Integration of statistical and simulation analyses for ternary hybrid nanofluid over a moving surface with melting heat transfer.

In industrial and engineering fields including lamination, melt-spinning, continuous casting, and fiber spinning, the flow caused by a continually moving surface is significant. Therefore, the problem of ternary hybrid nanofluid flow over a moving surface is studied. This study explores the stability and statistical analyses of the magnetohydrodynamics (MHD) forced flow of the ternary hybrid nanofluid with melting heat transfer phenomena. The impacts of viscous dissipation, Joule heating, and thermal radiation are also included in the flow. Different fluids including ternary hybrid nanofluid, hybrid nanofluids, and nanofluids with base fluid ethylene glycol (EG) are examined and compared, where magnetite (Fe3O4) and silica (SiO2) are taken as the magnetic nanomaterials while silver (Ag) is chosen as the nonmagnetic nanomaterial. The skin friction coefficient and the local Nusselt number are estimated through regression analysis. By employing similarity transformations, the governing partial differential equations are converted into non-linear ordinary differential equations. Then, the least square method is applied to solve the equations analytically. Dual solutions are established in a particular range of moving parameterλ. Due to this, a stability test is implemented to find the stable solution by using the bvp4c function in MATLAB software. It is found that the first solution is the stable one while the second is unstable. The use of ternary hybrid nanomaterials improves the heat transport rate. The increasing values of the Eckert number enlarge the heat passage. The fluid velocity and temperature profiles for nonmagnetic nanomaterials are higher than that of magnetic nanomaterials. The uniqueness and originality of this study stems from the fact that, to the best of the authors' knowledge, it is the first to use this combination technique.

Exploring the Botanical Origins of Bee-Collected Pollen: A Comprehensive Historical and Contemporary Analysis.

Bee-collected pollen is one of the most important bee products. In order to predict its chemical composition and nutritional value botanical origin of pollen plays a crucial role. This review intended to collect all available data published about botanical origin of pollen collected all around the world. Due to enourmous amount of data and variables nonlinear principal component analysis (NLPCA), by applying Categorical Principal Component Analysis (CATPCA), was conducted in order to try to determine any specifity and/or differences among samples. Also, importance of some plant families/genera/species for bees was monitored. Based on CATPCA results families can serve in order to distinct samples from North/South America. Also, some samples from Europe (Turkey and Serbia) were characterized with presence of some specific families. Genera were excellent tool to distinguish samples from different parts of Brazil as well as Australia, Asia and Africa. Due to high and specific biodiversity pollen samples obtained from Sonoran desert (USA) completely were separated during analysis. This review presents the first attempt to summarize and classify a large number of data about botanical sources of bee-collected pollen.

The Cholinergic Selectivity of FDA-Approved and Metabolite Compounds Examined with Molecular-Docking-Based Virtual Screening.

The search for selective anticholinergic agents stems from varying cholinesterase levels as Alzheimer's Disease progresses from the mid to late stage. In this computational study, we probed the selectivity of FDA-approved and metabolite compounds against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) with molecular-docking-based virtual screening. The results were evaluated using locally developed codes for the statistical methods. The docking-predicted selectivity for AChE and BChE was predominantly the consequence of differences in the volume of the active site and the narrower entrance to the bottom of the active site gorge of AChE.

Evaluation of irrigation, drinking, and risk indices for water quality parameters of alpine lakes.

Alpine lakes are aquatic ecosystems that maintain and regulate water supply for the downstream streams, rivers, and other reservoirs. This study examined the water characteristics of various alpine lakes in Gilgit-Baltistan, Northern Pakistan. For this purpose, water was sampled and investigated for basic parameters, anions, and cations using the multi-parameter analyzers and atomic absorption spectrophotometer. Physicochemical parameters of alpine lakes were noted under the World Health Organization water guidelines, except for fluoride (F-) and turbidity in 4.3% and 36% of samples, respectively. Water quality index (WQI) classified samples (93%) as excellent and good quality (7%). Results showed maximum chronic daily intake values (0.14 ± 0.01 mg/kg-day) for nitrate (NO3-) and hazard quotient (0.80 ± 0.24) for F- in children via water intake from Upper Kachura and Shausar Lakes, respectively. Statistical analyses of Piper and Gibbs's plots revealed that the water quality is mainly characterized by bedrock geology.

Determination of threshold values and heavy metal pollution assessment of soils in an industrial area in Ghana.

Industrial activities have the potential to pollute soils with a wide variety of heavy metals (HMs). In Ghana, however, assessment of HM pollution of soils in industrial areas remains limited. Accordingly, HM soil pollution in one of the industrial areas in Accra, Ghana was assessed. Soil samples were taken and analysed for HMs, including Fe, Zr, Zn, Ti, Sr, Rb, Mn, Pb, Cu, and Co, using X-Ray Fluorescence (XRF). HM geochemical threshold values (GTVs) were determined to establish soil HM pollution levels and identify areas needing remediation. Furthermore, risk assessments were conducted to evaluate the potential ecological and human health risks associated with these metals. The mean concentrations of Fe, Zn, Rb, Sr, Zr, Ti, Mn, Co, Cu, and Pb in the soils were: 27133.83, 147.72, 16.30, 95.95, 307.11, 4663.66, 289.85, 418.54, 44.97, and 112.88 mg/kg, respectively. Generally, the concentrations of HMs decreased with depth, although some lower layers exhibited elevated HM levels. Soil pollution levels were categorized as low for Fe, Rb, Zr, Ti, Mn, Co, and Cu; moderate for Sr and Zn; and considerable for Pb. Notably, the northwestern part of the study area displayed a considerable to very high degree of HM contamination. While HMs in the soils posed low ecological risk, the human health risk assessment indicated potential health effects from Co, particularly in children. The presence of HMs in the soils was noted to originate from both natural geological phenomena and human activities, including industrial operations, agricultural practices, landfill activities, and vehicular emissions.

Spatiotemporal variations, health risk assessment, and sources of potentially toxic elements in potamic water of the Anday Stream Basin (Türkiye), Black Sea Region.

Monitoring and protecting freshwater habitats are paramount for a sustainable water management perspective. This study investigated potentially toxic elements (PTEs) in the potamic water of the Anday Stream Basin (Türkiye), Black Sea Region, for a hydrological year (from May 2020 to April 2021). Among PTEs, the highest average values were recorded for sodium (Na) at 41.3 mg/L and the lowest for mercury (Hg) at 0.009 µg/L and noted under quality guidelines. The stream was found to be at the level of "Low Heavy Metal Pollution" and "Low Contamination" based on the ecotoxicological risk indices. The highest calculated hazard quotient (HQ) value of 1.21E-02 for Cd was noted in the children via the dermal pathway and the lowest of 6.91E-06 for Fe in adults via the ingestion pathway. Results revealed a higher hazard index (HI) value of 1.50E-02 for Cd to children and the lowest of 1.98E-05 for Fe to adults. As a result of applying agricultural risk indices, the stream showed sodium adsorption ratio values less than 6 and was found to be "Excellent" for agriculture. However, the sodium percentage values were less than 20 and found "Permissible" and the magnesium hazard > 50 and noted as "Unsuitable" for agriculture. Statistical analysis revealed that natural factors mainly attributed to PTE contamination of the Anday Stream Basin.

Prescribing Blood Flow Restricted Exercise: Limb Composition Influences the Pressure Required to Create Arterial Occlusion.

CONTEXT: As blood flow restriction gains popularity across different populations (eg, young and older adults) and settings (eg, clinical and sports rehabilitation), the accuracy of blood flow restricted percentage becomes crucial. We aimed to compare manually measured arterial occlusion pressure (AOP) among young adults to understand whether lower limb composition affects the pressure required to achieve AOP. The results will shed light on the adequacy of published calculations used to estimate AOP in practical and research settings. DESIGN: An observational cross-sectional study design was implemented to examine the relationship between lower limb composition, lower limb circumference, and measured AOP. METHODS: Twenty-two participants (12 males, 26 [4] y, 1.74 [0.07] m, 73.2 [12.5] kg) underwent a whole-body Dual-energy X-ray Absorptiometry scan before AOP (in millimeters of mercury) and lower limb circumference (in centimeters) were determined. In a supine position, a 10-cm wide cuff was manually inflated on the dominant leg to the point where a pulse could no longer be detected by a Doppler ultrasound of the posterior tibial artery to determine AOP. Lower limb composition (fat, muscle, and bone mass [in grams]) was obtained from the Dual-energy X-ray Absorptiometry scan. RESULTS: Lower limb muscle mass had a moderate negative relationship with AOP (r2 = .433, ß = -0.004) and a moderate positive relationship with lower limb circumference (r2 = .497, ß = 0.001). Lower limb circumference had the weakest relationship with AOP (r2 = .316, ß = 0.050) of all measures. CONCLUSIONS: The reported relationships between lower limb muscle mass, lower limb circumference, and AOP suggest that as muscle mass increases, lower limb circumference also increases, yet AOP decreases. This implies that limb circumference should not be used as the primary measure for calculating AOP within the sampled population. We recommend individually measuring AOP when implementing blood flow restriction in all exercise modalities.

Asterics: a simple tool for the ExploRation and Integration of omiCS data.

BACKGROUND: The rapid development of omics acquisition techniques has induced the production of a large volume of heterogeneous and multi-level omics datasets, which require specific and sometimes complex analyses to obtain relevant biological information. Here, we present ASTERICS (version 2.5), a publicly available web interface for the analyses of omics datasets. RESULTS: ASTERICS is designed to make both standard and complex exploratory and integration analysis workflows easily available to biologists and to provide high quality interactive plots. Special care has been taken to provide a comprehensive documentation of the implemented analyses and to guide users toward sound analysis choices regarding some specific omics data. Data and analyses are organized in a comprehensive graphical workflow within ASTERICS workspace to facilitate the understanding of successive data editions and analyses leading to a given result. CONCLUSION: ASTERICS provides an easy to use platform for omics data exploration and integration. The modular organization of its open source code makes it easy to incorporate new workflows and analyses by external contributors. ASTERICS is available at https://asterics.miat.inrae.fr and can also be deployed using provided docker images.

Anti-Inflammatory Activity of Lauraceae Plant Species and Prediction Models Based on Their Metabolomics Profiling Data.

The Lauraceae is a botanical family known for its anti-inflammatory potential. However, several species have not yet been studied. Thus, this work aimed to screen the anti-inflammatory activity of this plant family and to build statistical prediction models. The methodology was based on the statistical analysis of high-resolution liquid chromatography coupled with mass spectrometry data and the ex vivo anti-inflammatory activity of plant extracts. The ex vivo results demonstrated significant anti-inflammatory activity for several of these plants for the first time. The sample data were applied to build anti-inflammatory activity prediction models, including the partial least square acquired, artificial neural network, and stochastic gradient descent, which showed adequate fitting and predictive performance. Key anti-inflammatory markers, such as aporphine and benzylisoquinoline alkaloids were annotated with confidence level 2. Additionally, the validated prediction models proved to be useful for predicting active extracts using metabolomics data and studying their most bioactive metabolites.

The relationship between mountain wetland health and water quality: A case study of the upper Hanjiang River Basin, China.

This study investigates the degradation process of mountain wetlands in the upper Hanjiang River Basin (HRB) over a 30-year span from 1990 to 2020. In particular, the landscape development intensity (LDI) index was employed to conduct a comprehensive assessment of the wetland health. This was subsequently combined with the spatio-temporal changes of water quality in the basin to explore the potential correlations between the health status of mountain wetlands and the associated watershed water quality. The results show that over the past three decades, wetland ecosystems have shrunk by 18% due to conversion into farmland, grass, construction land and forest land. This was significant between 2010 and 2020, as shown by a land use dynamic index of -1.121% during 2010-2020, which was significantly higher than that in the preceding two decades (0.003%, 0.367%) (p < 0.05). LDI values for individual sub-watersheds across different years ranged from 2.39 to 4.93, demonstrating an increasing trend since 2010. This indicates a heightened level of human interference in mountain wetlands. Although the water quality within the basin generally adhered to the Class II surface water quality standard, total nitrogen (TN) (primarily from farming) was a concern. Areas with relatively more human activity were observed to exhibit increased pollution levels, as demonstrated by a positive correlation between LDI and the concentrations of total phosphorus (TP), ammonium nitrogen (NH4+-N), and chemical oxygen demand (COD) in the basin. The LDI of the mountain wetland exhibited a consistent positive correlation with the water quality comprehensive function, both during the flood (r = 0.77-0.81) and non-flood (r = 0.61-0.70) seasons (p < 0.05). This indicates the significant impact of the wetland landscape structure on the water quality within a 1000 m radius on either side of the river. Special attention should be paid to the management and allocation of wetland landscapes within this 1000 m buffer zone. Furthermore, efforts to control upstream pollutant emission should be strengthened.

A step forward on site-specific environmental risk assessment and insight into the main influencing factors of CECs removal from wastewater.

The presence of Contaminants of Emerging Concern (CECs) in water systems has been recognized as a potential source of risk for human health and the ecosystem. The present paper aims at evaluating the effects of different characteristics of full-scale Wastewater Treatment Plants (WWTPs) on the removal of 14 selected CECs belonging to the classes of caffeine, illicit drugs and pharmaceuticals. Particularly, the investigated plants differed because of the treatment lay-out, the type of biological process, the value of the operating parameters, the fate of the treated effluent (i.e. release into surface water or reuse), and the treatment capacity. The activity consisted of measuring concentrations of the selected CECs and also traditional water quality parameters (i.e. COD, phosphorous, nitrogen species and TSS) in the influent and effluent of 8 plants. The study highlights that biodegradable CECs (cocaine, methamphetamine, amphetamine, benzoylecgonine, 11-nor-9carboxy-Δ9-THC, lincomycin, trimethoprim, sulfamethoxazole, sulfadiazine, sulfadimethoxine, carbamazepine, ketoprofen, warfarin and caffeine) were well removed by all the WWTPs, with the best performance achieved by the MBR for antibiotics. Carbamazepine was removed at the lowest extent by all the WWTPs. The environmental risk assessed by using the site-specific value of the dilution factor resulted to be high in 3 out of 8 WWTPs for carbamazepine and less frequently for caffeine. However, the risk was reduced when the dilution factor was assumed equal to the default value of 10 as proposed by EU guidelines. Therefore, a specific determination of this factor is needed taking into account the hydraulic characteristics of the receiving water body.

Analysis and Discrimination of Canadian Honey Using Quantitative NMR and Multivariate Statistical Methods.

To address the growing concern of honey adulteration in Canada and globally, a quantitative NMR method was developed to analyze 424 honey samples collected across Canada as part of two surveys in 2018 and 2019 led by the Canadian Food Inspection Agency. Based on a robust and reproducible methodology, NMR data were recorded in triplicate on a 700 MHz NMR spectrometer equipped with a cryoprobe, and the data analysis led to the identification and quantification of 33 compounds characteristic of the chemical composition of honey. The high proportion of Canadian honey in the library provided a unique opportunity to apply multivariate statistical methods including PCA, PLS-DA, and SIMCA in order to differentiate Canadian samples from the rest of the world. Through satisfactory model validation, both PLS-DA as a discriminant modeling technique and SIMCA as a class modeling method proved to be reliable at differentiating Canadian honey from a diverse set of honeys with various countries of origins and floral types. The replacement method of optimization was successfully applied for variable selection, and trigonelline, proline, and ethanol at a lower extent were identified as potential chemical markers for the discrimination of Canadian and non-Canadian honeys.

Best practices in metabarcoding of fungi: From experimental design to results.

The development of high-throughput sequencing (HTS) technologies has greatly improved our capacity to identify fungi and unveil their ecological roles across a variety of ecosystems. Here we provide an overview of current best practices in metabarcoding analysis of fungal communities, from experimental design through molecular and computational analyses. By reanalysing published data sets, we demonstrate that operational taxonomic units (OTUs) outperform amplified sequence variants (ASVs) in recovering fungal diversity, a finding that is particularly evident for long markers. Additionally, analysis of the full-length ITS region allows more accurate taxonomic placement of fungi and other eukaryotes compared to the ITS2 subregion. Finally, we show that specific methods for compositional data analyses provide more reliable estimates of shifts in community structure. We conclude that metabarcoding analyses of fungi are especially promising for integrating fungi into the full microbiome and broader ecosystem functioning context, recovery of novel fungal lineages and ancient organisms as well as barcoding of old specimens including type material.

Metabolomics with multi-block modelling of mass spectrometry and nuclear magnetic resonance in order to discriminate Haplosclerida marine sponges.

A comprehensive metabolomic strategy, integrating 1H NMR and MS-based multi-block modelling in conjunction with multi-informational molecular networking, has been developed to discriminate sponges of the order Haplosclerida, well known for being taxonomically contentious. An in-house collection of 33 marine sponge samples belonging to three families (Callyspongiidae, Chalinidae, Petrosiidae) and four different genera (Callyspongia, Haliclona, Petrosia, Xestospongia) was investigated using LC-MS/MS, molecular networking, and the annotations processes combined with NMR data and multivariate statistical modelling. The combination of MS and NMR data into supervised multivariate models led to the discrimination of, out of the four genera, three groups based on the presence of metabolites, not necessarily previously described in the Haplosclerida order. Although these metabolomic methods have already been applied separately, it is the first time that a multi-block untargeted approach using MS and NMR has been combined with molecular networking and statistically analyzed, pointing out the pros and cons of this strategy.

Anti-Inflammatory Markers of Hops Cultivars (Humulus lupulus L.) Evaluated by Untargeted Metabolomics Strategy.

Hops (Humulus lupulus L.) are edible flowers commonly used to add flavour and aroma to beer, besides they have rich chemical diversity and medicinal potential. In this work, an ex vivo anti-inflammatory assay via the LPS-induced signalling pathway and metabolomics approaches were performed to evaluate the ability of hops to inhibit the production of prostaglandin E2 (PGE2) inflammatory mediator and analyze which metabolites produced by the nine different hop cultivars are potential anti-inflammatory markers. Columbus, Chinook and Hallertau Mittelfrüh hop cultivars yielded extracts with PGE2 release inhibition rates of 86.7, 92.5 and 73.5 %, respectively. According to the multivariate statistical analysis, the majority of the metabolites correlated with the activity were prenylated phloroglucinol and phenolic homologs. These results suggest promissory anti-inflammatory hop metabolites.

Methods and Statistical Analyses in Studies of Motivation for E-Cigarette Use Among University Students: An Integrative Review.

Understanding the motivations for e-cigarette use among college and university students is essential for developing and implementing effective interventions. Evaluating existing literature is necessary to identify methodological gaps and limitations and improve the quality of future research.We aimed to evaluate the quality of the methods and statistical analyses and integrate evidence addressing motivations for e-cigarette use among college and university students.An integrative literature review was conducted by two researchers to identify and evaluate peer-reviewed, quantitative, and mixed methods research exploring motivations for e-cigarette use among college and university students. A systematic analytic method of data reduction was used to identify alignment and divergence of the data, gaps in the literature, and methodological limitations.Fifteen quantitative studies and three mixed methods studies published between 2015-2020 were included. Most studies were cross-sectional, used convenience sampling, and lacked psychometric and assumptions testing. Half performed regression analyses, however, very few adhered to research and statistical reporting standards.Current literature provides a foundation for developing and implementing interventions aimed to prevent e-cigarette use and encourage cessation. Future research should incorporate stronger sampling methods and research designs, as well as the use of rigorous statistical analyses in conjunction with thorough reporting.Supplemental data for this article is available online at https://doi.org/10.1080/10826084.2021.1990332.

Parallel Cooperative Coevolutionary Grey Wolf Optimizer for Path Planning Problem of Unmanned Aerial Vehicles.

The path planning of Unmanned Aerial Vehicles (UAVs) is a complex and hard task that can be formulated as a Large-Scale Global Optimization (LSGO) problem. A higher partition of the flight environment leads to an increase in route's accuracy but at the expense of greater planning complexity. In this paper, a new Parallel Cooperative Coevolutionary Grey Wolf Optimizer (PCCGWO) is proposed to solve such a planning problem. The proposed PCCGWO metaheuristic applies cooperative coevolutionary concepts to ensure an efficient partition of the original search space into multiple sub-spaces with reduced dimensions. The decomposition of the decision variables vector into several sub-components is achieved and multi-swarms are created from the initial population. Each sub-swarm is then assigned to optimize a part of the LSGO problem. To form the complete solution, the representatives from each sub-swarm are combined. To reduce the computation time, an efficient parallel master-slave model is introduced in the proposed parameters-free PCCGWO. The master will be responsible for decomposing the original problem and constructing the context vector which contains the complete solution. Each slave is designed to evolve a sub-component and will send the best individual as its representative to the master after each evolutionary cycle. Demonstrative results show the effectiveness and superiority of the proposed PCCGWO-based planning technique in terms of several metrics of performance and nonparametric statistical analyses. These results show that the increase in the number of slaves leads to a more efficient result as well as a further improved computational time.

Valorization of a Waste Product of Edible Flowers: Volatile Characterization of Leaves.

(1) Background: The leaves of some plants are reported for their culinary uses, while in edible flowers, they are one of the discarded products in the supply chain. We investigated the volatile profile (VP) and the essential oil (EO) compositions of leaves from 12 Lamiaceae species, of which nine belong to the Mentheae tribe and three to the Ocimeae tribe. (2) Methods: Phytochemical analyses were performed using a GC-MS instrument. (3) Results: More than 53% of the Ocimeae tribe VP was represented by sesquiterpene hydrocarbons (SH), followed by phenylpropanoids, except for O. × citriodorum, where oxygenated monoterpenes (OM) were the second main class. OM prevailed in six species of the Mentheae tribe except for Agastache 'Arcado Pink', Salvia discolor, and S. microphylla, where SH dominated. The EO composition of Ocimeae tribe showed a similar behavior to that of VP concerning the predominant classes. O. basilicum 'Blue Spice' (Ob-BS) was an exception, since it showed oxygenated sesquiterpenes (OS: 29.6%) as a second principal class. Sesquiterpene compounds were also present in a high amount in two species of the Salviinae subtribe (S. microphylla and S. discolor) and two of the Nepetinae subtribe (Nepeta × faasenii and A. 'Arcado Pink'). The remaining species of the Mentheae tribe were characterized by OM. (4) Conclusions: Many of the main compounds found were reported for their importance in human health and thus are important as ingredients in several new industrial products.

Rapid Classification and Recognition Method of the Species and Chemotypes of Essential Oils by ATR-FTIR Spectroscopy Coupled with Chemometrics.

In the present work, the applicability of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, coupled with chemometric tools in recognizing essential oils (EOs) for routine control, was evaluated. EOs belonging to Mentha, Cymbopogon, and Lavandula families and to S. rosmarinus and T. vulgaris species were analyzed, and the performance of several untargeted approaches, based on the synergistic combination of ATR-FTIR and Partial Least Squares Discriminant Analysis (PLS-DA), was tested to classify the species and chemotypes. Different spectra pre-processing methods were employed, and the robustness of the built models was tested by means of a Receiver Operating Characteristic (ROC) curve and random permutations test. The application of these approaches revealed fruitful results in terms of sensitivity and specificity, highlighting the potentiality of ATR-FTIR and chemometrics techniques to be used as a sensitive, cost-effective, and rapid tool to differentiate EO samples according to their species and chemotype.

Differential disease phenotypes and progression in relapsing-remitting multiple sclerosis: comparative analyses of single Canadian and Saudi Arabian clinics.

OBJECTIVE: Relapsing-remitting multiple sclerosis (RR-MS) phenotypes differ widely although the variables contributing to this heterogeneity remain uncertain. To assess geographic and ethnic effects on RR-MS phenotypes, we investigated RR-MS patients in Canada and Saudi Arabia. METHODS: A retrospective analysis of patients followed in two MS Clinics was performed in Medina, Saudi Arabia and Edmonton, Canada. Demographic and clinical data were collected for each patient and analyzed using univariable and multivariable statistics. Univariable and multivariable linear regression were used to distinguish the significant clinical and demographic features and neurological systems associated with the change in expanded disability status scale (EDSS) between clinical assessments. RESULTS: Patients with treated RR-MS were recruited (n = 51, Saudi; n = 47, Canada) although the disease duration was longer in the Canadian cohort (5.6 ± 2.2 yr.) compared to the Saudi cohort (4.4 ± 1.4 yr.) (P < 0.05), annual relapse rate and EDSS change were higher in the Saudi cohort (P < 0.05). Infratentorial lesion-associated presentation differed (Canada, n = 23; Saudi, n = 13) among groups (P < 0.05). Spinal cord lesions on MRI were more frequently detected in Canadian (n = 23) compared to Saudi (n = 1) patients (P < 0.05). Patients within the Saudi cohort displayed a significantly greater change in Expanded Disability Status Scale (EDSS) between first and second assessments. CONCLUSIONS: Despite differences in geographic location, ethnicity, and predominance of infratentorial lesions in the Canadian group, the RR-MS phenotypes were similar although the Saudi cohort displayed a more severe disease course.