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Fine-grained vehicle type recognition using on-road cameras is among interesting topics in machine vision. It has several challenges like inter-class similarity, different viewing angles, and different lighting and weather conditions. This paper presents a novel approach for vehicle classification based on a novel augmentation method and deep learning. In the proposed smart augmentation, the vehicle images of each class are registered on the reference vehicles of all other classes and then added to the training set of that class. In this way, we will have a lot of new images which are very similar to both reference and target classes. This helps the CNN model to handle inter-class similarities very well. In the test phase, the input image is registered on every reference image in parallel and applied to the model. Finally, the winner is determined by summing up the provided scores of all models. The targeted data augmentation along with the proposed classification strategy has high recognition power and is capable of providing high accuracy using small CNNs or any other classification method without the need for large datasets. The proposed method achieved a recognition rate of 99.8% with only 150K parameters. [ABSTRACT FROM AUTHOR]

Herein, we present 1,1,1,3,3,3-hexafluoroisopropanol (HFIP) as an efficient solvent for synthesizing resorcin[ n ]arenes in the presence of catalytic amounts of HCl at ambient temperature and within minutes. Remarkably, resorcinols with electron-withdrawing groups and halogens, which are reported in the literature as the most challenging precursors in this cyclization, are tolerated. This method leads to a variety of 2-substituted resorcin[ n ]arenes in a single synthetic step with isolated yields up to 98%., (Copyright © 2024, Khosravi et al.)

Background: The utilization of the Internet can lead to adverse outcomes in students' lives. Prolonged Internet usage may result in academic failure, an elevated risk of musculoskeletal problems, and the emergence of issues impacting the lives of students and their peers. This study aimed to explore the relationship between Internet addiction and musculoskeletal disorders (MSDs) among students in the field of medical sciences., Methods: In this cross-sectional study, 314 medical sciences students in Semnan, Iran, were assessed using the census sampling method. The participants' Internet addiction status and the presence of MSDs were determined through Young's Internet Addiction questionnaire and the Nordic self-report questionnaire, respectively. Data underwent analysis employing logistic regression test to ascertain the relationship between Internet addiction and MSDs., Results: Among the 314 participating students in this research, about 21% and 1.6% of the participants were lay open to and suffered from Internet addiction, respectively. Internet addiction was associated with the presence of pain, discomfort, burning, or numbness in the neck, wrist, upper back, hips, and thighs. For each unit increase in the Internet addiction score, the chance of neck and wrist pain rises by 3% compared to a 2% increase in upper back and hip/thigh pain., Conclusion: The findings of this study indicate that excessive Internet use is linked to a heightened risk of MSDs in medical sciences students. Consequently, it is imperative to raise awareness about these complications and promote the adoption of proper posture when using the Internet. Further research is also warranted among diverse student populations to investigate the impact of Internet addiction., (© 2024. The Author(s).)

Purpose of Review: Marital quality (MQ) is a psychosocial factor that has been neglected in cardiovascular prevention guidelines, although its association with cardiovascular diseases has been identified in several studies. Therefore, we aim to investigate how MQ either in positive or negative dimensions affect different cardiovascular risk factors and diseases., Recent Findings: We systematically searched different databases in September 2023 for longitudinal studies conducted to assess the contribution of MQ to well-established cardiovascular risk factors and diseases. Two independent researchers screened studies and carried out data extraction and quality assessment of included ones. From 12,175 potential studies screened, 40 were included. The presence of significant heterogeneity in methodology, follow-up, and subsequent effect estimates made it unfeasible to do a meta-analysis. Despite the variation, most studies found a significant association of negative MQ measures with physical inactivity (2/2), high levels of smoking (4/5) and alcohol (3/3) use, increased metabolic syndrome risk (3/3), elevated type 2 diabetes mellitus (T2DM) risk and poor T2DM management (3/6), elevated cardiovascular disease risk and progression (9/11), increased body weight and obesity risk (2/3), elevated blood pressure and hypertension risk (7/8). Positive MQ measures were mainly associated with improvement in blood pressure control (2/2), reduced T2DM risk and its good management (1/1), reduced body weight and obesity risk (2/2), and increased survival in cardiovascular diseases (4/4). Based on current evidence, MQ seems to play a crucial role in developing established cardiovascular risk factors and diseases and is worth considering in preventive strategies., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Aim: The potential of different foods to induce postprandial hyperinsulinemia may be involved in the development of metabolic syndrome (MetS). We aimed to evaluate the association between dietary insulin indices and MetS in a large population of adults in Iran. Methods: A total of 6356 adults aged 35-70 years were included in the present cross-sectional study. A validated block-format 125-item semiquantitative food frequency questionnaire (FFQ) was used to obtain usual food intakes, and MetS was defined according to the International Diabetes Federation (IDF) and American Heart Association (AHA)/National Heart, Lung, and Blood Institute (NHLBI) criteria. Results: MetS was prevalent in 13.8% of participants. Mean age of the study participants was 46.58 ± 8.82 years, and mean body mass index (BMI) was 25.02 ± 4.60 kg/m 2 . Mean dietary insulin index (DII) and dietary insulin load (DIL) were 63.15 ± 7.57 and 168.253 ± 52.09, respectively. In the crude model, men in the highest DIL quartile were more likely to have hyperglycemia than those in the lowest quartile (OR: 1.75, 95% CI: 1.12-2.73, p  trend = 0.04). This association remained significant and was even stronger after adjusting for potential confounders in model I (OR: 3.64, 95% CI: 1.57-8.47, p  trend = 0.005) and further adjustment for BMI in model II (OR: 3.61, 95% CI: 1.55-8.44, p  trend = 0.006). Conclusions: In healthy men, adherence to a high-DIL diet may be associated with a greater likelihood of having hyperglycemia. No statistically significant association was observed between insulin indices and the odds of having MetS., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 Seyede Hamide Rajaie et al.)

Background: Genital self-image is among the factors affecting women's sexual function., Aim: The present study aimed to determine changes in the genital self-image and its relationship with women's sexual function in the third trimester of pregnancy and postpartum., Methods: The participants of this prospective cohort study included 301 eligible pregnant women chosen through stratified random sampling with proportional allocation from comprehensive health centers in Gorgan, Iran. The Persian version of the 7-item Female Genital Self-Image Scale, the 6-item Female Sexual Function Index, and Depression Anxiety and Stress Scale 21 were filled in a self-report manner on 2 occasions: (1) 30 to 37 weeks of pregnancy and (2) 12 to 16 weeks (± 2 weeks) postpartum. Finally, the data were analyzed using SPSS 24 software., Outcomes: Outcomes included Female Genital Self-Image Scale and Female Sexual Function Index changes from pregnancy to postpartum according to the childbirth mode., Results: The mean age of participants was 29.66 ± 5.27 years. These values for the genital self-image scores of women during pregnancy (19.18 ± 3.25) and postpartum (19.43 ± 3.57) were not significantly different (P = .30). Also, this difference was not statistically significant regarding the mode of delivery in 2 groups of women with vaginal birth (P = .62) and cesarean section (P = .14). The mean Female Sexual Function Index scores during pregnancy (15.15 ± 6.73) and postpartum (17.52 ± 6.46) were significantly different (P = .001). In addition, this difference was significant in women with vaginal birth (P = .004) and cesarean section (P = .001)., Clinical Implications: Clinicians should inform women/couples about changes in female sexual function and address genital self-image as a factor involved in female sexual function during pregnancy and postpartum.Strengths and Limitations: Because the participants of this study were women in the third trimester of pregnancy, the obtained results may not be generalized to pregnant women in the first and second trimesters of pregnancy or even to different postpartum periods (ie, midterm and long term)., Conclusion: The results showed that the female genital self-image is not significantly different during pregnancy and postpartum, or with the mode of delivery. However, the female sexual function score in postpartum is higher than in pregnancy, regardless of the mode of delivery., (© The Author(s) 2024. Published by Oxford University Press on behalf of The International Society of Sexual Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Suicide is the second leading cause of death among individuals aged 5 to 24 in the United States (US). However, the precursors to suicide often do not surface, making suicide prevention challenging. This study aims to develop a machine learning model for predicting suicide ideation (SI), suicide planning (SP), and suicide attempts (SA) among adolescents in the US during the coronavirus pandemic. We used the 2021 Adolescent Behaviors and Experiences Survey Data. Class imbalance was addressed using the proposed data augmentation method tailored for binary variables, Modified Synthetic Minority Over-Sampling Technique. Five different ML models were trained and compared. SHapley Additive exPlanations analysis was conducted for explainability. The Logistic Regression model, identified as the most effective, showed superior performance across all targets, achieving high scores in recall: 0.82, accuracy: 0.80, and area under the Receiver Operating Characteristic curve: 0.88. Variables such as sad feelings, hopelessness, sexual behavior, and being overweight were noted as the most important predictors. Our model holds promise in helping health policymakers design effective public health interventions. By identifying vulnerable sub-groups within regions, our model can guide the implementation of tailored interventions that facilitate early identification and referral to medical treatment.

Background: Radiotherapy is one of the primary treatments for cancer, but it can cause damage to normal tissues and lead to side effects. The use of radiosensitizers can enhance the sensitivity of cancer cells to radiation, thereby reducing the amount of radiation required and minimizing damage to healthy tissues. Bismuth selenide nanoparticles (Bi2Se3 NPs) have been shown to have potential as radiosensitizers., Materials and Methods: In this study, we investigated the potential of Bi2Se3 NPs as a radiosensitizer in colon cancer cells (HCT-116) in vitro. The cells were treated with various concentrations of Bi2Se3 NPs and then exposed to ionizing radiation. The viability of the cells was assessed using the MTT assay, and the survival rate was evaluated., Results: Our results showed that Bi2Se3 NPs significantly enhanced the sensitivity of colon cancer cells to ionizing radiation in a dose-dependent manner. The combination of Bi2Se3 NPs and radiation resulted in a significant decrease in cell viability and survival rate compared to radiation alone., Conclusion: Bi2Se3 NPs have the potential to be used as a radiosensitizer in the treatment of colon cancer. The findings of this study suggest that combining Bi2Se3 NPs with radiation may enhance the effectiveness of radiotherapy and reduce the mortality rate associated with colon cancer. Further studies are needed to investigate the safety and efficacy of this approach in vivo., Competing Interests: The researchers state that they have no conflict of interest., (© 2024 The Authors. Published by Elsevier B.V.)

The first example of intramolecular nucleophilic addition of 1,4-diazabutatriene to ester is disclosed. This approach provides a facile and versatile synthesis for functionalized 2 H -1,4-benzoxazines under metal-, reagent-, and solvent-free conditions. Experimental and computational studies revealed the pivotal role of 1,5-acyl migration as the self-catalytic step in the reaction selectivity.

Constructing dual‐ion energy storage devices using anion‐intercalation graphite cathodes offers the unique opportunity to simultaneously achieve high energy density and output power density. However, a critical challenge remains in the lack of proper anodes that match with graphite cathodes, particularly in sustainable electrolyte systems using abundant potassium. Here, a surface grafting approach utilizing multifunctional azobenzene sulfonic acid is reported, which transforms V2C MXene into a high‐kinetics K+‐intercalation anode (denoted ASA‐V2C) for dual‐ion energy storage devices. Importantly, the grafted azobenzene sulfonic acid offers extra K+‐storage centers and fast K+‐hopping sites, while concurrently acting as a buffer between V2C layers to mitigate the structural distortion during K+ intercalation/de‐intercalation. These functionalities enable the V2C electrode with significantly enhanced specific capacity (173.9 mAh g−1 vs 121.5 mAh g−1 at 0.05 A g−1), rate capability (43.1% vs 12.0% at 20 A g−1), and cycling stability (80.3% vs 45.2% after 900 cycles at 0.05 A g−1). When coupled with an anion‐intercalation graphite cathode, the ASA‐V2C anode demonstrates its potential in a dual‐ion energy storage device. Notably, the device depicts a maximum energy density of 175 Wh kg−1 and a supercapacitor‐comparable power density of 6.5 kW kg−1, outperforming recently reported Li+‐, Na+‐, and K+‐based dual‐ion devices. [ABSTRACT FROM AUTHOR]

Introduction: The basic strategy to mitigate water crisis is to save agricultural water consumption by increasing productivity, which will result in more income for farmers and sustainable production. Due to the economic importance of barley production in the country, it is necessary to study the volume of irrigation water and water productivity to produce this strategic product. Based on extensive field research on irrigation water management and application of different irrigation methods in barley farms, the innovations of this research were: a) measuring water consumed and determining water use efficiency in barley production, b) the up-to-date of the measurements and research findings, c) findings applicability for application in agricultural planning at the national and regional levels, d) the ability to development the findings in barley farms at the national level to improve water use efficiency. The hypotheses of this research are: a) barley irrigation water is various in different regions, b) water applied in barley farms is more than the required one, c) the water use efficiency of barley is different in the main production areas, and d) The applied water of barley is not the same in different irrigation methods. Therefore, the main objective of this study is to determine the water consumed and water use efficiency in barley production; to measure the water applied to barley farms in the main production areas; to compare the water measured in the production areas with the net irrigation requirement; and finally to determine water use efficiency of the barley in the main production areas in the Iran. Materials and Methods For this purpose, the volume of irrigation water and barley yield in 296 selected farms in 12 provinces (about 75% of the area under cultivation and production of barley in Iran) including Khuzestan, East Azerbaijan, Ardabil, North Khorasan, Fars, Khorasan Razavi, Tehran, Semnan, Markazi, Isfahan, Hamedan and Qazvin were measured directly. Farms in the mentioned provinces were selected to cover various factors such as irrigation method, level of ownership, proper distribution and quality of irrigation water. By carefully monitoring the irrigation program of selected farms during the growing season, the amount of irrigation water for barley during one year was measured. At the end of the season and after determining the average yield of barley during the 2020-2021 year, the values of irrigation water productivity and total water productivity (irrigation+effective rainfall) were determined in selected barley farms in each region. The volume of water supplied was compared with the gross irrigation requirements estimated by the Penman-Monteith method using meteorological data from the last ten years, and compared with the values of the National Water Document. Analysis of variance was used to investigate the possible differences in yield, irrigation water and water productivity in barley production. Results and Discussion To assess the reliability of statistical analysis, we evaluated the sufficiency of the number of measurements needed for both the quantity of irrigation water and the ley yield on the farms. Subsequently, we computed statistical indices, such as the mean and standard deviation. The results showed that the number of measurements of irrigation water and barley yield was to be 296 and 283, respectively, which was more than the number of measurements required for irrigation water (41 dataset) and yield (50 dataset). Therefore, the sufficiency of the data for the statistical analysis was reliable. The results showed that the difference in yield, volume of irrigation water and water productivity indices were significant in the mentioned provinces. The volume of barley irrigation water in the studied areas varied from 1900 to 9300 cubic meters per hectare and its average weight was 4875 cubic meters per hectare. The average barley yield in selected farms varied from 1630 to 7050 kg ha-1 and the average was 3985 kg ha-1. Irrigation water productivity in selected provinces ranged from 0.22 to 1.53 and its weight average was 0.90 kg m-3. Average gross irrigation water requirement in the study areas by the Penman-Monteith method using meteorological data of the last ten years and the national water document were 4710 and 4950 cubic meters per hectare, respectively. Irrigation efficiency of barley fields in the country is estimated at 6265% without deficit irrigation. Conclusion In order to reduce water consumption and improve water productivity, it is suggested to manage water delivery to farms during the season and deliver water rights to them according to crops water requirements. To reduce water losses and enhance productivity in the barley farms, it is suggested the application of modern irrigation systems according to the farms conditions with the suitable operation; and modification and improvement of surface and traditional irrigation methods. Note that, water is only one of several necessary and effective inputs in the optimal and economic production of barley. On the other hand, attention should be paid to the optimal application of other inputs including: seeds, fertilizers, equipment and tools etc. [ABSTRACT FROM AUTHOR]

Background: This study aimed to evaluate the psychometric indicators of the Persian version of the Sense of Belonging in Nursing School scale (SBNS)., Methods: The study conducted in Shahroud and Semnan schools of nursing and midwifery in Iran examined nursing students using a cross-sectional approach by convenience sampling method from 3/6/2023 to 24/8/2023. To assess the SBNS scale, the forward-backward procedure was used to translate it into Persian. Face and content validity were evaluated, and exploratory and confirmatory factor analyses were conducted with sample sizes of 200 and 182, respectively. Reliability was assessed using Cronbach's alpha coefficient, MacDonald's omega, and intra-class correlation coefficient., Results: The exploratory factor analysis resulted in the exclusion of four items, leaving a final selection of 15 items. These items were categorized into three factors: classmates, clinical staff, and inclusive educational environment, which accounted for 49.16% of the overall variance. The confirmatory factor analysis indicated that the model was a good fit for the observed data, and the subscales had high internal consistency (Cronbach's alpha coefficient was 0.752 to 0.880) and stability (intra-class correlation coefficient was 0.889 to 0.968)., Conclusion: According to the results, it can be concluded that the Persian version of the SBNS scale demonstrates sufficient validity and reliability in assessing students' sense of belonging to the nursing school., (© 2024. The Author(s).)

Background: Metabolic syndrome (MetS) is a cluster of metabolic abnormalities (including obesity, insulin resistance, hypertension, and dyslipidemia), which can be used to identify at-risk populations for diabetes and cardiovascular diseases, the main causes of morbidity and mortality worldwide. The achievement of a simple approach for diagnosing MetS without needing biochemical tests is so valuable. The present study aimed to predict MetS using non-invasive features based on a successful random forest learning algorithm. Also, to deal with the problem of data imbalance that naturally exists in this type of data, the effect of two different data balancing approaches, including the Synthetic Minority Over-sampling Technique (SMOTE) and Random Splitting data balancing (SplitBal), on model performance is investigated., Results: The most important determinant for MetS prediction was waist circumference. Applying a random forest learning algorithm to imbalanced data, the trained models reach 86.9% and 79.4% accuracies and 37.1% and 38.2% sensitivities in men and women, respectively. However, by applying the SplitBal data balancing technique, the best results were obtained, and despite that the accuracy of the trained models decreased by 7.8% and 11.3%, but their sensitivity improved significantly to 82.3% and 73.7% in men and women, respectively., Conclusions: The random forest learning method, along with data balancing techniques, especially SplitBal, could create MetS prediction models with promising results that can be applied as a useful prognostic tool in health screening programs., (© 2024. The Author(s).)

The stability of emulsions is a critical concern across multiple industries, including food products, agricultural formulations, petroleum, and pharmaceuticals. Achieving prolonged emulsion stability is challenging and depends on various factors, with particular emphasis on droplet size, shape, and spatial distribution. Addressing this issue necessitates an effective investigation of these parameters and finding solutions to enhance emulsion stability. Image analysis offers a powerful tool for researchers to explore these characteristics and advance our understanding of emulsion instability in different industries. In this review, we highlight the potential of state-of-the-art deep learning-based approaches in computer vision and image analysis to extract relevant features from emulsion micrographs. A comprehensive summary of classic and cutting-edge techniques employed for characterizing spherical objects, including droplets and bubbles observed in micrographs of industrial emulsions, has been provided. This review reveals significant deficiencies in the existing literature regarding the investigation of highly concentrated emulsions. Despite the practical importance of these systems, limited research has been conducted to understand their unique characteristics and stability challenges. It has also been identified that there is a scarcity of publications in multimodal analysis and a lack of a complete automated in-line emulsion characterization system. This review critically evaluates the existing challenges and presents prospective directions for future advancements in the field, aiming to address the current gaps and contribute to the scientific progression in this area., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Healthcare organizations are among high-risk organizations due to the nature of their work as well as structural, physical and technological complexities. Accordingly, it is important to use risk management and control programs in all departments of these organizations., Objective: The present study was conducted for the first time to evaluate the risk management status of the operating room and laboratory departments of Hamadan hospitals in 2022., Methods: In this descriptive-observational cross-sectional study, laboratory and operating room departments were selected as the research environment. To conduct this research, a valid and reliable questionnaire was used to collect data, and the data were analyzed using SPSS 22 statistical software., Results: The findings of the present study showed that the overall mean score of risk management status for the laboratory and operating room departments was 2.66 ± 0.15 and 2.89 ± 0.13, respectively. Furthermore, there was no statistically significant difference in the mean scores of the research components based on work experience, education level, and gender., Conclusion: It is suggested that the laboratory and operating room departments should focus more on adopting policies and solutions to improve the position of risk management, training and budget allocation for risk management.

Background and Aims: Metabolic syndrome (MetS) is a widely used index for finding people at risk for chronic diseases, including cardiovascular disease and diabetes. Early detection of MetS is especially important in prevention programs. Relying on previous studies that suggest machine learning methods as a valuable approach for diagnosing MetS, this study aimed to develop MetS prediction models based on support vector machine (SVM) algorithms, applying non-invasive and low-cost (NI&LC), and also dietary parameters., Methods and Results: This population-based research was conducted on a large dataset of 4596 participants within the framework of the Shahedieh cohort study. An Extremely Randomized Trees Classifier was used to select the most effective features among NI&LC and dietary data. The prediction models were developed based on SVM algorithms, and their performance was assessed by accuracy, sensitivity, specificity, positive prediction value, negative prediction value, f1-score, and receiver operating characteristic curve. MetS was diagnosed in 14% of men and 22% of women. Among NI&LC features, waist circumference, body mass index, waist-to-height ratio, waist-to-hip ratio, systolic blood pressure, and diastolic blood pressure were the most predictive variables. By using NI&LC features, models with 78.4% and 63.5% accuracy and 81.2% and 75.3% sensitivity were yielded for men and women, respectively. By incorporating NI&LC and dietary features, the accuracy of the model in women improved by 3.7%., Conclusions: SVM algorithms had promising potential for early detection of MetS relying on NI&LC parameters. These models can be used in prevention programs, clinical practice, and personal applications., Competing Interests: Declaration of competing interest The authors declare that they have no conflicts of interest., (Copyright © 2023 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.)

Introduction Metabolic syndrome (MetS) remains one of the leading health challenges worldwide. A combination of genetic and environmental factors has been implicated in the etiology of MetS. Diet is a changeable environmental risk factor, and dietary modifications could significantly reduce the incidence and mortality of numerous diseases, including MetS. Certain dietary factors may contribute to MetS by affecting the acid-base balance within the body. This study examined the association of dietary acid load (DAL) with MetS and its components in Iranian adults. Materials and methods This cross-sectional study was conducted in 2022 on 6356 Iranian adults aged 35-70 years. Potential renal acid load (PRAL) and net endogenous acid production (NEAP) as two indicators of DAL were calculated based on nutrient intake data from validated food frequency questionnaires. MetS and its components were defined according to the Adult Treatment Panel III criteria. Logistic regression analysis was used to explore the associations between DAL and MetS and its components. Age, energy intake, physical activity, education, marital status, home ownership, socioeconomic status, history of obesity-related disease, and calcium supplements were included in model I. Further adjustment in model II was made for body mass index. Results Higher NEAP scores were associated with increased odds of low high-density lipoprotein cholesterol (HDL-C) in the crude model (OR: 1.26, 95% CI: 1.01-2.56, p trend = 0.06) in women, which was confirmed in the adjusted models. In model I, women in the last quintile of NEAP had 54% greater odds of having hypertriglyceridemia compared to the first quintile (OR: 1.54, 95% CI: 1.007-2.36, p trend = 0.02). This association was still significant and even stronger after further adjustment for BMI (OR: 1.55, 95% CI: 1.01-2.40, p trend = 0.01). In addition, in model I, men in the fourth quintile of NEAP had 5.68-fold greater odds of hyperglycemia compared to the first quintile (OR: 5.68, 95% CI: 1.18-27.25, p trend = 0.11). Similar results were found in the fully adjusted model (OR: 5.89, 95% CI: 1.19-28.99, p trend = 0.54). Conclusion There was no significant association between DAL and MetS. DAL was positively associated with the odds of low HDL-C and hypertriglyceridemia in women. Moreover, moderate DAL (NEAP) was associated with an increased odds of hyperglycemia in men., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Rajaie et al.)

The pregnane X receptor (PXR) is a ligand-activated regulator of cytochrome P450 (CYP)3A enzymes. Among the ligands of human PXR is hyperforin, a constituent of St John's wort (SJW) extracts and potent inducer of human CYP3A4. It was the aim of this study to compare the effect of hyperforin and SJW formulations controlled for its content on CYP3A23-3A1 in rats. Hyperiplant was used as it contains a high hyperforin content and Rebalance because it is controlled for a low hyperforin content. In silico analysis revealed a weak hyperforin-rPXR binding affinity, which was further supported in cell-based reporter gene assays showing no hyperforin-mediated reporter activation in presence of rPXR. However, cellular exposure to Hyperiplant and Rebalance transactivated the CYP3A reporter 3.8-fold and 2.8-fold, respectively, and they induced Cyp3a23-3a1 mRNA expression in rat hepatoma cells compared with control 48-fold and 18-fold, respectively. In Wistar rats treated for 10 days with 400 mg/kg of Hyperiplant, we observed 1.8 times the Cyp3a23-3a1 mRNA expression, a 2.6-fold higher CYP3A23-3A1 protein amount, and a 1.6-fold increase in activity compared with controls. For Rebalance we only observed a 1.8-fold hepatic increase of CYP3A23-3A1 protein compared with control animals. Even though there are differing effects on r Cyp3a23-3a1 /CYP3A23-3A1 in rat liver reflecting the hyperforin content of the SJW extracts, the modulation is most likely not linked to an interaction of hyperforin with rPXR. SIGNIFICANCE STATEMENT: Treatment with St John's wort (SJW) has been reported to affect CYP3A expression and activity in rats. Our comparative study further supports this finding but shows that the pregnane X receptor-ligand hyperforin is not the driving force for changes in rat CYP3A23-3A1 expression and function in vivo and in vitro. Importantly, CYP3A induction mimics findings in humans, but our results suggest that another so far unknown constituent of SJW is responsible for the expression- and function-modifying effects in rat liver., (Copyright © 2023 by The Author(s).)

Several studies have examined the association between CD36 rs1761667 polymorphism with cardiometabolic risk factors and metabolic syndrome (MetS). This study aimed to investigate the interactions between rs1761667 polymorphism and dietary patterns on the cardiometabolic risk factors and the risk of MetS in apparently healthy individuals aged 20-70 years. Food consumption data were acquired using a validated semi-quantitative FFQ. Dietary patterns were identified by factor analysis. CD36 rs1761667 was genotyped by PCR-restriction fragment length polymorphism. The gene-diet interaction was detected by the general linear model or logistic regression. Significant or marginally significant interactions were observed between healthy dietary pattern (HDP) and CD36 rs1761667 on weight ( P = 0·006), BMI ( P = 0·009), waist circumference ( P = 0·005), hip circumference ( P = 0·06), body muscle percentage ( P = 0·02), body fat percentage ( P = 0·09), TAG-glucose index ( P = 0·057), atherogenic index of plasma ( P = 0·07), the risk of MetS ( P = 0·02), risk of abdominal obesity ( P = 0·02) and elevated blood pressure ( P = 0·07). Besides, a gene-diet interaction was detected between the traditional dietary pattern and rs1761667 variants on odds of hypertriglyceridaemia ( P = 0·02). The adherence to HDP was associated with a lower weight, BMI and higher odds of HDL-cholesterol only in A-allele carriers. In conclusion, adherence to HDP (a diet with high fibre, fish and dairy products) can be more effective on some cardiometabolic risk factors and risk of MetS components in the A-allele carrier than the GG genotype of rs1761667 polymorphism. However, future studies are required to shed light on this issue.

High cost and low electrochemical stability of the interconnection in Proton Exchange Membrane Fuel Cell (PEMFC) in the presence of H2SO4 are one of the main issues hindering the commercialization of these devices. This manuscript presents the utilization of cost-effective steel in an attempt to minimize the PEMFC interconnection costs with a thin-film solid oxide coating (TFSOC) providing sufficient corrosion resistance for efficient long-term operation. Novel Ti0.50-y/2Si0.50-y/2Nby1,2O2 as TFSOC was deposited on the C45E steel as a metal interconnect utilizing a sol–gel process at various annealing temperatures. The analysis of the phase and surface morphology demonstrates that lower annealing temperatures developed nanometric crystallite size of 68 nm, more uniform structure and higher corrosion resistance. Under standard test conditions, the TFSOC demonstrated high polarization resistance (1.3 kΩ cm2) even after 720 hours (h). Electrical conductivity of the TFSOC as low as 1.4 × 10−2 (Ω m)−1 and activation energy of 0.20 eV were achieved, which helps to maintain the PEMFC output power.

Background: Gel polymers are considered as new dosimeters for determining radiotherapy dose distribution in three dimensions. Objective: The ability of a new formulation of MAGIC-f polymer gel was assessed by experimental measurement and Monte Carlo (MC) method for studying the effect of gold nanoparticles (GNPs) in prostate dose distributions under the internal Ir-192 and external 18MV radiotherapy practices. Method: A Plexiglas phantom was made representing human pelvis. The GNP shaving 15 nm in diameter and 0.1 mM concentration were synthesized using chemical reduction method. Then, a new formulation of MAGIC-f gel was synthesized. The fabricated gel was poured in the tubes located at the prostate (with and without the GNPs) and bladder locations of the phantom. The phantom was irradiated to an Ir-192 source and 18 MV beam of a Varian linac separately based on common radiotherapy procedures used for prostate cancer. After 24 hours, the irradiated gels were read using a Siemens 1.5 Tesla MRI scanner. The absolute doses at the reference points and isodose curves resulted from the experimental measurement of the gels and MC simulations following the internal and external radiotherapy practices were compared. Results: The mean absorbed doses measured with the gel in the presence of the GNPs in prostate were 15% and 8 % higher than the corresponding values without the GNPs under the internal and external radiation therapies, respectively. MC simulations also indicated a dose increase of 14 % and 7 % due to presence of the GNPs, for the same experimental internal and external radiotherapy practices, respectively. Conclusion: There was a good agreement between the dose enhancement factors (DEFs) estimated with MC simulations and experiment gel measurements due to the GNPs. The results indicated that the polymer gel dosimetry method as developed and used in this study, can be recommended as a reliable method for investigating the DEF of GNPs in internal and external radiotherapy practices.

One of the major issues related to traffic monitoring systems is analysis of the behavior of vehicles and identification of their characteristics. In this paper, an automated algorithm is proposed for calibration of road cameras. This calibration is used to estimate the speed and dimensions of passing vehicles. By using this method, a motion plane is obtained in the initial frames according to the direction of moving vehicles. After modeling the background, removing shadows, and identifying the exact boundaries of passing vehicles, a number of common vehicles are recognized through the bag of words method. Given the actual metric dimensions of these vehicles and the equivalent dimensions on the motion plane, the metric coefficients are calculated and the calibration process is completed. Each passing vehicle is projected on the motion plane, and speed and dimensions are calculated by tracking it along the road. To test the accuracy of the proposed method, a ground-truth video dataset is constructed by simultaneously capturing road vehicles using RGB and speed cameras. Furthermore, to identify common vehicles, a dataset of vehicle images is collected. The proposed method is evaluated based on our dataset and the mean error of 1.15 km/h is achieved. Accordingly, it outperforms previous methods. [ABSTRACT FROM AUTHOR]

Recycling and revalorization of waste are currently essential for sustainable growth. Mill scale, a waste product from steel production industries, which contains high levels of iron and minimal impurities, is proposed in this study as the source to synthesize magnetite nanoparticles (Fe 3 O 4 ) for an enhancement of a lactate biosensor range. The synthesized Fe 3 O 4 nanoparticles were coated with polydopamine (PDA) to prevent aggregation and degradation, creating a stable platform for immobilizing lactate oxidase enzyme (LOx) on their surfaces. The characterization of the Fe 3 O 4 @PDA material was carried out using transmission electron microscopy (TEM), dynamic light scattering (DLS), and measurement of the polydispersity index (PdI). The Fe 3 O 4 @PDA-LOx material was then deposited on a screen-printed carbon electrode modified with Prussian blue (SPCE-PB) for lactate detection. The biosensor exhibited a broad, dual linear concentration-response range, one from 0.1 to 4.62 mM with a limit of detection of 0.32 mM and sensitivity of 1.54 μAmM-1cm-2, and another one from 4.62 to 149.21 mM with a limit of detection of 6.31 mM and sensitivity of 0.08 μAmM-1cm-2. The dual-range concentration response of the biosensor makes it an ideal tool for lactate determination in various applications, including sports medicine, clinical diagnosis, and industrial bioprocessing.

Background & Aims: Obesity is linked to the pathogenesis of non-alcoholic fatty liver disease (NAFLD). Patients with NAFLD are at increased risk for hypertension. Some investigations have hypothesized that Cornus mas L. fruit can improve obesity and hypertension. We investigated the effect of C. mas L. fruit extract on blood pressure, anthropometric and body composition indices in patients with NAFLD., Methods: This 12-week double-blind randomized controlled trial was conducted on fifty patients with NAFLD. Patients received 20 cc/d C. mas L. fruit extract or placebo. We measured diastolic blood pressure (DBP), systolic blood pressure (SBP), weight, waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), body fat mass (BFM), body fat percent (BFP) and fat free mass (FFM) before and after intervention., Results: Treatment group compared to control group showed a significant reduction in DBP (-8.62 ± 11.86 mmHg vs. 0.53 ± 8.53 mmHg; P crude  = 0.003; P adjucted  = 0.03) and SBP (-8.63 ± 14.37 mmHg vs. 0.0 ± 12.67 mmHg; P crude  = 0.02; P adjucted  = 0.02). We found no difference between groups in weight, WC, HC, WHR, BFM, BFP and FFM (P > 0.05). After adjusting for confounding factors, a significant reduction was observed in treatment group compared to control group in BFM (-0.2 ± 3.9 kg vs. 0.7 ± 2.4 kg; P = 0.01) and BFP (-0.2 ± 4.9% vs. 0.8 ± 2.8%; P = 0.02)., Conclusions: C. mas L. fruit extract statistically reduced blood pressure and body fat. However, it had no effect on other anthropometric and body composition indices. Studies with larger sample sizes and higher dosages of extract are needed., Trial Registration: Registered on 30/9/2018 at Iranian Registry of Clinical Trials IRCT20180419039359N1 (https://www.irct.ir/trial/30707)., (Copyright © 2023 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights reserved.)

This paper tries to introduce a time-series of temperature parameters as a potential method for studying the global warming. So, we investigated the spatial-temporal variations of warm-season temperature parameters (WSTP), including start time, end time, length of season, base value, peak time, peak value, amplitude, large integrated value, right drive, and left drive, using a database of 30 years' period in different climates of Iran. We used daily temperature data from 1989 to 2018 over Iran to extract the parameters by TIMESAT software. We studied the trend analysis of WSTP through the Mann-Kendall method. Then, we considered the Pearson correlation coefficient to calculate the correlation between WSTP and time. We assessed the trends of the slope using a simple linear regression method. Then, we compared the results of the WSTP trend analysis in climatic zones. Our results accused the hyper-arid climatic zone has the longest warm season (194.89 days a year). The warm season in this region starts earlier than other regions and increases with moderate speed (left drive, 0.19 °C day -1 ). Then, it reaches a peak value (31.3 °C) earlier than the different climatic zones. On the other hand, the humid regions' warm season starts with the shortest length and ends later than the other climatic zones (112.1 and 297.5 days a year for start and end times, respectively). We detected that the trend of the start time parameter has decreased by 98.02% of the study area during the last 30 years. The base value, length, and large integrated value parameters have an increasing trend of 66.47%, 80.11%, and 92.95% in Iran. The highest correlation coefficient with time was for start time and large integrated value parameters. Hence, the start time and large integrated value parameters have almost the most negative (< - 0.5) and positive (> 5) trend slope, among other parameters, respectively. In general, these results demonstrate that the studied region has faced global warming impacts over time by increasing the warm season and thermal energy, especially in arid and hyper-arid. We highlight the necessity of planning the land use under the high natural vulnerability of the studied local, especially in this new age of global warming., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: Recent investigations have proposed that sesame and canola oils might affect body fat distribution. The present study aimed to examine the effects of sesame, canola and sesame-canola (a blend of sesame and canola oils) oils on body weight and composition in adults with type 2 diabetes mellitus in the context of a randomized, triple-blind, three-way, cross-over clinical trial., Results: Eligible participants were randomized to replace their regular dietary oil with sesame oil (SO), canola oil (CO) and sesame-canola oil (SCO) (with 40% SO and 60% CO). Treatment periods lasted 9 weeks and were separated by 4-week wash-out periods. Body weight and composition were measured at the beginning, in the middle and at the end of each intervention phase. In total, 93 participants completed the study. After adjustment for confounders, within-period changes were observed following SO and CO intake for body weight (0.34 ± 0.16 kg and 0.33 ± 0.17 kg) and visceral fat (0.13 ± 0.06% and 0.13 ± 0.05%, P < 0.05), respectively. Body mass index was increased within SO intake (0.13 ± 0.05 kg m -2 , P = 0.031). All of the treatment oils resulted in reduced waist circumference and index of central obesity (P < 0.05). A significant difference in change values was observed for visceral fat between SCO (-0.14 ± 0.07%) and SO (0.12 ± 0.08%) treatment periods in females (P = 0.02)., Conclusion: Sesame and canola oils might lead to a modest favorable body fat redistribution by reducing central adiposity, particularly in females; however, the changes were of little clinical importance. © 2021 Society of Chemical Industry., (© 2021 Society of Chemical Industry.)