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Interactive effects of eight weeks massage therapy along with Apium graveolens seed consumption on serum levels of IGF-1 and P53 in overweight women
Mahdieh Asadi, Parvin Farzanegi,
Volume 2, Issue 1 (5-2014)
Abstract
Background & Objective: High blood levels of IGF-1 in women before menopause, is a risk factor and P53 tumor suppressor gene is also one of the most common genes involved in breast cancer. Since some studies demonstrated that physical activity and compounds found in Celery have anti-cancer effects, this study aimed to investigate the interactive effects of eight weeks massage therapy along with celery seed supplementation on the levels of IGF-1 and P53 in overweight women. Method: In a single, blind, placebo-controlled clinical trial, the interactive effects of eight weeks massage therapy along with celery seed consumption on IGF-1 and P53 serum concentrations in overweight women were measured. For this purpose, 28 overweight women with a BMI of more than 25 kg/m2 in Ghaemshahr were randomly divided into four groups. Weight and serum levels variables of IGF-1 and P53, prior and after the therapy were measured. Then the data were analyzed using t-test and one-way variance analysis. P<0.05 was considered as the level of significance Results: At the end of the study, the average of weight and level of IGF-1 and P53 in experimental groups (massage therapy, Therapy and supplementation, Supplementation) were decreased. There was a significant difference between the weight (P=0.003), the level of IGF-1 (P <0.001) and P53 (P<0.001) of women before and after the start of the intervention in the experimental group while the control group was not changed. Conclusion: The results show that massage therapy along with celery seed supplements, especially the combination of these two non-pharmaceutical approaches have beneficial effects on body weight and IGF-1 and P53 levels in overweight women.
Tumorigenicity of Esophageal Cancer Stem Cells (ECSCs) in nude mouse xenograft model
Ayyoob Khosravi, Fariba Kokabi, Ramezan Behzadi, Jahanbakhsh Asadi,
Volume 7, Issue 3 (9-2019)
Abstract
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.
 

A Survey for Predictors of Mortality among COVID-19 Patients: A Retrospective Study from Iran
Arezoo Monfared, Mohammad Taghi Moghadamnia, Samad Karkhah, Saman Maroufizadeh, Mohammad Asadian Rad, Jalal Kheirkhah, Fatemeh Jafaraghayee,
Volume 9, Issue 4 (12-2021)
Abstract
Background and Objective: In the current COVID-19 pandemic, disease diagnosis is essential for optimal management and timely isolation of infected cases in order to prevent further spread. The aim of this study is to assess of predictors of mortality among COVID-19 patients.
Material and Methods: In a retrospective study, 522 COVID-19 patients were enrolled in Razi hospital, Guilan Province, Iran. This hospital was the main center for the treatment of COVID-19 patients in Guilan province. Data gathering was performed by census sampling from March to August 2020. Simple and Multiple logistic regression analysis was applied to assess the relationships of clinical and demographic characteristics with in-hospital mortality.
Results: Multiple logistic regression showed that older age (aOR=1.04, 95%CI: 1.02 to 1.06, P<0.001), decreased O2 saturation (aOR=0.89, 95%CI: 0.86 to 0.92, P<0.001), having a dysrhythmia (aOR=2.97, 95%CI: 1.46 to 6.05, P=0.003), symptoms associated with heart failure (aOR=0.43, 95%CI: 0.18 to 0.99, P=0.048), and mixed drug antiviruses (aOR=2.44, 95%CI: 1.22 to 4.90, P=0.012) were mortality predictor variables among COVID-19 patients.
Conclusion: Therefore, special attention should be paid to the factors influencing the mortality of COVID-19 patients. It is recommended that older patients, dysrhythmia, and symptoms associated with heart failure be treated with extreme caution.

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