Search

Introduction: Metabolomics is the comprehensive study of small molecules in biological systems. It has recently garnered attention for its wide variety of applications such as diseases, drug treatments, agriculture, and more. As the interest in metabolomics grow, meeting the demands of cutting-edge research requires software tools that not only advance analytical capabilities, but also prioritize user-friendly features. Objectives: In response to this need, we present two new computer programs, A-SIMA: Advanced-Software for Interactive Metabolite Analysis and A-MAP: A Multivariate Analysis Program. These tools aim to introduce new capabilities for metabolite identification and data analysis, and thereby advancing the computational methodology in NMR-based metabolomics. Methods: A-SIMA is designed with an easy-to-use graphical user interface which allows users to perform metabolite identification on 1D and 2D NMR data effortlessly with complete control over the identification process. Similarly, A-MAP facilitates multivariate statistical analysis of metabolite data through a straightforward process. It offers analysis options such as Principal Component Analysis and Orthogonal Partial Least Squares-Discriminant Analysis using regions of interests as inputs. Results: Both A-SIMA and A-MAP are pre-built in the POKY suite, available at https://poky.clas.ucdenver.edu, with tutorial videos on YouTube for guidance on not only the programs, but also installation. The POKY suite is a software program for NMR biomolecular analysis. With the addition of these programs in POKY, researchers and professionals can experience a fully integrated process for every step of their metabolite analysis. Data can also be easily exported from these programs to be applied elsewhere. Conclusion: The introduction of A-SIMA and A-MAP can be promising tools that can lead significant advancements in metabolomics research. These tools offer enhanced capabilities for metabolite analysis and statistical modelling in a user-friendly manner. Their integration into the POKY suite ensures accessibility, usability, and efficiency. [ABSTRACT FROM AUTHOR]

Introduction: The aim of this study was to predict depression on the basis of family communication dimensions with the mediation of cognitive flexibility. Materials and Methods: In this correlational study, 390 students (201 girls and 189 boys) constructed the sample group. They were selected from 2nd grade of high schools in Shiraz in the academic year of 2015-16 through randomized multi-stage cluster sampling style. To measure the research variables, Fitzpatrick and Ritchie's family communication patterns (RFCP), Dennis and Van der Wal's cognitive flexibility (CFI) and Beck depression-second edition (BDI-II) inventories were used. Pearson correlation coefficient and path analysis by SPSS 22 and AMOS 20 were used to analyze research data. Results: The results of path analysis indicated that the conversation orientation has direct negative effect (P=0.005) and an indirect effect through the mediation of cognitive flexibility (P=0.001) on depression. Also conformity orientation had only direct and positive effect (P=0.001) on depression. Conclusion: In overall, the results of this study showed that cognitive flexibility plays mediating role in the relationship between conversation orientation and depression. [ABSTRACT FROM AUTHOR]