فهرست مطالب

  • Volume:7 Issue: 3, 2019
  • تاریخ انتشار: 1398/06/10
  • تعداد عناوین: 6
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  • Marie Saghaeian Jazi* Pages 1-3

    Summary:SOX2 overlapping transcript (SOX2OT) is a long non-coding RNA associated with cancer pathogenesis. It contributes to a variety of cellular functions and recent evidence propounds its association with autophagy process. It has been showed that SOX2OT can regulate the expression of different autophagy associated factors in human cells with different mechanisms, however more remains to be investigated.

    Keywords: SOX2OT, lncRNA, Autophagy
  • Ayyoob Khosravi, Fariba Kokabi, Ramezan Behzadi, Jahanbakhsh Asadi* Pages 4-10
    Background and objectives

    Modeling cancer in vivo is a very important tool to investigate cancer pathogenesis and molecular mechanisms involved in cancer progression. Laboratory mice are the most common animal used for rebuilding human cancer in vivo. Cancer stem cells (CSCs) are the main reason of failure in cancer therapy because of tumor relapse and metastasis. Isolation of cancer stem cells helps us to study their function and behavior. In the current study we separate cancer stem-like cells using sphere formation assay then investigate their tumorigenicity in xenograft tumor model.

    Methods

    YM1 cancer cells were cultured in serum-free media (SFM) in low adherent culture dishes for enrichment of cancer stem cells. The resulting spheres containing cancer stem-like cells were dissociated into single cells and were injected into the dorsal flank of B6 nude mice.

    Results

    A few days after injection, subcutaneous tumors formed. The growth curves of the resulting tumors were plotted using their weekly recorded lengths. The tumors' volume and weight were measured. The size of resulting tumors was appropriate to the number of cells injected. Pathological analysis confirmed esophageal origin of the resulting tumors.

    Conclusion

    Using laboratory mice models is a practical modeling system that provides us investigation of human tumors pathogenesis in vivo.

    Keywords: Cancer stem cell, ESCC, Xenograft mouse model
  • Mahsa Saadati, Arezoo Bagheri* Pages 11-23
    Background and objectives

    Application of statistical machine learning methods such as ensemble based approaches in survival analysis has been received considerable interest over the past decades in time-to-event data sets. One of these practical methods is survival forests which have been developed in a variety of contexts due to their high precision, non-parametric and non-linear nature. This article aims to evaluate the performance of survival forests by comparing them with Cox-proportional hazards (CPH) model in studying first birth interval (FBI).

    Methods

    A cross sectional study in 2017 was conducted by the stratified random sampling and a structured questionnaire to gather the information of 610, 15-49-year-old married women in Tehran. Considering some influential covariates on FBI, random survival forest (RSF) and conditional inference forest (CIF) were constructed by bootstrap sampling method (1000 trees) using R-language packages. Then, the best model is used to identify important predictors of FBI by variable importance (VIMP) and minimal depth measures.

    Results

    According to prediction accuracy results by out-of-bag (OOB) C-index and integrated Brier score (IBS), RSF outperforms CPH and CIF in analyzing FBI (C-index of 0.754 for RSF vs 0.688 for CIF and 0.524 for CPH and IBS of 0.076 for RSF vs 0.086 for CIF and 0.107 for CPH). Woman’s age was the most important predictor on FBI.

    Conclusions

    Applying suitable method in analyzing FBI assures the results which be used for making policies to overcome decrement in total fertility rate.

    Keywords: Survival Analysis, Machine Learning, Cox-proportional hazards model, First Birth Intervals
  • Masoomeh Gholami*, Majid Najafzadeh, Naser Behnampour, Zahra Abdollahi, Farzaneh Sadeghi Ghotbabadi, Farhad Lashkarboluki, Mohammad Reza Honarvar Pages 24-33
    Background and objectives

    Iran was reported in the high-risk group of World Food Security Map in 2008 .Identifying food insecurity is first step for executing interventions. Measuring household food security is its cornerstone. SAMAT System was designed to provide a variety of GIS-based reports to policy makers and managers in the field of food security.

    Methods and Materials:

     SAMAT system was developed by a team working with various specialties. The system was analyzed using Rational Unified Process methodology and after optimization and normalization process, centralized database was formed. SQL Server 2014 software was used for its implementation. SharpMap open source engine was used to render spatial data and display maps on the web, and many parts of the engine were coded specifically to meet different organizational needs. The system was designed using the WEB GIS engine.

    Results

    SAMAT system was executed in nine provinces of the country in different periods. SAMAT dashboard provides a variety of information for executive managers. Based on demographic data, the state of food insecurity can be identified at different levels from city to village, in a variety of graphs. A spectrum from the urban distribution to the local distribution of food insecurity can be identified on the GIS map. Zooming in on different areas can help to identify more food insecure neighborhoods within the village or town, thus giving managers the priority of food insecurity interventions at the neighborhood or village level. One can view household characteristics and the results of questionnaire information .

    Conclusion

      SAMAT system can be useful for managing food security at the national, provincial, city and even rural or urban levels. we recommend periodically prioritizing points, Identifying the provinces and re-evaluating the effectiveness of interventions through the SAMAT-based system after comprehensive implementation of food insecurity reduction

    Keywords: Nutritional Status, Software, Geographic Information Systems, Food Supply
  • Javad Sayyahi*, Hayedeh Mobaiyen, Behboud Jafari, Abolfazl Jafari Sales Pages 35-44
    Background and objectives

    As much as people become aware of the dangerous side effects of synthetic antibiotics, the demand for natural alternatives to these drugs increases. Natural ingredients, lower risk of complications and even have beneficial side effects. The aim of this study was to determine the antibacterial effect of herbs Reum ribes L and hyssop Hyssopus officinalis is on some pathogenic bacteria.

    Methods

    After collecting and confirming the scientific name, the methanolic extract of R. ribes L. and  H. officinalis  plants was prepared and the antimicrobial effects of the extracts by agar well diffusion and disk diffusion , as well as the determination of The minimum bactericidal concentration and the minimum inhibitory concentration (MIC / MBC)  were dilution test on Staphylococcus aureus, Bacillus cereus, Escherichia coli and Pseudomonas aeruginosa.

    Results

    The highest growth inhibitory zone in S. aureus, B. cereus, P. aeruginosa, and E. coli at concentrations of 400 mg / ml, respectively, in the disc method of 13.21, 13.41, 11.2 and10.74 mm and the well method, respectively 13.64, 13.11, 10.67 mm, and 9.38 mm for the R. ribes L extract, and the disc method of 11.74, 10.2, 10.71, and 9.1 mm, and the well method of 12.41, 11.6, 10.2, and 9.9 respectively. 4.3 mm was observed for H. officinalis extract. The results of MBC / MIC showed that the extract of medicinal plants had the highest susceptibility to B. cereus bacteria and the least susceptibility to E. coli.

    Conclusion

    R. ribes L. and  H. officinalis  plants have significant inhibitory effects on the growth of pathogenic bacteria in vitro. Therefore, it can be expected that these extracts can be used for the treatment of bacterial infections and are a good alternative to the usual chemical treatments for the treatment of infections.

    Keywords: Antibacterial effects, Pathogenic bacteria, Medicinal plants, Extract
  • Paria Motahari*, Fatemeh Pournaghi Azar, Parisa Rasouly Pages 45-55
    Background and objectives

    Most studies have identified interferon-gamma (IFN-γ) as a key role in the pathogenesis of oral lichen planus (OLP). Recent studies have also shown a link between IFN-γ (+874 A/T) gene polymorphism and OLP. The purpose of the present meta-analysis is to investigate the relationship between IFN-γ (+874 A/T) gene polymorphism and susceptibility to OLP.

    Methods

    A systematic search of resources to investigate the association between IFN-γ and OLP from Google scholar, PubMed, Embase, Cochrane, Scopus, Proquest, Ovid and Web of science (from 2000 to April 2019) completed. Two individuals independently assessed the quality of the articles. Endnote X5 resource management software was used to organize, study titles and abstracts as well as identify duplicates. A random effect model was also used to perform the meta-analysis.

    Results

    Four IFN-γ (+874 A/T) polymorphism studies with 297 patients in the case group and 621 healthy controls in the 4 different countries were included. After meta-analysis, a significant association was found between IFN-γ polymorphism (+874 A/T) and OLP. (T vs A: odds ratio (OR) = 1.62; 95% CI = 1.28-2.04; TT vs AA: OR = 2.67; 95% CI = 1.6- 4.45; AT vs AA: OR = 1.56; 95% CI = 1.6- 4.45; TT vs AT + AA: OR = 1.73; 95% CI = 1.13-2.64; AT + TT vs AA: OR = 1.75; 95% CI = 1.28-2.43)

    Conclusion

    Based on this meta-analysis, there was a positive relationship between IFN-γ (+874 A/T) gene polymorphism and the risk of OLP. The findings showed that increasing TT genotypes significantly increased susceptibility to OLP in comparison with other genotypes.

    Keywords: oral lichen planus, gene polymorphism, IFN-γ