Islamic Azad University, Isfahan

Amyotrophic lateral sclerosis (ALS) is a complex neurodegenerative disease with significant challenges in diagnosis and treatment. Recent research has highlighted the complex nature of ALS, encompassing behavioral impairments in addition to its neurological manifestations. While several medications have been approved to slow disease progression, ongoing research is focused on identifying new therapeutic targets. The current review focuses on emerging therapeutic strategies and personalized approaches aimed at improving patient outcomes. Recent advancements highlight the importance of targeting additional pathways such as mitochondrial dysfunction and neuroinflammation to develop more effective treatments. Personalized medicine, including genetic testing and biomarkers, is proving valuable in stratifying patients and tailoring treatment options. Complementary therapies, such as nutritional interventions like the ketogenic diet and microbiome modulation, also show promise. This review emphasizes the need for a multidisciplinary approach that integrates early diagnosis, targeted treatments, and supportive care to address the multisystemic nature of ALS and improve the quality of life for patients.

Evaluating students' academic translations constitutes a prevalent and essential practice in the context of translator education and training. Such evaluations are typically conducted by allocating numerical scores or letter grades to ensure the congruence between the intended pedagogical objectives and the actual learning outcomes. Existing research indicates that university instructors' prevailing translation evaluation methods in undergraduate English translation programs are grounded mainly in the theoretical frameworks of the traditional testing paradigm. This article seeks to address the 'problem' inherent in evaluative practices arising from the challenges and criticisms directed towards the principles and methodologies underpinning Classical True Score Measurement Theory and the conventional testing tradition. To this end, the article first examines the current state of language assessment in general

Objective Increase in vertical marginal discrepancy (VMD) during repeated firing cycles and its clinical outcomes is a major concern for high and low translucent monolithic zirconia crowns. The purpose of this in vitro study was to evaluate and compare VMD in high and low translucent monolithic zirconia crowns in repeated firing cycles. Material and Methods To perform this study, 10 monolithic zirconia crowns made by computer-aided design and computer-aided manufacturing method were used in two groups of five with high and low translucency, which were designed on Zimmer tissue-level implant abutment. The crowns in each group were randomly numbered from 1 to 5 and each underwent 1, 3, and 5 firing cycles. After completing each mentioned cycle, the VMD was measured at eight predetermined points on abutment by optical microscope and their average was recorded for each sample. Data analysis was done by SPSS 22 software through repeated-measure analysis of variance, paired t-test, and t-test with a 5% significance threshold. Results A total of 240 measurements were made for the VMD, which, due to the presence of five samples in each translucency group and eight examined points in each sample, was finally summed up to six averages for each translucency group in the mentioned three stages of firing cycles. The averages for the low-translucency group after 1, 3, and 5 firing cycles were 76.86, 85.02, and 90.55 μm, respectively, and for the high-translucency group after 1, 3, and 5 firing cycles were 80.38, 87.33, and 97.78 μm, respectively. The average VMD of the samples regardless of the translucency level after 1, 3 and 5 firing cycles was calculated as 78.62, 86.18, and 94.16 μm, respectively. Conclusion This study found that VMD increased with repeated firing cycles, with no significant difference between high- and low-translucency zirconia crowns. Repeated firings significantly raised VMD, but all values remained within clinically acceptable limits, supporting the suitability of both translucency types for clinical use.

Water‐in‐oleogels are structured oils formed using gelators with varying gelation performance. In this study, the production of novel bigels and their consumption as a commercial shortening substitute in croissant formulation to reduce the fat and saturated fatty acid content and produce a healthier product are of concern. Water‐in‐oleogels of sunflower oil were prepared by consuming different combinations of gelators, monoglyceride, Zein protein (2.5%, 5%, and 7.5%), and Persian gum (0%, 1.5%). After assessing their thermal and rheological properties, they were substituted with shortening in the formulation of croissants to reduce fat and saturated fatty acid content. The qualitative properties of the products were assessed from different perspectives. Water‐in‐oleogels had solid, viscoelastic gel‐like structure, with pseudoplastic behavior and an increase in the Zein concentration in the presence of hydrocolloids enhanced the viscoelastic properties and melting enthalpy of created crystals in the bigel structure. The moisture content and hardness of croissants produced with water‐in‐oleogels were higher and lower, respectively, than those in the control. Using hydrocolloid next to increasing the Zein concentration decreased the oil release of the product. The croissant prepared using water‐in‐oleogel containing 2.5% Zein had the lowest density compared to the other samples. The intensity of yellowness, chroma, and browning index were higher in samples produced with water‐in‐oleogels containing low levels of gelators. The water‐in‐oleogel prepared with 2.5% Zein was useful in the production of croissants with favorable quality properties and 15% lower fat compared to the control without significant difference in terms of peroxide value. The total volume of the saturated and essential unsaturated fatty acids in the developed product decreased by 47% and increased by 65%, respectively, next to maintaining the aroma, taste, color, and most of the organoleptic properties.

AIM The purpose of the present study was to compare the effectiveness of an occupational stress training package with mindfulness-based cognitive therapy (MBCT) on job burnout of Tam Kar employees. MATERIAL AND METHODS The research method was a three-stage, three-group semiexperimental design. To this end, the statistical population including all the employees who worked in the technical departments of Tam Kar Company in Isfahan and in terms of the level of stress in middle and higher levels, using purposive sampling, 60 employees were selected and randomly divided into three groups (20 for each group). Geldard (1989) burnout inventory (GBI) was used for data collection. Experimental group 1 received eight 90-min sessions of mindfulness-based cognitive therapy training, and experimental group 2 received job stress coping training in ten 90-min sessions. Repeated measurement ANOVA was used to analyze the data with the help of a statistical software package in social sciences (SPSS) version 22. RESULTS The results showed that coping with job stress training and mindfulness-based cognitive therapy were equally effective in reducing the employees’ burnout (P ≤ 0.05) and this effect continued at follow-up. CONCLUSION Given the high prevalence of burnout and psychopathologic symptoms among industry staff, coping with job stress training and mindfulness-based cognitive therapy training can be suggested to reduce burnout syndrome in the industry.

While digitalization promotes grid management efficiency, it also makes power systems more vulnerable to a variety of anomalies, especially false data injection (FDI) anomalies. FDI intrusions pose a serious threat to the security of smart grids. The existing approaches, like machine learning, have certain limitations, which can be addressed by proposing the optimized neuro‐fuzzy meta‐learning (ONF‐ML) model. This model combines several machine learning classifiers serving as a two‐step optimization process including hyperparameter optimization for individual classifiers and simulated annealing for tuning neuro‐fuzzy parameters. Simulation results conducted on the IEEE 14‐bus system using MATPOWER demonstrate the superior performance of ONF‐ML in detecting FDI intrusions compared to baseline models, especially for subtle injections. In every bus, FDI intrusion has occurred and average performance metrics are considered. The results illustrate an average detection rate of 91.7% and 81.9% for intrusion samples and 99.9% and 99.8% for normal instances in cases of −3% and +3% occurrences, respectively. While baseline models illustrated critical performance degradation during robust analyses, this technique was remarkably stable, maintaining a detection rate of over 75%, outperforming the second‐best technique by up to 45% in worst‐case scenarios. By addressing real‐world challenges such as sensitivity to noise, inflexibility and incompetence in detecting subtle intruders, the ONF‐ML approach enables continuous learning from new data, ensuring adaptability to new threats. Taken together, these features make ONF‐ML a practical and scalable solution to overcome the limitations of traditional FDI detection techniques and provide a path to improved smart grid security.

Chitosan, a non-toxic and biodegradable compound, enhances plant growth and secondary metabolite production, presenting innovative approaches to mitigating plant stress. Salinity, a common abiotic stress, significantly impairs plant growth and development. This study investigates the effects of chitosan on the physiological, biochemical, and gene expression responses of salt-stressed Brassica napus L. exposed to NaCl concentrations of 0, 50, 100, and 150 mM. Chitosan was applied as a foliar spray at concentrations of 0, 5 and 10 mg/L. The research focuses on gene expression changes in P5CS, PIP, and PAL genes in the roots and shoots of Brassica napus, revealing notable alterations, particularly in PIP expression under saline conditions. The study also observed enhanced PAL enzyme activity, increased chlorophyll and proline levels, and changes in iron, potassium, and nitrogen content. These findings demonstrate chitosan’s potential to improve plant resilience to salt stress. By modulating gene expression and enhancing physiological responses, chitosan presents a promising solution for enhancing plant tolerance to salinity, with valuable implications for agricultural practices.

In this study, a magnetic disk was prepared using nanoparticles with a diameter of less than 15 nm. The morphological and structural characteristics of these nanoparticles were systematically examined using X‐ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and alternating force gradient magnetometry (AGFM). XRD analysis confirmed that the average diameter of the copper–magnesium ferrite nanoparticles doped with cadmium was approximately 12 nm, consistent with TEM results, which also showed uniform particle distribution and a tendency to form clusters in powdered form. AGFM measurements revealed that the magnetic property of the powder sample was 15.83 emu/g, which increased to 22.70 emu/g after compression, highlighting the influence of particle density and morphology on magnetic behaviour. Gas sensing tests demonstrated that the fabricated sensors achieved exceptional sensitivity, particularly to acetonitrile, with a maximum sensitivity of 92.3%. A hybrid deep learning model, Bi‐LSTM, was utilised to enhance the precision of gas classification. The proposed methodology was benchmarked against traditional machine learning models, including LSTM and RNN, and demonstrated superior performance. The accuracy of gas detection reached an impressive 99.89%, as validated by ROC analysis, underscoring the efficacy of the deep learning‐based approach. These findings highlight the potential of cadmium‐doped ferrite nanoparticles for high‐performance gas sensing applications, suitable for both industrial and medical uses.

The objective of this study is to assess the most commonly applied mechanical techniques with a concentration on their effects on the physical properties of cellulose micro and nanofibers from sugarcane bagasse by consuming acid and alkaline hydrolysis to remove non-cellulosic components. In this research, a sample produced at 150 °C for 1 h with a concentration of 1 M acid exhibited minimal fiber damage. X-ray diffraction (XRD) analysis confirmed accurate microcellulose extraction. Brunauer-Emmett-Teller (BET) analysis revealed a specific surface area of approximately 3 m²/g and pore sizes of approximately 13 nm, highlighting microcellulose’s structural attributes. Chemical composition analysis demonstrated an 88.7% lignin volume reduction while retaining 92.5% of extracted cellulose fibers. Furthermore, scanning electron microscopy (SEM) showed initial micrometer-scale fiber dimensions with a wide distribution of microfiber diameters. As the extraction process continued, the distribution narrowed, reducing the average microfiber diameter. Among the mechanical methods employed, the ultrasonic treatment proved the most effective in reducing microfiber diameter, with homogenization and Ultra-Turrax showing varying degrees of influence. Extended ultrasonic treatment durations efficiently disentangle and distribute microfibers throughout the composite structure, reducing microfiber diameter and enhancing uniformity. A 3-h ultrasonic exposure efficiently reduced particle size to 30 nm, establishing the optimal duration. Graphical Abstract

Background Multiple sclerosis (MS) is one of the most common reasons of neurological disabilities in young adults. The disease occurs when the immune system attacks the central nervous system and destroys the myelin of nervous cells. This results in appearing several lesions in the magnetic resonance (MR) images of patients. Accurate determination of the amount and the place of lesions can help physicians to determine the severity and progress of the disease. Method Due to the importance of this issue, this challenge has been dedicated to the segmentation and localization of lesions in MR images of patients with MS. The goal was to segment and localize the lesions in the flair MR images of patients as close as possible to the ground truth masks. Results Several teams sent us their results for the segmentation and localization of lesions in MR images. Most of the teams preferred to use deep learning methods. The methods varied from a simple U-net structure to more complicated networks. Conclusion The results show that deep learning methods can be useful for segmentation and localization of lesions in MR images. In this study, we briefly described the dataset and the methods of teams attending the competition.

The present study examines the effects of silver nitrate on the activity of the enzyme alkaline phosphatase (ALP) and its regulatory influence on inflammatory cytokines, specifically interleukin-10 (IL-10) and tumor necrosis factor-alpha (TNF-α). These parameters are critical for elucidating the biochemical and immunological responses associated with metal exposure. The research employed enzyme-linked immunosorbent assay (ELISA) techniques to quantify IL-10 and TNF-α levels using serum assay kits. Additionally, gel filtration chromatography with Sephacryl S300 demonstrated that serum from silver nitrate-treated groups exhibited a significantly elevated concentration of high molecular weight alkaline phosphatase compared to control groups. In the TNF-α ELISA assay, no significant differences were observed between the control and treatment groups 15 days post-injection of silver nitrate. However, a statistically significant alteration was detected in both groups 45 days post-injection (P < 0.005). Molecular docking analysis further revealed that the optimal binding pose for ALP, based on the docking score, was −5.28 kcal/mol, with a re-ranking score of −7.43 kcal/mol. Collectively, the findings indicate that silver nitrate exerts a significant impact on ALP activity, leading to a sustained increase in TNF-α levels over time, while IL-10 levels remain unaffected.

Objective To investigate how various morbidities affect older patients’ performance on the Timed Up and Go (TUG) test. Design Cross-sectional study. Setting The seven government hospitals of Lahore, Pakistan, included are major tertiary care centres, representing an older patient population of Punjab, Pakistan. Method 160 elderly participants completed the TUG test, frailty evaluations and Charlson Comorbidity Index (CCI) scoring to assess mobility, frailty and comorbidity burden. The Student’s t-test analysed differences between TUG groups (<10 vs ≥10 s). Multivariate linear regression pinpointed key predictors of CCI scores. All analyses were performed using SPSS software. Results A total of 160 participants (mean age: 67.2±6.9 years and body mass index (BMI): 28.7±4.9 kg/m²) were included. Those with TUG test times under 10 s had lower CCI scores (5.06±1.8) and frailty index (0.15±0.07), compared with those with longer times (CCI: 8.6±4.3 and frailty index: 0.42±0.1). Multivariate regression analysis revealed that TUG time (β=0.342, p=0.001), frailty index (β=0.680, p=0.003), age (β=0.128, p=0.002) and BMI (β=0.098, p=0.027) were significant predictors of CCI. Additionally, higher Mini-Mental State Examination scores (β=−0.092, p=0.017) were associated with lower comorbidity burden. These results highlight mobility, frailty and cognitive function as a predictors of comorbidities in the elderly. Conclusion Our study highlights a significant relationship between mobility, frailty and cognitive function with the comorbidity burden in older adults. Incorporating these metrics into routine care can guide targeted interventions, promoting healthier ageing and improved quality of life.

Nanosilver particles (NSPs) used by customers may contain detergents/solvents. However, in most of the toxicological studies, nanosilvers are prepared in water and very little is known about the interaction of these agents with NSPs in causing adverse effects. The aim of this study was to investigate the interaction of NSPs and tween-20 in causing tissue injuries after inhalation. In this experiment, 16 rats were divided into four groups (n=4/group) as follows. Controls, exposed to water vapors; Tween-treated exposed to tween-20 alone (0.01% V/V); NSP-tween group exposed to 1000 ppm containing tween-20; Group treated with 1000 ppm of NSP alone. Whole-body exposure technique was performed in an exposure chamber for 16 hours (4 hours/day for 4 days). At the end of exposure, blood, liver and lungs were collected and processed for histopathological analysis. Serum glucose, total protein, alkaline phosphatase (ALP), aspartate transaminase (AST) and lactate dehydrogenase (LDH) were compared between experimental groups. The results showed no significant changes in serum ALT, AST, glucose, and albumin in rats exposed to either NSP or NSP suspended in tween-20. Whereas, lipid peroxidation in liver and lungs in rats exposed to NSPs prepared in tween-20 was elevated by 50 and 95% respectively compared to their controls ( p <0.05). The interaction of tween-20 and Ag-NSP was further confirmed by observing tissue damage (histology) in tissues. In conclusion, data show that exposure to NSPs prepared in water is associated with negligible toxicity in rats. However, the toxicity of NSPs is potentiated if prepared in tween-20. It appears that Tween-20 can increase the absorption of NSPs and enhance lipid peroxidation in cellular and subcellular membranes leading to liver damage.

This paper presents a novel two‐switch high step‐down converter based on the conventional Ćuk converter. The proposed converter features lower gain and higher efficiency due to reduced switching and conduction losses. Notably, it enables zero current switching turn‐on for switches without requiring additional components, enhancing its efficiency. The low voltage stress on the switches significantly impacts efficiency. Additionally, its simple topology reduces the component count, further improving efficiency. Zero current switching turn‐off condition for the diode effectively addresses reverse recovery problem. To validate its performance, a prototype operating at 200 W output power, 300 V input voltage, 24 V output voltage, and 40 kHz switching frequency is implanted.

One of the major problems facing the water industry is corrosion and sedimentation, which causes problems such as reduced water quality and the useful life of water supply network equipment. This study aimed to investigate the corrosion and sediments formed in the drinking water distribution network of Sough City. In this cross-sectional study, samples were prepared from 7 wells, water storage reservoirs, and a dedicated water supply network in this area from 2006 to 2017. The parameters included pH, TDS, water temperature, total alkalinity, calcium hardness, and total hardness indices of Langelier, Ryznar, Pokurious, and Aggressive were measured in all sources. The mean indices were -0.59 ± 0.62, 8.48 ± 0.79, 7.24 ± 0.28, and 12.01 ± 0.22, respectively. The average PSI in all seasons was more than 7, AI was equal to 12, and pH in all seasons was 7.8, but in the summer it increased slightly to 8.5. This research showed that the amount of corrosiveness and sedimentation of water is not related to physicochemical parameters. Examination of corrosion indices of the dedicated water supply network of Sough City in the summer of 2011 showed that the water of this network tends to calcium carbonate sedimentation. A magnetic field was used to remove sediments formed in this water distribution network.