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Potential of methanol extracts of Nephelium lappaceum (Sapindaceae) and Hyphaene thebaica (Arecaceae) as adjuvants to enhance the efficacy of antibiotics against critical class priority bacteria
Botanicals have shown promise in mitigating antibiotic resistance in bacteria. This study examined the efficacy of methanolic extracts from two food plants (Nephelium lappaceum and Hyphaene thebaica), alone and in combination with antibiotics, against critical class priority bacteria, including multi-drug resistant (MDR) strains and clinical isolates of Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, Enterobacter aerogenes, and Escherichia coli. The herbals underwent testing using a 96-well microplate serial dilution technique before being analyzed for their effects on bacterial cell membrane integrity and H+-ATPase-mediated proton pumping. Phytochemical analysis was carried out using established techniques. The bioactive extracts displayed very good to weak antibacterial activities (128 ≤ MIC ≤ 2048 μg/mL). The bark, leaf, and peel extracts of N. lappaceum were found to be effective against all studied MDR bacteria. N. lappaceum leaf extract exhibited the best activity (128 ≤ MIC ≤ 1024 μg/mL on all studied MDR bacteria). Interestingly, all MBC/MIC ratios calculated were ≤ 4, suggesting bactericidal activities. N. lappaceum leaf extract has shown significant inhibition of bacterial H+-ATPase-mediated proton pumping and changes in the cell membrane integrity, suggesting possible modes of action. N. lappaceum (leaves and peels) and H. thebaica (fruits) extracts demonstrated a notable potential to synergize with tetracycline, vancomycin, imipenem, ciprofloxacin, and cefixime (up to 8-fold reduction of the antibiotic’s MIC was recorded). N. lappaceum leaves and peels, and fruits of H. thebaica significantly improved the efficacy of all antibiotics tested against K. pneumoniae ATCC11296 at MIC/2. Similar effects were observed against P. aeruginosa PA01 and E. coli AG100, respectively, with leaves and peels of N. lappaceum. No antagonistic interactions were recorded. Qualitative phytochemical screening revealed the presence of tannins, phenols, and saponins in all test extracts. The findings of this study are promising and suggest that N. lappaceum and H. thebaica can be used either for direct action on bacteria or to revitalize outdated antibiotics that are gradually losing their potency due to resistance.
Quinalizarin induces autophagy, apoptosis and mitotic catastrophe in cervical and prostate cancer cells
Multi spectroscopic investigation of maisine-based microemulsions as convenient carriers for co-delivery of anticancer and anti-inflammatory drugs
Abstract Lipid-based drug delivery systems are very promising in addressing critical medical needs associated with cancer because they are able to enhance the efficacy of the therapeutic agents loaded in. Yet, their transferability from bench to bedside is still a challenge as it hits many barriers. Among them, the absence of a clear design made on the deeper understanding of the intermolecular forces underlying the formation of the drug-carrier system and the controlled release of the drug is relevant. In this contribution, we rationally designed and prepared lipid-based formulations of an anticancer drug, fluorouracil (FU - hydrophilic) and an anti-inflammatory drug, ibuprofen (IBU - hydrophobic) to thoroughly characterize the specific intermolecular interactions between drugs and components of the carrier matrix. Microemulsions (ME) were selected as the main carriers for this study, but a comparison with liposomes was performed to observe if different organization of the lipophilic and hydrophilic compartments influences the loading capacity and controlled release of these two drugs. Using Maisine CC, a biocompatible oil, and Tween 20 as the surfactant, normal oil-in-water ME loaded with FU and IBU (1:1, 1:3, 1:6, wt:wt) were prepared by the water titration method. MEs were characterized by DLS, Zeta potential, and DOSY spectroscopies to assess their droplet size, surface charge, structure and type of emulsion. Intermolecular interactions between drugs and components of the ME’s matrix were investigated by FT-IR, RAMAN and 1H-NMR spectroscopies. The experimental results of DOSY revealed that all components of MEs are gathered in normal oil-in-water ME. Due to their different affinities for the main components of the ME, FU, and IBU were mainly distributed in the aqueous and oily phases, respectively, as supported by the droplet size measured by DLS. It was observed that co-loading the two drugs impacted the release behavior, assessed by the dialysis bag method, as compared with the mono-drug formulations. Based on the findings of this work, a release mechanism for FU and IBU was proposed, as well. Overall, the ME proved to be more suitable nanocarriers since the drugs, which were loaded in higher amounts as compared to liposomes, followed a controlled and sustained release of at least 96 h.
Application of machine learning approach to estimate the solubility of some solid drugs in supercritical CO2
Global burden of vaccine-associated kidney injury using an international pharmacovigilance database
Experimental and theoretical assessment to investigate the impact of Gast Reg drug on the copper corrosion control in an acidic environment
Abstract Herein, a corrosion inhibitor called the Gast Reg drug (GRD) was used to prevent the copper from corroding. The aggressive solution used in this investigation was HCl acid solution. A mix of electrochemical and quantum investigations are used to assess GRD’s anti-corrosion properties. It has been discovered that the GRD is essential for stopping copper from corroding in a 2 M HCl solution. The study’s results indicated that GRD shown considerable corrosion prevention capabilities for copper in 2 M HCl solution. The inhibitory effectiveness of GRD was seen to rise with higher concentrations of GRD. It is noteworthy that the maximum levels of inhibitory effectiveness (82.1%) for HCl solution were obtained at 123.87 × 10− 5 M. The primary cause of GRD’s anti-corrosion properties is its propensity to adsorb on the surface of copper via its heteroatoms. The inhibitor’s adsorption behavior was described using the Langmuir model. Surface assessments with Energy Dispersive X-ray (EDX), Scanning Electron Microscope (SEM), and Atomic Force Microscope (AFM) demonstrated the development of a prominent adsorbed film on the copper surface. The correlation between molecule structure and its inhibitory effect has been investigated and analyzed using DFT and Monte Carlo simulation. The actual adsorption occurs through a variety of active centers and physical and chemical processes that are coordinated with the calculated quantum parameters. The outcomes gathered from electrochemical, surface, and theoretical studies are well correlated.
Precision Molecular Engineering of Compact Near-Infrared Fluorophores
Research on intrusion detection model based on improved MLP algorithm
Rapid and sustained antidepressant effects of tubastatin A in a mouse model of depression
An efficient and compact mid-infrared polarization splitter and rotator based on a bifurcated tapered-bent waveguide
Prediction and risk assessment of Magantang landslide generated waves in Shuibuya Reservoir, Qingjiang River, China
Spatial Control of CAR T Cell Activation Using Tumor-Homing Polymers
Prospective association of estimated cardiorespiratory fitness and risk of chronic kidney diseases
Study on the bearing performance of extra-long pile group foundation in accumulation slope under landslide effect
"Suspended" Single Rhenium Atoms on Nickel Oxide for Efficient Electrochemical Oxidation of Glucose
Instrumental variable estimation for compositional treatments
Abstract Many scientific datasets are compositional in nature. Important biological examples include species abundances in ecology, cell-type compositions derived from single-cell sequencing data, and amplicon abundance data in microbiome research. Here, we provide a causal view on compositional data in an instrumental variable setting where the composition acts as the cause. First, we crisply articulate potential pitfalls for practitioners regarding the interpretation of compositional causes from the viewpoint of interventions and warn against attributing causal meaning to common summary statistics such as diversity indices in microbiome data analysis. We then advocate for and develop multivariate methods using statistical data transformations and regression techniques that take the special structure of the compositional sample space into account while still yielding scientifically interpretable results. In a comparative analysis on synthetic and real microbiome data we show the advantages and limitations of our proposal. We posit that our analysis provides a useful framework and guidance for valid and informative cause-effect estimation in the context of compositional data.