Comparative Evaluation of Sentiment Analysis Methods Across Arabic Dialects

Sentiment analysis in Arabic is challenging due to the complex morphology of the language. The task becomes more challenging when considering Twitter data that contain significant amounts of noise such as the use of Arabizi, code-switching and different dialects that varies significantly across the Arab world, the use of non-Textual objects to express sentiments, and the frequent occurrence of misspellings and grammatical mistakes. Modeling sentiment in Twitter should become easier when we understand the characteristics of Twitter data and how its usage varies from one Arab region to another. We describe our effort to create the first Multi-Dialect Arabic Sentiment Twitter Dataset (MD-ArSenTD) that is composed of tweets collected from 12 Arab countries, annotated for sentiment and dialect. We use this dataset to analyze tweets collected from Egypt and the United Arab Emirates (UAE), with the aim of discovering distinctive features that may facilitate sentiment analysis. We also perform a comparative evaluation of different sentiment models on Egyptian and UAE tweets. These models are based on feature engineering and deep learning, and have already achieved state-of-The-Art accuracies in English sentiment analysis. Results indicate the superior performance of deep learning models, the importance of morphological features in Arabic NLP, and that handling dialectal Arabic leads to different outcomes depending on the country from which the tweets are collected.This work was made possible by NPRP 6-716-1-138 grant from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Genetic Evidence Implicates the Immune System and Cholesterol Metabolism in the Aetiology of Alzheimer's Disease

Background 1Late Onset Alzheimer's disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. Principal Findings We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. Significance Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimer's disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches

Correction: genetic evidence implicates the immune system and cholesterol metabolism in the aetiology of Alzheimer's disease.

[This corrects the article on p. e13950 in vol. 5.]. Background: Late Onset Alzheimer's disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology: We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. Principal Findings: We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. Significance: Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimer's disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches

Two syndromes, a same gene : Consequences of an abnormal dosage of MeCP2 on synaptic transmission and behavior in mice

MeCP2 est une protéine multifonctionnelle agissant à de nombreux niveaux de contrôle des programmes génétiques. Un mauvais dosage de MeCP2 cause un groupe de maladies neurologiques dont le point commun est une déficience intellectuelle sévère. Des mutations ou une délétion de MECP2 causent le syndrome de Rett chez les filles, alors que sa surexpression cause chez les garçons le syndrome de duplication de MECP2. Plusieurs modèles murins de Mecp2-pathies ont été générés qui permettent d’expliciter les mécanismes qui sous-tendent l’apparition des symptômes dans ces différentes maladies. Dans notre laboratoire, deux modèles murins sont utilisés: le modèle Mecp2tm1Bird qui présente une déficience en Mecp2 et le modèle Mecp2Tg1 présentant une surexpression de Mecp2. Ce travail de thèse a permis de caractériser l’évolution postnatale des déficits moteurs et physiologique affectant la souris Mecp2Tg1. Nos résultats montrent que la surexpression de Mecp2 conduit à l’apparition de problèmes moteurs, et des convulsions chez la souris. En parallèle, nous avons étudié les déficits neuronaux affectants la voie GABAergique et glutamatergique chez la souris déficiente en Mecp2. Nous avons montré que la déficience en Mecp2 cause une dérégulation de la transmission synaptique dépendante du ‘territoire’ et de l’âge de la maladie. Ces dérégulations sous-tendent vraisemblablement des différences neurophysiologiques importantes entre les régions du cerveau qu’il nous reste encore à découvrir. Par ailleurs, nous avons constaté que la stimulation pharmacologique du système GABAergique par la Tiagabine, permet d’augmenter la survie des animaux Mecp2-déficients.MeCP2 is a multifunctional protein acting on many levels of control of genetic programs. Thus, an abnormal dosage of MeCP2 protein causes a group of neurological disorders with a common feature of severe intellectual disability. Mutations or deletions in MECP2 gene cause Rett Syndrome in females, whereas in boys its overexpression causes the MECP2-duplication Syndrome. Several mouse models of MECP2-pathologies were generated. The use of these models is crucial for understanding the mechanisms underlying the onset of symptoms related to the pathology. In our laboratory, two mouse models are under study: The Mecp2tm1Bird model with an Mecp2 deficiency and the transgenic Mecp2Tg1 model with a double expression of Mecp2. My thesis work enabled the characterization of the postnatal physiological and motor deficits affecting Mecp2Tg1 mice. My work led to a better understanding of the gene dosage effect. Our results showed that overexpression of Mecp2 in mice, led to the occurrence of motor problems, and seizures. In parallel, we studied the neural deficits affecting the GABA and the glutamate pathway in several structures of the Mecp2 deficient brain (Mecp2tm1bird). We showed that Mecp2-deficiency causes deregulation of the synaptic transmission, which is dependent on the area, and the age of the study. These deregulations underlie significant neurophysiological differences between the different regions of the brain that we still have to uncover. Furthermore, we found that pharmacological stimulation of the GABA system with Tiagabine, a molecule capable of acting on GABA transporters to prevent its uptake, increases the survival of Mecp2-deficients animals

GABA and Glutamate Pathways Are Spatially and Developmentally Affected in the Brain of Mecp2-Deficient Mice

International audienceProper brain functioning requires a fine-tuning between excitatory and inhibitory neurotransmission, a balance maintained through the regulation and release of glutamate and GABA. Rett syndrome (RTT) is a rare genetic disorder caused by mutations in the methyl-CpG binding protein 2 (MECP2) gene affecting the postnatal brain development. Dysfunctions in the GABAergic and glutamatergic systems have been implicated in the neuropathology of RTT and a disruption of the balance between excitation and inhibition, together with a perturbation of the electrophysiological properties of GABA and glutamate neurons, were reported in the brain of the Mecp2-deficient mouse. However, to date, the extent and the nature of the GABA/glutamate deficit affecting the Mecp2-deficient mouse brain are unclear. In order to better characterize these deficits, we simultaneously analyzed the GABA and glutamate levels in Mecp2-deficient mice at 2 different ages (P35 and P55) and in several brain areas. We used a multilevel approach including the quantification of GABA and glutamate levels, as well as the quantification of the mRNA and protein expression levels of key genes involved in the GABAergic and glutamatergic pathways. Our results show that Mecp2-deficient mice displayed regional-and age-dependent variations in the GABA pathway and, to a lesser extent, in the glutamate pathway. The implication of the GABA pathway in the RTT neuropathology was further confirmed using an in vivo treatment with a GABA reuptake inhibitor that significantly improved the lifespan of Mecp2-deficient mice. Our results confirm that RTT mouse present a deficit in the GABAergic pathway and suggest that GABAergic modulators could be interesting therapeutic agents for this severe neurological disorder

The contribution of authors from low- and middle-income countries to top-tier mental health journals

Background: Low- and middle-income countries (LMICs) have been consistently under-represented in the pool of contributors to academic journals on health. For the past two decades, prominent voices within the psychiatric profession have called for better representation of LMICs in the interest of advancing the understanding of mental health globally and benefiting health systems in these countries.Objective: To investigate the absolute and relative representation of authors affiliated to institutes from LMICs in the most influential journals on mental health in 2019.Method: Thirty top-ranking journals on mental health based on Scimago Journal Rank were selected, and all papers other than correspondence and letters to the editor published in those journals in 2019 were examined to extract the country of affiliation of each of their authors and their position (corresponding author, first author, second author).Results: Of the 4022 articles examined, 3720 articles (92.5%) were written exclusively by authors from high-income countries (HICs); 302 (7.5%) featured one or more authors from a LMIC along with those from HICs; 91 (2.2%) featured authors only from one LMIC; and only 3 (0.07%) featured authors from more than one LMICs but without any co-author from a HIC. The ratio of articles by contributors from LMICs to all the articles published in 2019 in a given journal ranged from 0% to 19%. Of 1855 individual contributors from 45 LMICs, 1050 (56%) were from China.Conclusion: Despite the growth of the global health movement and frequent calls for academic inclusivity, LMICs were significantly under-represented among the authors of papers published in top-ranking journals on mental health in 2019

A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models

Opinion mining in Arabic is a challenging task given the rich morphology of the language. The task becomes more challenging when it is applied to Twitter data, which contains additional sources of noise, such as the use of unstandardized dialectal variations, the non-conformation to grammatical rules, the use of Arabizi and code-switching, and the use of non-text objects such as images and URLs to express opinion. In this paper, we perform an analytical study to observe how such linguistic phenomena vary across different Arab regions. This study of Arabic Twitter characterization aims at providing better understanding of Arabic Tweets, and fostering advanced research on the topic. Furthermore, we explore the performance of the two schools of machine learning on Arabic Twitter, namely the feature engineering approach and the deep learning approach. We consider models that have achieved state-of-the-art performance for opinion mining in English. Results highlight the advantages of using deep learning-based models, and confirm the importance of using morphological abstractions to address Arabic's complex morphology. 2017 Association for Computational LinguisticsThis work was made possible by NPRP 6-716-1-138 grant from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Malva pseudolavatera Leaf Extract Promotes ROS Induction Leading to Apoptosis in Acute Myeloid Leukemia Cells In Vitro

Malva pseudolavatera Webb & Berthel. is a plant from the Malvaceae family that has long been included in the human diet due to its various curative effects. Many plant leaf extracts from the various species of Malva genus have been reported to possess anti-cancer properties, however, studies on M. pseudolavatera Webb & Berthel. leaves have documented anti-inflammatory and anti-oxidant effects with no emphasis on their possible anti-cancer potential. The present study explores the anti-cancer properties of Malva pseudolavatera Webb & Berthel. leaf extract on acute myeloid leukemia (AML) cell lines in vitro and deciphers the underlying molecular mechanism. Treatment of AML cell lines with M. pseudolavatera methanolic leaf extract showed a dose- and time-dependent inhibition of proliferation and a dose-dependent increase in apoptotic hallmarks such as an increase in phosphatidylserine on the outer membrane leaflet and membrane leakage in addition to DNA fragmentation. The pro-apoptotic effect was induced by reactive oxygen species (ROS) as well as an upregulation of cleaved poly(ADP-ribose) polymerase (PARP), increase in Bax/Bcl-2 ratio, andrelease of cytochrome-c from the mitochondria. Major compounds of the extract included methyl linolenate, phytol, gamma-sitosterol, and stigmasterol as revealed by gas chromatography coupled with mass spectrometry, and amino acids, amino acid derivatives, tiliroside, 13-hydroxyperoxyoctadecadienoic, and quercitrin as detected by liquid chromatography coupled to mass spectrometry

Aflatoxin B1 in Rice: Effects of Storage Duration, Grain Type and Size, Production Site, and Season

ABSTRACT: Our study evaluated aflatoxin B1 (AFB1) levels in packed rice marketed in Lebanon and determined the exposure to this toxin from rice consumption. A total of 105 packed white, parboiled, and brown rice bags were collected. Enzyme-linked immunosorbent assay was used to measure AFB1. A comprehensive food frequency questionnaire was completed by 500 participants to determine patterns of rice consumption and, subsequently, the exposure levels to AFB1 from rice consumption in Lebanon. AFB1 was detected in all rice samples (100%). The average concentration ± standard deviation of AFB1 was 0.5 ± 0.3 μg/kg. Contamination ranged between 0.06 and 2.08 μg/kg. Moisture content in all rice samples was below the recommended percentage (14%). Only 1% of the samples had an AFB1 level above the European Union limit (2 μg/kg). Brown rice had a significantly higher AFB1 level than white and parboiled rice (P = 0.02), while a significant difference was found between both collections for the same brands (P = 0.016). Packing season, packing country, country of origin, presence of a food safety management certification, grain size, and time between packing and purchasing had no significant effect. Exposure to AFB1 from rice consumption in Lebanon was calculated as 0.1 to 2 ng/kg of body weight per day

The pro-apoptotic properties of a phytonutrient rich infusion of A. cherimola leaf extract on AML cells

Annonaceae family has broad uses in herbal medicine for treatment of several diseases, whether through seeds’ or leaves’ extracts. The present study investigates the antiproliferative and antitumor activity of Annona cherimola aqueous leaf (AAL) extract/infusion in acute myeloid leukemia (AML) cell lines in vitro. High-resolution LC-MS was first used to analyze the composition of the aqueous extract. Cell proliferation assay, Annexin V staining, cell cycle analysis, dual Annexin V/PI staining, cell death quantification by ELISA, ROS level detection and Western Blotting were then performed to elucidate the therapeutic effects of AAL extract. The results obtained revealed a potent antioxidant activity of AAL extract. Moreover, the extract exhibited dose- and time-dependent antiproliferative effects on AML cell lines by decreasing cell viability with an IC50 of 5.03% (v/v) at 24 h of treatment of KG-1 cells. This decrease in viability was accompanied with a significant increase in apoptotic cell death with cell cycle arrest and flipping of the phosphatidylserine from the inner to the outer leaflet of the cell membrane. The respective overexpression and downregulation of proapoptotic proteins like cleaved caspase-8, cleaved PARP-1 and Bax and antiapoptotic proteins like Bcl-2 further validated the apoptotic pathway induced by AAL on AML cells. Finally, LC-MS revealed the presence of several compounds like fatty acids, terpenes, phenolics, cinnamic acids and flavonoids that could contribute to the antioxidant and anti-cancer effects of this herbal infusion. In addition to the generally known nutritional effects of the Annona cherimola fruit and leaves, the presented data validates the antioxidant and anti-cancerous effects of the leaf infusion on AML cell lines, proposing its potential therapeutic use against acute myeloid leukemia with future in vivo and clinical trials