Background: Brucellosis is an endemic disease in many countries, especially in the Mediterranean region, as well as countries such as the Islamic Republic of Iran. Despite the preventive measures against brucellosis adopted in different countries throughout the world, the disease is still a public health concern. Aims: Our aim in the present study was to examine the cognitive factors associated with Brucellosis Preventive Behaviours (BPBs) among diagnosed patients utilizing Empowerment Model. Methods: In 2013, applying a cross-sectional study, all 238 patients with brucellosis in Chaldoran County, Islamic Republic of Iran, were recruited to answer a researcher-made EM-based questionnaire and BPBs Scale through interview. Results: Hierarchical multiple linear regressions were performed with BPBs as the outcome variable. Predictors for this variable, according to their natures, were classified in two different blocks. In the first block, significant effect was found on BPBs by demographic variables (∆R2 = 0.301). In the second block, the level of education, knowledge, and self-efficacy were significant predictors (P < 0.001) of BPBs (∆R2 = 0.808). Conclusions: The Empowerment Model was found as a helpful framework in predicting the risk factors of BPBs. Health care providers in low-and middle-income countries should consider the patients' knowledge on the disease and their level of self-efficacy to perform BPBs as the core categories of empowerment while designing brucellosis prevention programmes.

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The aim of this study was to assess the efficacy of resveratrol (Res) on radiosensitivity of 5‐fluorouracil (5‐FU) in the spheroid culture of MCF‐7 breast cancer cell line using colony formation examination. Spheroids on day 9 with 300 µm diameters were treated with 20 µM resveratrol and/or 1 µM 5‐FU for one volume doubling time (VDT) (42 hours) and then irradiated with 2 Gy gamma radiation (60Co) in various groups. Then the viability of the cells and clonogenic ability were acquired by blue dye exclusion and colony formation assay, respectively. The population doubling time in the monolayer culture and the VDT of spheroid culture was 22.48 ± 0.23 hours and 42 ± 0.63 hours respectively. None of the drugs and combination of them had any effect on the viability of cells. The combination treatment of 5‐FU+Res+ radiation significantly reduced the colony formation ability of spheroid cells in comparison with each treatment alone. Our results indicated that resveratrol can significantly decrease colony number of breast cancer spheroid cells treated with 5‐FU in combination with gamma‐rays. Thus, resveratrol as a hypoxia‐inducible factor‐1‐alpha inhibitor increased the radiosensitization of breast cancer spheroid cells.

Our aim in this cross-sectional study was to investigate mental health-ill health differences in disease severity and its sociodemographic biobehavioral predictors among patients with knee osteoarthritis (OA). Applying convenient sampling, 180 patients with knee OA in Tabriz, Iran, were recruited to participate in completing a three-section questionnaire (SF-12, Lequesne Algofunctional Index and Self-Management Behaviors Scale). Separate hierarchical multiple linear regressions were performed with OA severity as dependent variable: one for OA patients with positive mental health and other for OA patients with mental disorders symptoms. Among the patients with positive mental health, but not those with symptoms of mental disorder, pain management, duration of OA, physical activity management, living alone, and level of education were significant predictors of disease severity. Health care providers with a better understanding on the determinants of disease severity by mental health status may identify vulnerable patients and develop targeted interventions to foster disease management behaviors among OA patients.

By changing the lifestyle and increasing the cancer incidence, accurate diagnosis becomes a significant medical action. Today, DNA microarray is widely used in cancer diagnosis and screening since it is able to measure gene expression levels. Analyzing them by using common statistical methods is not suitable because of the high gene expression data dimensions. So, this study aims to use new techniques to diagnose acute myeloid leukemia. In this study, the leukemia microarray gene data, contenting 22283 genes, was extracted from the Gene Expression Omnibus repository. Initial preprocessing was applied by using a normalization test and principal component analysis in Python. Then DNNs neural network designed and implemented to the data and finally results cross-validated by classifiers. The normalization test was significant (P>0.05) and the results show the PCA gene segregation potential and independence of cancer and healthy cells. The results accuracy for single-layer neural network and DNNs deep learning network with three hidden layers are 63.33 and 96.67, respectively. Using new methods such as deep learning can improve diagnosis accuracy and performance compared to the old methods. It is recommended to use these methods in cancer diagnosis and effective gene selection in various types of cancer.