Comparison of sexual function in infertile women with polycystic ovary syndrome and endometriosis: A cross-sectional study

Background: Infertility is one of the issues affecting sexual function (SF). Infertility is also one of the complications of polycystic ovary syndrome (PCOS) and endometriosis. Objective: This research seeks to assess and compare SF and the prevalence of sexual dysfunction in infertile women with PCOS and endometriosis. Materials and Methods: A cross-sectional study was carried out with a sample of 630 (210 infertile women with endometriosis, 210 infertile women with PCOS, and 210 healthy women of childbearing age as the control group). SF was assessed by the female sexual function index (FSFI). Descriptive statistics and inferential statistics were used to analyze the data. The primary outcome measured was FSFI score. Secondary outcome was hospital anxiety and depression scale score. Results: The results showed that the mean score of the total FSFI in the 2 groups of PCOS and endometriosis was lower than the control group (p < 0.001). In addition, women with higher education (university education) had a higher total FSFI. Conclusion: Sexual dysfunction rates are high in infertile women with endometriosis and PCOS. Infertility service providers in infertility centers need to pay attention to this issue. Key words: Polycystic ovarian syndrome, Endometriosis, Infertility, Sexual dysfunction

Hepatic Artery Aneurysms as a Rare but Important Cause of Abdominal Pain; a Case Series

Hepatic artery aneurysm (HAA) is the common visceral aneurysms with the highest reported rate of rupture. The clinical manifestations depending on the size of the aneurysm include epigastric pain, obstruction of biliary tract, rupture and death. Imaging modalities like computed tomography (CT) scan and CT-angiography have a valuable role in the early detection of HHAs. Complications and selecting appropriate treatments depending on the size and location of the aneurysms. This article aimed to report clinical presentation, imaging finding and treatment of some patients presenting with HAAs to emergency department

The Economic Burden of Acute Myeloid Leukemia in Iran

Background: Cancer imposes a significant economic burden on the health system and society. Acute myeloid leukemia (AML) is the third deadliest leukemia and is one of the leading health problems worldwide. The present study aimed to estimate the economic burden of AML in Iran for 2020. Methods: In this study, we estimated a prevalence-based on the cost-of-illness of the AML in Iran. A societal perspective was considered, in which the direct costs and productivity losses with the adoption of the human capital approach in the AML cases were estimated for 2020. Moreover, in the present study, several resources including national cancer registry reports, hospital records, occupational data, and interviews with experts were cited. Results: Approximately 98% of patients with AML received induction therapy. The AML economic burden was $33,243,107.39. Indirect costs accounted for 60$) of this amount, and direct medical costs and direct non-medical costs make up for 19% (6,359,380.88$) and 16$) of this estimated economic burden, respectively Conclusion: The economic burden of AML in Iran is very remarkable and due to the increasing prevalence of this disease, it is expected to increase gradually. Having insights into the costs associated with the disease provide an excellent opportunity for health policymakers and managers to effectively improve resource allocation

Correlation between Grades in the Medical Basic Science Course and Scores on the Comprehensive Basic Sciences Exam in Iran

Introduction: Medical students in Iran are required to undertake a Basic Sciences Comprehensive Exam (BSCE) at the end of their BS course in order to progress to the next stage of medical education. BSCE results are widely used to evaluate medical education programs among different medical universities. The aim of this study is to explore the correlation between BSCE results and students’ mean BS course scores.Methods: A cross-sectional study, using secondary data analysis, was carried out in 2007 in Hormozgan University of Medical Sciences (HUMS) in Iran. Data from the 20th BSCE (held in 1998) to the 36th BSCE (held in 2006) was collected. All medical students who took these exams and for whom the mean results of the BS course and the BSCE were available were eligible for inclusion in the study. For each medical student, data were obtained regarding age at the time of participation in BSCE, together with sex, entrance year, zone as categorised by the national quota system, mean BS course scores, BSCE result, duration of BS course (number of semesters) and number of failed semesters. Students whose data was not complete were excluded from the study. Data was analysed by using SPSS 15 (SPSS Inc., Chicago, Illinois, USA) software.Results: 372 students undertook the BSCE during the research study period. Complete data was available for 365 medical students (98.1%). Among the participants, 224 (61.4%) were female and 141 (38.6%) were male. The mean age at the time of sitting the BSCE was 22.01±1.22. Mean BSCE scores were higher among students who had not previously failed a semester and who also finished the BS course within five semesters. Students with higher BS course scores had higher BSCE scores (P=0.000).Conclusions: Students’ BS course scores were found to correlate to BSCE results. Hence it may be prudent to identify medical students with low BS course scores, in order to provide additional educational support to improve their medical knowledge and thereby enhance their performance on the BSCE

Potential Molecular Mechanisms of Bisphenol A in Obesity Development

Bisphenol A (BPA), an endocrine disruptor, is associated with metabolic disorders. However, several studies have suggested that exposure to BPA can cause obesity. It has recently got more attention from scientists as a risk factor for obesity due to its ability to mimic natural estrogens and bind to their receptors. Nonetheless, the molecular mechanism underpinning the environmental etiology of metabolic disorders has not been not fully clarified. In this regard, BPA exposure directly disrupts endocrine regulation, neuroimmune and signaling pathways, and gut microbes, resulting in obesity. In addition, epidemiological studies have revealed a significant relationship between BPA exposure and the development of obesity, although conflicting results have been reported. Therefore, this review summarized the possible role and molecular mechanisms associated with BPA exposure that may lead to obesity based on in vivo and in vivo studies

Effectiveness of Acceptance and Commitment-based Therapy on Psychological Flexibility among Mothers with Autistic Children

Background and Aim: The purpose of this study was to investigate the effectiveness of acceptance-based treatment on psychological flexibility of mothers of children with autism disorder. Materials and Methods: This study was a quasi-experimental pretest-posttest with control group. The statistical population of the present study included mothers with autistic children referring to the autism community in Qom city at 2017. According to the semi-experimental design and Criteria for research, a sample of 30 patients (each group of 15) was selected voluntarily. Samples were randomly assigned to two experimental and control groups. The experimental group received 8 sessions of "acceptance and commitment therapy. The instrument for collecting information included the Acceptance and Action Questionnaire-II (AAQ-II). Data were analyzed by SPSS software using covariance. Ethical Considerations: This study with research ethics code IR.IAU.ARAK.REC.1396.39 has been approved by research ethics committee at Islamic Azad University of Arak, Iran. Findings: Based on study findings, the acceptance- and commitment-based therapy had significant impact on psychological flexibility in mothers of children with autism. Conclusion: Based on the findings, it can be concluded that acceptance and commitment therapy is effective in improving the mental health of mothers with childhood autism

Disaster Preparedness: Knowledge, Attitude, and Practice of Hospital Staff

Background: A disaster, as a serious disruption in the functioning of society, may cause extensive damage. Following a disaster, the demand for healthcare increases, and people rush to healthcare centers. In such situations, health staff and medical services play an important role. As a result, people’s knowledge, attitude, and practice toward disaster preparedness in the workplace play an important role in accident prevention. Materials and Methods: This cross-sectional analytical descriptive study was conducted to evaluate the level of knowledge, attitude, and practice of hospital staff to prepare for disasters in 2020. A total number of 350 hospital staff working at Shiraz University of Medical Sciences were selected using the cluster sampling method. A researcher-made questionnaire was used to collect the data and SPSS software, version 21 was used to analyze the data. Results: The mean scores for knowledge, attitude, and practice regarding disaster preparedness were 9.44±1.53, 39.26±4.8, and 7.26±3.66, respectively. In addition, 74.5%, 89.5%, and 29.2% of participants showed good knowledge, attitude, and practice, respectively. There was a significant relationship between knowledge and attitude (r=254, P<0.001), knowledge and practice (r=205, P<0.001), and attitude and practice (r=161, P=0.004).  Conclusion: Results revealed a good level of knowledge and attitude and a moderate level of practice in hospital staff in terms of disaster preparedness. It seems necessary to hold both theoretical and practical training programs as well as operational maneuvers with an emphasis on repetition in appropriate intervals

The Assessment of the Theory of Planned Behavior Structures on Nutritional Prophylactic Treatment of Anemia in Pregnant Women of Arak City in 2018

Background and Aim: Iron deficiency is one of the most common nutritional problems during pregnancy. The purpose of this study was to assess the theory of planned behavior structures on nutritional prophylactic treatment of anemia in pregnant women of Arak city in 2018. Materials and Methods: This is a cross-sectional study that was carried out on 199 pregnant women in Arak city using simple random sampling in 2018. The data were gathered with valid and reliable researcher-made questionnaire including demographic information and the theory of planned behavior structures. The study was conducted to determine the most important predictive constructs of pregnant womens’ behavior using a multivariate linear regression model. Findings: The finding showed that mean age of mothers was 28.81 ± 5.1 years and the mean weekly gestation was 28.04 ± 8.9 weeks and the gestational interval with previous pregnancy was 5.18 ± 3.9 years. Mean±standard deviation of attitude score (3.61 ± 0.62), subjective norm (3.60 ± 0.74), perceived behavior control (3.50 ± 0.58), behavioral intention (3.49 ± 0.61), performance (3.55 ± 0.76) and awareness (0.57±0.2) were observed. Linear regression model showed that the performance score of pregnant women improved for each unit of attitude and subjective norms and perceived behavioral control, respectively, by 0.463, 0.343 and 0.347, respectively. Conclusion: The results emphasize the provision of educational programs on the prevention of anemia in pregnant women with an emphasis on attitudinal structures, mental norm, and perceived behavioral control. It is suggested that at the time of designing interventions to improve the prevention of anemia in pregnancy, the structures of the theory of planned behavior should be considered

A Deep Learning Approach for Exploring the Design Space for the Decarbonization of the Canadian Electricity System

Conventional energy system models have limitations in evaluating complex choices for transitioning to low-carbon energy systems and preventing catastrophic climate change. To address this challenge, we propose a model that allows for the exploration of a broader design space. We develop a supervised machine learning surrogate of a capacity expansion model, based on residual neural networks, that accurately approximates the model&rsquo;s outputs while reducing the computation cost by five orders of magnitude. This increased efficiency enables the evaluation of the sensitivity of the outputs to the inputs, providing valuable insights into system development factors for the Canadian electricity system between 2030 and 2050. To facilitate the interpretation and communication of a large number of surrogate model results, we propose an easy-to-interpret method using an unsupervised machine learning technique. Our analysis identified key factors and quantified their relationships, showing that the carbon tax and wind energy capital cost are the most impactful factors on emissions in most provinces, and are 2 to 4 times more impactful than other factors on the development of wind and natural gas generations nationally. Our model generates insights that deepen our understanding of the most impactful decarbonization policy interventions

A Deep Learning Approach for Exploring the Design Space for the Decarbonization of the Canadian Electricity System

Conventional energy system models have limitations in evaluating complex choices for transitioning to low-carbon energy systems and preventing catastrophic climate change. To address this challenge, we propose a model that allows for the exploration of a broader design space. We develop a supervised machine learning surrogate of a capacity expansion model, based on residual neural networks, that accurately approximates the model’s outputs while reducing the computation cost by five orders of magnitude. This increased efficiency enables the evaluation of the sensitivity of the outputs to the inputs, providing valuable insights into system development factors for the Canadian electricity system between 2030 and 2050. To facilitate the interpretation and communication of a large number of surrogate model results, we propose an easy-to-interpret method using an unsupervised machine learning technique. Our analysis identified key factors and quantified their relationships, showing that the carbon tax and wind energy capital cost are the most impactful factors on emissions in most provinces, and are 2 to 4 times more impactful than other factors on the development of wind and natural gas generations nationally. Our model generates insights that deepen our understanding of the most impactful decarbonization policy interventions.Science, Faculty ofNon UBCComputer Science, Department ofReviewedFacult