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The emergence of new variants of SARS-CoV-2 associated with varying infectivity, pathogenicity, diagnosis, and effectiveness against treatments challenged the overall management of the COVID-19 pandemic. Wastewater surveillance (WWS), i.e., monitoring COVID-19 infections in communities through detecting viruses in wastewater, was applied to track the emergence and spread of SARS-CoV-2 variants globally. However, there is a lack of comprehensive understanding of the use and effectiveness of WWS for new SARS-CoV-2 variants. Here we systematically reviewed published articles reporting monitoring of different SARS-CoV-2 variants in wastewater by following the PRISMA guidelines and provided the current state of the art of this study area. A total of 80 WWS studies were found that reported different monitoring variants of SARS-CoV-2 until November 2022. Most of these studies (66 out of the total 80, 82.5%) were conducted in Europe and North America, i.e., resource-rich countries. There was a high variation in WWS sampling strategy around the world, with composite sampling (50/66 total studies, 76%) as the primary method in resource-rich countries. In contrast, grab sampling was more common (8/14 total studies, 57%) in resource-limited countries. Among detection methods, the reverse transcriptase polymerase chain reaction (RT-PCR)-based sequencing method and quantitative RT-PCR method were commonly used for monitoring SARS-CoV-2 variants in wastewater. Among different variants, the B1.1.7 (Alpha) variant that appeared earlier in the pandemic was the most reported (48/80 total studies), followed by B.1.617.2 (Delta), B.1.351 (Beta), P.1 (Gamma), and others in wastewater. All variants reported in WWS studies followed the same pattern as the clinical reporting within the same timeline, demonstrating that WWS tracked all variants in a timely way when the variants emerged. Thus, wastewater monitoring may be utilized to identify the presence or absence of SARS-CoV-2 and follow the development and transmission of existing and emerging variants. Routine wastewater monitoring is a powerful infectious disease surveillance tool when implemented globally. [ABSTRACT FROM AUTHOR]

The worldwide crises from multi-drug-resistant (MDR) bacterial infections are pushing us to search for new alternative therapies. The renewed interest in medicinal plants has gained the attention of our research group. Tamarindus indica L. (T. indica) is one of the traditional medicines used for a wide range of diseases. Therefore, we evaluated the antimicrobial activities of ethanolic extract of T. indica. The inhibitions zones, minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), and fractional inhibitor concentration indices (FICI) against Gram+ve and −ve pathogens were detected. The bioactive compounds from T. indica extract were identified by mass spectroscopy, thin-layer chromatography, and bio-autographic assay. We performed scanning electron microscopy (SEM) and molecular docking studies to confirm possible mechanisms of actions and antivirulence activities, respectively. We found more promising antimicrobial activities against MDR pathogens with MIC and MBC values for Staphylococcus aureus (S. aureus) and Pseudomonas aeruginosa (P. aeruginosa), i.e., (0.78, 3.12 mg/mL) and (1.56, 3.12 mg/mL), respectively. The antimicrobial activities of this extract were attributed to its capability to impair cell membrane permeability, inducing bacterial cell lysis, which was confirmed by the morphological changes observed under SEM. The synergistic interactions between this extract and commonly used antibiotics were confirmed (FICI values < 0.5). The bioactive compounds of this extract were bis (2-ethylhexyl)phthalate, phenol, 2,4-bis(1,1-dimethylethyl), 1,2-benzenedicarboxylic acid, and bis(8-methylnonyl) ester. Additionally, this extract showed antivirulence activities, especially against the S. aureus protease and P. aeruginosa elastase. In conclusion, we hope that pharmaceutical companies can utilize our findings to produce a new formulation of T. indica ethanolic extract with other antibiotics. [ABSTRACT FROM AUTHOR]

Early hepatocellular carcinoma (HCC) diagnosis is challenging. Moreover, for patients with alpha-fetoprotein (AFP)-negative HCC, this challenge is augmented. MicroRNAs (miRs) profiles may serve as potential HCC molecular markers. We aimed to assess plasma homo sapiens—(hsa)-miR-21-5p, hsa-miR-155-5p, hsa-miR-192-5p, and hsa-miR-199a-5p—expression levels as a panel of biomarkers for HCC in chronic hepatitis C virus (CHCV) patients with liver cirrhosis (LC), especially AFP-negative HCC cases, as a step toward non-protein coding (nc) RNA precision medicine. Subjects and methods: 79 patients enrolled with CHCV infection with LC, subclassified into an LC group without HCC (n = 40) and LC with HCC (n = 39). Real-time quantitative PCR was used to measure plasma hsa-miR-21-5p, hsa-miR-155-5p, hsa-miR-192-5p, and hsa-miR-199a-5p. Results: Plasma hsa-miR-21-5p and hsa-miR-155-5p demonstrated significant upregulation, while hsa-miR-199a-5p demonstrated significant downregulation in the HCC group (n = 39) when compared to the LC group (n = 40). hsa-miR-21-5p expression was positively correlated with serum AFP, insulin, and insulin resistance (r = 0.5, p < 0.001, r = 0.334, p = 0.01, and r = 0.303, p = 0.02, respectively). According to the ROC curves, for differentiating HCC from LC, combining AFP with each of hsa-miR-21-5p, hsa-miR-155-5p, and miR199a-5p improved the diagnostic sensitivity to 87%, 82%, and 84%, respectively, vs. 69% for AFP alone, with acceptable specificities of 77.5%, 77.5%, and 80%, respectively, and AUC = 0.89, 0.85, and 0.90, respectively vs. 0.85 for AFP alone. hsa-miR-21-5p/hsa-miR-199a-5p and hsa-miR-155-5p/hsa-miR-199a-5p ratios discriminated HCC from LC at AUC = 0.76 and 0.71, respectively, with sensitivities = 94% and 92% and specificities = 48% and 53%, respectively. Upregulation of plasma hsa-miR-21-5p was considered as an independent risk factor for HCC development [OR = 1.198(1.063–1.329), p = 0.002]. Conclusions: Combining each of hsa-miR-21-5p, hsa-miR-155-5p, and hsa-miR-199a-5p with AFP made it possible to identify HCC development in the LC patients' cohort with higher sensitivity than using AFP alone. hsa-miR-21-5p/hsa-miR-199a-5p and hsa-miR-155-5p/hsa-miR-199a-5p ratios are potential HCC molecular markers for AFP-negative HCC patients. hsa-miR-21-5p was linked, clinically and via in silico proof, to insulin metabolism, inflammation, dyslipidemia, and tumorigenesis in the HCC patients' group as well as for an upregulated independent risk factor for the emergence of HCC from LC in the CHCV patients. [ABSTRACT FROM AUTHOR]

Sunitinib has been associated with several cardiotoxic effects such as cardiac fibrosis. The present study was designed to explore the role of interleukin (IL)-17 in sunitinib-induced myocardial fibrosis (MF) in rats and whether its neutralization and/or administration of black garlic (BG), a form of fermented raw garlic (Allium sativum L.), could extenuate this adverse effect. Male Wistar albino rats received sunitinib (25 mg/kg three times a week, orally) and were co-treated with secukinumab (3 mg/kg, subcutaneously, three times total) and/or BG (300 mg/kg/day, orally) for four weeks. Administration of sunitinib induced significant increase in cardiac index, cardiac inflammatory markers, and cardiac dysfunction that were ameliorated by both secukinumab and BG, and to a preferable extent, with the combined treatment. Histological examination revealed disruption in the myocardial architecture and interstitial fibrosis in cardiac sections of the sunitinib group, which were reversed by both secukinumab and BG treatments. Both drugs and their co-administration restored normal cardiac functions, downregulated cardiac inflammatory cytokines, mainly IL-17 and NF-κB, along with increasing the MMP1/TIMP1 ratio. Additionally, they attenuated sunitinib-induced upregulation of the OPG/RANK/RANKL axis. These findings highlight another new mechanism through which sunitinib can induce interstitial MF. The current results propose that neutralizing IL-17 by secukinumab and/or supplementation with BG can be a promising therapeutic approach for ameliorating sunitinib-induced MF. [ABSTRACT FROM AUTHOR]

Integrating renewable energy sources (RESs) into modern electric power systems offers various techno-economic benefits. However, the inconsistent power profile of RES influences the power flow of the entire distribution network, so it is crucial to optimize the power flow in order to achieve stable and reliable operation. Therefore, this paper proposes a newly developed circle search algorithm (CSA) for the optimal solution of the probabilistic optimal power flow (OPF). Our research began with the development and evaluation of the proposed CSA. Firstly, we solved the OPF problem to achieve minimum generation fuel costs; this used the classical OPF. Then, the newly developed CSA method was used to deal with the probabilistic power flow problem effectively. The impact of the intermittency of solar and wind energy sources on the total generation costs was investigated. Variations in the system's demands are also considered in the probabilistic OPF problem scenarios. The proposed method was verified by applying it to the IEEE 57-bus and the 118-bus test systems. This study's main contributions are to test the newly developed CSA on the OPF problem to consider stochastic models of the RESs, providing probabilistic modes to represent the RESs. The robustness and efficiency of the proposed CSA in solving the probabilistic OPF problem are evaluated by comparing it with other methods, such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and the hybrid machine learning and transient search algorithm (ML-TSO) under the same parameters. The comparative results showed that the proposed CSA is robust and applicable; as evidence, an observable decrease was obtained in the costs of the conventional generators' operation, due to the penetration of renewable energy sources into the studied networks. [ABSTRACT FROM AUTHOR]

This paper proposes a novel hybrid optimization technique based on a machine learning (ML) approach and transient search optimization (TSO) to solve the optimal power flow problem. First, the study aims at developing and evaluating the proposed hybrid ML-TSO algorithm. To do so, the optimization technique is implemented to solve the classical optimal power flow problem (OPF), with an objective function formulated to minimize the total generation costs. Second, the hybrid ML-TSO is adapted to solve the probabilistic OPF problem by studying the impact of the unavoidable uncertainty of renewable energy sources (solar photovoltaic and wind turbines) and time-varying load profiles on the generation costs. The evaluation of the proposed solution method is examined and validated on IEEE 57-bus and 118-bus standard systems. The simulation results and comparisons confirmed the robustness and applicability of the proposed hybrid ML-TSO algorithm in solving the classical and probabilistic OPF problems. Meanwhile, a significant reduction in the generation costs is attained upon the integration of the solar and wind sources into the investigated power systems. [ABSTRACT FROM AUTHOR]

Thanks to high-throughput data technology, microRNA analysis studies have evolved in early disease detection. This work introduces two complete models to detect the biomarkers of two autoimmune diseases, multiple sclerosis and rheumatoid arthritis, via miRNA analysis. Based on work the authors published previously, both introduced models involve complete pipelines of text mining methods, integrated with traditional machine learning methods, and LSTM deep learning. This work also studies the fragmentation of miRNA sequences to reduce the needed processing time and computational power. Moreover, this work studies the impact of obtaining two different library preparation kits (NEBNEXT and NEXTFLEX) on the detection accuracy for rheumatoid arthritis. Additional experiments are applied to the proposed models based on three different transcriptomic datasets. The results denote that the transcriptomic fragmentation model reported a biomarker detection accuracy of 96.45% on a sequence fragment size of 0.2, indicating a significant reduction in execution power while retaining biomarker detection accuracy. On the other hand, the LSTM model obtained a promising detection accuracy of 72%, implying savings in feature engineering processing. Additionally, the fragmentation model and the LSTM model reported 22.4% and 87.5% less execution time than work in the literature, respectively, denoting a considerable execution power reduction. [ABSTRACT FROM AUTHOR]

A novel method to improve the robustness of steel end plate connections is presented in this paper. Existing commonly adopted techniques alter the stiffness of the beam or the end plate to improve the connection's robustness. In this study, the robustness is enhanced by improving the contribution of the bolts to the rotational capacity of connections; the higher the bolts' elongation, the higher the rotational capacity that can be achieved. However, the brittleness of the bolt material, combined with its small length, results in negligible elongation. Alternatively, the load path between the end plate and the bolts can be interrupted with a ductile element to achieve the required elongation. This can be achieved by inserting a steel sleeve with a designated length, thickness, and wall curvature between the end plate and the washer. The proposed sleeve should be designed so that its ultimate capacity is less than the force in the bolt at failure; accordingly, the sleeve develops a severe bending deformation before the failure of any connection components. Using a validated finite element model, end plate connections with various parameters are numerically investigated to understand the performance of the sleeve device. The proposed system substantially enhances the rotational capacity of the connections, ranging between 1.37 and 2.46 times that of the standard connection. It is also concluded that the sleeved connections exhibit a consistent elastic response with the standard connections, indicating the proposed system is compatible with codified elastic design approaches without modification. Furthermore, for a specific connection, various ductile responses can be achieved without altering the connection capacity nor configuration. [ABSTRACT FROM AUTHOR]

The limitations in the therapeutic options for foodborne pathogens lead to treatments failure, especially for multidrug-resistant (MDR) Salmonella sp., worldwide. Therefore, we aimed to find alternative and complementary therapies against these resistant foodborne pathogens. Out of 100 meat products samples, the prevalence rate of salmonella was 6%, serotyped only as S. Typhimurium and S. Enteritidis. According to the antibiotic susceptibility assays, the majority of our isolates were MDR and susceptible to cefotaxime. Out of the 13 tested plant extracts, five only showed an inhibition zone in the range of 8–50 mm against both serotypes. Based on their promising activity, the oily extract of cinnamon and aqueous extract of paprika represented the highest potency. Surprisingly, a significant synergistic effect was detected between cinnamon oil and cefotaxime. Depending on Gas Chromatography/Mass Spectrometry (GC-MS), the antimicrobial activity of cinnamon oil was attributed to four components including linalool, camphor, (Z)-3-Phenylacrylaldehyde and its stereoisomer 2-Propenal-3-phenyl. The anti-virulence activities of these compounds were confirmed on the basis of computational molecular docking studies. Accordingly, we recommended the use of cinnamon oil as a food additive to fight the resistant foodborne pathogens. Additionally, we confirmed its therapeutic uses, especially when co-administrated with other antimicrobial agents. [ABSTRACT FROM AUTHOR]

This article introduces an application of the recently developed hunger games search (HGS) optimization algorithm. The HGS is combined with chaotic maps to propose a new Chaotic Hunger Games search (CHGS). It is applied to solve the optimal power flow (OPF) problem. The OPF is solved to minimize the generation costs while satisfying the systems' constraints. Moreover, the article presents optimal siting for mixed renewable energy sources, photovoltaics, and wind farms. Furthermore, the effect of adding renewable energy sources on the overall generation costs value is investigated. The exploration field of the optimization problem is the active output power of each generator in each studied system. The CHGS also obtains the best candidate design variables, which corresponds to the minimum possible cost function value. The robustness of the introduced CHGS algorithm is verified by performing the simulation 20 independent times for two standard IEEE systems—IEEE 57-bus and 118-bus systems. The results obtained are presented and analyzed. The CHGS-based OPF was found to be competitive and superior to other optimization algorithms applied to solve the same optimization problem in the literature. The contribution of this article is to test the improvement done to the proposed method when applied to the OPF problem, as well as the study of the addition of renewable energy sources on the introduced objective function. [ABSTRACT FROM AUTHOR]

Defects in cardiac contractility and heart failure (HF) are common following doxorubicin (DOX) administration. Different miRs play a role in HF, and their targeting was suggested as a promising therapy. We aimed to target miR-24, a suppressor upstream of junctophilin-2 (JP-2), which is required to affix the sarcoplasmic reticulum to T-tubules, and hence the release of Ca2+ in excitation–contraction coupling using pachymic acid (PA) and/or losartan (LN). HF was induced with DOX (3.5 mg/kg, i.p., six doses, twice weekly) in 24 rats. PA and LN (10 mg/kg, daily) were administered orally for four weeks starting the next day of the last DOX dose. Echocardiography, left ventricle (LV) biochemical and histological assessment and electron microscopy were conducted. DOX increased serum BNP, HW/TL, HW/BW, mitochondrial number/size and LV expression of miR-24 but decreased EF, cardiomyocyte fiber diameter, LV content of JP-2 and ryanodine receptors-2 (RyR2). Treatment with either PA or LN reversed these changes. Combined PA + LN attained better results than monotherapies. In conclusion, HF progression following DOX administration can be prevented or even delayed by targeting miR-24 and its downstream JP-2. Our results, therefore, suggest the possibility of using PA alone or as an adjuvant therapy with LN to attain better management of HF patients, especially those who developed tolerance toward LN. [ABSTRACT FROM AUTHOR]

For the precise simulation performance, the accuracy of fuel cell modeling is important. Therefore, this paper presents a developed optimization method called Chaos Game Optimization Algorithm (CGO). The developed method provides the ability to accurately model the proton exchange membrane fuel cell (PEMFC). The accuracy of the model is tested by comparing the simulation results with the practical measurements of several standard PEMFCs such as Ballard Mark V, AVISTA SR-12.5 kW, and 6 kW of the Nedstack PS6 stacks. The complexity of the studied problem stems from the nonlinearity of the PEMFC polarization curve that leads to a nonlinear optimization problem, which must be solved to determine the seven PEMFC design variables. The objective function is formulated mathematically as the total error squared between the laboratory measured terminal voltage of PEMFC and the estimated terminal voltage yields from the simulation results using the developed model. The CGO is used to find the best way to fulfill the preset requirements of the objective function. The results of the simulation are tested under different temperature and pressure conditions. Moreover, the results of the proposed CGO simulations are compared with alternative optimization methods showing higher accuracy. [ABSTRACT FROM AUTHOR]

Intracellular growth of pathogenic Legionella in free-living amoebae (FLA) results in the critical concentrations that are problematic in engineered water systems (EWS). However, being amoeba-resistant bacteria (ARB), how Legionella spp. becomes internalized within FLA is still poorly understood. Using fluorescent microscopy, we investigated in real-time the preferential feeding behavior of three water-related FLA species, Willaertia magna, Acanthamoeba polyphaga, and Vermamoeba vermiformis regarding Legionella pneumophila and two Escherichia coli strains. Although all the studied FLA species supported intracellular growth of L. pneumophila, they avoided this bacterium to a certain degree in the presence of E. coli and mostly fed on it when the preferred bacterial food-sources were limited. Moreover, once L. pneumophila were intracellular, it inhibited digestion of co-occurring E. coli within the same trophozoites. Altogether, based on FLA–bacteria interactions and the shifts in microbial population dynamics, we propose that FLA's feeding preference leads to an initial growth of FLA and depletion of prey bacteria, thus increases the relative abundance of Legionella and creates a "forced-feeding" condition facilitating the internalization of Legionella into FLA to initiate the cycles of intracellular multiplication. These findings imply that monitoring of FLA levels in EWS could be useful in predicting possible imminent high occurrence of Legionella. [ABSTRACT FROM AUTHOR]

The appropriate planning of electric power systems has a significant effect on the economic situation of countries. For the protection and reliability of the power system, the optimal reactive power dispatch (ORPD) problem is an essential issue. The ORPD is a non-linear, non-convex, and continuous or non-continuous optimization problem. Therefore, introducing a reliable optimizer is a challenging task to solve this optimization problem. This study proposes a robust and flexible optimization algorithm with the minimum adjustable parameters named Improved Marine Predators Algorithm and Particle Swarm Optimization (IMPAPSO) algorithm, for dealing with the non-linearity of ORPD. The IMPAPSO is evaluated using various test cases, including IEEE 30 bus, IEEE 57 bus, and IEEE 118 bus systems. An effectiveness of the proposed optimization algorithm was verified through a rigorous comparative study with other optimization methods. There was a noticeable enhancement in the electric power networks behavior when using the IMPAPSO method. Moreover, the IMPAPSO high convergence speed was an observed feature in a comparison with its peers. [ABSTRACT FROM AUTHOR]

Postmenopausal women are at an increased risk of vascular calcification which is defined as the pathological deposition of minerals in the vasculature, and is strongly linked with increased cardiovascular disease risk. Since estrogen-replacement therapy is associated with increased cancer risk, there is a strong need for safer therapeutic approaches. In this study we aimed to investigate the protective and therapeutic effects of the phytoestrogen resveratrol against vascular calcification in ovariectomized rats, a preclinical model of postmenopause. Furthermore, we aimed to compare the effects of resveratrol to those of estrogen and to explore the mechanisms underpinning those effects. Treatment with resveratrol or estrogen ameliorated aortic calcification in ovariectomized rats, as shown by reduced calcium deposition in the arterial wall. Mechanistically, the effects of resveratrol and estrogen were mediated via the activation of SIRT1 signaling. SIRT1 protein expression was downregulated in the aortas of ovariectomized rats, and upregulated in rats treated with resveratrol or estrogen. Moreover, resveratrol and estrogen reduced the levels of the osteogenic markers: runt-related transcription factor 2 (RUNX2), osteocalcin and alkaline phosphatase (ALP) which have been shown to play a role during vascular calcification. Additionally, the senescence markers (p53, p16 and p21) which were also reported to play a role in the pathogenesis of vascular calcification, were reduced upon treatment with resveratrol and estrogen. In conclusion, the phytoestrogen resveratrol may be a safer alternative to estrogen, as a therapeutic approach against the progression of vascular calcification during postmenopause.