A Framework for Arabic Concept-Level Sentiment Analysis using SenticNet

Arabic Sentiment analysis research field has been progressing in a slow pace compared to English and other languages. In addition to that most of the contributions are based on using supervised machine learning algorithms while comparing the performance of different classifiers with different selected stylistic and syntactic features. In this paper, we presented a novel framework for using the Concept-level sentiment analysis approach which classifies text based on their semantics rather than syntactic features. Moreover, we provided a lexicon dataset of around 69 k unique concepts that covers multi-domain reviews collected from the internet. We also tested the lexicon on a test sample from the dataset it was collected from and obtained an accuracy of 70%. The lexicon has been made publicly available for scientific purposes

Neuroprotective effect of ranolazine improves behavioral discrepancies in a rat model of scopolamine-induced dementia

BackgroundRanolazine (Rn), an antianginal agent, acts in the central nervous system and has been used as a potential treatment agent for pain and epileptic disorders. Alzheimer’s disease (AD) is one of the most prevalent neurodegenerative diseases and the leading factor in dementia in the elderly.AimWe examined the impact of Rn on scopolamine (Sco)-induced dementia in rats.MethodsThirty-two albino male rats were divided into four groups: control, Rn, Sco, and Rn + Sco.ResultsA significant decrease in the escape latency in the Morris water maze test after pre-treatment with Rn explained better learning and memory in rats. Additionally, Rn significantly upregulated the activities of the antioxidant enzymes in the treated group compared to the Sco group but substantially reduced acetylcholinesterase activity levels in the hippocampus. Moreover, Rn dramatically reduced interleukin-1 β (IL-1β) and IL-6 and upregulated the gene expression of brain-derived neurotrophic factor (BDNF). Furthermore, in the Sco group, the hippocampal tissue’s immunohistochemical reaction of Tau and glial factor activating protein (GFAP) was significantly increased in addition to the upregulation of the Caspase-3 gene expression, which was markedly improved by pre-treatment with Rn. The majority of pyramidal neurons had large vesicular nuclei with prominent nucleoli and appeared to be more or less normal, reflecting the all-beneficial effects of Rn when the hippocampal tissue was examined under a microscope.ConclusionOur findings indicated that Rn, through its antioxidative, anti-inflammatory, and anti-apoptotic effects, as well as the control of the expression of GFAP, BDNF, and Tau proteins, has a novel neuroprotective impact against scopolamine-induced dementia in rats

Distribution pattern of antibiotic resistance genes in Escherichia coli isolated from colibacillosis cases in broiler farms of Egypt

Background and Aim: Multidrug resistance (MDR) of Escherichia coli has become an increasing concern in poultry farming worldwide. However, E. coli can accumulate resistance genes through gene transfer. The most problematic resistance mechanism in E. coli is the acquisition of genes encoding broad-spectrum β-lactamases, known as extended-spectrum β-lactamases, that confer resistance to broad-spectrum cephalosporins. Plasmid-mediated quinolone resistance genes (conferring resistance to quinolones) and mcr-1 genes (conferring resistance to colistin) also contribute to antimicrobial resistance. This study aimed to investigate the prevalence of antimicrobial susceptibility and to detect β-lactamase and colistin resistance genes of E. coli isolated from broiler farms in Egypt. Materials and Methods: Samples from 938 broiler farms were bacteriologically examined for E. coli isolation. The antimicrobial resistance profile was evaluated using disk diffusion, and several resistance genes were investigated through polymerase chain reaction amplification. Results: Escherichia coli was isolated and identified from 675/938 farms (72%) from the pooled internal organs (liver, heart, lung, spleen, and yolk) of broilers. Escherichia coli isolates from the most recent 3 years (2018–2020) were serotyped into 13 serotypes; the most prevalent serotype was O125 (n = 8). The highest phenotypic antibiotic resistance profiles during this period were against ampicillin, penicillin, tetracycline, and nalidixic acid. Escherichia coli was sensitive to clinically relevant antibiotics. Twenty-eight selected isolates from the most recent 3 years (2018–2020) were found to have MDR, where the prevalence of the antibiotic resistance genes ctx, tem, and shv was 46% and that of mcr-1 was 64%. Integrons were found in 93% of the isolates. Conclusion: The study showed a high prevalence of E. coli infection in broiler farms associated with MDR, which has a high public health significance because of its zoonotic relevance. These results strengthen the application of continuous surveillance programs

Genomic characterization of SARS-CoV-2 in Egypt: insights into spike protein thermodynamic stability

The overall pattern of the SARS-CoV-2 pandemic so far has been a series of waves; surges in new cases followed by declines. The appearance of novel mutations and variants underlie the rises in infections, making surveillance of SARS-CoV-2 mutations and prediction of variant evolution of utmost importance. In this study, we sequenced 320 SARS-CoV-2 viral genomes isolated from patients from the outpatient COVID-19 clinic in the Children’s Cancer Hospital Egypt 57357 (CCHE 57357) and the Egypt Center for Research and Regenerative Medicine (ECRRM). The samples were collected between March and December 2021, covering the third and fourth waves of the pandemic. The third wave was found to be dominated by Nextclade 20D in our samples, with a small number of alpha variants. The delta variant was found to dominate the fourth wave samples, with the appearance of omicron variants late in 2021. Phylogenetic analysis reveals that the omicron variants are closest genetically to early pandemic variants. Mutation analysis shows SNPs, stop codon mutation gain, and deletion/insertion mutations, with distinct patterns of mutations governed by Nextclade or WHO variant. Finally, we observed a large number of highly correlated mutations, and some negatively correlated mutations, and identified a general inclination toward mutations that lead to enhanced thermodynamic stability of the spike protein. Overall, this study contributes genetic and phylogenetic data, as well as provides insights into SARS-CoV-2 viral evolution that may eventually help in the prediction of evolving mutations for better vaccine development and drug targets

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Energy consumption forecast in peer to peer energy trading

Abstract This study predicts future values of energy consumption demand from a novel dataset that includes the energy consumption during COVID-19 lockdown, using up-to-date deep learning algorithms to reduce peer-to-peer energy system losses and congestion. Three learning algorithms, namely Random Forest (RF), Bi-LSTM, and GRU, were used to predict the future values of a building’s energy consumption. The results were compared using the RMSE and MAE evaluation metrics. The results show that predicting the future energy demand with accurate results is achievable, and that Bi-LSTM and GRU perform better, especially when trained as univariate models with only the energy consumption values and no other features included

Investigation of the phytochemical composition, antioxidant, antibacterial, anti-osteoarthritis, and wound healing activities of selected vegetable waste

Abstract Agri-food wastes, produced following industrial food processing, are mostly discarded, leading to environmental hazards and losing the nutritional and medicinal values associated with their bioactive constituents. In this study, we performed a comprehensive analytical and biological evaluation of selected vegetable by-products (potato, onion, and garlic peels). The phytochemical analysis included UHPLC-ESI-qTOF-MS/MS in combination with molecular networking and determination of the total flavonoid and phenolic contents. Further, the antimicrobial, anti-osteoarthritis and wound healing potentials were also evaluated. In total, 47 compounds were identified, belonging to phenolic acids, flavonoids, saponins, and alkaloids as representative chemical classes. Onion peel extract (OPE) showed the higher polyphenolic contents, the promising antioxidant activity, the potential anti-osteoarthritis activity, and promising antimicrobial activity, especially against methicillin-resistant Staphylococcus aureus (MRSA). Furthermore, OPE revealed to have promising in vivo wound healing activity, restoring tissue physiology and integrity, mainly through the activation of AP-1 signaling pathway. Lastly, when OPE was loaded with nanocapsule based hydrogel, the nano-formulation revealed enhanced cellular viability. The affinities of the OPE major metabolites were evaluated against both p65 and ATF-2 targets using two different molecular docking processes revealing quercetin-3,4′-O-diglucoside, alliospiroside C, and alliospiroside D as the most promising entities with superior binding scores. These results demonstrate that vegetable by-products, particularly, those derived from onion peels can be incorporated as natural by-product for future evaluation against wounds and osteoarthritis

3D CT Volumetric Analysis of the Lung in COPD Patients: Comparison with Pulmonary Function Tests

Background: Retro and prospective comparative analytical study will be done over a 2-year period on patients with a multidisciplinary diagnosis of chronic obstructive pulmonary disease at the radiology department of Ain Shams University Hospitals. The aim of the study: To&nbsp;assess the role of the new CT lung analysis in quantitative assessment of chronic obstructive lung disease. The procedures: Patients will be subjected to CT chest without contrast then 3D models will be reconstructed using a software that allows automatic segmentation of each lung lobes and volume calculation, and giving each lung zone a Goddard score to determine the severity. The instruments: Patients will be assessed by the pulmonary function tests and body plethysmography. The results: The results will be collected and compared together. Data analysis will be performed using IBM statistical program for social science, version 22.0 (SPSS, 2013; IBM Corp., USA). Quantitative and qualitative data will be expressed as mean±SD, frequencies, and percentages. In addition, the relationship between total lung capacity (TLC), CT lung volume, and percentage LAA will be assessed and considered significant when the P-value is less than 0.05.&nbsp