6 research outputs found

    Fractional Biswas–Milovic Equation in Random Case Study

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    We apply two mathematical techniques, specifically, the unified solver approach and the exp(−φ(ξ))-expansion method, for constructing many new solitary waves, such as bright, dark, and singular soliton solutions via the fractional Biswas–Milovic (FBM) model in the sense of conformable fractional derivative. These solutions are so important for the explanation of some practical physical problems. Additionally, we study the stochastic modeling for the fractional Biswas–Milovic, where the parameter and the fraction parameters are random variables. We consider these parameters via beta distribution, so the mathematical methods that were used in this paper may be called random methods, and the exact solutions derived using these methods may be called stochastic process solutions. We also determined some statistical properties of the stochastic solutions such as the first and second moments. The proposed techniques are robust and sturdy for solving wide classes of nonlinear fractional order equations. Finally, some selected solutions are illustrated for some special values of parameters

    Metagenomic analysis reveals the fate of antibiotic resistance genes in a full-scale wastewater treatment plant in egypt

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    Wastewater treatment plants (WWTPs) are recognized as hotspots for the dissemination of antibiotic resistance genes (ARGs) and antibiotic-resistant bacteria (ARBs) in the environment. Our study utilized a high-throughput sequencing-based metagenomic analysis approach to compare the ARG abundance profiles of the raw sewage, treated effluent and activated sludge samples from a full-scale WWTP in Egypt. In addition, the difference in microbial community composition due to the treatment process was assessed. As a result, 578 ARG subtypes (resistance genes) belonging to 18 ARG types (antibiotic resistance classes) were identified. ARGs encoding for resistance against multidrug, aminoglycoside, bacitracin, beta-lactam, sulfonamide, and tetracycline antibiotics were the most abundant types. The total removal efficiency percentage of ARGs in the WWTP was found to be 98% however, the ARG persistence results indicated that around 68% of the ARGs in the influent could be found in the treated effluent. This finding suggests that the treated wastewater poses a potential risk for the ARG dissemination in bacterial communities of the receiving water bodies via horizontal gene transfer (HGT). The community composition at phylum level showed that Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria were the most abundant phyla in all datasets. Although the relative abundance of several pathogenic bacteria in the influent declined to less than 1% in the effluent, the taxonomic assignments at species level for the effluent and sludge metagenomes demonstrated that clinically important pathogens such as Escherichia coli, Klebsiella pneumonia, and Aeromonas caviae were present. Overall, the results of this study would hopefully enhance our knowledge about the abundance profiles of ARGs and their fate in different wastewater treatment compartments that have never been examined before

    The Assessment of the Risk Ranking and Mobility Potential Associated with Environmental Resistomes in Wastewater Using Metagenomic Assembly

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    The environmental pollution of antibiotic resistance genes (ARGs) and antibiotic-resistant bacteria (ARB) is a growing public health concern. In the current study, de novo metagenomic assembly and bioinformatics analysis approaches were utilized to estimate the quantitative risk index of the environmental resistomes in wastewater influent (INF) and effluent (EFF) of a conventional wastewater treatment plant (WWTP) in Egypt. Furthermore, the risk indices of the local INF and EFF resistomes were compared to those calculated for the selected publicly available wastewater datasets from eight countries worldwide. Additionally, a classification framework prioritizing the public health hazard level of the discharged non-redundant highly mobilized ARGs was introduced. This integrative outline considered the estimated mobility potential percentage, host pathogenicity, and annotation category (perfect, strict, and loose) of the detected ARGs on their assembled contigs. Moreover, high-quality metagenome-assembled genomes (MAGs) were extracted and the putative genome bins with acquired ARGs were determined. The comprehensive resistome risk scores of the local WWTP showed that INF resistome had a slightly higher risk index (47.87) compared to the average score of the other examined counterparts (41.06). However, the estimated risk value of EFF resistome (26.80) was ranked within the global average (26.06) of the selected international WWTPs. Furthermore, the determination of the samples’ risk ranking showed that most of the effluent resistomes were clustered in a lower risk rank compared to the other selected samples for raw sewage, influent, and hospital wastewater, indicating the impact of the wastewater treatment process on reducing the ARG mobilization potential in downstream environments. The evaluation of the ARGs’ genetic context in their ARG-carrying contigs (ACCs) indicated that a total of 161/648 (25%) non-redundant ARGs were co-located with sequences of mobile genetic determinants on the same ACC in both the INF and EFF assemblies. These ARGs comprised the pan mobile resistome of the studied WWTP. Of them, 111 ARGs with a mobility potential percent (M%) less than 95% were grouped at the least risk level 5. The remaining 50 highly mobilized ARGs (M% ≥ 95%) were extracted and classified into four higher risk levels. Those of risk levels 1 and 2 (39 ARGs) represented the current ARG dissemination threats for further monitoring in downstream environments, where they were all carried by pathogenic hosts and annotated to the perfect and strict categories by the resistance gene identifier software (RGI). A total of 10 highly mobilized ARGs were assigned to risk rank 3, as they comprised the loose hits of the RGI analysis. Finally, the risk level 4 ARGs constituted genes that co-existed with the non-pathogenic sequence on the ACCs and were represented by one gene in the current analysis framework. The two previous categories constituted new highly mobilized ARGs of emergent threat to public health. On the other hand, a total of 35 and 118 MAGs were recovered from INF and EFF assembled metagenomes, respectively, using selection cutoff thresholds of a minimum completeness of 70% and a maximum contamination of 10%. While none of the INF MAGs carried any acquired ARGs, six EFF genome bins (5%) were associated with ten acquired ARGs, as indicated by the ResFinder software. These results suggest that potential horizontal gene transfer (HGT) events have evolved among the community members of the studied EFF samples

    The Assessment of the Risk Ranking and Mobility Potential Associated with Environmental Resistomes in Wastewater Using Metagenomic Assembly

    No full text
    The environmental pollution of antibiotic resistance genes (ARGs) and antibiotic-resistant bacteria (ARB) is a growing public health concern. In the current study, de novo metagenomic assembly and bioinformatics analysis approaches were utilized to estimate the quantitative risk index of the environmental resistomes in wastewater influent (INF) and effluent (EFF) of a conventional wastewater treatment plant (WWTP) in Egypt. Furthermore, the risk indices of the local INF and EFF resistomes were compared to those calculated for the selected publicly available wastewater datasets from eight countries worldwide. Additionally, a classification framework prioritizing the public health hazard level of the discharged non-redundant highly mobilized ARGs was introduced. This integrative outline considered the estimated mobility potential percentage, host pathogenicity, and annotation category (perfect, strict, and loose) of the detected ARGs on their assembled contigs. Moreover, high-quality metagenome-assembled genomes (MAGs) were extracted and the putative genome bins with acquired ARGs were determined. The comprehensive resistome risk scores of the local WWTP showed that INF resistome had a slightly higher risk index (47.87) compared to the average score of the other examined counterparts (41.06). However, the estimated risk value of EFF resistome (26.80) was ranked within the global average (26.06) of the selected international WWTPs. Furthermore, the determination of the samples’ risk ranking showed that most of the effluent resistomes were clustered in a lower risk rank compared to the other selected samples for raw sewage, influent, and hospital wastewater, indicating the impact of the wastewater treatment process on reducing the ARG mobilization potential in downstream environments. The evaluation of the ARGs’ genetic context in their ARG-carrying contigs (ACCs) indicated that a total of 161/648 (25%) non-redundant ARGs were co-located with sequences of mobile genetic determinants on the same ACC in both the INF and EFF assemblies. These ARGs comprised the pan mobile resistome of the studied WWTP. Of them, 111 ARGs with a mobility potential percent (M%) less than 95% were grouped at the least risk level 5. The remaining 50 highly mobilized ARGs (M% ≥ 95%) were extracted and classified into four higher risk levels. Those of risk levels 1 and 2 (39 ARGs) represented the current ARG dissemination threats for further monitoring in downstream environments, where they were all carried by pathogenic hosts and annotated to the perfect and strict categories by the resistance gene identifier software (RGI). A total of 10 highly mobilized ARGs were assigned to risk rank 3, as they comprised the loose hits of the RGI analysis. Finally, the risk level 4 ARGs constituted genes that co-existed with the non-pathogenic sequence on the ACCs and were represented by one gene in the current analysis framework. The two previous categories constituted new highly mobilized ARGs of emergent threat to public health. On the other hand, a total of 35 and 118 MAGs were recovered from INF and EFF assembled metagenomes, respectively, using selection cutoff thresholds of a minimum completeness of 70% and a maximum contamination of 10%. While none of the INF MAGs carried any acquired ARGs, six EFF genome bins (5%) were associated with ten acquired ARGs, as indicated by the ResFinder software. These results suggest that potential horizontal gene transfer (HGT) events have evolved among the community members of the studied EFF samples

    SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

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    Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population
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