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  • br Experimental design materials and methods br

    2018-10-29


    Experimental design, materials and methods
    Data and experimental design Annotation information was obtained for 29 representative genes in bikonts (Table 1) and 81 genes in unikonts (Table 2) [1-3]using Blast2GO program.
    Materials and methods Annotation of the predicted genes and proteins was mined at the National Center for Biotechnology Information database (NCBI) and Phytozome database, version 11. Additional annotation of other predicted BAP-like proteins and genes was extracted from The UniProt Knowledgebase database (http://www.uniprot.org/).
    Acknowledgements Database searches and table preparation were performed by A.S., A.P., A.A., and S.M. in Moscow State University with financial support of the Russian Science Foundation (grant 17-14-01032).
    Data
    Experimental design, materials and methods Analytical characterization of the newly synthetized and purified deuterated Isopropyl myristate Langmuir monolayers
    Acknowledgements We thank Dr. Christian Ihling, Antje Herbrich-Peters and Manuela Woigk (Martin Luther University Halle-Wittenberg) for the analytical dates. This work was supported by the DFG (BR 1378/13-1, DO 463/6-1 and HU 720/13-1).
    Data We provide data on demographic, histopathological and clinical characteristic of 51 endometrial cancer patients treated at the University Medical Centre Ljubljana, at the Division of Gynaecology and Obstetrics. Demographic (age, body mass, BMI, menopausal status, parity), histopathological and clinical data (histological type and grade of tumor, depth of myometrial invasion, presence of lymphovascular invasion, FIGO stage) (Table 1) together with data on statistical analysis of gene prostaglandin receptors ratios (Tables 2–11) are included. The study was approved by the National Medical Ethics Committee of the Republic of Slovenia.
    Experimental design, materials and methods
    Acknowledgements We thank personnel from the Department of Obstetrics and Gynecology, University Clinical Centre, Ljubljana, Slovenia, and Tamara Knific from the Institute of Biochemistry, Faculty of Medicine for their help with preparation of Table 1. The contribution of Dr. Tina Šmuc and Dr. Neli Hevir with the published gene expression data is also acknowledged. This study was supported by a grant J3-5510 to T.L.R. from the Slovenian Research Agency.
    Data This paper contains the scores and the psychometric properties of the Modified Somatic Perception Questionnaire (MSPQ) administered in its Italian version to a sample of 143 immigrants in Genoa (Italy) compared with a sample of 186 Italian patients. Univariate and multivariate descriptive statistics is reported in Tables 1 and 2 and pictorially shown in Figs. 1 and 2, with the fit indexes of the 1-factor model reported in Table 3, whilst results of the receiver operator characteristic (ROC) analysis are shown in Tables 4, 5, 6 and 7, and pictorially shown in Figs. 3 and 4, the outcomes of the 2-way analysis of variance (ANOVA) analysis are tabulated in Table 8, whilst Table 9 reports the overall Cronbach׳s alpha coefficient and the effect of dropping each item. Structural models are shown in Figs. 5 and 6. For further details (such as the composition of the sample) and the interpretation and discussion of the data, the reader is referred to the original publication [1].
    Experimental design, materials and methods Descriptive statistics analyses (mean and standard deviation, skewness and kurtosis) were carried out. Independent sample Student׳s test, analysis of variance/ANOVA one- and two-ways, ROC analyses were performed in order to assess the impact of geographic provenience and presence of a chronic pathology on the total MSPQ score. Figures with p-value<0.05 were considered statistically significant. Statistical analyses were performed using the commercial software Statistical Package for Social Sciences (SPSS v22.0; IBM Corporation, Armonk, NY, USA). The factorial structure was assessed using the software Factor Analysis for Windows (v10.4.01, Rovira i Virgili University, Tarragona, Spain), performing a Parallel Analysis (PA) on a polychoric correlations–based dispersion matrix. A partial least-square structural equation model was carried out using the SmartPLS software v3.2.6 for Windows.