https://jsmj.ajums.ac.ir/ Jundishapur Scientific Medical Journal en daily 1 Wed, 21 Jan 2026 00:00:00 +0330 Wed, 21 Jan 2026 00:00:00 +0330 https://jsmj.ajums.ac.ir/article_237110.html Background and Objectives Given the highly contagious nature of the coronavirus (SARSCoV-2), dental healthcare providers are at particularly high risk of infection and transmission due to close contact with patients and the use of aerosol-generating procedures. This study aimed to assess the knowledge, attitude, and practice of dentists and dental students regarding patient evaluation and adherence to infection control principles during the COVID-19 pandemic. Subjects and Methods This descriptive cross-sectional study included 363 individuals from across the country. Data were collected using an electronic questionnaire with acceptable reliability (Cronbach's alpha > 0.7 in all dimensions). Results The findings showed that participants had an appropriate level of knowledge in various dimensions, including patient management, clinical services, and environmental engineering. There was a significant positive correlation among different questionnaire dimensions. Variables such as age, work experience, and participation in educational webinars were significantly associated with overall scores, whereas gender and educational degree showed significant differences only in certain areas, such as practice. Conclusion The results indicate that continuous education, particularly through targeted webinars, plays an important role in enhancing dentists' preparedness for future epidemiological threats. Moreover, strict adherence to protective protocols and minimizing aerosol production can help reduce the risk of transmission in dental settings. https://jsmj.ajums.ac.ir/article_237114.html Background and Objectives Artificial intelligence plays a crucial role in predicting patient conditions, optimizing drug doses, monitoring clinical status, and providing clinical decision support during anesthesia. This narrative review examines the applications of artificial intelligence in the field of anesthesia.Subjects and Methods This review article was conducted in 2023 [Solar Hijri 1402] by searching international databases, including Scopus, PubMed, IEEE Xplore, and Web of Science, as well as Iranian databases such as IranDoc and SID, for the period 2019–2024.Results The applications of artificial intelligence in anesthesia include the Infuse-OR system, which operates via magnetic coding, and Stanpump software, designed to automate the anesthetic process and reduce reliance on manual clinical intervention. Furthermore, machine learning models are utilized to determine anesthetic dosages by analyzing input datasets and patient conditions. Neural network algorithms are specifically applied for dose optimization, while Long Short-Term Memory (LSTM) networks are employed to analyze and predict anesthetic performance. For signal classification during anesthesia, a Convolutional Neural Network (CNN) architecture is utilized, consisting of an initial layer with 32 convolutional filters and max-pooling, a second convolutional layer with 32 filters followed by a secondary pooling layer, and a final fully connected layer.Conclusion Integrating artificial intelligence into anesthesia enhances the quality of medical care, improves diagnostic accuracy, and increases patient safety. However, this integration also presents several challenges such as protecting patient privacy, ensuring responsible AI decision-making, preventing discrimination, improving the transparency of algorithms, clarifying physician responsibility, and addressing the impact of artificial intelligence on the role of physicians. https://jsmj.ajums.ac.ir/article_237117.html Background and Objectives Sudden cardiac death (SCD) remains one of the leading causes of mortality worldwide. The purpose of this study is to predict SCD early and to distinguish it from congestive heart failure (CHF), which presents with similar electrocardiographic patterns. Subjects and Methods In this study, shallow and fully automated models based on convolutional neural networks (CNNs) are presented to predict SCD. In these models the electrocardiogram (ECG) signal is given as input to the model, and classification is performed at the output of the model. Results The first model, which is based on one-dimensional CNNs, could predict SCD with an accuracy of 96%. In the next step, by adding data related to CHF, an accuracy of 97.85 was obtained in the three-class classification (normal, before SCD, and CHF). In the second model, which is based on two-dimensional CNNs, first, each part of the ECG signals was converted into two-dimensional images using continuous wavelet transform (CWT) and given as input to the model. This model was able to predict SCD with 99% accuracy.Conclusion The proposed fully automated CNN-based models demonstrated high predictive accuracy for SCD within one hour before its occurrence. https://jsmj.ajums.ac.ir/article_237112.html Background and Aim: Training session frequency is a key variable in exercise program design, capable of influencing metabolic adaptations and physiological responses to exercise. This study aimed to examine the effect of weekly training frequency on fasting serum asprosin levels and insulin resistance in men with metabolic syndrome.Methods: In this semi-experimental study, 45 men with metabolic syndrome were randomly assigned to three groups: aerobic interval training three times per week, aerobic interval training six times per week, and a control group. Weekly training volume was matched between the two intervention groups, and exercise intensity was progressively adjusted. Fasting serum asprosin levels were measured using ELISA, and insulin resistance was assessed via the HOMA-IR index before and after the intervention. Statistical analysis was performed using ANCOVA.Results: Both training groups showed a significant reduction in insulin resistance and serum asprosin levels compared to the control group (P<0.01). The reduction in insulin resistance was significantly greater in the six-sessions-per-week group compared to the three-sessions-per-week group (P=0.016), while no significant difference in serum asprosin reduction was observed between the two training groups (P=0.847).Conclusion: Regular aerobic interval training, especially at higher frequencies, can improve insulin sensitivity and modulate metabolic pathways associated with asprosin. These findings suggest that adjusting training frequency may serve as a novel non-pharmacological approach to managing metabolic syndrome. https://jsmj.ajums.ac.ir/article_237115.html Background and Objectives Chronic non-specific low back pain is one of the causes of disability in individuals and chronic pain is considered one of the most important medical problems in the world. The aim of the present study was to determine the effect and durability of Pilates exercises on pain, range of motion, and proprioception in women with chronic non-specific low back pain.Subjects and Methods The present study is a quasi-experimental study. In this study, 20 women with chronic non-specific low back pain diagnosed by an orthopedic specialist were randomly and equally selected into two groups: Pilates (n=10) and control (n=10). Physical factors including pain intensity (VAS), proprioception (goniometer), reconstruction of 30 degrees of lumbar flexion angle, range of motion (Schuber), were recorded in the pre-test and post-test after eight weeks. The exercises were performed by the exercise group for 8 weeks and 3 sessions per week. Also, the retention was measured after one month. The repeated analysis of variance and Bonferroni post-hoc test were used to investigate the hypotheses. All the above analyses were performed using SPSS version 24 software (p≥0.05).Results The results of this study indicate the effect of the Pilates exercise program on pain reduction. (p=0.005), increased proprioception (p=0.005) and improved range of motion (p=0.001). In the intergroup comparison, a significant difference was observed in the range of motion variable between the control and training groups in the post-test period (p=0.002) and follow-up (p=0.001). Also, in examining the difference between the groups in the variables of pain and proprioception between the two groups in the post-test period (p=0.001) and follow-up (p=0.001), a significant difference was observed.Conclusion According to the findings of the study, Pilates exercises were effective in reducing pain, increasing proprioception, and range of motion. Therefore, it seems that the Pilates training protocol can be used as a useful method for the rehabilitation of people with chronic non-specific low back pain, and these effects were persistent after 8 weeks. https://jsmj.ajums.ac.ir/article_237111.html Background and Objectives Malaria is a parasitic disease caused by five species of Plasmodium and transmitted by Anopheles mosquitoes. Hormozgan Province is one of the endemic foci of malaria in the south of Iran. Therefore, the present study was designed to determine the epidemiology of malaria over a ten-year period in Hormozgan Province.Subjects and Methods To determine the ten-year epidemiology of malaria in Hormozgan province, data from 2012 to 2021 were collected from health centers. Information extracted from patient records included gender, age, season of illness, nationality, place of residence, year, and the diagnosed parasites. The data were analyzed using the chi-square test.Results A total of 682 malaria cases were reported. In this study, 87.8% of the patients were male and 12.2% were female. The highest numbers of cases were recorded in September, July, and August, respectively, with 45.7% of cases occurring during the summer. Most cases were observed in individuals older than 15 years. The prevalence of malaria in Jask, Bandar Abbas, and Qeshm was 23.9%, 22.3%, and 13.3%, respectively. Plasmodium vivax was the most prevalent species. In addition, 49.3% of the patients were of Pakistani nationality.Conclusion The high prevalence of patients of Pakistani and Afghan nationality highlights the need for effective decision-making and the adoption of appropriate strategies for the prevention and control of the disease and its vectors. Furthermore, the findings of this study emphasize the importance of strengthening malaria elimination programs, enhancing local surveillance and monitoring systems, educating at-risk populations, and promoting intersectoral collaboration. https://jsmj.ajums.ac.ir/article_237340.html Background and Objectives Fetuins, as liver-secreted proteins, play a significant role in regulating metabolic homeostasis, inflammation, and the progression of non-alcoholic fatty liver disease (NAFLD). This study aimed to determine the effect of CrossFit training on liver fat content, insulin sensitivity, and serum levels of C-reactive protein (CRP), Fetuin-A, and Fetuin-B in middle-aged men with NAFLD.Subjects and Methods This quasi-experimental study involved 24 men with NAFLD who were purposively selected and randomly assigned to exercise (n=12) and control (n=12) groups. The exercise group performed CrossFit training, three sessions per week continued for 12 weeks, at an intensity of 80 to 90% heart rate reserve (HRR). Blood samples were collected before and 72 hours after the last training session. Data were analyzed using ANCOVA at a significance level of P ≤ 0.05.Results After the intervention, the exercise group showed significant reductions in CRP (33.6%), Fetuin-A (12.3%), Fetuin-B (5.5%), and liver fat grade (54.2%), and a significant increase in insulin sensitivity (4.8%) was observed compared to the control group (P < 0.05).Conclusion The reduction in liver fat content and serum CRP levels appears to result from improved hepatic insulin sensitivity and decreased systemic inflammation. Furthermore, decreased Fetuin-A and Fetuin-B indicate modulation of inflammatory responses and improved liver function, which play important roles in the clinical improvement of this disease. These changes may serve as an effective non-pharmacological intervention to slow NAFLD progression and enhance metabolic health in middle-aged patients. https://jsmj.ajums.ac.ir/article_237109.html Scorpion venom is a valuable source of biologically active components which mainly are variable peptides and proteins with pharmacological potential. Therefore, identification of scorpion venom glands can introduce new potent pharmacological active components to facilitate development of new drugs. In addition, determining the envenomation factors could help to produce specific antivenoms for scorpion sting treatment. Applying new methods to identify scorpion venom compounds can increase accuracy, efficiency, and productivity. Transcriptomics and proteomics have provided a good opportunity to identification of these compounds in recent years. Transcriptomics offers detailed information about venom peptides and toxins by analyzing gene expression in the venom gland, while proteomics provides complementary and complementary data by directly identifying proteins and examining post-translational modifications (PTM). The combination of these two methods, which is known as venomics, provides an integrated view of the molecular structure and function of scorpion venom and has led to the discovery of novel bioactive molecules that can be used in the design of new drugs against a wide range of diseases such as cancers, resistant bacterial infections, and neurological disorders. This review article examines the key role of these technologies in the identification of scorpion venom compounds and discusses future prospects for pharmaceutical and biotechnological applications.