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This study aimed to propose a novel method for dynamic risk assessment using a Bayesian network (BN) based on fuzzy data to decrease uncertainty compared to traditional methods by integrating Interval Type-2 Fuzzy Sets (IT2FS) and Z-numbers. A bow-tie diagram was constructed by employing the System Hazard Identification, Prediction, and Prevention (SHIPP) approach, the Top Event Fault Tree, and the Barriers Failure Fault Tree. The experts then provided their opinions and confidence levels on the prior probabilities of the basic events, which were then quantified utilizing the IT2FS and combined using the Z-number to reduce the uncertainty of the prior probability. The posterior probability of the critical basic events (CBEs) was obtained using the beta distribution based on recorded data on their requirements and failure rates over five years. This information was then fed into the BN. Updating the BN allowed calculating the posterior probability of barrier failure and consequences. Spherical tanks were used as a case study to demonstrate and confirm the significant benefits of the methodology. The results indicated that the overall posterior probability of Consequences after the failure probability of barriers displayed an upward trend over the 5-year period. This rise in IT2FS-Z calculation outcomes exhibited a shallower slope compared to the IT2FS mode, attributed to the impact of experts' confidence levels in the IT2FS-Z mode. These differences became more evident by considering the 10-4 variance compared to the 10-5. This study offers industry managers a more comprehensive and reliable understanding of achieving the most effective accident prevention performance.

Toxoplasmosis ranks among the most prevalent parasitic diseases globally. It seems that chronic toxoplasmosis is associated with several neuropsychiatric and other harmful effects in infected people, therefore, there is a need to investigate the prevalence of toxoplasmosis across various world regions. In this study, we conducted a meticulous meta-analysis to estimate the seroprevalence of anti-Toxoplasma gondii IgG antibodies within the general population in Iran (GPI). International and national scientific databases for studies published between January 1, 2000, and September 30, 2023, were searched. Observational studies reporting anti-T. gondii IgG seroprevalence in the GPI was selected/included. The data were synthesized using a random-effects model to calculate with a 95% confidence interval (95% CI) the national and regional anti-T. gondii IgG seroprevalence rates in Iran. Additionally, subgroup analyses were conducted to investigate the frequency of exposition to T. gondii in different socio-demographic, climatic, and geographical scenarios. From 18661 identified studies, 327 were included in the present meta-analysis, encompassing 122,882 individuals across the 31 Iranian provinces. The pooled nationwide anti-T. gondii IgG seroprevalence among the GPI was determined to be 32.9% (95% CI: 30.9-35.1%). The highest anti-T. gondii IgG seroprevalence was observed in Mazandaran province (North of Iran) (61%), whereas the lowest was in Semnan province (12.5%).Anti-T. gondii IgG seroprevalence demonstrated a higher occurrence in provinces characterized by moderate temperatures of 16-21°C, high relative humidity, and annual precipitation. Additionally, a higher anti-T. gondii IgG seroprevalence was identified among individuals with a habit of consumption of undercooked meat, raw fruits or vegetables, and untreated water. Moreover, those reporting direct contact with cats, possessing a lower level of education, residing in rural areas, being engaged in farming occupations, or playing the role of housewives exhibited higher anti-T. gondii IgG seroprevalence figures.The anti-T. gondii IgG seroprevalence within GPI closely aligns with the estimated worldwide average exposition rates. This underscores the imperative for public health policymakers to prioritize educational efforts regarding toxoplasmosis transmission pathways and its link to harmful effects.

Epilepsy, particularly in older people, is associated with significant changes in physical activities, social and occupational functions, and diet. It is associated with significant changes in physical activities, social and occupational functions, and diet. Valid and reliable instruments are needed to assess these changes. This study aimed to develop and validate a questionnaire to assess lifestyle in older people with epilepsy, named the Epilepsy Lifestyle Questionnaire (ELQ). This methodological study was conducted in 2022. The primary ELQ items were generated through reviewing the literature. Then, its face, content, construct, convergent, and discriminant validity, internal consistency, and test-retest stability were evaluated. Older patients aged ≥ 60 years were recruited from the Iranian Epilepsy Association to assess construct validity using confirmatory factor analysis (CFA). Data were analyzed using the SPSS (v. 26.0), AMOS (v. 24.0), and JASP software. The primary ELQ had 99 items with five subscales, namely health-oriented self-care, risk-averse behavior, emotional and psychosocial adaptation, epilepsy stigma, and intimacy and sexual behaviors. Sixty five items were deleted during psychometric evaluation. CFA showed the good fitting of the five-factor structure of the 34-item ELEQ (PCFI = 0.741, PNFI = 0.693, CMIN/DF = 0.073, IFI = 0.917, CFI = 0.916, AND GFI = 0.902). The values of internal consistency based on Cronbach's alpha and test-retest reliability based on intraclass correlation coefficient (ICC) of ELQ were 0.89 and 0.95, respectively. The ELQ is a valid and reliable self-report instrument. The results suggest that the ELQ is a useful clinical tool for assessing the lifestyle of patients with epilepsy.

BackgroundMicroRNAs (miRNAs) are small noncoding RNAs that play important post-transcriptional regulatory roles in animals and plants. Despite the importance of plant miRNAs, the inherent complexity of miRNA biogenesis in plants hampers the application of standard miRNA prediction tools, which are often optimized for animal sequences. Therefore, computational approaches to predict putative miRNAs (merely) from genomic sequences, regardless of their expression levels or tissue specificity, are of great interest.ResultsHere, we present AmiR-P3, a novel ab initio plant miRNA prediction pipeline that leverages the strengths of various utilities for its key computational steps. Users can readily adjust the prediction criteria based on the state-of-the-art biological knowledge of plant miRNA properties. The pipeline starts with finding the potential homologs of the known plant miRNAs in the input sequence(s) and ensures that they do not overlap with protein-coding regions. Then, by computing the secondary structure of the presumed RNA sequence based on the minimum free energy, a deep learning classification model is employed to predict potential pre-miRNA structures. Finally, a set of criteria is used to select the most likely miRNAs from the set of predicted miRNAs. We show that our method yields acceptable predictions in a variety of plant species.ConclusionAmiR-P3 does not (necessarily) require sequencing reads and/or assembled reference genomes, enabling it to identify conserved and novel putative miRNAs from any genomic or transcriptomic sequence. Therefore, AmiR-P3 is suitable for miRNA prediction even in less-studied plants, as it does not require any prior knowledge of the miRNA repertoire of the organism. AmiR-P3 is provided as a docker container, which is a portable and self-contained software package that can be readily installed and run on any platform and is freely available for non-commercial use from: https://hub.docker.com/r/micrornaproject/amir-p3.

The behavior of an illuminated solar module can be characterized by its power-voltage curve. Tracking the peak of this curve is essential to harvest the maximum power by the module. The position of the peak varies with temperature and irradiance and needs to be traced. Under partial shading conditions, the number of peaks increases and makes it more difficult to find the global maximum power point (MPP). Various methods are used for maximum power point tracking (MPPT) that are based on iterations. These methods are time-consuming and fail to work satisfactorily under rapidly changing environmental conditions. In this paper, a novel algorithm is proposed that for the first time, utilizes computer vision to find the global maximum power point. This algorithm, which is implemented in Matlab/Simulink, is free of voltage iterations and gives the real-time data for the maximum power point. The proposed algorithm increases the speed and the reliability of the MPP tracking via replacing analogue electronics calculations by digital means. The validity of the algorithm is experimentally verified.

The prioritization of research topics in the health domain is a critical step toward channelling efforts and resources into areas that have received less attention. The objective of this study is to evaluate the implementation of research priorities determined at the national level within Iran for the period spanning five years between 2009 and 2013. We extracted the required data from the Iranian Registry of Clinical Trials (IRCT) website. Then we conducted a matching process between the titles of trials registered in the IRCT until December 3rd, 2013, and the list of national health research priorities in the domains of communicable and non-communicable diseases. The latter was compiled and regulated by the Research and Technology Deputy of the Ministry of Health since 2008. Out of the total 5,049 clinical trials registered in IRCT, 92.3% were carried out within the domain of non-communicable diseases, while 6.1% pertained to the field of communicable diseases and the remaining 1.3% in other fields. 56.4% of the clinical trials conducted in the field of communicable diseases and 32.8% of those conducted in the field of non-communicable diseases were consistent with the research priorities determined in these two fields. During the five-year period of the prioritization goal, there was no significant improvement in adherence to the list of priorities compared to the previous five-year period. Furthermore, certain priorities were neglected within both areas during these periods. It is possible to evaluate the effectiveness of research prioritization using the data obtained from the registration centers of clinical trials. Our study has revealed that the list of priorities has not garnered adequate attention from the research community within the country. Hence, remedial measures are imperative to ensure the priorities are given more attention after publication.

Alzheimer's disease is the most prevalent form of dementia, which is a gradual condition that begins with mild memory loss and progresses to difficulties communicating and responding to the environment. Recent advancements in neuroimaging techniques have resulted in large-scale multimodal neuroimaging data, leading to an increased interest in using deep learning for the early diagnosis and automated classification of Alzheimer's disease. This study uses machine learning (ML) methods to determine the severity level of Alzheimer's disease using MRI images, where the dataset consists of four levels of severity. A hybrid of 12 feature extraction methods is used to diagnose Alzheimer's disease severity, and six traditional machine learning methods are applied, including decision tree, K-nearest neighbor, linear discrimination analysis, Naïve Bayes, support vector machine, and ensemble learning methods. During training, optimization is performed to obtain the best solution for each classifier. Additionally, a CNN model is trained using a machine learning system algorithm to identify specific patterns. The accuracy of the Naïve Bayes, Support Vector Machines, K-nearest neighbor, Linear discrimination classifier, Decision tree, Ensembled learning, and presented CNN architecture are 67.5%, 72.3%, 74.5%, 65.6%, 62.4%, 73.8% and, 95.3%, respectively. Based on the results, the presented CNN approach outperforms other traditional machine learning methods to find Alzheimer severity.

ObjectivesHospital-acquired infections (HAIs) are significant problems as public health issues which need attention. Such infections are significant problems for society and healthcare organizations. This study aimed to carry out a systematic review and a meta-analysis to analyze the prevalence of HAIs globally.MethodsWe conducted a comprehensive search of electronic databases including EMBASE, Scopus, PubMed and Web of Science between 2000 and June 2021. We found 7031 articles. After removing the duplicates, 5430 studies were screened based on the titles/ abstracts. Then, we systematically evaluated the full texts of the 1909 remaining studies and selected 400 records with 29,159,630 participants for meta-analysis. Random-effects model was used for the analysis, and heterogeneity analysis and publication bias test were conducted.ResultsThe rate of universal HAIs was 0.14 percent. The rate of HAIs is increasing by 0.06 percent annually. The highest rate of HAIs was in the AFR, while the lowest prevalence were in AMR and WPR. Besides, AFR prevalence in central Africa is higher than in other parts of the world by 0.27 (95% CI, 0.22-0.34). Besides, E. coli infected patients more than other micro-organisms such as Coagulase-negative staphylococci, Staphylococcus spp. and Pseudomonas aeruginosa. In hospital wards, Transplant, and Neonatal wards and ICU had the highest rates. The prevalence of HAIs was higher in men than in women.ConclusionWe identified several essential details about the rate of HAIs in various parts of the world. The HAIs rate and the most common micro-organism were different in various contexts. However, several essential gaps were also identified. The study findings can help hospital managers and health policy makers identify the reason for HAIs and apply effective control programs to implement different plans to reduce the HAIs rate and the financial costs of such infections and save resources.

This study aimed to propose a novel method for dynamic risk assessment using a Bayesian network (BN) based on fuzzy data to decrease uncertainty compared to traditional methods by integrating Interval Type-2 Fuzzy Sets (IT2FS) and Z-numbers. A bow-tie diagram was constructed by employing the System Hazard Identification, Prediction, and Prevention (SHIPP) approach, the Top Event Fault Tree, and the Barriers Failure Fault Tree. The experts then provided their opinions and confidence levels on the prior probabilities of the basic events, which were then quantified utilizing the IT2FS and combined using the Z-number to reduce the uncertainty of the prior probability. The posterior probability of the critical basic events (CBEs) was obtained using the beta distribution based on recorded data on their requirements and failure rates over five years. This information was then fed into the BN. Updating the BN allowed calculating the posterior probability of barrier failure and consequences. Spherical tanks were used as a case study to demonstrate and confirm the significant benefits of the methodology. The results indicated that the overall posterior probability of Consequences after the failure probability of barriers displayed an upward trend over the 5-year period. This rise in IT2FS-Z calculation outcomes exhibited a shallower slope compared to the IT2FS mode, attributed to the impact of experts' confidence levels in the IT2FS-Z mode. These differences became more evident by considering the 10−4 variance compared to the 10−5. This study offers industry managers a more comprehensive and reliable understanding of achieving the most effective accident prevention performance. [ABSTRACT FROM AUTHOR]

Improving plant performance in salinity-prone conditions is a significant challenge in breeding programs. Genomic selection is currently integrated into many plant breeding programs as a tool for increasing selection intensity and precision for complex traits and for reducing breeding cycle length. A rice reference panel (RP) of 241 Oryza sativa L. japonica accessions genotyped with 20,255 SNPs grown in control and mild salinity stress conditions was evaluated at the vegetative stage for eight morphological traits and ion mass fractions (Na and K). Weak to strong genotype-by-condition interactions were found for the traits considered. Cross-validation showed that the predictive ability of genomic prediction methods ranged from 0.25 to 0.64 for multi-environment models with morphological traits and from 0.05 to 0.40 for indices of stress response and ion mass fractions. The performances of a breeding population (BP) comprising 393 japonica accessions were predicted with models trained on the RP. For validation of the predictive performances of the models, a subset of 41 accessions was selected from the BP and phenotyped under the same experimental conditions as the RP. The predictive abilities estimated on this subset ranged from 0.00 to 0.66 for the multi-environment models, depending on the traits, and were strongly correlated with the predictive abilities on cross-validation in the RP in salt condition (r = 0.69). We show here that genomic selection is efficient for predicting the salt stress tolerance of breeding lines. Genomic selection could improve the efficiency of rice breeding strategies for salinity-prone environments.

ObjectivesTo quantify the associations between shielding status and loneliness at the start of the COVID-19 pandemic, and physical activity (PA) levels throughout the pandemic.MethodsDemographic, health and lifestyle characteristics of 7748 cognitively healthy adults aged >50, and living in London, were surveyed from April 2020 to March 2021. The International Physical Activity Questionnaire (IPAQ) short-form assessed PA before COVID-19 restrictions, and up to 6 times over 11 months. Linear mixed models investigated associations between shielding status and loneliness at the onset of the pandemic, with PA over time.ResultsParticipants who felt 'often lonely' at the outset of the pandemic completed an average of 522 and 547 fewer Metabolic Equivalent of Task (MET) minutes/week during the pandemic (95% CI: -809, -236, pConclusionsThose shielding or lonely at pandemic onset were likely to have completed low levels of PA during the pandemic. These associations are influenced by co-morbidities and health status.

BackgroundCardiovascular Disease (CVD) is the leading cause of death in developing countries. CVD risk stratification guides the health policy to make evidence-based decisions.AimTo provide current picture and future trend of CVD risk in the adult Iranian population.MethodsNationally representative datasets of 2005, 2006, 2007, 2008, 2009, 2011, and 2016 STEPwise approach to non-communicable diseases risk factor surveillance (STEPS) studies were used to generate the 10-year and 30-year risks of CVD based on Framingham, Globorisk, and World Health Organization (WHO) risk estimation models. Trend of CVD risk was calculated from 2000 until 2016 and projected to 2030.ResultsIn 2016, based on Framingham model, 14.0% of the Iranian, aged 30 to 74, were at great risk (≥20%) of CVD in the next 10 years (8.0% among females, 20.7% among males). Among those aged 25 to 59, 12.7% had ≥45% risk of CVD in the coming 30 years (9.2% among females, 16.6 among males). In 2016, CVD risk was higher among urban area inhabitants. Age-standardized Framingham 10-year CVD risk will increase 32.2% and 19%, from 2000 to 2030, in females and males, respectively. Eastern provinces had the lowest and northern provinces had the greatest risk.ConclusionsThis study projected that CVD risk has increased from 2000 to 2016 in Iran. Without further risk factor modification, this trend will continue until 2030. We have identified populations at higher risks of CVD to guide future intervention.

The consumption of processed foods and sugary sodas in Western diets correlates with an increased incidence of obesity, metabolic syndromes such as type 2 diabetes, cardiovascular diseases, and autoimmune diseases including inflammatory bowel disease and rheumatoid arthritis. All these diseases have an inflammatory component, of which T lymphocytes can play a critical role in driving. Much has been learned regarding the importance of sugar, particularly glucose, in fueling effector versus regulatory T cells that can promote or dampen inflammation, respectively. In particular, glucose and its metabolic breakdown products via glycolysis are essential for effector T cell differentiation and function, while fatty acid-fueled oxidative phosphorylation supports homeostasis and function of regulatory T cells. Nevertheless, a critical knowledge gap, given the prevalence of diabetes in Western societies, is the impact of elevated glucose concentrations on the balance between effector versus regulatory T cells. To begin addressing this, we cultured naïve CD4+ T cells with different concentrations of glucose, and examined their differentiation into effector versus regulatory lineages. Surprisingly, high glucose promoted regulatory T cell differentiation and inhibited Th1 effector differentiation. This skewing towards the regulatory lineage occurred via an indirect mechanism that depends on lactate produced by activated glycolytic T cells. Addition of lactate to the T cell differentiation process promotes the differentiation of Treg cells, and activates Akt/mTOR signaling cascade. Hence, our findings suggest the existence of a novel feedback mechanism in which lactate produced by activated, differentiating T cells skews their lineage commitment towards the regulatory fate.

IntroductionThe effective treatment of anal fistulas almost always requires surgical intervention, which could be accompanied by post-operative complications, and affect the quality of life of patients. This study aimed to cross-culturally adapt the Persian version of the Quality of Life in patients with Anal Fistula questionnaire and evaluate its validity and reliability.Materials and methodsSixty patients with a mean age of 44 years ranging from 21 to 72 years entered the study. Forty-seven participants were men, and thirteen were women. After performing a scientific translation of the questionnaire based on Beaton's guidelines for cross-cultural adaptation and after extensive reviews by experts and specialists, the final version of the questionnaire was obtained. Then, 60 questionnaires (100%) were filled out by the participants (n = 60) and retrieved during a 7 to 21-day period. Data were collected and analyzed. Finally, according to the obtained data, the validity and reliability of the questionnaire were calculated.ResultsCross-cultural adaptation of the translated questionnaire was verified by the expert committee. The results showed perfect internal consistency (Cronbach alpha = 0.842), and external consistency (intraclass correlation coefficient = 0.800; PConclusionThe Persian translation of the Quality of Life in patients with the Anal Fistula questionnaire was proven to be valid and reliable for the evaluation of the QoL of patients with anal fistula.

One of the famous economic models in game theory is the duopoly Stackelberg model, in which a leader and a follower firm manufacture a single product in the market. Their goal is to obtain the maximum profit while competing with each other. The desired dynamics for a firm in a market is the convergence to its Nash equilibrium, but the dynamics of real-world markets are not always steady and can result in unpredictable market changes that exhibit chaotic behaviors. On the other hand, to approach reality more, the two firms in the market can be considered heterogeneous. The leader firm is bounded rationale, and the follower firm is adaptable. Modifying the cost function that affects the firms' profit by adding the marginal cost term is another step toward reality. We propose a Stackelberg model with heterogeneous players and marginal costs, which exhibits chaotic behavior. This model's equilibrium points, including the Nash equilibrium, are calculated by the backward induction method, and their stability analyses are obtained. The influence of changing each model parameter on the consequent dynamics is investigated through one-dimensional and two-dimensional bifurcation diagrams, Lyapunov exponents spectra, and Kaplan-Yorke dimension. Eventually, using a combination of state feedback and parameter adjustment methods, the chaotic solutions of the model are successfully tamed, and the model converges to its Nash equilibrium.

Toxoplasmosis ranks among the most prevalent parasitic diseases globally. It seems that chronic toxoplasmosis is associated with several neuropsychiatric and other harmful effects in infected people, therefore, there is a need to investigate the prevalence of toxoplasmosis across various world regions. In this study, we conducted a meticulous meta-analysis to estimate the seroprevalence of anti-Toxoplasma gondii IgG antibodies within the general population in Iran (GPI). International and national scientific databases for studies published between January 1, 2000, and September 30, 2023, were searched. Observational studies reporting anti-T. gondii IgG seroprevalence in the GPI was selected/included. The data were synthesized using a random-effects model to calculate with a 95% confidence interval (95% CI) the national and regional anti-T. gondii IgG seroprevalence rates in Iran. Additionally, subgroup analyses were conducted to investigate the frequency of exposition to T. gondii in different socio-demographic, climatic, and geographical scenarios. From 18661 identified studies, 327 were included in the present meta-analysis, encompassing 122,882 individuals across the 31 Iranian provinces. The pooled nationwide anti-T. gondii IgG seroprevalence among the GPI was determined to be 32.9% (95% CI: 30.9–35.1%). The highest anti-T. gondii IgG seroprevalence was observed in Mazandaran province (North of Iran) (61%), whereas the lowest was in Semnan province (12.5%).Anti-T. gondii IgG seroprevalence demonstrated a higher occurrence in provinces characterized by moderate temperatures of 16–21°C, high relative humidity, and annual precipitation. Additionally, a higher anti-T. gondii IgG seroprevalence was identified among individuals with a habit of consumption of undercooked meat, raw fruits or vegetables, and untreated water. Moreover, those reporting direct contact with cats, possessing a lower level of education, residing in rural areas, being engaged in farming occupations, or playing the role of housewives exhibited higher anti-T. gondii IgG seroprevalence figures.The anti-T. gondii IgG seroprevalence within GPI closely aligns with the estimated worldwide average exposition rates. This underscores the imperative for public health policymakers to prioritize educational efforts regarding toxoplasmosis transmission pathways and its link to harmful effects. [ABSTRACT FROM AUTHOR]

Epilepsy, particularly in older people, is associated with significant changes in physical activities, social and occupational functions, and diet. It is associated with significant changes in physical activities, social and occupational functions, and diet. Valid and reliable instruments are needed to assess these changes. This study aimed to develop and validate a questionnaire to assess lifestyle in older people with epilepsy, named the Epilepsy Lifestyle Questionnaire (ELQ). This methodological study was conducted in 2022. The primary ELQ items were generated through reviewing the literature. Then, its face, content, construct, convergent, and discriminant validity, internal consistency, and test-retest stability were evaluated. Older patients aged ≥ 60 years were recruited from the Iranian Epilepsy Association to assess construct validity using confirmatory factor analysis (CFA). Data were analyzed using the SPSS (v. 26.0), AMOS (v. 24.0), and JASP software. The primary ELQ had 99 items with five subscales, namely health-oriented self-care, risk-averse behavior, emotional and psychosocial adaptation, epilepsy stigma, and intimacy and sexual behaviors. Sixty five items were deleted during psychometric evaluation. CFA showed the good fitting of the five-factor structure of the 34-item ELEQ (PCFI = 0.741, PNFI = 0.693, CMIN/DF = 0.073, IFI = 0.917, CFI = 0.916, AND GFI = 0.902). The values of internal consistency based on Cronbach's alpha and test-retest reliability based on intraclass correlation coefficient (ICC) of ELQ were 0.89 and 0.95, respectively. The ELQ is a valid and reliable self-report instrument. The results suggest that the ELQ is a useful clinical tool for assessing the lifestyle of patients with epilepsy. [ABSTRACT FROM AUTHOR]

Background: MicroRNAs (miRNAs) are small noncoding RNAs that play important post-transcriptional regulatory roles in animals and plants. Despite the importance of plant miRNAs, the inherent complexity of miRNA biogenesis in plants hampers the application of standard miRNA prediction tools, which are often optimized for animal sequences. Therefore, computational approaches to predict putative miRNAs (merely) from genomic sequences, regardless of their expression levels or tissue specificity, are of great interest. Results: Here, we present AmiR-P3, a novel ab initio plant miRNA prediction pipeline that leverages the strengths of various utilities for its key computational steps. Users can readily adjust the prediction criteria based on the state-of-the-art biological knowledge of plant miRNA properties. The pipeline starts with finding the potential homologs of the known plant miRNAs in the input sequence(s) and ensures that they do not overlap with protein-coding regions. Then, by computing the secondary structure of the presumed RNA sequence based on the minimum free energy, a deep learning classification model is employed to predict potential pre-miRNA structures. Finally, a set of criteria is used to select the most likely miRNAs from the set of predicted miRNAs. We show that our method yields acceptable predictions in a variety of plant species. Conclusion: AmiR-P3 does not (necessarily) require sequencing reads and/or assembled reference genomes, enabling it to identify conserved and novel putative miRNAs from any genomic or transcriptomic sequence. Therefore, AmiR-P3 is suitable for miRNA prediction even in less-studied plants, as it does not require any prior knowledge of the miRNA repertoire of the organism. AmiR-P3 is provided as a docker container, which is a portable and self-contained software package that can be readily installed and run on any platform and is freely available for non-commercial use from: https://hub.docker.com/r/micrornaproject/amir-p3 [ABSTRACT FROM AUTHOR]

Afghan refugees child labourers face many challenges as they are labelled as refugees. In an attempt to explore these challenges, the present study was conducted in Tehran with a qualitative approach. The present qualitative research was conducted using a conventional content analysis approach with 25 Afghan child labourers in 2022 in Tehran. Child labourers were selected through purposive and snowball sampling and interviewed in a semi-in-depth interview. The data were analysed based on Granheim and Lundman's criteria, as well as those of Guba and Lincoln, to further enrich the findings. A total of 3 categories, 13 sub-categories, and 183 initial codes were extracted from the data analysis, including: "psychological challenges" (history of harassment and abuse, negative effects, high-risk behaviours, and family detachment); "health challenges" (physical problems, inappropriate accommodation, medical/therapeutic problems, and health threats); and "social challenges" (neglected childhood, dual identity, educational limitations, inadequate social support, social isolation, and social humiliation). At the individual level, it is possible to meet the child labourers' health needs and make them aware of the hazards of working in the streets through physical examination at certain intervals and holding training workshops on harassment prevention, anger control, prevention of high-risk behaviours, prevention of infectious diseases such as hepatitis, and strengthening self-confidence to improve health. Also, the Afghan child labourers' work could be intervened at the social and familial level by providing accommodation in more suitable neighbourhoods, providing health insurance for child labourers, creating the chances of studying in schools, preventing dropouts, and strengthening social relations in order to improve children's health. [ABSTRACT FROM AUTHOR]

BackgroundPeptic ulcer disease (PUD) affects four million people worldwide annually and has an estimated lifetime prevalence of 5-10% in the general population. Worldwide, there are significant heterogeneities in coping approaches of healthcare systems with PUD in prevention, diagnosis, treatment, and follow-up. Quantifying and benchmarking health systems' performance is crucial yet challenging to provide a clearer picture of the potential global inequities in the quality of care.ObjectiveThe objective of this study was to compare the health-system quality-of-care and inequities for PUD among age groups and sexes worldwide.MethodsData were derived from the Global Burden of Disease Study 1990-2019. Principal-Component-Analysis was used to combine age-standardized mortality-to-incidence-ratio, disability-adjusted-life-years-to-prevalence-ratio, prevalence-to-incidence-ratio, and years-of-life-lost-to-years-lived-with-disability-into a single proxy named Quality-of-Care-Index (QCI). QCI was used to compare the quality of care among countries. QCI's validity was investigated via correlation with the cause-specific Healthcare-Access-and-Quality-index, which was acceptable. Inequities were presented among age groups and sexes. Gender Disparity Ratio was obtained by dividing the score of women by that of men.ResultsGlobal QCI was 72.6 in 1990, which increased by 14.6% to 83.2 in 2019. High-income-Asia-pacific had the highest QCI, while Central Latin America had the lowest. QCI of high-SDI countries was 82.9 in 1990, which increased to 92.9 in 2019. The QCI of low-SDI countries was 65.0 in 1990, which increased to 76.9 in 2019. There was heterogeneity among the QCI-level of countries with the same SDI level. QCI typically decreased as people aged; however, this gap was more significant among low-SDI countries. The global Gender Disparity Ratio was close to one and ranged from 0.97 to 1.03 in 100 of 204 countries.ConclusionQCI of PUD improved dramatically during 1990-2019 worldwide. There are still significant heterogeneities among countries on different and similar SDI levels.

The COVID-19 pandemic has had a devastating impact on the global economy. In this paper, we use the Phillips curve to compare and analyze the macroeconomics of three different countries with distinct income levels, namely, lower-middle (Nigeria), upper-middle (South Africa), and high (Canada) income. We aim to (1) find macroeconomic changes in the three countries during the pandemic compared to pre-pandemic time, (2) compare the countries in terms of response to the COVID-19 economic crisis, and (3) compare their expected economic reaction to the COVID-19 pandemic in the near future. An advantage to our work is that we analyze macroeconomics on a monthly basis to capture the shocks and rapid changes caused by on and off rounds of lockdowns. We use the volume and social sentiments of the Twitter data to approximate the macroeconomic statistics. We apply four different machine learning algorithms to estimate the unemployment rate of South Africa and Nigeria on monthly basis. The results show that at the beginning of the pandemic the unemployment rate increased for all the three countries. However, Canada was able to control and reduce the unemployment rate during the COVID-19 pandemic. Nonetheless, in line with the Phillips curve short-run, the inflation rate of Canada increased to a level that has never occurred in more than fifteen years. Nigeria and South Africa have not been able to control the unemployment rate and did not return to the pre-COVID-19 level. Yet, the inflation rate has increased in both countries. The inflation rate is still comparable to the pre-COVID-19 level in South Africa, but based on the Phillips curve short-run, it will increase further, if the unemployment rate decreases. Unfortunately, Nigeria is experiencing a horrible stagflation and a wild increase in both unemployment and inflation rates. This shows how vulnerable lower-middle-income countries could be to lockdowns and economic restrictions. In the near future, the main concern for all the countries is the high inflation rate. This work can potentially lead to more targeted and publicly acceptable policies based on social media content.

BackgroundThere are conflicting results regarding the relationship between overweight/obesity and the outcomes of coronary artery bypass graft surgery (CABG), termed "the obesity paradox". This study aimed to evaluate the effects of body mass index (BMI) on the midterm outcomes of CABG.MethodsThis historical cohort study included all patients who underwent isolated CABG at our center between 2007 and 2016. The patients were divided into five categories based on their preoperative BMIs (kg/m2): 18.5≤BMIResultsOf 17 751 patients (BMI = 27.30 ±4.17 kg/m2) who underwent isolated CABG at our center, 17 602 patients (mean age = 61.16±9.47 y, 75.4% male) were included in this study. Multivariable analysis demonstrated that patients with pre-obesity and normal weight had similar outcomes, whereas patients with preoperative BMIs exceeding 30 kg/m2 kg/m2 had a significantly higher risk of 5-year all-cause mortality and 5-year MACCEs than those with pre-obesity. Additionally, a positive association existed between obesity degree and all-cause mortality and MACCEs. Further, BMIs of 40 kg/m2 or higher showed a trend toward higher MACCE risks (adjusted hazard ratio, 1.32; 95% confidence interval, 0.89 to 1.95), possibly due to the small sample size. A nonlinear, albeit negligible, association was also found between continuous BMI and the study endpoints.ConclusionsOur findings suggest that preoperative obesity (BMI>30 kg/m2) in patients who survive early after CABG is associated with an increased risk of 5-year all-cause mortality and 5-year MACCEs. These findings indicate that physicians and cardiac surgeons should encourage patients with high BMIs to reduce weight for risk modification.

BackgroundPatient engagement in patient safety is aimed at increasing the awareness and participation of patients in error-prevention strategies. The aim of this project was to improve the patient safety with the patient engagement within the local context of a maternity hospital by implementing best practice.MethodsA clinical audit was conducted using the JBI Practical Application of Clinical Evidence System tool. The current project was conducted in surgical ward of Shahid-Beheshti maternity hospital, Iran. The sample size was 46 patients and 46 healthcare practitioners for both the baseline and follow-up. In phase 1, four audit criteria were used and a baseline audit was conducted for this project. In phase 2, barriers to compliance were identified, and strategies were adopted to promote best practice. In phase 3, a follow-up audit was conducted.ResultsThe results showed varying levels of compliance with the four criteria used in this project. The criterion 1, which was related to training of healthcare practitioners on how they can support patients, has the highest compliance at 87% in baseline and follow up data collection. Furthermore, compared with the baseline data (criterion 2 = 52%; criterion 3 = 37%; criterion 4 = 61%), compliance with criteria 2, 3, and 4 notably improved at 85, 76, and 92%, respectively.ConclusionsThe present project successfully implements patient engagement in Iran and reveals varying results on compliance and the increasing knowledge of healthcare practitioners and patients on evidence-based patient engagement in order to improve the patient safety. The used strategies can facilitate implementation of evidence based procedures in clinical practice.

BackgroundThere is uncertainty around the health impact and economic costs of the recent slowing of the historical decline in cardiovascular disease (CVD) incidence and the future impact on dementia and disability.MethodsPreviously validated IMPACT Better Ageing Markov model for England and Wales, integrating English Longitudinal Study of Ageing (ELSA) data for 17,906 ELSA participants followed from 1998 to 2012, linked to NHS Hospital Episode Statistics. Counterfactual design comparing two scenarios: Scenario 1. CVD Plateau-age-specific CVD incidence remains at 2011 levels, thus continuing recent trends. Scenario 2. CVD Fall-age-specific CVD incidence goes on declining, following longer-term trends. The main outcome measures were age-related healthcare costs, social care costs, opportunity costs of informal care, and quality adjusted life years (valued at £60,000 per QALY).FindingsThe total 10 year cumulative incremental net monetary cost associated with a persistent plateauing of CVD would be approximately £54 billion (95% uncertainty interval £14.3-£96.2 billion), made up of some £13 billion (£8.8-£16.7 billion) healthcare costs, £1.5 billion (-£0.9-£4.0 billion) social care costs, £8 billion (£3.4-£12.8 billion) informal care and £32 billion (£0.3-£67.6 billion) value of lost QALYs.InterpretationAfter previous, dramatic falls, CVD incidence has recently plateaued. That slowdown could substantially increase health and social care costs over the next ten years. Healthcare costs are likely to increase more than social care costs in absolute terms, but social care costs will increase more in relative terms. Given the links between COVID-19 and cardiovascular health, effective cardiovascular prevention policies need to be revitalised urgently.

BackgroundColorectal cancer (CRC) is among the five most incident and lethal cancers in world and its burden varies between countries and sexes. We aimed to present a comprehensive measure called the quality of care index (QCI) to evaluate the inequity and healthcare quality of care regarding CRC by sex and location.MethodsData on the burden of CRC were extracted from the Global Burden of Disease study 2019. It was transformed to four ratios, including mortality-to-incidence, disability-adjusted life years (DALYs)-to-prevalence, prevalence-to-incidence, and years of life lost (YLLs)-to-years lived with disability (YLDs). Principal component analysis was implemented on the four ratios and the most influential component was considered as QCI with a score ranging from zero to 100, for which higher scores represented better quality of care. Gender Disparity Ratio (GDR) was calculated by dividing QCI for females by males.ResultsThe global incidence and death numbers of CRC were 2,166,168 (95% uncertainty interval: 1,996,298-2,342,842) and 1,085,797 (1,002,795-1,149,679) in 2019, respectively. Globally, QCI and GDR values were 77.6 and 1.0 respectively in 2019. There was a positive association between the level of quality of care and socio-demographic index (SDI) quintiles. Region of the Americas and African Region had the highest and lowest QCI values, respectively (84.4 vs. 23.6). The QCI values started decreasing beyond the age of 75 in 2019 worldwide.ConclusionThere is heterogeneity in QCI between SDI quintiles. More attention should be paid to people aged more than 75 years old because of the lower quality of care in this group.

Although metabolic syndrome is associated with increased risk of cardiovascular disease and events, its added prognostic value beyond its components remains unknown. This study compared the prevalence, severity of coronary artery disease (CAD), and prognosis of patients with metabolic syndrome to those with individual metabolic syndrome components. The study cohort consisted of 27125 consecutive individuals who underwent ≥ 64-detector row coronary CT angiography (CCTA) at 12 centers from 2003 to 2009. Metabolic syndrome was defined as per NCEP/ATP III criteria. Metabolic syndrome patients (n = 690) were matched 1:1:1 to those with 1 component (n = 690) and 2 components (n = 690) of metabolic syndrome for age, sex, smoking status, and family history of premature CAD using propensity scoring. Major adverse cardiac events (MACE) were defined by a composite of myocardial infarction (MI), acute coronary syndrome, mortality and late target vessel revascularization. Patients with 1 component of metabolic syndrome manifested lower rates of obstructive 1-, 2-, and 3-vessel/left main disease compared to metabolic syndrome patients (9.4% vs 13.8%, 2.6% vs 4.5%, and 1.0% vs 2.3%, respectively; p < 0.05), while those with 2 components did not (10.5% vs 13.8%, 2.8% vs 4.5% and 1.3% vs 2.3%, respectively; p > 0.05). At 2.5 years, metabolic syndrome patients experienced a higher rate of MACE compared to patients with 1 component (4.4% vs 1.6%; p = 0.002), while no difference observed compared to individuals with 2 components (4.4% vs 3.2% p = 0.25) of metabolic syndrome. In conclusion, Metabolic syndrome patients have significantly greater prevalence, severity, and prognosis of CAD compared to patients with 1 but not 2 components of metabolic syndrome.

The prioritization of research topics in the health domain is a critical step toward channelling efforts and resources into areas that have received less attention. The objective of this study is to evaluate the implementation of research priorities determined at the national level within Iran for the period spanning five years between 2009 and 2013. We extracted the required data from the Iranian Registry of Clinical Trials (IRCT) website. Then we conducted a matching process between the titles of trials registered in the IRCT until December 3rd, 2013, and the list of national health research priorities in the domains of communicable and non-communicable diseases. The latter was compiled and regulated by the Research and Technology Deputy of the Ministry of Health since 2008. Out of the total 5,049 clinical trials registered in IRCT, 92.3% were carried out within the domain of non-communicable diseases, while 6.1% pertained to the field of communicable diseases and the remaining 1.3% in other fields. 56.4% of the clinical trials conducted in the field of communicable diseases and 32.8% of those conducted in the field of non-communicable diseases were consistent with the research priorities determined in these two fields. During the five-year period of the prioritization goal, there was no significant improvement in adherence to the list of priorities compared to the previous five-year period. Furthermore, certain priorities were neglected within both areas during these periods. It is possible to evaluate the effectiveness of research prioritization using the data obtained from the registration centers of clinical trials. Our study has revealed that the list of priorities has not garnered adequate attention from the research community within the country. Hence, remedial measures are imperative to ensure the priorities are given more attention after publication. [ABSTRACT FROM AUTHOR]

Background: Hematologic malignancies have a great essential role in cancer global burden. Leukemia which two major subtypes based on the onset, is one of the common subtypes of this malignancy. Method: For the GBD 2019 study, cancer registry data and vital registration system were used to estimate leukemia mortality. The Meta-Regression-Bayesian Regularized Trimmed (MR-BRT), Cause of Death Ensemble model (CODEm) and Spatiotemporal Gaussian Process Regression (ST-GPR) were used to model our data and estimate each quantity of interest. Mortality to incidence ratios (MIR) were used to generate incidence and survival from mortality rate. Prevalence and survival were used to generate years lived with disability (YLDs). Age-specific mortality and life expectancy at the same age were used to estimate years of life lost (YLLs). The sum of YLLs and YLDs generates DALYs. Results: The total national incidence of leukemia increased from 6092 (UI 95%: 3803–8507) in 1990 to 6767 (4646–7890) new cases in 2019. However, leukemia age-standardized incidence ratio(ASIR) decreased from 11.6 (8–14.8) to 8.9 (6.2–10.3) new cases per 100,000 in this exact period. At the national level, deaths from leukemia increased 1.5-fold between 1990 and 2019, from 3287 (2284–4201) to 4424 (3137–5030), whereas the age-standardized death rate(ASDR) decreased from 8.3 (6.1–9.8) in 1990 to 6 (4.3–6.8) per 100,000 in 2019. In the study period, total leukemia DALYs decreased 12.2% and reached 162850 (110681–188806), in 2019. The age-standardized DALYs decreased 36.7% from 324.3 (224.8–413.4) in 1990 to 205.3 (140.3–237.8) in 2019. ASDR, DALYs, YLLs, and YLDs rate to high BMI was increasing while smoking and occupational exposure to benzene and formaldehyde were decreasing in the study period. Conclusion: This study provided a better understanding of leukemia burden and to reduce controversies of leukemia across Iran. The leukemia status alteration of the country, is trackable. [ABSTRACT FROM AUTHOR]

Salinity tolerance is an important quality for European rice grown in river deltas. We evaluated the salinity tolerance of a panel of 235 temperate japonica rice accessions genotyped with 30,000 SNP markers. The panel was exposed to mild salt stress (50 mM NaCl; conductivity of 6 dS m-1) at the seedling stage. Eight different root and shoot growth parameters were measured for both the control and stressed treatments. The Na+ and K+ mass fractions of the stressed plants were measured using atomic absorption spectroscopy. The salt treatment affected plant growth, particularly the shoot parameters. The panel showed a wide range of Na+/K+ ratio and the temperate accessions were distributed over an increasing axis, from the most resistant to the most susceptible checks. We conducted a genome-wide association study on indices of stress response and ion mass fractions in the leaves using a classical mixed model controlling structure and kinship. A total of 27 QTLs validated by sub-sampling were identified. For indices of stress responses, we also used another model that focused on marker × treatment interactions and detected 50 QTLs, three of which were also identified using the classical method. We compared the positions of the significant QTLs to those of approximately 300 genes that play a role in rice salt tolerance. The positions of several QTLs were close to those of genes involved in calcium signaling and metabolism, while other QTLs were close to those of kinases. These results reveal the salinity tolerance of accessions with a temperate japonica background. Although the detected QTLs must be confirmed by other approaches, the number of associations linked to candidate genes involved in calcium-mediated ion homeostasis highlights pathways to explore in priority to understand the salinity tolerance of temperate rice.