Cytochrome P450 inhibitory action of Echinacea preparations differs widely and co-varies with alkylamide content

Echinacea preparations are one of the best selling herbal medicinal products with a well established therapeutic use in the prophylaxis of upper respiratory tract infections. Their consumption is increasing, but information about their ability to inhibit cytochrome P450 enzymes (CYP) is fragmentary. The picture is further complicated by a lack of phytochemical characterization of previously tested preparations. Due to its well characterized immunomodulatory activity, the standardized Swiss registered Echinacea purpurea (L.) Moench Echinaforce extract was selected for detailed study. With the single baculovirus-expressed CYP isoforms 1A2, 2C19, 2D9 and 3A4, inhibitory actions were measured by monitoring fluorescent metabolites derived from enzyme substrates (supersome assay). The Echinaforce extract induced mild inhibition of all these isoforms, with CYP 3A4 being the most, and CYP 2D6 the least sensitive enzyme. To assess whether CYP inhibition might be a general feature of Echinacea preparations, an additional nine commercially available preparations were screened using CYP 3A4. All tested preparations were able to inhibit CYP 3A4, but inhibitory potencies (expressed as median inhibitory concentration, IC50) varied by a factor of 150. The alkylamides are thought to be responsible for the immunomodulatory activity of Echinacea, and so the concentration of 2E,4E,8Z,10E/Z-tetranoic acid isobutylamide (1) and total alkylamide content were determined in all preparations, and the latter was found to be associated with their CYP 3A4 inhibitory potency. The chemically pure alkylamides dodeca-2E,4E,8Z,10E/Z-tetranoic acid isobutylamide (1) and dodeca-2E,4E-dieonoic acid isobutylamide (2) showed inhibitory activity on CYP 2C19, 2D6 and 3A4. However, unlike the Echinaforce extract, the alkylamides did not induce CYP 1A2 inhibition. Thus, other, as yet unidentified constituents also contribute to the overall weak inhibitory effects seen with Echinacea preparations in-vitro.

Creating LaTeX documents from within Stata using texdoc

At least since Thomas Piketty's best-selling "Capital in the Twenty-First Century" (2014, Cambridge, MA: The Belknap Press), percentile shares have become a popular approach for analyzing distributional inequalities. In their work on the development of top incomes, Piketty and collaborators typically report top-percentage shares, using varying percentages as thresholds (top 10%, top 1%, top 0.1%, etc.). However, analysis of percentile shares at other positions in the distribution may also be of interest. In this paper I present a new Stata command called pshare that estimates percentile shares from individual-level data and displays the results using histograms or stacked bar charts.

Assessing inequality using percentile shares

At least since Thomas Piketty's best-selling \Capital in the Twenty- First Century" (2014, Cambridge, MA: The Belknap Press), percentile shares have become a popular approach for analyzing distributional inequalities. In their work on the development of top incomes, Piketty and collaborators typically report top- percentage shares, using varying percentages as thresholds (top 10%, top 1%, top 0.1%, etc.). However, analysis of percentile shares at other positions in the distri- bution may also be of interest. In this paper I present a new Stata command called pshare that estimates percentile shares from individual-level data and displays the results using histograms or stacked bar charts.

Assessing inequality using percentile shares

At least since Thomas Piketty's best-selling "Capital in the Twenty-First Century" (2014, Cambridge, MA: The Belknap Press), percentile shares have become a popular approach for analyzing distributional inequalities. In their work on the development of top incomes, Piketty and collaborators typically report top-percentage shares, using varying percentages as thresholds (top 10%, top 1%, top 0.1%, etc.). However, analysis of percentile shares at other positions in the distribution may also be of interest. In this paper I present a new Stata command called -pshare- that estimates percentile shares from individual-level data and displays the results using histograms or stacked bar charts.