Solanum elaeagnifolium Var. Obtusifolium (Dunal) Dunal: Antioxidant,Antibacterial, and Antifungal Activities of Polyphenol-Rich Extracts Chemically Characterized by Use of In Vitro and In Silico Approaches

The present work was designed to study the chemical composition and the antioxidant and antimicrobial properties of fruits (SFr) and leaf (SF) extracts from Solanum elaeagnifolium var. obtusifolium (Dunal) Dunal (S. elaeagnifolium). The chemical composition was determined using HPLC-DAD analysis. Colorimetric methods were used to determine polyphenols and flavonoids. Antioxidant capacity was assessed with DPPH, TAC, and FRAP assays. Antimicrobial activity was assessed using disk diffusion and microdilution assays against two Gram (+) bacteria (Staphylococcus aureus ATCC-6633 and Bacillus subtilis DSM-6333) and two Gram (-) bacteria (Escherichia coli K-12 and Proteus mirabilis ATCC-29906), while the antifungal effect was tested vs. Candida albicans ATCC-1023. By use of in silico studies, the antioxidant and antimicrobial properties of the studied extracts were also investigated. HPLC analysis showed that both fruits and leaf extracts from S. elaeagnifolium were rich in luteolin, quercetin, gallic acid, and naringenin. Both SFr and SF generated good antioxidant activity, with IC₅₀ values of 35.15 ± 6.09 μg/mL and 132.46 ± 11.73 μg/mL, respectively. The EC₅₀ of SFr and SF was 35.15 ± 6.09 μg/mL and 132.46 ± 11.73 μg/mL, respectively. SFr and SF also showed a good total antioxidant capacity of 939.66 ± 5.01 μg AAE/and 890.1 ± 7.76 μg AAE/g, respectively. SFr had important antibacterial activity vs. all tested strains—most notably B. subtilis DSM-6333 and E. coli, with MICs values of 2.5 ± 0.00 mg/mL and 2.50 ± 0.00 mg/mL, respectively. SFr demonstrated potent antifungal activity against C. albicans, with an inhibition diameter of 9.00 ± 0.50 mm and an MIC of 0.31 ± 0.00 mg/mL. The in silico approach showed that all compounds detected in SFr and SF had high activity (between −5.368 and 8.416 kcal/mol) against the receptors studied, including NADPH oxidase, human acetylcholinesterase, and beta-ketoacyl-[acyl carrier protein] synthase.     

Ameliorative Effect of Citrus Lemon Peel Extract and Resveratrol on Premature Ovarian Failure Rat Model: Role of iNOS/Caspase-3 Pathway

Premature ovarian failure (POF) is described as a loss of oocytes and the absence of folliculogenesis and is considered an adverse effect of chemotherapeutic drugs, which leads to infertility. Subsequently, the existing inquiry was achieved by exploring the potential suspicious influences of lemon peel extract (LPE), and resveratrol (RES) on cyclophosphamide (CPA) induced-POF. The results showed that CPA-induced POF significantly decreased serum estradiol (E2) and progesterone levels, along with a considerable rise in serum luteinizing hormone (LH) and follicle-stimulating hormone (FSH) levels. Moreover, CPA administration to rats significantly increased the serum level of Malondialdehyde (MDA) and significantly lowered the levels of reduced glutathione (GSH) and superoxide dismutase (SOD); in addition, it increased nuclear factor kappa B (NF-κB) levels, tumor necrosis factor-α (TNF-α), as well as cyclooxygenase 2 (COX-2) with the spread expression of inducible nitric oxide synthase (iNOS) mRNA levels and caspase-3 (Casp3) levels in ovarian tissues versus the control rats. However, treatment with LPE and RES suppressed the triggering of NF- κB pathways, evidenced by a considerable reduction in Casp3 & iNOS mRNA expression level and significant ameliorative effects in all evaluated parameters, as confirmed by the histological and immunohistochemical investigation when comparing the model group. In overall findings, both lemon peel extract and resveratrol can mitigate the adverse effects of CPA-induced POF. Most crucially, its combination therapy is a promising pharmacological agent for this disease.     

Phytochemical Characterization,Antioxidant and Anti-Inflammatory Effects of Cleome arabica L. Fruits Extract against Formalin Induced Chronic Inflammation in Female Wistar Rat: Biochemical,Histological, and In Silico Studies

In recent decades, the use of herbs and plants has been of great interest, as they have been the sources of natural products, commonly named as bioactive compounds. In specific, the natural compounds from the Capparaceae family which has been proved to have antioxidant, anti-inflammatory, antimicrobial and anti-carcinogenic activities, by several studies. Cleome arabica L. (CA) specie is the most used medicinal plants in Tunisia and elsewhere in North African countries for treatment of various diseases including diabetes, rheumatism, inflammation, cancer, and digestive disorders. The current work was undertaken to estimate the total phenolic, flavonoid and condensed tannin contents, to identify and quantify the polyphenolic compounds, and to evaluate the antioxidant and the anti-inflammatory proprieties of CA fruits extract against formalin induced chronic inflammation in Female Wistar rats. In fact, the antioxidant activity was tested by Diphenyl-1-Picrylhydrazyl free radical scavenging (DPPH), Ferric reducing antioxidant power (FRAP) and Nitric Oxide radical (NO·). Anti-inflammatory effect of fruits extract was examined using formalin (2%) induced paw edema in rats. Molecular docking tools were used to investigate the interaction of some compounds from CA fruits extract with the cyclooxygenase-2 (COX-2) target protein. Our results showed that, the total phenolic, flavonoid and tannins contents, which were assessed by the Folin-Ciocalteu, Quercetin, and Catechin methods, respectively, were 230.22 mg gallic acid equivalent/g dry weight (mg GAE/g DW), 55.08 mg quercetin equivalent/g dry weight (QE/g DW) and 15.17 mg catechin equivalents/g dry weight (CatE/g DW), respectively. HPLC analysis revealed the presence of five polyphenolic compounds whose catechin was found to be the most abundant compounds. The antioxidant activity of extract was quantified by DPPH, FRAP and NO· tests and IC₅₀ reached the values of 3.346 mg/mL, 2.306 and 0.023 mg/mL, respectively. Cleome fruits ameliorated the histological integrity of the skin and alleviated the disruptions in hematological parameters (WBC, LYM, RBC, and HGB), inflammatory cytokines (IL-1β, IL-6, TNF-α), C-reactive protein, and some oxidative stress markers (TBARS (−49%) and AOPP (−42%) levels, SOD (+33%) and GPx (+75%) activities, and GSH (+49%) content) induced by formalin injection. Moreover, the in-silico investigation had shown that CA fruits extract compounds have a stronger interaction with COX-2 active site, more than the reference drug “indomethacin” (two H-bonds). Our research gives pharmacological backing to the healthcare utilization of Cleome plant in the treatment of inflammatory diseases and oxidative harm.     

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.     

Highly Efficient Photocatalysts for Methylene Blue Degradation Based on a Platform of Deposited GO-ZnO Nanoparticles on Polyurethane Foam

The demand for reactive dyes in industries has increased rapidly in recent years, and producing a large quantity of dye-containing effluent waste contaminates soils and water streams. Current efforts to remove these harmful dyes have focused on utilizing functionalized nanomaterials. A 3D polyurethane foam loaded with reduced graphene oxide (rGO) and ZnO nanocomposite (PUF/rGO/ZnO) has been proposed as an efficient structural design for dye degradation under the influence of visible light. The proposed structure was synthesized using a hydrothermal route followed by microwave irradiation. The resultant 3D PUF/rGO/ZnO was examined and characterized by various techniques such as XRD, FTIR, SEM, EDAX, BET, and UV–visible spectroscopy. SEM data illustrated that a good dispersion and embedment of the rGO/ZnO NPs within the PUF matrix occurred. The adsorption capacity for neat PUF showed that around 20% of the Methylene blue (MB) dye was only adsorbed on its surface. However, it was found that an exceptional adsorption capacity for MB degradation was observed when the rGO/ZnO NPs inserted into the PUF, which initially deteriorated to ~ 70 % of its initial concentration. Notably, the MB dye was completely degraded within 3 h.     

Residual and Past Discrete Tsallis and Renyi Extropy with an Application to Softmax Function

In this paper, based on the discrete lifetime distribution, the residual and past of the Tsallis and Renyi extropy are introduced as new measures of information. Moreover, some of their properties and their relation to other measures are discussed. Furthermore, an example of a uniform distribution of the obtained models is given. Moreover, the softmax function can be used as a discrete probability distribution function with a unity sum. Thus, applying those measures to the softmax function for simulated and real data is demonstrated. Besides, for real data, the softmax data are fit to a convenient ARIMA model.     

Design,synthesis, and molecular docking studies of new [1,2,4]triazolo[4,3-a]quinoxaline derivatives as potential A2B receptor antagonists

Molecular Diversity - Many shreds of evidence have recently correlated A2B receptor antagonism with anticancer activity. Hence, the search for an efficient A2B antagonist may help in the...     

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.     

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.