Classification of human astrocytic gliomas on the basis of gene expression: a correlated group of genes with angiogenic activity emerges as a strong predictor of subtypes.

The development of targeted treatment strategies adapted to individual patients requires identification of the different tumor classes according to their biology and prognosis. We focus here on the molecular aspects underlying these differences, in terms of sets of genes that control pathogenesis of the different subtypes of astrocytic glioma. By performing cDNA-array analysis of 53 patient biopsies, comprising low-grade astrocytoma, secondary glioblastoma (respective recurrent high-grade tumors), and newly diagnosed primary glioblastoma, we demonstrate that human gliomas can be differentiated according to their gene expression. We found that low-grade astrocytoma have the most specific and similar expression profiles, whereas primary glioblastoma exhibit much larger variation between tumors. Secondary glioblastoma display features of both other groups. We identified several sets of genes with relatively highly correlated expression within groups that: (a). can be associated with specific biological functions; and (b). effectively differentiate tumor class. One prominent gene cluster discriminating primary versus nonprimary glioblastoma comprises mostly genes involved in angiogenesis, including VEGF fms-related tyrosine kinase 1 but also IGFBP2, that has not yet been directly linked to angiogenesis. In situ hybridization demonstrating coexpression of IGFBP2 and VEGF in pseudopalisading cells surrounding tumor necrosis provided further evidence for a possible involvement of IGFBP2 in angiogenesis. The separating groups of genes were found by the unsupervised coupled two-way clustering method, and their classification power was validated by a supervised construction of a nearly perfect glioma classifier.

Where will conflicts between alien and rare species occur after climate and land-use change? A test with a novel combined modelling approach

Protecting native biodiversity against alien invasive species requires powerful methods to anticipate these invasions and to protect native species assumed to be at risk. Here, we describe how species distribution models (SDMs) can be used to identify areas predicted as suitable for rare native species and also predicted as highly susceptible to invasion by alien species, at present and under future climate and land-use scenarios. To assess the condition and dynamics of such conflicts, we developed a combined predictive modelling (CPM) approach, which predicts species distributions by combining two SDMs fitted using subsets of predictors classified as acting at either regional or local scales. We illustrate the CPM approach for an alien invader and a rare species associated to similar habitats in northwest Portugal. Combined models predict a wider variety of potential species responses, providing more informative projections of species distributions and future dynamics than traditional, non-combined models. They also provide more informative insight regarding current and future rare-invasive conflict areas. For our studied species, conflict areas of highest conservation relevance are predicted to decrease over the next decade, supporting previous reports that some invasive species may contract their geographic range and impact due to climate change. More generally, our results highlight the more informative character of the combined approach to address practical issues in conservation and management programs, especially those aimed at mitigating the impact of invasive plants, land-use and climate changes in sensitive regions

Land use regulation and productivity - Land matters: Evidence from a UK Supermarket chain

We use store-specific data for a major UK supermarket chain to estimate the impact of planning on store output. Using the quasi-natural experiment of the variation in policies between England and other UK countries, we isolate the impact of Town Centre First policies. We find that space contributes directly to store productivity; and planning policies in England directly reduce output both by reducing store sizes and forcing stores onto less productive sites. We estimate that since the late 1980s planning policies have imposed a loss of output of at least 18.3 to 24.9% - more than a “lost decade’s” growth. JEL codes: D2, L51, L81, R32.

Combining probabilistic land-use change and tree population dynamics modelling to simulate responses in mountain forests

Altitudinal tree lines are mainly constrained by temperature, but can also be influenced by factors such as human activity, particularly in the European Alps, where centuries of agricultural use have affected the tree-line. Over the last decades this trend has been reversed due to changing agricultural practices and land-abandonment. We aimed to combine a statistical land-abandonment model with a forest dynamics model, to take into account the combined effects of climate and human land-use on the Alpine tree-line in Switzerland. Land-abandonment probability was expressed by a logistic regression function of degree-day sum, distance from forest edge, soil stoniness, slope, proportion of employees in the secondary and tertiary sectors, proportion of commuters and proportion of full-time farms. This was implemented in the TreeMig spatio-temporal forest model. Distance from forest edge and degree-day sum vary through feed-back from the dynamics part of TreeMig and climate change scenarios, while the other variables remain constant for each grid cell over time. The new model, TreeMig-LAb, was tested on theoretical landscapes, where the variables in the land-abandonment model were varied one by one. This confirmed the strong influence of distance from forest and slope on the abandonment probability. Degree-day sum has a more complex role, with opposite influences on land-abandonment and forest growth. TreeMig-LAb was also applied to a case study area in the Upper Engadine (Swiss Alps), along with a model where abandonment probability was a constant. Two scenarios were used: natural succession only (100% probability) and a probability of abandonment based on past transition proportions in that area (2.1% per decade). The former showed new forest growing in all but the highest-altitude locations. The latter was more realistic as to numbers of newly forested cells, but their location was random and the resulting landscape heterogeneous. Using the logistic regression model gave results consistent with observed patterns of land-abandonment: existing forests expanded and gaps closed, leading to an increasingly homogeneous landscape.

Meta-analysis based SVM classification enables accurate detection of Alzheimer's disease across different clinical centers using FDG-PET and MRI.

The application of support vector machine classification (SVM) to combined information from magnetic resonance imaging (MRI) and [F18]fluorodeoxyglucose positron emission tomography (FDG-PET) has been shown to improve detection and differentiation of Alzheimer's disease dementia (AD) and frontotemporal lobar degeneration. To validate this approach for the most frequent dementia syndrome AD, and to test its applicability to multicenter data, we randomly extracted FDG-PET and MRI data of 28 AD patients and 28 healthy control subjects from the database provided by the Alzheimer's Disease Neuroimaging Initiative (ADNI) and compared them to data of 21 patients with AD and 13 control subjects from our own Leipzig cohort. SVM classification using combined volume-of-interest information from FDG-PET and MRI based on comprehensive quantitative meta-analyses investigating dementia syndromes revealed a higher discrimination accuracy in comparison to single modality classification. For the ADNI dataset accuracy rates of up to 88% and for the Leipzig cohort of up to 100% were obtained. Classifiers trained on the ADNI data discriminated the Leipzig cohorts with an accuracy of 91%. In conclusion, our results suggest SVM classification based on quantitative meta-analyses of multicenter data as a valid method for individual AD diagnosis. Furthermore, combining imaging information from MRI and FDG-PET might substantially improve the accuracy of AD diagnosis.

The IC3D classification of the corneal dystrophies.

BACKGROUND: The recent availability of genetic analyses has demonstrated the shortcomings of the current phenotypic method of corneal dystrophy classification. Abnormalities in different genes can cause a single phenotype, whereas different defects in a single gene can cause different phenotypes. Some disorders termed corneal dystrophies do not appear to have a genetic basis. PURPOSE: The purpose of this study was to develop a new classification system for corneal dystrophies, integrating up-to-date information on phenotypic description, pathologic examination, and genetic analysis. METHODS: The International Committee for Classification of Corneal Dystrophies (IC3D) was created to devise a current and accurate nomenclature. RESULTS: This anatomic classification continues to organize dystrophies according to the level chiefly affected. Each dystrophy has a template summarizing genetic, clinical, and pathologic information. A category number from 1 through 4 is assigned, reflecting the level of evidence supporting the existence of a given dystrophy. The most defined dystrophies belong to category 1 (a well-defined corneal dystrophy in which a gene has been mapped and identified and specific mutations are known) and the least defined belong to category 4 (a suspected dystrophy where the clinical and genetic evidence is not yet convincing). The nomenclature may be updated over time as new information regarding the dystrophies becomes available. CONCLUSIONS: The IC3D Classification of Corneal Dystrophies is a new classification system that incorporates many aspects of the traditional definitions of corneal dystrophies with new genetic, clinical, and pathologic information. Standardized templates provide key information that includes a level of evidence for there being a corneal dystrophy. The system is user-friendly and upgradeable and can be retrieved on the website www.corneasociety.org/ic3d.

Clustering and hot spot detection in socio-economic spatio-temporal data

Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.

Hypertensive portal colopathy in schistosomiasis mansoni: proposal for a classification

Portal hypertension is a frequent complication of chronic liver disease, detected not only in schistosomiasis, but also in cirrhosis of any etiology. Vascular alterations in the colonic mucosa are a potential source for acute or chronic bleeding and have been observed in patients with portal hypertension. The purpose of this prospective study was to describe and propose a classification for the vascular alterations of portal hypertension in the colonic mucosa among patients with hepatosplenic schistosomiasis mansoni. One or more alterations of portal colopathy were observed in all patients and they were classified according to their intensity, obeying the classification proposed by the authors. Portal colopathy is an important finding in hepatosplenic schistosomiasis and might be the cause of lower gastrointestinal bleeding in patients with severe portal hypertension.

Plasma membrane cyclic nucleotide gated calcium channels control land plant thermal sensing and acquired thermotolerance.

Typically at dawn on a hot summer day, land plants need precise molecular thermometers to sense harmless increments in the ambient temperature to induce a timely heat shock response (HSR) and accumulate protective heat shock proteins in anticipation of harmful temperatures at mid-day. Here, we found that the cyclic nucleotide gated calcium channel (CNGC) CNGCb gene from Physcomitrella patens and its Arabidopsis thaliana ortholog CNGC2, encode a component of cyclic nucleotide gated Ca(2+) channels that act as the primary thermosensors of land plant cells. Disruption of CNGCb or CNGC2 produced a hyper-thermosensitive phenotype, giving rise to an HSR and acquired thermotolerance at significantly milder heat-priming treatments than in wild-type plants. In an aequorin-expressing moss, CNGCb loss-of-function caused a hyper-thermoresponsive Ca(2+) influx and altered Ca(2+) signaling. Patch clamp recordings on moss protoplasts showed the presence of three distinct thermoresponsive Ca(2+) channels in wild-type cells. Deletion of CNGCb led to a total absence of one and increased the open probability of the remaining two thermoresponsive Ca(2+) channels. Thus, CNGC2 and CNGCb are expected to form heteromeric Ca(2+) channels with other related CNGCs. These channels in the plasma membrane respond to increments in the ambient temperature by triggering an optimal HSR, leading to the onset of plant acquired thermotolerance.

IEF pattern classification-derived criteria for the identification of epoetin-delta in urine.

Epoetin-delta (Dynepo Shire Pharmaceuticals, Basing stoke, UK) is a synthetic form of erythropoietin (EPO) whose resemblance with endogenous EPO makes it hard to identify using the classical identification criteria. Urine samples collected from six healthy volunteers treated with epoetin-delta injections and from a control population were immuno-purified and analyzed with the usual IEF method. On the basis of the EPO profiles integration, a linear multivariate model was computed for discriminant analysis. For each sample, a pattern classification algorithm returned a bands distribution and intensity score (bands intensity score) saying how representative this sample is of one of the two classes, positive or negative. Effort profiles were also integrated in the model. The method yielded a good sensitivity versus specificity relation and was used to determine the detection window of the molecule following multiple injections. The bands intensity score, which can be generalized to epoetin-alpha and epoetin-beta, is proposed as an alternative criterion and a supplementary evidence for the identification of EPO abuse.

Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models.

BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60-80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.

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.

Indicators of inequality: Classification and selection of ethnic health disparity indicators

Classification and selection of ethnic disparity health indicators in New Zealand

Proposal of a new classification for optimising outcome assessment following partial cricotracheal resections in severe pediatric subglottic stenosis.

OBJECTIVE: Creation of a patent subglottic airway after partial cricotracheal resection (PCTR) may not always result in successful decannulation due to associated parameters such as co-morbidity and/or glottic involvement. We classified patients after incorporating these additional parameters into the original Myer-Cotton classification to assess whether this could better predict the outcome measures after PCTR. METHODS: One hundred children with Myer-Cotton grade III or IV subglottic stenosis who underwent PCTR between 1978 and 2008 were identified from a prospectively collected database. The patients were classified into four groups based on the association of co-morbidity and/or glottic involvement. Delay in decannulation, revision open surgery and rates of decannulation were the outcome measures compared between the groups. RESULTS: There were 68 children with Myer-Cotton grade III and 32 children with grade IV stenosis. Based on the new classification, there were 36 children with isolated SGS, 31 with associated co-morbidity, 19 with associated glottic involvement and 14 children with both co-morbidity and glottic involvement. A trend towards less optimal results was noticed with the association of co-morbidity and/or glottic involvement. Statistical significance was reached for maximum decannulation failure in the group with both co-morbidity and glottic involvement. Delayed decannulation significantly correlated in the group with associated glottic involvement. CONCLUSION: This new classification is relatively simple and aimed at providing more accurate and uniform prognostic information to both patients and surgeons when dealing with the whole spectrum of severe SGS.

Briefing 29: NCMP data 2008/9, East of England: ONS SOA classification

One in a series of six data briefings based on regional-level analysis of data from the National Child Measurement Programme (NCMP) undertaken by the National Obesity Observatory (NOO). The briefings are intended to complement the headline results for the region published in January 2010, at Quick Link 20510.