Mehrzad Jafarzadeh

Background: In the majority of cancers, metastasis of tumor cells is the main cause of treatment failure. This study intended to investigate the effectiveness of basic fibroblast growth factor (bFGF) peptide designed to inhibit tumor growth in 4T1 metastatic breast cancer through the PI3K/AKT and ERK/MAPK signal transduction pathways. Methods: The tumor was induced through 4T1 tumor graft in BALB/c mice. The designed peptide was injected intraperitoneal at three selected doses after two weeks for 14 days. The PBS and doxorubicin were used as the negative and positive control groups, respectively. Tumor size was measured and after the treatment period, the mice underwent a surgery and tumors were used for the western blot examinations. Results: the peptide injection was effective in reducing or inhibiting tumor growth in mice model and in vitro. The western blot analysis results showed that the p-AKT and p-ERK levels in peptide treated tumors were reduced (p<0.05). Conclusion: The peptide injection was effective in mice model. Findings showed that in the two signal transduction pathways, the p-AKT and p-ERK levels were significantly different from the negative control group.

Objectives. Although the risk factors for diabetic neuropathy and diabetic foot ulcer have been detected, there was no practical modeling for their prediction. We aimed to design a logistic regression model on an Iranian dataset to predict the probability of experiencing diabetic foot ulcers up to a considered age in diabetic patients. Methods. The present study was a statistical modeling on a previously published dataset. The covariates were sex, age, body mass index (BMI), fasting blood sugar (FBS), hemoglobin A1C (HbA1C), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglyceride (TG), insulin dependency, and statin use. The final model of logistic regression was designed through a manual stepwise method. To study the performance of the model, an area under receiver operating characteristic (AUC) curve was reported. A scoring system was defined according to the beta coefficients to be used in logistic function for calculation of the probability. Results. The pretest probability for the outcome was 30.83%. The final model consisted of age ( ), BMI ( ), FBS ( ), HDL ( ), and insulin dependency ( ) ( ). The performance of the model was definitely acceptable ( ). Conclusion. This model can be used clinically for consulting the patients. The only negative predictor of the risk is HDL cholesterol. Keeping the HDL level more than 50 (mg/dl) is strongly suggested. Logistic regression modeling is a simple and practical method to be used in the clinic.

Background In the majority of cancers, metastasis of tumor cells is main cause of treatment failure. The current research investigated the effectiveness basic fibroblast growth factor (bFGF) peptide developed to inhibit tumor growth in 4T1 metastatic breast cancer through the PI3K/AKT and ERK/MAPK signal transduction pathways. In BALB/c mice, the tumor was induced through 4T1 tumor graft. Administration of the peptide was done one time a day at various doses of 1, 2.5, or 10 mg/kg over 14 days. After two weeks, the designed peptide injected .After the treatment period, the mice underwent surgery, and tumors were used for the Immunohistochemistry, Apoptosis, and western blot examinations.Results Based on one-way ANOVA and p ≤0.05, findings showed that the P-AKT and p-ERK contents in tumors treated with peptide reduced in two mentioned signaling pathways and the peptide injection were effective in reducing or inhibiting tumor growth.Conclusion Our findings showed that in the two signal transduction pathways, the P-AKT and p-ERK levels were significantly different from the negative control group.