IMRT credentialing for prospective trials using institutional virtual phantoms: results of a joint European Organization for the Research and Treatment of Cancer and Radiological Physics Center project.

BACKGROUND AND PURPOSE: Intensity-modulated radiotherapy (IMRT) credentialing for a EORTC study was performed using an anthropomorphic head phantom from the Radiological Physics Center (RPC; RPCPH). Institutions were retrospectively requested to irradiate their institutional phantom (INSTPH) using the same treatment plan in the framework of a Virtual Phantom Project (VPP) for IMRT credentialing. MATERIALS AND METHODS: CT data set of the institutional phantom and measured 2D dose matrices were requested from centers and sent to a dedicated secure EORTC uploader. Data from the RPCPH and INSTPH were thereafter centrally analyzed and inter-compared by the QA team using commercially available software (RIT; ver.5.2; Colorado Springs, USA). RESULTS: Eighteen institutions participated to the VPP. The measurements of 6 (33%) institutions could not be analyzed centrally. All other centers passed both the VPP and the RPC ±7%/4 mm credentialing criteria. At the 5%/5 mm gamma criteria (90% of pixels passing), 11(92%) as compared to 12 (100%) centers pass the credentialing process with RPCPH and INSTPH (p = 0.29), respectively. The corresponding pass rate for the 3%/3 mm gamma criteria (90% of pixels passing) was 2 (17%) and 9 (75%; p = 0.01), respectively. CONCLUSIONS: IMRT dosimetry gamma evaluations in a single plane for a H&N prospective trial using the INSTPH measurements showed agreement at the gamma index criteria of ±5%/5 mm (90% of pixels passing) for a small number of VPP measurements. Using more stringent, criteria, the RPCPH and INSTPH comparison showed disagreement. More data is warranted and urgently required within the framework of prospective studies.

The integrin antagonist cilengitide activates alphaVbeta3, disrupts VE-cadherin localization at cell junctions and enhances permeability in endothelial cells.

Cilengitide is a high-affinity cyclic pentapeptdic alphaV integrin antagonist previously reported to suppress angiogenesis by inducing anoikis of endothelial cells adhering through alphaVbeta3/alphaVbeta5 integrins. Angiogenic endothelial cells express multiple integrins, in particular those of the beta1 family, and little is known on the effect of cilengitide on endothelial cells expressing alphaVbeta3 but adhering through beta1 integrins. Through morphological, biochemical, pharmacological and functional approaches we investigated the effect of cilengitide on alphaVbeta3-expressing human umbilical vein endothelial cells (HUVEC) cultured on the beta1 ligands fibronectin and collagen I. We show that cilengitide activated cell surface alphaVbeta3, stimulated phosphorylation of FAK (Y(397) and Y(576/577)), Src (S(418)) and VE-cadherin (Y(658) and Y(731)), redistributed alphaVbeta3 at the cell periphery, caused disappearance of VE-cadherin from cellular junctions, increased the permeability of HUVEC monolayers and detached HUVEC adhering on low-density beta1 integrin ligands. Pharmacological inhibition of Src kinase activity fully prevented cilengitide-induced phosphorylation of Src, FAK and VE-cadherin, and redistribution of alphaVbeta3 and VE-cadherin and partially prevented increased permeability, but did not prevent HUVEC detachment from low-density matrices. Taken together, these observations reveal a previously unreported effect of cilengitide on endothelial cells namely its ability to elicit signaling events disrupting VE-cadherin localization at cellular contacts and to increase endothelial monolayer permeability. These effects are potentially relevant to the clinical use of cilengitide as anticancer agent.

Prediction of cross-recognition of peptide-HLA A2 by Melan-A-specific cytotoxic T lymphocytes using three-dimensional quantitative structure-activity relationships.

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

Sublimation of new matrix candidates for high spatial resolution imaging mass spectrometry of lipids: enhanced information in both positive and negative polarities after 1,5-diaminonapthalene deposition.

Matrix sublimation has demonstrated to be a powerful approach for high-resolution matrix-assisted laser desorption ionization (MALDI) imaging of lipids, providing very homogeneous solvent-free deposition. This work presents a comprehensive study aiming to evaluate current and novel matrix candidates for high spatial resolution MALDI imaging mass spectrometry of lipids from tissue section after deposition by sublimation. For this purpose, 12 matrices including 2,5-dihydroxybenzoic acid (DHB), sinapinic acid (SA), α-cyano-4-hydroxycinnamic acid (CHCA), 2,6-dihydroxyacetphenone (DHA), 2',4',6'-trihydroxyacetophenone (THAP), 3-hydroxypicolinic acid (3-HPA), 1,8-bis(dimethylamino)naphthalene (DMAN), 1,8,9-anthracentriol (DIT), 1,5-diaminonapthalene (DAN), p-nitroaniline (NIT), 9-aminoacridine (9-AA), and 2-mercaptobenzothiazole (MBT) were investigated for lipid detection efficiency in both positive and negative ionization modes, matrix interferences, and stability under vacuum. For the most relevant matrices, ion maps of the different lipid species were obtained from tissue sections at high spatial resolution and the detected peaks were characterized by matrix-assisted laser desorption ionization time-of-flight/time-of-flight (MALDI-TOF/TOF) mass spectrometry. First proposed for imaging mass spectrometry (IMS) after sublimation, DAN has demonstrated to be of high efficiency providing rich lipid signatures in both positive and negative polarities with high vacuum stability and sub-20 μm resolution capacity. Ion images from adult mouse brain were generated with a 10 μm scanning resolution. Furthermore, ion images from adult mouse brain and whole-body fish tissue sections were also acquired in both polarity modes from the same tissue section at 100 μm spatial resolution. Sublimation of DAN represents an interesting approach to improve information with respect to currently employed matrices providing a deeper analysis of the lipidome by IMS.

Human fetal bone cells in delivery systems for bone engineering.

The aim of this study was to culture human fetal bone cells (dedicated cell banks of fetal bone derived from 14 week gestation femurs) within both hyaluronic acid gel and collagen foam, to compare the biocompatibility of both matrices as potential delivery systems for bone engineering and particularly for oral application. Fetal bone cell banks were prepared from one organ donation and cells were cultured for up to 4 weeks within hyaluronic acid (Mesolis(®)) and collagen foams (TissueFleece(®)). Cell survival and differentiation were assessed by cell proliferation assays and histology of frozen sections stained with Giemsa, von Kossa and ALP at 1, 2 and 4 weeks of culture. Within both materials, fetal bone cells could proliferate in three-dimensional structure at ∼70% capacity compared to monolayer culture. In addition, these cells were positive for ALP and von Kossa staining, indicating cellular differentiation and matrix production. Collagen foam provides a better structure for fetal bone cell delivery if cavity filling is necessary and hydrogels would permit an injectable technique for difficult to treat areas. In all, there was high biocompatibility, cellular differentiation and matrix deposition seen in both matrices by fetal bone cells, allowing for easy cell delivery for bone stimulation in vivo. Copyright © 2011 John Wiley & Sons, Ltd.

Fate of the herbicide glyphosate and its metabolite AMPA in soils and their transfer to surface waters: A multi-scale approach in the Lavaux vineyards, western Switzerland

The use of herbicides in agriculture may lead to environmental problems, such as surface water pollution, with a potential risk for aquatic organisms. The herbicide glyphosate is the most used active ingredient in the world and in Switzerland. In the Lavaux vineyards it is nearly the only molecule applied. This work aimed at studying its fate in soils and its transfer to surface waters, using a multi-scale approach: from molecular (10-9 m) and microscopic scales (10-6 m), to macroscopic (m) and landscape ones (103 m). First of all, an analytical method was developed for the trace level quantification of this widely used herbicide and its main by-product, aminomethylphosphonic acid (AMPA). Due to their polar nature, their derivatization with 9-fluorenylmethyl chloroformate (FMOC-Cl) was done prior to their concentration and purification by solid phase extraction. They were then analyzed by ultra performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). The method was tested in different aqueous matrices with spiking tests and validated for the matrix effect correction in relevant environmental samples. Calibration curves established between 10 and 1000ng/l showed r2 values above 0.989, mean recoveries varied between 86 and 133% and limits of detection and quantification of the method were as low as 5 and 10ng/l respectively. At the parcel scale, two parcels of the Lavaux vineyard area, located near the Lutrive River at 6km to the east of Lausanne, were monitored to assess to which extent glyphosate and AMPA were retained in the soil or exported to surface waters. They were equipped at their bottom with porous ceramic cups and runoff collectors, which allowed retrieving water samples for the growing seasons 2010 and 2011. Results revealed that the mobility of glyphosate and AMPA in the unsaturated zone was likely driven by the precipitation regime and the soil characteristics, such as slope, porosity structure and layer permeability discrepancy. Elevated glyphosate and AMPA concentrations were measured at 60 and 80 cm depth at parcel bottoms, suggesting their infiltration in the upper parts of the parcels and the presence of preferential flow in the studied parcels. Indeed, the succession of rainy days induced the gradual saturation of the soil porosity, leading to rapid infiltration through macropores, as well as surface runoff formation. Furthermore, the presence of more impervious weathered marls at 100 cm depth induced throughflows, the importance of which for the lateral transport of the herbicide molecules was determined by the slope steepness. Important rainfall events (>10 mm/day) were clearly exporting molecules from the soil top layer, as indicated by important concentrations in runoff samples. A mass balance showed that total loss (10-20%) mainly occurred through surface runoff (96%) and, to a minor extent, by throughflows in soils (4%), with subsequent exfiltration to surface waters. Observations made in the Lutrive River revealed interesting details of glyphosate and AMPA dynamics in urbanized landscapes, such as the Lavaux vineyards. Indeed, besides their physical and chemical properties, herbicide dynamics at the catchment level strongly depend on application rates, precipitation regime, land use and also on the presence of drains or constructed channels. Elevated concentrations, up to 4970 ng/l, observed just after the application, confirmed the diffuse export of these compounds from the vineyard area by surface runoff during main rain events. From April to September 2011, a total load of 7.1 kg was calculated, with 85% coming from vineyards and minor urban sources and 15% from arable crops. Small vineyard surfaces could generate high concentrations of herbicides and contribute considerably to the total load calculated at the outlet, due to their steep slopes (~10%). The extrapolated total amount transferred yearly from the Lavaux vineyards to the Lake of Geneva was of 190kg. At the molecular scale, the possible involvement of dissolved organic matter (DOM) in glyphosate and copper transport was studied using UV/Vis fluorescence spectroscopy. Combined with parallel factor (PARAFAC) analysis, this technique allowed characterizing DOM of soil and surface water samples from the studied vineyard area. Glyphosate concentrations were linked to the fulvic-like spectroscopic signature of DOM in soil water samples, as well as to copper, suggesting the formation of ternary complexes. In surface water samples, its concentrations were also correlated to copper ones, but not in a significant way to the fulvic-like signature. Quenching experiments with standards confirmed field tendencies in the laboratory, with a stronger decrease in fluorescence intensity for fulvic-like fluorophore than for more aromatic ones. Lastly, based on maximum concentrations measured in the river, an environmental risk for these compounds was assessed, using laboratory tests and ecotoxicity data from the literature. In our case and with the methodology applied, the risk towards aquatic species was found negligible (RF<1).

Textual autocorrelation : formalism and illustrations

Abstract Textual autocorrelation is a broad and pervasive concept, referring to the similarity between nearby textual units: lexical repetitions along consecutive sentences, semantic association between neighbouring lexemes, persistence of discourse types (narrative, descriptive, dialogal...) and so on. Textual autocorrelation can also be negative, as illustrated by alternating phonological or morpho-syntactic categories, or the succession of word lengths. This contribution proposes a general Markov formalism for textual navigation, and inspired by spatial statistics. The formalism can express well-known constructs in textual data analysis, such as term-document matrices, references and hyperlinks navigation, (web) information retrieval, and in particular textual autocorrelation, as measured by Moran's I relatively to the exchange matrix associated to neighbourhoods of various possible types. Four case studies (word lengths alternation, lexical repulsion, parts of speech autocorrelation, and semantic autocorrelation) illustrate the theory. In particular, one observes a short-range repulsion between nouns together with a short-range attraction between verbs, both at the lexical and semantic levels. Résumé: Le concept d'autocorrélation textuelle, fort vaste, réfère à la similarité entre unités textuelles voisines: répétitions lexicales entre phrases successives, association sémantique entre lexèmes voisins, persistance du type de discours (narratif, descriptif, dialogal...) et ainsi de suite. L'autocorrélation textuelle peut être également négative, comme l'illustrent l'alternance entre les catégories phonologiques ou morpho-syntaxiques, ou la succession des longueurs de mots. Cette contribution propose un formalisme markovien général pour la navigation textuelle, inspiré par la statistique spatiale. Le formalisme est capable d'exprimer des constructions bien connues en analyse des données textuelles, telles que les matrices termes-documents, les références et la navigation par hyperliens, la recherche documentaire sur internet, et, en particulier, l'autocorélation textuelle, telle que mesurée par le I de Moran relatif à une matrice d'échange associée à des voisinages de différents types possibles. Quatre cas d'étude illustrent la théorie: alternance des longueurs de mots, répulsion lexicale, autocorrélation des catégories morpho-syntaxiques et autocorrélation sémantique. On observe en particulier une répulsion à courte portée entre les noms, ainsi qu'une attraction à courte portée entre les verbes, tant au niveau lexical que sémantique.

Mapping the human connectome at multiple scales with diffusion spectrum MRI.

The global structural connectivity of the brain, the human connectome, is now accessible at millimeter scale with the use of MRI. In this paper, we describe an approach to map the connectome by constructing normalized whole-brain structural connection matrices derived from diffusion MRI tractography at 5 different scales. Using a template-based approach to match cortical landmarks of different subjects, we propose a robust method that allows (a) the selection of identical cortical regions of interest of desired size and location in different subjects with identification of the associated fiber tracts (b) straightforward construction and interpretation of anatomically organized whole-brain connection matrices and (c) statistical inter-subject comparison of brain connectivity at various scales. The fully automated post-processing steps necessary to build such matrices are detailed in this paper. Extensive validation tests are performed to assess the reproducibility of the method in a group of 5 healthy subjects and its reliability is as well considerably discussed in a group of 20 healthy subjects.

Efficiency in inventories of ants in a forest reservein Central Amazonia

The objective of this work was to evaluate an inventory method efficiency for ants. We used subsamples collected in 24 transects of 100 m, distributed in 6 plots of 600 ha each in primary forest, as part of a long-term project. Ten litter subsamples were extracted per transect using Winkler extractors. Ants were identified to genus level, and Crematogaster, Gnamptogenys and Pachycondyla genera to species/morphospecies level. To evaluate the consequences of reduced sampling on the retention of ecological information, we estimated the lowest number of subsamples needed to detect the effects of environmental variables. Multidimensional scaling (MDS) was used to generate dissimilarity matrices, and Mantel correlations between each reduced-sampling effort and maximum effort were used as an index of how much information was maintained and could still be used in multivariate analyses. Lower p-values was observed on the effect of soil pH in the community of genera, and on the effect of the litter volume for the community of Crematogaster. The trend was still detectable in the analysis based on reduced-sampling. The number of subsamples can be reduced, and the cost-efficiency of the protocol can be improved with little loss of information.

Modelo discreto de transiciones entre estados de dependencia

En este trabajo se analiza el modelo markoviano de transiciones anuales entre estados de dependencia asumiendo la hipótesis de estacionariedad. Se suponen conocidas las tasas de mortalidad de la población autónoma y las tasas de prevalencia de los tres estados de dependencia considerados. La indeterminación del modelo se resolverá incorporando restricciones en forma de hipótesis en las interrelaciones, a partir de las cuales se obtienen las matrices de transición por edades y se analiza el comportamiento de las mismas. Se realizan aplicaciones numéricas utilizando distribuciones de mortalidad y de prevalencia que pueden ser adecuadas para la población española y que han surgido de un análisis preliminar. Por último, se efectúa un análisis de sensibilidad de los resultados respecto al cambio de hipótesis en las mencionadas interrelaciones. Abstract

Agronomical and molecular characterization of banana germplasm

The objective of the present work was to characterize banana accessions from the Germplasm Bank at Embrapa Mandioca e Fruticultura Tropical (Brazil), using agronomical, physical and physicochemical characteristics of fruit and simple sequence repeats (SSR) markers. Twenty-six accessions were analyzed, in which high genetic variability was found, especially for the agronomical characters number of fruit and weight of bunch. Accessions with high contents of carotenoids (diploid 'Jaran'), polyphenols (triploid 'Caipira' and tetraploid 'Teparod') and vitamin C (diploid 'Tuugia' and an unknown triploid AAA) in the fruit were identified. Thirteen microsatellite primers revealed an average of 7.23 alleles, which showed high variability. A dendrogram was prepared using the Gower algorithm for the distance matrices obtained from the agronomical, physical and physicolchemical analysis of fruit and SSR markers. Adopting the average genetic divergence as the cut-off point, three clusters were found: G1, formed by the diploids 'Jaran', 028003-01 and M-48; G2, by the diploids 'Malbut' and 'Ido 110'; and G3, by 21 tri-and tetraploid accessions, including one diploid, 'Tuugia'. The triploids with the B genome 'Thap Maeo', 'Walha', 'Pacha Nadan' and 'Champa Madras' were grouped in G2. Results from this work can be used for breeding hybrids with good agronomical traits and fruit quality.

A connectome-based comparison of diffusion MRI schemes.

Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion encoding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, q-ball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.

Mixed spectral-structural classification of very high resolution images with summation kernels

In this paper, mixed spectral-structural kernel machines are proposed for the classification of very-high resolution images. The simultaneous use of multispectral and structural features (computed using morphological filters) allows a significant increase in classification accuracy of remote sensing images. Subsequently, weighted summation kernel support vector machines are proposed and applied in order to take into account the multiscale nature of the scene considered. Such classifiers use the Mercer property of kernel matrices to compute a new kernel matrix accounting simultaneously for two scale parameters. Tests on a Zurich QuickBird image show the relevance of the proposed method : using the mixed spectral-structural features, the classification accuracy increases of about 5%, achieving a Kappa index of 0.97. The multikernel approach proposed provide an overall accuracy of 98.90% with related Kappa index of 0.985.

Molecular characterization of soybean cultivars by microsatellite markers with universal tail sequence

The objective of this work was to standardize a semiautomated method for genotyping soybean, based on universal tail sequence primers (UTSP), and to compare it with the conventional genotyping method that uses electrophoresis in polyacrylamide gels. Thirty soybean cultivars were genotypically characterized by both methods, using 13 microsatellite loci. For the UTSP method, the number of alleles (NA) was 50 (2-7 per marker) and the polymorphic information content (PIC) ranged from 0.40 to 0.74. For the conventional method, the NA was 38 (2-5 per marker) and the PIC varied from 0.39 to 0.67. The genetic dissimilarity matrices obtained by the two methods were highly correlated with each other (0.8026), and the formed groups were coherent with the phenotypic data used for varietal registration. The 13 markers allowed the distinction of all analyzed cultivars. The low cost of the UTSP method, associated with its high accuracy, makes it ideal for the characterization of soybean cultivars and for the determination of genetic purity.

JPEG standard uniform quantization error modeling with applications to sequential and progressive operation modes

In this paper we propose a method for computing JPEG quantization matrices for a given mean square error or PSNR. Then, we employ our method to compute JPEG standard progressive operation mode definition scripts using a quantization approach. Therefore, it is no longer necessary to use a trial and error procedure to obtain a desired PSNR and/or definition script, reducing cost. Firstly, we establish a relationship between a Laplacian source and its uniform quantization error. We apply this model to the coefficients obtained in the discrete cosine transform stage of the JPEG standard. Then, an image may be compressed using the JPEG standard under a global MSE (or PSNR) constraint and a set of local constraints determined by the JPEG standard and visual criteria. Secondly, we study the JPEG standard progressive operation mode from a quantization based approach. A relationship between the measured image quality at a given stage of the coding process and a quantization matrix is found. Thus, the definition script construction problem can be reduced to a quantization problem. Simulations show that our method generates better quantization matrices than the classical method based on scaling the JPEG default quantization matrix. The estimation of PSNR has usually an error smaller than 1 dB. This figure decreases for high PSNR values. Definition scripts may be generated avoiding an excessive number of stages and removing small stages that do not contribute during the decoding process with a noticeable image quality improvement.