A Composition Analysis and an Antibacterial Activity Mechanism Exploration of Essential Oil Obtained from Artemisia giraldii Pamp

The goal of this work was to use the GC-MS technique to explore the chemical components of Artemisia giraldii Pamp essential oil (AgEo) and to uncover its antibacterial activity, specifically the antibacterial mechanism of this essential oil. There were a total of 63 chemical constituents in the AgEo, monoterpenes (10.2%) and sesquiterpenes (30.14%) were found to be the most common chemical components, with camphor (15.68%) coming in first, followed by germacrene D. (15.29%). AgEo displayed significant reducing power and good scavenging ability on hydroxyl radicals, 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radicals, and 2,2′-Azinobis-(3-ethylbenzthiazoline-6-sulphonate (ABTS) radicals, according to antioxidant data. The diameter of the inhibition zone (DIZ) of AgEo against S. aureus and E. coli was (14.00 ± 1.00) mm and (16.33 ± 1.53) mm, respectively; the minimum inhibitory concentration (MIC) of AgEo against E. coli and S. aureus was 3 μL/mL and 6 μL/mL, respectively; and the minimum bactericidal concentration (MBC) of AgEo against E. coli and S. aureus was 6 μL/mL and 12 μL/mL, respectively. The antibacterial curve revealed that 0.5MIC of AgEo may delay bacterial growth while 2MIC of AgEo could totally suppress bacterial growth. The relative conductivity, alkaline phosphatase (AKP) activity, and protein concentration of the bacterial suspension were all higher after the AgEo treatment than in the control group, and increased as the essential oil concentration was raised. In addition, the cell membrane ruptured and atrophy occurred. The study discovered that AgEo is high in active chemicals and can be used as an antibacterial agent against E. coli and S. aureus, which is critical for AgEo’s future research and development.     

Effects of Extraction Methods on the Bioactivities and Nutritional Value of Virginia and Valencia-Type Peanut Oil

This study aimed to evaluate the effects of peanut varieties cultivated in Morocco (Virginia and Valencia) and extraction methods (cold press, CP; Soxhlet, Sox and maceration, and Mac) on the fatty acid profile, phytosterol, and tocopherol contents, quality characteristics, and antioxidant potential of peanut seed oil. The DPPH method was used to determine the antioxidant activity of the oils. The results revealed that fatty acid content was slightly affected by the extraction technique. However, the CP method was shown to be an excellent approach for extracting oil with desirable quality features compared to the Sox and Mac methods. Furthermore, the peanut oil extracted via CP carried a higher amount of bioactive compounds and exhibited remarkable antioxidant activities. The findings also revealed higher oleic acid levels from the Virginia oil, ranging from 56.46% to 56.99%. Besides, a higher total phytosterol and tocopherol content and DPPH scavenging capacity were obtained from the Valencia oil. Analyzing the study, it can be inferred that extraction method and variety both affect the composition of the peanut oil’s bioactive compounds and antioxidant activity. This information is relevant for extracting peanut oil with a greater level of compounds of industrial interest.     

Grafting of Anionic Decahydro-Closo-Decaborate Clusters on Keggin and Dawson-Type Polyoxometalates: Syntheses,Studies in Solution,DFT Calculations and Electrochemical Properties

Herein we report the synthesis of a new class of compounds associating Keggin and Dawson-type Polyoxometalates (POMs) with a derivative of the anionic decahydro-closo-decaborate cluster [B₁₀H₁₀]²⁻ through aminopropylsilyl ligand (APTES) acting as both a linker and a spacer between the two negatively charged species. Three new adducts were isolated and fully characterized by various NMR techniques and MALDI-TOF mass spectrometry, notably revealing the isolation of an unprecedented monofunctionalized SiW₁₀ derivative stabilized through intramolecular H-H dihydrogen contacts. DFT as well as electrochemical studies allowed studying the electronic effect of grafting the decaborate cluster on the POM moiety and its consequences on the hydrogen evolution reaction (HER) properties.     

Chemical Composition of Tagetes patula Flowers Essential Oil and Hepato-Therapeutic Effect against Carbon Tetrachloride-Induced Toxicity (In-Vivo)

The liver is a crucial organ among body organs due to its wide functions, in particular, detoxification and metabolism. Exposure to detrimental chemicals or viral infections may provoke liver dysfunction and ultimately induce liver tissue damage. Finding natural substances for liver disease treatment to overcome the conventional treatments’ side effects has attracted the attention of researchers worldwide. Our current work was conducted to investigate the hepato-therapeutic activities of essential oil (EO) isolated from Tagetes patula flowers. EO was extracted using the hydro-distillation (HD) technique and its chemical composition was identified by GC/MS. Then, the hepatic treatment potential of extracted EO was evaluated in vivo against CCL₄ in rats. HD of T. patula flowers yielded highly chemical constituents of EO along with significant antioxidant potential. A coherent molecular network was fashioned via the Global Natural Products Social Molecular Networking (GNPS) to visualize the essential components and revealed that the sesquiterpene (E)-β-caryophyllene was the most predominant volatile constituent which accounted for 24.1%. The treatment of CCL₄ led to significant induced oxidative stress markers malonaldehyde, total protein, and non-protein sulfhydryl, as well as elevated serum aminotransferase, gamma-glutamyl transferase, alkaline phosphatase, and bilirubin. In addition, it disrupted the level of lipid profile. The post-treatment using T. patula EO succeeded in relieving all toxic effects of CCl₄ and recuperating the histopathological signs induced by CCL₄. Silymarin was used as a standard hepatoprotective agent. The obtained results demonstrated that the extracted EO exerted high protective activities against the toxicity of CCL₄. Moreover, the T. patula flowers EO can be used as a natural remedy to relieve many contemporary liver diseases related to oxidative stress.     

Mechanistic Insights into the Ameliorative Effect of Cichoriin on Diabetic Rats—Assisted with an In Silico Approach

Type 2 diabetes mellitus is considered to be a substantial socioeconomic burden worldwide on both patients and governments. Coumarins are biomolecules with a diversity of biological activities. The current investigation aimed to explore the ameliorative effects of cichoriin, which is a type of coumarin, on high-fat diet/streptozotocin (HFD/STZ)-induced diabetic rats. Methods: Rats were allocated into five groups. Group I was considered as the control group, while the other groups were HFD/STZ-induced diabetic rats. Group II was assigned as the diabetic control. Groups III and IV were treated with cichoriin (50 or 100 mg/kg, respectively). Group V received glibenclamide (5 mg/kg) (as a positive control). The blood glucose (BG), serum insulin, triglycerides (TG), total cholesterol (TC), total antioxidant capacity (TAC), catalase, hepatic superoxide dismutase (SOD) and content of malondialdehyde (MDA) were assessed. Histopathological and immunohistochemistry analysis of pancreatic tissue were performed. mRNA and protein expressions of GLUT4, AMPK, and PI3K were estimated. Results: Cichoriin treatment ameliorated HFD/STZ-induced diabetic conditions and mitigated the histopathological characteristics of the pancreas, as well as increasing pancreatic insulin expression. This decreased the levels of BG, TG, TC, and MDA and improved the TAC, catalase and SOD contents. Cichoriin demonstrated upregulation of mRNA and protein expressions of GLUT4, AMPK, and PI3K. The in silico binding of cichoriin with GLUT4, AMPK, and PI3K supported the possible current activities. Conclusion: Collectively, this work highlighted the potential role of cichoriin in mitigating HFD/STZ-induced diabetic conditions and showed it to be a valuable product.     

Quantitative Analysis of Solar Photovoltaic Panel Performance with Size-Varied Dust Pollutants Deposition Using Different Machine Learning Approaches

In this paper, the impact of dust deposition on solar photovoltaic (PV) panels was examined, using experimental and machine learning (ML) approaches for different sizes of dust pollutants. The experimental investigation was performed using five different sizes of dust pollutants with a deposition density of 33.48 g/m² on the panel surface. It has been noted that the zero-resistance current of the PV panel is reduced by up to 49.01% due to the presence of small-size particles and 15.68% for large-size (ranging from 600 µ to 850 µ). In addition, a significant reduction of nearly 40% in sunlight penetration into the PV panel surface was observed due to the deposition of a smaller size of dust pollutants compared to the larger size. Subsequently, different ML regression models, namely support vector machine (SVMR), multiple linear (MLR) and Gaussian (GR), were considered and compared to predict the output power of solar PV panels under the varied size of dust deposition. The outcomes of the ML approach showed that the SVMR algorithms provide optimal performance with MAE, MSE and R² values of 0.1589, 0.0328 and 0.9919, respectively; while GR had the worst performance. The predicted output power values are in good agreement with the experimental values, showing that the proposed ML approaches are suitable for predicting the output power in any harsh and dusty environment.     

Curcumin and Its Derivatives Induce Apoptosis in Human Cancer Cells by Mobilizing and Redox Cycling Genomic Copper Ions

Turmeric spice contains curcuminoids, which are polyphenolic compounds found in the Curcuma longa plant’s rhizome. This class of molecules includes curcumin, demethoxycurcumin, and bisdemethoxycurcumin. Using prostate cancer cell lines PC3, LNCaP, DU145, and C42B, we show that curcuminoids inhibit cell proliferation (measured by MTT assay) and induce apoptosis-like cell death (measured by DNA/histone ELISA). A copper chelator (neocuproine) and reactive oxygen species scavengers (thiourea for hydroxyl radical, superoxide dismutase for superoxide anion, and catalase for hydrogen peroxide) significantly inhibit this reaction, thus demonstrating that intracellular copper reacts with curcuminoids in cancer cells to cause DNA damage via ROS generation. We further show that copper-supplemented media sensitize normal breast epithelial cells (MCF-10A) to curcumin-mediated growth inhibition, as determined by decreased cell proliferation. Copper supplementation results in increased expression of copper transporters CTR1 and ATP7A in MCF-10A cells, which is attenuated by the addition of curcumin in the medium. We propose that the copper-mediated, ROS-induced mechanism of selective cell death of cancer cells may in part explain the anticancer effects of curcuminoids.     

Solubility Optimization of Loxoprofen as a Nonsteroidal Anti-Inflammatory Drug: Statistical Modeling and Optimization

Industrial-based application of supercritical CO₂ (SCCO₂) has emerged as a promising technology in numerous scientific fields due to offering brilliant advantages, such as simplicity of application, eco-friendliness, and high performance. Loxoprofen sodium (chemical formula C₁₅H₁₈O₃) is known as an efficient nonsteroidal anti-inflammatory drug (NSAID), which has been long propounded as an effective alleviator for various painful disorders like musculoskeletal conditions. Although experimental research plays an important role in obtaining drug solubility in SCCO₂, the emergence of operational disadvantages such as high cost and long-time process duration has motivated the researchers to develop mathematical models based on artificial intelligence (AI) to predict this important parameter. Three distinct models have been used on the data in this work, all of which were based on decision trees: K-nearest neighbors (KNN), NU support vector machine (NU-SVR), and Gaussian process regression (GPR). The data set has two input characteristics, P (pressure) and T (temperature), and a single output, Y = solubility. After implementing and fine-tuning to the hyperparameters of these ensemble models, their performance has been evaluated using a variety of measures. The R-squared scores of all three models are greater than 0.9, however, the RMSE error rates are 1.879 × 10⁻⁴, 7.814 × 10⁻⁵, and 1.664 × 10⁻⁴ for the KNN, NU-SVR, and GPR models, respectively. MAE metrics of 1.116 × 10⁻⁴, 6.197 × 10⁻⁵, and 8.777 × 10⁻⁵errors were also discovered for the KNN, NU-SVR, and GPR models, respectively. A study was also carried out to determine the best quantity of solubility, which can be referred to as the (x₁ = 40.0, x₂ = 338.0, Y = 1.27 × 10⁻³) vector.     

Optimized Green Extraction of Polyphenols from Cassia javanica L. Petals for Their Application in Sunflower Oil: Anticancer and Antioxidant Properties

The total phenolic content (TPC) from Cassia javanica L. petals were extracted using ethanolic solvent extraction at concentrations ranging from 0 to 90% and an SCF-CO₂ co-solvent at various pressures. Ultrasound-assisted extraction parameters were optimized using response surface methodology (RSM). Antioxidant and anticancer properties of total phenols were assessed. An SCF-CO₂ co-solvent extract was nano-encapsulated and applied to sunflower oil without the addition of an antioxidant. The results indicated that the best treatment for retaining TPC and total flavonoids content (TFC) was SCF-CO₂ co-solvent followed by the ultrasound and ethanolic extraction procedures. Additionally, the best antioxidant activity by β-carotene/linoleic acid and DPPH free radical-scavenging test systems was observed by SCF-CO₂ co-solvent then ultrasound and ethanolic extraction methods. SCF-CO₂ co-solvent recorded the highest inhibition % for PC3 (76.20%) and MCF7 (98.70%) and the lowest IC₅₀ value for PC3 (145 µ/mL) and MCF7 (96 µ/mL). It was discovered that fortifying sunflower oil with SCF-CO₂ co-solvent nanoparticles had a beneficial effect on free fatty acids and peroxide levels. The SCF-CO₂ method was finally found to be superior and could be used in large-scale processing.     

Oil-in-Water Nanoemulsion Can Modulate the Fermentation,Fatty Acid Accumulation,and the Microbial Population in Rumen Batch Cultures

In this study, three oil-in-water nanoemulsions were tested in two stages: In the first stage, three levels (on the substrate dry matter (DM)), namely 3%, 6%, and 9%, of three different oils, olive oil (OO), corn oil (CO), and linseed oil (LO), in raw and nanoemulsified (N) forms were used separately in three consecutive rumen batch cultures trials. The second stage, which was based on the first stage’s results, consisted of a batch culture trial that compared the raw and nanoemulsified (N) forms of all three oils together, provided at 3% of the DM. In the first stage, NOO, NCO, and NLO preserved higher unsaturated fatty acid (UFA) and less saturated fatty acid (SFA) compared to OO, CO, and LO, respectively; noticeably, NCO had UFA:SFA = 1.01, 1.16, and 1.34 compared to CO, which had UFA:SFA = 0.66, 0.69, and 0.72 when supplemented at 3%, 6%, 9% of DM, respectively. In the second stage, UFA:SFA = 1.04, 1.12, and 1.07 for NOO, NCO, NLO, as compared to UFA:SFA = 0.69, 0.68, and 0.72 for OO, CO, and LO supplemented at 3% of DM. In conclusion, oil-in-water nanoemulsions showed an ability to decrease the transformation of UFA to SFA in the biohydrogenation environment without affecting the rumen microorganisms.