Clinical significance of circulating tumor cell related markers in patients with epithelial ovarian cancer before and after adjuvant chemotherapy

Acknowledgment This study was financially supported by grants from Mashhad University of Medical Sciences (No. 961802) and National Institute for Medical Research Development (NIMAD) (No. 973128).Peer reviewedPublisher PD

The effect of fasting on the important molecular mechanisms related to cancer treatment

Fasting does have remarkable benefits in the treatment of cancer and another diseases such as metabolic syndrome, diabetes, and a multitude of other chronic diseases. It has been determined that fasting could play an important role during cancer treatment and progression via the regulation of insulin-like growth factor-1 (IGF-1) as well as other growth factors. Also, it has been shown that fasting would enhance the chemotherapy effect in cancer patients, selectively protects normal cells and organisms from chemotherapy toxicity, while simultaneously sensitizing tumors. In this article, we discuss the benefits of fasting in the treatment of cancer through several different molecular pathways

Detection of effective genes in colon cancer: A machine learning approach

Nowadays, a variety of cancers have become common among humans which unfortunately are the cause of death for many of these people. Early detection and diagnosis of cancers can have a significant impact on the survival of patients and treatment cost reduction. Colon cancer is the third and the second main cause of women's and men's death worldwide among cancers. Hence, many researchers have been trying to provide new methods for early diagnosis of colon cancer. In this study, we apply statistical hypothesis tests such as t-test and Mann–Whitney–Wilcoxon and machine learning methods such as Neural Network, KNN and Decision Tree to detect the most effective genes in the vital status of colon cancer patients. We normalize the dataset using a new two-step method. In the first step, the genes within each sample (patient) are normalized to have zero mean and unit variance. In the second step, normalization is done for each gene across the whole dataset. Analyzing the results shows that this normalization method is more efficient than the others and improves the overall performance of the research. Afterwards, we apply unsupervised learning methods to find the meaningful structures in colon cancer gene expressions. In this regard, the dimensionality of the dataset is reduced by employing Principle Component Analysis (PCA). Next, we cluster the patients according to the PCA extracted features. We then check the labeling results of unsupervised learning methods using different supervised learning algorithms. Finally, we determine genes which have major impact on colon cancer mortality rate in each cluster. Our conducted study is the first which suggests that the colon cancer patients can be categorized into two clusters. In each cluster, 20 effective genes were extracted which can be important for early diagnosis of colon cancer. Many of these genes have been identified for the first time

Investigating the Effect of Inflammation on Atrial Fibrillation Occurrence by Measuring Highly Sensitive C-reactive Protein (hs-CRP)

Introduction: Atrial fibrillation (AF) is the most prevalent cardiac arrhythmias that cardiologists and internists encounter. The goal of this article is to clarify an overview of the evidence linking inflammation to AF existence, which may highlight the effect of some pharmacological agents that have genuine potential to reduce the clinical burden of AF by modulating inflammatory pathways. Materials and Methods: In a case-control study, 50 patients with atrial fibrillation (AF) with different etiologies and 50 patients with sinus rhythm and similar bases were selected. Sampling for highly sensitive c-reactive (hs-CRP) was done on the patients presenting with AF to the Ghaem hospital between October 2006 and June 2007. Results: Mean age of the patients was 62 years with maximum of 90 and minimum of 36 and standard deviation of 13.80. The most frequent age group was 71-80years. Fifty-four percent of patients were male and 46% were female. Mean serum hs-CRP levels in AF patients with hypertension (HTN) ,Ischemic heart disease(IHD), Valvular heart disease (VHD), HTN+IHD and hyperthyroidism were 8.10, 9.40, 8.68, 10.16 and 5.98 mg/Lit; respectively. There was significant difference between hs-CRP levels in hypertensive patients in the two groups (P=0.010). Similar results were observed in IHD patients, VHD patients and HTN+IHD patients in two groups (P=0.015, P=0.037, P=0.000). Conclusion: In addition to some risk factors like baseline cardiac diseases, aging, thyrotoxicosis, pulmonary embolism, pneumonia and cardiac surgery, there also appears to be consistent links between hs-CRP, a marker of inflammation, and the pathogenesis of AF

Ovarian cancer stem cells and targeted therapy

Abstract Background Ovarian cancer has the highest ratio of mortality among gynecologic malignancies. Chemotherapy is one of the most common treatment options for ovarian cancer. However, tumor relapse in patients with advanced tumor stage is still a therapeutic challenge for its clinical management. Main body Therefore, it is required to clarify the molecular biology and mechanisms which are involved in chemo resistance to improve the survival rate of ovarian cancer patients. Cancer stem cells (CSCs) are a sub population of tumor cells which are related to drug resistance and tumor relapse. Conclusion In the present review, we summarized the recent findings about the role of CSCs in tumor relapse and drug resistance among ovarian cancer patients. Moreover, we focused on the targeted and combinational therapeutic methods against the ovarian CSCs

Identification of clinical features associated with mortality in COVID-19 patients

Summary Background To prevent infectious diseases, it is necessary to understand how they are spread and their clinical features. Early identification of risk factors and clinical features is needed to identify critically ill patients, provide suitable treatments, and prevent mortality. Methods We conducted a prospective study on COVID-19 patients referred to a tertiary hospital in Iran between March and November 2020. Of the 3008 patients (mean age 59.3±18.7 years, range 1 to 100 years), 1324 were women. We investigated COVID-19 related mortality and its association with clinical features including headache, chest pain, symptoms on CT, hospitalization, time to infection, history of neurological disorders, having a single or multiple risk factors, fever, myalgia, dizziness, seizure, abdominal pain, nausea, vomiting, diarrhoea and anorexia. Findings There was a significant association between COVID-19 mortality and old age, headache, chest pain, respiratory distress, low respiratory rate, oxygen saturation less than 93%, need for a mechanical ventilator, having symptoms on CT, hospitalization, time to infection, history of hypertension, neurological disorders, cardiovascular diseases and having a risk factor or multiple risk factors. In contrast, there was no significant association between mortality and gender, fever, myalgia, dizziness, seizure, abdominal pain, nausea, vomiting, diarrhoea and anorexia. Interpretation Our results might help identify early symptoms related to COVID-19 and better manage patients clinically