Soil fungal communities of grasslands are environmentally structured at a regional scale in the Alps.

Studying patterns of species distributions along elevation gradients is frequently used to identify the primary factors that determine the distribution, diversity and assembly of species. However, despite their crucial role in ecosystem functioning, our understanding of the distribution of below-ground fungi is still limited, calling for more comprehensive studies of fungal biogeography along environmental gradients at various scales (from regional to global). Here, we investigated the richness of taxa of soil fungi and their phylogenetic diversity across a wide range of grassland types along a 2800 m elevation gradient at a large number of sites (213), stratified across a region of the Western Swiss Alps (700 km(2)). We used 454 pyrosequencing to obtain fungal sequences that were clustered into operational taxonomic units (OTUs). The OTU diversity-area relationship revealed uneven distribution of fungal taxa across the study area (i.e. not all taxa are everywhere) and fine-scale spatial clustering. Fungal richness and phylogenetic diversity were found to be higher in lower temperatures and higher moisture conditions. Climatic and soil characteristics as well as plant community composition were related to OTU alpha, beta and phylogenetic diversity, with distinct fungal lineages suggesting distinct ecological tolerances. Soil fungi, thus, show lineage-specific biogeographic patterns, even at a regional scale, and follow environmental determinism, mediated by interactions with plants.

Classification and management of seeds in retinoblastoma. Ellsworth Lecture Ghent August 24th 2013.

Retinoblastoma has the unique capacity to accelerate its own intra-ocular propagation by adopting semi-solid or even liquid growth properties through seeding. Until recently, the presence of any degree of seeding was mostly incompatible with successful conservative management, due to the multiresistant nature of the seeds. Surprisingly, this well-recognized retinoblastoma behavior has not undergone any detailed description of seeding patterns and anatomic sites. In this paper, we describe the phenotypic variability of seeds across the four possible intraocular seeding compartments and classify them into three fundamental types: namely dust, spheres, and clouds. We also provide an overview of the different therapeutic strategies developed for seeding, with special attention to intravitreal chemotherapy as the treatment of choice for vitreous and retro-hyaloid seeding. Finally, we propose criteria to enable assessment of the response to treatment by reporting seed regression patterns, as well as a clinical grading system for the retinal toxicity observed following intravitreal melphalan.

An ecoregional classification for the state of Roraima, Brazil: the importance of landscape in malaria biology

Understanding the different background landscapes in which malaria transmission occurs is fundamental to understanding malaria epidemiology and to designing effective local malaria control programs. Geology, geomorphology, vegetation, climate, land use, and anopheline distribution were used as a basis for an ecological classification of the state of Roraima, Brazil, in the northern Amazon Basin, focused on the natural history of malaria and transmission. We used unsupervised maximum likelihood classification, principal components analysis, and weighted overlay with equal contribution analyses to fine-scale thematic maps that resulted in clustered regions. We used ecological niche modeling techniques to develop a fine-scale picture of malaria vector distributions in the state. Eight ecoregions were identified and malaria-related aspects are discussed based on this classification, including 5 types of dense tropical rain forest and 3 types of savannah. Ecoregions formed by dense tropical rain forest were named as montane (ecoregion I), submontane (II), plateau (III), lowland (IV), and alluvial (V). Ecoregions formed by savannah were divided into steppe (VI, campos de Roraima), savannah (VII, cerrado), and wetland (VIII, campinarana). Such ecoregional mappings are important tools in integrated malaria control programs that aim to identify specific characteristics of malaria transmission, classify transmission risk, and define priority areas and appropriate interventions. For some areas, extension of these approaches to still-finer resolutions will provide an improved picture of malaria transmission patterns.

Analysis of prion strains by PrPSc profiling in sporadic Creutzfeldt-Jakob disease.

BACKGROUND: Prion diseases are a group of invariably fatal neurodegenerative disorders affecting humans and a wide range of mammals. An essential part of the infectious agent, termed the prion, is composed of an abnormal isoform (PrPSc) of a host-encoded normal cellular protein (PrPC). The conversion of PrPC to PrPSc is thought to play a crucial role in the development of prion diseases and leads to PrPSc deposition, mainly in the central nervous system. Sporadic Creutzfeldt-Jakob disease (sCJD), the most common form of human prion disease, presents with a marked clinical heterogeneity. This diversity is accompanied by a molecular signature which can be defined by histological, biochemical, and genetic means. The molecular classification of sCJD is an important tool to aid in the understanding of underlying disease mechanisms and the development of therapy protocols. Comparability of classifications is hampered by disparity of applied methods and inter-observer variability. METHODS AND FINDINGS: To overcome these difficulties, we developed a new quantification protocol for PrPSc by using internal standards on each Western blot, which allows for generation and direct comparison of individual PrPSc profiles. By studying PrPSc profiles and PrPSc type expression within nine defined central nervous system areas of 50 patients with sCJD, we were able to show distinct PrPSc distribution patterns in diverse subtypes of sCJD. Furthermore, we were able to demonstrate the co-existence of more than one PrPSc type in individuals with sCJD in about 20% of all patients and in more than 50% of patients heterozygous for a polymorphism on codon 129 of the gene encoding the prion protein (PRNP). CONCLUSION: PrPSc profiling represents a valuable tool for the molecular classification of human prion diseases and has important implications for their diagnosis by brain biopsy. Our results show that the co-existence of more than one PrPSc type might be influenced by genetic and brain region-specific determinants. These findings provide valuable insights into the generation of distinct PrPSc types.

Does a shift in host plants trigger speciation in the Alpine leaf beetle Oreina speciosissima (Coleoptera, Chrysomelidae)?

Background: Within the Coleoptera, the largest order in the animal kingdom, the exclusively herbivorous Chrysomelidae are recognized as one of the most species rich beetle families. The evolutionary processes that have fueled radiation into the more than thirty-five thousand currently recognized leaf beetle species remain partly unresolved. The prominent role of leaf beetles in the insect world, their omnipresence across all terrestrial biomes and their economic importance as common agricultural pest organisms make this family particularly interesting for studying the mechanisms that drive diversification. Here we specifically focus on two ecotypes of the alpine leaf beetle Oreina speciosissima (Scop.), which have been shown to exhibit morphological differences in male genitalia roughly corresponding to the subspecies Oreina speciosissima sensu stricto and Oreina speciosissima troglodytes. In general the two ecotypes segregate along an elevation gradient and by host plants: Oreina speciosissima sensu stricto colonizes high forb vegetation at low altitude and Oreina speciosissima troglodytes is found in stone run vegetation at higher elevations. Both host plants and leaf beetles have a patchy geographical distribution. Through use of gene sequencing and genome fingerprinting (AFLP) we analyzed the genetic structure and habitat use of Oreina speciosissima populations from the Swiss Alps to examine whether the two ecotypes have a genetic basis. By investigating a wide range of altitudes and focusing on the structuring effect of habitat types, we aim to provide answers regarding the factors that drive adaptive radiation in this phytophagous leaf beetle.Results: While little phylogenetic resolution was observed based on the sequencing of four DNA regions, the topology and clustering resulting from AFLP genotyping grouped specimens according to their habitat, mostly defined by plant associations. A few specimens with intermediate morphologies clustered with one of the two ecotypes or formed separate clusters consistent with habitat differences. These results were discussed in an ecological speciation framework.Conclusions: The question of whether this case of ecological differentiation occurred in sympatry or allopatry remains open. Still, the observed pattern points towards ongoing divergence between the two ecotypes which is likely driven by a recent shift in host plant use.

A Classification of Tools for Learning Logic

A table showing a comparison and classification of tools (intelligent tutoring systems) for e-learning of Logic at a college level.

Health problems among detainees in Switzerland: a study using the ICPC-2 classification.

BACKGROUND: Little is known about the health status of prisoners in Switzerland. The aim of this study was to provide a detailed description of the health problems presented by detainees in Switzerland's largest remand prison. METHODS: In this retrospective cross-sectional study we reviewed the health records of all detainees leaving Switzerland's largest remand prison in 2007. The health problems were coded using the International Classification for Primary Care (ICPC-2). Analyses were descriptive, stratified by gender. RESULTS: A total of 2195 health records were reviewed. Mean age was 29.5 years (SD 9.5); 95% were male; 87.8% were migrants. Mean length of stay was 80 days (SD 160). Illicit drug use (40.2%) and mental health problems (32.6%) were frequent, but most of these detainees (57.6%) had more generic primary care problems, such as skin (27.0%), infectious diseases (23.5%), musculoskeletal (19.2%), injury related (18.3%), digestive (15.0%) or respiratory problems (14.0%). Furthermore, 7.9% reported exposure to violence during arrest by the police. CONCLUSION: Morbidity is high in this young, predominantly male population of detainees, in particular in relation to substance abuse. Other health problems more commonly seen in general practice are also frequent. These findings support the further development of coordinated primary care and mental health services within detention centers.

Pathophysiology and classification of the vibration white finger.

Skin, arteries and nerves of the upper extremities can be affected by vibration exposure. Recent advances in skin and vascular biology as well as new investigative methods, have shown that neurovascular symptoms may be due to different vascular and neurological disorders which should be differentiated if proper management is to be evaluated. Three types of vascular disorder can be observed in the vibration white finger: digital organic microangiopathy, a digital vasospastic phenomenon and arterial thrombosis in the upper extremities. An imbalance between endothelin-1 and calcitonin-gene-related peptide is probably responsible for the vasospastic phenomenon. Moreover, paresthesiae can be due to either a diffuse vibration neuropathy or a carpal tunnel syndrome. A precise diagnosis is then necessary to adapt the treatment to individual cases. A classification describing the type and severity of the vascular lesions is presented. Asymptomatic lesions are included for adequate epidemiological studies and risk assessment of vibrating tools. Monitoring of vibration exposed workers should include not only a questionnaire about symptoms, but also a clinical evaluation including diagnostic tests for the screening of early asymptomatic neurovascular injuries.

Cluster kernels for semisupervised classification of VHR urban images

In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and workable by unexperimented users.

Scene Classification Using a Hybrid Generative/Discriminative Approach

We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

Molecular epidemiology reveals long-term changes in HIV type 1 subtype B transmission in Switzerland.

BACKGROUND: Sequence data from resistance testing offer unique opportunities to characterize the structure of human immunodeficiency virus (HIV) infection epidemics. METHODS: We analyzed a representative set of HIV type 1 (HIV-1) subtype B pol sequences from 5700 patients enrolled in the Swiss HIV Cohort Study. We pooled these sequences with the same number of sequences from foreign epidemics, inferred a phylogeny, and identified Swiss transmission clusters as clades having a minimal size of 10 and containing >or=80% Swiss sequences. RESULTS: More than one-half of Swiss patients were included within 60 transmission clusters. Most transmission clusters were significantly dominated by specific transmission routes, which were used to identify the following patient groups: men having sex with men (MSM) (38 transmission clusters; average cluster size, 29 patients) or patients acquiring HIV through heterosexual contact (HETs) and injection drug users (IDUs) (12 transmission clusters; average cluster size, 144 patients). Interestingly, there were no transmission clusters dominated by sequences from HETs only. Although 44% of all HETs who were infected between 1983 and 1986 clustered with injection drug users, this percentage decreased to 18% for 2003-2006 (P<.001), indicating a diminishing role of injection drug users in transmission among HETs over time. CONCLUSIONS: Our analysis suggests (1) the absence of a self-sustaining epidemic of HIV-1 subtype B in HETs in Switzerland and (2) a temporally decreasing clustering of HIV infections in HETs and IDUs.

A framework for assessing the scale of influence of environmental factors on ecological patterns

The distribution of living organisms, habitats and ecosystems is primarily driven by abiotic environmental factors that are spatially structured. Assessing the spatial structure of environmental factors, e.g., through spatial autocorrelation analyses (SAC), can thus help us understand their scale of influence on the distribution of organisms, habitats, and ecosystems. Yet SAC analyses of environmental factors are still rarely performed in biogeographic studies. Here, we describe a novel framework that combines SAC and statistical clustering to identify scales of spatial patterning of environmental factors, which can then be interpreted as the scales at which those factors influence the geographic distribution of biological and ecological features. We illustrate this new framework with datasets at different spatial or thematic resolutions. This framework is conceptually and statistically robust, providing a valuable approach to tackle a wide range of issues in ecological and environmental research and particularly when building predictors for ecological models. The new framework can significantly promote fundamental research on all spatially-structured ecological patterns. It can also foster research and application in such fields as global change ecology, conservation planning, and landscape management.

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Improving Clustering Algorithms for Image Segmentation using Contour and Region Information

In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach

Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.