Time Series Input Selection using Multiple Kernel Learning

In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).

GeoKernels: Modeling of Spatial Data on GeoManifolds

This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental data modeling on natural manifolds, such as complex topographies of the mountainous regions, where environmental processes are highly influenced by the relief. These relations, possibly regionalized and nonlinear, can be modeled from data with machine learning using the digital elevation models in semi-supervised kernel methods. The range of the tools and methodological issues discussed in the study includes feature selection and semisupervised Support Vector algorithms. The real case study devoted to data-driven modeling of meteorological fields illustrates the discussed approach.

Individual Classification of Mild Cognitive Impairment Subtypes by Support Vector Machine Analysis of White Matter DTI.

BACKGROUND AND PURPOSE: MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI. MATERIALS AND METHODS: Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs. RESULTS: The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI. CONCLUSIONS: Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.

Retinal degeneration progression changes lentiviral vector cell targeting in the retina.

In normal mice, the lentiviral vector (LV) is very efficient to target the RPE cells, but transduces retinal neurons well only during development. In the present study, the tropism of LV has been investigated in the degenerating retina of mice, knowing that the retina structure changes during degeneration. We postulated that the viral transduction would be increased by the alteration of the outer limiting membrane (OLM). Two different LV pseudotypes were tested using the VSVG and the Mokola envelopes, as well as two animal models of retinal degeneration: light-damaged Balb-C and Rhodopsin knockout (Rho-/-) mice. After light damage, the OLM is altered and no significant increase of the number of transduced photoreceptors can be obtained with a LV-VSVG-Rhop-GFP vector. In the Rho-/- mice, an alteration of the OLM was also observed, but the possibility of transducing photoreceptors was decreased, probably by ongoing gliosis. The use of a ubiquitous promoter allows better photoreceptor transduction, suggesting that photoreceptor-specific promoter activity changes during late stages of photoreceptor degeneration. However, the number of targeted photoreceptors remains low. In contrast, LV pseudotyped with the Mokola envelope allows a wide dispersion of the vector into the retina (corresponding to the injection bleb) with preferential targeting of Müller cells, a situation which does not occur in the wild-type retina. Mokola-pseudotyped lentiviral vectors may serve to engineer these glial cells to deliver secreted therapeutic factors to a diseased area of the retina.

Morphometric shape analysis using learning vector quantization neural networks - an example distinguishing two microtine vole species

Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish between field and root voles from Procrustes transformed landmark coordinates on the dorsal side of the skull, which is so similar in these two species that the human eye cannot make this distinction. Properly trained neural networks misclassified only 3% of specimens. Therefore, we conclude that the capacity of learning vector quantization neural networks to analyse spatial coordinates is a powerful tool among the range of pattern recognition procedures that is available to employ the information content of geometric morphometrics.

New record of Pterotaenia fasciata (Wiedemann) (Diptera, Ulidiidae) in Brazil, a probably mechanical vector of enteric bacteria

Pterotaenia fasciata is commonly recorded in rural areas in Argentina, but during a Diptera survey study developed in a reservoir which retains storm water from polluted canals in an urban area of Taboão da Serra municipality, SP, Brazil, we could capture P. fasciata adults. Enteric bacteria Escherichia coli T. Escherich, 1885 and Proteus sp. were isolated from P. fasciata collected in traps inside the reservoir and around it. Fecal coliforms and E. coli were found in the water of the reservoir. These records suggest that a high abundance of this species at urban areas with inadequate sewage canals should reveal these muscoid dipterans as mechanical vectors of enteric bacteria.

Vector competence of Culex quinquefasciatus Say, 1823 exposed to different densities of microfilariae of Dirofilaria immitis (Leidy, 1856)

The metropolitan region of Recife, Brazil is endemic for Dirofilaria immitis and has an environment favorable to the development of Culex quinquefasciatus. The goal of this study was to evaluate the vector competence of the Cx. quinquefasciatus RECIFE population for D. immitis transmission. A total of 2,104 females of Cx. quinquefasciatus RECIFE population were exposed to different densities of D. immitis microfilariae blood meals, ranging from 1,820 to 2,900 mf/ml of blood, in a natural membrane apparatus. The results showed a variation between 92.3% and 98.8% of females fed. The exposure of the Cx. quinquefasciatus RECIFE population to different densities of microfilariae did not influence the mortality of the mosquitoes. Infective larvae from D. immitis were observed in the Malpighian tubules beginning on the 12th day, whereas larvae were observed in the head and proboscis beginning on the 13th day following infection. The vector efficiency index (VEI) presented by the mosquitoes ranged from 7.8 to 56.5. The data demonstrates that the Cx. quinquefasciatus RECIFE population has great potential for the transmission of D. immitis, as it allowed the development of the filarid until the infectious stage at the different densities of microfilariae to which it was exposed.

Spatial evaluation of larvae of Culicidae (Diptera) from different breeding sites: application of a geospatial method and implications for vector control

Spatial evaluation of Culicidae (Diptera) larvae from different breeding sites: application of a geospatial method and implications for vector control. This study investigates the spatial distribution of urban Culicidae and informs entomological monitoring of species that use artificial containers as larval habitats. Collections of mosquito larvae were conducted in the São Paulo State municipality of Santa Bárbara d' Oeste between 2004 and 2006 during house-to-house visits. A total of 1,891 samples and nine different species were sampled. Species distribution was assessed using the kriging statistical method by extrapolating municipal administrative divisions. The sampling method followed the norms of the municipal health services of the Ministry of Health and can thus be adopted by public health authorities in disease control and delimitation of risk areas. Moreover, this type of survey and analysis can be employed for entomological surveillance of urban vectors that use artificial containers as larval habitat.

Retinal degeneration progression changes lentiviral vector cell targeting in the retina

Ce travail de thèse a été réalisé au sein de l'Unité de Thérapie Génique et Biologie des Cellules Souches de l'Hôpital Jules- Gonin dans le Service d'Ophtalmologie de l'Université de Lausanne. Ce laboratoire recherche des solutions thérapeutiques pour des maladies dégénératives et incurables de la rétine comme les rétinites pigmentaires (RP). Ayant déjà montré certains résultats dans le domaine, la thérapie génique a été notre outil pour ce travail. Cette méthode se base sur le principe de remplacer un gène déficient par sa copie normale, en transportant celle-ci au coeur même du noyau par un vecteur. Il existe à l'heure actuelle différents vecteurs. Un des plus efficaces est un vecteur viral non-réplicatif : le lentivirus, dérivé de HIV-1. Celui-ci a la capacité d'intégrer le génome de la cellule cible, lui conférant ainsi un nouveau matériel génétique. Notre but a été d'établir le tropisme du lentivirus dans une rétine en dégénérescence. Ce lentivirus est connu pour transduire efficacement les cellules de l'épithélium pigmentaire rétinien dans l'oeil adulte sain, ainsi que celles de la neurorétine, mais ce, uniquement durant le développement. On sait aussi que le vecteur lentiviral présente un tropisme différent selon les enveloppes dont il est muni ; par exemple, le lentivirus avec une enveloppe Mokola est connu pour transduire les cellules gliales du système nerveux central. La rétine qui dégénère montre quant à elle des changements de sa structure qui pourraient influencer la diffusion du vecteur et/ou son tropisme. Le postulat de base a été le suivant : chez l'adulte, la transduction des neurones de la rétine via le lentivirus pourrait être facilitée par l'altération de la membrane limitante externe induite par la dégénérescence (meilleure pénétrance du virus). D'un point de vue technique, nous avons utilisé deux types distincts de modèles murins de dégénérescence rétinienne : des souris Balb/C soumises à une dose toxique de lumière et les souris Rhodopsin knockout, animaux génétiquement modifiés. Comme vecteur viral, nous avons employé deux différents pseudotypes de lentivirus (caractérisés par les enveloppes virales) avec différents promoteurs (séquence d'ADN qui initie la transduction et confère la spécificité d'expression d'un gène). En changeant l'enveloppe et le promoteur, nous avons essayé de trouver la meilleure combinaison pour augmenter l'affinité du vecteur vis-à-vis des photorécepteurs d'abord, puis vis-à-vis d'autres cellules de la rétine. Nos résultats ont montré que la membrane limitante externe est effectivement altérée chez les deux modèles de dégénérescence, mais que cette modification ne favorise pas la transduction des photorécepteurs lorsqu'on utilise un vecteur lentiviral contenant une enveloppe VSVG et un promoteur photorécepteur-spécifique ou ubiquitaire. En effet, une forte réaction gliale a été observée. Par contre, en utilisant le lentivirus avec une enveloppe Mokola et un promoteur ubiquitaire, nous avons constaté une très bonne transduction au niveau des cellules de Millier dans la rétine en dégénérescence, phénomène non observé chez les souris sauvages. Ce travail a donc permis de trouver un vecteur viral efficace pour atteindre et transduire les cellules de Miiller, ceci seulement pendant la dégénérescence de la rétine. Ces cellules, une fois transduites, pourraient être utilisées pour sécréter dans la rétine des agents thérapeutiques tels que des facteurs neurotrophiques pour soutenir la survie des photorécepteurs ou des facteurs anti-angiogéniques pour prévenir la néo-vascularisation lors de diabète ou de dégénérescence maculaire liée à l'âge. - In normal mice, the lentiviral vector (LV) is very efficient to target the RPE cells, but transduces retinal neurons well only during development. In the present study, the tropism of LV has been investigated in the degenerating retina of mice, knowing that the retina structure changes during degeneration. We postulated that the viral transduction would be increased by the alteration of the iuter limiting membrane (OLM). Two different LV pseudotypes were tested using the VSVG arid the Mokola envelopes, as well as two animal models of retinal degeneration: light-damaged Balb-C and Rhodopsin knockout (Rho-/-) mice. After light damage, the OLM is altered and no significant increase of the number of transduced photoreceptors can be obtained with a LV-VSVG-Rhop-GFP vector. In the Rho-/- mice, an altération of the OLM was also observed, but the possibility of transducing photoreceptors was decreased, probably by ongoing gliosis. The use of a ubiquitous promoter allows better photoreceptor transduction, suggesting that photoreceptór-specific promoter activity change during late stages of photoreceptor degeneration. However, the number of targeted photoreceptors remains low. In contrast, LV pseudotyped with the tfokola envelope allows a wide dispersion of the ctor into the retina (corresponding to the injection bleb) with preferential targeting of Muller cells, a situation Mc\ does ot occur in the wild- type retina. Mokola-pseudotyped lentiviral vectors may serve to engineer these glial cells to deliver secreted therapeutic factors to a diseased area of the retina.

Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition

Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques

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.