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Abstract Objective This study aims to explore the relationship between pre-existing renal impairment and oncological outcomes in upper tract urothelial carcinoma (UTUC) patients treated with radical nephroureterectomy (RNU) using data from a multicentre international registry. Patients and methods Data on non-metastatic UTUC patients who underwent RNU were obtained from the Clinical Research Office of the Endourology Society Urothelial Carcinomas of the Upper Tract (CROES-UTUC) Registry. Patients were categorised into normal pre-operative renal function and chronic renal impairment (CKD) groups, with CKD defined as an estimated glomerular filtration rate below 60 mL/kg/1.73 m². Kaplan–Meier survival analysis was employed to investigate disease-free survival (DFS) and overall survival (OS). Multivariable Cox regression analysis was conducted to identify confounding variables. Results A total of 1393 patients diagnosed with UTUC who underwent RNU between 2014 and 2019 were analysed. 875 patients (62.4%) had normal renal function, whilst 528 patients (37.6%) had CKD prior to RNU. The two groups had similar proportions of bladder cancer history, comparable cardiovascular comorbidity, similar tumour stage, and comparable proportions receiving laparoscopic or robotic-assisted RNU. In multivariable cox regression analysis, CKD was found to be associated with inferior DFS (HR = 1.419; 95%CI = 1.060–1.898; p = 0.019). Upon multivariable analysis, pre-existing renal impairment and higher T stage (HR = 4.613; 95%CI = 1.829–4.712; p

Abstract Cadmium (Cd) contamination poses significant risks to agricultural productivity and human health, particularly through its accumulation in staple crops such as bread wheat (Triticum aestivum L.). This study evaluated Cd accumulation and tolerance among six bread wheat cultivars exposed to six Cd concentrations (0, 2.5, 5, 10, 15, 20, and 25 mg kg−1 soil). Phenotypic assessments and quantitative real-time PCR (qRT-PCR) were conducted to analyze the expression patterns of TaNRAMP and TaZIP genes in various tissues and developmental stages of wheat, which play crucial roles in Cd uptake and transport. Results demonstrated significant variability in Cd accumulation. The Barat cultivar exhibited the lowest accumulation in grain (ranging from 0.21 to 8.8 mg kg−1) and the highest tolerance. In contrast, Kavir and Pishtaz displayed elevated Cd levels in both grain and straw, while Parsi accumulated more Cd in straw at lower concentrations (56.9 mg kg−1 in Cd concentration of 10 mg kg−1 soil). The gene expression analysis revealed that most cultivars showed increased expression of TaNRAMP genes, particularly TaNRAMP2 in Cd concentration of 10 mg kg−1 soil, which facilitates Cd uptake from the soil, and TaZIP genes, such as TaZIP4 and TaZIP7, involved in transporting Cd within the plant. Notably, the expression of TaZIP1 was significantly lower in cultivars with high Cd accumulation, suggesting a potential regulatory mechanism for Cd tolerance. Furthermore, cultivars exhibiting higher Cd levels correlated with increased expression of stress-responsive genes, indicating a broader response to Cd stress. These findings highlight Barat’s potential for bread-making applications due to its low Cd accumulation, while Morvarid and Pishtaz which show reduced Cd content in the straw even under high Cd exposure are better suited for animal feed. This research underscores the genetic variability of wheat cultivars in response to Cd stress and provides essential insights into the molecular mechanisms underlying Cd accumulation, offering valuable information for breeding programs aimed at developing Cd-tolerant varieties to ensure food security in contaminated regions.

Background: Classifying COVID-19 hospitalized patients based on multimorbidity could aid in individual evaluation and provide effective triage for better treatment and management. The aim of this study was to extract multimorbidity patterns among hospitalized COVID-19 patients and determine their associations with admission to intensive care units (ICU) and mortality. Methods: The data in this retrospective study were acquired from the registry system for all 13,960 COVID-19 patients from 42 hospitals in Mazandaran Province in northern Iran between March 20, 2020, and July 20, 2021. The multimorbidity patterns of 11 chronic diseases were extracted using latent class analysis (LCA). The association between multimorbidity patterns and mortality from COVID-19 and admission to the ICU was examined using multilevel logistic regression modeling. Results: Four classes were identified, including diabetes and cardiovascular disease (class 1, 3.7%), metabolic diseases and others (class 2, 0.6 %), diabetes and hypertension (class 3, 23.0%), and non-multimorbidity (class 4, 72.7%). Membership in class 1 (diabetes and cardiovascular disease) and class 3 (diabetes and hypertension), compared with class 4 (non-multimorbidity), was associated with higher odds of experiencing death (OR=2.66 for class 1 and 1.21 for class 3). Class 2 did not show a significant difference from class 4 regarding mortality. Conclusion: Multimorbidity classification is a key predictor of COVID-19 patient prognosis, guiding treatment decisions and prioritizing protective measures, such as vaccination. Notably, those with multimorbidity patterns of “diabetes and cardiovascular diseases” and “diabetes and hypertension” exhibit the highest risk of ICU admission and mortality.

Background: As physical inactivity is presently a global concern, encouraging people to engage in physical activity (PA) is a public health policy priority. This study was conducted to analyze the process of change in the adoption of policies which aim at promoting PA in setting the policy agenda.Methods: This qualitative study was conducted using document reviews and semi-structured interviews. A total of 23 key informants from different sections of the policymaking process for PA promotion programs in Iran participated in the study. Purposeful sampling with a maximum variation was used to identify the key informants. Analysis of documents and interviews was conducted on the basis of Kingdon’s multiple streams Framework (MSF): problems, policies, and political streams. The MAXQDA-10 software was used to manage the data analysis process.Results: The problem stream was found to be “the high prevalence of physical inactivity, perceived subjective barriers, and contextual factors for PA” throughout the country. The policy stream focused on integrating PA services into primary health care, scheduling national and global calendar campaigns and events, and using the existing legal structures to promote PA in communities. At the political stream, support for policy documents and various legislative and governing authorities, as well as international support, particularly the World Health Organization 2018–2030 agenda, provided a favorable environment for this issue.Conclusion: Despite the opening of a policy window for developing policies to promote PA, several challenges may hinder the policy implementation process, including a lack of health promotion approach in the health system, lack of inter-sectoral cooperation, COVID-19 pandemic-associated restrictions, and management and structural issues. As the policy window is not being used appropriately, the policymakers must review the policies, with particular attention to the feasibility of policies, the organizational culture of the different ministries, and the mediating and advocating roles of the health sector in operationalizing the policies.

Abstract Medical image machines serve as a valuable tool to monitor and diagnose a variety of diseases. However, manual and centralized interpretation are both error-prone and time-consuming due to malicious attacks. Numerous diagnostic algorithms have been developed to improve precision and prevent poisoning attacks by integrating symptoms, test methods, and imaging data. But in today’s digital technology world, it is necessary to have a global cloud-based diagnostic artificial intelligence model that is efficient in diagnosis and preventing poisoning attacks and might be used for multiple purposes. We propose the Healthcare Federated Ensemble Internet of Learning Cloud Doctor System (FDEIoL) model, which integrates different Internet of Things (IoT) devices to provide precise and accurate interpretation without poisoning attack problems, thereby facilitating IoT-enabled remote patient monitoring for smart healthcare systems. Furthermore, the FDEIoL system model uses a federated ensemble learning strategy to provide an automatic, up-to-date global prediction model based on input local models from the medical specialist. This assures biomedical security by safeguarding patient data and preserving the integrity of diagnostic processes. The FDEIoL system model utilizes local model feature selection to discriminate between malicious and non-malicious local models, and ensemble strategies use positive and negative samples to optimize the performance of the test dataset, enhancing its capability for remote patient monitoring. The FDEIoL system model achieved an exceptional accuracy rate of 99.24% on the Chest X-ray dataset and 99.0% on the MRI dataset of brain tumors compared to centralized models, demonstrating its ability for precision diagnosis in IoT-enabled healthcare systems.

Abstract The quality of images we perceive visually is heavily impacted by the settings used for camera exposure. When these settings are imbalanced, it can result in an undesired prominent phenomenon known as blur effects. To address this problem, an ExposureNet project has been undertaken, which aims to develop an autonomous camera exposure settings control system for blur effects prevention. The proposed ExposureNet model is a CNN/Transformer hybrid neural structure, created and trained in a comprehensive manner to effectively predict the ideal exposure settings based on the semantic features of the scene being captured. This system is designed to learn the necessary steps for processing, such as identifying relevant scene features, using only two camera exposure parameters (shutter speed (SHS) and ISO) as training signals. As a result, this system can associate the semantic features of a scene with the appropriate exposure parameter adjustments, customized to the scene's dynamics and lighting conditions. By simultaneously optimizing all processing steps and bypassing traditional post‐processing stages, the proposed system is designed to achieve faster performance, reduced computational cost, and lower power consumption. Experimental results demonstrate that the proposed system significantly outperforms existing methods and achieves cutting‐edge performance.

Abstract Rapid urbanization and inadequate environmental planning have significantly increased pressure on ecosystems, leading to unsustainable urban growth. Understanding the environmental impact of urbanization is crucial for sustainable development, especially in rapidly growing cities like Mashhad, Iran. Emergy Analysis, a method that quantifies the total energy used to support an ecosystem, was applied in this study to assess Mashhad’s environmental sustainability using emergy-based indicators. Key sustainability indicators, such as the Emergy Sustainability Index, Environmental Load Ratio, and Emergy Self-Support Ratio, were analyzed using data from 2011, 2016, and 2021. The results reveal that Mashhad's development is currently unsustainable, with heavy dependence on non-renewable resources and increasing environmental pressure. While the Emergy Sustainability Index showed modest improvement, key indicators like the Emergy Yield Ratio and Emergy Density declined, indicating reduced resource efficiency. Additionally, the Environmental Load Ratio increased, reflecting higher environmental stress. Without significant interventions, Mashhad’s current development trajectory will remain unsustainable. The study offers practical recommendations, such as reducing urban sprawl, promoting green spaces, and transitioning to renewable energy sources. Educating residents about resource efficiency and sustainable urban planning is critical. These findings provide actionable insights for other developing cities facing similar environmental challenges and serve as a blueprint for sustainable urban development in resource-constrained settings.

Abstract Deriving an effective massless field theory for fluctuations about a braneworld spacetime requires analysis of the transverse-space-wavefunction’s second-order differential equation. There can be two strikingly different types of effective theory. For a supersymmetric braneworld, one involves a technically consistent embedding of a supergravity theory on the worldvolume; the other can produce, in certain situations, a genuine localisation of gravity near the worldvolume but not via a technically consistent embedding. So, in the latter situation, the theory’s dynamics remains higher-dimensional but there can still be a lower-dimensional effective-theory interpretation of the dynamics at low worldvolume momenta / large worldvolume distances. This paper examines the conditions for such a gravity localisation to be possible. Localising gravity about braneworld spacetimes requires finding solutions to transverse-space self-adjoint Sturm-Liouville problems admitting a normalisable zero mode in the noncompact transverse space. This in turn requires analysis of Sturm-Liouville problems with radial singular endpoints following a formalism originating in the work of Hermann Weyl. Examples of such gravity-localising braneworld systems are found and analysed in this formalism with underlying “skeleton” braneworlds of Salam-Sezgin, resolved D3-brane and Randall-Sundrum II types.

Abstract This study evaluates silver-doped carbon dots (AgCDs) as a novel agent for chemical castration using a rat model. Six groups of rats (five males and ten females each, except for the surgical group which had only males) were utilized to compare the effects of different concentrations of AgCDs. The groups included control, sham, and three experimental groups injected with 1.25, 50, and 200 µg/mL AgCDs, respectively, along with a surgical castration group. Testosterone levels, sperm parameters, fertility index, oxidative damage, histopathological parameters, and gene expression of P53, Bax, Bcl-2, caspase-3, AKT, and PI3K were analyzed. Results demonstrated that the high-dose AgCDs group significantly reduced testosterone levels, sperm concentration, and motility, resulting in a decreased fertility index. MDA and NO significantly increased, while CAT, SOD, GPx, and TAC significantly reduced in the chemically castrated groups. Histological and genes expression analysis also revealed apoptosis and testicular damage in the AgCDs groups, indicated by significant increases in P53, Bax, and Caspase-3 levels, and significant reductions in AKT, PI3K, and Bcl-2. Based on these findings, AgCDs could be considered a potent and efficient agent for chemical castration, offering a less invasive, cost-effective solution with potential applications for population control.

Abstract Hyperspectral image (HSI) data has a wide range of valuable spectral information for numerous tasks. HSI data encounters challenges such as small training samples, scarcity, and redundant information. Researchers have introduced various research works to address these challenges. Convolution Neural Network (CNN) has gained significant success in the field of HSI classification. CNN’s primary focus is to extract low-level features from HSI data, and it has a limited ability to detect long-range dependencies due to the confined filter size. In contrast, vision transformers exhibit great success in the HSI classification field due to the use of attention mechanisms to learn the long-range dependencies. As mentioned earlier, the primary issue with these models is that they require sufficient labeled training data. To address this challenge, we proposed a spectral-spatial feature extractor group attention transformer that consists of a multiscale feature extractor to extract low-level or shallow features. For high-level semantic feature extraction, we proposed a group attention mechanism. Our proposed model is evaluated using four publicly available HSI datasets, which are Indian Pines, Pavia University, Salinas, and the KSC dataset. Our proposed approach achieved the best classification results in terms of overall accuracy (OA), average accuracy (AA), and Kappa coefficient. As mentioned earlier, the proposed approach utilized only 5%, 1%, 1%, and 10% of the training samples from the publicly available four datasets.

Abstract Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder with a global impact, yet its pathogenesis remains poorly understood. While age, metabolic abnormalities, and accumulation of neurotoxic substances are potential risk factors for AD, their effects are confounded by other factors. To address this challenge, we first utilized multi-omics data from 87 well phenotyped AD patients and generated plasma proteomics and metabolomics data, as well as gut and saliva metagenomics data to investigate the molecular-level alterations accounting the host-microbiome interactions. Second, we analyzed individual omics data and identified the key parameters involved in the severity of the dementia in AD patients. Next, we employed Artificial Intelligence (AI) based models to predict AD severity based on the significantly altered features identified in each omics analysis. Based on our integrative analysis, we found the clinical relevance of plasma proteins, including SKAP1 and NEFL, plasma metabolites including homovanillate and glutamate, and Paraprevotella clara in gut microbiome in predicting the AD severity. Finally, we validated the predictive power of our AI based models by generating additional multi-omics data from the same group of AD patients by following up for 3 months. Hence, we observed that these results may have important implications for the development of potential diagnostic and therapeutic approaches for AD patients.

Abstract Background/Objectives Childhood obesity, particularly in girls, is linked to early puberty onset, heightening risks for adult-onset diseases. Addressing childhood obesity and precocious puberty is vital to mitigate societal burdens. Despite existing costly and invasive medical interventions, introducing lifestyle-based alternatives is essential. Our study investigates alternate-day fasting’s (ADF) impact on pubertal development in normal-weight and high-fat diet (HFD)-induced obese female mice. Methods Four groups of female mice were utilized, with dams initially fed control chow during and before pregnancy. Post-parturition, two groups continued on control chow, while two switched to an HFD. Offspring diets mirrored maternal exposure. One control and one HFD group were subjected to ADF. Morphometry and hormone analyses at various time points were performed. Results Our findings demonstrate that ADF in normal-weight mice led to reduced body length, weight, uterine, and ovarian weights, accompanied by delayed puberty and lower levels of sex hormones and growth hormone (GH). Remarkably, GH treatment effectively prevented ADF-induced growth reduction but did not prevent delayed puberty. Conversely, an HFD increased body length, induced obesity and precocious puberty, and altered sex hormones and leptin levels, which were counteracted by ADF regimen. Our data indicate ADF’s potential in managing childhood obesity and precocious puberty. Conclusions ADF reduced GH and sex hormone levels, contributing to reduced growth and delayed puberty, respectively. Therefore, parents of normal-weight children should be cautious about prolonged overnight fasting. ADF prevented HFD-induced obesity and precocious puberty, offering an alternative to medical approaches; nevertheless, further studies are needed for translation into clinical practice.

ABSTRACT Introduction Neonatal diabetes mellitus (NDM) is a rare non‐immunological monogenic disorder characterized by hyperglycemic conditions primarily occurring within the first 6 months of life. The majority of cases are attributed to pathogenic variants in genes affecting beta‐cell survival, insulin regulation, and secretion. This study aims to investigate the genetic landscape of NDM in Iran. Methods We recruited a total of 135 patients who were initially diagnosed with diabetes at

The objective of this work was to assess the potential effect of bone marrow mast cells (BMMCs) on burn wound healing in rats. We included 45 male rats into three groups of 15 animals each: CNTRL group: We treated the burn wounds with normal saline (0.1 ml). TRTMENT group: In this group, the burn wounds were treated with bone marrow mast cells (1× 106/ml). SSD (Positive control) group: In this group, the wounds were treated with silver sulfadiazine 1% ointment. Wound area reduction measurements, histopathological studies, and biochemical assessments levels showed significant differences between rats in TRTMENT group in comparison with other groups (p < 0.05). Accelerated repair of the wounds in TRTMENT group showed that local application of BMMCs could be taken into consideration in burn wound healing.

Effects of interaperitoneal administration of α-tocopherol acetate on ischemia-reperfusion injury in ovaries torsion and detorsion were studied using a cat ovary model. Twenty healthy female DSH cats ~3 kg were randomized into five experimental groups (n = 5): Group SHAM: The cats underwent only celiotomy. Group Ischemia: A 3-hour ischemia only. Group I/R: A 3-hour ischemia and a 3-hour reperfusion. Group I/ATA: A 3-hour ischemia only and 10 mg/kg intraperitoneal administration (IP) of α-tocopherol 2.5 hours after induction of ischemia. Group I/R/ATA: A 3-hour ischemia, 3-hour reperfusion, and 10 mg/kg IP of α-tocopherol 2.5 hours after induction of ischemia. Animals treated with ATA showed significantly ameliorated development of ischemia and reperfusion tissue injury compared to those of other groups (p < 0.05). The significantly higher values of SOD, tGSH, GPO, GSHRd, and GST were observed in I/R/ATA animals compared to those of other groups (p = 0.001). Damage indicators (NOS, MDA, MPO, and DNA damage level) were significantly lower in I/R/ATA animals compared to those of other groups (p = 0.001). Intraperitoneal administration of ATA could be helpful in minimizing ischemia-reperfusion injury in ovarian tissue exposed to ischemia.

Abstract In this study, a spatiotemporal disaggregated simulation model was developed based on water–food–energy (WFE) nexus approach to assess water and food supply security considering ecosystem provisioning services. The main components of the developed model in this study (SD-WFE model) are population, water, agriculture, and energy modules. The model, which was developed using system dynamics (SD) approach, was utilized to simulate effectiveness of sectoral municipal, industrial, and agricultural water and energy consumption management and environmental protection policies in improving ecosystem provisioning services during a 20-year period. Through sensitivity analysis utilizing the Monte Carlo model, the study addresses the formulation of sustainable water resource policies across four main categories: water demand management, water supply management, food resource management, and energy resource demand management. Additionally, it explores the integration of policies within an optimal framework. The simulation of proposed solutions revealed that a combination of water demand management and food resource management yielded the most promising outcome. Specifically, the recommended solution entails enhancing water irrigation efficiency by 18% through the expansion of pressurized irrigation network coverage, adjusting cropping patterns by 14%, reducing agricultural product losses by 8% via improved food supply management, minimizing food demand by 9% due to reduced food consumption losses, and achieving an annual 10% increase in crop performance. These selected policies form the foundation for sustainable water resource management strategies.

Abstract Background Although unplanned deliveries in ambulances are uncommon, Emergency Medical Services (EMS) providers may encounter this situation before reaching the hospital. This research aims to gather insights from Emergency Medical Technicians (EMTs), midwives, and expectant mothers to examine the causes of giving birth in ambulances and the challenges EMTs, pregnant women, and midwives face during delivery. Methods A qualitative study was conducted, and 28 EMTs, midwives, and pregnant women who had experience with pre-hospital births in the ambulance were interviewed. Data were analyzed using thematic content analysis. The MAXQDA/10 software was employed for data analysis and code extraction. Results The analysis of the interviews revealed two main categories: factors that cause delivery in the ambulance and its challenges. The factors include cultural problems, weak management, and inaccessibility to facilities. The challenges consist of fear and anxiety, native culture, and lack of resources. Conclusions Several approaches should be implemented to reduce the number of births in ambulances and Pre-hospital Emergency Medical Services (PEMS). These include long-term community cultural activities, public education, awareness campaigns, education and follow-up for pregnant women, and improved accessibility to health facilities. Additionally, EMTS need to receive proper education and training for ambulance deliveries. Enhancing ambulance services and supporting EMTs in dealing with litigation claims are also critical.

Background. Universities have established a system of periodic evaluation and accreditation in order to manage the quality of education, enhance their physical resources and educational equipment, and improve their human resources. This study aimed to conduct an analysis of second-generation institutional accreditation standards for medical sciences universities from the experts' perspective. Methods. The present research was a qualitative study with an inductive approach conducted at Tabriz University of Medical Sciences between the years 2019- 2022. The sampling method was purposeful, and data were collected through semi-structured interviews with 34 managers, officials of development offices, and experts involved in the accreditation programs of educational institutions. As for study validation, the four criteria of Guba and Lincoln (i.e., credibility, dependability, confirmability, and transferability) were used. As for data analysis, MAXQDA 20, a software program designed for computer-assisted qualitative and mixed-methods data analysis, was used. The interview texts were analyzed using the content analysis method. Results. The results of the content analysis identified 204 initial codes, 9 subcategories, and 2 main categories (the strengths and weaknesses of the content). The subcategories of strengths included standardization, improvement of educational processes, development of assessment areas, restructuring of educational structure, benchmarking global experiences, and transparency in criteria. The subcategories of weaknesses included structural weaknesses, lack of validity, and ambiguity in criteria. Conclusion. The process of analyzing the content of accreditation standards for educational institutions periodically and obtaining regular feedback will lead to the enhancement of the standards and the realization of activities, ultimately resulting in the improvement of educational quality and the dynamism of the community.

The purpose of this study was to systematically present and present a meta-combination of research related to acceptance and commitment education for high school students with stuttering disorder. The research was qualitative using a hybrid strategy with a synthetic research approach and considering the seven-step model of Sandlowski and Barso. Required data by keyword search Act, Acceptance and Commitment, Stuttering, Transformational Nerve Disorder in Library Resources, Theses and Articles in ERIC, GoogleSchoolar, ProQuest, PubMed, Science Direct, Scopus, Springer Databases Magiran, Irandoc was collected between 1990 and 2021. It was used to search internal and external databases separately and in combination. Theoretical bases and main and combined themes were extracted, content analysis and classified. The results of the review and analysis of studies and researches showed that the act training program has been effective in the fields of acceptance and commitment training. The findings of this study, by specifying the nature of the admission and commitment education program, show that according to the existing theoretical and experimental background, this idea can be designed as an educational package for students with stuttering.

Abstract Household food consumption is a major driver of environmental impacts globally. Promoting sustainable consumption practices is crucial for addressing the challenges of resource depletion, food waste, and climate change. This study investigates the role of media literacy in fostering sustainable consumption awareness and behavior. A total of 432 Iranian consumers participated in the study by completing an online structured questionnaire. The data was analyzed using partial least squares structural equation modeling (PLS-SEM), revealing that the different aspects of media literacy, including usage, accessibility, content generation, and critical understanding, accounted for 93% of the variance in sustainable consumption awareness. Additionally, these factors explained 51% of the variance in sustainable consumption intention. The combined influences of sustainable consumption awareness and intention accounted for 87% of the variance in sustainable consumption behavior. To promote sustainable consumption, it is recommended to establish dedicated networks and channels that focus on delivering sustainable and healthy consumption content. Furthermore, organizing programs featuring environmental experts and interactive platforms, such as question-and-answer panels, can enhance critical understanding among media-literate audiences and contribute to the adoption of more sustainable consumption practices.

Abstract Background Federal deregulation of opioid agonist therapies are an attractive policy option to improve access to opioid use disorder care and achieve widespread beneficial impacts on growing opioid-related harms. There have been few evaluations of such policy interventions and understanding effects can help policy planning across jurisdictions. Methods Using health administrative data from eight of ten Canadian provinces, this study evaluated the impacts of Health Canada’s decision in May 2018 to rescind the requirement for Canadian health professionals to obtain an exemption from the Canadian Drugs and Substance Act to prescribe methadone for opioid use disorder. Over the study period of June 2017 to May 2019, we used descriptive statistics to capture overall trends in the number of agonist therapy prescribers across provinces and we used interrupted time series analysis to determine the effect of this decision on the trajectories of the agonist therapy prescribing workforces. Results There were important baseline differences in the numbers of agonist therapy prescribers. The province with the highest concentration of prescribers had 7.5 more prescribers per 100,000 residents compared to the province with the lowest. All provinces showed encouraging growth in the number of prescribers through the study period, though the fastest growing province grew 4.5 times more than the slowest. Interrupted time series analyses demonstrated a range of effects of the federal policy intervention on the provinces, from clearly positive changes to possibly negative effects. Conclusions Federal drug regulation policy change interacted in complex ways with provincial health professional regulation and healthcare delivery, kaleidoscoping the effects of federal policy intervention. For Canada and other health systems such as the US, federal policy must account for significant subnational variation in OUD epidemiology and drug regulation to maximize intended beneficial effects and mitigate the risks of negative effects.

Abstract There are two major forms of solar energy that are typically utilized: photovoltaic and concentrated applications. The application of fractal glass texture to photovoltaic solar panels is a cutting-edge technique in the field of solar panels that generate electricity from exposure to light. When it comes to studying the environmental implications of a product during its development and commercialization, the life cycle assessment (LCA) approach is an excellent technique that can be utilized. The purpose of this study is to offer a thorough understanding of the product’s effects on the environment by taking into consideration a wide range of criteria, including environmental, economic, and other evaluations. Through the utilization of the life cycle assessment (LCA) methodology and the SimaPro software, this paper presents a comparative analysis of conventional solar panels and fractal glass texture panels. During the course of this research, 18 midpoint indicators and three endpoint indices were investigated. In addition, a sensitivity analysis has been carried out on the fractal property of the panel in order to evaluate the impact that it has on environmental impacts and damages. For the purpose of this study, three distinct levels of fractal coating were applied to the panel surface: one percent, three percent, and five percent. As a result of the data, it was determined that the “Photovoltaic cell single-Si wafer” and the “Transport, freight, sea, transoceanic tanker” had the most significant impact on the midpoint and endpoint indices for both panels, respectively. Furthermore, there is a direct association between the rise in fractal coating on panels and the reduction in environmental repercussions, approximately. This correlation exists because of several factors.

Abstract The authors present spatio‐temporally resolved wideband measurements of Sub‐Terahertz (Sub‐THz) reflection coefficients in the frequency range of 92–110 GHz. A stochastic model for single reflection fixed links that is capable of modelling random scattering from small‐scale discontinuities such as those encountered in complex structures in walls and partitions of buildings is presented. The model auto‐regressively produces filter coefficients that are fed into an Infinite‐Impulse‐Response (IIR) filter which convolves them with the spatio‐temporal series in order to generate the next output sample based on previous observations. The IIR filter allows for flexible stochastic generation of samples, and its parameters can be adjusted as needed to suit different channel conditions. A total of 20 suitable start‐up filter coefficients are generated from 21.7 % of the sample size for each complex delay tap distribution, which corresponds to 50 complex instances of the channel. These coefficients are then utilised to validate the remaining measured sample set. The model is in quantitative agreement with measurement statistics and can be used to construct relatively simple modified reflection coefficients that can be used in micro‐cellular ray‐optical network planning tools.

Background: Uterine and Cervical cancer survivors face challenges like the disruption of emotional and sexual relationships, struggle to maintain sexual life and intimacy, and the possibility of divorce. The study aimed to determine the effect of group counseling based on couples’ constructive communication on perceived spousal support in uterine and cervical cancer survivors.Methods: A randomized controlled trial on 40 women who survived uterine and cervical cancer were recruited using convenience sampling and then randomly allocated to a couple-based constructive communication intervention group and a routine cancer center care control group from June 2019 to March 2020 in Motahhari and Imam Khomeini hospitals in Urmia. The intervention group was involved in a group counseling session weekly for 5 weeks, regarding constructive couple communication skills. Perceived spouse support was assessed using the sources of social support scale which has 4 subscales informational, instrumental, emotional, and negative support before and one week after the end of the intervention in both groups. Data analysis was performed using SPSS version 24 through Independent and paired t-tests, Mann-Whitney U test, Wilcoxon, chi-square, and ANCOVA. P value

The aim of the present study was to investigate the impact of conceptual learning in Quran education based on the escape room game on the academic engagement of third-grade elementary school students. The research method was a semi-experimental pretest-posttest design with a control group. The statistical population of the study included all male third-grade elementary school students in Arak city during the academic year 2022-2023. The convenience sampling method was used to select the sample. Accordingly, 48 students from the third-grade elementary school were selected, and then the selected sample was randomly assigned to experimental (24 students) and control (24 students) groups. Data were collected using the Reeve Academic Engagement Questionnaire (2013). The experimental group received training on the third-grade Quran education using the escape room computer game in 6 sessions, while the control group received conventional training. Descriptive statistical methods (measures of central tendency and dispersion) and inferential statistics (independent t-test and analysis of covariance) were used for data analysis. The findings indicated a significant difference in academic engagement between the experimental and control groups after adjusting pretest scores. Therefore, the results of this study suggest the positive role of using innovative technologies in increasing students' academic engagement in Quran education, proposing the incorporation of gamified conceptual learning into the Quran curriculum in the elementary education department.

The digital world provides many opportunities for marketers to reach customers. However, in the fast-paced world, finding new and innovative ways to advertise and sell products and services is very important. Due to the advancement of artificial intelligence and its development in the field of advertising and sales, professionals now have the tools to completely redefine the current understanding of branding, marketing, advertising and sales. The growing popularity of the Internet and the increased use of mobile devices are generating massive amounts of consumer data that feed artificial intelligence-based systems. This research is a type of mixed research with a qualitative and quantitative approach, which is a survey descriptive study in terms of its purpose, application, and in terms of data collection. The statistical population of the research was managers and experts in the field of digital marketing and IT in the field of advertising and sales, who were selected using the snowball sampling method. In the qualitative part, the tools for collecting information were library and articles review, interviews, and in the quantitative part, questionnaires. In the qualitative part of the data analysis method, using the theme analysis that was compiled with MAXQDA software and using the coding method, and in the quantitative part, the analysis method was based on Kendall's correlation test. According to the results of the research, 7 main themes, 22 sub-themes and 44 codes were discovered, which included the consequences of using artificial intelligence and machine learning in advertising and sales

Objective(s): Renal and testicular disorders are primarily associated with oxidative damage and inflammation. Here, alpha-pinene (a type of monoterpene) was investigated for its effect on oxidative/nitrosative stress and the expression of inflammatory and apoptotic factors in the kidneys and testes of rats treated with CCl4.Materials and Methods: CCl4 was injected intraperitoneally (IP) at a dose of 2 ml/kg (twice a week for six weeks). Alpha-pinene (50 mg/kg/day, IP) was also treated during the same period. Results: CCl4 increased the level of malondialdehyde (P

This research aimed to determine the effectiveness of intervention program based on resilience and forgiveness in irritability and learning behavior in Bullying Victims. The research design was a semi-experimental pre-test and post-test type with a control group and a three-month follow-up period. The research sample included 30 bullying victims’ students, in the second secondary school in Bostan Abad city (Iran) in the academic year 2024-2023, which were selected through the purposeful sampling method. The measurement instruments included the Bullying Victim Questionnaire, Irritability Scale, and Learning Behavior Scale. The intervention program based on resilience and forgiveness was implemented in eight 45-minute sessions, during eight weeks in a group separated by gender for the experimental group, and the control group did not receive any training. Analysis of variance with repeated measure and Tukey and Bonferroni post hoc tests were used to analyze the data. The results showed that the intervention program based on resilience and forgiveness significantly reduced irritability and increased the learning behavior of bullying victims’ students. Therefore, given these findings using such comprehensive programs by education authorities at the schools is recommended.

Renal cavernous hemangioma is a rare benign tumor. This case report describes a 44-year-old male who was incidentally found to have a renal mass during an abdominal and pelvic ultrasound. The patient's abdominal ultrasound revealed a mass, which was further evaluated with a CT scan. The CT findings suggested renal cell carcinoma. Suspecting malignancy, the patient underwent radical nephrectomy. Histopathological and immunohistochemical examinations ultimately diagnosed the mass as a cavernous hemangioma. Despite its benign nature, the patient was followed up with a control ultrasound three months post-surgery. This case is presented due to the significant clinical and radiological resemblance of this tumor to renal carcinomas, highlighting the importance of considering benign tumors in differential diagnoses.

Rhizomania destroys sugar beet globally, but breeding disease-resistant genotypes is crucial in fighting it. In this study, 13 modern genotypes were examined based on the list provided by the Iraniai Seed Registration and Certification Institute. Genotypes grown in a randomized complete block design, with four replications in Iran's Karaj, Mashhad, Miandoab, Shiraz, and Hamedan stations. Results revealed that F-21375 and F-21092 genotypes achieved the highest white sugar yield in all five investigated stations. The results of additive mean effect multiplicative interaction (AMMI) analysis based on white sugar yield showed that the additive effects of genotype and environment and the multiplicative effect of G×E accounted for 13.11, 51.29, and 10.60% of the total data variance, respectively. The AMMI stability parameters identified the F-21376 genotype as a stable variety that produces a high white sugar yield in five locations. Also, the first two components of the interaction effect (G×E) explained 80.70% of the variance. The biplot analysis showed that F-21376 was the genotype that produced the greatest white sugar yield and stability in infected conditions. Based on the results of the multi-trait stability index (MTSI), F-21375, and F-21372 genotypes were selected as ideal genotypes. Finally, it can be concluded that two genotypes, F-21375 and F-21376, can be introduced as high-yielding and disease-resistant genotypes in the beet cultivation areas due to their white sugar yield and stability in experimental environments.

Abstract Background Radiation-induced fibrosis (RIF) is an important late complication of radiation therapy, and the resulting damaging effects of RIF can significantly impact reconstructive outcomes. There is currently a paucity of effective treatment options available, likely due to the continuing knowledge gap surrounding the cellular mechanisms involved. In this study, detailed analyses of irradiated and non-irradiated human skin samples were performed incorporating histological and single-cell transcriptional analysis to identify novel features guiding development of skin fibrosis following radiation injury. Methods Paired irradiated and contralateral non-irradiated skin samples were obtained from six female patients undergoing post-oncologic breast reconstruction. Skin samples underwent histological evaluation, immunohistochemistry, and biomechanical testing. Single-cell RNA sequencing was performed using the 10X single cell platform. Cells were separated into clusters using Seurat in R. The SingleR classifier was applied to ascribe cell type identities to each cluster. Differentially expressed genes characteristic to each cluster were then determined using non-parametric testing. Results Comparing irradiated and non-irradiated skin, epidermal atrophy, dermal thickening, and evidence of thick, disorganized collagen deposition within the extracellular matrix of irradiated skin were readily appreciated on histology. These histologic features were associated with stiffness that was higher in irradiated skin. Single-cell RNA sequencing revealed six predominant cell types. Focusing on fibroblasts/stromal lineage cells, five distinct transcriptional clusters (Clusters 0–4) were identified. Interestingly, while all clusters were noted to express Cav1, Cluster 2 was the only one to also express Cav2. Immunohistochemistry demonstrated increased expression of Cav2 in irradiated skin, whereas Cav1 was more readily identified in non-irradiated skin, suggesting Cav1 and Cav2 may act antagonistically to modulate fibrotic cellular responses. Conclusion In response to radiation therapy, specific changes to fibroblast subpopulations and enhanced Cav2 expression may contribute to fibrosis. Altogether, this study introduces a novel pathway of caveolin involvement which may contribute to fibrotic development following radiation injury.

Abstract Introduction Brain metastases (BMs) are common in lung cancer (LC) and are associated with poor prognosis. Magnetic resonance imaging (MRI) plays a vital role in the detection, diagnosis and management of BMs. This review summarises recent advances in MRI techniques for BMs from LC. Methods This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines. A comprehensive literature search was conducted in three electronic databases: PubMed, Scopus and the Web of Science. The search was limited to studies published between January 2000 and March 2023. The quality of the included studies was evaluated using appropriate tools for different study designs. A narrative synthesis was carried out to describe the key findings of the included studies. Results Sixty‐five studies were included. Standard MRI sequences such as T1‐weighted (T1w), T2‐weighted (T2w) and fluid‐attenuated inversion recovery (FLAIR) were commonly used. Advanced techniques included perfusion‐weighted imaging (PWI), diffusion‐weighted imaging (DWI) and radiomics analysis. DWI and PWI parameters could distinguish tumour recurrence from radiation necrosis. Radiomics models predicted genetic mutations and the risk of BMs. Diagnostic accuracy was improved with deep learning (DL) approaches. Prognostic factors such as performance status and concurrent chemotherapy impacted survival. Conclusion Advanced MRI techniques and specialised MRI methods have emerging roles in managing BMs from LC. PWI and DWI improve diagnostic accuracy in treated BMs. Radiomics and DL facilitate personalised prognosis and treatment. Magnetic resonance imaging plays a key role in the continuum of care for BMs of patients with LC, from screening to treatment monitoring.

Abstract Background The auxin/indole-3-acetic acid (Aux/IAA) gene family is a crucial element of the auxin signaling pathway, significantly influencing plant growth and development. Hence, we conducted a comprehensive investigation of Aux/IAAs gene family using the Sp75 and Monoe-Viroflay genomes in spinach. Results A total of 24 definitive Aux/IAA genes were identified, exhibiting diverse attributes in terms of amino acid length, molecular weight, and isoelectric points. This diversity underscores potential specific roles within the family, such as growth regulation and stress response. Structural analysis revealed significant variations in gene length and molecular weight. These variations indicate distinct roles within the Aux/IAA gene family. Chromosomal distribution analysis exhibited a dispersed pattern, with chromosomes 4 and 1 hosting the highest and lowest numbers of Aux/IAA genes, respectively. Phylogenetic analysis grouped the identified genes into distinct clades, revealing potential evolutionary relationships. Notably, the phylogenetic tree highlighted specific gene clusters suggesting shared genetic ancestry and potential functional synergies within spinach. Expression analysis under NAA treatment unveiled gene-specific and time-dependent responses, with certain genes exhibiting distinct temporal expression patterns. Specifically, SpoIAA5 displayed a substantial increase at 2 h post-NAA treatment, while SpoIAA7 and SpoIAA9 demonstrated continuous rises, peaking at the 4-hour time point. Conclusions These observations indicate a complex interplay of gene-specific and temporal regulation in response to auxin. Moreover, the comparison with other plant species emphasized both shared characteristics and unique features in Aux/IAA gene numbers, providing insights into the evolutionary dynamics of this gene family. This comprehensive characterization of Aux/IAA genes in spinach not only establishes the foundation for understanding their specific functions in spinach development but also provides a valuable resource for experimental validation and further exploration of their roles in the intricate network of auxin signaling pathways.

The present study aimed to investigate the effect of integrating reality-based instructional strategy (based on the Education for the Future project) on self-directed learning and academic motivation of mechanical engineering students at the Faculty of Engineering and Technology of Arak University. The research method was a quasi-experimental pre-test-post-test design with a control group. The statistical population of the study included all mechanical engineering students of Arak University in the academic year 2023-2024. 28 students who had taken the Pressure Vessels course in the second semester of the academic year were selected using the available sampling method and then the selected sample was randomly divided into experimental (14 people) and control (14 people) groups. To collect data, the Self-Directed Learning Questionnaire of Fisher and the Academic Motivation Questionnaire of Gunuc & Kuzu were used. The experimental group was trained in the Pressure Vessels course using a reality-based instructional strategy integrated with a reality-based instructional strategy for 26 sessions, and the control group was trained in the usual way and by attending university classes. To analyze the data, multivariate analysis of covariance (MANCOVA) was used. The findings showed that after adjusting the pre-test scores, there was a significant difference between the experimental and control groups in the variables of self-directed learning and academic motivation. Therefore, the results of this research indicate that considering the learning styles of new generation learners, if a reality-based instructional strategy is used for these people, it will play an important role in increasing self-directed learning and academic motivation of students and will facilitate the transfer of learning to other situations.

Background:. Recent advancements in artificial intelligence (AI) have reshaped telehealth, with AI chatbots like Chat Generative Pretrained Transformer (ChatGPT) showing promise in various medical applications. ChatGPT is capable of offering basic patient education on procedures in plastic and reconstructive surgery (PRS), yet the preference between human AI VideoBots and traditional chatbots in plastic and reconstructive surgery remains unexplored. Methods:. We developed a VideoBot by integrating ChatGPT with Synthesia, a human AI avatar video platform. The VideoBot was then integrated into Tolstoy to create an interactive experience that answered four of the most asked questions related to breast reconstruction. We used Zapier to develop a ChatGPT-integrated chatbot. A 16-item survey adapted from the 2005 validated measurement of online trust by Corritore et al was distributed online to female participants via Amazon Mechanical Turk. Results:. A total of 396 responses were gathered. Participants were 18 to 64 years old. Perceptions of truthfulness, believability, content expertise, ease of use, and safety were similar between the VideoBot and chatbot. Most participants preferred the VideoBot compared with the traditional chatbot (63.5% versus 28.1%), as they found it more captivating than the text-based chatbot. Of the participants, 77% would have preferred to see someone who they identified with in terms of gender and race. Conclusions:. Both the VideoBot and text-based chatbot show comparable effectiveness, usability, and trust. Nonetheless, the VideoBot’s human-like qualities enhance interactivity. Future research should explore the impact of race and gender concordance in telehealth to provide a more personalized experience for patients.

BackgroundEcotourism as a responsible travel to natural areas is proposed as a strategy for forest conservation by enhancing the livelihoods of local communities. However, engaging in environmentally friendly behaviors during forest visit is a crucial factor in achieving this conservation. This study aimed to examine the determinants of intention and actual environmental behavior among ecotourists during their visits to forests.MethodsUtilizing social cognitive theory as the theoretical framework, the data from 409 visitors of recreational forest were analyzed. After confirming the validity and reliability of the data, structural equation modeling was employed for analysis.ResultsThe results indicated that the model could explain 59% of the behavioral intention and 27% of the actual environmentally friendly behaviors of ecotourists during their forest visits. Additionally, social influence and the behaviors of other ecotourists were identified as two significant determinants of individuals’ behavioral intention. Self-efficacy and behavioral intention also emerged as significant factors which shape the actual environmental behaviors of tourists, positively.DiscussionThe findings suggest that social expectations, learning from fellow tourists, and enhancing individuals’ abilities while addressing barriers to exhibiting environmentally friendly behaviors should be prioritized in promotional planning for ecotourism.

Floods pose significant threats to urban areas, resulting in substantial human and financial losses annually. The vulnerability of key urban centers to these risks diminishes their efficiency, leading to public dissatisfaction and service deficiencies. Recognizing and enhancing the resilience of essential buildings becomes crucial in mitigating these challenges. This study employs a comprehensive approach to achieve a resilience model for critical buildings facing floods. The research process involves the identification of city assets based on leveling criteria, utilizing GIS technology for spatial mapping. HECRAS software aids in river flow modeling, identifying areas lacking flood-carrying capacity. By overlaying vulnerable gravity centers with flood-prone regions, building resilience components are computed through structural factor analysis and LISREL modeling. The study identifies ten key criteria. Further analysis includes resilience modeling using TOPSIS and AHP methods. The positive ideal and negative ideal solutions are determined, resulting in the grading of building resilience. Notably, the balance redundancy index with cascading potential effects attains the highest positive ideal value at 0.257, while the resistance to a level of stress index achieves the lowest negative ideal value at 0.02. This comprehensive approach and modeling contribute to the understanding and enhancement of urban building resilience in the face of flood threats.

IntroductionIn the context of forest conservation, individuals’ attitude can significantly influence their intentions and subsequent behaviors towards conserving forests. However, there is a research gap when it comes to understanding the determinants of individuals’ attitude towards forests conservation. To address this gap, the present study aimed to investigate the influence of variables associated with values from value-belief-norm theory, awareness of consequences, and ascription of responsibility from norm activation model on individuals’ attitudes as main determinant of behavior intention.MethodsThe Data of study was collected from a sample of 200 students from Behbahan University, Iran. through a questionnaire designed specifically for this purpose. The validity and reliability of questionnaire were confirmed. Structural equation modeling was employed to analyze the collected data.ResultsThe findings of the study revealed that the examined variables were able to describe 88.6% of the variance in individuals’ attitude towards forest conservation. Specifically, it was found that biospheric (ƛ= 0.097) and altruistic (ƛ= 0.385) values, ascription of responsibility (ƛ= 0.150), and awareness of consequences (ƛ= 0.380) had significant and positive effects on individuals’ attitude towards forest conservation. On the other hand, egoistic values exhibited a significant and negative impact (ƛ= –0.071) on individuals’ attitude.DiscussionThese research findings hold significant implications for planners and policymakers involved in forest conservation efforts. By understanding the factors that shape individuals’ conservation attitudes, decision-makers can develop targeted strategies and interventions to strengthen positive attitudes towards forest conservation. Given the positive influence of biospheric values and awareness of consequences, developing awareness-raising programs to enhance individuals’ environmental knowledge and the awareness of outcomes of their conservation actions can be considered as strategy to strengthen public’s attitude and improvement their participation in forest conservation projects.

Industrial wastewater treatment increasingly relies on membrane separation, with ceramic membranes offering many advantages such as thermal stability and pH resistance. The resistance of ceramic membranes to extreme pH conditions indicates their ability to maintain structure and performance when exposed to highly acidic or alkaline environments. A high-permeability ceramic nanofiltration membrane was developed, boasting excellent rejection rates through a multilayer asymmetric design. Initially, two tubular porous supports, mullite and mullite-alumina, with a weight percent of 50, were fabricated using the extrusion method. Subsequently, a colloidal sol of titania (TiO2) and titania-zirconia (TiO2- ZrO2) was prepared via the sol–gel method and coated on the ceramic supports using the dip-coating method. After analyzing the membrane microstructure using SEM, XRD, and BET, the efficiency of the membranes in treating synthetic oily wastewater was evaluated. The results underscore the significant impact of the Donnan exclusion mechanism on the rejection of nanofiltration (NF) membranes. An increase in pressure led to a rise in rejection rates up to 7 bars. The Chemical Oxygen Demand (COD) rejection for mullite-titania zirconia (MTZ) and mullite-alumina-titania zirconia (MATZ) membranes was 98.65 % and 98 %, respectively. The pure water permeability test results for mullite and mullite-alumina supports, as well as MTZ and MATZ membranes, were recorded as 254, 382, 70, and 89 L bar-1m-2h−1, respectively.

Urban forests have a critical role in providing a wide array of ecosystem services that significantly contribute to enhancing the quality of life for urban residents. To ensure the sustainable management of urban forests, citizens’ participation is a crucial component of management. Payment for ecosystem services of urban forests is a mechanism for financial participation of citizens. Identifying the influencing factors on individuals' willingness to pay (WTP) is a crucial step in planning for this endeavor. In determining these factors, there has been limited attention to psychological factors. Therefore, this study employed an extended model of the theory of planned behavior, incorporating two new variables including perceived trustworthiness in the payment mechanism (PTPM) and environmental knowledge (EK). It examined the factors influencing individuals' WTP for ecosystem services provided by urban forests. The study results demonstrated that the extended model improved the explanatory power for the variance in individuals' WTP compared to the original model. The results revealed that PTPM, EK, perceived behavioral control, attitudes, and subjective norms had the greatest impact on individuals' WTP, respectively. These findings provide recommendations for policymaking and planning regarding payment for ecosystem services in urban forests.

Objective To estimate the effect of (a) the COVID-19 pandemic and (b) COVID-19 restriction stringency on daily minutes of device-measured moderate-to-vigorous physical activity (MVPA).Design Physical activity data were collected from the INTerventions, Equity, Research and Action in Cities Team (INTERACT) cohorts in Montreal, Saskatoon and Vancouver before (May 2018 to February 2019, ‘phase 1’) and during the pandemic (October 2020 to February 2021, ‘phase 2’). We estimated the effect of the two exposures by comparing daily MVPA measured (a) before vs during the pandemic (phase 1 vs phase 2) and (b) at different levels of COVID-19 restriction stringency during phase 2. Separate mixed effects negative binomial regression models were used to estimate the association between each exposure and daily MVPA, with and without controlling for confounders. Analyses were conducted on person-days with at least 600 min of wear time. Effect modification by gender, age, income, employment status, education, children in the home and city was assessed via stratification.Setting Montreal (Quebec), Saskatoon (Saskatchewan) and Vancouver (British Columbia), Canada.Main outcome measure Daily minutes of MVPA, as measured using SenseDoc, a research-grade accelerometer device.Results Daily minutes of MVPA were 21% lower in phase 2 (October 2020 to February 2021) compared with phase 1 (May 2018 to February 2019), controlling for gender, age, employment status, household income, education, city, weather and wear time (rate ratio=0.79, 95% CI 0.69, 0.92). This did not appear to be driven by changes in the sample or timing of data collection between phases. The results suggested effect modification by employment, household income and education. Restriction stringency was not associated with daily MVPA between October 2020 and February 2021 (adjusted rate ratio=0.99, 95% CI 0.96, 1.03).Conclusions Between October 2020 and February 2021, daily minutes of MVPA were significantly lower than 2 years prior, but were not associated with daily COVID-19 restriction stringency.

Alzheimer's disease (AD) is characterized by progressive neurodegeneration, memory loss, and cognitive impairment leading to dementia and death. The blood-brain barrier (BBB) prevents the delivery of drugs into the brain, which can limit their therapeutic potential in the treatment of AD. Therefore, there is a need to develop new approaches to bypass the BBB for appropriate treatment of AD. Recently, focused ultrasound (FUS) has been shown to disrupt the BBB, allowing therapeutic agents to penetrate the brain. In addition, microbubbles (MBs) as lipophilic carriers can penetrate across the BBB and deliver the active drug into the brain tissue. Therefore, combined with FUS, the drug-encapsulated MBs can pass through the ultrasound-disrupted zone of the BBB and diffuse into the brain tissue. This review provides clear and concise statements on the recent advances of the various FUS-mediated MBs-based carriers developed for delivering AD-related drugs. In addition, the sonogenetics-based FUS/MBs approaches for the treatment of AD are highlighted. The future perspectives and challenges of ultrasound-based MBs drug delivery in AD are then discussed.

Objectives Diabetes, a pressing global public health crisis, Diabetes, a global health crisis, is significantly impacted by social determinants, including neighborhood characteristics. This study aims to to assess whether relocation from a high poverty to lower poverty neighbourhood is associated with a reduction in T2D incidence. Methods and Results This population-based, propensity-matched cohort study will use linked administrative health to examine the association between neighborhood relocation and T2D incidence. The study population will include adults (age ≥20 years) residing in high poverty urban neighborhoods between April 1st, 2002, to March 31st, 2021, as defined by an area Low-Income Measure - After Tax value of 38,730 dollars for a household size 4 based on the Canadian Census. Individuals will be followed for a new diagnosis of T2D using a validated algorithm based on hospitalization and physicians’ claims data. Propensity score matching will used to match individuals who moved from high-to-lower poverty neighbourhoods to one of two comparison groups: those moving from high-to-high poverty areas and those who remain in their original neighbourhood. Time-to-event analysis utilizing Cox proportional hazards regression with a robust variance estimator will be used to compare T2D incidence between matched groups. As a sensitivity analysis, non-propensity score modeling will be conducted using neighbourhood of residence as a time-varying covariate. The results of the aforementioned analyses will be presented during the conference. Implications By clarifying the link between neighborhood poverty and T2D incidence, the results will guide focused interventions to alleviate health inequalities in socioeconomically disadvantaged areas.

إن الصراع بين الحق والباطل قائم منذ ان خلق الله تعالى آدم (على نبينا وآله وعليه السلام)، وما زال مستمراً ما دام هناك منهجان وسيرتان، وسيستمر هذا الصراع حتى يأذن الله تعالى بانتصار الحق على الباطل، حيث يورث الله سبحانه الأرض لعباده الصالحين. ولكل طرف في الصراع قادته ورجاله الذين يدافعون عن منهجهم ووجودهم، فأتباع الحق يريدون للبشرية السعادة وللإنسانية القسط والخير، أما أهل الباطل ورموزه فلا يفكرون إلا في مصالحهم وأهوائهم، ويمارسون شتى أنواع الظلم، فلم يسلم الحرث والنسل من جورهم وفسادهم على مر الدهور. وللتأريخ فإن المسلمين السائرين على نهج علي وأولاده (عليهم السلام) منذ بزوغ فجر الإسلام الساطع وعلى طول التاريخ لم يكونوا يوماً ما مصدر قلق أو تفرقة للأمّة الإسلامية، فضلاً عن أن يكونوا منبع حرب وعدوان على غيرهم، ولم يمنحوا على مدى سيرتهم الطويلة سوى الرحمة والعفو والاحسان إلى بني البشر سواء أكانوا مسلمين أم كفار، بل لم يضعوا العراقيل ولم يصطنعوا الدمار ولا تمنوا الشر للغير، فضلاً عن زرع بذوره ونشر سمومه، سائرين على نهج الرسول الأكرم (صلى الله عليه وآله وسلـم) الذي نطق به التنـزيل ﴿وَمَا أَرْسَلْنَاكَ إِلَّا رَحْمَةً لِّلْعَالَمِينَ﴾، فهو الرحيم بأمته والشفيق عليهم، وكانت سيرته هادية إلى الخير والسعادة، وسار على نهجه أهل بيته وأولاده من بعده فهم أئمة الهدى ومصابيح الدجى (عليهم السلام).

An improved understanding of the oxidation resistance of HfC-TaC ultra-high temperature ceramics (UHTCs) is developed through modeling of the phase equilibria in the Hf-Ta-O system and HfO2-Ta2O5 isoplethal section. CALculation of PHAse Diagrams (CALPHAD) thermodynamic models of the systems are developed in conjunction with experimental data from the literature and first-principles calculations. Density functional theory (DFT) calculations accurately describe thermodynamic properties of binary oxides in the Hf-Ta-O system and predict cation disorder in Hf(n-5)/2Ta2On. The ternary modeling includes revised models of the Hf–O system and existing models of the Ta–O and Hf–Ta systems. The Hf(n-5)/2Ta2On ternary oxide series is modeled as three entropically stabilized solid solutions with disordered cation sublattices that increase in stability with structure size. Hf4Ta2O13 is considered a metastable phase based on the present models and phase diagram, consistent with the lack of experimental data supporting its stability. The calculated phase diagrams improve upon prior ones and predict optimal thermal resistance of HfC-TaC ceramics at compositions between 3HfC-1TaC and 4HfC-1TaC.

Fishermen all over the world have traditions to gather with their families and friends to give thanks for their harvest and the abundance of the sea. This study described the existence, implementation, and religious values of the Nadran tradition in the coastal areas of Pandeglang Regency of Banten, Indonesia. The research used qualitative research with the Anthropology of education as the data analysis tool, especially through cultural transmission theory. This research found that there had been a process of cultural transmission through the Nadran ceremony from one individual or group to another group. Then, in terms of context, the ceremony is still in accordance with past generations. However, in terms of content and method, there have been changes. It found that the philosophical value of the nadran tradition in the Islamic view is that culture is drawn to religion because in the Panimbang and Labuan areas, nadran events, which always used to use wayang golek (puppet shows), have now been replaced with other activities such as prayer together (istigosah), religious lectures, and other Islamic activities. It indicates the existing cultural norms inserted into Islamic religious and cultural values. Even though the buffalo head offerings are still used, this nadran expresses gratitude to God. Apart from being a tourist attraction, this nadran can also instill religious character values in the younger generation.

Abstract Depression is a major cause of disability and, if left untreated, can increase the risk of suicide. Evidence on the determinants of depression is incomplete, making it challenging to interpret results across studies. This study aims to identify the social, economic, environmental, political, and technological factors influencing the great recession in Iran. The study was conducted in two parts. The first step involved a literature review to identify the factors, using PubMed, Scopus, and Web of Science for the search. The reference lists of all identified articles were reviewed to find relevant studies, and the extracted information was summarized and reported descriptively. The second steps involved compiling and consulting 14 experts from different fields, using a framework analysis method. Twenty-four articles were used as primary sources of information, and a total of 28 factors were found to exist. After removing duplicates and related factors, 19 of these were subsequently declared as factors, resulting in a total of 36 determinants being identified. Most of these factors belong to the social category. The health policies implemented have a significant impact on disease risk factors and ultimately their occurrence. Political decisions and policy-making processes play a crucial role in all areas, particularly in addressing disease risk factors. Severe depression can disrupt all aspects of the healthcare system, underscoring the importance of access to care. Policies concerning physical education, transportation, nutrition, employment, green spaces, recreational facilities, and tobacco are vital in this context. The influence of health policies on disease risk factors and disease occurrence is profound. Severe depression can have far-reaching effects on the healthcare system, emphasizing the critical need for access to care. The formulation of policies to combat depression must be thoroughly evaluated in terms of economic, political, social, technological, and environmental factors. The findings suggest that addressing social inequalities and emphasizing the role of political action, as highlighted by the social determinants of health, should be top priorities in addressing depression. Efforts to prevent depression should incorporate ecological approaches that consider the impact of the socioeconomic environment on depressive symptoms.