Phytochemicals and antimicrobial properties of Thai edible plant extracts and their prebiotic-like effects

In this study, the phytochemicals and antimicrobial activities of ethanolic extracts of Thai edible plants, green tea, red cotton tree flower, fingerroot and ginger were evaluated. The plant extracts were taken for evaluation of antimicrobial activities against Cutibacterium acnes DMST 14916, Staphylococcus epidermidis TISTR 518, and Staphylococcus aureus TISTR 746. The minimum inhibitory concentrations (MICs) of green tea, fingerroot, and ginger extracts against C. acnes DMST 14916 were 3.92, 0.49, and 7.85 mg cm-3, respectively and the minimum bacteriostatic concentrations (MBCs) were 3.92, 0.49, and 7.85 mg cm-3, respectively. The MICs and MBCs of fingerroot extract against S. epidermidis TISTR 518 were 0.12 and 0.49 mg cm-3, respectively, while those against S. aureus TISTR 746 were 0.12 and 0.98 mg cm-3, respectively. Red cotton tree flower extract showed no antimicrobial activity against the acne-causing bacteria. By scanning electron microscopy (SEM) evaluation, the bacterial cells treated with the plant extracts revealed visible shrinkages compared to the smooth cell surfaces of the controls. The phytochemicals in the plant extracts were analysed by liquid chromatography with tandem mass spectrometry (LC-MS/MS). Well-known antimicrobial compounds like azelaic acid, embelin and kaempferol 3-rutinoside-4’-glucoside were identified in all extracts. The cytotoxic effects of the plant extracts on human cell lines were further investigated. The green tea extract was slightly toxic to HaCaT cells found at the initial concentration of 62.5 mg cm-3, but not toxic to MRC-5 cells. The fingerroot and ginger extracts had no cytotoxicity on HaCaT cells, but promoted the MRC-5 cell proliferation. The combination effects of the plant extracts were prebiotic-like and indifferent effects. Regarding all results, the ethanolic extracts of green tea, fingerroot, and ginger could be used individually as natural anti-acne ingredients capable of further product development to improve human skin health

Progress in the analysis of phytocannabinoids by HPLC and UPLC (or UHPLC) during 2020-2023

Introduction: Organic molecules that bind to cannabinoid receptors are known as cannabinoids. These molecules possess pharmacological properties similar to those produced by Cannabis sativa L. High-performance liquid chromatography (HPLC) and ultra-performance liquid chromatography (UPLC, also known as ultra-high-performance liquid chromatography, UHPLC) have become the most widely used analytical tools for detection and quantification of phytocannabinoids in various matrices. HPLC and UPLC (or UHPLC) are usually coupled to an ultraviolet (UV), photodiode array (PDA) or mass spectrometric (MS) detector. Objective: To critically appraise the literature on the application of HPLC and UPLC (or UHPLC) methods for the analysis of phytocannabinoids published from January 2020 to December 2023. Methodology: An extensive literature search was conducted using Web of Science, PubMed and Google Scholar, and published materials including relevant books. In various combinations, using cannabinoid in all combinations, cannabis, hemp, hashish, Cannabis sativa, marijuana, analysis, HPLC, UHPLC, UPLC, quantitative, qualitative and quality control were used as the keywords for the literature search. Results: Several HPLC and UPLC (or UHPLC)-based methods for the analysis of phytocannabinoids were reported. While simple HPLC-UV or HPLC-PDA-based methods were common, the use of HPLC-MS, HPLC-MS/MS, UPLC (or UHPLC)-PDA, UPLC (or UHPLC)-MS and UPLC (or UHPLC)MS/MS, was also reported. Applications of mathematical and computational models for optimization of protocols were noted. Pre-analyses included various environmentally friendly extraction protocols. Conclusion: During the last four years, HPLC and UPLC (or UHPLC) remained the main analytical tools for phytocannabinoid analysis in different matrices

A quantitative estimation of the global translational activity in logarithmically growing yeast cells.

BACKGROUND: Translation of messenger mRNAs makes significant contributions to the control of gene expression in all eukaryotes. Because translational control often involves fractional changes in translational activity, good quantitative descriptions of translational activity will be required to achieve a comprehensive understanding of this aspect of biology. Data on translational activity are difficult to generate experimentally under physiological conditions, however, translational activity as a parameter is in principle accessible through published genome-wide datasets. RESULTS: An examination of the accuracy of genome-wide expression datasets generated for Saccharomyces cerevisiae shows that the available datasets suffer from large random errors within studies as well as systematic shifts in reported values between studies, which make predictions of translational activity at the level of individual genes relatively inaccurate. In contrast, predictions of cell-wide translational activity are possible from such datasets with higher accuracy, and current datasets predict a production rate of about 13,000 proteins per haploid cell per second under fast growth conditions. This prediction is shown to be consistent with independently derived kinetic information on nucleotide exchange reactions that occur during translation, and on the ribosomal content of yeast cells. CONCLUSIONS: This study highlights some of the limitations in published genome-wide expression datasets, but also demonstrates a novel use for such datasets in examining global properties of cells. The global translational activity of yeast cells predicted in this study is a useful benchmark against which biochemical data on individual translation factor activities can be interpreted