Multiparameter analysis of naevi and primary melanomas identifies a subset of naevi with elevated markers of transformation

Here we have carried out a multiparameter analysis using a panel of 28 immunohistochemical markers to identify markers of transformation from benign and dysplastic naevus to primary melanoma in three separate cohorts totalling 279 lesions. We have identified a set of eight markers that distinguish naevi from melanoma. None of markers or parameters assessed differentiated benign from dysplastic naevi. Indeed, the naevi clustered tightly in terms of their immunostaining patterns whereas primary melanomas showed more diverse staining patterns. A small subset of histopathologically benign lesions had elevated levels of multiple markers associated with melanoma, suggesting that these represent naevi with an increased potential for transformation to melanoma

Close binary stars in the solar-age Galactic open cluster M67

We present multi-colour time-series CCD photometry of the solar-age galactic open cluster M67 (NGC 2682). About 3600 frames spread over 28 nights were obtained with the 1.5 m Russian-Turkish and 1.2 m Mercator telescopes. High-precision observations of the close binary stars AH Cnc, EV Cnc, ES Cnc, the $\delta$ Scuti type systems EX Cnc and EW Cnc, and some long-period variables belonging to M67 are presented. Three full multi-colour light curves of the overcontact binary AH Cnc were obtained during three observing seasons. Likewise we gathered three light curves of EV Cnc, an EB-type binary, and two light curves of ES Cnc, a blue straggler binary. Parts of the light change of long-term variables S1024, S1040, S1045, S1063, S1242, and S1264 are obtained. Period variation analysis of AH Cnc, EV Cnc, and ES Cnc were done using all times of mid-eclipse available in the literature and those obtained in this study. In addition, we analyzed multi-colour light curves of the close binaries and also determined new frequencies for the $\delta$ Scuti systems. The physical parameters of the close binary stars were determined with simultaneous solutions of multi-colour light and radial velocity curves. Finally we determined the distance of M67 as 857(33) pc via binary star parameters, which is consistent with an independent method from earlier studies.Comment: 12 pages, 9 Figures, 13 Table

Investigation of optimal parameters for finite element solution of the forward problem in magnetic field tomography based on magnetoencephalography

This paper presents an investigation of optimal parameters for finite element (FE) solution of the forward problem in magnetic field tomography (MFT) brain imaging based on magnetoencephalography (MEG). It highlights detailed analyses of the main parameters involved and evaluates their optimal values for various cases of FE model solutions (e.g., steady-state, transient, etc.). In each case, a detail study of some of the main parameters and their effects on FE solution and its accuracy are carefully tested and evaluated. These parameters include: total number and size of 3D FE elements used, number and size of elements used in surface discretisation (of both white and grey matters of the brain), number and size of elements used for approximation of current sources, number of anisotropic properties used in steady-state and transient solutions, and the time steps used in transient analyses. The optimal values of these parameters in relation to solution accuracy and mesh convergence criteria have been found and presented

Evaluation of colorectal cancer subtypes and cell lines using deep learning

Colorectal cancer (CRC) is a common cancer with a high mortality rate and a rising incidence rate in the developed world. Molecular profiling techniques have been used to better understand the variability between tumors and disease models such as cell lines. To maximize the translatability and clinical relevance of in vitro studies, the selection of optimal cancer models is imperative. We have developed a deep learning-based method to measure the similarity between CRC tumors and disease models such as cancer cell lines. Our method efficiently leverages multiomics data sets containing copy number alterations, gene expression, and point mutations and learns latent factors that describe data in lower dimensions. These latent factors represent the patterns that are clinically relevant and explain the variability of molecular profiles across tumors and cell lines. Using these, we propose refined CRC subtypes and provide best-matching cell lines to different subtypes. These findings are relevant to patient stratification and selection of cell lines for early-stage drug discovery pipelines, biomarker discovery, and target identification

Evaluation of colorectal cancer subtypes and cell lines using deep learning

Colorectal cancer (CRC) is a common cancer with a high mortality rate and rising incidence rate in the developed world. Molecular profiling techniques have been used to study the variability between tumours as well as cancer models such as cell lines, but their translational value is incomplete with current methods. Moreover, first generation computational methods for subtype classification do not make use of multi-omics data in full scale. Drug discovery programs use cell lines as a proxy for human cancers to characterize their molecular makeup and drug response, identify relevant indications and discover biomarkers. In order to maximize the translatability and the clinical relevance of in vitro studies, selection of optimal cancer models is imperative. We present a novel subtype classification method based on deep learning and apply it to classify CRC tumors using multi-omics data, and further to measure the similarity between tumors and disease models such as cancer cell lines. Multi-omics Autoencoder Integration (maui) efficiently leverages data sets containing copy number alterations, gene expression, and point mutations, and learns clinically important patterns (latent factors) across these data types. Using these latent factors, we propose a refinement of the gold-standard CRC subtypes, and propose best-matching cell lines for the different subtypes. These findings are relevant for patient stratification and selection of cell lines for drug discovery pipelines, biomarker discovery, and target identification

Prevention of chronic rejection in mouse aortic allografts by combined treatment with CTLA4-Ig and anti-CD40 ligand monoclonal antibody

Background. In this study, using a murine model of aortic allotransplantation, the role of blockade of signaling through CD28/B7 and CD40/CD40 ligand costimulatory pathways in the evolvement of posttransplant vasculopathy was examined. Methods. Aortic allografts were transplanted across C57BL/10J (H2b)→C3H (H2(k)) strain combinations. Transient or more stable blockade of second signaling was achieved by either a single injection or multiple injections of CTLA4-Ig fusion protein (200 μg/dose i.p.) and/or anti-CD40 ligand (CD40L) monoclonal antibody (250 μg i.m.). At day 30 after transplantation, the grafts were harvested for histopathological and immunohistochemical examination. Results. Similar to allografts of untreated animals, aortic allografts obtained from recipients treated with either CTLA4-Ig or anti-CD40L monoclonal antibody alone exhibited marked narrowing of the lumen primarily due to concentric intimal thickening caused by proliferation of α-smooth muscle actin-positive cells. Contemporaneous treatment, however, with either a single injection or multiple injections of CTLA4-Ig and anti-CD40L monoclonal antibody resulted in marked diminution of intimal thickening. Interestingly, concurrent prolonged inhibition of CD28/B7 and CD40/ CD40L pathways resulted in complete abrogation of the development of posttransplant arteriopathy. Conclusion. These data suggest that a more stable disruption of signaling through costimulatory pathways may be required to obviate the development of posttransplant vasculopathy

Microestructura de quesos blancos turcos bajos en grasa producidos industrialmente, influencia de la homogenización de la crema

The microstructure and fat globule distribution of reduced and low fat Turkish white cheese were evaluated. Reduced and low fat cheeses were manufactured from 1.5% and 0.75% fat milk respectively which were standardized unhomogenized and homogenized cream in a dairy plant. Homogenized and non-homogenized creams and cheese whey were analyzed for fat globule distribution and cheese samples were also analyzed for microstructure characteristics. According to the results, the homogenization of cream decreased the size of fat globules; and showed that a large number of fat particles were dispersed in the in matrix and improved the lubrication of cheese microstructure. According to the micrographs for the fat, which was not removed, they exhibited a more extended matrix with a few small fat globules compared to the defatted micrographs. Homogenization of cream produces small fat globules and unclustured fat globules were found in the resulting whey. These results are important for dairy processors for using cream homogenization as a processing tool at the industrial level.Se estudia la microestructura y distribución de los glóbulos de grasa de quesos blancos turcos bajos en grasa. Quesos con reducida y baja cantidad en grasa fueron fabricados conteniendo entre el 1,5% y 0,75% de grasa de leche, respectivamente, y con cremas homogeneizadas y no homogeneizadas, en una planta de lácteos. Las cremas homogeneizadas y no homogeneizadas y el suero de los quesos se analizaron para determinar la distribución de los glóbulos de grasa y también se analizaron las características de la microestructura de muestras de queso. De acuerdo con los resultados, la homogeneización de la crema reduce el tamaño de los glóbulos de grasa, mostrando un gran número de partículas de grasa dispersa en la matriz de caseína que mejoró la lubricación de la microestructura del queso. De acuerdo con las micrografías de la grasa que no se elimina, estas exhiben una matriz más amplia en la que hay pocos glóbulos de grasa en comparación con las micrografías de las muestras desgrasadas. La homogenización de la crema produce pequeños glóbulos de grasa y el suero resultante contiene glóbulos de grasa no incrustados. Estos resultados son importantes para los procesadores de productos lácteos, y muestran la utilidad de la homogeneización de crema como una herramienta del procesamiento a nivel industrial

The RNA workbench: Best practices for RNA and high-throughput sequencing bioinformatics in Galaxy

RNA-based regulation has become a major research topic in molecular biology. The analysis of epigenetic and expression data is therefore incomplete if RNA-based regulation is not taken into account. Thus, it is increasingly important but not yet standard to combine RNA-centric data and analysis tools with other types of experimental data such as RNA-seq or ChIP-seq. Here, we present the RNA workbench, a comprehensive set of analysis tools and consolidated workflows that enable the researcher to combine these two worlds. Based on the Galaxy framework the workbench guarantees simple access, easy extension, flexible adaption to personal and security needs, and sophisticated analyses that are independent of command-line knowledge. Currently, it includes more than 50 bioinformatics tools that are dedicated to different research areas of RNA biology including RNA structure analysis, RNA alignment, RNA annotation, RNA-protein interaction, ribosome profiling, RNA-seq analysis and RNA target prediction. The workbench is developed and maintained by experts in RNA bioinformatics and the Galaxy framework. Together with the growing community evolving around this workbench, we are committed to keep the workbench up-to-date for future standards and needs, providing researchers with a reliable and robust framework for RNA data analysis

A novel β-lactam-aminoglycoside combination in veterinary medicine: The couse of ceftiofur and gentamicin to combat resistant Escherichia coli

ΔΕΝ ΔΙΑΤΙΘΕΤΑΙ ΠΕΡΙΛΗΨΗThe focus of this study was to evaluate the efficacy of ceftiofur+gentamicin combination to increase the success of antimicrobial inhibition against resistant Escherichia coli (E.coli) strains isolated from animals. Interaction between drugs was determined using checkerboard method and the fractional inhibitory concentration index was interpreted as synergism, antagonism and indifference. The combination was defined as bactericidal or bacteriostatic based on the minimum bactericidal test results. Mutant prevention concentration test was used to evaluate the resistance tendency suppression potential of the combination. The synergistic effect was detected for all E. coli strains by the checkerboard method; even the strains that were resistant to the individual compounds in the combination. Based on the results of minimum bactericidal concentration test, the combination exhibited bactericidal effect against all E. coli strains. In addition, the individual mutant prevention concentrations of ceftiofur and gentamicin decreased up to 125-fold by using the combination for the inhibition of resistant E. coli strains. The results indicated that killing potential of co-use of the compounds is much stronger than their individual use. The combination achieved to decrease the mutant prevention concentrations and this can reduce the risk of emergence of single mutations during treatment done with suggested doses.

A modified sequence capture approach allowing standard and methylation analyses of the same enriched genomic DNA sample

Background: Bread wheat has a large complex genome that makes whole genome resequencing costly. Therefore, genome complexity reduction techniques such as sequence capture make re-sequencing cost effective. With a high-quality draft wheat genome now available it is possible to design capture probe sets and to use them to accurately genotype and anchor SNPs to the genome. Furthermore, in addition to genetic variation, epigenetic variation provides a source of natural variation contributing to changes in gene expression and phenotype that can be profiled at the base pair level using sequence capture coupled with bisulphite treatment. Here, we present a new 12 Mbp wheat capture probe set, that allows both the profiling of genotype and methylation from the same DNA sample. Furthermore, we present a method, based on Agilent SureSelect Methyl-Seq, that will use a single capture assay as a starting point to allow both DNA sequencing and methyl-seq. Results: Our method uses a single capture assay that is sequentially split and used for both DNA sequencing and methyl-seq. The resultant genotype and epi-type data is highly comparable in terms of coverage and SNP/methylation site identification to that generated from separate captures for DNA sequencing and methyl-seq. Furthermore, by defining SNP frequencies in a diverse landrace from the Watkins collection we highlight the importance of having genotype data to prevent false positive methylation calls. Finally, we present the design of a new 12 Mbp wheat capture and demonstrate its successful application to re-sequence wheat. Conclusions: We present a cost-effective method for performing both DNA sequencing and methyl-seq from a single capture reaction thus reducing reagent costs, sample preparation time and DNA requirements for these complementary analyses