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The present work aimed at studying the efficacy of mebendazole (MBZ) compared to artemisinin (ART) for the treatment of trichinellosis at various phases of infection. Seventy Swiss albino mice were orally infected by 300 Trichinella spiralis (T. spiralis) larvae. Mice were divided into infected untreated control group and infected groups treated with 50 mg kg−1 MBZ and 300 mg kg−1 ART for three and five consecutive days, respectively, at the enteral phase [2–4 days post infection (PI)], invasive phase (10–12 days PI) and encapsulated phase (28–30 days PI). All mice were sacrificed 35–42 days PI. MBZ and ART revealed a significant decrease in mean larval counts and increase of larval per cent reduction (LR %) when treatment was initiated during the enteral phase compared to the other phases. MBZ showed significantly higher LR % (99.7, 83.95 and 89.65%) than ART (80.58, 67.0 and 79.2%) when administered at the three infection phases. Histopathological study showed a decrease in the number of encysted larvae, their surrounding cellular infiltrates and increased regenerative muscles in all treated mice. In conclusion, ART possesses a substantial anthelmintic activity against T. spiralis infection in mice both at the enteral and encapsulated phases, yet, significantly lower than MBZ.

Geopolymer concrete is an eco-efficient and environmentally friendly construction material. Various ashes were used as the binder in geopolymer concrete, such as fly ash, ground granulated blast furnace slag, rice husk ash, metakaolin ash, and Palm oil fuel ash. Fly ash was commonly consumed to prepare geopolymer concrete composites. It is essential to have 28 days resting period of the concrete to attain compressive strength in the structural design. In the present investigation, several soft computing models were employed to form the predictive models for forecasting the compressive strength of ground granulated blast furnace slag (GGBFS) concrete. A complete dataset of 268 samples was extracted from published research articles and analyzed to establish models. The modeling process incorporated seven effective parameters such as water content ( W ), temperature ( T ), water-to-binder ratio ( w/b ), ground granulated blast furnace slag-to-binder ratio (GGBFS/b), fine aggregate (FA) content, coarse aggregate (CA) content, and the superplasticizer dosage (SP) that were examined and measured on the compressive strength of GGBFS concrete by utilizing various modeling techniques, viz., Linear Regression (LR), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Support Vector Regression (SVR), Grey Wolf Optimization (GWO), Differential Evolution (DE), and Mantra Rays Foraging Optimization (MRFO). The compressive strength of the training datasets was predicted using the SVR-PSO and SVR-GWO models, with a reliable coefficient of correlation of 0.9765 and 0.9522, respectively.

Polyphenolics have been predicted to effectively develop antimicrobial agents for the food industry as food additives and promote human health. This study aims to synthesize pomegranate peel extract (PPE) with silver nanoparticles (AgNPs) against eight foodborne pathogens. Multispectroscopic analysis of UV–vis spectroscopy, Zeta potential, Fourier transform infrared (FTIR) and scanning electron microscopy (SEM) analysis were used to characterize the interaction between PPE and AgNPs. Eight foodborne pathogenic strains (six bacterial and two fungal strains) Bacillus subtilis ATCC 6633, Enterococcus faecalis ATCC 29212, Escherichia coli ATCC 8379, Klebsiella pneumoniae ATCC 00607, Salmonella typhi DSM 17058, Shigella sonnei DSM 5570, Aspergillus flavus ATCC 9643, and Rhizopus oryzae ATCC 96382 were used to test the inhibitory potential of PPW-AgNPs. The reaction colour of PPE-AgNPs from yellow to brown indicated that the nanoparticles were successfully formed. The UV absorption of PPE-AgNPs was detected at 440 nm of 0.9 SPR. SEM image of PPE-AgNPs exhibited spherical shapes with a zeta potential of − 20.1 mV. PPE-AgNPs showed high antimicrobial activity against all tested strains. The highest inhibition activity of PPE-AgNPs was recorded for the B. subtilis strain followed by K. pneumonia , while the highest resistance was noticed for R. oryzae. The components of pomegranate peel were analyzed using gas chromatography–mass spectrometry (GC–MS). The major constituents of pomegranate peel is phenol (51.1%), followed by Isocitronellol (19.41%) and 1-Propanol, 2-(2-hydroxypropyl)- (16.05%). PPE is key in the simple, eco-friendly green synthesis of extracellular stable AgNPs as an alternative source for harmful chemical disinfectants.

A novel series of pyrido[2,3-d]pyrimidines; pyrido[3,2-e][1,3,4]triazolo; and tetrazolo[1,5-c]pyrimidines were synthesized via different chemical transformations starting from pyrazolo[3,4-b]pyridin-6-yl)-N,N-dimethylcarbamimidic chloride 3b (prepared from the reaction of o-aminonitrile 1b and phosogen iminiumchloride). The structures of the newly synthesized compounds were elucidated based on spectroscopic data and elemental analyses. Designated compounds are subjected for molecular docking by using Auto Dock Vina software in order to evaluate the antiviral potency for the synthesized compounds against SARS-CoV-2 (2019-nCoV) main protease M pro. The antiviral activity against SARS-CoV-2 showed that tested compounds 7c, 7d, and 7e had the most promising antiviral activity with lower IC50 values compared to Lopinavir, “the commonly used protease inhibitor”. Both in silico and in vitro results are in agreement.

Despite the interdependence of general and periodontal health, there is paucity of national representative data on the prevalence of periodontal diseases and their associated risk factors in Egyptian population. This cross-sectional study, thus, aimed to assess the prevalence of periodontitis and tooth loss among Egyptian adults and investigate the association between potential risk factors and periodontal diseases. A total of 5,954 adults aged ≥ 20 years were included in this study as a subsample from Egypt's national oral health survey. Periodontitis was diagnosed with Community Periodontal Index 'CPI' scores ≥3 and tooth loss not due to caries was included in the analysis. Socio-demographic data and information on behavioral factors and history of diabetes were gathered in a face-to-face interview. Logistic regression was done to interpret the impact of potential predictors on the incidence of the two selected outcome variables. The overall prevalence of periodontitis was 26% and regression analysis revealed that higher odds of periodontitis existed among illiterate participants (OR = 1.74; 95% CI: 1.40-2.17), smokers (OR = 1.93; 95% CI: 1.69-2.20) and rural residents (OR = 1.16; 95% CI: 1.03-1.30). On the other hand, old age, frequency of dental attendance and history of diabetes were the main predictive factors for tooth loss. Among Egyptian adults, periodontal diseases were strongly associated with a multitude of modifiable and non-modifiable risk factors and inequalities in distribution of periodontal treatment needs were determined mainly by age, gender, level of education and residency location.

Seagull optimization algorithm (SOA) is a recent bio-inspired technique utilized to improve the constrained large-scale problems in low computational cost and quick convergence speed. However, the globally optimized search space for the SOA is linear, which means that the SOA’s global search capability could not be fully utilized. Thus, we propose an improved SOA algorithm (ISOA) using Lévy flight and mutation operators. The ISOA obtains some Lévy flight features, which improves the original SOA by performing large jumps, making the search escape from the local optima and begin at a different search space region. The mutation operator, which improves the exploration–exploitation trade-off, allows the catch of the optimal solution quickly and accurately. In order to examine the performance of the proposed ISOA approach, three experiments were conducted. The first one evaluates the ISOA in solving the global optimization problem. The second one is a comparative study based on twenty benchmark datasets to evaluate the general capability of ISOA in feature selection, compared to ten recent and well-established algorithms constructed using the other meta-heuristics methods. Furthermore, the third experiment is conducted using a real dataset with various face poses to investigate the efficiency of the ISOA in pose-variation recognition. Compared to the other meta-heuristics methods, the results show that the proposed model is more accurate and efficient in global optimization, feature selection purposes, and pose variation recognition. Furthermore, the ISOA approach outperforms the other methods proposed in the state-of-the-art literature.

Azithromycin (AZT), a persistent macrolide antibiotic, is an emerging environmental contaminant due to its high aqueous stability and role in antimicrobial resistance. In this study, natural serpentinite was chemically exfoliated using dimethyl sulfoxide (DMSO), dimethylformamide (DMF), and urea (U) to enhance surface reactivity and adsorption performance toward AZT. Textural characterization revealed a marked increase in surface accessibility, with BET area rising from 6.1 m²/g (raw) to 23.7 m²/g (DMSO/SP), 18.8 m²/g (DMF/SP), and 15.3 m²/g (U/SP), while pore diameters expanded from 11.1 nm to ~ 16 nm, exposing more reactive hydroxyl groups. Batch adsorption experiments showed pH-dependent uptake, with maximum removal at pH 9. Adsorption kinetics followed the pseudo-first-order model (R² > 0.90), and intra-particle diffusion confirmed a multi-stage adsorption pathway. Statistical physics modeling revealed saturation capacities (Q sat ) of 329.7 mg/g for DMSO/SP, 292.3 mg/g for DMF/SP, and 279.9 mg/g for U/SP, confirming the superior adsorption of DMSO-assisted exfoliation. Active site density (N m ) reached 109.5 mg/g for DMSO/SP, compared to 77.5 mg/g for DMF/SP and 84.3 mg/g for U/SP. The number of AZT molecules per site (n) exceeded unity, indicating multi-molecular stacking: DMSO/SP: 3.01–3.44, DMF/SP: 3.77–4.41, U/SP: 3.32–4.40 molecules/site. The mean adsorption energy (ΔE ≈ 5 kJ/mol) confirmed a reversible, exothermic physisorption process dominated by electrostatic attraction. Expanded interlayer spacing facilitated multilayer stacking, while hydroxyl groups promoted hydrogen bonding, creating a synergistic mechanism for enhanced retention. These findings show solvent polarity and molecular geometry governs serpentinite delamination, site density, and adsorption, with DMSO producing the most open, high-capacity adsorbent.

This study investigated the effect of foliar application of extract and culture of Nostoc calcicola and Nostoc linckia on the Fusarium oxysporum f. sp.lycopersici (FOL) that infects tomatoes (Solanum lycopersicum) plant in vitro and in vivo. Cyanobacterial isolates were isolated from saline soils at El-Hamoul and Seidy Salem locations Kafr Elsheikh, Egypt, and identified to be N. calcicola and N. linckia Bioactive compounds of extract were analyzed by Gas chromatography-mass spectrometry (GC–MS). Dry weight, carotene, chlorophyll content, and total phenolic compounds of isolates were measured. Plant height, dry weight, fruit number, and fruit weight of tomatoes were estimated. GC/MS analysis showed 49 and 35 bioactive compounds in extracts of N. calcicola and N. linckia, respectively. N. calcicola possesses the highest values of chlorophyll a, carotenoid, and total phenol contents in dry weight compared with N. linckia. After 100 days of tomato growth, the results showed the highest yield of tomato fruits with the application of N. calcicola and N. linckia compared with the untreated plants and the plants which were infected with Fusarium, suggesting that N. calcicola and N. linckia can serve as a new bioagent for biological control of the soil fungus Fusarium oxysporum f. sp. lycopersici (FOL).

For accurate estimation of streamflow of a mountainous river basin, a novel hybrid method is developed in this study, where gradient-based optimization (GBO) algorithm is employed to adjust adaptive neuro-fuzzy system's (ANFIS) hyperparameters. Two key mountainous basins in Pakistan, namely, Gilgit and Astore basins, were selected to show the model's effectiveness in predicting monthly streamflows using temperature and antecedent streamflow data. Several benchmark methods for optimizing ANFIS parameters were compared, which includes particle swarm optimization (PSO), genetic algorithm (GA), differential evolution (DE), ant colony optimization (ACO) and grey wolf optimization (GWO). The GBO algorithm enhanced ANFIS prediction accuracy more than the other benchmark methods. ANFIS-GBO improved the prediction accuracy of other benchmark algorithms hybrid ANFIS models by about 28–29.5, 28–26.9, 28.7−40.4, 11.2–20.1 and 10.4–20.9% with respect to root mean square error (RMSE), normalized RMSE, mean absolute error, determination coefficient and Nash Sutcliffe Efficiency in the studied basins, respectively. The ANFIS-GBO model also improved the peak streamflow prediction accuracy of ANFIS-GWO, ANFIS-PSO, ANFIS-ACO, ANFIS-GA and ANFIS-DE by about 4–23.7, 23.1–32.4, 15.4–41.6, 18.9–49.4 and 17.2–52.3%, respectively. The ANFIS-GBO also showed higher strength than the other models in estimating streamflows from nearby station data as input. Performance comparison of GBO based ANFIS hybridized model with standalone ANFIS model showed that GBO successfully enhanced the prediction accuracy of ANFIS model by optimal tuning of its parameters.

A series of 1″-(alkylsulfonyl)-dispiro[indoline-3,2′-pyrrolidine-3′,3″-piperidine]-2,4″-diones 6a‒o has been synthesized through regioselective multi-component azomethine dipolar cycloaddition reaction of 1-(alkylsulfonyl)-3,5-bis(ylidene)-piperidin-4-ones 3a ‒ h . X-ray diffraction studies ( 6b‒d , h ) confirmed the structures. The majority of the synthesized analogs reveal promising antiproliferation properties against a variety of human cancer cell lines (MCF7, HCT116, A431 and PaCa2) with good selectivity index towards normal cell (RPE1). Some of the synthesized agents exhibit potent inhibitory properties against the tested cell lines with higher efficacies than the standard references (sunitinib and 5-fluorouracil). Compound 6m is the most potent. Multi-targeted inhibitory properties against EGFR and VEGFR-2 have been observed for the synthesized agents. Flow cytometry supports the antiproliferation properties and shows the tested agents as apoptosis and necrosis forming. Vero cell viral infection model demonstrates the anti-SARS-CoV-2 properties of the synthesized agents. Compound 6f is the most promising (about 3.3 and 4.8 times the potency of the standard references, chloroquine and hydroxychloroquine). QSAR models explain and support the observed biological properties.