Wavelet-denoising of electroencephalogram and the absolute slope method: a new tool to improve electroencephalographic localization and lateralization

OBJECTIVE: In ictal scalp electroencephalogram (EEG) the presence of artefacts and the wide ranging patterns of discharges are hurdles to good diagnostic accuracy. Quantitative EEG aids the lateralization and/or localization process of epileptiform activity. METHODS: Twelve patients achieving Engel Class I/IIa outcome following temporal lobe surgery (1 year) were selected with approximately 1-3 ictal EEGs analyzed/patient. The EEG signals were denoised with discrete wavelet transform (DWT), followed by computing the normalized absolute slopes and spatial interpolation of scalp topography associated to detection of local maxima. For localization, the region with the highest normalized absolute slopes at the time when epileptiform activities were registered (>2.5 times standard deviation) was designated as the region of onset. For lateralization, the cerebral hemisphere registering the first appearance of normalized absolute slopes >2.5 times the standard deviation was designated as the side of onset. As comparison, all the EEG episodes were reviewed by two neurologists blinded to clinical information to determine the localization and lateralization of seizure onset by visual analysis. RESULTS: 16/25 seizures (64%) were correctly localized by the visual method and 21/25 seizures (84%) by the quantitative EEG method. 12/25 seizures (48%) were correctly lateralized by the visual method and 23/25 seizures (92%) by the quantitative EEG method. The McNemar test showed p=0.15 for localization and p=0.0026 for lateralization when comparing the two methods. CONCLUSIONS: The quantitative EEG method yielded significantly more seizure episodes that were correctly lateralized and there was a trend towards more correctly localized seizures. SIGNIFICANCE: Coupling DWT with the absolute slope method helps clinicians achieve a better EEG diagnostic accuracy.

A multiplex PCR for the simultaneous detection and genotyping of the Echinococcus granulosus complex.

Echinococcus granulosus is characterized by high intra-specific variability (genotypes G1-G10) and according to the new molecular phylogeny of the genus Echinococcus, the E. granulosus complex has been divided into E. granulosus sensu stricto (G1-G3), E. equinus (G4), E. ortleppi (G5), and E. canadensis (G6-G10). The molecular characterization of E. granulosus isolates is fundamental to understand the spatio-temporal epidemiology of this complex in many endemic areas with the simultaneous occurrence of different Echinococcus species and genotypes. To simplify the genotyping of the E. granulosus complex we developed a single-tube multiplex PCR (mPCR) allowing three levels of discrimination: (i) Echinococcus genus, (ii) E. granulosus complex in common, and (iii) the specific genotype within the E. granulosus complex. The methodology was established with known DNA samples of the different strains/genotypes, confirmed on 42 already genotyped samples (Spain: 22 and Bulgaria: 20) and then successfully applied on 153 unknown samples (Tunisia: 114, Algeria: 26 and Argentina: 13). The sensitivity threshold of the mPCR was found to be 5 ng Echinoccoccus DNA in a mixture of up to 1 µg of foreign DNA and the specificity was 100% when template DNA from closely related members of the genus Taenia was used. Additionally to DNA samples, the mPCR can be carried out directly on boiled hydatid fluid or on alkaline-lysed frozen or fixed protoscoleces, thus avoiding classical DNA extractions. However, when using Echinococcus eggs obtained from fecal samples of infected dogs, the sensitivity of the mPCR was low (<40%). Thus, except for copro analysis, the mPCR described here has a high potential for a worldwide application in large-scale molecular epidemiological studies on the Echinococcus genus.

Microscopic analysis of chromatin localization and dynamics in C. elegans

During development, the genome undergoes drastic reorganization within the nuclear space. To determine tridimensional genome folding, genome-wide techniques (damID/Hi-C) can be applied using cell populations, but these have to be calibrated using microscopy and single-cell analysis of gene positioning. Moreover, the dynamic behavior of chromatin has to be assessed on living samples. Combining fast stereotypic development with easy genetics and microscopy, the nematode C. elegans has become a model of choice in recent years to study changes in nuclear organization during cell fate acquisition. Here we present two complementary techniques to evaluate nuclear positioning of genes either by fluorescence in situ hybridization in fixed samples or in living worm embryos using the GFP-lacI/lacO chromatin-tagging system.

Assessing and mapping LD and SLM to directly support the planning and scaling up of SLM interventions to combat desertification

Global investment in Sustainable Land Management (SLM) has been substantial, but knowledge gaps remain. Overviews of where land degradation (LD) is taking place and how land users are addressing the problem using SLM are still lacking for most individual countries and regions. Relevant maps focus more on LD than SLM, and they have been compiled using different methods. This makes it impossible to compare the benefits of SLM interventions and prevents informed decision-making on how best to invest in land. To fill this knowledge gap, a standardised mapping method has been collaboratively developed by the World Overview of Conservation Approaches and Technologies (WOCAT), FAO’s Land Degradation Assessment in Drylands (LADA) project, and the EU’s Mitigating Desertification and Remediating Degraded Land (DESIRE) project. The method generates information on the distribution and characteristics of LD and SLM activities and can be applied at the village, national, or regional level. It is based on participatory expert assessment, documents, and surveys. These data sources are spatially displayed across a land-use systems base map. By enabling mapping of the DPSIR framework (Driving Forces-Pressures-State-Impacts-Responses) for degradation and conservation, the method provides key information for decision-making. It may also be used to monitor LD and conservation following project implementation. This contribution explains the mapping method, highlighting findings made at different levels (national and local) in South Africa and the Mediterranean region. Keywords: Mapping, Decision Support, Land Degradation, Sustainable Land Management, Ecosystem Services, Participatory Expert Assessment

Simultaneous detection and discrimination of virulent and benign Dichelobacter nodosus in sheep of flocks affected by foot rot and in clinically healthy flocks by competitive real-time PCR.

Ovine foot rot caused by Dichelobacter nodosus is affecting sheep worldwide. The current diagnostic methods are difficult and cumbersome. Here, we present a competitive real-time PCR based on allelic discrimination of the protease genes aprV2 and aprB2. This method allows direct detection and differentiation of virulent and benign D. nodosus from interdigital skin swabs in a single test. Clinically affected sheep harbored high loads of only virulent strains, whereas healthy sheep had lower loads of predominantly benign strains.

Classifying and mapping the urban transition in Vietnam

The urban transition almost always involves wrenching social adjustment as small agricultural communities are forced to adjust rapidly to industrial ways of life. Large-scale in-migration of young people, usually from poor regions, creates enormous demand and expectations for community and social services. One immediate problem planners face in approaching this challenge is how to define, differentiate, and map what is rural, urban, and transitional (i.e., peri-urban). This project established an urban classification for Vietnam by using national census and remote sensing data to identify and map the smallest administrative units for which data are collected as rural, peri-urban, urban, or urban core. We used both natural and human factors in the quantitative model: income from agriculture, land under agriculture and forests, houses with modern sanitation, and the Normalized Difference Vegetation Index. Model results suggest that in 2006, 71% of Vietnam's 10,891 communes were rural, 18% peri-urban, 3% urban, and 4% urban core. Of the communes our model classified as peri-urban, 61% were classified by the Vietnamese government as rural. More than 7% of Vietnam's land area can be classified as peri-urban and approximately 13% of its population (more than 11 million people) lives in peri-urban areas. We identified and mapped three types of peri-urban places: communes in the periphery of large towns and cities; communes along highways; and communes associated with provincial administration or home to industrial, energy, or natural resources projects (e.g., mining). We validated this classification based on ground observations, analyses of multi-temporal night-time lights data, and an examination of road networks. The model provides a method for rapidly assessing the rural–urban nature of places to assist planners in identifying rural areas undergoing rapid change with accompanying needs for investments in building, sanitation, road infrastructure, and government institutions.

3D Intervertebral Disc Localization and Segmentation from MR Images by Data-Driven Regression and Classification

In this paper we propose a new fully-automatic method for localizing and segmenting 3D intervertebral discs from MR images, where the two problems are solved in a unified data-driven regression and classification framework. We estimate the output (image displacements for localization, or fg/bg labels for segmentation) of image points by exploiting both training data and geometric constraints simultaneously. The problem is formulated in a unified objective function which is then solved globally and efficiently. We validate our method on MR images of 25 patients. Taking manually labeled data as the ground truth, our method achieves a mean localization error of 1.3 mm, a mean Dice metric of 87%, and a mean surface distance of 1.3 mm. Our method can be applied to other localization and segmentation tasks.

Localization and Segmentation of 3D Intervertebral Discs in MR Images by Data Driven Estimation

This paper addresses the problem of fully-automatic localization and segmentation of 3D intervertebral discs (IVDs) from MR images. Our method contains two steps, where we first localize the center of each IVD, and then segment IVDs by classifying image pixels around each disc center as foreground (disc) or background. The disc localization is done by estimating the image displacements from a set of randomly sampled 3D image patches to the disc center. The image displacements are estimated by jointly optimizing the training and test displacement values in a data-driven way, where we take into consideration both the training data and the geometric constraint on the test image. After the disc centers are localized, we segment the discs by classifying image pixels around disc centers as background or foreground. The classification is done in a similar data-driven approach as we used for localization, but in this segmentation case we are aiming to estimate the foreground/background probability of each pixel instead of the image displacements. In addition, an extra neighborhood smooth constraint is introduced to enforce the local smoothness of the label field. Our method is validated on 3D T2-weighted turbo spin echo MR images of 35 patients from two different studies. Experiments show that compared to state of the art, our method achieves better or comparable results. Specifically, we achieve for localization a mean error of 1.6-2.0 mm, and for segmentation a mean Dice metric of 85%-88% and a mean surface distance of 1.3-1.4 mm.

Localization and production of peptide endocannabinoids in the rodent CNS and adrenal medulla.

The endocannabinoid system (ECS) comprises the cannabinoid receptors CB1 and CB2 and their endogenous arachidonic acid-derived agonists 2-arachidonoyl glycerol and anandamide, which play important neuromodulatory roles. Recently, a novel class of negative allosteric CB1 receptor peptide ligands, hemopressin-like peptides derived from alpha hemoglobin, has been described, with yet unknown origin and function in the CNS. Using monoclonal antibodies we now identified the localization of RVD-hemopressin (pepcan-12) and N-terminally extended peptide endocannabinoids (pepcans) in the CNS and determined their neuronal origin. Immunohistochemical analyses in rodents revealed distinctive and specific staining in major groups of noradrenergic neurons, including the locus coeruleus (LC), A1, A5 and A7 neurons, which appear to be major sites of production/release in the CNS. No staining was detected in dopaminergic neurons. Peptidergic axons were seen throughout the brain (notably hippocampus and cerebral cortex) and spinal cord, indicative of anterograde axonal transport of pepcans. Intriguingly, the chromaffin cells in the adrenal medulla were also strongly stained for pepcans. We found specific co-expression of pepcans with galanin, both in the LC and adrenal gland. Using LC-MS/MS, pepcan-12 was only detected in non-perfused brain (∼40 pmol/g), suggesting that in the CNS it is secreted and present in extracellular compartments. In adrenal glands, significantly more pepcan-12 (400-700 pmol/g) was measured in both non-perfused and perfused tissue. Thus, chromaffin cells may be a major production site of pepcan-12 found in blood. These data uncover important areas of peptide endocannabinoid occurrence with exclusive noradrenergic immunohistochemical staining, opening new doors to investigate their potential physiological function in the ECS. This article is part of a Special Issue entitled 'Fluorescent Neuro-Ligands'.

Drosophila valois encodes a divergent WD protein that is required for Vasa localization and Oskar protein accumulation

valois (vls) was identified as a posterior group gene in the initial screens for Drosophila maternal-effect lethal mutations. Despite its early genetic identification, it has not been characterized at the molecular level until now. We show that vls encodes a divergent WD domain protein and that the three available EMS-induced point mutations cause premature stop codons in the vls ORF. We have generated a null allele that has a stronger phenotype than the EMS mutants. The vlsnull mutant shows that vls+ is required for high levels of Oskar protein to accumulate during oogenesis, for normal posterior localization of Oskar in later stages of oogenesis and for posterior localization of the Vasa protein during the entire process of pole plasm assembly. There is no evidence for vls being dependent on an upstream factor of the posterior pathway, suggesting that Valois protein (Vls) instead acts as a co-factor in the process. Based on the structure of Vls, the function of similar proteins in different systems and our phenotypic analysis, it seems likely that vls may promote posterior patterning by facilitating interactions between different molecules.