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The objective of present research is to examine the thermal radiation effect in three-dimensional mixed convection flow of viscoelastic fluid. The boundary layer analysis has been discussed for flow by an exponentially stretching surface with convective conditions. The resulting partial differential equations are reduced into a system of nonlinear ordinary differential equations using appropriate transformations. The series solutions are developed through a modern technique known as the homotopy analysis method. The convergent expressions of velocity components and temperature are derived. The solutions obtained are dependent on seven sundry parameters including the viscoelastic parameter, mixed convection parameter, ratio parameter, temperature exponent, Prandtl number, Biot number and radiation parameter. A systematic study is performed to analyze the impacts of these influential parameters on the velocity and temperature, the skin friction coefficients and the local Nusselt number. It is observed that mixed convection parameter in momentum and thermal boundary layers has opposite role. Thermal boundary layer is found to decrease when ratio parameter, Prandtl number and temperature exponent are increased. Local Nusselt number is increasing function of viscoelastic parameter and Biot number. Radiation parameter on the Nusselt number has opposite effects when compared with viscoelastic parameter.

BackgroundWe sought to conduct this comprehensive systematic review and meta-analysis to assess the prevalence of depression, anxiety, and sleep disturbance in Iranian medical students and resident physicians.MethodsA systematic search was conducted on 23 December 2023 in PubMed/MEDLINE, Web of Science, Scopus, and Iranian national databases. We pooled the prevalence of individual studies using the random effect model.ResultsOur systematic search showed 36 articles that meet the eligibility criteria. Most included studies were cross-sectional. The most used questionnaire to assess depression, anxiety, and sleep disturbance were Beck Depression Inventory (BDI), The Depression, Anxiety and Stress Scale-21 Items (DASS-21), and The Pittsburgh Sleep Quality Index (PSQI), respectively. The overall prevalence of depression, anxiety, and sleep disturbance among Iranian medical students were 43% (95%CI: 33%-53%%, I2 = 98%), 44% (95%CI: 31%-58%%, I2 = 99%), 48% (95%CI: 39%-56%%, I2 = 97%), respectively. The results of subgroup and meta-regression analyses showed questionnaires used and the place of the medical school were significantly associated with the prevalence of aforementioned outcomes. Funnel plot and Begg's regression test did not show a significant source of funnel plot asymmetry for depression, anxiety, and sleep disturbance.ConclusionIn conclusion, our study showed that nearly half of the medical students had some type of depression, anxiety, and sleep disturbance problems. To address this serious national public health issue, efficient preventive measures, routine screenings, and prompt interventions are required.

There is a disagreement on whether extremely low frequency electromagnetic fields (ELF-EMF) have a beneficial or harmful effect on anxiety-like behavior. Prenatal stress induces frequent disturbances in offspring physiology such as anxiety-like behavior extending to adulthood. This study was designed to evaluate the effects of prenatal stress and ELF-EMF exposure before and during pregnancy on anxiety-like behavior and some anxiety-related pathways in the hippocampus of female rat offspring. A total of 24 female rats 40 days of age were distributed into four groups of 6 rats each: control, Stress (rats whose mothers underwent chronic stress), EMF (rats whose mothers were exposed to electromagnetic fields) and EMF/S (rats whose mothers were simultaneously exposed to chronic stress and ELF-EMF). The rats were given elevated plus-maze and open field tests and then their brains were dissected and their hippocampus were subjected to analysis. ELISA was used to measure 24(S)-hydroxy cholesterol, corticosterone, and serotonin levels. Cryptochrome2, steroidogenic acute regulatory protein, 3B-Hydroxy steroid dehydrogenase, N-methyl-D-aspartate receptor 2(NMDAr2) and phosphorylated N-methyl-D-aspartate receptor 2(PNMDAr2) were assayed by immunoblotting. Anxiety-like behavior increased in all treatment groups at the same time EMF increased anxiety induced by maternal stress in the EMF/S group. The stress group showed decreased serotonin and increased corticosterone levels. ELF-EMF elevated the PNMDAr2/NMDAr2 ratio and 24(S)-hydroxy cholesterol compared to the control group but did not change corticosterone. EMF did not restore changes induced by stress in behavioral and molecular tests. The results of the current study, clarified that ELF-EMF can induce anxiety-like behavior which may be attributed to an increase in the PNMDAr2/NMDAr2 ratio and 24(S)-OHC in the hippocampus, and prenatal stress may contribute to anxiety via a decrease in serotonin and an increase in corticosterone in the hippocampus. We also found that anxiety-like behavior induced by maternal stress exposure, is exacerbated by electromagnetic fields radiation.

BackgroundMental health literacy (MHL) has been relatively neglected, despite the increase of mental health illnesses worldwide, as well as within the Middle East region. A low level of MHL may hinder public acceptance of evidence-based mental health care.AimThis systematic review aims to identify and appraise existing research, focusing on MHL among adults in the Gulf Cooperation Council (GCC) countries.MethodsA systematic search of electronic databases (PubMed, PsychInfo, and Medline) was carried out from database inception to July 2019, in order to identify peer-reviewed journal articles that investigated MHL in the GCC countries. Studies were eligible for inclusion if they were: cross-sectional studies, reported in English, targeted adults (aged 18 and above), conducted in any of the GCC countries, include at least one outcome measure of the main components of MHL: knowledge of mental illnesses and their treatment, stigmatizing attitudes towards mental illnesses, and seeking help for self and offering help.ResultsA total of 27 studies (16,391 participants) were included. The outcome across studies varied due to disparity in the tested populations. Findings show that limited MHL was observed among participants, even health care professionals. Results also show a high cumulative level of stigma and negative attitude towards mental health illness in the public. Negative beliefs and inappropriate practices are common, as well. The majority of studies yielded a moderate to high risk of bias.ConclusionThis work indicates that research on MHL must be tackled through well-designed large-scale studies of the public. Campaigns to promote early identification and treatment of mental illness is also encouraged to improve overall level of MHL in the general population of the GCC region. Registration number: PROSPERO 2018 CRD42018104492.

A network of myenteric interstitial cells of Cajal in the corpus of the stomach serves as its "pacemaker", continuously generating a ca 0.05 Hz electrical slow wave, which is transmitted to the brain chiefly by vagal afferents. A recent study combining resting-state functional MRI (rsfMRI) with concurrent surface electrogastrography (EGG), with cutaneous electrodes placed on the epigastrium, found 12 brain regions with activity that was significantly phase-locked with this gastric basal electrical rhythm. Therefore, we asked whether fluctuations in brain resting state networks (RSNs), estimated using a spatial independent component analysis (ICA) approach, might be synchronized with the stomach. In the present study, in order to determine whether any RSNs are phase-locked with the gastric rhythm, an individual participant underwent 22 scanning sessions; in each, two 15-minute runs of concurrent EGG and rsfMRI data were acquired. EGG data from three sessions had weak gastric signals and were excluded; the other 19 sessions yielded a total of 9.5 hours of data. The rsfMRI data were analyzed using group ICA; RSN time courses were estimated; for each run, the phase-locking value (PLV) was computed between each RSN and the gastric signal. To assess statistical significance, PLVs from all pairs of "mismatched" data (EGG and rsfMRI data acquired on different days) were used as surrogate data to generate a null distribution for each RSN. Of a total of 18 RSNs, three were found to be significantly phase-locked with the basal gastric rhythm, namely, a cerebellar network, a dorsal somatosensory-motor network, and a default mode network. Disruptions to the gut-brain axis, which sustains interoceptive feedback between the central nervous system and the viscera, are thought to be involved in various disorders; manifestation of the infra-slow rhythm of the stomach in brain rsfMRI data could be useful for studies in clinical populations.

Despite the significant progress in characterizing mechanical functions of individual scleral extracellular matrix (ECM) components, the biomechanical contribution of sulfated glycosaminoglycans (sGAGs) is still poorly understood. The primary purpose of this study was to determine the possible function of sGAGs in scleral mechanical response by characterizing the tensile behavior of normal and sGAG-depleted samples. We used chondroitinase ABC solution to remove sGAGs from scleral samples that were dissected from posterior porcine eyes. We performed biochemical analyses for assessing the efficacy of sGAG removal protocol. Furthermore, we conducted stress-controlled uniaxial tensile tests to characterize the influence of sGAG removal on mechanical properties of sclera. The tensile behavior of scleral strips right after dissection and after being soaked in buffer was also determined. Biochemical analyses confirmed that 18 hour incubation in 0.125 U/ml Chondroitinase ABC solution removed over 90% of chondroitin and dermatan sGAGs. No significant difference was observed in the thickness/hydration of samples because of enzyme- and buffer-treated samples. Furthermore, it was found that sGAG depletion did not significantly alter the tangent modulus, energy dissipation, and peak strain of posterior scleral strips. It was concluded that sGAGs did not influence the stress-controlled viscoelastic tensile response of sclera.

Reproducibility in the statistical analyses of data from high-throughput phenotyping screens requires a robust and reliable analysis foundation that allows modelling of different possible statistical scenarios. Regular challenges are scalability and extensibility of the analysis software. In this manuscript, we describe OpenStats, a freely available software package that addresses these challenges. We show the performance of the software in a high-throughput phenomic pipeline in the International Mouse Phenotyping Consortium (IMPC) and compare the agreement of the results with the most similar implementation in the literature. OpenStats has significant improvements in speed and scalability compared to existing software packages including a 13-fold improvement in computational time to the current production analysis pipeline in the IMPC. Reduced complexity also promotes FAIR data analysis by providing transparency and benefiting other groups in reproducing and re-usability of the statistical methods and results. OpenStats is freely available under a Creative Commons license at www.bioconductor.org/packages/OpenStats.

Following the Evidence Based Medicine (EBM) practice, practitioners make use of the existing evidence to make therapeutic decisions. This evidence, in the form of scientific statements, is usually found in scholarly publications such as randomised control trials and systematic reviews. However, finding such information in the overwhelming amount of published material is particularly challenging. Approaches have been proposed to automatically extract scientific artefacts in EBM using standardised schemas. Our work takes this stream a step forward and looks into consolidating extracted artefacts-i.e., quantifying their degree of similarity based on the assumption that they carry the same rhetorical role. By semantically connecting key statements in the literature of EBM, practitioners are not only able to find available evidence more easily, but also can track the effects of different treatments/outcomes in a number of related studies. We devise a regression model based on a varied set of features and evaluate it both on a general English corpus (the SICK corpus), as well as on an EBM corpus (the NICTA-PIBOSO corpus). Experimental results show that our approach performs on par with the state of the art on the general English and achieves encouraging results on the biomedical text when compared against human judgement.

Corynebacteria are used for a wide variety of industrial purposes but some species are associated with human diseases. With increasing number of corynebacterial genomes having been sequenced, comparative analysis of these strains may provide better understanding of their biology, phylogeny, virulence and taxonomy that may lead to the discoveries of beneficial industrial strains or contribute to better management of diseases. To facilitate the ongoing research of corynebacteria, a specialized central repository and analysis platform for the corynebacterial research community is needed to host the fast-growing amount of genomic data and facilitate the analysis of these data. Here we present CoryneBase, a genomic database for Corynebacterium with diverse functionality for the analysis of genomes aimed to provide: (1) annotated genome sequences of Corynebacterium where 165,918 coding sequences and 4,180 RNAs can be found in 27 species; (2) access to comprehensive Corynebacterium data through the use of advanced web technologies for interactive web interfaces; and (3) advanced bioinformatic analysis tools consisting of standard BLAST for homology search, VFDB BLAST for sequence homology search against the Virulence Factor Database (VFDB), Pairwise Genome Comparison (PGC) tool for comparative genomic analysis, and a newly designed Pathogenomics Profiling Tool (PathoProT) for comparative pathogenomic analysis. CoryneBase offers the access of a range of Corynebacterium genomic resources as well as analysis tools for comparative genomics and pathogenomics. It is publicly available at http://corynebacterium.um.edu.my/.

Numerous changes in epigenetic mechanisms have been described in various types of tumors. In search for new biomarkers, we investigated the expression of Polycomb-group (PcG) proteins EZH2, BMI1 and SUZ12 and associated histone modification H3K27me3 in colorectal cancer. Nuclear expression of PcG proteins and histone modification H3K27me3 were immunohistochemically (IHC) stained on a tissue microarray (TMA), including 247 tumor tissues and 47 normal tissues, and scored using the semi-automated Ariol system. Tumor tissues showed higher expression of EZH2 (p = 0.05) and H3K27me3 (p

SUMMARY: Mycobacterium abscessus is a rapidly growing non-tuberculous mycobacterial species that has been associated with a wide spectrum of human infections. As the classification and biology of this organism is still not well understood, comparative genomic analysis on members of this species may provide further insights on their taxonomy, phylogeny, pathogenicity and other information that may contribute to better management of infections. The MabsBase described in this paper is a user-friendly database providing access to whole-genome sequences of newly discovered M. abscessus strains as well as resources for whole-genome annotations and computational predictions, to support the expanding scientific community interested in M. abscessus research. The MabsBase is freely available at http://mabscessus.um.edu.my.

Pulse repetition interval modulation (PRIM) is integral to radar identification in modern electronic support measure (ESM) and electronic intelligence (ELINT) systems. Various distortions, including missing pulses, spurious pulses, unintended jitters, and noise from radar antenna scans, often hinder the accurate recognition of PRIM. This research introduces a novel three-stage approach for PRIM recognition, emphasizing the innovative use of PRI sound. A transfer learning-aided deep convolutional neural network (DCNN) is initially used for feature extraction. This is followed by an extreme learning machine (ELM) for real-time PRIM classification. Finally, a gray wolf optimizer (GWO) refines the network's robustness. To evaluate the proposed method, we develop a real experimental dataset consisting of sound of six common PRI patterns. We utilized eight pre-trained DCNN architectures for evaluation, with VGG16 and ResNet50V2 notably achieving recognition accuracies of 97.53% and 96.92%. Integrating ELM and GWO further optimized the accuracy rates to 98.80% and 97.58. This research advances radar identification by offering an enhanced method for PRIM recognition, emphasizing the potential of PRI sound to address real-world distortions in ESM and ELINT systems., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Hasani Azhdari et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: One of the common concerns of healthcare systems is the potential for re-admission of COVID-19 patients. In addition to adding costs to the healthcare system, re-admissions also endanger patient safety. Recognizing the factors that influence re-admission, can help provide appropriate and optimal health care. The aim of this study was to assess comorbidities that affect re-admission and survival in COVID-19 patients using a joint frailty model., Methods: This historical cohort study was done using data of patients with COVID-19 who were re-hospitalized more than twice in a referral hospital in North of Iran. We used the joint frailty model to investigate prognostic factors of survival and recurrence, simultaneously using R version 3.5.1 (library "frailtypack"). P-values less than 0.05 were considered as statistically significant., Results: A total of 112 patients with mean (SD) age of 63.76 (14.58) years old were recruited into the study. Forty-eight (42.9%) patients died in which 53.83% of them were re-admitted for a second time. Using adjusted joint model, the hazard of re-admission increased with cancer (Hazard ratio (HR) = 1.92) and hyperlipidemia (HR = 1.22). Furthermore, the hazard of death increased with hyperlipidemia (HR = 4.05) followed by age (HR = 1.76) and cancer (HR = 1.64). It Also decreased with lung disease (HR = 0.11), hypothyroidism (HR = 0.32), and hypertension (HR = 0.97)., Conclusion: Considering the correlation between re-admission and mortality in the joint frailty model, malignancy and hyperlipidemia increased the risk of both re-admission and mortality. Moreover, lung disease probably due to the use of corticosteroids, was a protective factor against both mortality and re-admission., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Yazdani et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Leishmaniasis refers to a disease with a wide range of manifestations; and there are three main forms of disease, cutaneous, mucocutaneous, and visceral. Leishmaniasis is one of the diseases with a protozoan agent which is vector-borne. Visceral leishmaniasis (VL) is the most severe form that can be fiercely life-threatening if left untreated. VL can be caused by members of Leishmania donovani complex, in Iran, Leishmania infantum is considered the primary causative agent of VL, resulting in a zoonotic form of VL. The two main goals of our work, which followed our prior sero-epidemiological and entomological survey, were to characterize and conduct a phylogenetic analysis of the Leishmania species that infect people, dogs, and sandflies. The samples were collected throughout 2017, from January to December, so blood samples were collected from humans and dogs, while sandfly samples were collected with sticky traps. DNA extracted from all seropositive samples of humans and dogs, 10% of sero-negative human samples, and all collected sandflies were subjected to kDNA-nested-PCR for tracing parasites. A total of 30 samples, including 20 human samples, 8 dog samples, and 2 sandfly samples, were found positive for the kDNA gene of L. infantum. Sequences were evaluated to study the genetic diversity among the six discovered L. infantum. Based on kDNA, the phylogenetic study of L. infantum demonstrated a high level of genetic variety and a relationship between the host, the parasite's geographic origin, and its genetic diversity., Competing Interests: The authors declare that they have no conflict of interest., (Copyright: © 2024 Behniafar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Quad bikes are popular recreational, four-wheeled bikes in the Middle East. Injury prevention programs targeting quad bike crashes in the United Arab Emirates (UAE) need evidence about the risk factors and behaviours associated with these crashes in the target population. This is a protocol for a study aiming to investigate quad bike rider behaviours and to assess the risk factors associated with related injuries in the UAE., Methods: This is a cross-sectional observational study aiming to describe a seasonal sport in a desert environment. With an estimated sample size of 451, the survey will follow a three-stage, location-based sampling strategy using the line-transect method. A sampling frame of desert locations with high injury incidences was developed, using Dubai ambulance injury records. Further expansion of the sampling frame was participatory, involving police, enthusiasts, emergency responders and gas station employees. The data collection will be limited to the winter months in fifteen high-injury desert locations across three major Emirates in the UAE. Trained researchers will observe the riders directly in the desert to note their riding habits, followed by a researcher-administered interview on riding and injury history. The interviews will be administered in Arabic and English using Qualtrics software on handheld tablets with offline and online entry mode. In addition, paper-based entry with the same format will be used as a contingency in busy quad bike locations., Conclusion: The objective of this study protocol is to develop a comprehensive survey that will furnish substantial evidence for the formulation of effective injury prevention strategies. To enhance the credibility of the recorded riding behaviors, field observations will be employed. The uniqueness of this study lies in its innovative sampling strategy, custom-tailored to accommodate the highly mobile and transient population of desert bikers in the UAE., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Menon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objectives: Caffeine's potential benefits on multiple sclerosis (MS), as well as on the ambulatory performance of non-MS populations, prompted us to evaluate its potential effects on balance, mobility, and health-related quality of life (HR-QoL) of persons with MS (PwMS)., Methods: This single-arm pilot clinical trial consisted of a 2-week placebo run-in and a 12-week caffeine treatment (200 mg/day) stage. The changes in outcome measures during the study period (weeks 0, 2, 4, 8, and 12) were evaluated using the Generalized Estimation Equation (GEE). The outcome measures were the 12-item Multiple Sclerosis Walking Scale (MSWS-12) for self-reported ambulatory disability, Berg Balance Scale (BBS) for static and dynamic balance, Timed Up and Go (TUG) for dynamic balance and functional mobility, Multiple Sclerosis Impact Scale (MSIS-29) for patient's perspective on MS-related QoL (MS-QoL), and Patients' Global Impression of Change (PGIC) for subjective assessment of treatment efficacy. GEE was also used to evaluate age and sex effect on the outcome measures over time. (Iranian Registry of Clinical Trials, IRCT2017012332142N1)., Results: Thirty PwMS were included (age: 38.89 ± 9.85, female: 76.7%). Daily caffeine consumption significantly improved the objective measures of balance and functional mobility (BBS; P-value<0.001, and TUG; P-value = 0.002) at each study time point, and the subjective measure of MS-related QoL (MSIS-29; P-value = 0.005) two weeks after the intervention. Subjective measures of ambulatory disability (MSWS-12) and treatment efficacy (PGIC) did not significantly change. The effect of age and sex on the outcome measures were also assessed; significant sex-time interaction effects were found for MSWS-12 (P-value = 0.001) and PGIC (P-value<0.001). The impact of age on BBS scores increased as time progressed (P-value = 0.006)., Conclusions: Caffeine may enhance balance, functional mobility, and QoL in PwMS. Being male was associated with a sharper increase in self-reported ambulatory disability over time. The effects of aging on balance get more pronounced over time., Trial Registration: This study was registered with the Iranian Registry of Clinical Trials (Registration number: IRCT2017012332142N1), a Primary Registry in the WHO Registry Network., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Dadvar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The rapid spread and evolving nature of COVID-19 variants have raised concerns regarding their competitive dynamics and coinfection scenarios. In this study, we assess the competitive interactions between the Omicron variant and other prominent variants (Alpha, Beta and Delta) on a social network, considering both single infection and coinfection states. Using the SIRS model, we simulate the progression of these variants and analyze their impact on infection rates, mortality and overall disease burden. Our findings demonstrate that the Alpha and Beta strains exhibit comparable contagion levels, with the Alpha strain displaying higher infection and mortality rates. Moreover, the Delta strain emerges as the most prevalent and virulent strain, surpassing the other variants. When introduced alongside the less virulent Omicron strain, the Delta strain results in higher infection and mortality rates. However, the Omicron strain's dominance leads to an overall increase in disease statistics. Remarkably, our study highlights the efficacy of the Omicron variant in supplanting more virulent strains and its potential role in mitigating the spread of infectious diseases. The Omicron strain demonstrates a competitive advantage over the other variants, suggesting its potential to reduce the severity of the disease and alleviate the burden on healthcare systems. These findings underscore the importance of monitoring and understanding the dynamics of COVID-19 variants, as they can inform effective prevention and mitigation strategies, particularly with the emergence of variants that possess a relative advantage in controlling disease transmission., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Jabraeilian, Jamali. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Road grade or slope is a key factor for walking and cycling behavior and outcomes (influencing route, speed, energy, etc.). For this reason, the scarcity of precise road grade data presents a challenge for travel information and analysis. This paper examines the accuracy of using crowd-sourced GPS data from a fitness application to estimate roadway grade profiles, which can then be used to develop network-wide road grade datasets. We externally validate an elevation estimation method described by McKenzie and Janowicz using field surveying data, and then propose and evaluate modifications for estimation of road grade (which is more directly relevant than elevation for walking and cycling analysis). We find that a modest amount of crowd-sourced GPS data can be used to generate relatively accurate road grade estimates: better than commonly-used low-resolution elevation models, but not as accurate as high-resolution data derived from LiDAR (Light Detection and Ranging). We also find that the grade estimates are more reliable than the elevation estimates, relative to alternative data sources. The most accurate method to aggregate crowd-sourced GPS data builds a composite roadway grade profile using partition-around-medoid clustering of individual grade sequences, first smoothed with a Savitzky-Golay filter and cleaned with Density-Based Spatial Clustering of Applications with Noise (DBSCAN). Implementing this method with an average of 150 GPS traces per location yields a root mean square error (RMSE) of 1% road grade. The findings in this paper can be used to incorporate precise road grade information into street network datasets over a wide spatial scale, which is necessary for walking and cycling analysis that fully considers the physiological aspects of active transportation., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Berjisian et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Accurate velocity reconstruction is essential for assessing coronary artery disease. We propose a Gaussian process method to reconstruct the velocity profile using the sparse data of the positron emission particle tracking (PEPT) in a biological environment, which allows the measurement of tracer particle velocity to infer fluid velocity fields. We investigated the influence of tracer particle quantity and detection time interval on flow reconstruction accuracy. Three models were used to represent different levels of stenosis and anatomical complexity: a narrowed straight tube, an idealized coronary bifurcation with stenosis, and patient-specific coronary arteries with a stenotic left circumflex artery. Computational fluid dynamics (CFD), particle tracking, and the Gaussian process of kriging were employed to simulate and reconstruct the pulsatile flow field. The study examined the error and uncertainty in velocity profile reconstruction after stenosis by comparing particle-derived flow velocity with the CFD solution. Using 600 particles (15 batches of 40 particles) released in the main coronary artery, the time-averaged error in velocity reconstruction ranged from 13.4% (no occlusion) to 161% (70% occlusion) in patient-specific anatomy. The error in maximum cross-sectional velocity at peak flow was consistently below 10% in all cases. PEPT and kriging tended to overestimate area-averaged velocity in higher occlusion cases but accurately predicted maximum cross-sectional velocity, particularly at peak flow. Kriging was shown to be useful to estimate the maximum velocity after the stenosis in the absence of negative near-wall velocity., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Keramati et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: Teaching-learning is the heart of medical education in the clinical setting. The objective of this research was to develop a conceptual model of effective clinical teaching in undergraduate medical education and conceptualize its operational framework based on the best fit approach., Materials and Methods: This research consisted of three sub-studies conducted using a multi-method approach. The first sub-study was conducted using a qualitative meta-synthesis approach. The second sub-study used Clarke's situational analysis approach as a postmodern version of grounded theory. Finally, the third sub-study was designed in two stages. First, it was conducted using the expert panel, in the second step, framework of synthesis based on best fit, and the framework of Ottenhoff- de Jonge et al., which formed the basis of this study., Results: In the first sub-study, qualitative evidence on the factors of effective teaching-learning in clinical education was synthesized into five dimensions. Based on the second sub-study, the clinical teaching-learning situation in undergraduate medical education in Iran was represented in three maps, including situational, social worlds/arenas, and positional. Finally, in the third sub-study, based on model modification and development in the expert panel, the effective teaching-learning dimensions were developed into behavioral, social, pedagogical, technology, contextual, educational leadership, and financial dimensions. In the second step, based on the framework of Ottenhoff- de Jonge et al., a three-dimensional matrix was developed concerning epistemological orientations about teaching and learning., Discussion: Moving from a single teaching-centered and learning-centered orientation to a teaching-learning-centered orientation is required for effective teaching-learning in clinical medical education., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Khani et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The important feature of petunia in tissue culture is its unpredictable and genotype-dependent callogenesis, posing challenges for efficient regeneration and biotechnology applications. To address this issue, machine learning (ML) can be considered a powerful tool to analyze callogenesis data, extract key parameters, and predict optimal conditions for petunia callogenesis, facilitating more controlled and productive tissue culture processes. The study aimed to develop a predictive model for callogenesis in petunia using ML algorithms and to optimize the concentrations of phytohormones to enhance callus formation rate (CFR) and callus fresh weight (CFW). The inputs for the model were BAP, KIN, IBA, and NAA, while the outputs were CFR and CFW. Three ML algorithms, namely MLP, RBF, and GRNN, were compared, and the results revealed that GRNN (R2≥83) outperformed MLP and RBF in terms of accuracy. Furthermore, a sensitivity analysis was conducted to determine the relative importance of the four phytohormones. IBA exhibited the highest importance, followed by NAA, BAP, and KIN. Leveraging the superior performance of the GRNN model, a genetic algorithm (GA) was integrated to optimize the concentration of phytohormones for maximizing CFR and CFW. The genetic algorithm identified an optimized combination of phytohormones consisting of 1.31 mg/L BAP, 1.02 mg/L KIN, 1.44 mg/L NAA, and 1.70 mg/L IBA, resulting in 95.83% CFR. To validate the reliability of the predicted results, optimized combinations of phytohormones were tested in a laboratory experiment. The results of the validation experiment indicated no significant difference between the experimental and optimized results obtained through the GA. This study presents a novel approach combining ML, sensitivity analysis, and GA for modeling and predicting callogenesis in petunia. The findings offer valuable insights into the optimization of phytohormone concentrations, facilitating improved callus formation and potential applications in plant tissue culture and genetic engineering., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Rezaei et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: Thyroid Cancer (TC) is the most frequent endocrine malignancy neoplasm. It is the sixth cause of cancer in women worldwide. The treatment process could be expedited by identifying the controlling molecular mechanisms at the early and late stages, which can contribute to the acceleration of treatment schemes and the improvement of patient survival outcomes. In this work, we study the significant mRNAs through Machine Learning Algorithms in both the early and late stages of Papillary Thyroid Cancer (PTC)., Method: During the course of our study, we investigated various methods and techniques to obtain suitable results. The sequence of procedures we followed included organizing data, using nested cross-validation, data cleaning, and normalization at the initial stage. Next, to apply feature selection, a t-test and binary Non-Dominated Sorting Genetic Algorithm II (NSGAII) were chosen to be employed. Later on, during the analysis stage, the discriminative power of the selected features was evaluated using machine learning and deep learning algorithms. Finally, we considered the selected features and utilized Association Rule Mining algorithm to identify the most important ones for improving the decoding of dominant molecular mechanisms in PTC through its early and late stages., Result: The SVM classifier was able to distinguish between early and late-stage categories with an accuracy of 83.5% and an AUC of 0.78 based on the identified mRNAs. The most significant genes associated with the early and late stages of PTC were identified as (e.g., ZNF518B, DTD2, CCAR1) and (e.g., lnc-DNAJB6-7:7, RP11-484D2.3, MSL3P1), respectively., Conclusion: Current study reveals a clear picture of the potential candidate genes that could play a major role not only in the early stage, but also throughout the late one. Hence, the findings could be of help to identify therapeutic targets for more effective PTC drug developments., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Hosseiniyan Khatibi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

People with communication difficulties encounter several challenges in their daily online interactions, such as a limited right to talk (RoT), insufficient social support (SS), and a low sense of being attended to (SoBA). Computer-mediated technologies are limited in addressing such problems owing to their limited capacity in transferring verbal and nonverbal cues between users. In this study, to address the limited RoT, low SS, and low SoBA challenges, we proposed a robotic video conference system with two teleoperated robot avatars. The proposed system was compared with another robotic video conference system that adopts only one teleoperated robot avatar. In the field experiment, 37 participants took part in two discussion sessions using each system type, where RoT, SS, and SoBA were adopted as the measured indices. The proposed system significantly increased the users' RoT and SS compared with other robotic video conference systems. This study contributes to the literature by demonstrating the effect exerted by the type of robotic video conference adopted on users' feelings about RoT, SS, and SoBA., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Mehmood et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Acute kidney injury is a complication of COVID-19 and is associated with severity. Despite no specific antiviral treatment strategy, lopinavir/ritonavir and remdesivir have been used. Data on the association between AKI and receiving antiviral agents with outcomes in hospitalized patients with COVID-19 is scarce. We aimed to determine the incidence of AKI and its outcomes in COVID-19 patients with and without antiviral medications., Methods: We conducted a retrospective study on hospitalized adult patients with SARS-CoV-2 infection in a tertiary center. The primary endpoint was determining mortality, intensive care unit (ICU) admission, and length of hospitalization affected by AKI development using antiviral agents. The logistic regression method was used to explore the predictive effects of AKI and antiviral therapy on composite outcomes (i.e., mortality, ICU admission, and prolonged hospitalization) in four defined groups by AKI development/not and utilizing antivirals/not. We used IBM SPSS version 24.0 software for statistical analysis., Results: Out of 833 COVID-19 patients who were included, 75 patients were treated with antiviral agents and developed AKI. There was a significant difference in the occurrence of AKI and using antiviral medications (p = 0.001). Also, the group using antiviral agents and the development of AKI had the highest rate of preexisting hypertension (p = 0.002). Of note, the group of patients who used antiviral agents and also developed AKI had the most remarkable association with our composite outcome (p<0.0001), especially ICU admission (OR = 15.22; 95% CI: 8.06-27.32)., Conclusions: The presence of AKI among COVID-19 patients treated with antiviral agents is linked to increased severity and mortality. Therefore, it is imperative to explore preventive measures for AKI development in patients receiving antiviral therapy. Larger-scale randomized controlled trials may be warranted to provide a more comprehensive understanding of these associations., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Mousavi Movahed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: There is debate over whether physical attendance at school affects the spread of the SARS-CoV-2 pandemic., Methods: A cohort of personnel from several schools in Qatar provided nasopharyngeal swabs (NPS) for SARS-CoV-2 RT-PCR and rapid antigen testing. Each of them was monitored for infection until February 2022., Results: In total, 3,241 employees gave samples for analysis. Prior to the start of the 2020-2021 academic year (Group I), 3.49% of samples tested positive for SARS-CoV-2. Most of the positive PCR results were from male, senior, non-teaching staff members. Only 110 (3.39%) employees who had enrolled in face-to-face instruction before the B.1.1.7 variant's emergence (Group II), 238 (7.34%) after the B.1.1.7 variant's emergence (Group III), and 410 (12.65%) after the introduction of the Omicron variant (Group IV) had reported infection by PCR test. Most people who tested positive by PCR after enrolling in school were young, female teachers. In the Cox Proportional-Hazards Model, exposure to a confirmed case, the presence of symptoms in the two weeks prior to exposure in all groups-young age in Groups II and III, male gender in Groups I and IV, shared housing in Group III, and the presence of comorbidities in Groups II and III independently predicted SARS-CoV-2 infection in school staff., Conclusion: Critical information about the risk of SARS-CoV-2 infection in school workers during the whole pandemic is provided by our study. School operations in Qatar were made safer through initial and ongoing screenings, as well as widespread vaccination of school personnel., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Alishaq et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

When there is an extensive number of inputs and outputs compared to the number of DMUs, one of the drawbacks of Data Envelopment Analysis appears, which incorrectly classifies inefficient DMUs, as efficient ones. Accordingly, the DEA ranking power becomes further moderated. To improve the ranking power, this paper renders the details of an algorithm that presents a model combining the Principal Component Analysis and the Slacks-Based Measure (PCA-SBM) which reduces the number of the incorrectly determined efficient DMUs. Also to complete ranking of DMUs, the algorithm presents a Super-Efficiency model integrated with PCA (PCA-Super SBM) which can rank the efficient DMUs (extreme and non-extreme). Whereas the most important previous models for ranking efficient units cannot rank non-extreme ones. Additionally, in most previous studies, DEA models combined with PCA fail to handle negative data, while, the presented models can cover this data. Two case studies (pharmaceutical companies listed on the Iranian stock market and bank branches) are manipulated to demonstrate the applicability and performance of the algorithm. To show the superiority of the presented models, the SBM model without PCA and the Super SBM model without PCA have been implemented on the data of both cases. In comparing the two methods (PCA-SBM and SBM), the PCA-SBM model has higher ranking power (five efficient DMUs versus nineteen in the case of pharmaceutical companies and four efficient DMUs versus twenty-nine in the case of bank branches). Also in comparing the PCA-Super SBM and Super SBM, the PCA-Super SBM model works more powerfully in complete ranking. As the Super SBM model cannot rank non-extreme units unlike the PCA-Super SBM. Consequently, the presented algorithm works successfully in ranking the DMUs completely (inefficient, extreme, and non-extreme efficient) with low complexity., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Yazdi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Short- and long-wavelength light can alter pupillary responses differently, allowing inferences to be made about the contribution of different photoreceptors on pupillary constriction. In addition to classical retinal photoreceptors, the pupillary light response is formed by the activity of melanopsin-expressing intrinsically photosensitive retinal ganglion cells (ipRGC). It has been shown in rodents that melanopsin is expressed in the axons of ipRGCs that bundle at the optic nerve head, which forms the perceptual blind-spot. Hence, the first aim of this study was to investigate if blind-spot stimulation induces a pupillary response. The second aim was to investigate the effect of blind-spot stimulation by using the contrast sensitivity tests. Fifteen individuals participated in the pupil response experiment and thirty-two individuals in the contrast sensitivity experiment. The pupillary change was quantified using the post-illumination pupil response (PIPR) amplitudes after blue-light (experimental condition) and red-light (control condition) pulses in the time window between 2 s and 6 s post-illumination. The contrast sensitivity was assessed using two different tests: the Freiburg Visual Acuity Test and Contrast Test and the Tuebingen Contrast Sensitivity Test, respectively. Contrast sensitivity was measured before and 20 minutes after binocular blue-light stimulation of the blind-spot at spatial frequencies higher than or equal to 3 cycles per degree (cpd) and at spatial frequencies lower than 3 cpd (control condition). Blue-light blind-spot stimulation induced a significantly larger PIPR compared to red-light, confirming a melanopsin-mediated pupil-response in the blind-spot. Furthermore, contrast sensitivity was increased after blind-spot stimulation, confirmed by both contrast sensitivity tests. Only spatial frequencies of at least 3 cpd were enhanced. This study demonstrates that stimulating the blind-spot with blue-light constricts the pupil and increases the contrast sensitivity at higher spatial frequencies., Competing Interests: TS and HB are employees of Dopavision GmbH. HB is supported by and has financial interest in Dopavision GmbH. Remaining authors have no competing interest. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2023 Schilling et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Providing intensive care to acute patients is a vital part of health systems. However, the high cost of Intensive Care Units (ICU) has limited their development, especially in low-income countries. Due to the increasing need for intensive care and limited resources, ICU cost management is important. This study aimed to analyze the cost-benefit of ICU during COVID-19 in Tehran, Iran., Methods: This cross-sectional study is an economic evaluation of health interventions. The study was conducted in the COVID-19 dedicated ICU, from the provider's point of view and within one-year horizon. Costs were calculated using a top-down approach and the Activity-Based Costing technique. Benefits were extracted from the hospital's HIS system. Benefit Cost ratio (BCR) and Net Present Value (NPV) indexes were used for cost-benefit analysis (CBA). A sensitivity analysis was performed to evaluate the dependence of the CBA results on the uncertainties in the cost data. Analysis was performed with Excel and STATA software., Results: The studied ICU had 43 personnel, 14 active beds, a 77% bed occupancy rate, and 3959 occupied bed days. The total costs were $2,372,125.46 USD, of which 70.3% were direct costs. The highest direct cost was related to human resources. The total net income was $1,213,314.13 USD. NPV and BCR were obtained as $-1,158,811.32 USD and 0.511 respectively., Conclusion: Despite operating with a relatively high capacity, ICU has had high losses during the COVID-19. Proper management and re-planning in the structure of human resources is recommended due to its importance in the hospital economy, provision of resources based on needs assessment, improvement of drugs management, reduction of insurance deductions in order to reduce costs and improve ICU productivity., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Rahimi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The process of optimizing in vitro seed sterilization and germination is a complicated task since this process is influenced by interactions of many factors (e.g., genotype, disinfectants, pH of the media, temperature, light, immersion time). This study investigated the role of various types and concentrations of disinfectants (i.e., NaOCl, Ca(ClO)2, HgCl2, H2O2, NWCN-Fe, MWCNT) as well as immersion time in successful in vitro seed sterilization and germination of petunia. Also, the utility of three artificial neural networks (ANNs) (e.g., multilayer perceptron (MLP), radial basis function (RBF), and generalized regression neural network (GRNN)) as modeling tools were evaluated to analyze the effect of disinfectants and immersion time on in vitro seed sterilization and germination. Moreover, non‑dominated sorting genetic algorithm‑II (NSGA‑II) was employed for optimizing the selected prediction model. The GRNN algorithm displayed superior predictive accuracy in comparison to MLP and RBF models. Also, the results showed that NSGA‑II can be considered as a reliable multi-objective optimization algorithm for finding the optimal level of disinfectants and immersion time to simultaneously minimize contamination rate and maximize germination percentage. Generally, GRNN-NSGA-II as an up-to-date and reliable computational tool can be applied in future plant in vitro culture studies., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Rezaei et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The activities of alpha-amylase, beta-amylase, sucrose synthase, and invertase enzymes are under the influence of storage conditions and can affect the structure of starch, as well as the sugar content of potatoes, hence altering their quality. Storage in a warehouse is one of the most common and effective methods of storage to maintain the quality of potatoes after their harvest, while preserving their freshness and sweetness. Smart monitoring and evaluation of the quality of potatoes during the storage period could be an effective approach to improve their freshness. This study is aimed at assessing the changes in the potato quality by an electronic nose (e-nose) in terms of the sugar and carbohydrate contents. Three potato cultivars (Agria, Santé, and Sprite) were analyzed and their quality variations were separately assessed. Quality parameters (i.e. sugar and carbohydrate contents) were evaluated in six 15-day periods. The e-nose data were analyzed by means of chemometric methods, including principal component analysis (PCA), linear data analysis (LDA), support vector machine (SVM), and artificial neural network (ANN). Quadratic discriminant analysis (QDA) and multivariate discrimination analysis (MDA) offer the highest accuracy and sensitivity in the classification of data. The accuracy of all methods was higher than 90%. These results could be applied to present a new approach for the assessment of the quality of stored potatoes., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Khorramifar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Detection of fatigue helps prevent injuries and optimize the performance of horses. Previous studies tried to determine fatigue using physiological parameters. However, measuring the physiological parameters, e.g., plasma lactate, is invasive and can be affected by different factors. In addition, the measurement cannot be done automatically and requires a veterinarian for sample collection. This study investigated the possibility of detecting fatigue non-invasively using a minimum number of body-mounted inertial sensors. Using the inertial sensors, sixty sport horses were measured during walk and trot before and after high and low-intensity exercises. Then, biomechanical features were extracted from the output signals. A number of features were assigned as important fatigue indicators using neighborhood component analysis. Based on the fatigue indicators, machine learning models were developed for classifying strides to non-fatigue and fatigue. As an outcome, this study confirmed that biomechanical features can indicate fatigue in horses, such as stance duration, swing duration, and limb range of motion. The fatigue classification model resulted in high accuracy during both walk and trot. In conclusion, fatigue can be detected during exercise by using the output of body-mounted inertial sensors., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Darbandi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Lipoprotein lipase (LPL), a crucial enzyme in the intravascular hydrolysis of triglyceride-rich lipoproteins, is a potential drug target for the treatment of hypertriglyceridemia. The activity and stability of LPL are influenced by a complex ligand network. Previous studies performed in dilute solutions suggest that LPL can appear in various oligomeric states. However, it was not known how the physiological environment, that is blood plasma, affects the action of LPL. In the current study, we demonstrate that albumin, the major protein component in blood plasma, has a significant impact on LPL stability, oligomerization, and ligand interactions. The effects induced by albumin could not solely be reproduced by the macromolecular crowding effect. Stabilization, isothermal titration calorimetry, and surface plasmon resonance studies revealed that albumin binds to LPL with affinity sufficient to form a complex in both the interstitial space and the capillaries. Negative stain transmission electron microscopy and raster image correlation spectroscopy showed that albumin, like heparin, induced reversible oligomerization of LPL. However, the albumin induced oligomers were structurally different from heparin-induced filament-like LPL oligomers. An intriguing observation was that no oligomers of either type were formed in the simultaneous presence of albumin and heparin. Our data also suggested that the oligomer formation protected LPL from the inactivation by its physiological regulator angiopoietin-like protein 4. The concentration of LPL and its environment could influence whether LPL follows irreversible inactivation and aggregation or reversible LPL oligomer formation, which might affect interactions with various ligands and drugs. In conclusion, the interplay between albumin and heparin could provide a mechanism for ensuring the dissociation of heparan sulfate-bound LPL oligomers into active LPL upon secretion into the interstitial space., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Risti et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Giardia duodenalis is a cryptic protozoan, which has eight assemblages (A-H). Assemblages A and B are the main genotypes reported from humans with probable anthroponotic and zoonotic transmission. The current study aimed to characterize G. duodenalis assemblages in tuberculosis (TB) patients and healthy subjects using multilocus genotyping (MLG). Thirty Giardia-positive stool samples, which were obtained from TB patients and healthy subjects were included in the study. After total DNA extraction, three β-giardin (bg), triosephosphate isomerase (tpi), glutamate dehydrogenase (gdh) genes were amplified and sequenced. Obtained sequences were compared to the GenBank database to characterize assemblages. Phylogenetic analysis using Maximum Likelihood (ML) and Tamura 3-parameter was performed for each gene. From 30 Giardia-positive subjects, 17 (57%) and 13 (43%) were from healthy and TB-infected subjects, respectively. There was no significant co-existence of Giardia and tuberculosis (P-value = 0.051). In addition, 14 (46.7%) and 16 (53.3%) of Giardia isolates were from asymptomatic and symptomatic subjects, respectively. PCR amplification was successful in 25 single samples (83.3%) consisted of 20 for tpi, 15 for bg, and 13 for gdh genes. Accordingly, 13/25 (52%) and 8/25 (32%) belonged to assemblage A and assemblages B, respectively, whereas 4/25 (16%) were either assemblage A or B with different genes at the same time. Significant correlation between assemblages and TB, age, and symptoms was not seen. The phylogenetic analyses represented no separation based on TB and gastrointestinal symptoms. Assemblage A was the predominant genotype in samples. The high frequency of assemblage AII indicated importance of anthroponotic transmission of Giardia in both healthy and TB patients. In addition, considering the exclusive reports of sub-assemblage AIII in wild ruminants, the presence of AIII in the current study have to be carefully interpreted. The inconsistency between the assemblage results of either bg or gdh loci with tpi gene signifies the insufficiency of single gene analysis and the necessity for MLG in molecular epidemiology of G. duodenalis., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Mohammad Rahimi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Fossil and archaeological evidence indicates that hominin dispersals into Southwest Asia occurred throughout the Pleistocene, including the expansion of Homo sapiens populations out of Africa. While there is evidence for hominin occupations in the Pleistocene in Iran, as evidenced by the presence of Lower to Upper Paleolithic archaeological sites, the extent to which humid periods facilitated population expansions into western Asia has remained unclear. To test the role of humid periods on hominin dispersals here we assess Paleolithic site distributions and paleoenvironmental records across Iran. We developed the first spatially comprehensive, high-resolution paleohydrological model for Iran in order to assess water availability and its influence on hominin dispersals. We highlight environmentally mediated routes which likely played a key role in Late Pleistocene hominin dispersals, including the expansion of H. sapiens and Neanderthals eastwards into Asia. Our combined analyses indicate that, during MIS 5, there were opportunities for hominins to traverse a northern route through the Alborz and Kopet Dagh Mountains and the Dasht-I Kavir desert owing to the presence of activated fresh water sources. We recognize a new southern route along the Zagros Mountains and extending eastwards towards Pakistan and Afghanistan. We find evidence for a potential northern route during MIS 3, which would have permitted hominin movements and species interactions in Southwest Asia. Between humid periods, these interconnections would have waned, isolating populations in the Zagros and Alborz Mountains, where hominins may have continued to have had access to water., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Shoaee et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Decreasing calories, salt, sugar and fat intake is considered the golden solution to reduce obesity and cardiovascular diseases (CVDs) related to unhealthy diet. This study aimed to investigate the health system induced barriers to a healthy diet in Iran., Methods: This is a qualitative health policy analysis. We collected data through 30 semi-structured, face-to-face interviews with purposefully identified experts, including policy-makers, top-level managers and related stakeholders. All interviews were transcribed verbatim, and analyzed with qualitative content analysis, facilitated by MAXQDA 11 software., Results: We identified six categories of barriers: structural problems within the Ministry of Health and Medical Education (MoHME), i.e. Supreme Council of Health and Food Security (SCHFS); the MoHME's inadequate stewardship of public health, the short life of the deputy of social affairs within the MoHME and its possible impact on the National Health Assembly; inefficient traffic lights labelling for foods; lack of adequate policies and guidelines for monitoring restaurants and fast foods and insufficient incentive policies for the food industry., Conclusion: In line with the World Health Organization (WHO) Global Action Plan, in 2015, Iran defined its roadmap for prevention and control of NCDs, i.e. some nutritional interventions. However, different stakeholders including MoHME and other sectors need to provide series of interventions to change people's approach about food choice so that they might reduce the consumption of foods with excessive salt, fat and sugar., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Amerzadeh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Problematic internet use (PIU) can cause mental and physical harm to individuals and may be an emerging factor contributing to unsafe work behavior. In this study, the relationship between PIU and safety behavior was investigated. Moreover, it was hypothesized that safety climate can moderate the relationship between PIU and safety behavior. Participants were employees from a mining industry in Iran. Three validated questionnaires were distributed to gather the required data regarding PIU, safety climate, and safety behavior. Hierarchical regression analysis was used to assess the moderating effect of safety climate on the relationship between PIU and safety behavior. The size of moderation effect was assessed using f2 index. Four hundred eighty-five employees participated in this study. The results demonstrated a negative relationship between PIU and safety behavior. The moderating effect of safety climate on the relationship between PIU and safety behavior was supported. The f2 index was 0.027 which demonstrates a small moderation effect. In conclusion, PIU has a significant negative effect on the safety behavior of employees. Providing a strong safety climate can be a long-term solution for reducing the negative effect of PIU on safety behavior., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Ghasemi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

With fast and reliable international transportation, more people with different language backgrounds can interact now. As a result, the need for communicative agents fluent in several languages to assist those people is highlighted. The high cost of hiring human attendants fluent in several languages makes using social robots a more affordable alternative in international gatherings. A social robot capable of presenting a piece of information in more than one language at the same time to its audience is the goal of this line of study. However, the negative effect of background noise on speech comprehension in humans is well-established. Hence, presenting a piece of information in two different languages at the same time by the robot creates an adverse listening condition for both individuals listening to the speech of such a bilingual robot. In this study, we investigated whether manipulating the pitch and gender of the robot's voice could affect human subjects' memory of the presented information in the presence of background noise. The results indicate that the pitch and gender of the speaking voice do indeed affect our memory of the presented information. when a male voice was used, a higher pitch resulted in significantly better memory performance than a lower pitch. Contrarily, when a female voice was used, a lower pitch resulted in significantly better memory in participants than a higher pitch. Both male and female subjects performed significantly better with a female voice in a noisy background. In nutshell, the result of this study suggests using a female voice for robots in noisy conditions, as in the case of simultaneously speaking robots, can significantly improve the retrieval of presented information in human subjects., Competing Interests: NO., (Copyright: © 2022 Pourfannan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The XRCC3 p.Thr241Met (rs861539) polymorphism has been extensively studied for its association with glioma risk, but results remain conflicting. Therefore, we performed a systematic review and meta-analysis to resolve this inconsistency., Methods: Studies published up to June 10, 2022, were searched in PubMed, Web of Science, Scopus, VIP, Wanfang, and China National Knowledge Infrastructure databases and screened for eligibility. Then, the combined odds ratio (OR) of the included studies was estimated based on five genetic models, i.e., homozygous (Met/Met vs. Thr/Thr), heterozygous (Thr/Met vs. Thr/Thr), dominant (Thr/Met + Met/Met vs. Thr/Thr), recessive (Met/Met vs. Thr/Thr + Thr/Met) and allele (Met vs. Thr). The study protocol was preregistered at PROSPERO (registration number: CRD42021235704)., Results: Overall, our meta-analysis of 14 eligible studies involving 12,905 subjects showed that the p.Thr241Met polymorphism was significantly associated with increased glioma risk in both homozygous and recessive models (homozygous, OR = 1.381, 95% CI = 1.081-1.764, P = 0.010; recessive, OR = 1.305, 95% CI = 1.140-1.493, P<0.001). Subgroup analyses by ethnicity also revealed a statistically significant association under the two aforementioned genetic models, but only in the Asian population and not in Caucasians (P>0.05)., Conclusion: We demonstrated that the XRCC3 p.Thr241Met polymorphism is associated with an increased risk of glioma only in the homozygous and recessive models., Competing Interests: The authors declare no conflicts of interest.

Background: A number of circulating micro-ribonucleic acids (miRNAs) have been introduced as convincing predictive determinants in a variety of cardiovascular diseases. This study aimed to evaluate some miRNAs' diagnostic and prognostic value in patients with acute heart failure (AHF)., Method: Forty-four AHF patients were randomly selected from a tertiary heart center, and 44 healthy participants were included in the control group. Plasma levels of assessed miRNAs, including miR -1, -21, -23, and -423-5-p were measured in both groups. The patients were followed for one year, and several clinical outcomes, including in-hospital mortality, one-year mortality, and the number of readmissions, were recorded., Results: An overall 88 plasma samples were evaluated. There was no significant difference in terms of demographic characteristics between the AHF and healthy groups. Our findings revealed that mean levels of miR-1, -21, -23, and -423-5-p in AHF patients were significantly higher than in the control group. Although all assessed miRNAs demonstrated high diagnostic potential, the highest sensitivity (77.2%) and specificity (97.7%) is related to miR-1 for the values above 1.22 (p = 0.001, AUC = 0.841; 95%CI, 0.751 to 946). Besides, the levels of miR-21 and -23 were significantly lower in patients with ischemia-induced HF. However, the follow-up data demonstrated no significant association between miRNAs and prognostic outcomes including in-hospital mortality, one-year mortality, and the number of readmissions., Conclusion: The result of our study demonstrated that miR-1, -21, -23, and -423-5-p can be taken into account as diagnostic aids for AHF. Nevertheless, there was no evidence supporting the efficacy of these miRNAs as prognostic factors in our study., Competing Interests: The authors have declared that no competing interests exist.

Background: The increasing burden of hypertension in low- to middle-income countries necessitates the assessment of care coverage to monitor progress and guide future policies. This study uses an ensemble learning approach to evaluate hypertension care coverage in a nationally representative Iranian survey., Methods: The data source was the cross-sectional 2016 Iranian STEPwise approach to risk factor surveillance (STEPs). Hypertension was based on blood pressure ≥140/90 mmHg, reported use of anti-hypertensive medications, or a previous hypertension diagnosis. The four steps of care were screening (irrespective of blood pressure value), diagnosis, treatment, and control. The proportion of patients reaching each step was calculated, and a random forest model was used to identify features associated with progression to each step. After model optimization, the six most important variables at each step were considered to demonstrate population-based marginal effects., Results: The total number of participants was 30541 (52.3% female, median age: 42 years). Overall, 9420 (30.8%) had hypertension, among which 89.7% had screening, 62.3% received diagnosis, 49.3% were treated, and 7.9% achieved control. The random forest model indicated that younger age, male sex, lower wealth, and being unmarried/divorced were consistently associated with a lower probability of receiving care in different levels. Dyslipidemia was associated with reaching diagnosis and treatment steps; however, patients with other cardiovascular comorbidities were not likely to receive more intensive blood pressure management., Conclusion: Hypertension care was mostly missing the treatment and control stages. The random forest model identified features associated with receiving care, indicating opportunities to improve effective coverage., Competing Interests: The authors have declared that no competing interests exist.

There is a disagreement on whether extremely low frequency electromagnetic fields (ELF-EMF) have a beneficial or harmful effect on anxiety-like behavior. Prenatal stress induces frequent disturbances in offspring physiology such as anxiety-like behavior extending to adulthood. This study was designed to evaluate the effects of prenatal stress and ELF-EMF exposure before and during pregnancy on anxiety-like behavior and some anxiety-related pathways in the hippocampus of female rat offspring. A total of 24 female rats 40 days of age were distributed into four groups of 6 rats each: control, Stress (rats whose mothers underwent chronic stress), EMF (rats whose mothers were exposed to electromagnetic fields) and EMF/S (rats whose mothers were simultaneously exposed to chronic stress and ELF-EMF). The rats were given elevated plus-maze and open field tests and then their brains were dissected and their hippocampus were subjected to analysis. ELISA was used to measure 24(S)-hydroxy cholesterol, corticosterone, and serotonin levels. Cryptochrome2, steroidogenic acute regulatory protein, 3B-Hydroxy steroid dehydrogenase, N-methyl-D-aspartate receptor 2(NMDAr2) and phosphorylated N-methyl-D-aspartate receptor 2(PNMDAr2) were assayed by immunoblotting. Anxiety-like behavior increased in all treatment groups at the same time EMF increased anxiety induced by maternal stress in the EMF/S group. The stress group showed decreased serotonin and increased corticosterone levels. ELF-EMF elevated the PNMDAr2/NMDAr2 ratio and 24(S)-hydroxy cholesterol compared to the control group but did not change corticosterone. EMF did not restore changes induced by stress in behavioral and molecular tests. The results of the current study, clarified that ELF-EMF can induce anxiety-like behavior which may be attributed to an increase in the PNMDAr2/NMDAr2 ratio and 24(S)-OHC in the hippocampus, and prenatal stress may contribute to anxiety via a decrease in serotonin and an increase in corticosterone in the hippocampus. We also found that anxiety-like behavior induced by maternal stress exposure, is exacerbated by electromagnetic fields radiation., Competing Interests: The authors have declared that no competing interests exist.

The emotion expressions of social robots are some of the most important developments in recent studies on human-robot interactions (HRIs). Several research studies have been conducted to assess effective factors to improve the quality of emotion expression of the robots. In this study, we examined the effects of a robot's vertical oscillation and transition on the quality of its emotion expression, where the former indicates the periodic up/down movement of the body of the robot, while the latter indicates a one-time up or down movement. Short-term and long-term emotion expressions of the robot were studied independently for the four basic emotions described in the circumplex model of emotions: joy, anger, sadness, and relief. We designed an experiment with an adequate statistical power and minimum sample size of human subjects based on a priori power analysis. Human subjects were asked to evaluate the robot's emotion expressions by watching its video with/without vertical movement. The results of the experiment showed that for the long-term emotions, the speed of vertical oscillation corresponded to the degree of arousal of the emotion expression as noted in the circumplex model; this indicated that fast oscillations improved the emotion expression with a higher degree of arousal, such as joy and anger, while slow or no oscillations were more suited to emotions with a lower degree of arousal, such as sadness and relief. For the short-term emotions, the direction of the vertical transition corresponded to the degree of valence for most of the expressed emotions, while the speed of vertical oscillation reflected the degree of arousal. The findings of this study can be adopted in the development of conversational robots to enhance their emotion expression., Competing Interests: The authors have declared that no competing interests exist.

A spatially-resolved understanding of the intensity of a flood hazard is required for accurate predictions of infrastructure reliability and losses in the aftermath. Currently, researchers who wish to predict flood losses or infrastructure reliability following a flood usually rely on computationally intensive hydrodynamic modeling or on flood hazard maps (e.g., the 100-year floodplain) to build a spatially-resolved understanding of the flood's intensity. However, both have specific limitations. The former requires both subject matter expertise to create the models and significant computation time, while the latter is a static metric that provides no variation among specific events. The objective of this work is to develop an integrated data-driven approach to rapidly predict flood damages using two emerging flood intensity heuristics, namely the Flood Peak Ratio (FPR) and NASA's Giovanni Flooded Fraction (GFF). This study uses data on flood claims from the National Flood Insurance Program (NFIP) to proxy flood damage, along with other well-established flood exposure variables, such as regional slope and population. The approach uses statistical learning methods to generate predictive models at two spatial levels: nationwide and statewide for the entire contiguous United States. A variable importance analysis demonstrates the significance of FPR and GFF data in predicting flood damage. In addition, the model performance at the state-level was higher than the nationwide level analysis, indicating the effectiveness of both FPR and GFF models at the regional level. A data-driven approach to predict flood damage using the FPR and GFF data offer promise considering their relative simplicity, their reliance on publicly accessible data, and their comparatively fast computational speed., Competing Interests: The authors have declared that no competing interests exist.

Background: The present systematic review and meta-analysis aimed to ascertain if the circulating levels of apelin, as an important regulator of the cardiovascular homeostasis, differ in patients with cardiovascular diseases (CVDs) and controls., Methods: A comprehensive search was performed in electronic databases including PubMed, Scopus, EMBASE, and Web of Science to identify the studies addressing apelin in CVD up to April 5, 2021. Due to the presence of different units to measure the circulating levels of apelin across the included studies, they expressed the standardized mean difference (SMD) and their 95% confidence interval (CI) as summary effect size. A random-effects model comprising DerSimonian and Laird method was used to pool SMDs., Results: Twenty-four articles (30 studies) comprised of 1793 cases and 1416 controls were included. Pooled results obtained through random-effects model indicated that apelin concentrations in the cases' blood samples were significantly lower than those of the control groups (SMD = -0.72, 95% CI: -1.25, -0.18, P = 0.009; I2 = 97.3%, P<0.001). New combined biomarkers showed a significant decrease in SMD of apelin/high-density lipoprotein cholesterol (apelin/HDL-C) ratio [-5.17; 95% CI, -8.72, -1.63, P = 0.000; I2 = 99.0%], apelin/low-density lipoprotein cholesterol (apelin/LDL-C) ratio [-4.31; 95% CI, -6.08, -2.55, P = 0.000; I2 = 98.0%] and apelin/total cholesterol (apelin/TC) ratio [-17.30; 95% CI, -22.85, -11.76, P = 0.000; I2 = 99.1%]. However, no significant differences were found in the SMD of apelin/triacylglycerol (apelin/TG) ratio in cases with CVDs compared to the control group [-2.96; 95% CI, -7.41, 1.49, P = 0.000; I2 = 99.2%]., Conclusion: The association of apelin with CVDs is different based on the region and disease subtypes. These findings account for the possible usefulness of apelin as an additional biomarker in the diagnosis of CVD in diabetic patients and in the diagnosis of patients with CAD. Moreover, apelin/HDL-c, apelin/LDL-c, and apelin/TC ratios could be offered as diagnostic markers for CVD., Competing Interests: I have read the journal’s policy and have no conflicts.

Purpose: Changes in retinal thickness are common in various ocular diseases. Transverse magnification due to differing ocular biometrics, in particular axial length, affects measurement of retinal thickness in different regions. This study evaluated the effect of axial length and refractive error on measured macular thickness in two community-based cohorts of healthy young adults., Methods: A total of 2160 eyes of 1247 community-based participants (18-30 years; 23.4% myopes, mean axial length = 23.6mm) were included in this analysis. Macular thickness measurements were obtained using a spectral-domain optical coherence tomography (which assumes an axial length of 24.385mm). Using a custom program, retinal thickness data were extracted at the 9 Early Treatment of Diabetic Retinopathy Study (ETDRS) regions with and without correction for transverse magnificent effects, with the corrected measurements adjusting according to the participant's axial length. Linear mixed models were used to analyse the effect of correction and its interaction with axial length or refractive group on retinal thickness., Results: The raw measures (uncorrected for axial length) underestimated the true retinal thickness at the central macula, while overestimating at most non-central macular regions. There was an axial length by correction interaction effect in all but the nasal regions (all p<0.05). For each 1mm increase in axial length, the central macular thickness is overestimated by 2.7-2.9μm while thicknesses at other regions were underestimated by 0.2-4.1μm. Based on the raw thickness measurements, myopes have thinner retinas than non-myopes at most non-central macular. However, this difference was no longer significant when the corrected data was used., Conclusion: In a community-based sample, the raw measurements underestimate the retinal thickness at the central macula and overestimate the retinal thickness at non-central regions of the ETDRS grid. The effect of axial length and refractive error on retinal thickness is reduced after correcting for transverse magnification effects resulting from axial length differences., Competing Interests: The authors have declared that no competing interests exist.

Engineered proteins generally must possess a stable structure in order to achieve their designed function. Stable designs, however, are astronomically rare within the space of all possible amino acid sequences. As a consequence, many designs must be tested computationally and experimentally in order to find stable ones, which is expensive in terms of time and resources. Here we use a high-throughput, low-fidelity assay to experimentally evaluate the stability of approximately 200,000 novel proteins. These include a wide range of sequence perturbations, providing a baseline for future work in the field. We build a neural network model that predicts protein stability given only sequences of amino acids, and compare its performance to the assayed values. We also report another network model that is able to generate the amino acid sequences of novel stable proteins given requested secondary sequences. Finally, we show that the predictive model-despite weaknesses including a noisy data set-can be used to substantially increase the stability of both expert-designed and model-generated proteins., Competing Interests: JMS and AZ are employed by Two Six Technologies, which has filed a patent on a portion of the technology described in this manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials.