Introduction: Glioblastoma multiforme (GBM) is a grade IV glioma and accounts for 15% of all primary brain tumors. This GBM has a median survival range of less than 2 years after diagnosis and it is highly vascularized by neoformed vessels. Neoangiogenesis is a crucial factor in the malignant tumoral behavior and prognosis of patients and Nestin protein belongs to class VI which is expressed in endothelial cells of neoformed vessels in GBM. Our study shows the correlation between EGFR mutation and Nestin expression in endothelial of neoformed vessels in GBM. Methods: We analyzed 40 GBM samples by immunohistochemistry staining. The immunohistochemical expression of EGFR in tumoral cells and Nestin in endothelial cells in paraffin sections were analyzed. EGFR scoring was the based on staining intensity. Score 0 shows No staining, Score1, mild to moderate staining and score2 sever staining. Microvascular density (MVD) was evaluated with Nestin-immunoreactive. Results: The mean of MVD was 14.6 ±8.25. Nestin-MVD was significantly higher in GBM with sever vascular prolifration (p-value=0.01). EGFR was expressed in 92.5% of samples. The EGFR scoring for tumoral tissue was 7.5%(score:0), 22.5% (score:1) and 70% (score:2). There was a significant relationship between EGFR expression and MVD (p-value=0.017). Conclusion: We suggest that some important mutations as like as EGFR in GBM is responsible for inducing angiogenesis and vascular proliferation. Nestin overexpression as a novel marker might reflect the extent of neoangiogenesis, thus target therapy against EGFR pathway and anti angiogenic may be useful for GBM treatment.
When dealing with risks associated with complex sociotechnical systems, one needs to employ approaches that will make it possible to better understand the systems' complexity and analyze them more efficiently. Several approaches have been proposed and in the recent literature, the System-Theoretic Accident Model and Processes (STAMP) and Functional Resonance Analysis Method (FRAM) stand out. These have been applied both separately and integrated with other methods for risk analysis. This study aims to provide an overview of the literature related to the application of FRAM and STAMP integrated with other methods. Papers from various scientific resources, including Scopus, IEEE, Compendex and INSPEC, Google Scholar, and Espace ÉTS from 2004 to 2021, in English, were consulted. The keywords used to narrow our search were FRAM, STAMP, STPA, and risk analysis. The results show that FRAM and STAMP have been used in combination with other methods such as fuzzy logic, Monte Carlo Simulation, bow tie, and model checking. Their combination with other methods has enhanced their efficiency and capability in risk analysis and provides better and more precise outcomes for some specific contexts of study. These combined proposed approaches have been applied and validated for specific contexts in specific studies. Therefore, the generalization and validation of the combined methods in different contexts could be an outlook for future studies.
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