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Amin Jalili Sarqaleh, Mohammad Azizi, Kianosh Khamoshyan,
Volume 16, Issue 1 (3-2022)
Volume 16, Issue 1 (3-2022)
Abstract
Background and Aim: Multiple Sclerosis is a chronic disease of myelin sheath degradation that reduces the quality of life in patients. Recent studies emphasize on the effect of exercise and natural supplements on the improvement of disease symptoms and quality of life. The aim of this study was to evaluate the effect of eight weeks combined training at home with red grape juice supplementation on quality of life in women with Multiple Sclerosis.
Materials and Methods: In this study, 48 women with MS in the age range of 20-40 years were voluntarily selected and divided into 4 groups: training (n=12), supplement (n=12), training+supplement (n=12) and control (n=12). Combined training included 8 weeks and 3 sessions per week for 60 minutes of endurance and resistance training with an intensity of 10-12 rate of perceived exertion. Subjects consumed 250 cc of grape juice supplement with 68% concentration for 8 weeks, 3 times a week. The control group engaged in their daily activities. Quality of life was measured with standard questionnaire (WHOQOL-BREF) 48 hours before and after the end of the study.
Results: Eight weeks of intervention made a significant change in the quality of life. Based on the correlation t the results were as follows training groups (P=0.001)(7.1%), supplement (P=0.001)(10.5%) and training+supplement (0.000), There was a significant difference between the pre-test and the post-test (P≤0.05). But the changes in the training+supplement group were more than the other groups (P=0.000)(13.3%). In addition, based on the results of one-way analysis of variance, the amount of changes between the groups was also significant (P≤0.05). There was a significant difference between the training group and the control group, supplement group and supplement+training group (P≤0.05). Also, the supplement group had a significant difference with the exercise group and the control group, but there was no significant difference with the supplement + training group (P≥0.05). A significant difference was observed in the supplement+training group with all groups except the supplement group (P≤0.05).
Conclusion: According to the results of the present study, women with Multiple Sclerosis can use combined training at home with red grape juice supplement to improve their quality of life.
Materials and Methods: In this study, 48 women with MS in the age range of 20-40 years were voluntarily selected and divided into 4 groups: training (n=12), supplement (n=12), training+supplement (n=12) and control (n=12). Combined training included 8 weeks and 3 sessions per week for 60 minutes of endurance and resistance training with an intensity of 10-12 rate of perceived exertion. Subjects consumed 250 cc of grape juice supplement with 68% concentration for 8 weeks, 3 times a week. The control group engaged in their daily activities. Quality of life was measured with standard questionnaire (WHOQOL-BREF) 48 hours before and after the end of the study.
Results: Eight weeks of intervention made a significant change in the quality of life. Based on the correlation t the results were as follows training groups (P=0.001)(7.1%), supplement (P=0.001)(10.5%) and training+supplement (0.000), There was a significant difference between the pre-test and the post-test (P≤0.05). But the changes in the training+supplement group were more than the other groups (P=0.000)(13.3%). In addition, based on the results of one-way analysis of variance, the amount of changes between the groups was also significant (P≤0.05). There was a significant difference between the training group and the control group, supplement group and supplement+training group (P≤0.05). Also, the supplement group had a significant difference with the exercise group and the control group, but there was no significant difference with the supplement + training group (P≥0.05). A significant difference was observed in the supplement+training group with all groups except the supplement group (P≤0.05).
Conclusion: According to the results of the present study, women with Multiple Sclerosis can use combined training at home with red grape juice supplement to improve their quality of life.
Synergism of Linezolid and Rifampin to Combat Multidrug-Resistant Environmental Enterococci Isolates
Mobina Noori, Leila Fozouni, Ania Ahani Azari,
Volume 16, Issue 3 (8-2022)
Volume 16, Issue 3 (8-2022)
Abstract
Background and Aim: Wastewater is one of the most dangerous and important sources of pathogens and their treatment does not always guarantee the elimination of pathogenic bacteria. Enterococci, as opportunistic pathogenic bacteria, fastidious and cause of nosocomial infections, have a wide environmental distribution and one of the routes of their transmission to humans is water and wastewater. The increasing rate of drug- resistance among bacteria indicates the need for investigation of novel antibacterial agents or their combination effects. The aim of this study was to investigate the effect of linezolid in combination with rifampin on the elimination of multidrug- resistant enterococci in two treatment plants in Golestan province.
Materials and Methods: Enterococcus species from eighty samples were isolated from treatment plants in two cities of the Golestan Province (North of Iran) including Gorgan and Bandar-e Torkaman during January-June 2021. The isolates were identified based on the most probable number (MPN), filtration, microbiological tests and finally by using specific gene detection by ddlE primer with polymerase chain reaction. Kirby Bauer performed an antibiotic resistance pattern according to CLSI- 2020 guidelines for six classes of antibiotics. The minimum inhibitory concentration of linezolid was determined individually and by synergist effect with rifampin by broth microdilution method.
Results: After phenotypic and molecular diagnosis (PCR) of raw and treated wastewater samples, in 32 (40%) wastewater samples, enterococci species were identified and confirmed. Tetracycline was the least effective so, about 100% of Enterococcus faecalis and Enterococcus faecium isolates were resistant to it. The prevalence of linezolid-resistant E. faecalis was 11%. A total of 20 enterococcal isolates (62.5%) had multiple resistance. The concentration of linezolid in combination with rifampin, which inhibited 90% growth of the isolates (MIC90) was 1μg /ml, four-fold lower than linezolid alone (MIC90=4 μg/ml). In addition, none of the enterococci isolates showed resistance to the linezolid/rifampin combination (P=0.001).
Conclusion: The results of this research confirmed the presence of enterococci resistant to vancomycin and other antibiotics in the wastewater treatment plant samples in Golestan province. The favorable combination effect of linezolid and rifampin on the inhibition of multi-drug resistant isolates implies their synergy.
Materials and Methods: Enterococcus species from eighty samples were isolated from treatment plants in two cities of the Golestan Province (North of Iran) including Gorgan and Bandar-e Torkaman during January-June 2021. The isolates were identified based on the most probable number (MPN), filtration, microbiological tests and finally by using specific gene detection by ddlE primer with polymerase chain reaction. Kirby Bauer performed an antibiotic resistance pattern according to CLSI- 2020 guidelines for six classes of antibiotics. The minimum inhibitory concentration of linezolid was determined individually and by synergist effect with rifampin by broth microdilution method.
Results: After phenotypic and molecular diagnosis (PCR) of raw and treated wastewater samples, in 32 (40%) wastewater samples, enterococci species were identified and confirmed. Tetracycline was the least effective so, about 100% of Enterococcus faecalis and Enterococcus faecium isolates were resistant to it. The prevalence of linezolid-resistant E. faecalis was 11%. A total of 20 enterococcal isolates (62.5%) had multiple resistance. The concentration of linezolid in combination with rifampin, which inhibited 90% growth of the isolates (MIC90) was 1μg /ml, four-fold lower than linezolid alone (MIC90=4 μg/ml). In addition, none of the enterococci isolates showed resistance to the linezolid/rifampin combination (P=0.001).
Conclusion: The results of this research confirmed the presence of enterococci resistant to vancomycin and other antibiotics in the wastewater treatment plant samples in Golestan province. The favorable combination effect of linezolid and rifampin on the inhibition of multi-drug resistant isolates implies their synergy.
Nillofar Moradi, Mohammad Azizi, Elham Niromand, Worya Tahmasebi,
Volume 16, Issue 3 (8-2022)
Volume 16, Issue 3 (8-2022)
Abstract
Background and Aim: Diabetes is a multifactorial disease characterized by chronic high blood sugar and insulin resistance. In general, the global increase in the incidence of type 2 diabetes is caused by poor nutrition and inactivity. Therefore, the aim of this study was to evaluate the effect of 8 weeks of combined exercise with quinoa supplementation on fasting blood sugar, appetite and quality of life in women with type 2 diabetes.
Materials and Methods: In this study, 36 women with type 2 diabetes were divided into 3 groups: exercise+supplement (n=12), supplement (n=12) and control (n=12). The exercise+supplement and supplement group consumed 25 grams of cooked quinoa seeds for 3 days a week. The exercise+supplement group also did combined exercise for 8 weeks, 3 times a week. Exercise was performed with an intensity of 10-12 pressure perception. The Persian version of the quality-of-life questionnaire was used to measure the quality-of-life index and the appetite questionnaire was used to assess appetite. Blood samples were taken 48 hours before and after the interventions, measurements and questionnaires were completed. One Way ANOVA, LSD post hoc and paired t were used at the significance level of P≤0.05.
Results: According to the results of 8 weeks of intervention in the exercise+supplement group (P=0.001)(2.59%) and the supplement group (P=0.04)(1.54%) compared to the control group (P=0.32)(1.54%) caused a significant reduction in Fasted blood sugar. There was also a significant decrease in appetite index in the exercise+supplement group (P<0.001)(54.20%) and the supplement group (P=0.001)(60.31%) as compared to the control group (P=0.11)(7.91%). Quality of life data also showed a significant increase in this index in the exercise+supplement group (P=0.008)(5.95%) and supplement group (P=0.002)(3.80%) as compared to the control group (P=0.10)(0.99%).
Conclusion: Eight weeks of combined exercise with consumption of quinoa seeds has a positive and improving effect on fasting blood sugar index, quality of life and appetite in patients with type 2 diabetes.
Materials and Methods: In this study, 36 women with type 2 diabetes were divided into 3 groups: exercise+supplement (n=12), supplement (n=12) and control (n=12). The exercise+supplement and supplement group consumed 25 grams of cooked quinoa seeds for 3 days a week. The exercise+supplement group also did combined exercise for 8 weeks, 3 times a week. Exercise was performed with an intensity of 10-12 pressure perception. The Persian version of the quality-of-life questionnaire was used to measure the quality-of-life index and the appetite questionnaire was used to assess appetite. Blood samples were taken 48 hours before and after the interventions, measurements and questionnaires were completed. One Way ANOVA, LSD post hoc and paired t were used at the significance level of P≤0.05.
Results: According to the results of 8 weeks of intervention in the exercise+supplement group (P=0.001)(2.59%) and the supplement group (P=0.04)(1.54%) compared to the control group (P=0.32)(1.54%) caused a significant reduction in Fasted blood sugar. There was also a significant decrease in appetite index in the exercise+supplement group (P<0.001)(54.20%) and the supplement group (P=0.001)(60.31%) as compared to the control group (P=0.11)(7.91%). Quality of life data also showed a significant increase in this index in the exercise+supplement group (P=0.008)(5.95%) and supplement group (P=0.002)(3.80%) as compared to the control group (P=0.10)(0.99%).
Conclusion: Eight weeks of combined exercise with consumption of quinoa seeds has a positive and improving effect on fasting blood sugar index, quality of life and appetite in patients with type 2 diabetes.
Fatemeh Bahador, Azam Sabahi, Samaneh Jalali, Fatemeh Ameri,
Volume 16, Issue 6 (1-2023)
Volume 16, Issue 6 (1-2023)
Abstract
Background and Aim: Diabetes is one of the most common metabolic diseases in Iran and the fifth leading cause of death all over the world. Its spread around the world has created new methods in biomedical research, including artificial intelligence. The present study was carried out to review the studies conducted in the area of artificial intelligence and diabetes in Iran.
Materials and Methods: This study was carried out using a systematic review method. Valid domestic databases, including Irandoc, Magiran, Sid and Google Scholar search engine, were reviewed using the keywords of artificial intelligence and diabetes in Persian both individually and in a combined manner without time limitation until June 20, 2021. A total number of 7495 articles were retrieved, which were screened in different stages (exclusion of duplicates (1824), title and summary of the articles (5884) and full text (30) and finally 20 articles that met the criteria desired by the researchers were carefully reviewed.
Results: Among the retrieved articles, 20 articles met the inclusion criteria, of which 16 articles dealt with methods based on artificial intelligence and 4 articles dealt with the design of new systems based on artificial intelligence. Also, 10 articles examined the role of artificial intelligence in prediction, 8 articles in diagnosis, and 2 articles dealt with the control and management of diabetes. Most of the articles were related to the use of data mining methods such as artificial neural network, decision tree, etc. (16 articles). Some studies also evaluated and compared artificial intelligence methods on application, accuracy and the sensitivity of artificial intelligence in diagnosing and predicting diabetes (10 studies).
Conclusion: A systematic review of articles revealed that the use of data mining methods for diabetes management in Iran has been associated with good progress, but there is a need to design artificial intelligence systems and algorithms and more measures should be taken in the area of diabetes control and management.
Materials and Methods: This study was carried out using a systematic review method. Valid domestic databases, including Irandoc, Magiran, Sid and Google Scholar search engine, were reviewed using the keywords of artificial intelligence and diabetes in Persian both individually and in a combined manner without time limitation until June 20, 2021. A total number of 7495 articles were retrieved, which were screened in different stages (exclusion of duplicates (1824), title and summary of the articles (5884) and full text (30) and finally 20 articles that met the criteria desired by the researchers were carefully reviewed.
Results: Among the retrieved articles, 20 articles met the inclusion criteria, of which 16 articles dealt with methods based on artificial intelligence and 4 articles dealt with the design of new systems based on artificial intelligence. Also, 10 articles examined the role of artificial intelligence in prediction, 8 articles in diagnosis, and 2 articles dealt with the control and management of diabetes. Most of the articles were related to the use of data mining methods such as artificial neural network, decision tree, etc. (16 articles). Some studies also evaluated and compared artificial intelligence methods on application, accuracy and the sensitivity of artificial intelligence in diagnosing and predicting diabetes (10 studies).
Conclusion: A systematic review of articles revealed that the use of data mining methods for diabetes management in Iran has been associated with good progress, but there is a need to design artificial intelligence systems and algorithms and more measures should be taken in the area of diabetes control and management.
Ashraf Dehghani, Maryam Ghanbari Khoshnood, Somayeh Amini Sarteshnizi, Arezoo Farhadi,
Volume 17, Issue 1 (3-2023)
Volume 17, Issue 1 (3-2023)
Abstract
Background and Aim: The emergence and continuity of Corona has forced universities and higher education centers to change their educational strategy to take appropriate and consistent action to improve their educational programs. Due to the importance of e-learning and e-learning in response to these conditions, the present study investigated the experience of students of Hamadan University of Medical Sciences from e-learning in the Covid-19 crisis condition.
Materials and Methods: This was a qualitative research with an interpretive phenomenological approach. The purposeful sampling method was used. Semi-structured interviews were used to collect data. After the thirteenth interview, the theoretical saturation of the data was achieved and the interview process with the sixteenth person was completed. In order to analyze the text of the interviews, the Colaizzi method was used.
Results: From the analysis of the obtained data, three main themes: “Communication and interaction” with five sub-themes (lack of proper interaction between student/professor and student/student, lack of motivation, security and mental health, knowledge sharing and efficiency atmosphere in time and cost), “Management of time and learning style” with six sub-themes (low quality of teaching, stress, access and provision of resources, exam health, gaining experience and skills and opportunity to learn again and innovation in education) and “Infrastructure and technical facilities” were extracted with three sub-themes (weak support, ignoring educational equality and promoting media literacy). Weak interaction between professor and student, increasing level of anxiety and individual responsibility to achieve success in learning and weak technical and management infrastructure were the main challenges obtained from these three themes. Providing a platform for research, self-regulation and self-management in learning, increasing the knowledge and skills of information and communication technology are among the opportunities that are included in these themes.
Conclusion: The results of the current research require attention to the approach of interaction and communication between the learner and the learner, to review the methods of teaching and skill-learning, to improve the quality of electronic learning and to prepare suitable infrastructures for optimal use of electronic learning.
Materials and Methods: This was a qualitative research with an interpretive phenomenological approach. The purposeful sampling method was used. Semi-structured interviews were used to collect data. After the thirteenth interview, the theoretical saturation of the data was achieved and the interview process with the sixteenth person was completed. In order to analyze the text of the interviews, the Colaizzi method was used.
Results: From the analysis of the obtained data, three main themes: “Communication and interaction” with five sub-themes (lack of proper interaction between student/professor and student/student, lack of motivation, security and mental health, knowledge sharing and efficiency atmosphere in time and cost), “Management of time and learning style” with six sub-themes (low quality of teaching, stress, access and provision of resources, exam health, gaining experience and skills and opportunity to learn again and innovation in education) and “Infrastructure and technical facilities” were extracted with three sub-themes (weak support, ignoring educational equality and promoting media literacy). Weak interaction between professor and student, increasing level of anxiety and individual responsibility to achieve success in learning and weak technical and management infrastructure were the main challenges obtained from these three themes. Providing a platform for research, self-regulation and self-management in learning, increasing the knowledge and skills of information and communication technology are among the opportunities that are included in these themes.
Conclusion: The results of the current research require attention to the approach of interaction and communication between the learner and the learner, to review the methods of teaching and skill-learning, to improve the quality of electronic learning and to prepare suitable infrastructures for optimal use of electronic learning.
Akram Hemmatipour, Ali Hatami, Azam Jahangirimehr, Foruzan Jelodari, Zahra Mehri,
Volume 17, Issue 1 (3-2023)
Volume 17, Issue 1 (3-2023)
Abstract
Background and Aim: There is a correlation between disease and quality of life in patients with chronic disease and physical disorders have a direct effect on all aspects of quality of life. Therefore, this study was conducted to determine the effect of family-centered empowerment model based on multimedia education on the quality of life of children with thalassemia.
Materials and Methods: In this experimental study, 120 patients along with their parents, who had medical records at the thalassemia center of Khatam al-Anbiya Hospital in Shoushtar, were selected according to the inclusion criteria and were divided into two groups of intervention and control (n=60) by random allocation. Subjects were matched in terms of age and gender. The data collection tools included Pediatric Quality of Life Inventory (Ped-SQL) and researcher-made questionnaires of awareness and self-efficacy in the area of thalassemia. The collected data were analyzed using SPSS and Mann-Whitney and Wilcoxon statistical tests and Pearson’s correlation coefficient.
Results: Out of 120 children who were included in the study, 87 were girls (72.5%), the mean age of these children was 9.74±2.25 years and disease duration was 5.35±4.47 years. In this study, in terms of children’s quality of life and its dimensions, after the implementation of the educational model, a significant increase was observed compared to pre-test phase only in the intervention group (P<0.001). After implementing this model, the level of knowledge (P<0.001) and self-efficacy of parents (P=0.003) was faced with a significant increase, and this significance was also observed compared to the control group (P<0.001). The variables of age, gender, disease duration and parents’ education level had no effect on parents’ self-efficacy and knowledge as well as children’s quality of life (P>0.05).
Conclusion: Based on the results of the present study, the implementation of family-centered empowerment programs based on multimedia education among parents of children with thalassemia improved the quality of life of these children by increasing the knowledge and self-efficacy of their parents. It is suggested that this program be implemented on a wider scale with better facilities for parents and the family members.
Materials and Methods: In this experimental study, 120 patients along with their parents, who had medical records at the thalassemia center of Khatam al-Anbiya Hospital in Shoushtar, were selected according to the inclusion criteria and were divided into two groups of intervention and control (n=60) by random allocation. Subjects were matched in terms of age and gender. The data collection tools included Pediatric Quality of Life Inventory (Ped-SQL) and researcher-made questionnaires of awareness and self-efficacy in the area of thalassemia. The collected data were analyzed using SPSS and Mann-Whitney and Wilcoxon statistical tests and Pearson’s correlation coefficient.
Results: Out of 120 children who were included in the study, 87 were girls (72.5%), the mean age of these children was 9.74±2.25 years and disease duration was 5.35±4.47 years. In this study, in terms of children’s quality of life and its dimensions, after the implementation of the educational model, a significant increase was observed compared to pre-test phase only in the intervention group (P<0.001). After implementing this model, the level of knowledge (P<0.001) and self-efficacy of parents (P=0.003) was faced with a significant increase, and this significance was also observed compared to the control group (P<0.001). The variables of age, gender, disease duration and parents’ education level had no effect on parents’ self-efficacy and knowledge as well as children’s quality of life (P>0.05).
Conclusion: Based on the results of the present study, the implementation of family-centered empowerment programs based on multimedia education among parents of children with thalassemia improved the quality of life of these children by increasing the knowledge and self-efficacy of their parents. It is suggested that this program be implemented on a wider scale with better facilities for parents and the family members.
Davoud Haseli, Somayeh Paknahad,
Volume 17, Issue 2 (5-2023)
Volume 17, Issue 2 (5-2023)
Abstract
Background and Aim: Bibliometric analysis by describing the state of publications and identifying key entities and emerging topics plays an important role in evaluating research. The aim of the paper is to study the global trends of scientific collaboration networks of researchers, organizations and countries and the co-occurrence of words in the field of social medicine in the database of Web of Science.
Materials and Methods: The method of investigation is bibliometric. The sample comprises 8494 publications in the area of social medicine between 2002 and 2021 in the Web of science database. The drawing of the scientific collaboration network of researchers, organisations and countries, and the analysis of the words network of co-occurrence, was made using the bibliometric software Vosviewer.
Results: The publication process of social medicine documents in the target period is increasing. Research articles had the highest number of documents frequency and review articles received the most citations. The United States had the most published literature in this area, and most authors and organizations were from that country. The degrees of two countries, Canada and Australia, had the most citations per documents, and the five countries of South Africa, Portugal, Pakistan, India, and Iran were emerging players in this field. The network of words co-occurrence of social medicine in three groups was devoted to “preventive research in social medicine”, “social determinants of health” and “healthy lifestyle, nutrition and physical activity”. In terms of temporal occurrence, the five keywords public health, mental health, social medicine, meta-analysis and epidemiology were emerging subjects in the area of social medicine.
Conclusion: Understanding impact of non-clinical studies of social medicine on people’s lives has led to an increase in research in this field. In addition to the traditional role of developed countries, some developing countries are also new players in this field and seeking to develop their infrastructure in social medicine.
Materials and Methods: The method of investigation is bibliometric. The sample comprises 8494 publications in the area of social medicine between 2002 and 2021 in the Web of science database. The drawing of the scientific collaboration network of researchers, organisations and countries, and the analysis of the words network of co-occurrence, was made using the bibliometric software Vosviewer.
Results: The publication process of social medicine documents in the target period is increasing. Research articles had the highest number of documents frequency and review articles received the most citations. The United States had the most published literature in this area, and most authors and organizations were from that country. The degrees of two countries, Canada and Australia, had the most citations per documents, and the five countries of South Africa, Portugal, Pakistan, India, and Iran were emerging players in this field. The network of words co-occurrence of social medicine in three groups was devoted to “preventive research in social medicine”, “social determinants of health” and “healthy lifestyle, nutrition and physical activity”. In terms of temporal occurrence, the five keywords public health, mental health, social medicine, meta-analysis and epidemiology were emerging subjects in the area of social medicine.
Conclusion: Understanding impact of non-clinical studies of social medicine on people’s lives has led to an increase in research in this field. In addition to the traditional role of developed countries, some developing countries are also new players in this field and seeking to develop their infrastructure in social medicine.
Shima Derakhshan, Negar Yavari Tehrani Fard, Nahid Abotalbe, Maryam Naseroleslami,
Volume 17, Issue 2 (5-2023)
Volume 17, Issue 2 (5-2023)
Abstract
Background and Aim: Today, natural compounds such as peptides and probiotics can be mentioned as a supplement to the treatment of diseases such as cancer. These compounds may be effective in preventing the progression or treatment of cancer by affecting some molecular pathways including inflammation. The aim of this study was to investigate the effect of D-peptide-B and B.bifidum probiotic lysate on the expression of TNF-α and IL-1 genes in gastric cancer cells of AGS cell line.
Materials and Methods: In this study, AGS and HEK cells were cultured in DMEM medium with 10% bovine serum. The cells were treated with different concentrations of D-peptide-B and B.bifidum lysate and were incubated for 24 hours. The cell viability was checked by MTT. For molecular investigations, after RNA extraction and cDNA synthesis, the relative expression of TNF-α and IL-1 genes was evaluated using Real time PCR, and the data were analyzed using statistical methods One-way ANOVA.
Results: The MTT results indicated that the AGS cancer cells’ survival rate decreased after treatment with dipeptide-B and lysate of B.bifidum as compared to HEK control cells. Furthermore, the study found that the expression levels of TNF-α and IL-1 genes in gastric cancer cells were significantly higher after treatment with D-Peptide-B, bacterial lysate, or both, when compared to normal HEK cells (P≤0.05). Specifically, the IL-1 gene expression increased by 300% (4 times) for peptide treatment, 100% (2 times) for bacterial treatment, and 650% (7.5 times) for combined treatment. Similarly, the TNF-α gene expression increased by 350% for peptide treatment, 100% for bacterial treatment, and 520% for combined treatment. These results suggest that these compounds may have induced cell death in cancer cells by affecting other molecular pathways.
Conclusion: Considering that D-peptide-B and B.bifidum lysate had no significant toxicity on normal cells and caused a significant decrease in the survival of cancer cells and this toxicity was dose dependent, therefore, consideration might be given to these natural compounds in treatment of gastric cancer.
Materials and Methods: In this study, AGS and HEK cells were cultured in DMEM medium with 10% bovine serum. The cells were treated with different concentrations of D-peptide-B and B.bifidum lysate and were incubated for 24 hours. The cell viability was checked by MTT. For molecular investigations, after RNA extraction and cDNA synthesis, the relative expression of TNF-α and IL-1 genes was evaluated using Real time PCR, and the data were analyzed using statistical methods One-way ANOVA.
Results: The MTT results indicated that the AGS cancer cells’ survival rate decreased after treatment with dipeptide-B and lysate of B.bifidum as compared to HEK control cells. Furthermore, the study found that the expression levels of TNF-α and IL-1 genes in gastric cancer cells were significantly higher after treatment with D-Peptide-B, bacterial lysate, or both, when compared to normal HEK cells (P≤0.05). Specifically, the IL-1 gene expression increased by 300% (4 times) for peptide treatment, 100% (2 times) for bacterial treatment, and 650% (7.5 times) for combined treatment. Similarly, the TNF-α gene expression increased by 350% for peptide treatment, 100% for bacterial treatment, and 520% for combined treatment. These results suggest that these compounds may have induced cell death in cancer cells by affecting other molecular pathways.
Conclusion: Considering that D-peptide-B and B.bifidum lysate had no significant toxicity on normal cells and caused a significant decrease in the survival of cancer cells and this toxicity was dose dependent, therefore, consideration might be given to these natural compounds in treatment of gastric cancer.
Shima Moradi, Fatemeh Rezaei Zadeh, Monireh Rahimkhani,
Volume 17, Issue 4 (10-2023)
Volume 17, Issue 4 (10-2023)
Abstract
Background and aim: This study aimed to determine the position of Iran in terms of scientific publications in Immunology and Microbiology, and also to identify the general status of science production and the patterns of publishing in the world, the Middle East, and Iran, analyze Iran scientific collaboration with the Middle East and the world, and explore the relationship between these indicators.
Materials and Methods: The study population contained 30622 Middle Eastern publications in Immunology and Microbiology from 2009 to 2018. Positioning the countries and exploring the relations of indicators, the exploratory factor analysis, and the correlation matrix were conducted using Scival.
Results: According to the findings Iran, Turkey, and Saudi Arabia were among the most powerful countries in the region in terms of publication, citation, regional, international, and overall scientific collaboration. As for regional positioning, the citations had the highest weight comparing to other indicators. Iran have the first rank in the indices of scientific production and citations with 43.63% and 33.76% respectively, third rank in the regional cooperation index with 43.63%, second rank in the extra-regional cooperation index with 23.56%, and also second rank in the total cooperation index with 22.12%.
Conclusion: The indicators were strongly connected togather; however, the citations and international scientific collaborations displayed the strongest amongst others. Despite Iran’s prominent position in both fields, the quality of the publication was lower than the regional and global average. This identified the most powerful and weak countries in the region in regards to scientific capacities in Immunology and Microbiology. Moreover, it reckoned that there was a strong relation between citations and scientific production in contrast with others.
Sara Hashemi, Shahla Faramarzi, Laya Rahmani Pirouz, Azita Yazdani,
Volume 18, Issue 2 (5-2024)
Volume 18, Issue 2 (5-2024)
Abstract
Background and Aim: Burn injury are one of the most common traumas worldwide and the sixth leading cause of death in Iran. The challenges related to the survival rate of burn patients, as well as the associated mortality cases, have led to advancements in the identification of risk factors. Early detection and recognition of these risk factors are essential, and the provision of predictive models can be beneficial. This research was conducted with the aim of reviewing the effectiveness of artificial intelligence in predicting survival in burn patients.
Materials and Methods: This study was a systematic review. A comprehensive search of Scopus, PubMed, IEEE, and Web of Science databases was conducted from inception to July 2023 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Keywords and Mesh terms related to burn, artificial intelligence, survival and prediction were used in the search.
Results: Out of 3599 identified studies, only nine were included in the analysis. Based on the articles reviewed, the effective factors in predicting survival or mortality in burn patients were classified into four main categories: demographic, clinical, tests and co-morbidities. Some of the known effective factors in patient survival, which have been examined in over 40% of studies, include age, gender, total body surface area, inhalation injury, and type of burn. The results showed that in the studies reviewed, the volume of the smallest dataset used in the analyses was 92 samples. In contrast, the volume of the largest dataset used was reported to be 66,611 samples. Among these studies, 33% have indicated that artificial neural network algorithms and random forest show the best performance. The criteria used to evaluate the models in the retrieved studies are diverse.
Conclusion: The use of machine learning algorithms in predicting the survival of burn patients is promising. The results obtained from identified influential factors can assist data science researchers in the data understanding phase and can serve as a roadmap in collecting the initial dataset.
Materials and Methods: This study was a systematic review. A comprehensive search of Scopus, PubMed, IEEE, and Web of Science databases was conducted from inception to July 2023 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Keywords and Mesh terms related to burn, artificial intelligence, survival and prediction were used in the search.
Results: Out of 3599 identified studies, only nine were included in the analysis. Based on the articles reviewed, the effective factors in predicting survival or mortality in burn patients were classified into four main categories: demographic, clinical, tests and co-morbidities. Some of the known effective factors in patient survival, which have been examined in over 40% of studies, include age, gender, total body surface area, inhalation injury, and type of burn. The results showed that in the studies reviewed, the volume of the smallest dataset used in the analyses was 92 samples. In contrast, the volume of the largest dataset used was reported to be 66,611 samples. Among these studies, 33% have indicated that artificial neural network algorithms and random forest show the best performance. The criteria used to evaluate the models in the retrieved studies are diverse.
Conclusion: The use of machine learning algorithms in predicting the survival of burn patients is promising. The results obtained from identified influential factors can assist data science researchers in the data understanding phase and can serve as a roadmap in collecting the initial dataset.
Fahimeh Mohammadi, Maryam Shekofteh, Maryam Kazerani,
Volume 18, Issue 3 (7-2024)
Volume 18, Issue 3 (7-2024)
Abstract
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.
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.
Zahra Karbasi, Michaeel Motaghi Niko, Maryam Zahmatkeshan,
Volume 18, Issue 3 (7-2024)
Volume 18, Issue 3 (7-2024)
Abstract
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.
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.
Mazyar Karamali, Azadeh Soleimaninejad, Peirhossein Kolivand, Reza Dehkhodaei,
Volume 18, Issue 4 (10-2024)
Volume 18, Issue 4 (10-2024)
Abstract
Background and Aim: The Iranian Red Crescent Society (IRCS) is recognized as one of the ten most powerful national societies among the Red Cross and Red Crescent societies globally in responding to disasters and emergencies. The purpose of this study is to outline the research topics of the Iranian Red Crescent Society by analyzing its scientific outputs over the past years.
Materials and Methods: The research is of an applied type with a scientometric approach and bibliometric analysis, which uses event network visualization techniques and synonym analysis. The statistical population of the study included all research conducted by the Iranian Red Crescent Society and articles indexed in the Scopus database since the 1990s. The synonym analysis of research titles conducted in the organization and article abstract information and data visualization techniques were used with VOSviewer, NVIVO, WordCloud and iThoughts software.
Results: The trend of publishing research outputs has been upward. Analysis of outputs showed that Shiraz University of Medical Sciences had the highest output and the Gastroenterology and Liver Research Center and Isfahan University of Medical Sciences had the lowest output among the 10 most active institutions. Also, the Iranian Red Crescent Medical Journal had the highest output, and among the topics related to outputs, the field of medicine was ranked first and the field of Multidisciplinary was ranked lowest. Among the frequently used words, “human” was ranked first. Identifying and drawing a map of research issues for this organization showed that the problem-oriented research topics of the Red Crescent Society were categorized into nine main areas, among which relief and rescue was ranked first with 21.4% and technology and innovation was ranked lowest with 4.6%.
Conclusion: The study of the scientific and research outputs of the Iranian Red Crescent indicates the breadth and diversity of research issues in the subject areas raised. The status of research conducted in the map of Iranian Red Crescent issues by comparing the keywords showed that the research performance of this organization is higher in the fields of health services, relief and rescue, and education. Given the breadth of issues commensurate with its missions, it needs balanced growth in research and knowledge production in other areas.
Materials and Methods: The research is of an applied type with a scientometric approach and bibliometric analysis, which uses event network visualization techniques and synonym analysis. The statistical population of the study included all research conducted by the Iranian Red Crescent Society and articles indexed in the Scopus database since the 1990s. The synonym analysis of research titles conducted in the organization and article abstract information and data visualization techniques were used with VOSviewer, NVIVO, WordCloud and iThoughts software.
Results: The trend of publishing research outputs has been upward. Analysis of outputs showed that Shiraz University of Medical Sciences had the highest output and the Gastroenterology and Liver Research Center and Isfahan University of Medical Sciences had the lowest output among the 10 most active institutions. Also, the Iranian Red Crescent Medical Journal had the highest output, and among the topics related to outputs, the field of medicine was ranked first and the field of Multidisciplinary was ranked lowest. Among the frequently used words, “human” was ranked first. Identifying and drawing a map of research issues for this organization showed that the problem-oriented research topics of the Red Crescent Society were categorized into nine main areas, among which relief and rescue was ranked first with 21.4% and technology and innovation was ranked lowest with 4.6%.
Conclusion: The study of the scientific and research outputs of the Iranian Red Crescent indicates the breadth and diversity of research issues in the subject areas raised. The status of research conducted in the map of Iranian Red Crescent issues by comparing the keywords showed that the research performance of this organization is higher in the fields of health services, relief and rescue, and education. Given the breadth of issues commensurate with its missions, it needs balanced growth in research and knowledge production in other areas.
Zohre Abbaszade Molaei, Aeen Mohammadi, Manijeh Hooshmandja,
Volume 18, Issue 5 (11-2024)
Volume 18, Issue 5 (11-2024)
Abstract
Background and Aim: With the advancement of information technology in the new century, changes are experienced in all aspects of life. One of the reflections of these changes in education is conducting exams electronically instead of paper-and-pencil examinations. The success of virtual education is not achievable without considering the students’ viewpoints towards it. This study aimed to investigate the attitude and performance of students in online exams and their relationship with academic achievement.
Materials and Methods: This research is a mixed-method study (qualitative-quantitative). First, all related articles published, between 2000 to 2022, were extracted from ERIC, PubMed, ScienceDirect databases, and the Google Scholar search engine. Then, the attitude and performance questionnaire was designed and validated based on the literature review results. All BSc and MSc. nursing and midwifery students of Sarivar Nassibeh School filled out the questionnaire. Two hundred and five questionnaires were analyzed with SPSS using descriptive (mean and standard deviation) and inferential (t-test) statistics.
Results: Based on a content analysis of 15 selected articles, the extracted components were structured into 12 items. A preliminary questionnaire was designed with 28 questions across these 12 extracted components. Face validity was assessed using expert opinions, and necessary revisions were made. Both the Content Validity Index (CVI) and Content Validity Ratio (CVR) coefficients were employed for content validity. The final questionnaire comprised 22 items using a five-point Likert scale, ranging from strongly agree (score 5) to strongly disagree (score 1), with an internal consistency of 0.69. Exploratory factor analysis revealed that the questionnaire has six factors: “validity and accuracy”, “technical problems”, “types of questions and announcing the results”, “technique and simplicity”, “motivation and anxiety”, and “speed and error recording” that explain 60.88 percent of the total variance. Correlation results indicated no relationship between students’ attitudes and performance toward electronic examinations and academic achievement (r = 0.055, P-value = 0.432). There was a significant difference between male and female groups, BSc. and MSc. nursing and midwifery students, and semester of study.
Conclusion: The tool for measuring students’ attitudes and performance towards electronic exams has acceptable validity and reliability. This tool can be used to assess online exams and improvement plans.
Materials and Methods: This research is a mixed-method study (qualitative-quantitative). First, all related articles published, between 2000 to 2022, were extracted from ERIC, PubMed, ScienceDirect databases, and the Google Scholar search engine. Then, the attitude and performance questionnaire was designed and validated based on the literature review results. All BSc and MSc. nursing and midwifery students of Sarivar Nassibeh School filled out the questionnaire. Two hundred and five questionnaires were analyzed with SPSS using descriptive (mean and standard deviation) and inferential (t-test) statistics.
Results: Based on a content analysis of 15 selected articles, the extracted components were structured into 12 items. A preliminary questionnaire was designed with 28 questions across these 12 extracted components. Face validity was assessed using expert opinions, and necessary revisions were made. Both the Content Validity Index (CVI) and Content Validity Ratio (CVR) coefficients were employed for content validity. The final questionnaire comprised 22 items using a five-point Likert scale, ranging from strongly agree (score 5) to strongly disagree (score 1), with an internal consistency of 0.69. Exploratory factor analysis revealed that the questionnaire has six factors: “validity and accuracy”, “technical problems”, “types of questions and announcing the results”, “technique and simplicity”, “motivation and anxiety”, and “speed and error recording” that explain 60.88 percent of the total variance. Correlation results indicated no relationship between students’ attitudes and performance toward electronic examinations and academic achievement (r = 0.055, P-value = 0.432). There was a significant difference between male and female groups, BSc. and MSc. nursing and midwifery students, and semester of study.
Conclusion: The tool for measuring students’ attitudes and performance towards electronic exams has acceptable validity and reliability. This tool can be used to assess online exams and improvement plans.
Zohreh Ehteshami, Azam Shahbodaghi, Mohammad Javad Mansourzadeh,
Volume 18, Issue 5 (11-2024)
Volume 18, Issue 5 (11-2024)
Abstract
Background and Aim: An efficient data librarian equipped with the necessary competencies and capabilities is one of the most crucial elements in managing research data. The aim of this study is to identify the expected competencies and capabilities for data librarians in research data management according Harvard Biomedical Data Life Cycle.
Materials and Methods: This study is a scoping review, utilizing the Harvard Biomedical Data Lifecycle model to systematically present the findings. To retrieve relevant literature, a search strategy was employed using related keywords in databases such as Scopus, PubMed, Web of Science, Google scholar and other reputable domestic databases, over the past five years. The research population comprised original research articles published in Persian and English that addressed the expected skills and capabilities for data librarians in managing research data.
Results: Out of 5064 documents found, 196 were selected for full-text review. After reviewing the full texts, 17 studies were included in the research. In total, 92 competencies and capabilities were identified across 23 processes within the 7 stages of the Harvard Biomedical Data Lifecycle: 16 in the first stage, 16 in the second stage, 7 in the third stage, 15 in the fourth and fifth stages, 12 in the sixth stage, 8 in the seventh stage, and 18 general competencies and capabilities. According to the findings, the most studies focused on the competencies and capabilities required for the second stage, “Collection and Creation,” while the fewest studies addressed the seventh stage, “Publish and Reuse.” No studies mentioned competencies and capabilities for the processes “Image Management” in the third stage and “Preprints and Publishing” in the seventh stage.
Conclusion: The results of this study indicate that among the various stages of the data lifecycle, the “Collection and Creation” stage received the most attention. Additionally, data librarians should possess not only specialized and professional skills but also general competencies and capabilities. It is recommended that the findings of this research be considered for designing short-term and long-term educational programs to train data librarians for research data managenet.
Materials and Methods: This study is a scoping review, utilizing the Harvard Biomedical Data Lifecycle model to systematically present the findings. To retrieve relevant literature, a search strategy was employed using related keywords in databases such as Scopus, PubMed, Web of Science, Google scholar and other reputable domestic databases, over the past five years. The research population comprised original research articles published in Persian and English that addressed the expected skills and capabilities for data librarians in managing research data.
Results: Out of 5064 documents found, 196 were selected for full-text review. After reviewing the full texts, 17 studies were included in the research. In total, 92 competencies and capabilities were identified across 23 processes within the 7 stages of the Harvard Biomedical Data Lifecycle: 16 in the first stage, 16 in the second stage, 7 in the third stage, 15 in the fourth and fifth stages, 12 in the sixth stage, 8 in the seventh stage, and 18 general competencies and capabilities. According to the findings, the most studies focused on the competencies and capabilities required for the second stage, “Collection and Creation,” while the fewest studies addressed the seventh stage, “Publish and Reuse.” No studies mentioned competencies and capabilities for the processes “Image Management” in the third stage and “Preprints and Publishing” in the seventh stage.
Conclusion: The results of this study indicate that among the various stages of the data lifecycle, the “Collection and Creation” stage received the most attention. Additionally, data librarians should possess not only specialized and professional skills but also general competencies and capabilities. It is recommended that the findings of this research be considered for designing short-term and long-term educational programs to train data librarians for research data managenet.
Najmeh Nazeri, Ali Shabani, Alireza Noruzi, Mostafa Hossini Golkar,
Volume 18, Issue 6 (2-2025)
Volume 18, Issue 6 (2-2025)
Abstract
Background and Aim: One of the pillars of scientific authority is the creation of a process for accessing information, referencing, and applying knowledge. The presence of strong information centers is considered a requirement for supporting this authority. Given the uncertainties of the future, there are various scenarios for accessing information in Iran, each of which requires appropriate measures for the effective application of knowledge. This research aims to understand the needs and requirements of the country’s information sector to achieve scientific authority.
Materials and Methods: Using futures studies methodologies and a combination of quantitative and qualitative methods, the indicators of information centers were first identified. Then, based on expert opinions, measures to achieve scientific authority were determined. The expert panel was purposefully selected from specialists with at least 10 years of experience in relevant fields. Validation of the scenarios and consensus-building were accomplished using an expert panel and focus group.
Results: A conceptual model was identified, comprising five components and 26 factors, which were prioritized based on 10 key drivers. Two critical uncertainties-access and information management, as well as the completion of the information cycle, led to the development of three scenarios: traditional, monopolistic, and democratic. Furthermore, indicators related to scientific authority were estimated based on expert opinions for a ten-year horizon within each scenario. The findings indicated that there was less differentiation among scenarios in the indicators of knowledge exchange and transfer, whereas greater differentiation was observed in the indicators of translation, outsourcing, and knowledge utilization. This highlights the necessity of directing effectiveness toward utility. These changes in the layers of processes and value creation in scientific authority could be traced.
Conclusion: According to the experts’ assessment of the indicators, in the knowledge exploitation stage of the traditional and exclusive scenarios, access to information in the components of knowledge exchange and transfer will not be adequately established. Therefore, to implement knowledge application, the presence of processes for support, promote, and facilitate scientific interaction will play a significant role in establishing scientific authority. Although the dominance of the view of knowledge as power and information as a source of power is expected to continue in the medium term, achieving scientific authority requires a transition to perspectives that offer greater support and provide a better platform for the formation of the information cycle and its broader distribution.
Materials and Methods: Using futures studies methodologies and a combination of quantitative and qualitative methods, the indicators of information centers were first identified. Then, based on expert opinions, measures to achieve scientific authority were determined. The expert panel was purposefully selected from specialists with at least 10 years of experience in relevant fields. Validation of the scenarios and consensus-building were accomplished using an expert panel and focus group.
Results: A conceptual model was identified, comprising five components and 26 factors, which were prioritized based on 10 key drivers. Two critical uncertainties-access and information management, as well as the completion of the information cycle, led to the development of three scenarios: traditional, monopolistic, and democratic. Furthermore, indicators related to scientific authority were estimated based on expert opinions for a ten-year horizon within each scenario. The findings indicated that there was less differentiation among scenarios in the indicators of knowledge exchange and transfer, whereas greater differentiation was observed in the indicators of translation, outsourcing, and knowledge utilization. This highlights the necessity of directing effectiveness toward utility. These changes in the layers of processes and value creation in scientific authority could be traced.
Conclusion: According to the experts’ assessment of the indicators, in the knowledge exploitation stage of the traditional and exclusive scenarios, access to information in the components of knowledge exchange and transfer will not be adequately established. Therefore, to implement knowledge application, the presence of processes for support, promote, and facilitate scientific interaction will play a significant role in establishing scientific authority. Although the dominance of the view of knowledge as power and information as a source of power is expected to continue in the medium term, achieving scientific authority requires a transition to perspectives that offer greater support and provide a better platform for the formation of the information cycle and its broader distribution.
Meisam Dastani, Narjes Bahri, Mehdi Moshki,
Volume 19, Issue 1 (4-2025)
Volume 19, Issue 1 (4-2025)
Abstract
Background and Aim: The Social Determinants of Health Research Centers in Iran utilize existing capacities to conduct research aimed at identifying and implementing effective methods to reduce social health inequalities. Therefore, this study analyzes the scientific publications of these centers using Bibliomerix tools.
Materials and Methods: This descriptive study employs a bibliometric aimed to analyze approach. The study population consisted of all scientific documents produced by the Social Determinants of Health Research Centers in Iran, ind in the Scopus database up to the end of 2023. Data analysis was conducted using the Bibliometrix package in the R programming language.
Results: The results revealed that Iranian Social Determinants of Health Research Centers have produced 8,358 scientific publications. The publication trend began in 2010, peaking in 2022. Original research articles (7,197 documents) constituted the majority of publications. The journals Health Education and Health Promotion, Medical Journal of the Islamic Republic of Iran, and Koomesh published the highest number of articles. Tehran University of Medical Sciences (1505 documents), Shahid Beheshti University of Medical Sciences (1080 documents), and Tabriz University of Medical Sciences (955 documents) were the leading institutions. Inter-institutional collaborations highlighted the pivotal role of Tehran University. International collaborations were primarily with United States, United Kingdom, and Australia. Key keywords included COVID-19, quality of life, and prevalence. Research themes focused on mental health, women, obesity, and diabetes, expanding in 2023–2024 toward primary healthcare and vulnerable populations.
Conclusion: The findings of this study indicate that research centers focusing on social determinants of health in Iran have experienced a growing trend in scientific production and the expansion of their research domains. This progress is evident not only in the increasing number of scientific publications but also in the shift of research approaches from focusing on specific diseases to broader issues such as health policy, mental health, and social health inequalities. These findings may serve of this study can serve as a valuable guide for policymakers and researchers in setting research priorities in the field of social determinants of health.
Materials and Methods: This descriptive study employs a bibliometric aimed to analyze approach. The study population consisted of all scientific documents produced by the Social Determinants of Health Research Centers in Iran, ind in the Scopus database up to the end of 2023. Data analysis was conducted using the Bibliometrix package in the R programming language.
Results: The results revealed that Iranian Social Determinants of Health Research Centers have produced 8,358 scientific publications. The publication trend began in 2010, peaking in 2022. Original research articles (7,197 documents) constituted the majority of publications. The journals Health Education and Health Promotion, Medical Journal of the Islamic Republic of Iran, and Koomesh published the highest number of articles. Tehran University of Medical Sciences (1505 documents), Shahid Beheshti University of Medical Sciences (1080 documents), and Tabriz University of Medical Sciences (955 documents) were the leading institutions. Inter-institutional collaborations highlighted the pivotal role of Tehran University. International collaborations were primarily with United States, United Kingdom, and Australia. Key keywords included COVID-19, quality of life, and prevalence. Research themes focused on mental health, women, obesity, and diabetes, expanding in 2023–2024 toward primary healthcare and vulnerable populations.
Conclusion: The findings of this study indicate that research centers focusing on social determinants of health in Iran have experienced a growing trend in scientific production and the expansion of their research domains. This progress is evident not only in the increasing number of scientific publications but also in the shift of research approaches from focusing on specific diseases to broader issues such as health policy, mental health, and social health inequalities. These findings may serve of this study can serve as a valuable guide for policymakers and researchers in setting research priorities in the field of social determinants of health.
Mozhgan Farazmand, Mandana Asgari, Hamid Bouraghi, Taleb Khodaveisi, Ali Mohammadpour, Soheila Saeedi,
Volume 19, Issue 3 (9-2025)
Volume 19, Issue 3 (9-2025)
Abstract
Background and Aim: Cardiovascular diseases have a very high prevalence globally and are recognized as one of the main causes of mortality worldwide. Artificial intelligence, as a novel technology, has garnered attention in recent years in Iran and other parts of the world for the management of a wide variety of diseases. The present study aimed to systematically review research studies conducted in the field of applying artificial intelligence in cardiovascular diseases.
Materials and Methods: To investigate research studies conducted in the field of cardiovascular diseases utilizing artificial intelligence, the Persian language databases SID, Google Scholar, and Magiran were searched. This search was conducted without time limitations on April 3, 2024 and included all research studies that, up to this date, had used various artificial intelligence methods in the field of cardiovascular diseases in the present systematic review.
Results: The results of the search in the aforementioned three databases led to the retrieval of 17,819 research studies, of which 46 research studies met the inclusion and exclusion criteria of the study. These research studies had used artificial intelligence in three areas: prediction, treatment, and diagnosis. Neural networks (n=22), support vector machines (n=20), and decision trees (n=16) were the algorithms that were used more than other techniques. The data sources of the included research studies were mainly patient medical records and the UCI database. Additionally, MATLAB software was used more than other software. The most frequently mentioned limitations in the research studies included not considering all factors, limited access to data, insufficient data, the presence of noise in signals or images, and the presence of outliers, missing values, and non-normality of data.
Conclusion: The systematic review of research studies conducted in the field of cardiovascular diseases utilizing artificial intelligence showed that this technology has been used in a wide range of cardiovascular diseases, and most of the conducted research studies confirmed its effectiveness and successful performance.
Materials and Methods: To investigate research studies conducted in the field of cardiovascular diseases utilizing artificial intelligence, the Persian language databases SID, Google Scholar, and Magiran were searched. This search was conducted without time limitations on April 3, 2024 and included all research studies that, up to this date, had used various artificial intelligence methods in the field of cardiovascular diseases in the present systematic review.
Results: The results of the search in the aforementioned three databases led to the retrieval of 17,819 research studies, of which 46 research studies met the inclusion and exclusion criteria of the study. These research studies had used artificial intelligence in three areas: prediction, treatment, and diagnosis. Neural networks (n=22), support vector machines (n=20), and decision trees (n=16) were the algorithms that were used more than other techniques. The data sources of the included research studies were mainly patient medical records and the UCI database. Additionally, MATLAB software was used more than other software. The most frequently mentioned limitations in the research studies included not considering all factors, limited access to data, insufficient data, the presence of noise in signals or images, and the presence of outliers, missing values, and non-normality of data.
Conclusion: The systematic review of research studies conducted in the field of cardiovascular diseases utilizing artificial intelligence showed that this technology has been used in a wide range of cardiovascular diseases, and most of the conducted research studies confirmed its effectiveness and successful performance.
Abdolahad Nabiolahi, Nasser Keikha,
Volume 19, Issue 4 (11-2025)
Volume 19, Issue 4 (11-2025)
Abstract
Background and Aim: Point of Care Tests (POCTs) are a laboratory diagnostic system that can be performed at the patient care location and help diagnose diseases quickly. Due to the increase in population, the prevalence of contagious diseases, none access of society members to laboratories, the global need for the availability of modern diagnostic and health technologies at the place of patient care, the aim of research was to explore new aspects of the application of Point of Care Tests to patients as well as the process of developing these technologies in the field of healthcare.
Materials and Methods: A scoping review method were applied by determining the key words through medical subject headings and related articles, searching in the databases of Web of Science, Scopus and PubMed databases as well as Google Scholar, Google and Magiran and Scientific information database. Furthermore to preserve the variety of sources and articles, the criteria for entering the study were English-language articles and no time limit was applied.
Results: Most of the 17 related articles were reviews. The most common technologies in POCTs were lateral flow assays (LFA) that applied to diagnosis of Cryptococcus fungal infection, tuberculosis, hepatitis, legionella, malaria and covid-19, and nucleic acid amplification tests have helped to detect viruses and bacteria using DNA and RNA. From NAAT (Nucleic Acid Amplification Tests) based on microsialate, it can be referred to RT-PCR (Reverse transcription- polymerase chain reactio) and LAMP oop-Mediated- Isothermal Amplification (LAMP), where in recent years are widely used for detection of infectious diseases specially SARS-CoV-19. Additional basic diagnostic tools have focused on Small handheld, POCT devices with a monitoring device, cartridge, and other devices; whereas in the new generations, special focus were on quality assurance, microfluidics, Nano-biosensors and smart phones.
Conclusion: The analysis of published studies showed that the diagnostic tools of tests on POCTs are expanding and have been able to provide better clinical and economic results. In addition to the extensive use of two advanced types of lateral flow assays and nucleic acid amplification tests to diagnose tests at the patient’s bedside; Microfluidics, Nano biosensors and smart phones have also expanded. Quality assurance also requires the determination of accurate quality management procedures, policy programming and necessary policy formulation by officials to achieve reliable results for patient care.
Materials and Methods: A scoping review method were applied by determining the key words through medical subject headings and related articles, searching in the databases of Web of Science, Scopus and PubMed databases as well as Google Scholar, Google and Magiran and Scientific information database. Furthermore to preserve the variety of sources and articles, the criteria for entering the study were English-language articles and no time limit was applied.
Results: Most of the 17 related articles were reviews. The most common technologies in POCTs were lateral flow assays (LFA) that applied to diagnosis of Cryptococcus fungal infection, tuberculosis, hepatitis, legionella, malaria and covid-19, and nucleic acid amplification tests have helped to detect viruses and bacteria using DNA and RNA. From NAAT (Nucleic Acid Amplification Tests) based on microsialate, it can be referred to RT-PCR (Reverse transcription- polymerase chain reactio) and LAMP oop-Mediated- Isothermal Amplification (LAMP), where in recent years are widely used for detection of infectious diseases specially SARS-CoV-19. Additional basic diagnostic tools have focused on Small handheld, POCT devices with a monitoring device, cartridge, and other devices; whereas in the new generations, special focus were on quality assurance, microfluidics, Nano-biosensors and smart phones.
Conclusion: The analysis of published studies showed that the diagnostic tools of tests on POCTs are expanding and have been able to provide better clinical and economic results. In addition to the extensive use of two advanced types of lateral flow assays and nucleic acid amplification tests to diagnose tests at the patient’s bedside; Microfluidics, Nano biosensors and smart phones have also expanded. Quality assurance also requires the determination of accurate quality management procedures, policy programming and necessary policy formulation by officials to achieve reliable results for patient care.
Pezhman Sadeghi, Nader Jahanmehr, Reza Rabiei,
Volume 19, Issue 5 (12-2025)
Volume 19, Issue 5 (12-2025)
Abstract
Background and Aim: Information systems serve different purposes in organizational and management hierarchies. The hospital intelligent management system is an analytical and decision-support management information system that provides information and important performance indicators for managers in hospitals. Considering the role of this system in increasing the efficiency and effectiveness and the lack of academic hospitals having the desired level of productivity, this research was conducted to investigate the effective factors in improving the acceptance of the intelligent hospital management system in the hospitals of Shahid Beheshti University of Medical Sciences (SBMU).
Materials and Methods: This descriptive and correlational research was conducted in 19 hospitals (12 teaching hospitals and 7 non-teaching hospitals) of Shahid Beheshti University of Medical Sciences in 2022. In this study, 126 senior and middle managers and experts of the productivity committee participated. The data of this study were collected Using the Unified Theory of Acceptance and Use of Technology(UTAUT) Questionnaire and for statistical analysis, SPSS software (statistical table and linear and multiple regression tests, sequencing, and chi-square) was used. The validity of the questionnaire was determined using the opinion of research experts and its reliability was also determined using Cronbach’s alpha coefficient (0.824).
Results: Most of the participants in the study were from teaching hospitals (63.2%) and were middle managers (50.8%). Behavioral intentions were identified as the most important factors in the use of system by senior and middle managers and experts of productivity committee (P<0.001). The effort expectancy had the greatest impact on the intention to use the system as compared to the expected components of Performance expectancy and social influence. Also, training and having educational programs on how to use the HIM and its applications can increase the intention and use of the HIM by employees (P<0.001).
Conclusion: Based on the results, the effect of the moderating variables in this study was insignificant. If senior managers and influential people encourage working with the system, and employees also make more effort to learn the system, and working with the system meets their expectations, employees will be willing to use the system. In other words, employees use the system when they believe that this system is user-friendly, valuable, and useful for them.
Materials and Methods: This descriptive and correlational research was conducted in 19 hospitals (12 teaching hospitals and 7 non-teaching hospitals) of Shahid Beheshti University of Medical Sciences in 2022. In this study, 126 senior and middle managers and experts of the productivity committee participated. The data of this study were collected Using the Unified Theory of Acceptance and Use of Technology(UTAUT) Questionnaire and for statistical analysis, SPSS software (statistical table and linear and multiple regression tests, sequencing, and chi-square) was used. The validity of the questionnaire was determined using the opinion of research experts and its reliability was also determined using Cronbach’s alpha coefficient (0.824).
Results: Most of the participants in the study were from teaching hospitals (63.2%) and were middle managers (50.8%). Behavioral intentions were identified as the most important factors in the use of system by senior and middle managers and experts of productivity committee (P<0.001). The effort expectancy had the greatest impact on the intention to use the system as compared to the expected components of Performance expectancy and social influence. Also, training and having educational programs on how to use the HIM and its applications can increase the intention and use of the HIM by employees (P<0.001).
Conclusion: Based on the results, the effect of the moderating variables in this study was insignificant. If senior managers and influential people encourage working with the system, and employees also make more effort to learn the system, and working with the system meets their expectations, employees will be willing to use the system. In other words, employees use the system when they believe that this system is user-friendly, valuable, and useful for them.
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