Study of Post Operative Regression after Photorefractive Keratectomy for Treatment of Hyperopia and Hyperopic Astigmatism

Purpose: To study post operative regression rates after photorefractive keratectomy among patients with hyperopia and hyperopic astigmatism with follow-up of at least six months.Patients and Methods: In this historical cohort study, 171 eyes from 91 patients with moderate hyperopia and hyperopic astigmatism were treated using Bausch and Lomb Technolas 217 Z Excimer Laser. Pre-operation evaluation included; best spectacle corrected visual acuity, manifest and cycloplegic refraction, diameter of optical zone, central corneal thickness and simulated keratometry. Postoperative evaluation, performed at least six months after the procedure, included measurement of corneal curvature, manifest and cycloplegic refraction, best corrected visual acuity, uncorrected visual acuity, refraction manifest, haze, and any pathologic finding.Results: The mean regression was 0.35 ± 1.04. Post surgical manifest refraction equivalent in ± 0.5 diopter range of surgeon’s desired refraction was observed in 57.1 % of eyes. Manifest refraction equivalent in ± 1.00 diopter range was observed in 85.7 % of eyes, and manifest refraction equivalent in ± 2.00 diopter range in 96.6% of eyes. Uncorrected visual acuity of 20/20 or better was reported in 37.1 % and 20/40 or better in 92 % of patients. Loss of the best spectacle corrected visual acuity of one line was observed in 13.4 % and 2 lines or more in 5.7 % of patients.Conclusion: In patients with moderate hyperopia and hyperopic astigmatism undergoing PRK the rate of regression was in ± 1 diopter range of surgeon’s intended correction in 85.7 % of patients at least six months postoperatively, which is in line with other studies findings.Keywords: Photorefractive keratectomy; Hyperopia astigmatism; Regression.

A Study on the Indices of Professional Ethics the Martyr Teacher Morteza Motahari's Point of View

The present study aims to elaborate on the parameters of ethics of professional teaching from the point of view of Martyr Motahari. This qualitative study was conducted analytically and descriptively so as some parameters of ethics in professional teaching were extracted from ethical and educational views of Martyr Motahari.  These parameters could be listed as follows: training intellection as the first step of ethics; encouraging intellection and avoiding radical transmission of knowledge to students; augmenting senses in order to reach rational independence; attending to differences in thinking levels of students; trying to modify learning spirit; creating an inquisitive spirit in students; respecting and appreciating the educator; teaching useful knowledge and avoiding wasting time of the trainees; providing the basis for freedom of speech in class; ethical philosophy of the trainees; scientific modesty and improving the sense of religiosity. Keywords: Ethics; Muslim thinkers; Ethics of professional teaching; Martyr Motahar

Designing a model of cultural barriers for women's participation in leisure sports activities in sports recreation centers

Purpose: Leisure is one of the dimensions of social life that if it contradicts the common culture of society, it can become a social problem or dilemma; Therefore, the present study was conducted with the aim of designing a model of cultural barriers to women's participation in leisure sports activities in sports recreation centers.Methodology: The research method in terms of type and data analysis was qualitative with a data theorizing approach. The statistical population of the study consisted of senior managers, officials and faculty members aware of the field of research, which in order to select the sample people, purposeful sampling method based on a theoretical approach was used. The required data were collected using in-depth interviews and analyzed in three stages of open, axial and selective coding.Results: Based on the obtained results, causal conditions include the existence of non-indigenous culture, patriarchal perspective, weakness in the capital of women's sports culture, lack of social support and motivational barriers; Underlying conditions including economic factors, facility and facility factors and managerial factors and intervening conditions including individual factors and religious tendencies were identified. Strategies were introduced in three areas of needs assessment and policy-making, localization and alignment of relevant bodies, and after presenting the consequences, a paradigm model was presented.Conclusion: Needs assessment and policy-making, alignment of organs to achieve goals and localization of leisure activities have desirable results in order to remove cultural barriers to the presence of women in sports and recreation centers and use the benefits, Will bring

Interpretable generalized neural additive models for mortality prediction of COVID-19 hospitalized patients in Hamadan, Iran

Abstract Background The high number of COVID-19 deaths is a serious threat to the world. Demographic and clinical biomarkers are significantly associated with the mortality risk of this disease. This study aimed to implement Generalized Neural Additive Model (GNAM) as an interpretable machine learning method to predict the COVID-19 mortality of patients. Methods This cohort study included 2181 COVID-19 patients admitted from February 2020 to July 2021 in Sina and Besat hospitals in Hamadan, west of Iran. A total of 22 baseline features including patients' demographic information and clinical biomarkers were collected. Four strategies including removing missing values, mean, K-Nearest Neighbor (KNN), and Multivariate Imputation by Chained Equations (MICE) imputation methods were used to deal with missing data. Firstly, the important features for predicting binary outcome (1: death, 0: recovery) were selected using the Random Forest (RF) method. Also, synthetic minority over-sampling technique (SMOTE) method was used for handling imbalanced data. Next, considering the selected features, the predictive performance of GNAM for predicting mortality outcome was compared with logistic regression, RF, generalized additive model (GAMs), gradient boosting decision tree (GBDT), and deep neural networks (DNNs) classification models. Each model trained on fifty different subsets of a train-test dataset to ensure a model performance. The average accuracy, F1-score and area under the curve (AUC) evaluation indices were used for comparison of the predictive performance of the models. Results Out of the 2181 COVID-19 patients, 624 died during hospitalization and 1557 recovered. The missing rate was 3 percent for each patient. The mean age of dead patients (71.17 ± 14.44 years) was statistically significant higher than recovered patients (58.25 ± 16.52 years). Based on RF, 10 features with the highest relative importance were selected as the best influential features; including blood urea nitrogen (BUN), lymphocytes (Lym), age, blood sugar (BS), serum glutamic-oxaloacetic transaminase (SGOT), monocytes (Mono), blood creatinine (CR), neutrophils (NUT), alkaline phosphatase (ALP) and hematocrit (HCT). The results of predictive performance comparisons showed GNAM with the mean accuracy, F1-score, and mean AUC in the test dataset of 0.847, 0.691, and 0.774, respectively, had the best performance. The smooth function graphs learned from the GNAM were descending for the Lym and ascending for the other important features. Conclusions Interpretable GNAM can perform well in predicting the mortality of COVID-19 patients. Therefore, the use of such a reliable model can help physicians to prioritize some important demographic and clinical biomarkers by identifying the effective features and the type of predictive trend in disease progression

Antileishmanial Activity of Myrtle Methanolic Extract against Leishmaniamajor: an In Vitro Study

Background and Aim: In this study we assessed the in vitro antileishmanial activity of myrtle (Myrtus communis L.) methanolic extract against Leishmania major. Materials and Methods: The in vitro antileishmanial effects of myrtle methanolic extract against L. major promastigote and amastigotes were determined by colorimetric cell viability (MTT) assay and macrophage model, respectively. The IC50 values were also calculated by probit test in SPSS software. Results:The obtained results showed that myrtle extract was significantly inhibited promastigote growth of L. major based on a dose and time dependent manner. The measured IC50 values for myrtle methanolic extract and MA as control drug against promastigote forms of L. major were 23.6 µg/mL and 88.3 µg/mL, respectively. The obtained IC50 values were 13.

How may Doppler indices help in the differentiation of obstructive from nonobstructive hydronephrosis?

Background: We assess the potency of different Doppler indices in the differentiation of obstructive and nonobstructive hydronephrosis. Materials and Methods: In this study, infants and children who were referred for the evaluation of unilateral hydronephrosis were enrolled. Ultrasonography for the assessment of the degree of hydronephrosis and a voiding cystourethrogram for the exclusion of vesicoureteral reflux was performed. Then, Doppler ultrasonography was done for both kidneys of each patient using four classic Doppler indices as well as the difference (delta) of each index between to kidneys. Diuretic renography with 99 mTc-ethylene dicysteine (99 mTc-EC) was performed for each patient. Results: Thirty-nine patients met the inclusion criteria. After diuretic renography, 29 (74.35%) patients had shown a nonobstructive pattern, and ten (25.65%) patients had a partial (intermediate) or complete obstruction. Using receiver operating characteristic (ROC) curve, none of the classic indices of Doppler duplex (i.e., resistive index [RI], resistance index, end diastolic velocity, and peak systolic velocity) had the ability to make a difference between obstructive and nonobstructive hydronephrosis. However, by calculating the difference (delta) of these indices between two kidneys of each patient, delta RI could differentiate the nonobstructive condition, significantly (P = 0.006). A cutoff value of 0.055 has 60% sensitivity and 82.8% specificity. The area under the ROC curve for delta RI is 0.795 (standard error: 0.086, 95% confidence interval [CI]: 0.626, 0.964). Furthermore, RI ratio between two kidneys of each patient could differentiate the nonobstructive condition, significantly (P = 0.012). A cutoff point of 1.075 has 70% sensitivity and 82.8% specificity. The area under the ROC curve for RI ratio was 0.769 (standard error: 0.104, 95% CI: 0.565, 0.973). Conclusion: This study shows that RI ratio and delta RI with a high specificity could differentiate nonobstructive hydronephrosis and therefore it is a promising way to use especially in the follow-up of children with hydronephrosis

Protective Effect of Ghrelin on Sodium Valproate-induced Liver Injury in Rat

Ghrelin is a peptide that has protective effects on many tissues injury. It has anti-inflammatory and anti-oxidant effects. Sodium valproate is widely used anticonvuisant and anti-depression drug with hepatotoxic side effects. The aim of this study was to evaluated the protective role of ghrelin in liver toxicity due to sodium valproate overdose. Eighteen rats were used in this study and divided in to three groups, containing: control, sodium valproate, and sodium valproate and ghrelin groups. Nitric oxide (NO), prostaglandin E2 (PGE2) and hepatic enzymes AST (aspartate aminotransferase) and ALT (alanine aminotransferase), were assessed and histologic study of liver were performed as indicators of liver damage following sodium valproate toxicity. This study showed the ghrelin decreased ALT and AST to the normal level. Our results show that ghrelin significantly increased NO metabolites and decreased PGE2 level comparison with sodium valproate group, but had no significant change compared to the control group. we showed that ghrelin administration inhibited liver injury in rats due to sodium valproate toxicity

Prediction of water formation temperature in natural gas dehydrators using radial basis function (RBF) neural networks

Raw natural gases usually contain water. It is very important to remove the water from these gases through dehydration processes due to economic reasons and safety considerations. One of the most important methods for water removal from these gases is using dehydration units which use Triethylene glycol (TEG). The TEG concentration at which all water is removed and dew point characteristics of mixture are two important parameters, which should be taken into account in TEG dehydration system. Hence, developing a reliable and accurate model to predict the performance of such a system seems to be very important in gas engineering operations. This study highlights the use of intelligent modeling techniques such as Multilayer perceptron (MLP) and Radial Basis Function Neural Network (RBF-ANN) to predict the equilibrium water dew point in a stream of natural gas based on the TEG concentration of stream and contractor temperature. Literature data set used in this study covers temperatures from 10 °C to 80 °C and TEG concentrations from 90.000% to 99.999%. Results showed that both models are accurate in prediction of experimental data and the MLP model gives more accurate predictions compared to RBF model