Nosology and classification of genetic skeletal disorders: 2010 revision.

Genetic disorders involving the skeletal system arise through disturbances in the complex processes of skeletal development, growth and homeostasis and remain a diagnostic challenge because of their variety. The Nosology and Classification of Genetic Skeletal Disorders provides an overview of recognized diagnostic entities and groups them by clinical and radiographic features and molecular pathogenesis. The aim is to provide the Genetics, Pediatrics and Radiology community with a list of recognized genetic skeletal disorders that can be of help in the diagnosis of individual cases, in the delineation of novel disorders, and in building bridges between clinicians and scientists interested in skeletal biology. In the 2010 revision, 456 conditions were included and placed in 40 groups defined by molecular, biochemical, and/or radiographic criteria. Of these conditions, 316 were associated with mutations in one or more of 226 different genes, ranging from common, recurrent mutations to "private" found in single families or individuals. Thus, the Nosology is a hybrid between a list of clinically defined disorders, waiting for molecular clarification, and an annotated database documenting the phenotypic spectrum produced by mutations in a given gene. The Nosology should be useful for the diagnosis of patients with genetic skeletal diseases, particularly in view of the information flood expected with the novel sequencing technologies; in the delineation of clinical entities and novel disorders, by providing an overview of established nosologic entities; and for scientists looking for the clinical correlates of genes, proteins and pathways involved in skeletal biology. © 2011 Wiley-Liss, Inc.

Using a Bayesian method to assign individuals to karyotypic taxa in shrew hybrid zones.

Individuals sampled in hybrid zones are usually analysed according to their sampling locality, morphology, behaviour or karyotype. But the increasing availability of genetic information more and more favours its use for individual sorting purposes and numerous assignment methods based on the genetic composition of individuals have been developed. The shrews of the Sorex araneus group offer good opportunities to test the genetic assignment on individuals identified by their karyotype. Here we explored the potential and efficiency of a Bayesian assignment method combined or not with a reference dataset to study admixture and individual assignment in the difficult context of two hybrid zones between karyotypic species of the Sorex araneus group. As a whole, we assigned more than 80% of the individuals to their respective karyotypic categories (i.e. 'pure' species or hybrids). This assignment level is comparable to what was obtained for the same species away from hybrid zones. Additionally, we showed that the assignment result for several individuals was strongly affected by the inclusion or not of a reference dataset. This highlights the importance of such comparisons when analysing hybrid zones. Finally, differences between the admixture levels detected in both hybrid zones support the hypothesis of an impact of chromosomal rearrangements on gene flow.

A hybrid zone with coincident clines for autosomal and sex-specific markers in the Sorex araneus group.

In hybrid zones, endogenous counter-selection of hybrids is usually first expressed as reduced fertility or viability in hybrids of the heterogametic sex, a mechanism known as Haldane's rule. This phenomenon often leads to a differential of gene flow between sex-linked markers. Here, we address the possibility of a differential gene flow for Y chromosome, mtDNA and autosomal markers across the hybrid zone between the genetically and chromosomally well-differentiated species Sorex antinorii and Sorex araneus race Vaud. Intermarker comparison clearly revealed coincidental centre and very abrupt clines for all three types of markers. The overall level of genetic differentiation between the two species must be strong enough to hinder asymmetric introgression. Cyto-nuclear mismatches were also observed in the centre of hybrid zone. The significantly lower number of mismatches observed in males than in females possibly results from Y chromosome-mtDNA interactions. Results are compared with those previously reported in another hybrid zone between S. antinori and S. araneus race Cordon.

Alps, genes, and chromosomes: their role in the formation of species in the Sorex araneus group (Mammalia, Insectivora), as inferred from two hybrid zones.

During the Pleistocene glaciations, the Alps were an efficient barrier to gene flow between isolated populations, often leading to allopatric speciation. Afterwards, the Alps strongly influenced the post-glacial recolonization of Europe and represent a major suture zone between differentiated populations. Two hybrid zones in the Swiss and French Alps between genetically and chromosomally well-differentiated species-the Valais shrew, Sorex antinorii, and the common shrew, S. araneus-were studied karyotypically and by analyzing the distribution of seven microsatellite loci. In the center of the Haslital hybrid zone the two species coexist over a distance of 900 m. Hybrid karyotypes, among them the most complex known in Sorex, are rare. F-statistics based on microsatellite data revealed a strong heterozygote deficit only in the center of the zone, due to the sympatric distribution of the two species with little hybridization between them. Structuring within the species (both F(IS) and F(ST)) was low. An hierarchical analysis showed a high level of interspecific differentiation. Results were compared with those previously reported in another hybrid zone located at Les Houches in the French Alps. Genetic structuring within and between species was comparable in both hybrid zones, although chromosomal incompatibilities are more important in Haslital, where a linkage block of the race-specific chromosomes should additionally impede gene flow. Evidence for a more restricted gene flow in Haslital comes from the genetically intermediate hybrid karyotypes, whereas in Les Houches, hybrid karyotypes are genetically identical to individuals of the pure karyotypic races. Genic and chromosomal introgression was observed in Les Houches, but not in Haslital. The possible influence of a river, separating the two species at Les Houches, on gene flow is discussed.

Urban image classification with semisupervised multiscale cluster kernels

This paper presents a semisupervised support vector machine (SVM) that integrates the information of both labeled and unlabeled pixels efficiently. Method's performance is illustrated in the relevant problem of very high resolution image classification of urban areas. The SVM is trained with the linear combination of two kernels: a base kernel working only with labeled examples is deformed by a likelihood kernel encoding similarities between labeled and unlabeled examples. Results obtained on very high resolution (VHR) multispectral and hyperspectral images show the relevance of the method in the context of urban image classification. Also, its simplicity and the few parameters involved make the method versatile and workable by unexperienced users.

Automatic Mallampati Classification Using Active Appearance Models

Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.

Microsatellites can be misleading: an empirical and simulation study.

It has been long recognized that highly polymorphic genetic markers can lead to underestimation of divergence between populations when migration is low. Microsatellite loci, which are characterized by extremely high mutation rates, are particularly likely to be affected. Here, we report genetic differentiation estimates in a contact zone between two chromosome races of the common shrew (Sorex araneus), based on 10 autosomal microsatellites, a newly developed Y-chromosome microsatellite, and mitochondrial DNA. These results are compared to previous data on proteins and karyotypes. Estimates of genetic differentiation based on F- and R-statistics are much lower for autosomal microsatellites than for all other genetic markers. We show by simulations that this discrepancy stems mainly from the high mutation rate of microsatellite markers for F-statistics and from deviations from a single-step mutation model for R-statistics. The sex-linked genetic markers show that all gene exchange between races is mediated by females. The absence of male-mediated gene flow most likely results from male hybrid sterility.

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.

A vertebrate reproductive system involving three ploidy levels : hybrid origin of triploids in a contact zone of diploid and tetraploid green toads (Bufo viridis subgroup)

The rise and consequences of polyploidy in vertebrates, whose origin was associated with genome duplications, may be best studied in natural diploid and polyploid populations. In a diploid/tetraploid (2n/4n) geographic contact zone of Palearctic green toads in northern Kyrgyzstan, we examine 4ns and triploids (3n) of unknown genetic composition and origins. Using mitochondrial and nuclear sequence, and nuclear microsatellite markers in 84 individuals, we show that 4n (Bufo pewzowi) are allopolyploids, with a geographically proximate 2n species (B. turanensis) being their maternal ancestor and their paternal ancestor as yet unidentified. Local 3n forms arise through hybridization. Adult 3n mature males (B. turanensis mtDNA) have 2n mothers and 4n fathers, but seem distinguishable by nuclear profiles from partly aneuploid 3n tadpoles (with B. pewzowi mtDNA). These observations suggest multiple pathways to the formation of triploids in the contact zone, involving both reciprocal origins. To explain the phenomena in the system, we favor a hypothesis where 3n males (with B. turanensis mtDNA) backcross with 4n and 2n females. Together with previous studies of a separately evolved, sexually reproducing 3n lineage, these observations reveal complex reproductive interactions among toads of different ploidy levels and multiple pathways to the evolution of polyploid lineages.

Anti-tumor necrosis factor drug survival in axial spondyloarthritis is independent of the classification criteria.

To compare the impact of meeting specific classification criteria [modified New York (mNY), European Spondyloarthropathy Study Group (ESSG), and Assessment of SpondyloArthritis international Society (ASAS) criteria] on anti-tumor necrosis factor (anti-TNF) drug retention, and to determine predictive factors of better drug survival. All patients fulfilling the ESSG criteria for axial spondyloarthritis (SpA) with available data on the axial ASAS and mNY criteria, and who had received at least one anti-TNF treatment were retrospectively retrieved in a single academic institution in Switzerland. Drug retention was computed using survival analysis (Kaplan-Meier), adjusted for potential confounders. Of the 137 patients classified as having axial SpA using the ESSG criteria, 112 also met the ASAS axial SpA criteria, and 77 fulfilled the mNY criteria. Drug retention rates at 12 and 24 months for the first biologic therapy were not significantly different between the diagnostic groups. Only the small ASAS non-classified axial SpA group (25 patients) showed a nonsignificant trend toward shorter drug survival. Elevated CRP level, but not the presence of bone marrow edema on magnetic resonance imaging (MRI) scans, was associated with significantly better drug retention (OR 7.9, ICR 4-14). In this cohort, anti-TNF drug survival was independent of the classification criteria. Elevated CRP level, but not positive MRI, was associated with better drug retention.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.