Payavard Salamat

Co-Authorship and Word Co-Occurrence Maps in of Endocrinology and Metabolism Scientific Publications of Iran

Maryam Shekofteh

Background and Aim: The growth and development of scientific fields depends on correct and accurate planning and a general and comprehensive understanding of the structure of these fields. Scientific maps are a type of scientometric methods that help to understand the current state of scientific fields and reveal their internal structure. The aim of the present study is to analyze co-authorship and word co-occurrence maps of scientific publications of Iran in the field of endocrinology and metabolism.
Materials and Methods: This is a cross-sectional scientometrics study. The research population is all scientific publications of Iran in the field of Endocrinology and Metabolism on the Web of Science. The co-authorship and co-word maps were analyzed using VOSviewer, Gephi, and NodeXL software. Network analysis was done using social network analysis indicators. Thematic clusters and emerging subjects were also identified through the examination of word co-occurrence networks.
Results: The total scientific publications of Iran in the field of endocrinology and metabolism on the Web of Science was 4847 documents. The co-authorship network is a type of sparse network. The value of the cluster coefficient of this network was 0.212 and its diameter was 11. The average degree of the co-authorship network (6.62) shows that each node is connected with about 6 other nodes on average. The diameter of the co-authorship network is 11. The most productive and influential outhors are Azizi F and Larijani B. Six thematic clusters were identified in the word co-occurrence network, the largest one is oxidative stress and gene expression, followed by the obesity and diabetes cluster. The word “autoimmunity” is one of the emerging words in this field.
Conclusion: Iran’s research in the field of Endocrinology and Metabolism shows an increasing trend, but there is little cooperation between the authors of the field. Their co-authorship networks are sparse, and the authors’ tendency to form clusters is low. Therefore, planning is needed to increase scientific cooperation and the density of networks. It is suggested that the researchers of this field pay attention to the thematic clusters of the co-word network and emerging subjects in the design of their future research.

Performance Indicators of Hospitals Affiliated to Isfahan University of Medical Sciences before and after COVID-19 Using Pabon Lasso Model

Sedigheh Torki Harchegani

Background and Aim: Considering the limitation of resourses, improvement of the hospital efficiency is an absolute necessity. The Covid19 pandemic had a considerable effect on performance indicators of hospitals. This study aimed to investigate changes of indicators of hospitals affiliated to Isfahan University of Medical Sciences before and after Covid19.
Materials and Methods: This study was descriptive-cross sectional. The statistical population included all hospitals under the coverage of Isfahan University of Medical Sciences (38). The input data were related to the three years 2019 to 2021 (the year 2019 as the year before outbreak of Covid-19, the year 2020 as the first year of outbreak and the year 2021 as the second year of outbreak), which were collected using the researcher’s form based on reports extracted from the statistics and hospital information system available in the statistics and information technology management and finally the data analyzed through the PabonLasso model.
Results: Process of indicators during the years 2019-2021 shows that mean of indicators of bed occupancy rate and bed turnover rate as the first year of outbreak of Covid19 (2020) that was the peak of the disease has decreased as compared to the year 2019 and average length of stay has increased. In years 2019, 2020 and 2021, 24.32, 23.68 and 24.32 percent of hospitals were in the third area (efficient area). From 2019 to 2020, efficiency change was observed in 27 percent of the hospitals where 6 hospitals had positive trend and 4 hospitals had negative trend and from 2020 to 2021, efficiency change was observed in 16 percent of hospitals where 2 hospitals had positive and 4 had negative trend.
Conclusion: Considering the low efficiency of hospitals, it is suggested to carry out continuous and annual assessment of efficiency changes in hospitals in order to identify the causes of inefficiency early and preventing its drop and it is necessary for health managers and policy makers to take appropriate measures in the conditions of the outbreak of unexpected disease such as the outbreak of Covid-19 in order to use hospital resources more optimally.

Heuristic Usability Evaluation of Web-Based COVID-19 Management Dashboard

Somayyeh Zakerabasali

Background and Aim: Today, information dashboards are the main tools for understanding and extracting knowledge from large data sets and can be used in various forms by healthcare providers. At the same time as the COVID-19 epidemic, several information dashboards were designed and developed. Still, due to the speed of the spread of this virus, there was no opportunity to evaluate them. Therefore, this research was conducted to evaluate the usability of the Covid-19 management dashboard.
Materials and Methods: This descriptive-cross-sectional study was conducted on the management dashboard of Shiraz University of Medical Sciences. The dashboard was evaluated using an exploratory evaluation method with the participation of three medical informatics experts. Each of the evaluators evaluated the system independently and identified its problems by using thirteen principle checklist. Then, with the presence of all evaluators, the list of identified problems was combined, repeated problems were removed from the list and a single list was prepared. In this joint meeting, any disagreements about the problems found by the evaluators were discussed and reached a common opinion. Finally, the evaluators determined and reported the severity of the problems.
Results: In this evaluation, a total of 79 usability problems were identified. The highest number of problems was related to the feature “Help and Documentation” (12 problems), and the lowest number of problems was related to the features “Aesthetic and Minimalist Design” (2 problems) and “Privacy” (1 problem). 45.58% of the identified problems were in the category of major problems. The average degree of severity of the problems was from 2.05 (minor problem) related to the feature of “Pleasurable and Respectful Interaction with the User” to 2.99 (major problem) related to the feature of “User Control and Freedom”. Also, the average severity of problems was calculated as 2.5, classified in the range of minor problems.
Conclusion: The heuristic evaluation method identifies user interface problems of information systems and dashboards using predetermined standards. If these problems are not resolved, they will cause users’ time wasted, errors to increase, information quality to decrease, and users’ dissatisfaction and confusion.

Investigation of Artificial Intelligence Techniques for the Management of Cataract Disease: A Systematic Review

Maryam Zahmatkeshan

Background and Aim: Cataracts are recognized as the cause of 51% of blindness worldwide. Following the promising initial results of artificial intelligence systems in eye diseases, AI algorithms have been applied in the diagnosis of cataracts, grading the severity of cataracts, intraocular lens calculations, and even as an assistive tool in cataract surgery. This study presents a systematic review of AI techniques in the management of cataract disease.
Materials and Methods: This systematic review study was conducted to investigate artificial intelligence techniques to manage cataract disease until November 11, 2023, and based on PRISMA guidelines. We retrieved all relevant articles published in English through a systematic search of PubMed, Scopus, and Web of Science online databases.
Results: In our initial search, 192 records were identified in the databases, and eventually, 23 articles were selected for review. The results indicated that convolutional neural network algorithms (6 articles), recurrent neural networks (1 article), deep convolutional networks (1 article), support vector machines (2 articles), transfer learning (1 article), decision trees (4 articles), random forests (4 articles), logistic regression (3 articles), Bayesian algorithms (3 articles), XGBoost (3 articles), and K-nearest neighbors clustering algorithms (2 articles) were the artificial neural network and machine learning techniques and algorithms utilized. These techniques were employed in the studies for the diagnosis (70%), management (17%), and prediction (13%) of cataract disease.
Conclusion: Various artificial intelligence and machine learning techniques and algorithms can be effective and efficient in diagnosing, grading, managing, and predicting cataracts with high accuracy. In this study, deep learning techniques and convolutional neural networks have made the greatest contribution to cataract diagnosis. Deep learning techniques, decision trees, and Bayesian algorithms were involved in cataract management. Machine learning algorithms such as logistic regression, random forest, artificial neural network, decision tree, K1-nearest neighbor, XGBoost, and adaptive boosting also played a role in cataract prediction. Just as early prediction, diagnosis, and timely referral can reduce future complications of the disease, the use of systems based on artificial intelligence models that have acceptable accuracy can be effective in supporting the decision-making process of physicians and managing this disease.

The Molecular Isolation of the srf Gene from Thermophilic Soil Bacilli and Its Cloning in Susceptible Cells for Industry Use

Nooshin Khandandezfully

Background and Aim: Thermophilic bacillus is a type of thermophilic bacillus, carries various genes and biosurfactants, microbial surfactants are surface active molecules produced by various microorganisms such as bacteria, yeasts and filamentous fungi. Biosurfactants are able to reduce the surface energy between phases and create electrostatic barriers, thus preventing the integration of particles. The aim of the present study was the molecular isolation of the srf gene from thermophilic soil bacilli and its cloning in susceptible cells for industry use.
Materials and Methods: Fifteen samples from different regions of Kerman were collected and screened to isolate Bacillus strains. Morphological and biochemical studies were done to identify the strains. After biochemical examination of isolated microbial isolates and confirmation of Bacillus strains, DNA extraction was done. Then, the srf gene was identified by PCR method from these isolates. The amplified fragment was inserted into pTG19 vector by TA cloning method. Then, the recombinant vector was transformed into E.coli origami bacteria and cloning was confirmed using common methods. The housekeeping gene 16S rRNA was used as the internal control of the test. The analysis of the gene expression level was performed by measuring the relative expression of mRNA as compared to the negative control that E.coli bacteria lacked the srf gene.
Results: A total of 12 isolates of thermophilic bacilli were obtained from soil samples. As result, the PCR reaction for the srf gene with the designed primers was found to be positive in 1 isolate (8.3%). The presence of srf gene and the expression of this gene were checked by real time PCR test. Examining the white and blue colonies, M13 primer, junction location and determination of the 16S rRNA gene sequence confirmed the correctness of the cloning of the mentioned gene in the host bacteria.
Conclusion: As a result of the present study, it was possible to identify the native thermophilic bacillus carrying the srf gene, which can be used to obtain biosurfactant enzyme widely, conveniently and economically, for use in industrial and agricultural purposes, removing oil pollutants and reducing environmental surface tension, etc. which can be advantages.

Designing, Implementing and Evaluating the Protocol before, during and after Whipple Surgery and Its Effect on the Knowledge, Attitude and Clinical Skills of Surgical Technology Students

Parsa Farmahin farahany

Background and Aim: The usual trainings are not enough to acquire the knowledge and skills of operating room students to play the role of scrub and mobile person, especially in complex and specialized surgeries. This research was conducted with the aim of determining the effect of designing, implementing and evaluating the protocol before, during and after Whipple surgery and its effect on the knowledge, attitude and clinical skills of surgical technology students of Iran University of Medical Sciences.
Materials and Methods: This research was a semi-experimental study of pre- and post-intervention type, during which 50, fifth and seventh semester undergraduate students of surgical technology were selected and trained using the designed protocol. The content of the protocol included the latest principles of Whipple surgery technology in the field of surgical anatomy, pathology of the digestive system and pancreas, diagnostic procedures and preparations before Whipple surgery, the procedure of Whipple surgery and the post-surgery phase and the recovery period of Whipple surgery. Before and after the training, the amount of knowledge, attitude and clinical skills of the students were evaluated and compared using a questionnaire and an observational checklist. The data were analyzed using paired t-test, non-parametric Wilcoxon test and analysis of covariance test in SPSS software.
Results: The results of this study showed that after using the designed educational protocol, the knowledge, attitude and clinical skills of surgical technology students increased. That is, the use of the designed educational protocol was effective on the level of knowledge, attitude and especially the clinical skills of the students. So that a statistically significant difference was observed in the average scores of the knowledge, attitude and clinical skill test of the students before and after training (P<0.05).
Conclusion: Based on the results of this study, designing and using educational protocols is an effective method in the process of teaching and evaluating the level of knowledge, attitude and clinical skills of students in complex and specialized surgeries such as Whipple surgery. Therefore, the use of educational protocols designed in the process of teaching students is recommended to all professors and educational officials of surgical technology.

Designing a Decision Support System in the Diagnosis of Neurofibromatosis Type 1 Disease Using Fuzzy Cognitive Map

Alireza Shahraki

Background and Aim: Given the high sensitivity of the medical field, a mistake can cause irreparable damage to human society. For this reason, finding the symptoms of the disease and the relationships between them to facilitate the improvement of diseases is inevitable. Therefore, the aim of the present study was to first identify the symptoms of neurofibromatosis type 1 by specialists, then determine the relationship between the symptoms and the degree of their impact on each other in order to determine the most important criterion in improving the disease.
Materials and Methods: The present study is of a developmental-applied type in terms of its purpose and of a descriptive-survey type in terms of its data collection method. The case study of the present study is spinal disorders, of which neurofibromatosis type 1 has been diagnosed as one of them based on the opinion of experts. Neurofibromatosis type 1 is a genetic disorder that causes tumors in the nervous tissue. Accordingly, in the present study, the criteria, which are the symptoms of the disease, were first determined using the opinion of a group of experts and the implementation of the fuzzy Delphi method. In the next step, a model for the causal relationships between the symptoms of the disease is presented. For this purpose, a fuzzy cognitive map is drawn using MATLAB, FCMapper and Pajek software, then backward and forward scenarios are presented for neurofibromatosis type 1 and the disease improvement scenario is determined.
Results: The results showed that hormonal changes, flat brown spots on the skin, freckles in the armpit and groin area, soft bumps on the face or under the skin, high blood pressure, respiratory problems, bumps on the iris of the eye (Lish nodules), tumor in the optic nerve-ocular glioma, short stature, bone deformity, learning disabilities-attention deficit hyperactivity disorder (ADHD) and larger than average head size are ranked first to twelfth, respectively. The causal relationships between the symptoms showed that the criterion of hormonal changes has the greatest impact on the criterion of freckles in the armpit or groin area; Therefore, if the hormonal changes criterion improves, neurofibromatosis type 1 will also improve.
Conclusion: The findings of this study have helped the medical community to have a better understanding of the symptoms of the disease so that doctors can improve their prevention and care recommendations based on the severity of the symptoms of the diseases.

Relationship between FSH Receptor’s Exon 10 Polymorphisms with IVF Results in Iranian Women

Mohsen Ghadami

Background and Aim: Follicle stimulating glycoprotein hormone (FSH) exerts its functions through its receptor (FSHR). In women of reproductive age, this hormone causes the growth and development of follicles in the ovary during the follicular phase of the menstrual cycle. This hormone is widely used in the treatment of infertility. Several polymorphisms have been reported so far in the FSHR gene, which are effective in the ovarian response, but the FSHR gene has two very common single nucleotide polymorphisms at positions 680 and 307 in exon 10. One of them at position 307 changes the amino acid threonine to alanine and the other at position 680 changes asparagine to serine. The polymorphism at position 307 of exon 10 is in the extracellular region of the receptor and the binding site of the hormone, which can be affected in response to internal and external FSH stimulation. These two SNPs have been reported to be associated with various ovarian responses and IVF outcomes in different populations. Different studies have particularly focused on rs6166 (p. Asn680Ser), but this study was conducted to investigate the possible association between rs6166 and rs6165 (p. Thr307Ala) and the IVF outcome.
Materials and Methods: After blood sampling and DNA extraction, the two polymorphisms in exon 10 of FSHR gene were analyzed using PCR-RFLP method in 120 women randomly assigned to two equal groups including IVF successful and IVF unsuccessful infertile women. The selection of patients to enter the study as well as the criteria for successful IVF are described in the text. In order to confirm the results, DNA sequencing was done for some selected samples. Finally, the results were analyzed using SPSS software.
Results: No significant differences were found in either SNPs between successful IVF and unsuccessful IVF patients in allelic frequencies (P-value>0.05).
Conclusion: Despite the different results of the studies conducted regarding the effect of FSHR gene polymorphisms (rs6165 and rs6166) in different populations, considering the lack of significant difference in the frequency of the above polymorphisms in the studied population, it is concluded that these two polymorphisms cannot be used to predict the outcome of IVF in Iranian infertile women.