Ashraf Abu-Seida

New treatment against SARS-CoV-2 now is a must. Nowadays, the world encounters a huge health crisis by the COVID-19 viral infection. Nucleotide inhibitors gave a lot of promising results in terms of its efficacy against different viral infections. In this work, molecular modeling, docking, and dynamics simulations are used to build a model for the viral protein RNA-dependent RNA polymerase (RdRp) and test its binding affinity to some clinically approved drugs and drug candidates. Molecular dynamics is used to equilibrate the system upon binding calculations to ensure the successful reproduction of previous results, to include the dynamics of the RdRp, and to understand how it affects the binding. The results show the effectiveness of Sofosbuvir, Ribavirin, Galidesivir, Remdesivir, Favipiravir, Cefuroxime, Tenofovir, and Hydroxychloroquine, in binding to SARS-CoV-2 RdRp. Additionally, Setrobuvir, YAK, and IDX-184, show better results, while four novel IDX-184 derivatives show promising results in attaching to the SARS-CoV-2 RdRp. There is an urgent need to specify drugs that can selectively bind and subsequently inhibit SARS-CoV-2 proteins. The availability of a punch of FDA-approved anti-viral drugs can help us in this mission, aiming to reduce the danger of COVID-19. The compounds 2 and 3 may tightly bind to the SARS-CoV-2 RdRp and so may be successful in the treatment of COVID-19. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

The purpose of this paper is to present a proposal for scheduling shuttle ambulance vehicles assigned to COVID-19 patients using one of the discrete optimization techniques, namely, the multi-objective multiple 0–1 knapsack problem. The scheduling aims at achieving the best utilization of the predetermined planning time slot; the best utilization is evaluated by maximizing the number of evacuated people who might be infected with the virus to the isolation hospital and maximizing the effectiveness of prioritizing the patients relative to their health status. The complete mathematical model for the problem is formulated including the representation of the decision variables, the problem constraints, and the multi-objective functions. The proposed multi-objective multiple knapsack model is applied to an illustrated case study in Cairo, Egypt, the case study aims at improving the scheduling of ambulance vehicles in the back and forth shuttle movements between patient’ locations and the isolation hospital. The case study is solved using a novel Discrete Binary Gaining-Sharing knowledge-based optimization algorithm (DBGSK). The detail procedure of the novel DBGSK is presented along with the complete steps for solving the case study.

Abstract Background: Egypt is affected by the COVID-19 pandemic in all aspects of life: Health, economy and socially. Serological survey for SARS-CoV-2 antibodies is a valuable method to assess the extent of spread of the pandemic especially in healthcare workers (HCW), and to detect asymptomatic cases. Aim of Study: This research aims at proving the usefulness of SARS-CoV-2 antibody detection to identify and isolate infected individuals among HCW. Results may be employed as a surrogate to economize the use of RT-PCR evaluation and to make executive decision limiting viral spread among medical personnel in Kasr Al Ainy hospitals. Material and Methods: This cross-sectional survey study has included 897 HCW from multiple frontline and susceptible services within Kasr Al Ainy, Cairo University Hospitals. HCW were subjected to wide screening to study the presence of SARS-CoV-2 specific antibody responses (IgG and IgM) by Electro-chemiluminescence immunoassay tests and Lateral Flow Immunochromatographic assay (Rapid detection test) kits. Results: Our screening program has revealed 105 positive cases which accounts for 11.7% of the screened group. Of those, 33 (31.4%) were symptomatic and 72 (68.6%) were asymptomatic. Conclusion: The use of COVID-19 antibody testing for HCW can provide crucial information that might prevent further propagation of infection among HCW and their patients. Further research is warranted to provide evidence related to wide implementation of screening programs for HCW and to provide clear guidelines related to specifics of such programs.

Purpose: Vitamin D deficiency is highly prevalent in critically ill patients, and has been associated with more prolonged length of hospital stay and poor prognosis. Patients undergoing open-heart surgery are at higher risk due to the associated life-threatening postoperative complications. This study investigated the effect of alfacalcidol treatment on the length of hospital stay in patients undergoing valve-replacement surgery. Methods: This single-center, randomized, open-label, controlled trial was conducted at El-Demerdash Cardiac Academy Hospital (Cairo, Egypt), from April 2017 to January 2018. This study included adult patients undergoing valve-replacement surgery who were randomized to the intervention group (n = 47; alfacalcidol 2 μg/d started 48 h before surgery and continued throughout the hospital stay) or to the control group (n = 42). The primary end points were lengths of stay (LOS) in the intensive care unit (ICU) and in the hospital. Secondary end points were the prevalence of postoperative hospital-acquired infections, cardiac complications, and in-hospital mortality. Findings: A total of 86 patients were included in the final analysis, with 51 (59.3%) being vitamin D deficient on hospital admission. Treatment with alfacalcidol was associated with a statistically significant decrease in ICU LOS (hazard ratio = 1.61; 95% CI, 1.77–2.81; P = 0.041) and hospital LOS (hazard ratio = 1.63; 95% CI, 1.04–2.55; P = 0.034). Treated patients had a significantly lower postoperative infection rate than did the control group (35.5% vs 56.1%; P = 0.017). The median epinephrine dose was lower in the intervention group compared to that in the control group (5.9 vs 8.2 mg; P = 0.019). The rate of in-hospital mortality was not significantly different between the 2 groups. Implications: Early treatment with 2 μg of alfacalcidol in patients undergoing valve-replacement surgery is promising and well tolerated. This effect may be attributed to its immunomodulatory and cardioprotective mechanisms. ClinicalTrials.gov identifier: NCT04085770. © 2020 Elsevier Inc.

The pathophysiological mechanisms underlying multiple sclerosis include both inflammatory and degenerative processes. We aimed to study and compare markers of neuroinflammation and neurodegeneration in patients with first presentation of demyelinating disorder and to prospectively identify which of the studied markers serve as predictors for early conversion to multiple sclerosis. Thus, 42 patients with first clinical manifestations suggestive of demyelinating disease were included in a prospective study. Subjects underwent thorough history taking and clinical evaluation. Laboratory studies involved analysis of cerebrospinal fluid (CSF) and serum chitinase 3-like 1 levels. Brain imaging included MRI and ultrasonographic assessment.

Drug–drug interaction (DDI) is a major public health problem contributing to 30% of the unexpected clinical adverse drug events. Informatics-based studies for DDI signal detection have been evolving in the last decade. We aim at providing a boosted machine learning (ML) framework to predict novel DDI safety signals with high precision. We propose a similarity-based machine learning framework called “SMDIP” using DrugBank as one of the most reliable pharmaceutical knowledge bases. For this study, DrugBank provides the latest drug information in terms of DDIs, targets, enzymes, transporters, and carriers. We computed drug–drug similarities using a Russell–Rao measure for the available biological and structural information on DrugBank for representing the sparse feature space. Logistic regression is adopted to conduct DDI classification with a focus on searching for key similarity predictors. Six types of ML models are deployed on the selected DDI key features. Our study reveals that SMDIP has yielded favourable predictive performance compared to relevant studies with results as follows: AUC 76%, precision 82%, accuracy 79%, recall 62%, specificity 90%, and F-measure 78%. To further confirm the reliability and reproducibility of SMDIP, we investigate SMDIP on an unseen subset of direct-acting-antiviral (DAA) drugs for treating hepatitis C infections. Forty novel DAA DDIs are predicted that show consistency with the pharmacokinetic and pharmacodynamic profiles of these drugs. Furthermore, several reports from the pharmacovigilance literature corroborate our framework results. Those evaluations show that SMDIP is a promising framework for uncovering DDIs, which can be multifariously feasible in drug development, postmarketing surveillance, and public health fields.

We introduce a new numerical method based on the sinc-Gaussian operator Operatorsfor solving the inverse heat equation. We establish rigorous proofs of the error estimates for both truncation and aliasing errors. The effect of the amplitude error, which has not been considered before, is also investigated theoretically and numerically for the first time in inverse heat problems. The domain of solvability of the inverse heat problem Inverse heat problemis enlarged and numerical examples show the superiority of the technique over the classical sinc-method. The power of the method is exhibited through several examples.

Hadi, Anas A.Mohamed, Ali W.Jambi, Kamal M.Real parameter optimization is one of the active research fields during the last decade. The performance of LSHADE-SPACMALSHADE was competitive in IEEE CEC’2017 competition on Single Objective Bound Constrained Real-Parameter Single Objective Optimization. Besides, it was ranked fourth among twelve papers were presented on and compared to this new benchmark problems. In this work, an improved version named ELSHADE-SPACMASPACMA is introduced. In LSHADE-SPACMA, p value that controls the greediness of the mutation strategy is constant. While in ELSHADE-SPACMAESHADE, p value is dynamic. Larger value of p will enhance the exploration, while smaller values will enhance the exploitation. We further enhanced the performance of ELSHADE-SPACMA by integrating another directed mutation strategy within the hybridization framework. The proposed algorithm has been evaluated using IEEE CEC’2017 benchmark. According to the comparison results, the proposed ELSHADE-SPACMA algorithm is better than LSHADE and LSHADE-SPACMA. Besides, The comparison results between ELSHADE-SPACMA and the best three algorithms from the IEEE CEC’2017 Competition indicate that ELSHADE-SPACMA algorithm shows overall better performance and it is highly competitive algorithm for solving global optimization problems.

The Coronavirus Diseases 2019 (COVID-19) seriously affecting human health all over the world. More than 107 M people are reported positive for SARS-CoV-2, the virus causing COVID-19 pneumonia, from which +2.3 M died. Nucleotide Inhibitors (NI) have promising results in terms of its efficacy against different viral polymerases, including the Hepatitis C Virus (HCV) Non-Structural Protein 5 B (NS5B) RNA dependent RNA polymerase (RdRp) 1. Thus, the non-structural protein 12 (nsp12) RdRp of the human coronavirus represents an attractive target to develop a possible therapeutic agent. Sofosbuvir proved itself as a potential anti-SARS-CoV-2 RdRp and could inhibit viral replication and infection propagation. © 2021 Mohamed Nabil Ibrahim and Abdo Abdellah Elfiky.

Soil arsenic (As) contamination limits global agricultural productivity. Anthropogenic emissions are causing atmospheric CO2 levels to rise. Elevated CO2 (eCO2) boosts plant growth both under optimal and suboptimal growth conditions. However, the crop-specific interaction between eCO2 and soil arsenic exposure has not been investigated at the whole plant, physiological and biochemical level. Here, we tested the effects of eCO2 (620 ppm) and soil As exposure (mild and severe treatments, 25 and 100 mg As/Kg soil) on growth, photosynthesis and redox homeostasis in barley (C3) and maize (C4). Compared to maize, barley was more susceptible to soil As exposure at ambient CO2 levels. Barley plants accumulated more As, particularly in roots. As accumulation inhibited plant growth and induced oxidative damage in a species-specific manner. As-exposed barley experienced severe oxidative stress as illustrated by high H2O2 and protein oxidation levels. Interestingly, eCO2 differentially mitigated As-induced stress in barley and maize. In barley, eCO2 exposure reduced photorespiration, H2O2 production, and lipid/protein oxidation. In maize eCO2 exposure led to an upregulation of the ascorbate-glutathione (ASC/GSH)-mediated antioxidative defense system. Combined, this work highlights how ambient and future eCO2 levels differentially affect the growth, physiology and biochemistry of barley and maize crops exposed to soil As pollution.

Abstract The use of plant growth-promoting bacteria (PGPB) to enhance plant growth and protection against heavy metal toxicity has been extensively studied. However, its potentiality to reduce arsenate toxicity, a threat to plant growth and metabolism, has been hardly investigated. Moreover, the toxic effect of arsenic oxide nanoparticles (As-NPs) on plants and possible mechanisms for its alleviation has not yet been explored. In this study, the impact of the bioactive actinomycete Streptomyces spp. on the growth, physiology and stress-related metabolites, such as sugars and proline, on As-NPs-stressed wheat and maize plants was investigated. Soil amendment with arsenic oxide nanoparticles (As-NPs) induced the uptake and accumulation of As in the plants of both species, resulting in reduced growth and photosynthesis, but less marked in maize than in wheat plants. Under As-NPs-free conditions, Streptomyces spp. treatment markedly improved growth and photosynthesis in wheat only. The application of Streptomyces spp. reduced As accumulation, recovered the As-NPs-induced growth, photosynthesis inhibition, and oxidative damage in plants of both species. Wheat plants specifically accumulated soluble sugars, while both species accumulated proline. Under As-NPs stress, the ornithine pathway of proline biosynthesis was more important in maize than in wheat plants, while the glutamine pathway was dominant in wheat ones. The addition of Streptomyces spp. further induced the accumulation of proline and starch in both plant species. Overall, despite a different response to Streptomyces spp. under nontoxic conditions, the amendment of as-contaminated soil with Streptomyces spp. induced similar metabolic responses in the two tested species, which trigger stress recovery.

This article proposes a novel binary version of recently developed Gaining Sharing knowledge-based optimization algorithm (GSK) to solve binary optimization problems. GSK algorithm is based on the concept of how humans acquire and share knowledge during their life span. A binary version of GSK named novel binary Gaining Sharing knowledge-based optimization algorithm (NBGSK) depends on mainly two binary stages: binary junior gaining sharing stage and binary senior gaining sharing stage with knowledge factor 1. These two stages enable NBGSK for exploring and exploitation of the search space efficiently and effectively to solve problems in binary space. Moreover, to enhance the performance of NBGSK and prevent the solutions from trapping into local optima, NBGSK with population size reduction (PR-NBGSK) is introduced. It decreases the population size gradually with a linear function. The proposed NBGSK and PR-NBGSK applied to set of knapsack instances with small and large dimensions, which shows that NBGSK and PR-NBGSK are more efficient and effective in terms of convergence, robustness, and accuracy.

Assessing microbial identity, diversity, and community structure could be a valuable tool for monitoring the impact of xenobiotics and anthropogenic inputs in rivers, especially in urban and industrial settings. Here, we characterize the Nile River microbial community in water and sediments in summer and winter at five locations that span its natural flow through the Cairo metropolis. 16S rRNA gene datasets were analyzed to identify the role played by sample type (sediment versus water), season, and location in shaping the community, as well as to predict functional potential of the Nile River microbiome. Microbial communities were mostly influenced by sampling type (sediments versus water), while seasonal effects were only observed in water samples. Spatial differences did not represent a significant factor in shaping the community in either summer or winter seasons. Proteobacteria was the most abundant phylum in both water and sediment samples, with the order Betaproteobacteriales being the abundant one. Chloroflexi and Bacteroidetes were also prevalent in sediment samples, while Cyanobacteria and Actinobacteria were abundant in water samples. The linear discriminative analysis effect size (LEfSe) identified the cyanobacterial genus Cyanobium PCC-6307 as the main variable between summer and winter water. Sequences representing human and animal potential pathogens, as well as toxin-producing Cyanobacteria, were identified in low abundance within the Nile microbiome. Functionally predicted metabolic pathways predicted the presence of antibiotic biosynthesis, as well as aerobic xenobiotic degradation pathways in the river microbiome.

Excess selenium (Se) causes toxicity, and nitric oxide (NO)’s function in spermine (Spm)-induced tolerance to Se stress is unknown. Using wheat plants exposed to 1 mM sodium selenate—alone or in combination with either 1 mM Spm, 0.1 mM NO donor sodium nitroprusside (SNP) or 0.1 mM NO scavenger cPTIO—the potential beneficial effects of these compounds to palliate Se-induced stress were evaluated at physiological, biochemical and molecular levels. Se-treated plants accumulated Se in their roots (92%) and leaves (95%) more than control plants. Furthermore, Se diminished plant growth, photosynthetic traits and the relative water content and increased the levels of malondialdehyde, H2O2, osmolyte and endogenous NO. Exogenous Spm significantly decreased the levels of malondialdehyde by 28%, H2O2 by 37% and electrolyte leakage by 42%. Combined Spm/NO treatment reduced the Se content and triggered plant growth, photosynthetic traits, antioxidant enzymes and glyoxalase systems. Spm/NO also upregulated MTP1, MTPC3 and HSP70 and downregulated TaPCS1 and NRAMP1 (metal stress-related genes involved in selenium uptake, translocation and detoxification). However, the positive effects of Spm on Se-stressed plants were eliminated by the NO scavenger. Accordingly, data support the notion that Spm palliates selenium-induced oxidative stress since the induced NO elicits antioxidant defence upregulation but downregulates Se uptake and translocation. These findings pave the way for potential biotechnological approaches to supporting sustainable wheat crop production in selenium-contaminated areas.

Abstract The advent of a new pharmaceutical formulation evokes the need for examining the chemical stability of their constituents and establishing proper stability-indicating methods. Herein, the stability of the newly co-formulated Tamsulosin and Tadalafil were examined under different stress conditions. The acidic degradation of Tamsulosin yielded its sulfonated derivative, while Tadalafil was susceptible to both acidic and basic degradation. Two stability-indicating chromatographic methods, namely; high-performance thin-layer chromatography and high-performance liquid chromatography, have been developed. Significant high-performance thin-layer chromatography-fractionation could be achieved by utilizing a stationary phase of silica gel 60 F254 and a mobile phase composed of ethyl acetate/toluene/methanol/ammonia (4:2:4:0.6, by volumes) with densitometric recording at 280 nm over a concentration range of 0.5?25 ?g/band for both drugs. The HPLC-separation could be reached on XBridge? C18 column isocraticaly by using a mobile phase having acetonitrile/phosphate buffer, pH 6.0 (45:55, v/v) pumped at a flow rate of 1.7 mL/min and applying diode array ultraviolet-detection at 210 nm over a linearity range of 3?70 ?g/mL for each drug. Specificity of the two methods was additionally assured via peak purity assessment. Moreover, the methods were distinctly exploited for evaluating the drugs? stability in accelerated stability-studied samples of Tamplus? capsules.

In this paper, we introduce an estimation of the random Klinkenberg slip coefficient in the apparent permeability model using a chaos decomposition technique. The apparent permeability expression (Klinkenberg model) is used to describe natural gas transport in low-permeability media. In this process, the Klinkenberg factor is considered as a random parameter that depends on two random variables. The mean and variance (or standard deviation) of the two random variables can be estimated from the empirical data available in the literature. Therefore, the variation in the pressure is related directly to the random variation in the Klinkenberg factor. The polynomial chaos expansion is used to decompose the governing equation into a set of coupled deterministic equations that are solved and then used to compute the mean and variance of the solution. The algorithm of how to solve the deterministic coupled system is also presented. For verification, the model and its solution have been compared with the analytical solution of the basic steady-state version of the model. The comparison shows a very good agreement. The effects of a number of important parameters have been presented in graphs and discussed. It was found that the stochastic model works very well with small values of the liquid equivalent permeability, which meets the characteristics of low-permeability reservoirs. Also, the stochastic model works very well with small values of gas viscosity. On the other hand, the porosity seems to be not engaged well with the low-permeability model. The sensitivity of selection of random parameters is also investigated as well as the transient effect.

Stress triggered concurrent microbial/parasitic infections are prevalent in earthen pond based farmed Nile tilapia Oreochromis niloticus. In the current study, a total of thirty five O. niloticus were collected from a commercial fish farm with a history of severe mortalities at Port Said, Egypt. Nile tilapia samples were subjected to bacteriological, parasitological and pathological examinations. Twenty one Enterococcus fecalis and 15 Streptococcus agalactiae isolates were presumptively identified utilizing the semi-automated API 20 Strept test kit. The identities of the retrieved bacteria were confirmed by the sequencing of 16 S rRNA gene. Moribund O. niloticus were found to be heavily infected by one or both of Centrocestus formosanus encysted metacercariae (EMC) and/or Myxobolus tilapiae spores presenting a unique form of synergistic and/or symbiotic relationship. The identities of both parasites were confirmed through morphological and molecular characterization. Variable circulatory, degenerative, necrotic and proliferative changes were also noticed in hematopoietic organs. Interestingly, multiple myxobolus spores and EMC were noticed in some histological sections. It was obvious that the current concurrent bacterial and parasitic infections are triggered by the deleterious effects of some stressing environmental conditions. The unfavorable climatic conditions (high temperature and high relative humidity) recorded at the surge of mortalities are probable predisposing stress factors.

Streptomyces pactum (Act12), an agent of a gentle in situ remediation approach, has been recently used in few works in phytoextraction trials; however, the impact of Act12 on soil quality and metal phytoavailability has not been assessed in multi-metal contaminated soils. Consequently, here we assessed the potential impact of Act12 on the wheat (Triticum aestivum L.) growth, antioxidants activity, and the metal bioavailability in three industrial and mining soils collected from China and contained up to 118, 141, 339, and 6625 mg Cd, Cu, Pb, and Zn kg–1 soil, respectively. The Act12 was applied at 0 (control), 0.75 (Act-0.75), 1.50 (Act-1.5), and 2.25 (Act-2.25) g kg–1 (dry weight base) to the three soils; thereafter, the soils were cultivated with wheat (bio-indicator plant) in a pot experiment. The addition of Act12 (at Act-1.5 and Act-2.25) promoted wheat growth in the three soils and significantly increased the content of Cd, Cu, and Zn in the roots and shoots and Pb only in the roots (up to 121%). The Act12-induced increase in metals uptake by wheat might be attributed to the associated decrease in soil pH and/or the increase of metal chelation and production of indole acetic acid and siderophores. The Act12 significantly decreased the antioxidant activities and lipid peroxidation in wheat, which indicates that Act12 may mitigate metals stress in contaminated soils. Enhancing metals phytoextraction using Act12 is a promising ecofriendly approach for phytoremediation of metal-contaminated mining soils that can be safely utilized with non-edible plants and/or bioenergy crops.