Novel strategy for the determination of illegal adulterants in health foods and herbal medicines using high-performance liquid chromatography with high-resolution mass spectrometry

Lodenafil

Lodenafil is a class of drugs called an inhibitor of PDE5 which also include a wide range of other erectile medicines, such as sildenafil, tadalafil and vardenafil. It is part of a new generation of PDE5 inhibitors that includes udenafil and avanafil. Lodenafil is a prodrug manufactured in the form of lodenafil carbonate, the carbonate dimer that divides in the body into two active drug lodenafil molecules. The oral bioavailability of this formulation is higher than that of the parent drug. This article discusses, by a critical comprehensive review of the literature on lodenafil in terms of its description, names, formulae, elemental composition, appearance, and therapeutic uses. The article also discusses the methods for preparation of lodenafil, its physical-chemical properties, analytical methods for its determination, pharmacological-toxicological properties, and dosing information.

Novel synthesized attapulgite nanoparticles-based hydrophobic monolithic column for in-tube solid-phase microextraction of thiosildenafil, pseudovardenafil, and norneosildenafil in functional foods

In this study, a novel method which involved in-tube solid-phase microextraction (SPME) using an attapulgite (ATP) nanoparticles-based hydrophobic monolithic column was successfully developed. It was coupled with high-performance liquid chromatography-ultraviolet detection for the determination of three phosphodiesterase-5 (PDE-5) inhibitors, including thiosildenafil, pseudovardenafil, and norneosildenafil, in functional foods. The monolithic column was prepared by one-step polymerization, using 3-trimethoxysilylpropyl methacrylate-modified ATP nanoparticles and 1-butyl-3-vinylimidazolium bromide (VBIMBr) as the functional monomers, and ethylene glycol dimethacrylate (EDMA) as the cross-linker. The obtained poly(ATP-VBIMBr-EDMA) monolith was characterized by scanning electron microscopy equipped with energy-dispersive analysis of X-ray, Fourier transform infrared spectroscopy, thermogravimetric analysis, and X-ray diffraction. The adsorption capacity, up to 2.00 μg/cm calculated by the Langmuir isotherm model, was about six times that of the poly(VBIMBr-EDMA) monolith. Crucial factors affecting the extraction efficiency, including sample solvent, elution solvent, flow rates of sampling loading and elution, sample loading volume, and elution volume, were investigated in details. Under the optimal in-tube SPME conditions, the proposed method showed good reproducibility with run-to-run, column-to-column, and batch-to-batch relative standard deviations less than 7.2%, and low limits of detection of 0.5-0.9 ng/mL in real samples. Thiosildenafil was detected in four types of functional foods with the contents of 1.30-4.78 μg/g. This newly proposed in-tube SPME method based on poly(ATP-VBIMBr-EDMA) monolith may provide a simple, efficient, and promising alternative to daily monitoring of PDE-5 inhibitors in functional foods.

Using fragmentation trees and mass spectral trees for identifying unknown compounds in metabolomics

Identification of unknown metabolites is the bottleneck in advancing metabolomics, leaving interpretation of metabolomics results ambiguous. The chemical diversity of metabolism is vast, making structure identification arduous and time consuming. Currently, comprehensive analysis of mass spectra in metabolomics is limited to library matching, but tandem mass spectral libraries are small compared to the large number of compounds found in the biosphere, including xenobiotics. Resolving this bottleneck requires richer data acquisition and better computational tools. Multi-stage mass spectrometry (MSn) trees show promise to aid in this regard. Fragmentation trees explore the fragmentation process, generate fragmentation rules and aid in sub-structure identification, while mass spectral trees delineate the dependencies in multi-stage MS of collision-induced dissociations. This review covers advancements over the past 10 years as a tool for metabolite identification, including algorithms, software and databases used to build and to implement fragmentation trees and mass spectral annotations.