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Abstract Background Machine learning (ML) has shown exceptional promise in various domains of medical research. However, its application in predicting subsequent fragility fractures is still largely unknown. In this study, we aim to evaluate the predictive power of different ML algorithms in this area and identify key features associated with the risk of subsequent fragility fractures in osteoporotic patients. Methods We retrospectively analyzed data from patients presented with fragility fractures at our Fracture Liaison Service, categorizing them into index fragility fracture (n = 905) and subsequent fragility fracture groups (n = 195). We independently trained ML models using 27 features for both male and female cohorts. The algorithms tested include Random Forest, XGBoost, CatBoost, Logistic Regression, LightGBM, AdaBoost, Multi-Layer Perceptron, and Support Vector Machine. Model performance was evaluated through 10-fold cross-validation. Results The CatBoost model outperformed other models, achieving 87% accuracy and an AUC of 0.951 for females, and 93.4% accuracy with an AUC of 0.990 for males. The most significant predictors for females included age, serum C-reactive protein (CRP), 25(OH)D, creatinine, blood urea nitrogen (BUN), parathyroid hormone (PTH), femoral neck Z-score, menopause age, number of pregnancies, phosphorus, calcium, and body mass index (BMI); for males, the predictors were serum CRP, femoral neck T-score, PTH, hip T-score, BMI, BUN, creatinine, alkaline phosphatase, and spinal Z-score. Conclusion ML models, especially CatBoost, offer a valuable approach for predicting subsequent fragility fractures in osteoporotic patients. These models hold the potential to enhance clinical decision-making by supporting the development of personalized preventative strategies.

Introduction: There are contradictory results regarding the effects of the menstrual cycle on changes in blood pressure, heart rate, ventilation, and oxytocin hormone during anesthesia in patients who are candidates for laparoscopic cholecystectomy surgery. Therefore, the present study was performed with aim to investigate the effect of menstrual phases on the hemodynamic changes of patients during laparoscopic cholecystectomy. Methods: This cross-sectional descriptive study was conducted in 2018 on 100 patients who were candidates for laparoscopic cholecystectomy referred to Imam Reza Hospital (affiliated to Tabriz University of Medical Sciences). Patients were divided into two groups: luteal phase and follicular phase. Hemodynamic parameters, including heart rate, blood pressure, arterial oxygen saturation, and end-expiratory CO2 were compared between these groups. Demographic information and hemodynamic status before and during anesthesia were recorded in a researcher-made checklist. Data analysis was performed using SPSS software (version 22) and t-test, chi-square, and repeated measures tests. P0.05). However, according to the results of repeated measures tests, the mean arterial pressure changes during the study were significantly higher in the follicular phase group (P=0.031) than in the luteal phase group (P=0.059). Also, according to the results of t-test, the comparison of the heart rate status between the two groups did not show a significant statistical difference at any time (P˃0.05); However, according to the results of repeated measures tests, heart rate changes during the study were significantly higher in the follicular phase group (P=0.019) than in the luteal phase group (P=0.126). Conclusion: Menstrual cycle significantly affects hemodynamic parameters during anesthesia in patients undergoing laparoscopic cholecystectomy. These changes are more pronounced during the follicular phase compared to the luteal phase.

Background and purpose: The insulin-like growth factor binding protein 3 (IGFBP-3) and its novel death receptor (IGFBP-3R) have been exhibited to have tumor suppressor effects. Despite their prognostic value in some cancers, they have not been elucidated in gastric cancer. Experimental approach: We collected 68 samples from patients with gastric cancer. IGFBP-3 and IGFBP- 3R expression levels were evaluated with quantitative real-time polymerase chain reaction (RT-PCR) and western blotting in patients. The relationship between prognostic factors and IGFBP-3/IGFBP-3R expression was also evaluated. Findings/Results: Our results showed that IGFBP-3 and IGFBP-3R expression was reduced significantly in tumor tissues. We found that there was an association between the reduction of IGFBP-3 with lymph node metastasis and tumor-node-metastasis (TNM) staging. Besides, IGFBP-3R expression was associated with tumor size, lymph node metastasis, differentiation, and TNM classification. Interestingly, we presented that the downregulation of IGFBP-3R was stage-dependent. In survival analysis, our findings showed that low levels of IGFBP-3R mRNA expression exhibited a close correlation with survival rate. Conclusion and implications: The findings of this study showed that the expression levels of IGFBP-3 and IGFBP-3R are valuable prognostic factors. Despite the potential of IGFBP-3, IGFBP-3R plays a significant role as a prognostic factor in gastric cancer. However, these findings need to be developed and confirmed by further studies.

This paper investigates the flow of blood through a slanted stenosed artery beneath the impact of a magnetism field. The equations that control the behavior of blood use a type of derivative called Caputo Fabrizio time fractional derivatives. These equations explain that blood acts like a non-Newtonian Casson fluid. The objective of this study is to explore the governing equations of blood flow in a narrow artery by utilizing Caputo Fabrizio fractional derivatives. Using the Laplace and limited Hankel changes of arrange zero, expository arrangements for the overseeing conditions have been inferred. Using the Akbari Ganji method, simple math problems have been solved and transformed into simpler forms. Answers have been found using this method. This article introduces a new approach by applying the AGM analytical and numerical method to address dimensionless fractional equations related to velocity and pressure, in conjunction with the Capato method, marking a significant innovation. Generally, the velocity of the particles is slower than the velocity of the blood. Anyway, the Reynolds number and Casson's liquid parameters are incrementing in both blood and molecule velocities. However, blood velocity diminishes with an increment within the Hartmann number. These discoveries hold noteworthy suggestions for the progress of atherosclerosis treatment. The narrowing of the diameter of the blood vessel with a radius of 45° and a relative percentage of 35 increases the flow resistance and height of the stenosis.

We herein present a rare case of acute central serous chorioretinopathy (CSC) associated with nonspecific orbital inflammation (NSOI). A 38-year-old woman presented with a 3-day history of ocular pain, reduced vision, periorbital swelling, proptosis, conjunctival chemosis, and restricted eye movements. Optical coherence tomography of the affected eye confirmed signs of CSC. Additionally, a computed tomography scan revealed enlargement of intraconal soft tissues and the lacrimal gland. Ocular ultrasonography detected posterior sclera thickening, indicating posterior scleritis. Following the diagnosis of NSOI, the patient received treatment with systemic corticosteroids, resulting in gradual regression of both the orbital inflammation and CSC. This is the first reported case of localized posterior pole CSC documented in a patient with NSOI. Vigilant monitoring for any ocular disorders is important in patients with orbital inflammation.

Background. Diabetes mellitus (DM) presents a significant global health challenge with considerable cardiovascular implications. Coenzyme Q10 (CoQ10) has gained recognition for its potential as a natural antioxidant supplement in the management of diabetes and its associated cardiovascular complications. Aim. This comprehensive review systematically examines the scientific rationale underlying the therapeutic properties of CoQ10 in mitigating the impact of diabetes and its cardiovascular consequences. The analysis encompasses preclinical trials (in vitro and in vivo) and clinical studies evaluating the efficacy and mechanisms of action of CoQ10. Result & Discussion. Findings reveal that CoQ10, through its potent antioxidant and anti-inflammatory attributes, demonstrates significant potential in reducing oxidative stress, ameliorating lipid profiles, and regulating blood pressure, which are crucial aspects in managing diabetes-induced cardiovascular complications. CoQ10, chemically represented as C59H90O4, was administered in capsule form for human studies at doses of 50, 100, 150, 200, and 300 mg per day and at concentrations of 10 and 20 μM in sterile powder for experimental investigations and 10 mg/kg in powder for mouse studies, according to the published research. Clinical trials corroborate these preclinical findings, demonstrating improved glycemic control, lipid profiles, and blood pressure in patients supplemented with CoQ10. Conclusion. In conclusion, CoQ10 emerges as a promising natural therapeutic intervention for the comprehensive management of diabetes and its associated cardiovascular complications. Its multifaceted impacts on the Nrf2/Keap1/ARE pathway, oxidative stress, and metabolic regulation highlight its potential as an adjunct in the treatment of diabetes and related cardiovascular disorders. However, further extensive clinical investigations are necessary to fully establish its therapeutic potential and assess potential synergistic effects with other compounds.

Free overfalls are hydraulic structures used in flood control, water supply, irrigation, and flow measurements. The hydraulic systems of free overfall depend on rectangular end shape. The studies that dealt with triangular crest are few and almost non-existent. In this study, a triangular end-shape design uses multiple linear regression (MLR) and group method of data handling (GMDH) methods for four models with six sub-models. Then, 24 scenarios were chosen and compared. The discharge coefficient (Cd) of a free overfall with a triangular terminal was predicted using experimental data. The triangular end edge shape increased crest length, the discharge coefficient, and discharge passing over free overfall. To this goal, 180 triangular free fall tests were performed. Data were collected for two triangular free overfalls with an opposite flow direction with three angles 600, 750, and 900. Results of Cd acquired using the two ways discussed above show that the algorithm GMDH outperforms the other method. Values for the GMDH approach mod46 testing variables: RMSE, MARE, SI, R2, and NSE are 6.08 × 10−17, 2.65 × 10−17, 6.00 × 10−17, 100.00%, and 1.00, respectively, while these values for MLR are 0.06332, 0.05970, 0.06624, 15.431%, and −3.0419, respectively. The GMDH technique shows the best results concerning MLR and then chooses the best four scenarios from 24 with a Cd percentage error not exceeding ±2%. HIGHLIGHTS A new triangular end-shape design uses multiple linear regression (MLR) and group method of data handling (GMDH) methods for four models with six sub-models.; Twenty-four scenarios were chosen and compared.; The discharge coefficient (Cd) of a free overfall with a triangular terminal was predicted.; The GMDH technique shows the best results concerning MLR and then chooses the best four scenarios from 24 with a Cd percentage error not exceeding ±2%.;

Abstract Background The large number of SARS-Cov-2 cases during the COVID-19 global pandemic has burdened healthcare systems and created a shortage of resources and services. In recent years, mortality prediction models have shown a potential in alleviating this issue; however, these models are susceptible to biases in specific subpopulations with different risks of mortality, such as patients with prior history of smoking. The current study aims to develop a machine learning-based mortality prediction model for COVID-19 patients that have a history of smoking in the Iranian population. Methods A retrospective study was conducted across six medical centers between 18 and 2020 and 15 March 2022, comprised of 678 CT scans and laboratory-confirmed COVID-19 patients that had a history of smoking. Multiple machine learning models were developed using 10-fold cross-validation. The target variable was in-hospital mortality and input features included patient demographics, levels of care, vital signs, medications, and comorbidities. Two sets of models were developed for at-admission and post-admission predictions. Subsequently, the top five prediction models were selected from at-admission models and post-admission models and their probabilities were calibrated. Results The in-hospital mortality rate for smoker COVID-19 patients was 20.1%. For “at admission” models, the best-calibrated model was XGBoost which yielded an accuracy of 87.5% and F1 score of 86.2%. For the “post-admission” models, XGBoost also outperformed the rest with an accuracy of 90.5% and F1 score of 89.9%. Active smoking was among the most important features in patients’ mortality prediction. Conclusion Our machine learning-based mortality prediction models have the potential to be adapted for improving the management of smoker COVID-19 patients and predicting patients’ chance of survival.

Abstract Background and Aims Street children face a disproportionately higher risk of human immunodeficiency virus (HIV), hepatitis B virus (HBV), and hepatitis C virus (HCV) due to high‐risk sexual and drug use practices. We aimed to estimate the prevalence of these infections and related risk behaviors among street children in Iran. Methods We searched PubMed, Web of Science (ISI), Embase, Scopus, and Google Scholar for the English‐language records and Iranian databases, including SID, Magiran, and IRANDOC for the Farsi‐language records up to September 18, 2022. Random effects analysis was used to obtain prevalence estimates for each condition. Homogeneity across included studies was assessed using I2. Results We extracted data from 18 eligible studies, representing 5646 children (83.2% boys), with a mean age of 10.2 (range: 5–18). The prevalence of HIV, HBV, and HCV were 0.79% (95% confidence intervals [CIs]: 0.0–5.56), 1.97% (95% CI: 1.01–3.19), and 1.88% (95% CI: 0.74–3.46), respectively. The prevalence of lifetime drug use and sexual abuse was 8.32% (95% CI: 4.83–12.62) and 10.18% (95% CI: 3.02–20.67) among street children, respectively. Conclusion The estimated prevalence of HIV, HBV, and HCV among street children in Iran was higher than the estimates in the general population. Moreover, drug use and the experience of sexual abuse were prevalent among this population. These findings suggest the need for targeted prevention programs for street children in Iran.

Summary: qPCR is still the gold standard for gene expression quantification. However, its accuracy is highly dependent on the normalization procedure. The conventional method involves using the geometric mean of multiple study-specific reference genes (RGs) expression for cross-sample normalization. While research on selecting stably expressed RGs is extensive, scant literature exists regarding the optimal approach for aggregating multiple RGs into a unified RG. In this paper, we introduce a family of scale-invariant functions as an alternative to the geometric mean aggregation. Our candidate method (weighted geometric mean minimizing standard deviation) demonstrated significantly better results compared to other proposed methods. We provide theoretical and experimental support for this finding using real data from solid tumors and liquid biopsies. Moreover, the closed form and regression-based solution enable efficient computation and straightforward adoption on various platforms. All the proposed methods have been implemented within an easy-to-use R package with graphics processing unit (GPU) acceleration.

Abstract Background Healthcare-associated infections (HAIs) are a threat to patients. Accurate surveillance is required to identify and prevent HAIs. To estimate the incidence rate, report the accuracy and identify the barriers of reporting HAIs using a mixed-method study. Methods In this quantitative study, we externally evaluated the incidence rate and accuracy of the routine surveillance system in one of the main hospitals by an active follow-up of patients from September to December 2021. We used in-depth interviews with 18 experts to identify the barriers of the routine surveillance system. Results Among 404 hospitalized patients, 88 HAIs were detected. The estimated rate of HAIs was 17.1 (95% Confidence Intervals 95: 14.1, 21.1) per 1000 patient-days follow-up. However, in the same period, 116 HAIs were reported by the routine surveillance system, but the agreement between the two approaches was low (sensitivity = 61.4%, specificity = 82.6%, negative predictive value = 89.7%, and positive predictive validity = 46.5%). The minimum and maximum positive predictive values were observed in urinary tract infection (32.3%) and surgical site infection (60.9%). The main barrier of reporting HAIs was lack of cooperation in reporting HAIs by infection control link nurses and laboratory supervisors. Conclusions The discrepancy between the longitudinal study findings and the routine surveillance might be related to the inaccessibility of the surveillance system to clinical information of patients. In this regard, decreasing the barriers, increasing the knowledge of infection control nurses and other nurses, as well as the development of hospital information systems are necessary.

Introduction: Rhabdomyolysis (RM) may cause some complications such as compartment syndrome and disseminated intravascular coagulation (DIC), which can affect its prognosis. This systematic review and meta-analysis aimed to investigate the prevalence of the mentioned complications following RM. Methods: Medline, Embase, and Scopus databases were searched using keywords related to compartment syndrome, DIC, and rhabdomyolysis with appropriate combination. Cohort and cross-sectional studies that conducted research on the prevalence of compartment syndrome and DIC in patients with RM were included in the present study. The desired data were extracted from the included studies and meta-analysis was conducted on them to calculate pooled prevalence of these complications. Results: Twenty articles were included in our systematic review. The rate of compartment syndrome reported in these studies ranged from 0 to 30.7%. Our meta-analysis revealed the pooled prevalence of 4% (95% confidence interval (CI): 2.20 to 7.40) for compartment syndrome in these studies. The pooled prevalence of this complication was 7.1% (95% CI: 2.90 to 16.00) among patients with severe RM and 4.4% (95% CI: 1.80 to 10.00) in traumatic RM. The rate of DIC reported in the included studies ranged from 0 to 40.47%. Our meta-analysis showed the pooled prevalence of 8.3% (95% CI: 03.90 to 16.50) for this complication among RM patients. Conclusion: We reported the rates of compartment syndrome and DIC in RM patients based on rhabdomyolysis etiologies through an epidemiologic systematic review and meta-analysis. The rate of compartment syndrome was slightly higher in patients with severe RM and its rate in patients with traumatic RM was close to the overall rate of compartment syndrome.

Abstract Purpose: To assess the adverse drug reactions (ADR) of tetracaine among patients referred to an eye emergency department in the southeast of Iran. Methods: In this case series study, we assessed 31 eyes of 24 patients who were referred due to adverse effects of ocular anesthetics during2017–2020. We collected the data, including age, sex, job, how the medicine was obtained, symptoms, examination results, and ADR. Results: Of 24 patients, 22 (91.7%) were male. The mean (standard deviation) age of the patients was 32.6 (1.9) years. Twenty-two patients obtained the medicines without a prescription and a general practitioner prescribed the medicine to two patients. In the first interview, the most common symptoms were: photophobia, reduced vision, ocular pain, and redness. The main signs of persistent epithelial defect, patchy or diffuse corneal stromal infiltration, ring infiltration, and Descemet's folds were noticed in the examinations. Finally, 51.6% (n =16) of the eyes had decreased vision, 45.2% (n =14) had corneal opacity, 16.1% (n = 5) had elevated intraocular pressure that needed long-term anti-glaucoma therapy, and 6.5% (n = 2) had corneal pannus. Corneal perforation and phthisis bulbi were the final results in one eye. Conclusion: ADR related to the use of ophthalmic topical anesthetics could cause sight-threatening severe morbidities. It seems that some general practitioners are not careful regarding the prescription of these kinds of medicine. Moreover, the over-the-counter availability of tetracaine eye drops should be managed.

This paper presents a novel approach to distinguishing driving styles with respect to their energy efficiency. A distinct property of our method is that it relies exclusively on the global positioning system (GPS) logs of drivers. This setting is highly relevant in practice as these data can easily be acquired. Relying on positional data alone means that all features derived from them will be correlated, so we strive to find a single quantity that allows us to perform the driving style analysis. To this end we consider a robust variation of the so-called "jerk" of a movement. We give a detailed analysis that shows how the feature relates to a useful model of energy consumption when driving cars. We show that our feature of choice outperforms other more commonly used jerk-based formulations for automated processing. Furthermore, we discuss the handling of noisy, inconsistent, and incomplete data, as this is a notorious problem when dealing with real-world GPS logs. Our solving strategy relies on an agglomerative hierarchical clustering combined with an L-term heuristic to determine the relevant number of clusters. It can easily be implemented and delivers a quick performance, even on very large, real-world datasets. We analyse the clustering procedure, making use of established quality criteria. Experiments show that our approach is robust against noise and able to discern different driving styles.

The purpose of this study was to investigate the effectiveness of computerized cognitive training on the performance of response inhibition and sustained attention of students with mathematical problems. The research method in terms of goal was practical and semi-experimental with a pretest-posttest design with a control group. The statistical population of the study was all students with mathematical disorders in Tehran who were studying in the academic year 2018-2019. The sample of this study included 24 elementary school students with mathematics problems who were randomly selected and divided into a control group (12 subjects) and an experimental group (12 subjects). Their intelligence and mathematical abilities were assessed using the Wechsler Intelligence Scale for Children-Revised (WISC-R) and the Iran Key Math Diagnostic Test. The experimental group participated in 25 sessions of 50 to 60 minutes duration in the intervention program. For the development of response inhibition and maintenance of attention, the Continuous Performance Test (CPT) and the Stroop test, a subscale of the CNS Vital Sign (CNSVS) battery, were used. Data were analyzed with SPSS22 software and using analysis of covariance tests. The results of ANCOVA indicated that there was a statistically significant difference between the experimental group and the control group in terms of the concussion error of the Stroop test (p

Abstract Secondary infections in hospitalized and ill patients with coronavirus disease 2019 (COVID-19) are common. One of these life-threatening infectious diseases is rhino-orbital mucormycosis, which made an outbreak recently. This outbreak was mainly caused by the administration of high-dose corticosteroids in patients with COVID-19, especially those with diabetes mellitus. The increased incidence of rhino-orbital mucormycosis in the COVID-19 era presents different challenges for healthcare providers including ophthalmologists who are directly involved in disease management. We summarized the main challenges and recommendations for ophthalmologists on the management of rhino-orbital mucormycosis.

Background: This study was conducted to evaluate the status of eye and intraocular pressure (IOP), two-six hours, one day, and one week after cataract surgery and implantation of the intraocular lens.Methods: In a longitudinal study, 159 patients with senile cataracts were evaluated. Phacoemulsification surgery and intraocular lens (IOL) implantation in the capsular bag was done. The examinations including visual acuity measurement, slit-lamp examination, and measurement of IOP were done preoperatively, and three times after the surgery.Results: The mean±standard deviation (range) age of the patients was 65.8 ± 10.5 (40-90) years. Preoperatively the IOP was 12.8 ± 3.5 mmHg, it increased to 20.8 ± 10.7, 2-6 hours after surgery (P < 0.0001), and then reached 13.7 ± 4.4 mmHg on the first postoperative day (P < 0.0001), then it decreased to 12.4 ± 2.9 mmHg one week after the surgery (P=0.02). The IOP was 28.6 ± 12.2 mmHg in eyes with epithelial edema which was significantly higher than those with stromal edema (17.3 ± 7.5 mmHg), and those without edema (16.5 ± 7.1 mmHg) 2-6 hours after surgery.Conclusion: Since the IOP spike can damage the structure and function of the eye and cause pain, discomfort, and corneal edema that in turn prolongs recovery of vision, especially in those previously damaged, early postoperative examination on the same day after cataract surgery is strongly advised. IOP spikes can be managed safely by aqueous paracentesis without oral, parenteral, or topical drugs. Elevated IOP is more prevalent in eyes with postoperative epithelial corneal edema and in individuals whose cornea is totally edematous.

n recent decades, the hijab has been one of the most important rulings in the field of women, which has been considered by currents called religious modernists and Islamic feminism And they have tried to recite the verses of hijab with a customary attitude based on respect for women's rights. One of these people is Fatemeh Mernissi, who in one of her works called "The veil and The Male elites " examines verse 53 of Surah Al-Ahzab and believes that the concept of hijab in the verse in question means a barrier between two men. This research uses analytical-descriptive method and using valid interpretive and religious sources to study and analyze the views and methods of this researcher on the issue of hijab. According to studies, Mernissi's view is due to the limitation and lack of resources and selective use of them, confusion between veiling and covering women, deviation from the appearance of verse 53 of Surah Al-Ahzab and the context of adjacent verses, lack of attention to semantic relativity and lack Paying attention to the verses that explicitly legislate the ruling on hijab for Muslim women is flawed and not based on a solid basis

Today, Women comprise about half of the international migration flows. This weighting of men’s and women’s migration has been one of the most important recent migration developments that has attracted the attention of immigration researchers since the 1970s. The present study has investigated the trends, types, and characteristics of international migration of women in accordance with the latest statics and reports of international organizations. The results showed that this trend can be studied in the context of globalization and gender. In particular, globalization has greatly increased the demand for cheap and obedient female labor. Women may migrate freely or under duress. Also for women, the motivation for immigration can be freedom from discrimination and gender norms. Creating equal opportunities for women in international mobility and obtaining appropriate economic and social opportunities without gender stereotypes can be seen as an example of development. Although women in this process may also have to face challenges. On the one hand, the gender division of labor in the global economy, and on the other, gender stereotypes, put the immigrant interests of women in greater risk than men. Illegal female immigrants as well as unskilled immigrant women are more likely to be affected.

Abstract Keratoconus is the most common form of primary corneal thinning. Different methods have been suggested to deal with the condition, including glasses, contact lenses, and surgical interventions, like penetrating keratoplasty (PKP) and deep anterior lamellar keratoplasty (DALK), well-known methods of the latter. This study was conducted to compare the outcomes and side effects of the two mentioned keratoplasty techniques. First, we systematically reviewed all original articles studies on PubMed, Scopus, Web of Science, and Embase. Then, the extracted data were pooled and meta-analyzed on each of the intended outcomes. A total of 30 studies were included in which PKP was more commonly performed compared to DALK. We found that adverse outcomes consisting of cataracts, graft rejection, graft failure, High-IOP, and corneal infection, were all more common findings in the PKP groups compared to the DALK groups. However, only for the high-IOP, cataracts, and graft rejection, the analysis of the extracted results demonstrated statistical significance. Overall, the DALK groups demonstrated significantly better results when considering the improvement levels by measuring the Endothelial Cell Count (ECC) and Spherical Equivalent (SE). In addition, though statistically insignificant, the Central Corneal Thickness(CCT), Best Corrected Visual Acuity(BCVA), Topographic Cylinder(TC), Refractive Cylinder values were greater in the PKP groups. Based on our study and with its limitations in mind, we can conclude that DALK can be a relatively safer and more effective procedure. Though, a larger number of high-standard randomized clinical trials still need to be conveyed for more definite conclusions.

BackgroundApproximately 110 million Farsi speakers worldwide have access to a growing mobile app market. Despite restrictions and international sanctions, Iran’s internal mobile health app market is growing, especially for Android-based apps. However, there is a need for guidelines for developing health apps that meet international quality standards. There are also no tools in Farsi that assess health app quality. Developers and researchers who operate in Farsi could benefit from such quality assessment tools to improve their outputs. ObjectiveThis study aims to translate and culturally adapt the Mobile Application Rating Scale in Farsi (MARS-Fa). This study also evaluates the validity and reliability of the newly developed MARS-Fa tool. MethodsWe used a well-established method to translate and back translate the MARS-Fa tool with a group of Iranian and international experts in Health Information Technology and Psychology. The final translated version of the tool was tested on a sample of 92 apps addressing smartphone addiction. Two trained reviewers completed an independent assessment of each app in Farsi and English. We reported reliability and construct validity estimates for the objective scales (engagement, functionality, aesthetics, and information quality). Reliability was based on the evaluation of intraclass correlation coefficients, Cronbach α and Spearman-Brown split-half reliability indicators (for internal consistency), as well as Pearson correlations for test-retest reliability. Construct validity included convergent and discriminant validity (through item-total correlations within the objective scales) and concurrent validity using Pearson correlations between the objective and subjective scores. ResultsAfter completing the translation and cultural adaptation, the MARS-Fa tool was used to assess the selected apps for smartphone addiction. The MARS-Fa total scale showed good interrater reliability (intraclass correlation coefficient=0.83, 95% CI 0.74-0.89) and good internal consistency (Cronbach α=.84); Spearman-Brown split-half reliability for both raters was 0.79 to 0.93. The instrument showed excellent test-retest reliability (r=0.94). The correlations among the MARS-Fa subdomains and the total score were all significant and above r=0.40, suggesting good convergent and discriminant validity. The MARS-Fa was positively and significantly correlated with subjective quality (r=0.90, P

Abstract Background Ankylosing spondylitis (AS) is an autoimmune rheumatic disease. Few candidate gene associations have been reported for AS and the current understanding of its pathogenesis remains still poor. Thus, the exact mechanism of AS is needed to urgently be disclosed. The purpose of this study was to identify candidate genes involving in AS disease. Methods and results GSE25101 publicly available microarray and GSE117769 RNA-seq datasets of AS patients were obtained for bioinformatics analyses. Gene set enrichment analysis showed that in the microarray dataset, the ribosome pathway was significantly up-regulated in AS compared with controls. Furthermore, some ribosomal components demonstrated overexpression in patients in the RNA-seq dataset. To confirm the findings, 20 AS patients and 20 matching controls were selected from the Rheumatology Research Center clinic, Shariati Hospital. PBMCs were separated from whole blood and RNA contents were extracted. Following the results of datasets analysis, the expression level of rRNA5.8S pseudogene, rRNA18S pseudogene, RPL23, RPL7, and RPL17 genes were measured through real-time PCR. Our findings showed dysregulation of rRNA5.8S and rRNA18S pseudogenes, and also the RPL17 gene in patients. Conclusion Considering that genes involved in ribosome biogenesis contributed to some AS-associated biological processes as well as diseases that have comorbidities with AS, our results might advance our understanding of the pathological mechanisms of ankylosing spondylitis.

Background and Objectives: low utility of health care services is one of the main determinants of not achieving desired health indicators in urban areas. This study aimed to investigate the barriers and facilitators of receiving health services from health centers in Kerman city, Iran. Methods: This study was a qualitative study with a content analysis approach conducted in 2020. After selecting health centers with the experience of desirable or low utility services, purposive sampling continued until information saturation. A total of 78 staff members, recipients, and non-recipients of services citizens were interviewed semi-structured and face-to-face at health centers. All interviews were recorded and coded manually and then reviewed and analyzed using directional content analysis. Results: The essential services for children and mothers, free services, and service providers' behavior were mentioned as facilitators of referral. Distance and physical factors, knowledge of different types of services, preference of private centers, time access, view of people on regular visits to centers, addresses and telephone numbers registered in the system, responsiveness to health needs, fear of disease disclosure, lack of human resources in the centers, and service providers' behavior, were among the barriers of visiting the centers. Conclusion: According to the results of this study, an accurate understanding of the under-coverage people's views and perceptions can help national and local planners and policymakers design the necessary strategies to increase the use of health services in urban health centers.

BackgroundAs the era of big data analytics unfolds, machine learning (ML) might be a promising tool for predicting clinical outcomes. This study aimed to evaluate the predictive ability of ML models for estimating mortality after coronary artery bypass grafting (CABG).Materials and methodsVarious baseline and follow-up features were obtained from the CABG data registry, established in 2005 at Tehran Heart Center. After selecting key variables using the random forest method, prediction models were developed using: Logistic Regression (LR), Support Vector Machine (SVM), Naïve Bayes (NB), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), and Random Forest (RF) algorithms. Area Under the Curve (AUC) and other indices were used to assess the performance.ResultsA total of 16,850 patients with isolated CABG (mean age: 67.34 ± 9.67 years) were included. Among them, 16,620 had one-year follow-up, from which 468 died. Eleven features were chosen to train the models. Total ventilation hours and left ventricular ejection fraction were by far the most predictive factors of mortality. All the models had AUC > 0.7 (acceptable performance) for 1-year mortality. Nonetheless, LR (AUC = 0.811) and XGBoost (AUC = 0.792) outperformed NB (AUC = 0.783), RF (AUC = 0.783), SVM (AUC = 0.738), and KNN (AUC = 0.715). The trend was similar for two-to-five-year mortality, with LR demonstrating the highest predictive ability.ConclusionVarious ML models showed acceptable performance for estimating CABG mortality, with LR illustrating the highest prediction performance. These models can help clinicians make decisions according to the risk of mortality in patients undergoing CABG.

Introduction: Health information systems play an important role in improving the quality of patient care and patient safety. to ensure their effectiveness and efficiency, they need to be evaluated. Although HIS evaluation has been investigated in many studies, there is no consensus on which aspects of HIS to evaluate. The aim of this study is to identify the indicators for the evaluation of health information systems and to provide an overview of the criteria devised and studies conducted. Methods: An umbrella review was performed exploring databases PubMed, Science direct, Web of Science, Science, and IEEE while following the PRISMA protocol. Articles were reviewed by two authors independently using the covidence tool to check the inclusion criteria and to extract the data items. Risk of bias was assessed using ROBIS and AMSTAR. Result: All included studies showed a high risk of bias according to ROBIS criteria. The extracted evaluation criteria were classified into 13 categories. Most of the studies believe that a more reliable and standardized tool is needed for the evaluation of health information systems. Two studies mentioned that surveys and questionnaires were the most commonly used method for evaluation of the systems. Summative evaluation was the most used method in two studies and the least used method in another one study. Conclusion: All the included studies had high risk of bias. Accordingly, further research and evidence is needed in this field. Most of the studies highlighted the need for more reliable and standardized tools for evaluation of health information systems.

Abstract Background StrongestPath is a Cytoscape 3 application that enables the analysis of interactions between two proteins or groups of proteins in a collection of protein–protein interaction (PPI) network or signaling network databases. When there are different levels of confidence over the interactions, the application is able to process them and identify the cascade of interactions with the highest total confidence score. Given a set of proteins, StrongestPath can extract a set of possible interactions between the input proteins, and expand the network by adding new proteins that have the most interactions with highest total confidence to the current network of proteins. The application can also identify any activating or inhibitory regulatory paths between two distinct sets of transcription factors and target genes. This application can be used on the built-in human and mouse PPI or signaling databases, or any user-provided database for some organism. Results Our results on 12 signaling pathways from the NetPath database demonstrate that the application can be used for indicating proteins which may play significant roles in a pathway by finding the strongest path(s) in the PPI or signaling network. Conclusion Easy access to multiple public large databases, generating output in a short time, addressing some key challenges in one platform, and providing a user-friendly graphical interface make StrongestPath an extremely useful application.

Several studies have reported the characteristics of Coronavirus disease 2019 (COVID-19), yet there is a gap in our understanding of the ocular manifestations of COVID-19. In this systematic review and meta-analysis, we investigated the prevalence of ocular manifestations in COVID-19 patients. We searched Pubmed, Embase, Scopus, Web of Science, and medRxiv from December 1, 2019 to August 11, 2020. Two independent reviewers screened the articles, abstracted the data, and assessed the quality of included studies in duplicate. Thirty-eight studies were eligible after screening of 895 unique articles, with a total of 8,219 COVID-19 patients (55.3% female; n = 3,486 out of 6,308 patients). Using data extracted from cross-sectional studies, we performed random-effects meta-analyses to estimate the pooled prevalence of ocular symptoms along with 95% confidence interval (CI). The prevalence of ocular manifestations was estimated to be 11.03% (95% CI: 5.71–17.72). In the studies that reported the details of observed ocular symptoms, the most common ocular manifestations were dry eye or foreign body sensation (n = 138, 16%), redness (n = 114, 13.3%), tearing (n = 111, 12.8%), itching (n = 109, 12.6%), eye pain (n = 83, 9.6%) and discharge (n = 76, 8.8%). Moreover, conjunctivitis had the highest rate among reported ocular diseases in COVID-19 patients (79 out of 89, 88.8%). The results suggest that approximately one out of ten COVID-19 patients show at least one ocular symptom. Attention to ocular manifestations, especially conjunctivitis, can increase the sensitivity of COVID-19 detection among patients.

BackgroundMicroRNAs (miRNAs) are frequently deregulated in various types of cancer. While antisense oligonucleotides are used to block oncomiRs, delivery of tumour-suppressive miRNAs holds great potential as a potent anti-cancer strategy. Here, we aim to determine, and functionally analyse, miRNAs that are lowly expressed in various types of tumour but abundantly expressed in multiple normal tissues.MethodsThe miRNA sequencing data of 14 cancer types were downloaded from the TCGA dataset. Significant differences in miRNA expression between tumor and normal samples were calculated using limma package (R programming). An adjusted p value < 0.05 was used to compare normal versus tumor miRNA expression profiles. The predicted gene targets were obtained using TargetScan, miRanda, and miRDB and then subjected to gene ontology analysis using Enrichr. Only GO terms with an adjusted p < 0.05 were considered statistically significant. All data from wet-lab experiments (cell viability assays and flow cytometry) were expressed as means ± SEM, and their differences were analyzed using GraphPad Prism software (Student's t test, p < 0.05).ResultsBy compiling all publicly available miRNA profiling data from The Cancer Genome Atlas (TCGA) Pan-Cancer Project, we reveal a small set of tumour-suppressing miRNAs (which we designate as 'normomiRs') that are highly expressed in 14 types of normal tissues but poorly expressed in corresponding tumour tissues. Interestingly, muscle-enriched miRNAs (e.g. miR-133a/b and miR-206) and miRNAs from DLK1-DIO3 locus (e.g. miR-381 and miR-411) constitute a large fraction of the normomiRs. Moreover, we define that the CCCGU motif is absent in the oncomiRs' seed sequences but present in a fraction of tumour-suppressive miRNAs. Finally, the gain of function of candidate normomiRs across several cancer cell types indicates that miR-206 and miR-381 exert the most potent inhibition on multiple cancer types in vitro.ConclusionOur results reveal a pan-cancer set of tumour-suppressing miRNAs and highlight the potential of miRNA-replacement therapies for targeting multiple types of tumour.

Purpose Whole genome sequencing of SARS-CoV2 is important to find useful information about the viral lineages, variants of interests and variants of concern. As there are not enough data about the circulating SARS-CoV2 variants in Iran, we sequenced 54 SARS-CoV2 genomes during the 5 waves of pandemic in Iran. Methods After viral RNA extraction from clinical samples collected during the COVID-19 pandemic, next generation sequencing was performed using the Nextseq platform. The sequencing data were analyzed and compared with reference sequences. Results During the 1st wave, V and L clades were detected. The second wave was recognized by G, GH and GR clades. Circulating clades during the 3rd wave were GH and GR. In the fourth wave GRY (alpha variant), GK (delta variant) and one GH clade (beta variant) were detected. All viruses in the fifth wave were in clade GK (delta variant). There were different mutations in all parts of the genomes but Spike-D614G, NSP12-P323L, N-R203K and N-G204R were the most frequent mutants in these studied viruses. Conclusions These findings display the significance of SARS-CoV2 monitoring to help on time detection of possible variants for pandemic control and vaccination plans.

Intractable vomiting and elevated liver enzymes during pregnancy seem to be associated to the obstetric etiologies; however, other causes such as acute surgical emergencies should be considered. The patient was a 26-year-old woman at 18 weeks of gestation with intractable vomiting, intolerability of oral intake, weight loss, and absence of abdominal pain. Her physical examinations and laboratory tests had no remarkable findings except elevated liver function test (LFT) and hypokalemia. Considering the lab data and normal abdominopelvic ultrasound, magnetic resonance imaging was performed which revealed dilation of the D1-3 and collapse the D4 sections of duodenum. She underwent exploratory laparotomy which confirmed duodenal obstruction caused by Ladd’s band. After the Ladd’s operation, the patient started oral intake of nutritious, and her LFT decreased to normal ranges. After the last follow-up, she has had gained 18 kg and gave birth at 36 weeks of gestation due to the premature rapture of membranes and delivered a 2 kg small for gestational age otherwise healthy infant. The experience gained from this case was to consider all possibilities (such as small bowel obstruction) and evaluate them in a pregnant patient to consider other causes of nausea, vomiting, and abnormal LFTs in a pregnant patient.

The aim of this study was to investigate the profile analysis of memory and attention functioning in children with Attention Deficit/Hyperactivity Disorder, Specific Learning Disorder and Comorbid Condition. The descriptive and causal-comparative method was used for this research. Thirty students with ADHD, 30 students with an SLD, 30 children with the comorbid condition (ADHD + SLD) were selected by the convenience sampling method after diagnosis and evaluation with regard to the working memory and attention functioning in them. The MANOVA and post hoc Cheffe test were used to analyze the collected data. Furthermore, the profile functioning of the four groups in the working memory and attention was presented in a graph. The results of the study showed significant differences between normal children and children with ADHD, children with SLD, and children with the comorbid condition in terms of working memory and attention (p

Abstract Background A comprehensive intuition of the systemic lupus erythematosus (SLE), as a complex and multifactorial disease, is a biological challenge. Dealing with this challenge needs employing sophisticated bioinformatics algorithms to discover the unknown aspects. This study aimed to underscore key molecular characteristics of SLE pathogenesis, which may serve as effective targets for therapeutic intervention. Methods In the present study, the human peripheral blood mononuclear cell (PBMC) microarray datasets (n = 6), generated by three platforms, which included SLE patients (n = 220) and healthy control samples (n = 135) were collected. Across each platform, we integrated the datasets by cross-platform normalization (CPN). Subsequently, through BNrich method, the structures of Bayesian networks (BNs) were extracted from KEGG-indexed SLE, TCR, and BCR signaling pathways; the values of the node (gene) and edge (intergenic relationships) parameters were estimated within each integrated datasets. Parameters with the FDR

Abstract In irrigation and drainage structures, side weir is widely used for flow diversion from main to branch channels. Side weir is also used as a measuring device for discharge measurements, so discharge coefficient was mainly studied in many previous studies. Skew side weir was not taking a good highlight in previous studies and literature, so the present work discharge coefficient calculation for the skew side weir was adopted and studied. Multiple Linear Regression (MLR) and Gene Expression Programming (GEP) tools were used in the present study and compared with observed values of C d. The mean absolute error for C d observed and calculated in MLR and GEP was not exceeded 5%. The C d values for skew side weir ranged from (0.65) to (0.85), while its values for straight vertical side from previous literature weir ranged from (0.45) to (0.65); this mean skew side weir can be used for increase in discharge diversion to the branch channel at the same water levels by 27%. The Akaike information criteria (AIC) with (AICs), root-mean-square error (RMSE), mean absolute relative error (MARE) and scatter index (SI) are used in this study for measuring the GEP model performance. From results, the GEP model has AIC = − 216.51, AICs = − 918.51, RMSE = 0.004653, MARE = 0.005234, R 2 = 0.994 and SI = 0.006231 performed the best. According to previous results, the new equation presented through GEP can be adopted for discharge coefficient calculation in skew side weir.

Background Stigmatizing attitudes among healthcare providers are an important barrier to accessing services among people living with HIV (PLHIV). This cross-sectional study aimed to assess the status and correlates of HIV-related stigma among healthcare providers in Kerman, Iran. Methods Using a validated and pilot-tested stigma scale questionnaire, we measured HIV-related stigma among 400 healthcare providers recruited from three teaching hospitals (n = 363), private sectors (n = 28), and the only voluntary counseling and testing (VCT) center (n = 9) in Kerman city. Data were gathered using self-administered questionnaires at participants’ workplace during Fall 2016. To examine the correlates of stigmatizing attitudes, we constructed bivariable and multivariable linear regression models. Results The mean ± standard deviation (SD) of stigma score was 25.95 ± 7.20 out of the possible 50, with higher scores reflecting more stigmatizing attitudes. Paramedics, nurses’ aides, and housekeeping staff had the highest, and VCT personnel had the lowest average stigma scores, respectively. Multivariable regression analyses showed that prior experience of working with PLHIV (β = -2.48; P = .03), exposure to HIV-related educational courses (β = -2.03; P = .02), and P < .001) were associated with lower stigma scores. Conclusion Our findings highlight the need for health managers to provide training opportunities for healthcare providers, including programs that focus on improving HIV-related knowledge for healthcare providers. Enforcing policies that aim to reduce HIV-related stigma and discrimination among healthcare providers in Iran are urgently needed.

There is diversity of opinions about suhufan motahara (صحفا مطهره) impeccable scriptures in the second verse of surah Bayena. in this research done by analytic-dscriptive method after investigating different opinions of commentattors about divine intention, we are facing with nine interpretations that can classified in three main approaches. The first, some interpretations of verse without exact interpretation. Second, the interpreters those who have an esoteric approach, interpreting the suhuf as whol of Quran, sections of it or past imported heavenly books. Third group has interrior interpretive approch, interpreting suhuf as Guarded tablet, heat of prophet, heavenly souls or family of prophet. it seems that some of this nine opinios can be unified with others. First example literal interpretations can be observed as a preface to the other interpretations. and different interior interpretations can be merged with each other. Totally, we can relize that interpretations are in harmony with contexts of verses avd traditions are in the this manner.

Abstract Background Systemic sclerosis (SSc), a multi-organ disorder, is characterized by vascular abnormalities, dysregulation of the immune system, and fibrosis. The mechanisms underlying tissue pathology in SSc have not been entirely understood. This study intended to investigate the common and tissue-specific pathways involved in different tissues of SSc patients. Methods An integrative gene expression analysis of ten independent microarray datasets of three tissues was conducted to identify differentially expressed genes (DEGs). DEGs were mapped to the search tool for retrieval of interacting genes (STRING) to acquire protein–protein interaction (PPI) networks. Then, functional clusters in PPI networks were determined. Enrichr, a gene list enrichment analysis tool, was utilized for the functional enrichment of clusters. Results A total of 12, 2, and 4 functional clusters from 619, 52, and 119 DEGs were determined in the lung, peripheral blood mononuclear cell (PBMC), and skin tissues, respectively. Analysis revealed that the tumor necrosis factor (TNF) signaling pathway was enriched significantly in the three investigated tissues as a common pathway. In addition, clusters associated with inflammation and immunity were common in the three investigated tissues. However, clusters related to the fibrosis process were common in lung and skin tissues. Conclusions Analysis indicated that there were common pathological clusters that contributed to the pathogenesis of SSc in different tissues. Moreover, it seems that the common pathways in distinct tissues stem from a diverse set of genes.

Introduction: We investigated correlation between the retinal nerve fiber layer (RNFL) thickness and the severity of Parkinson's disease (PD). Methods: In this study, the RNFL thickness of 23 patients with Parkinson’s disease (PD) was compared to normal controls (NCs). PD severity was assessed by the MDS-UPDRS (movement disorder society Unified Parkinson Disease Rating Scale) rating scale thoroughly in all parts. RNFL is measured by Ocular Coherent tomography (OCT). Scatter plots were used to evaluate the relationship between disease severity and retinal thickness. Results: The findings of the study demonstrated that patients with PD had a significantly thinner average RNFL thickness compared with controls (P=0.035). Superior and inferior retinal quadrants were thinnest in PD compared with the healthy group (P=0.021 and P=0.045, respectively). The MDS-UPDRS had a significant reverse correlation with RNFL (r = -0.518, P=0.011) and its temporal quadrant (r = -0.594, P=0.003). Among all parts of MDS-UPDRS scale, Part III had the strongest correlation with OCT findings. Conclusion: A correlation was found between the severity of the disease and the thinning of RNFL. MDS-UPDRS Part III subscale had the strongest correlation with RNFL thickness. Temporal quadrant RNFL became thinner as Parkinson’s disease severity increased.

Abstract Background De novo drug discovery is a time-consuming and expensive process. Nowadays, drug repositioning is utilized as a common strategy to discover a new drug indication for existing drugs. This strategy is mostly used in cases with a limited number of candidate pairs of drugs and diseases. In other words, they are not scalable to a large number of drugs and diseases. Most of the in-silico methods mainly focus on linear approaches while non-linear models are still scarce for new indication predictions. Therefore, applying non-linear computational approaches can offer an opportunity to predict possible drug repositioning candidates. Results In this study, we present a non-linear method for drug repositioning. We extract four drug features and two disease features to find the semantic relations between drugs and diseases. We utilize deep learning to extract an efficient representation for each feature. These representations reduce the dimension and heterogeneity of biological data. Then, we assess the performance of different combinations of drug features to introduce a pipeline for drug repositioning. In the available database, there are different numbers of known drug-disease associations corresponding to each combination of drug features. Our assessment shows that as the numbers of drug features increase, the numbers of available drugs decrease. Thus, the proposed method with large numbers of drug features is as accurate as small numbers. Conclusion Our pipeline predicts new indications for existing drugs systematically, in a more cost-effective way and shorter timeline. We assess the pipeline to discover the potential drug-disease associations based on cross-validation experiments and some clinical trial studies.

Objective: Paraquat is a herbicide with potent toxicity in humans and animals. This study aimed to evaluate the protective effects of Origanum vulgare (O. vulgare) leaf extract on the acute nephrotoxicity and renal oxidative stress caused by paraquat. Materials and Methods: We randomly assigned forty male rats into five groups (G1-G5). The G1 was used as control; G2 only received paraquat (25 mg/kg body weight (bw)/day, po); and G3, G4 and G5 received 25 mg/kg b.w/day oral doses of paraquat and O. vulgare hydroethanolic leaf extract (200, 400, 800 mg/kg bw/day, po, respectively). After 2 weeks, superoxide dismutase (SOD), renal catalase (CAT), vitamin C levels, histopathological changes, and tumor necrosis factor-α (TNF-α) gene expression as well as serum levels of urea, creatinine (Cr), and protein carbonyl (PC) were determined. Results: In G2, oral administration of paraquat significantly increased (pTNF-α gene expression relative to those of the control group. Renal catalase, superoxide dismutase, and vitamin C levels were decreased significantly (pO. vulgare leaf extract not only increased the renal vitamin C, CAT, and SOD but also decreased the renal TNF-α gene expression, malondialdehyde (MDA), serum urea and creatinine in paraquat-induced nephrotoxicity in rats. Conclusion: Our results show that O. vulgareleaf extract has protective effects against nephrotoxicity induced by paraquat in rats. It seems that the nephroprotective effects of O. vulgare extract may be related to its antioxidant and anti-inflammatory effects.

Ankylosing spondylitis (AS) is a systemic inflammatory disorder of joints and entheses. Recent studies have reported an increased prevalence of dementia in AS patients. However, data for exploring the association between dementia and AS remain uncertain. In this study, enriched pathways and differentially expressed genes (DEGs) were identified in whole blood transcription data of AS patients obtained from the gene expression omnibus (GEO) database; using gene set enrichment analysis (GSEA) and differential expression analysis. Four pathways, including oxidative phosphorylation, Alzheimer’s, Parkinson’s, and Huntington’s diseases were significantly enriched in AS patients compared to the controls. We identified 22 common genes among the pathways that showed an increasing trend in AS compared to the controls. Five of them including COX7B, NDUFB3, ATP5PF, UQCRB, and NDUFS4 were the most significant genes which were selected for gene expression analysis; using real-time PCR on RNA contents of peripheral blood mononuclear cells (PBMCs) of AS patients and controls (20 samples from each group). The gene expression analysis indicated considerable overexpression of COX7B (p

Objective: microRNAs (miRNAs) play important role in progression of tumorigenesis. They can target self-renewal and epithelial-mesenchymal transition (EMT) abilities in tumor cells, especially in cancer stem cells (CSCs). The objective of this study was to implement data mining to identify important miRNAs for targeting both self-renewal and EMT. We also aimed to evaluate these factors in mammospheres as model of breast cancer stem cells (BCSCs) and metastatic tumor tissues. Materials and Methods: In this experimental study, mammospheres were derived from MCF-7 cells and characterized for the CSCs properties. Then expression pattern of the selected miRNAs in spheroids were evaluated, using the breast tumor cells obtained from seven patients. Correlation of miRNAs with self-renewal and EMT candidate genes were assessed in mammospheres and metastatic tumors. Results: The results showed that mammospheres represented more colonogenic and spheroid formation potential than MCF-7 cells (P

Abstract Background Pluripotency is proposed to exist in two different stages: Naive and Primed. Conventional human pluripotent cells are essentially in the primed stage. In recent years, several protocols have claimed to generate naive human embryonic stem cells (hESCs). To the best of our knowledge, none of these protocols is currently recognized as the gold standard method. Furthermore, the consistency of the resulting cells from these diverse protocols at the molecular level is yet to be shown. Additionally, little is known about the principles that govern the metabolic differences between naive and primed pluripotency. In this work, using a computational approach, we tried to shed light on these basic issues. Results We showed that, after batch effect removal, the transcriptome data of eight different protocols which supposedly produce naive hESCs are clustered consistently when compared to the primed ones. Next, by integrating transcriptomes of all hESCs obtained by these protocols, we reconstructed p-hESCNet and n-hESCNet, the first metabolic network models representing hESCs. By exploiting reporter metabolite analysis we showed that the status of NAD$$^{+}$$ + and the metabolites involved in the TCA cycle are significantly altered between naive and primed hESCs. Furthermore, using flux variability analysis (FVA), the models showed that the kynurenine-mediated metabolism of tryptophan is remarkably downregulated in naive human pluripotent cells. Conclusion The aim of the present paper is twofold. Firstly, our findings confirm the applicability of all these protocols for generating naive hESCs, due to their consistency at the transcriptome level. Secondly, we showed that in silico metabolic models of hESCs can be used to simulate the metabolic states of naive and primed pluripotency. Our models confirmed the OXPHOS activation in naive cells and showed that oxidation-reduction potential vary between naive and primed cells. Tryptophan metabolism is also outlined as a key pathway in primed pluripotency and the models suggest that decrements in the activity of this pathway might be an appropriate marker for naive pluripotency.

For downloading the full-text of this article please click here. Background and Objective: Adjustment to university is an important factor in different dimensions of students’ life such as mental- physical health and social adjustment in the fields outside the university. The aim of this study was to determine mediating role of distress tolerance in the relationship of spiritual intelligence and emotional maturity with adjustment to university. Method: In this correlation study, based on Krejsi and Murgan table, 273 students of Shahid Chamran University in Ahvaz city were selected via multistage cluster sampling method during the fall semester of the academic year of 2016-2017. The participants completed the items of Emotional Maturity Scale, Distress Tolerence Scale, Spiritual Intelligence Inventory and Adjustment to College Scale. The data were then analyzed using Pearson correlation coefficient, structural equation modeling. All ethical issues were observed in this study and the researchers declared no conflict of interests. Results: The findings showed that emotional maturity, spiritual intelligence, and distress tolerance had positive significant correlation with adjustment to college. There was also a positive significant correlation between emotional maturity as well as spiritual intelligence and distress tolerance. The proposed model for relationship between these variables has acceptable fit with a correction and removal of direct path of spiritual intelligence with adjustment to college. Direct path of emotional maturity to adjustment to college was significant. The analysis based on Bootstrapping indicated that all indirect paths were significant. Conclusion: It is proposed that to raise adjustment to university, educational programs for emotional maturity and spiritual intelligence with an emphasis on enhancing distress tolerance should be developed. For downloading the full-text of this article please click here.

Suffering in life is, in itself, a painful experience. However, what makes suffering in life cause extreme crises is its meaninglessness. Thus, a meaningful interpretation of suffering is a prerequisite for the durability of life and the meaning of it. The sufferings of a Muslim are given meaning through the Quran, Sunnah and their teachings. Through a descriptive-analytical approach aims to examine suffering and its meaning in the Quran and traditions. In this research, we have tried to find out what the approach of the Quran and traditions is in reducing human suffering. After reviewing the verses of the Quran and Islamic traditions, we reach the conclusion that the Quran and traditions, by providing particular interpretations and teachings of suffering, have the immense ability of linking the difficult and unfathomable predicament of the meaning of the immense sufferings of humans to the agency of faith in a sacred, spiritual, and intelligent system and make these sufferings meaningful despite their painful appearance.

Introduction: Paraquat is a quaternary nitrogen herbicide which induces kidney toxicity due to producing oxidative stress. We have investigated the potential protective effects of silymarin on paraquat-induced renal toxicity. Methods: Twenty-four male rats were divided into three groups, group 1, control group; group 2, rats that received paraquat only (25 mg/kg b.w./day, po); animals in group 3, was treated with paraquat (25 mg/kg b.w./day, po) and silymarin (50 mg/kg b.w./day, po). Then, the serum and tissue parameters of the oxidative stress and renal histopathological changes were examined. Results: In group 2 which received paraquat only, a remarkable increase (P

Objective The extracellular matrix (ECM) of the cumulus oocyte complex (COC) is composed of several molecules that have different roles during follicle development. This study aims to explore gene expression profiles for ECM and cell adhesion molecules in the cumulus cells of polycystic ovary syndrome (PCOS) patients based on their insulin sensitivity following controlled ovarian stimulation (COS). Materials And Methods In this prospective case-control study enrolled 23 women less than 36 years of age who participated in an intracytoplasmic sperm injection (ICSI) program. Patients were subdivided into 3 groups: control (n=8, fertile women with male infertility history), insulin resistant (IR) PCOS (n=7), and insulin sensitive (IS) PCOS (n=8). We compared 84 ECM component and adhesion molecule gene expressions by quantitative real-time polymerase chain reaction array (qPCR-array) among the groups. Results We noted that 21 of the 84 studied genes differentially expressed among the groups, from which 18 of these genes downregulated. Overall, comparison of PCOS cases with controls showed downregulation of extracellular matrix protein 1 (ECM1); catenin (cadherin-associated protein), alpha 1 (CTNNA1); integrin, alpha 5 (ITGA5); laminin, alpha 3 (LAMA3); laminin, beta 1 (LAMB1); fibronectin 1 (FN1); and integrin, alpha 7 (ITGA7). In the IS group, there was upregulation of ADAM metallopeptidase with thrombospondin type 1 motif, 8 (ADAMTS8) and neural cell adhesion molecule 1 (NCAM1) compared with the controls (P

BackgroundOne of the most widely used evaluation methods in miRNA experiments is qRT-PCR. However, selecting suitable internal controls (IC) is crucial for qRT-PCR experiments. Currently, there is no consensus on the ICs for miRNA qRT-PCR experiments in breast cancer. To this end, we tried to identify the most stable (the least expression alteration) and promising miRNAs in normal and tumor breast tissues by employing TCGA miRNA-Seq data and then experimentally validated them on fresh clinical samples.MethodsA multi-component scoring system was used which takes into account multiple expression stability criteria as well as correlation with clinical characteristics. Furthermore, we extended the scoring system for more than two biological sub-groups. TCGA BRCA samples were analyzed based on two grouping criteria: Tumor & Normal samples and Tumor subtypes. The top 10 most stable miRNAs were further investigated by differential expression and survival analysis. Then, we examined the expression level of the top scored miRNA (hsa-miR-361-5p) along with two commonly used ICs hsa-miR-16-5p and U48 on 34 pairs of Primary breast tumor and their adjacent normal tissues using qRT-PCR.ResultsAccording to our multi-component scoring system, hsa-miR-361-5p had the highest stability score in both grouping criteria and hsa-miR-16-5p showed significantly lower scores. Based on our qRT-PCR assay, while U48 was the most abundant IC, hsa-miR-361-5p had lower standard deviation and also was the only IC capable of detecting a significant up-regulation of hsa-miR-21-5p in breast tumor tissue.ConclusionsmiRNA-Seq data is a great source to discover stable ICs. Our results demonstrated that hsa-miR-361-5p is a highly stable miRNA in tumor and non-tumor breast tissue and we recommend it as a suitable reference gene for miRNA expression studies in breast cancer. Additionally, although hsa-miR-16-5p is a commonly used IC, it's not a suitable one for breast cancer studies.

Background and Objectives: Nowadays, adjustment to college in nursing and midwifery students requires more attention due to exposure to psychological and environmental stressors. The aim of the present study was to determine the role of emotional maturity, ego-resiliency, and spiritual intelligence in the prediction of adjustment to college with control of cognitive flexibility in nursing and midwifery students. Methods: In a correlational design, using stage sampling method, 273 students were selected from nursing and midwifery students of Ahvaz Jundishapur University, according to the Krejcie and Morgan table, in the academic year of 2017-2018. Information were collected using Emotional Maturity Scale, Ego-Resiliency Scale, Spiritual Intelligence Inventory, Adjustment to College Scale, and Cognitive Flexibility Inventory. Analysis of the data was performed using Pearson correlation coefficient and hierarchical regression analysis. Results: In this study, based on the results of Pearson correlation coefficient, there was significant positive correlations between all the predictive variables and the criterion variable. Moreover, there was a positive and significant correlation between cognitive flexibility and criterion variable. Hierarchical regression analysis showed that emotional maturity, ego-resiliency, and spiritual intelligence with control of cognitive flexibility could explain and predict 26% of variance of adjustment to college scores. Furthermore, in the analysis of hierarchical regression, emotional maturity and spiritual intelligence had a significant role in the prediction of adjustment to university. Conclusions: Considering the important role of emotional maturity, spiritual intelligence (beyond cognitive flexibility) is essential in the prediction of adaptation of nursing and midwifery students to university, targeting these variables in order to increase students’ compatibility and can improve the performance of students in personal-social areas, psychological well-being, and community health promotion.

The aim of the present study was to investigate the role of emotional maturity, ego-resiliency andspiritual intelligence in prediction ofadjustment to college with control of cognitive flexibility on students. In a correlation study 277 students of shahidchamran university in Ahvaz city were selected via multistage cluster sampling method during the fall semester of the 2016-2017 academic year. The participants completed the items of Emotional Maturity Scale(Sing and Bahargava), Ego-Resiliency Scale(Block and Kreman), Spiritual Intelligence Scale(King), Adjustment to CollegeScale(Baker and Siryk) and Cognitive Flexibility Inventory(Dennis and Vander). To analysis the data, statistical methods of Pearson correlation coefficient and Analytical Hierrarchy Process were conducted. The results showed that emotional maturity, ego resiliency, spiritual intelligence and cognitive flexibility had a significant positive correlation with adjustment to college. Moreover Analytical Hierrarchy Process showed that emotional maturity, ego-resiliency and spiritual intelligencewith control of cognitive flexibility were able to predict 28./. variance of adjustment to college scors. Therefore emotional maturity and spiritual intelligence were important predictors of adjustment to college, so in education programs for increase adjustment to college , emotional maturity, ego-resiliency and spiritual intelligence requires more attention.

Abstract Background Planarians are non-parasitic Platyhelminthes (flatworms) famous for their regeneration ability and for having a well-organized brain. Dugesia japonica is a typical planarian species that is widely distributed in the East Asia. Extensive cellular and molecular experimental methods have been developed to identify the functions of thousands of genes in this species, making this planarian a good experimental model for regeneration biology and neurobiology. However, no genome-level information is available for D. japonica, and few gene regulatory networks have been identified thus far. Results To obtain whole-genome information on this species and to study its gene regulatory networks, we extracted genomic DNA from 200 planarians derived from a laboratory-bred asexual clonal strain, and sequenced 476 Gb of data by second-generation sequencing. Kmer frequency graphing and fosmid sequence analysis indicated a complex genome that would be difficult to assemble using second-generation sequencing short reads. To address this challenge, we developed a new assembly strategy and improved the de novo genome assembly, producing a 1.56 Gb genome sequence (DjGenome ver1.0, including 202,925 scaffolds and N50 length 27,741 bp) that covers 99.4% of all 19,543 genes in the assembled transcriptome, although the genome is fragmented as 80% of the genome consists of repeated sequences (genomic frequency ≥ 2). By genome comparison between two planarian genera, we identified conserved non-coding elements (CNEs), which are indicative of gene regulatory elements. Transgenic experiments using Xenopus laevis indicated that one of the CNEs in the Djndk gene may be a regulatory element, suggesting that the regulation of the ndk gene and the brain formation mechanism may be conserved between vertebrates and invertebrates. Conclusion This draft genome and CNE analysis will contribute to resolving gene regulatory networks in planarians. The genome database is available at: http://www.planarian.jp.