusions from such studies. FOCUS: The current study focuses on the construction of classifiers, and the use of cross-validation to estimate their performance. In particular, we investigate the impact of batch effects and differences in sample composition between batches on the accuracy of the classification performance estimate obtained via cross-validation. The focus on estimation bias is a main difference compared to previous studies, which have mostly focused on the predictive performance and how it relates to the presence of batch effects. DATA: We work on simulated data sets. To have realistic intensity distributions, we use real gene expression data as the basis for our simulation. Random samples from this expression matrix are selected and assigned to group 1 (e.g., 'control') or group 2 (e.g., 'treated'). We introduce batch effects and select some features to be differentially expressed between the two groups. We consider several scenarios for our study, most importantly different levels of confounding between groups and batch effects. METHODS: We focus on well-known classifiers: logistic regression, Support Vector Machines (SVM), k-nearest neighbors (kNN) and Random Forests (RF). Feature selection is performed with the Wilcoxon test or the lasso. Parameter tuning and feature selection, as well as the estimation of the prediction performance of each classifier, is performed within a nested cross-validation scheme. The estimated classification performance is then compared to what is obtained when applying the classifier to independent data.

Genesis of self-organized zebra textures in burial dolomites: Displacive veins, induced stress, and dolomitization

The dolomite veins making up rhythmites common in burial dolomites are not cement infillings of supposed cavities, as in the prevailing view, but are instead displacive veins, veins that pushed aside the host dolostone as they grew. Evidence that the veins are displacive includes a) small transform-fault-like displacements that could not have taken place if the veins were passive cements, and b) stylolites in host rock that formed as the veins grew in order to compensate for the volume added by the veins. Each zebra vein consists of crystals that grow inward from both sides, and displaces its walls via the local induced stress generated by the crystal growth itself. The petrographic criterion used in recent literature to interpret zebra veins in dolomites as cements - namely, that euhedral crystals can grow only in a prior void - disregards evidence to the contrary. The idea that flat voids did form in dolostones is incompatible with the observed optical continuity between the saddle dolomite euhedra of a vein and the replacive dolomite crystals of the host. The induced stress is also the key to the self-organization of zebra veins: In a set of many incipient, randomly-spaced, parallel veins just starting to grow in a host dolostone, each vein¿s induced stress prevents too-close neighbor veins from nucleating, or redissolves them by pressure-solution. The veins that survive this triage are those just outside their neighbors¿s induced stress haloes, now forming a set of equidistant veins, as observed.