Search

Abstract The electrical conductivity of the earth’s mantle can provide important information about geodynamic phenomena. East Asia is associated with complex tectonics and geodynamic processes. Hence, it is necessary to better understand the deep structure beneath East Asia. In this study, geomagnetic data obtained from East Asian observatories are employed to image the conductivity structure of the mantle at depths ranging from 410 to 900 km. First, the data are processed using the modified bounded influence remote reference processing (BIRRP) method and the ratio method is used to correct for the ocean effect. Thereafter, the stable C-response curves at the 27 observatories are estimated, and 1D electrical conductivity models for these observatories are established using the L-BFGS method. The conductivity-depth profiles reveal a heterogeneous distribution of the electrical conductivity beneath East Asia. The mantle transition zone (MTZ) beneath East China and Japan is found to be more conductive, whereas the MTZ beneath central and southern regions of China is more resistive. In East China, the dehydration of the stagnant Pacific slab may lead to an increase in the conductivity of the mantle minerals. There is also the possibility of upwelling of the thermal material from the lower mantle beneath the Japanese Island arc. In Northwest China, there exists a large high-conductive body beneath the Tarim area, which could indicate an upwelling of the Tarim mantle plume. Our results provide insights into the deep structure of the earth at the mantle scale.

Abstract This is the protocol for a Campbell systematic review. The objectives are as follows. We will solve the following questions: (1) What are the characteristics of skills training services for individuals experiencing or at risk of homelessness? (2) How effectively do the different skills training programs improve employment status, work and life skills, or housing stability? (3) What factors are associated with the variation in the effectiveness of skills training services?

Abstract This is the protocol for a Campbell systematic review. The objectives are as follows: (1) To evaluate the reporting quality of systematic reviews published in Chinese social science journals against the PRISMA and MOOSE standards; (2) To evaluate the methodology quality of systematic reviews published in Chinese social science journals against the AMSTAR‐2 and DART standards; and (3) To analyze other characteristics of systematic reviews published in Chinese social science journals using content analysis.

Spontaneous coronary artery dissection (SCAD) is an increasingly recognized cause of acute coronary syndromes. Fibromuscular dysplasia (FMD) is an idiopathic, nonatherosclerotic, and noninflammatory arterial disease that affects small- to medium-sized arteries that can result in multifocal aneurysms, stenosis, tortuosity, and dissections. Extracoronary FMD has been identified in approximately 70% of SCAD patients and it is recommended that all SCAD patients undergo screening for FMD once in their lifetime using computed tomography angiography from head to pelvis. This focused review for cardiologists outlines current approaches to diagnosis and management of patients with FMD. Résumé: La dissection spontanée de l’artère coronaire (DSAC) est une cause de plus en plus reconnue du syndrome coronarien aigu. La dysplasie fibromusculaire (DFM) est une maladie idiopathique, non athéroscléreuse et non inflammatoire qui affecte les petites et moyennes artères et peut entraîner des anévrismes multifocaux, une sténose, une tortuosité et des dissections. Une DFM extracoronarienne a été observée chez environ 70 % des patients présentant une DSAC. Il est recommandé que tous les patients présentant une DSAC devraient une fois dans leur vie subir un test de dépistage de la DFM au moyen d’une angiographie par tomodensitométrie de la tête au bassin. Cette analyse destinée aux cardiologues décrit les approches actuelles dans le diagnostic et la prise en charge des patients atteints de DFM.

Abstract Background and Aim Several factors influence women’s perception of their genitalia. Understanding the elements associated with genital self‑image (GSI) can significantly contribute to enhancing women’s sexual experiences. Therefore, the present study aimed to identify the predictors of GSI in Iranian women. Materials and methods This online cross-sectional study was conducted on 722 healthy married reproductive-aged women with records in Amol-Iran health centers during 2022. Participants were selected using a random sampling method from all the healthcare centers. Data were collected through a checklist of socio-demographic and obstetrics information, the Female Genital Self-Image Scale (FGSI), the 6-item Female Sexual Function Index (FSFI-6), the Female Sexual Distress Scale – revised (FSDS-R), and the Multidimensional Sexual Self-Concept Questionnaire (MSSCQ) for assessing sexual esteem and sexual satisfaction. The general linear model was employed to assess the impact of each independent variable (socio-demographic and obstetrics characteristics, sexual function, sexual distress, sexual esteem, and sexual satisfaction) on the dependent variable (GSI). Results The mean score of GSI was 21.70 ± 3.82. Based on the Pearson correlation test, there were significant correlations between GSI and sexual function, sexual esteem, sexual satisfaction, and sexual distress (r = 0.20, r = 0.43, r = 0.42, r = -0.28 respectively; p

Abstract Background Knowledge networks, such as Communities of Practice (CoP), are essential elements of knowledge management. They play a crucial role in assimilating various knowledge domains and converting individual knowledge into collective knowledge. This study aimed to assess the concept of knowledge networks and identify facilitators and barriers influencing knowledge sharing in infectious diseases, according to Iranian experts. Methods This qualitative study employed content analysis and used purposive and snowball sampling. The data were collected via online or face-to-face interviews with 25 participants with diverse expertise in infectious diseases (both clinical and non-clinical), epidemiology, knowledge management, and knowledge-based business management in Iran. The thematic analysis technique was used to code the interviews, and the collected data were analyzed using MAXQDA 20 software. Results Thematic analysis of the interviews led to 437 codes. These codes were categorized into two groups: facilitators and barriers. The facilitators shaping the knowledge network for infectious diseases were classified into three main categories: individual factors, organizational factors, and communication mechanisms. Individual factors involved two themes: strengthening knowledge exchange between experts in infectious diseases and personal characteristics such as the criteria for network membership. Organizational factors comprised three themes: organizational and trans-organizational factors, management strategies, and interactions with non-governmental sectors. Communication mechanisms included two themes: the use of information technology and knowledge brokers. In addition, three important challenges were identified as barriers influencing the knowledge network: administration and policy-making, organizational and trans-organizational, and personal challenges. Conclusions Several facilitators and barriers influence the formation of an infectious disease knowledge network, which must be addressed to ensure its effectiveness, development, and long-term sustainability. Addressing these factors will enable the network to effectively integrate diverse knowledge and contribute to advancing infectious disease management.

Background: Bladder cancer is the 5th most prevalent cancer among Iranian men. Finding prognostic markers to predict behavior of this cancer can help us to choose the best treatment for patients from the first place. We aimed to evaluate the correlation of immunohistochemical markers with tumor stage, grade and prognosis of disease. Methods: In this study, we reassessed the specs of proven UC among Iranian patients. Sixty specimens were collected, contained of 30 low grade and 30 high grade urothelial carcinomas. All slides were assessed by immunohistochemistry study for p21, p27, Her-2/neu, E-cadherin, and CD10. Data were analyzed by SPSS 18.0 and a p-value < 0.05 was considered significant. Results: We evaluated 60 patients in this study with mean age of 66±11 years and majority of them are men. High expression of p27 showed significant correlation with LGUC (P=0.030). HGUC related with high expression of Her-2/neu, CD10 and aberrant expression of E-Cadherin (P

Abstract The compressive strength of concrete depends on various factors. Since these parameters can be in a relatively wide range, it is difficult for predicting the behavior of concrete. Therefore, to solve this problem, an advanced modeling is needed. The aim of the literature is to achieve an ideal and flexible solution for predicting the behavior of concrete. Therefore, it is necessary to develop new approaches. Artificial Neural Networks (ANNs) have evolved from a theoretical method to a widely utilized technology by successful applications for a variety of issues. Actually, ANNs are a strong computing tool that provides the right solutions to problems that are difficult to use conventional methods. Inspired by the biological neural system, these networks are now widely used for solving a wide range of complicated problems in civil engineering. This study’’s target is evaluating the performance of developed African vulture optimization algorithm (DAVOA)-Elman neural networks (ENNs) by considering different input parameters in predicting the self-compacting concrete compressive strength. Hence, once 8 parameters and again to get as close as possible to the prediction conditions in the laboratory, 140 parameters entered to the improved version of Elman Neural Networks as input. According to the results, the element network has the lowest mean squares of the test error in predicting the compressive strength of 7 and 28 days in 100 repetitions. Further, in predicting both compressive strengths, the element grid with the Logsig-Purelin interlayer transfer function has the lowest test error, which determines the optimal transfer function. Moreover, the results showed that DAVOA as a reliable tool with time and cost savings have high power in predicting the desired characteristics. Also, in predicting both 7-day and 28-day compressive strength, networks built with 140 parameters have a 74.54 and 70.44% improvement in test error over 8-parameter networks, respectively, which directly affects this effect. Further parameters are considered as input to the network error rate in predicting the desired properties.

Abstract Objectives Canine-induced root resorption (CIRR) is caused by impacted canines and CBCT images have shown to be more accurate in diagnosing CIRR than panoramic and periapical radiographs with the reported AUCs being 0.95, 0.49, and 0.57, respectively. The aim of this study was to use deep learning to automatically evaluate the diagnosis of CIRR in maxillary incisors using CBCT images. Methods A total of 50 cone beam computed tomography (CBCT) images and 176 incisors were selected for the present study. The maxillary incisors were manually segmented and labeled from the CBCT images by two independent radiologists as either healthy or affected by root resorption induced by the impacted canines. We used five different strategies for training the model: (A) classification using 3D ResNet50 (Baseline), (B) classification of the segmented masks using the outcome of a 3D U-Net pretrained on the 3D MNIST, (C) training a 3D U-Net for the segmentation task and use its outputs for classification, (D) pretraining a 3D U-Net for the segmentation and transfer of the model, and (E) pretraining a 3D U-Net for the segmentation and fine-tuning the model with only the model encoder. The segmentation models were evaluated using the mean intersection over union (mIoU) and Dice coefficient (DSC). The classification models were evaluated in terms of classification accuracy, precision, recall, and F1 score. Results The segmentation model achieved a mean intersection over union (mIoU) of 0.641 and a DSC of 0.901, indicating good performance in segmenting the tooth structures from the CBCT images. For the main classification task of detecting CIRR, Model C (classification of the segmented masks using 3D ResNet) and Model E (pretraining on segmentation followed by fine-tuning for classification) performed the best, both achieving 82% classification accuracy and 0.62 F1-scores on the test set. These results demonstrate the effectiveness of the proposed hierarchical, data-efficient deep learning approaches in improving the accuracy of automated CIRR diagnosis from limited CBCT data compared to the 3D ResNet baseline model. Conclusion The proposed approaches are effective at improving the accuracy of classification tasks and are helpful when the diagnosis is based on the volume and boundaries of an object. While the study demonstrated promising results, future studies with larger sample size are required to validate the effectiveness of the proposed method in enhancing the medical image classification tasks.

Abstract Prostate cancer as a critical global health issue, requires the exploration of a novel therapeutic approach. Noscapine, an opium-derived phthalide isoquinoline alkaloid, has shown promise in cancer treatment thanks to its anti-tumorigenic properties. However, limitations such as low bioavailability and potential side effects have hindered its clinical application. This study introduces nanonoscapine as a novel medication to overcome these challenges, leveraging the advantages of improved drug delivery and efficacy achieved in nanotechnology. We monitored the effects of nanonoscapine on the androgen-sensitive human prostate adenocarcinoma cell line, LNCaP, investigating its impact on GLI1 and BAX genes’ expressions, crucial regulators of cell cycle and apoptosis. Our findings, from MTT assays, flow cytometry, and gene expression analyses, have demonstrated that nanonoscapine effectively inhibits prostate cancer cell proliferation by inducing G2/M phase arrest and apoptosis. Furthermore, through bioinformatics and computational analyses, we have revealed the underlying molecular mechanisms, underscoring the therapeutic potential of nanonoscapine in enhancing patient outcomes. This study highlights the significance of nanonoscapine as an alternative or adjunct treatment to conventional chemotherapy, warranting further investigation in clinical settings.

The Mesolithic and Neolithic periods mark pivotal junctures in the evolving relationship between humansand the environment. During these epochs, millennia-old hunter-gatherer lifestyles underwent a profoundtransformation, giving rise to new modes of existence. A cornerstone of this shift was the development of strategiesto harness and optimize the diverse resources offered by the natural world. The Neolithic period, in particular,is often considered the dawn of the Anthropocene, as human activities began to exert a substantial and oftenirreversible impact on ecosystems. To explore the dynamics of this transformation in the southeastern Caspian Searegion, this article examines archaeological evidence from the Hotu, Kamarband, Komishan caves, and KomishaniTepe. Through the analysis of archaeobotanical, zooarchaeological, and lithic artifacts, we seek to reconstruct themultifaceted changes experienced by communities as they transitioned from hunting and gathering to agriculture.Our findings reveal a period of remarkable adaptability. Humans intelligently modified their environments to meettheir needs and employed diverse strategies to mitigate the challenges posed by climatic fluctuations, such as coldand warm. These adaptations underscore the ingenuity and resilience of early human societies as they navigatedthe complexities of their changing world.

BackgroundWe conducted a systematic review and meta-analysis on dairy consumption and its association with anthropometric measurements, blood glucose status, insulin levels, and testosterone levels in women with Polycystic Ovary Syndrome.MethodsThis study conducted a comprehensive literature search using electronic databases like MEDLINE, Scopus, PubMed, Web of Science, and Google Scholar to identify observational and interventional studies investigating the relationship between dairy product consumption and Polycystic Ovary Syndrome. A meta-analysis was performed on clinical trial studies that examined the effect of a low starch/low dairy diet in Polycystic Ovary Syndrome subjects. Statistical analyses were performed using Stata version 16.0 (Stata Corporation, College Station, Texas, USA), and statistical significance was defined as p-value < 0.05.ResultsOf the 1,313 citations reviewed, our systematic review identified 11 studies that met the inclusion criteria, comprising six case-control studies, four clinical trials, and one cross-sectional study. The case-control studies found limited evidence of an association between dairy consumption and Polycystic Ovary Syndrome. The result of the clinical trial studies in meta-analysis showed that reducing dairy intake along with reducing starch intake led to statistically significant improvements in anthropometric and metabolic measures including mean weight (Standardized mean difference: -8.43 (95% CI: -9.01, -7.86)), Body mass index (-3.14 (95% CI: -3.35, -2.92), waist circumference (-6.63 (95% CI: -10.70, -2.57)) and Waist-to-Height Ratio (-0.04 (95% CI: -0.07, -0.01), insulin fasting (-18.23 (95% CI: -22.11, -14.36)), insulin 120 minutes (-94.05 (95% CI: -157.67, -30.42)), HbA1c (-0.27 (95% CI: -0.37, -0.17)), Ferryman-Gallwey score (-2.07 (95% CI: -2.98, -1.16)) and total testosterone (-9.97 (95% CI: -14.75, -5.19)). No significant reduction was found in fasting glucose, 2 hours glucose, percent of fat mass, and mean free testosterone after intervention.ConclusionsThe findings of this systematic review show limited evidence about the association between dairy consumption and Polycystic Ovary Syndrome. The interventional studies suggest that a low-dairy/low-starch diet may improve some anthropometric and metabolic measures in women with Polycystic Ovary Syndrome.

Summary: Background & Aims: Adequate nutritional care to malnourished patients is described as a human right, and recommendations from nutritional care guidelines are legally binding in Norway. The primary objective of this study was to investigate nutritional care in malnourished hospitalized patients. We also wanted to describe the association between malnutrition and length of stay (LOS), readmission, comorbidity and mortality. Methods: In a cross-sectional, multi-center and quality assurance study, inpatients from four university hospitals across all regional health authorities in Norway were included. The hospital's nutritional care during admission was evaluated according to current malnutrition guidelines. Malnutrition risk screening, assessment for diagnosis and grading severity of malnutrition were performed with Nutritional risk screening 2002 (NRS-2002) and the Global Leadership Initiative on malnutrition (GLIM) criteria. Medical records were reviewed to collect data on nutritional support during admission, malnutrition coding, LOS, readmission, comorbidity and 30-days survival after hospital admission. Results: In our mixed inpatient population (n 442, mean age 61 years, 53 % women), 42 % were not adequately screened for risk of malnutrition at hospital admission. Among the 29 % of malnourished patients, only 36 % had documented nutritional support in the medical records, and a malnutrition diagnosis was registered for only 30 %. Malnutrition was associated with LOS, increased comorbidity and reduced 30-day survival. Conclusion: In this study across all Norwegian regional health authorities, we found a high malnutrition rate and the nutritional care in relation to malnutrition diverged from national and international established guidelines and the framework of national laws and legislation. The findings raise concerns regarding patient safety and potential for improved nutritional care as a human right. Although malnutrition was associated with longer length of hospital stay, comorbidity and reduced 30-day survival, this study does not establish causal relationships.

Abstract Waste from the brain has been shown to be cleared via the perivascular spaces through the so-called glymphatic system. According to this model the cerebrospinal fluid (CSF) enters the brain in perivascular spaces of arteries, crosses the astrocyte endfoot layer, flows through the parenchyma collecting waste that is subsequently drained along veins. Glymphatic clearance is dependent on astrocytic aquaporin-4 (AQP4) water channels that are highly enriched in the endfeet. Even though the polarized expression of AQP4 in endfeet is thought to be of crucial importance for glymphatic CSF influx, its role in extracellular solute clearance has only been evaluated using non-quantitative fluorescence measurements. Here we have quantitatively evaluated clearance of intrastriatally infused small and large radioactively labeled solutes in mice lacking AQP4 (Aqp4 –/– ) or lacking the endfoot pool of AQP4 (Snta1 –/– ). We confirm that Aqp4 –/– mice show reduced clearance of both small and large extracellular solutes. Moreover, we find that the Snta1 –/– mice have reduced clearance only for the 500 kDa [3H]dextran, but not 0.18 kDa [3H]mannitol suggesting that polarization of AQP4 to the endfeet is primarily important for clearance of large, but not small molecules. Lastly, we observed that clearance of 500 kDa [3H]dextran increased with age in adult mice. Based on our quantitative measurements, we confirm that presence of AQP4 is important for clearance of extracellular solutes, while the perivascular AQP4 localization seems to have a greater impact on clearance of large versus small molecules.

Background Transcatheter aortic valve replacement (TAVR) has become the standard of care for severe aortic stenosis treatment. Exponential growth in demand has led to prolonged wait times and adverse patient outcomes. Social marginalization may contribute to adverse outcomes. Our objective was to examine the association between different measures of neighborhood‐level marginalization and patient outcomes while on the TAVR waiting list. A secondary objective was to understand if sex modifies this relationship. Methods and Results We conducted a population‐based retrospective cohort study of 11 077 patients in Ontario, Canada, referred to TAVR from April 1, 2018, to March 31, 2022. Primary outcomes were death or hospitalization while on the TAVR wait‐list. Using cause‐specific Cox proportional hazards models, we evaluated the relationship between neighborhood‐level measures of dependency, residential instability, material deprivation, and ethnic and racial concentration with primary outcomes as well as the interaction with sex. After multivariable adjustment, we found a significant relationship between individuals living in the most ethnically and racially concentrated areas (quintile 4 and 5) and mortality (hazard ratio [HR], 0.64 [95% CI, 0.47–0.88] and HR, 0.73 [95% CI, 0.53–1.00], respectively). There was no significant association between material deprivation, dependency, or residential instability with mortality. Women in the highest ethnic or racial concentration quintiles (4 and 5) had significantly lower risks for mortality (HR values of 0.52 and 0.56, respectively) compared with quintile 1. Conclusions Higher neighborhood ethnic or racial concentration was associated with decreased risk for mortality, particular for women on the TAVR waiting list. Further research is needed to understand the drivers of this relationship.

Individuals with diabetes often have chronic inflammation and high levels of inflammatory cytokines, leading to insulin resistance and complications. Anti-inflammatory agents are proposed to prevent these issues, including using antidiabetic medications with anti-inflammatory properties like semaglutide, a GLP-1 analogue. Semaglutide not only lowers glucose but also shows potential anti-inflammatory effects. Studies suggest it can modulate inflammatory responses and benefit those with diabetes. However, the exact mechanisms of its anti-inflammatory effects are not fully understood. This review aims to discuss the latest findings on semaglutide's anti-inflammatory effects and the potential pathways involved.

Introduction: Leishmaniasis is one of the six infectious diseases emphasized by the World Health Organization. Mehran and Dehloran cities in the south of Ilam province are endemic centers of cutaneous leishmaniosis in the country. Ilam Province, having near to 420 km common border with Iraq, is exposed to many zoonotic and tropical diseases, including Cutaneous leishmaniasis. Therefore, prevention, early diagnosis and treatment are essential. The registration program is an inseparable and necessary component of comprehensive patient care systems, which can be used as a tool to show the status of the disease. By providing sufficient data, this program has a useful role for managers to use in health care planning. Registry is a necessary component of comprehensive patient care systems, which can be used as a tool to show the status of the disease, which is called follow-up. Material & Methods: The aim of Cutaneous leishmaniasis registration program in the endemic areas of Ilam province is collection and comparing the correct methods of diagnosis disease with the common one (microscopy) and determining the number of errors made by laboratory experts in the form of a cross-sectional study from May 2018 to august It is 2020. Findings: By using molecular tests (PCR) to 10% of all positive slides received from Dehloran and Mehran cities, about 5% were false positives, and 28% of all negative slides collected was false negative. It should be mentioned that the implementation of the registration program in Ilam province during the epidemic of corona disease. Discussion & Conclusion: According to the findings of this study and the importance of the disease due to its endemicity in the southern part of Ilam province, the presence of increasing prevalence of the disease in the past years, the relation between of the traffic of Arbain Hosseini pilgrims with the period of transmission of the disease, mental and physical complications caused by the disease, it is recommended to ensure the referral diagnosis reports of health and laboratory experts, and apply the correct method of diagnosis and reporting, elimination of suspicious, positive and false negative result, and start a molecular diagnosis center, that can help patients be followed up with the correct diagnosis until the of recovery of the treatment period.

Pedestrian trajectory prediction is a critical aspect of computer vision, aimed at predicting a pedestrian’s future locations by analyzing their past movements. Traditional trajectory prediction models primarily focus on individuals, which can be challenging in densely populated areas due to occlusions. These occlusions not only complicate the re-identification of pedestrians once they reappear but also increase processing times due to the more complex procedures and the greater number of objects involved. However, a common observation is that pedestrians often travel in groups. This insight led us to propose a novel approach, predicting the future trajectories of pedestrian groups instead of individuals. This strategy effectively addresses the complexities of predicting movements in crowded environments and the issues related to pedestrian occlusion. In this work, we introduced a distinctive methodology for identifying pedestrian groups, re-identifying them, and predicting their future trajectories. Our approach, unlike traditional state-of-the-art re-identification and trajectory prediction methods of individual pedestrians, focuses on re-identifying pedestrian groups and predicting their future trajectories while emphasizing processing time reduction with great accuracy. The process started with object detection to ascertain pedestrian coordinates. Subsequently, a zone-based clustering method was employed to form groups. Following this, a specific group re-identification was utilized to construct continuous trajectories for these groups, rather than for individual pedestrians. Finally, the group trajectory prediction technique was applied to estimate the future movements of these groups. Both the object detection and group detection methods were applied every five frames to generate these trajectories. The effectiveness of our approach has been validated using several evaluation metrics, including Average Displacement Error (ADE), Final Displacement Error (FDE), Cumulative Matching Characteristics (CMC) scores, IDF1 scores, and IDs, all assessed using the MOT17 dataset. These evaluations not only confirm the practicality and accuracy of our method in predicting pedestrian trajectories but also highlight its efficiency, with a reduction in processing time by 7.6% compared to individual trajectory prediction. This efficiency demonstrates the potential of our method for real-time applications and underscores its capacity to prevent accidents.

Abstract Studying the effects of the microbiome on the development of different types of cancer has recently received increasing research attention. In this context, the microbial content of organs of the gastrointestinal tract has been proposed to play a potential role in the development of pancreatic cancer (PC). Proposed mechanisms for the pathogenesis of PC include persistent inflammation caused by microbiota leading to an impairment of antitumor immune surveillance and altered cellular processes in the tumor microenvironment. The limited available diagnostic markers that can currently be used for screening suggest the importance of microbial composition as a non-invasive biomarker that can be used in clinical settings. Samples including saliva, stool, and blood can be analyzed by 16 s rRNA sequencing to determine the relative abundance of specific bacteria. Studies have shown the potentially beneficial effects of prebiotics, probiotics, antibiotics, fecal microbial transplantation, and bacteriophage therapy in altering microbial diversity, and subsequently improving treatment outcomes. In this review, we summarize the potential impact of the microbiome in the pathogenesis of PC, and the role these microorganisms might play as biomarkers in the diagnosis and determining the prognosis of patients. We also discuss novel treatment methods being used to minimize or prevent the progression of dysbiosis by modulating the microbial composition. Emerging evidence is supportive of applying these findings to improve current therapeutic strategies employed in the treatment of PC.

Background & Aims: Observing public health protocols for COVID-19 has been documented as one of the key strategies to prevent the spread of this contagious condition and mitigate its impact. The present study investigated public participation in terms of adopting preventive health behaviors during this pandemic. Materials & Methods: This descriptive cross-sectional study was performed in the city of Urmia, Iran, in 2020. Two statistical populations, viz., the general population and public places, were recruited. Employing the ratio estimate formula, the sample size of the general population was determined as 2,398 individuals. Additionally, eight public places were selected from the 30 neighborhoods in the city of Urmia, via convenience sampling. The data collection tool was a researcher-made 47-item questionnaire, whose face and content validity and reliability were confirmed. The questionnaire was then completed upon visiting the selected public places in person by naturalistic concealed observation. The data were finally analyzed using the SPSS Statistics-16, with descriptive statistics. Results: Face mask use was at a good level in seven public places, except for restaurants and diners. Also, social distancing practices were at a moderate level in bakeries, electronic government services offices, beauty salons, public transport vehicles, and banks. Conclusion: Based on the results, there is a dire need to strengthen and maintain public participation by paving the ground through running advertising campaigns, designing and implementing educational interventions for various trade guilds and jobs, conducting advisory activities, and exploiting social media to inform and train the general population.

Abstract Introduction Cenegermin is approved for treatment of neurotrophic keratopathy (NK) and has been studied in patients with stage 2 or 3 NK. This study evaluated the efficacy and safety of cenegermin in adults with stage 1 NK. Methods This was a phase IV, multicenter, prospective, open-label, uncontrolled trial. Adults with stage 1 NK (Mackie criteria) and decreased corneal sensitivity (≤ 4 cm) received 1 drop of cenegermin 20 mcg/ml in the affected eye(s) 6 times/day for 8 weeks with a 24-week follow-up. Results Of 37 patients, corneal epithelial healing was observed in 84.8% (95% confidence interval [CI] 68.1–94.9%; P

ABSTRACTBackground Traumatic brain injury (TBI) is a quite common health problem. A lot of delayed complications are related to inflammatory responses that occurred within the brain itself. Atorvastatin is related to lipid lowering drugs carrying some anti-inflammatory properties and upon this fact this study hypothesis was built.Methods Twenty adult patients with TBI, Glasgow coma scale (GCS) 9–11. Patients were equally and randomly allocated into two groups (group C as control group and group S received atorvastatin 40 mg once daily for 48 h). After 48 h, participants have undergone magnetic resonance imaging brain spectroscopy examination (MRS). The spectral peaks of N-Acetyl aspartate (NAA), Choline, and Creatinine (Cr) were assessed in brain tissue. The primary outcome was presented as ratios of NAA/Cr), Cho/Cr, and NAA/Cho. Other outcomes included GCS and ICU stay.Results There were insignificant variations between groups were found in the MRS results for metabolite alterations (NAA, Cr, and Cho). Contrasted with the control group, the statin group’s Cho/Cr ratio was significantly lower (P = 0.005), and NAA/Cho was significantly greater in the statin group than control group (P = 0.022). Statin group showed higher GCS the 1st day (P = 0.01), and lesser ICU stay (P = 0.04)Conclusion Atorvastatin can be used safely in mild-to-moderate TBI patients with a favourable outcome in the form of decreased Cho/Cr ratio and increased NAA/Cho ratio, higher GCS, and decreased ICU length of stay.

Janus monolayers of transition metal dichalcogenides (TMDCs) are promising building blocks for moiré superlattices because of their built‐in electric field and clean fabrication process. In particular, Janus TMDC monolayers can be chemically converted from conventional TMDC monolayers by atomic substitution, enabling the direct formation of lattice‐mismatched heterobilayers from TMDC bilayers. However, the moiré superlattices of Janus heterobilayers have not been studied experimentally. Herein, this work reports the fabrication and characterization of semiconductor moiré superlattices in chemically tailored Janus heterobilayers. The MoSSe/MoSe2 (or WSSe/WSe2) Janus heterobilayers are prepared by replacing the top layer Se atoms with S atoms in MoSe2 (or WSe2) bilayer using H2 plasma treatment. Scanning transmission electron microscopy reveals that an average moiré period of about 14 nm formed due to lattice mismatch resulting from the chalcogen substitutions. The cryogenic photoluminescence spectra show sharp, near‐infrared emissions, which are attributed to excitons trapped by moiré potentials based on comparison with theoretical calculations. The Janus‐based heterostructures provide a long‐period moiré system with built‐in potential even for nontwisted heterobilayers, allowing the functionalization of confined and correlated electron systems.

Dyslipidemia poses a significant risk to cardiovascular health in both diabetic and non-diabetic individuals. Therefore, it is crucial to normalize lipid homeostasis in order to prevent or minimize complications associated with dyslipidemia. However, pharmacological interventions for controlling lipid metabolism often come with adverse effects. As an alternative, utilizing herbal-based agents, which typically have fewer side effects, holds promise. Crocin, a naturally occurring nutraceutical, has been shown to impact various intracellular pathways, reduce oxidative stress, and alleviate inflammatory processes. Recent evidence suggests that crocin may also confer lipid-related benefits and potentially contribute to the normalization of lipid homeostasis. However, the specific advantages and the cellular pathways involved are not yet well understood. In this review, we present the latest findings regarding the lipid benefits of crocin, which could be instrumental in preventing or reducing disorders associated with dyslipidemia. Additionally, we explore the potential cellular mechanisms and pathways that mediate these lipid benefits.

There is no currently approved human vaccine against leishmaniasis. Utilization of immunogenic antigens and their epitopes capable of enhancing immune responses against leishmaniasis is a crucial step for rational in silico vaccine design. The objective of this study was to generate and evaluate a potential vaccine candidate against leishmaniasis, designed by immunodominant proteins from gp46 and gp63 of Leishmania major, which can stimulate helper T-lymphocytes (HTL) and cytotoxic T-lymphocytes (CTL). For this aim, the IFN-γ-inducing MHC-I and MHC-II binders were predicted for each examined protein (gp46 and gp63) and connected with appropriate linkers, along with an adjuvant (Mycobacterium tuberculosis L7/L12) and a histidine tag. The vaccine’s stability, antigenicity, structure, and interaction with the TLR-4 receptor were evaluated in silico. The resulting chimeric vaccine was composed of 344 amino acids and had a molecular weight of 35.64 kDa. Physico-chemical properties indicated that it was thermotolerant, soluble, highly antigenic, and non-allergenic. Predictions of the secondary and tertiary structures were made, and further analyses confirmed that the vaccine construct could interact with the human TLR-4 receptor. Virtual immune simulation demonstrated strong stimulation of T-cell responses, particularly by an increase in IFN-γ, following vaccination. In summary, the in silico data indicated that the vaccine candidate showed high antigenicity in humans. It was also found to trigger significant levels of clearance mechanisms and other components of the cellular immune profile. Nevertheless, further wet experiments are required to properly assess the efficacy of this multi-epitope vaccine candidate against leishmaniasis.

Background Transcatheter aortic valve implantation (TAVI) has seen indication expansion and thus exponential growth in demand over the past decade. In many jurisdictions, the growing demand has outpaced capacity, increasing wait times and preprocedural adverse events. In this study, we derived prediction models that estimate the risk of adverse events on the waitlist and developed a triage tool to identify patients who should be prioritized for TAVI. Methods and Results We included adult patients in Ontario, Canada referred for TAVI and followed up until one of the following events first occurred: death, TAVI procedure, removal from waitlist, or end of the observation period. We used subdistribution hazards models to find significant predictors for each of the following outcomes: (1) all‐cause death while on the waitlist; (2) all‐cause hospitalization while on the waitlist; (3) receipt of urgent TAVI; and (4) a composite outcome. The median predicted risk at 12 weeks was chosen as a threshold for a maximum acceptable risk while on the waitlist and incorporated in the triage tool to recommend individualized wait times. Of 13 128 patients, 586 died while on the waitlist, and 4343 had at least 1 hospitalization. A total of 6854 TAVIs were completed, of which 1135 were urgent procedures. We were able to create parsimonious models for each outcome that included clinically relevant predictors. Conclusions The Canadian TAVI Triage Tool (CAN3T) is a triage tool to assist clinicians in the prioritization of patients who should have timely access to TAVI. We anticipate that the CAN3T will be a valuable tool as it may improve equity in access to care, reduce preventable adverse events, and improve system efficiency.

Abstract Cutaneous leishmaniasis (CL) is a very common parasitic infection in subtropical areas worldwide. Throughout decades, there have been challenges in vaccine design and vaccination against CL. The present study introduced novel T-cell-based vaccine candidates containing IFN-γ Inducing epitopic fragments from Leishmania major (L. major) glycoprotein 46 (gp46), cathepsin L-like and B-like proteases, histone H2A, glucose-regulated protein 78 (grp78) and stress-inducible protein 1 (STI-1). For this aim, top-ranked human leukocyte antigen (HLA)-specific, IFN-γ Inducing, antigenic, CD4 + and CD8 + binders were highlighted. Four vaccine candidates were generated using different spacers (AAY, GPGPG, GDGDG) and adjuvants (RS-09 peptide, human IFN-γ, a combination of both, Mycobacterium tuberculosis Resuscitation promoting factor E (RpfE)). Based on the immune simulation profile, those with RS-09 peptide (Leish-App) and RpfE (Leish-Rpf) elicited robust immune responses and their tertiary structure were further refined. Also, molecular docking of the selected vaccine models with the human toll-like receptor 4 showed proper interactions, particularly for Leish-App, for which molecular dynamics simulations showed a stable connection with TLR-4. Upon codon optimization, both models were finally ligated into the pET28a( +) vector. In conclusion, two potent multi-epitope vaccine candidates were designed against CL and evaluated using comprehensive in silico methods, while further wet experiments are, also, recommended.

Abstract Non-alcoholic fatty liver disease (NAFLD) comprises a range of chronic liver diseases that result from the accumulation of excess triglycerides in the liver, and which, in its early phases, is categorized NAFLD, or hepato-steatosis with pure fatty liver. The mortality rate of non-alcoholic steatohepatitis (NASH) is more than NAFLD; therefore, diagnosing the disease in its early stages may decrease liver damage and increase the survival rate. In the current study, we screened the gene expression data of NAFLD patients and control samples from the public dataset GEO to detect DEGs. Then, the correlation betweenbetween the top selected DEGs and clinical data was evaluated. In the present study, two GEO datasets (GSE48452, GSE126848) were downloaded. The dysregulated expressed genes (DEGs) were identified by machine learning methods (Penalize regression models). Then, the shared DEGs between the two training datasets were validated using validation datasets. ROC-curve analysis was used to identify diagnostic markers. R software analyzed the interactions between DEGs, clinical data, and fatty liver. Ten novel genes, including ABCF1, SART3, APC5, NONO, KAT7, ZPR1, RABGAP1, SLC7A8, SPAG9, and KAT6A were found to have a differential expression between NAFLD and healthy individuals. Based on validation results and ROC analysis, NR4A2 and IGFBP1b were identified as diagnostic markers. These key genes may be predictive markers for the development of fatty liver. It is recommended that these key genes are assessed further as possible predictive markers during the development of fatty liver.

Background & Aims: The COVID-19 pandemic drastically changed the life of the general population potentially leading to various psychological problems which affect the quality of life and causes disruption in various dimensions of performance. It is necessary to provide evidence on its psychological effects to develop effective psychological interventions. The present study aimed to investigate the association between corona disease anxiety, post-traumatic stress disorder, and quality of life among the general population. Materials & Methods: This cross-sectional study was conducted on 500 adults living in Urmia city, Iran. Data were collected using a standard electronic questionnaire that consisted of four sections: demographic information, Corona Disease Anxiety Scale, Impact of Event Scale-Revised, and 12-item Short-Form Health Survey, which were sent through WhatsApp to participants. Data were analyzed by SPSS 16 software using descriptive and analytical statistics. Results: The mean scores of corona disease anxiety, post-traumatic stress disorder, and quality of life were 16.03 ± 11.12, 31.64 ± 18.78, and 66.12 ± 22.83, respectively. Corona disease anxiety (p value < 0.001, β = -0.396) and post-traumatic stress disorder (p value < 0.001, β = -0.225) were predictors of quality of life among the general population of Urmia Conclusion: The level of anxiety and post-traumatic stress disorder caused by COVID-19 was slightly lower than the moderate level among the general population of Urmia. The coronavirus is not the first virus that threatens humanity, and it will not be the last virus either. Therefore, communities should utilize effective strategies to protect themselves and others and interact better with each other in order to control and minimize the psychological consequences of disease outbreaks.

Abstract Pancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis. Therefore, there has been a focus on identifying new biomarkers for its early diagnosis and the prediction of patient survival. Genome-wide RNA and microRNA sequencing, bioinformatics and Machine Learning approaches to identify differentially expressed genes (DEGs), followed by validation in an additional cohort of PDAC patients has been undertaken. To identify DEGs, genome RNA sequencing and clinical data from pancreatic cancer patients were extracted from The Cancer Genome Atlas Database (TCGA). We used Kaplan–Meier analysis of survival curves was used to assess prognostic biomarkers. Ensemble learning, Random Forest (RF), Max Voting, Adaboost, Gradient boosting machines (GBM), and Extreme Gradient Boosting (XGB) techniques were used, and Gradient boosting machines (GBM) were selected with 100% accuracy for analysis. Moreover, protein–protein interaction (PPI), molecular pathways, concomitant expression of DEGs, and correlations between DEGs and clinical data were analyzed. We have evaluated candidate genes, miRNAs, and a combination of these obtained from machine learning algorithms and survival analysis. The results of Machine learning identified 23 genes with negative regulation, five genes with positive regulation, seven microRNAs with negative regulation, and 20 microRNAs with positive regulation in PDAC. Key genes BMF, FRMD4A, ADAP2, PPP1R17, and CACNG3 had the highest coefficient in the advanced stages of the disease. In addition, the survival analysis showed decreased expression of hsa.miR.642a, hsa.mir.363, CD22, BTNL9, and CTSW and overexpression of hsa.miR.153.1, hsa.miR.539, hsa.miR.412 reduced survival rate. CTSW was identified as a novel genetic marker and this was validated using RT-PCR. Machine learning algorithms may be used to Identify key dysregulated genes/miRNAs involved in the disease pathogenesis can be used to detect patients in earlier stages. Our data also demonstrated the prognostic and diagnostic value of CTSW in PDAC.

Abstract Accumulating data reveals that tumors possess a specialized subset of cancer cells named cancer stem cells (CSCs), responsible for metastasis and recurrence of malignancies, with various properties such as self‐renewal, heterogenicity, and capacity for drug resistance. Some signaling pathways or processes like Notch, epithelial to mesenchymal transition (EMT), Hedgehog (Hh), and Wnt, as well as CSCs' surface markers such as CD44, CD123, CD133, and epithelial cell adhesion molecule (EpCAM) have pivotal roles in acquiring CSCs properties. Therefore, targeting CSC‐related signaling pathways and surface markers might effectively eradicate tumors and pave the way for cancer survival. Since current treatments such as chemotherapy and radiation therapy cannot eradicate all of the CSCs and tumor relapse may happen following temporary recovery, improving novel and more efficient therapeutic options to combine with current treatments is required. Immunotherapy strategies are the new therapeutic modalities with promising results in targeting CSCs. Here, we review the targeting of CSCs by immunotherapy strategies such as dendritic cell (DC) vaccines, chimeric antigen receptors (CAR)‐engineered immune cells, natural killer‐cell (NK‐cell) therapy, monoclonal antibodies (mAbs), checkpoint inhibitors, and the use of oncolytic viruses (OVs) in pre‐clinical and clinical studies. This review will mainly focus on blood malignancies but also describe solid cancers.

Abstract The modulating factors within the tumor microenvironment, for example, transforming growth factor beta (TGF-β), may limit the response to chemo and immunotherapy protocols in colorectal cancer (CRC). In the current study, the therapeutic potential of targeting the TGF-β pathway using Pirfenidone (PFD), a TGF-β inhibitor, either alone or in combination with five fluorouracil (5-FU) has been explored in preclinical models of CRC. The anti-proliferative and migratory effects of PFD were assessed by MTT and wound-healing assays respectively. Xenograft models were used to study the anti-tumor activity, histopathological, and side effects analysis. Targeting of TGF-β resulted in suppression of cell proliferation and migration, associated with modulation of survivin and MMP9/E-cadherin. Moreover, the PFD inhibited TGF-β induced tumor progression, fibrosis, and inflammatory response through perturbation of collagen and E-cadherin. Targeting the TGF-β pathway using PFD may increase the anti-tumor effects of 5-FU and reduce tumor development, providing a new therapeutic approach to CRC treatment.

Abstract The feature-rich nature of 5G introduces complexities that make its performance highly conditional and dependent on a broad range of key factors, each with unique values and characteristics that further complicate 5G deployments. To address the complexities, this work develops a new modular model based on machine learning on both architecture and service factors (5GPA) that actively contribute to variations in 5G network performance. The objectives are to address the complications during the design and planning phases according to the requirements before 5G deployment, simplify the whole feature-selection process for different deployments, and optimize 5G network performance. The model is implemented and the results are utilized to determine the correlation between the 5GPA factors and the overall performance. Additionally, a simulated 5G dataset is generated and utilized to make predictions on 5G performance based on unseen factors and values of interest. The reliability of the model is validated by comparing the predicted and actual results in the context of quality of service requirements. The results represent a high level of accuracy, with an average of 95%, and low error rates in terms of mean absolute error, mean squared error, and root mean squared error, averaging 7.60e−03, 1.18e−04, and 8.77e−03, respectively.

Introduction: Pipelines are widely used to transport large volumes of oil and gas over long distances. Risk assessment can help identify risk factors and create an appropriate action plan and strategy to reduce or eliminate them. The main goal of this research is to provide a method for assessing the risk of pipelines based on the Fuzzy Inference System (FIS), creating a systematic format that is expected to be a more effective, accurate, and reliable model for controlling risks related to oil and gas pipelines. Material and Methods: In this article, fuzzy logic is used to model uncertainty and present a model for assessing pipeline risk. The Muhlbauer method, one of the most common risk assessment methods for oil and gas pipelines, has been employed to determine critical factors affecting the lines. This method has been implemented using the Mamdani algorithm and based on expert knowledge in the fuzzy logic toolbox of MATLAB software. To validate the results of the proposed model, data from the interphase pipelines of the fifth refinery of the South Pars Gas Field have been used as a study sample. Results: The findings from the implementation of the model created in South Pars Phases 9-10 pipelines (on shore) show that the studied pipelines are divided into three parts (A, B, and C) based on indicators such as population density and equipment deployment. Part C of the pipeline has the highest risk, with third-party damage and design being the most important factors affecting it. Part B has the lowest level of risk and results in the fewest consequences for human accidents. It was also observed that corrosion is essential in increasing leakage and risk in all three pipeline parts. Conclusion: To verify the developed model, the inter-phase shore pipe of phase 9-10 refinery in the South Pars Gas Field was considered as a case study. The findings indicate that the proposed method provides more accurate and reliable results than traditional methods. Factors such as improper operation, dispersion, receptors, leakage volume, and product risk, which are other factors affecting pipeline risk, were not considered in traditional methods. Therefore, the risk level of oil and gas pipelines can be calculated using this model as a comprehensive and intelligent tool.

Orange concentrate (OC) is one of the main raw materials in the nonalcoholic beverage industry. Considering the difference in orange varieties, preserving its natural quality is essential to yield a product with favorable attributes and physical stability. Thus, the present study is aimed at assessing the effect of pectin, xanthan, and carboxymethyl cellulose (CMC) in a concentration range of 0–0.2% (w/v) along with mixing temperature on Brix, pH, acidity, density, turbidity, and viscosity of OC and at calculating the model equation for each attribute. The results showed that, except for CMC, the influence of concentration, type, and amount of hydrocolloid on pH changes was insignificant. Adding each hydrocolloid individually, in pairs, or threes reduced the density, and the measured density was lower at a mixing temperature of 4°C. Also, it was observed that mixing temperature was the only factor influencing turbidity, and the values were significantly lower at 80°C compared to 4°C. A significant interaction effect of xanthan concentration and mixing temperature on the Brix was observed. Adding hydrocolloids, except pectin, resulted in a significant (p