Digital Holographic Microscopy of Phase Separation in Multicomponent Lipid Membranes

Lateral in-homogeneities in lipid compositions cause microdomains formation and change in the physical properties of biological membranes. With the presence of cholesterol and mixed species of lipids, phospholipid membranes segregate into lateral domains of liquid-ordered and liquid-disordered phases. Coupling of two-dimensional intralayer phase separations and interlayer liquid-crystalline ordering in multicomponent membranes has been previously demonstrated. By the use of digital holographic microscopy (DHMicroscopy), we quantitatively analyzed the volumetric dynamical behavior of such membranes. The specimens are lipid mixtures composed of sphingomyelin, cholesterol, and unsaturated phospholipid, 1,2-dioleoyl-sn-glycero-3-phosphocholine. DHMicroscopy in a transmission mode is an effective tool for quantitative visualization of phase objects. By deriving the associated phase changes, three-dimensional information on the morphology variation of lipid stacks at arbitrary time scales is obtained. Moreover, the thickness distribution of the object at demanded axial planes can be obtained by numerical focusing. Our results show that the volume evolution of lipid domains follows approximately the same universal growth law of previously reported area evolution. However, the thickness of the domains does not alter significantly by time; therefore, the volume evolution is mostly attributed to the changes in area dynamics. These results might be useful in the field of membrane-based functional materials

Hepatitis a seroprevalence and associated risk factors: A communitybased cross-sectional study in Shahrekord, Iran

Background: Recently, the epidemiology of hepatitis A virus (HAV) infection has been changing sue to lifestyle-related variations. To our knowledge, there are no published data about the seroepidemiology of this infection in Shahrekord, central Iran, by which decisions on the commissioning of a vaccination program could be made. Objectives: This study aimed to assess the seroprevalence of HAV immunoglobulin G (IgG) antibody at the Shahrekord Center of Chaharmahal and Bakhtiari province, southwest Iran. Patients and Methods: In this cross-sectional study, using the multistage cluster sampling method, a total of 501 serum samples from the same number of individuals over 15 years in both urban and rural areas of Shahrekord, during 2013 were tested for HAV IgG antibody using enzyme-linked immunosorbent assay (ELISA). The data were analyzed using the Pearson chi-square test. Logistic regression was also used to calculate odds ratios (ORs) with 95% confidence intervals (CIs). Results: It was found that 455 out of 501 (90.8%) serum samples, including those of 211 (42.1%) men and 290 (57.9%) women, were positive for HAV IgG antibody. Education level, age, marital status, and ethnicity were associated with HAV seropositivity in the studied individuals (P < 0.05). Conclusions: The HAV seroprevalence of 90.8% in the studied region may be representative of a highly endemic region of HAV that does not require a vaccination program to be commissioned. © 2016, Infectious Diseases and Tropical Medicine Research Center

A Study of the Comparison between Artificial Neural Networks, Logistic Regression and Similarity Weighted Instance-based Learning in Modeling and Predicting Trends in Deforestation

The change in forest cover plays a vital role in ecosystem services, atmospheric carbon balance, and, thus, climate change. In this study, land use maps for the periods 1984 and 2012, derived from Landsat TM satellite imagery, were used. The goal of this study is comparison of three procedures of artificial neural network, logistic regression, and similarity weighted instance-based learning (SIM Weight) to predict spatial trend of forest cover change. The SimWeight considers the nearest instances in the variable space, which are computed based on past changes and the relative importance of the driving variables. The LogReg approach, on the other hand, is a type of generalized linear model that assumes that the current land use pattern reflects the processes of land use in the past. Artificial Neural Network is a nonparametric algorithm that is capable of fitting complex nonlinear functions to find the relations between past changes and their driving variables. Such approaches are expected to produce better fitting between the change potential and their complex relationships with their driving variables. Artificial neural networks in comparison with logistic regression and SimWeight have higher accuracy and less error in modeling and predicting of forest changes

The impact of COVID-19 outbreak on emotional and cognitive vulnerability in Iranian women With Breast Cancer

The psychological cost on emotional well-being due to the collateral damage brought about by COVID-19 in accessing oncological services for breast cancer diagnosis and treatment has been documented by recent studies in the United Kingdom. The current study set out to examine the effect of delays to scheduled oncology services on emotional and cognitive vulnerability in women with a breast cancer diagnosis in Iran, one of the very first countries to be heavily impacted by COVID-19. One hundred thirty-nine women with a diagnosis of primary breast cancer answered a series of online questionnaires to assess the current state of rumination, worry, and cognitive vulnerability as well as the emotional impact of COVID-19 on their mental health. Results indicated that delays in accessing oncology services significantly increased COVID related emotional vulnerability. Regression analyses revealed that after controlling for the effects of sociodemographic and clinical variables, women’s COVID related emotional vulnerability explained higher levels of ruminative response and chronic worry as well as poorer cognitive function. This study is the first in Iran to demonstrate that the effects of COVID-19 on emotional health amongst women affected by breast cancer can exaggerate anxiety and depressive related symptoms increasing risks for clinical levels of these disorders. Our findings call for an urgent need to address these risks using targeted interventions exercising resilience

Corrigendum to “The effectiveness of counseling based on acceptance and commitment therapy on body image and self-esteem in polycystic ovary syndrome: An RCT” [Int J Reprod BioMed 2020; 18: 243–252]

This is a Corrigendum to “The effectiveness of counseling based on acceptance and commitment therapy on body image and self-esteem in polycystic ovary syndrome: An RCT” [Int J Reprod BioMed 2020; 18: 243–252]

The effectiveness of counseling based on acceptance and commitment therapy on body image and self-esteem in polycystic ovary syndrome: An RCT

Background: Polycystic ovary syndrome (PCOS) is one of the most common endocrine and metabolic disorders known with irregular menstruation, hirsutism, alopecia, obesity, infertility, and acne. These symptoms cause a negative effect on the satisfaction of body image, self-esteem, and quality of life in such patients. Recent studies emphasize the need to consider the psychological problems in these women and also the need for appropriate interventions. Objective: The aim of this study was to determine the effectiveness of group counseling based on acceptance and commitment therapy (ACT) on body image and self-esteem in patients with PCOS. Materials and Methods: In this randomized controlled trial, 52 women with PCOS were randomly allocated to intervention and control groups (n = 26/each) using the table of random numbers. Group counseling based on the ACT was held in eight sessions of 90 min once a week for the intervention group. The demographic questionnaire, Littleton development of the body image concern inventory and Rosenberg self-esteem scale were completed in both groups before, immediately after, and one month after the intervention. Results: The mean scores of body image concern (p = 0.001) and self-esteem (p ≤ 0.001) in the intervention group after the intervention and follow-up were significantly different from the control group. Conclusion: Based on the findings of this study, use of cognitive-behavioral therapies in health care centers is recommended as a complementary method. Key words: Acceptance and commitment therapy, Body image, Self-esteem, Polycystic ovary syndrome, Cognitive behavior therapies

Distribution and pollution level of nickel and vanadium in sediments from south part of the Caspian Sea, Iran

765-771Distribution and pollution level of nickel and vanadium in sediment from south part of the Caspian Sea, north of Iran, were studied. Sediment samples obtained by Van Veen Grab from four stations, including, Turkaman, Amirabad, Fereydunkenar and Noushahr along the south part of the Caspian Sea, during fall of 2015 and april, summer and winter of 2016. The concentrations of metal were ranged from 21.63 µg/g to 55.45 µg/g for nickel and from 58.23 µg/g to 146.27 µg/g for vanadium in sediments samples collected from all stations. There was significant difference in metals concentration between different stations along the Caspian Sea (P < 0.05), and the highest mean concentration of metals was absorbed in Fereydunkenar estuary, followed by Amirabad, Turkaman and Noushahr, respectively. The results showed that there were significant differences between metals pollution during four seasons (P < 0.05), and the highest concentration of metals were absorbed in dry season (summer) and the lowest concentration in wet season (winter). There was a positive correlation between nickel and vanadium concentration in sediment samples, and the Pearson correlation was (r = 0.67) between nickel and vanadium in sediment samples. The positive correlation between heavy metals can be related to same source of both metals in the environment. Based on our results, anthropogenic activities such as oil industry and agriculture activities are the main sources of pollution in the coasts along south part of Caspian Sea

Comparing clinical outcomes in patients with diabetes undergoing coronary artery bypass graft and percutaneous coronary intervention in real world practice in Iranian population

Funding Information: I would like to thank the Deutsche Forschungsgemeinschaft (DFG) for the financial support of our conference. Part of the funding for the conference also came from the European Union’s Horizon 2020 research and innovation program (RISE) under the Marie Skłodowska‐Curie grant agreement No. 101008129 ( project acronym “Mycobiomics”). Last but not least, I would like to thank Mr. Georg Schabel for the nice photographs that he took during the meeting.Peer reviewedPublisher PD