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https://www.selleckchem.com/Androgen-Receptor.html 16 mg/mL, with a correlation coefficient of 0.9998. A rational approach could be to determine the minimum inhibitory concentrations of the most active 1, 3, 9, 25, 50, and > 50% of a large number of plant extracts investigated against these six important microbial pathogens. Starting with an extract concentration of 10 mg/mL, I propose the following classification based on minimum inhibitory concentrations OUTSTANDING ACTIVITY  0.32 mg/mL. Higher minimum inhibitory concentrations may still be effective in ethnopharmacological studies.The growing use of herbal medicines worldwide requires ensuring their quality, safety, and efficiency to consumers and patients. Quality controls of vegetal extracts are usually undertaken according to pharmacopeial monographs. Analyses may range from simple chemical experiments to more sophisticated but more accurate methods. Nowadays, metabolomic analyses allow a fast characterization of complex mixtures. In the field, besides mass spectrometry (MS), nuclear magnetic resonance spectroscopy (NMR) has gained importance in the direct identification of natural products in complex herbal extracts. For a decade, automated dereplication processes based on 13C-NMR have been emerging to efficiently identify known major compounds in mixtures. Though less sensitive than MS, 13C-NMR has the advantage of being appropriate to discriminate stereoisomers. Since NMR spectrometers nowadays provide useful datasets in a reasonable time frame, we have recently made available MixONat, a software that processes 13C as well as distortionless enhancement by polarization transfer (DEPT)-135 and -90 data, allowing carbon multiplicity (i.e., CH3, CH2, CH, and C) filtering as a critical step. MixONat requires experimental or predicted chemical shifts (δ C) databases and displays interactive results that can be refined based on the user's phytochemical knowledge. The present article provides step-by-step instructi

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