Natural Clay as a Low-Cost Adsorbent for Crystal Violet Dye Removal and Antimicrobial Activity

This investigation aimed at evaluating the efficiency of micro and nanoclays as a low-cost material for the removal of crystal violet (CV) dye from an aqueous solution. The impacts of various factors (contact time, pH, adsorbent dosage, temperature, initial dye concentration) on the adsorption process have been taken into consideration. Six micro and nanoclay samples were obtained by treating clay materials collected from different locations in the Albaha region, Saudi Arabia. Out of the six tested micro and nanoclays materials, two (NCQ1 and NCQ3) were selected based on the highest adsorption efficiency for complete experimentation. The morphology and structure of the selected micro and nanoclay adsorbents were characterized by various techniques: SEM-EDX, FTIR, XRF, XRD, and ICP-MS. The XRF showed that the main oxides of both nanoclays were SiO2, Al2O3, Fe2O3, K2O, CaO, and MgO, and the rest were impurities. All the parameters affecting the adsorption of CV dye were optimized in a batch system, and the optimized working conditions were an equilibrium time of 120 min, a dose of 30 mg, a temperature of 25 °C, and an initial CV concentration of 400 mg/L. The equilibrium data were tested using nonlinear isotherm and kinetic models, which showed that the Freundlich isotherm and pseudo-second-order kinetics gave the best fit with the experimental data, indicating a physico-chemical interaction occurred between the CV dye and both selected micro and nanoclay surfaces. The maximum adsorption capacities of NCQ1 and NCQ3 adsorbents were 206.73 and 203.66 mg/g, respectively, at 25 °C. The thermodynamic factors revealed that the CV dye adsorption of both micro and nanoclays was spontaneous and showed an exothermic process. Therefore, the examined natural micro and nanoclays adsorbents are promising effective adsorbents for the elimination of CV dye from an aqueous environment

Comparison of trauma management between two major trauma services in Riyadh, Kingdom of Saudi Arabia and Melbourne, Australia

Introduction The burden of injury in the Kingdom of Saudi Arabia (KSA) has increased in recent years, but the country has lacked a consistent methodology for collecting injury data. A trauma registry has been established at a large public hospital in Riyadh from which these data are now available.Objectives We aimed to provide an overview of trauma epidemiology by reviewing the first calendar year of data collection for the registry. Risk-adjusted analyses were performed to benchmark outcomes with a large Australian major trauma service in Melbourne. The findings are the first to report the trauma profile from a centre in the KSA and compare outcomes with an international level I trauma centre.Methods This was an observational study using records with injury dates in 2018 from the registries at both hospitals. Demographics, processes and outcomes were extracted, as were baseline characteristics. Risk-adjusted endpoints were inpatient mortality and length of stay. Binary logistic regression was used to measure the association between site and inpatient mortality.Results A total of 2436 and 4069 records were registered on the Riyadh and Melbourne databases, respectively. There were proportionally more men in the Saudi cohort than the Australian cohort (86% to 69%). The Saudi cohort was younger, the median age being 36 years compared with 50 years, with 51% of injuries caused by road traffic incidents. The risk-adjusted length of stay was 4.4 days less at the Melbourne hospital (95% CI 3.95 days to 4.86 days, p<0.001). The odds of in-hospital death were also less (OR 0.25; 95% CI 0.15 to 0.43, p<0.001).Conclusions This is the first hospital-based study of trauma in the kingdom that benchmarks with an individual international centre. There are limitations to interpreting the comparisons, however the findings have established a baseline for measuring continuous improvement in outcomes for KSA trauma services

Multiobjective Optimization and Machine Learning Algorithms for Forecasting the 3E Performance of a Concentrated Photovoltaic-Thermoelectric System

Previous theoretical research efforts which were validated by experimental findings demonstrated the thermo-economic benefits of the hybrid concentrated photovoltaic-thermoelectric (CPV-TE) system over the stand-alone CPV. However, the operating conditions and TE material properties for maximum CPV-TE performance may differ from those required in a standalone thermoelectric module (TEM). For instance, a high-performing TEM requires TE materials with high Seebeck coefficients and electrical conductivities, and at the same time, low thermal conductivities (). Although it is difficult to attain these ideal conditions without complex material engineering, the low implies a high thermal resistance and temperature difference across the TEM which raises the PV backplate’s temperature in a hybrid CPV-TE operation. The increased PV temperature may reduce the overall system’s thermodynamic performance. To understand this phenomenon, a study is needed to guide researchers in choosing the best TE material for an optimal operation of a CPV-TE system. However, no prior research effort has been made to this effect. One method of finding the optimum TE material property is to parametrically vary one or more transport parameters until an optimum point is determined. However, this method is time-consuming and inefficient since a global optimum may not be found, especially when large incremental step sizes are used. This study provides a better way to solve this problem by using a multiobjective optimization genetic algorithm (MOGA) which is fast and reliable and ensures that the global optimum is obtained. After the optimization has been conducted, the best performing conditions for maximum CPV-TE energy, exergy, and environmental (3E) performance are selected using the technique for order performance by similarity to ideal solution (TOPSIS) decision algorithm. Finally, the optimization workflow is deployed for 7000 test cases generated from 10 features using the optimal machine learning (ML) algorithm. The result of the optimization chosen by the TOPSIS decision-making method generated an output power, exergy efficiency, and CO2 saving of 44.6 W, 18.3%, and 0.17 g/day, respectively. Furthermore, among other ML algorithms, the Gaussian process regression was the most accurate in learning the CPV-TE performance dataset, although it required more computational effort than some algorithms like the linear regression model

Naproxen Based 1,3,4-Oxadiazole Derivatives as EGFR Inhibitors: Design, Synthesis, Anticancer, and Computational Studies

A library of novel naproxen based 1,3,4-oxadiazole derivatives (8–16 and 19–26) has been synthesized and screened for cytotoxicity as EGFR inhibitors. Among the synthesized hybrids, compound2-(4-((5-((S)-1-(2-methoxynaphthalen-6-yl)ethyl)-1,3,4-oxadiazol-2-ylthio)methyl)-1H-1,2,3-triazol-1-yl)phenol(15) was the most potent compound against MCF-7 and HepG2cancer cells with IC50 of 2.13 and 1.63 µg/mL, respectively, and was equipotent to doxorubicin (IC50 1.62 µg/mL) towards HepG2. Furthermore, compound 15 inhibited EGFR kinase with IC50 0.41 μM compared to standard drug Erlotinib (IC50 0.30 μM). The active compound induces a high percentage of necrosis towards MCF-7, HePG2 and HCT 116 cells. The docking studies, DFT and MEP also supported the biological data. These results demonstrated that these synthesized naproxen hybrids have EGFR inhibition effects and can be used as leads for cancer therapy

Cell Cycle Arrest and Apoptosis-Inducing Ability of Benzimidazole Derivatives: Design, Synthesis, Docking, and Biological Evaluation

In the current study, new benzimidazole-based 1,3,4-oxadiazole derivatives have been synthesized and characterized by NMR, IR, MS, and elemental analysis. The final compounds were screened for cytotoxicity against MDA-MB-231, SKOV3, and A549 cell lines and EGFR for inhibitory activities. Compounds 10 and 13 were found to be the most active against all the tested cell lines, comparable to doxorubicin, and exhibited significant inhibition on EGFR kinase, with IC50 0.33 and 0.38 μM, respectively, comparable to erlotinib (IC50 0.39 μM). Furthermore, these two compounds effectively suppressed cell cycle progression and induced cell apoptosis in MDA-MB-231, SKOV3, and A549 cell lines. The docking studies revealed that these compounds showed interactions similar to erlotinib at the EGFR site. It can be concluded that the synthesized molecules effectively inhibit EGFR, can arrest the cell cycle, and may trigger apoptosis and therefore, could be used as lead molecules in the development of new anticancer agents targeting EGFR kinase

Antioxidant and Wound Healing Potential of <i>Vitis vinifera</i> Seeds Supported by Phytochemical Characterization and Docking Studies

This study explored the in vivo wound healing potential of Vitis vinifera seed extract using an excision wound model with focus on wound healing molecular targets including TGFBR1, VEGF, TNF-α, and IL-1β. The wound healing results revealed that V. vinifera seed extract enhanced wound closure rates (p β and VEGF levels, and significantly downregulated TNF-α and IL-1β levels in comparison to the Mebo®-treated group. The phenotypical results were supported by biochemical and histopathological findings. Phytochemical investigation yielded a total of 36 compounds including twenty-seven compounds (1–27) identified from seed oil using GC-MS analysis, along with nine isolated compounds. Among the isolated compounds, one new benzofuran dimer (28) along with eight known ones (29–36) were identified. The structure of new compound was elucidated utilizing 1D/2D NMR, with HRESIMS analyses. Moreover, molecular docking experiments were performed to elucidate the molecular targets (TNF-α, TGFBR1, and IL-1β) of the observed wound healing activity. Additionally, the in vitro antioxidant activity of V. vinifera seed extract along with two isolated compounds (ursolic acid 34, and β-sitosterol-3-O-glucopyranoside 36) were explored. Our study highlights the potential of V. vinifera seed extract in wound repair uncovering the most probable mechanisms of action using in silico analysis

The Protective and Therapeutic Anti-Alzheimer Potential of <i>Olea europaea</i> L. cv. Picual: An In Silico and In Vivo Study

LC-HRESIMS metabolomic profiling of Olea europaea L. cv. Picual (OEP) (Saudi Arabian olive cultivar, F. Oleacea) revealed 18 compounds. Using pharmacology networking to specify the targets of the identified compounds with a relationship to Alzheimer’s disease, it was possible to identify the VEGFA, AChE, and DRD2 genes as the top correlated genes to Alzheimer’s disease with 8, 8, and 6 interactions in the same order. The mechanism of action on cellular components, biological processes, and molecular functions was determined by gene enrichment analysis. A biological pathway comparison revealed 13 shared pathways between the identified genes and Alzheimer protein genes (beta-amyloid band tau proteins). The suggested extract’s anti-Alzheimer potential in silico screening was confirmed through in vivo investigation in regressing the neurodegenerative features of Alzheimer’s dementia in an aluminum-intoxicated rat model (protective and therapeutic effects, 100 mg/kg b.w.). In vivo results suggested that OEP extract significantly improved Alzheimer’s rats, which was indicated by the crude extract’s ability to improve T-maze performance; lower elevated serum levels of AChE, AB peptide, and Ph/T ratio; and normalize the reduced level of TAC during the study. The results presented in this study may provide potential dietary supplements for the management of Alzheimer’s disease