Mycotoxins are toxic substances naturally produced by various fungi, and these compounds not only inflict economic damage, but also pose risks to human and animal health. The goal of the present study was to optimize the QuEChERS-based extraction and liquid chromatography–tandem mass spectrometry (LC–MS/MS) method for the analysis of 11 mycotoxins, such as aflatoxins (AFs), ochratoxin A (OTA), fumonisins (FBs), T-2 toxin, HT-2 toxin, zearalenone (ZEN), and deoxynivalenol (DON), commonly found in feed. The QuEChERS method, characterized by being “quick, easy, cheap, effective, rugged, and safe”, has become one of the most common extractions and clean-up procedures for mycotoxin analyses in food. Therefore, in this experiment, an optimal method for the analysis of 11 mycotoxins in feed was established by modifying the general QuEChERS method. In this process, it was confirmed that even if feed samples of different weights were extracted, the quantitative value of mycotoxins in the feed was not affected. To reduce matrix effects, 13C-labeled compounds and deuterium were used as internal standards. This optimized method was then applied in the determination of 11 mycotoxins in 736 feed ingredients and compound feeds obtained from South Korea. The results showed that the occurrence rates of FBs, ZEN, and DON were 59.4%, 38.0%, and 32.1%, respectively, and OTA, AFs, and T-2 toxin and HT-2 toxin were found in fewer than 1% of the 736 feeds. The mean concentration ranges of FBs, ZEN, and DON were 757–2387, 44–4552, and 248–9680 μg/kg, respectively. Among the samples in which DON and ZEN were detected, 10 and 12 samples exceeded the management recommendation standards presented by the Ministry of Agriculture, Food and Rural Affairs (MAFRA). However, when the detected concentrations of DON and ZEN were compared with guideline levels in foreign countries, such as the US, Japan, China, and the EU, the number of positive samples changed. In addition, the co-occurrence of mycotoxins in the feed was analyzed, and the results showed that 43.8% of the samples were contaminated with two or three mycotoxins, among which the co-occurrence rate of FBs, ZEN, and DON was the highest. In conclusion, these results suggest the need for stricter management standards for FBs, DON, and ZEN in South Korea, and emphasize the importance of the continuous monitoring of feeds.

Schisandra chinensis has been widely used as a traditional herbal medicine to treat chronic coughs, fatigue, night sweats, and insomnia. Numerous bioactive components including lignans have been identified in this plant. Lignans with a dibenzocyclooctadiene moiety have been known to possess anti-cancer, anti-inflammatory, and hepatoprotective activity. Fragmentary studies have reported the ability of some lignans to modulate some cytochrome P450 (P450) enzymes. Herein, we investigated the drug interaction potential of six dibenzocyclooctadiene lignans (schisandrin, gomisin A, B, C, and N, and wuweizisu C) on nine P450 enzymes (CYP1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, and 3A) and six uridine 5′-diphosphoglucuronosyl transferase (UGT) enzymes (UGT1A1, 1A3, 1A4, 1A6, 1A9, and 2B7) using human liver microsomes. We found that lignans with one or two methylenedioxyphenyl groups inhibited CYP2B6, CYP2C8, CYP2C9, CYP2C19, and CYP2E1 activities in a time- and concentration-dependent like their CYP3A inhibition. In comparison, these lignans do not induce time-dependent inhibition of CYP1A2, CYP2A6, and CYP2D6. The time-dependent inhibition of gomisin A against CYP2C8, CYP2C19, and CYP3A4 was also elucidated using glutathione as a trapping reagent of reactive carbene metabolites given that gomisin A strongly inhibits these P450 enzymes in a time-dependent manner. A glutathione conjugate of gomisin A was generated in reactions with human recombinant CYP2C8, CYP2C19, and CYP3A4. This suggests that the time-dependent inhibition of gomisin A against CYP2C8, CYP2C9, and CYP3A4 is due to the production of carbene reactive metabolite. Six of the lignans we tested inhibited the activities of six UGT to a limited extent (IC₅₀ > 15 μM). This information may aid the prediction of possible drug interactions between Schisandra lignans and any co-administered drugs which are mainly metabolized by P450s.

A method was developed for the rapid and quantitative analysis of 30 veterinary drugs belonging to 17 classes (amphenicols (1), anthelmintics (1), cephalosporins (4), coccidiostats (1), lincosamides (1), macrolide (1), nitroimidazole (1), penicillins (3), phenylhydrazines (1), polypeptides (1), pyrethrins (1), quinolones (5), sulfonamides (3), tetracycline (3), neuroleptic agents (1), triazene trypanocidal agents (1), other. (1)) in feeds. The proposed method with a modified Quick Polar Pesticides (QuPPe) sample preparation was validated for the determination of 30 veterinary drugs in feed samples by liquid chromatography triple-quadrupole mass spectrometry (LC–MS/MS). The sample was extracted with methanol containing 1% acetic acid and purified by dispersive solid-phase extraction (d-SPE) with C18. Good linearity (r² ≥ 0.98) was observed, and the LOQ values ranged from 10 to 200 µg/kg. Average recoveries ranged from 70.8 to 118.4%, and the relative standard deviation was ≤ 18.7%. This validated method was used in the determination of 30 veterinary drugs in 142 feed samples obtained from South Korea. The results show that lincomycin was present in only one of the tested feed samples, although it was detected at a value lower than the LOQ. In conclusion, this multi-residue method can be used for screening through the detection and quantitation of residual multiclass veterinary drugs in feed samples.

The stereoselectivity of the food drug inhibition potential of resveratrol on cytochrome P450s and uridine 5′-diphosphoglucuronosyl transferases was investigated in human liver microsomes. Resveratrol enantiomers showed stereoselective inhibition of CYP2C9, CYP3A, and UGT1A1. The inhibitions of CYP1A2, CYP2B6, and CYP2C19 by resveratrol were stereo-nonselective. The estimated K_i values determined for CYP1A2 were 13.8 and 9.2 μM for trans- and cis-resveratrol, respectively. Trans-resveratrol noncompetitively inhibited CYP3A and UGT1A1 activities with K_i values of 23.8 and 27.4 μM, respectively. Trans-resveratrol inhibited CYP1A2, CYP2C19, CYP2E1, and CYP3A in a time-dependent manner with K_i shift values >2.0, while cis-resveratrol time-dependently inhibited CYP2C19 and CYP2E1. The time-dependent inhibition of trans-resveratrol against CYP3A4, CYP2E1, CYP2C19, and CYP1A2 was elucidated using glutathione as a trapping reagent. This information helped the prediction of food drug interaction potentials between resveratrol and co-administered drugs which are mainly metabolized by UGT1A1, CYP1A2, CYP2C19, CYP2E1, and CYP3A.

Donepezil is a reversible acetylcholinesterase inhibitor that is currently the most commonly prescribed drug for the treatment of Alzheimer’s disease. In general, donepezil is known as a safe and well-tolerated drug, and it was not associated with liver abnormalities in several clinical trials. However, rare cases of drug-related liver toxicity have been reported since it has become commercially available. Few studies have investigated the metabolic profile of donepezil, and the mechanism of liver damage caused by donepezil has not been elucidated. In this study, the in vitro metabolism of donepezil was investigated using liquid chromatography–tandem mass spectrometry based on a non-targeted metabolomics approach. To identify metabolites, the data were subjected to multivariate data analysis and molecular networking. A total of 21 donepezil metabolites (17 in human liver microsomes, 21 in mice liver microsomes, and 17 in rat liver microsomes) were detected including 14 newly identified metabolites. One potential reactive metabolite was identified in rat liver microsomal incubation samples. Metabolites were formed through four major metabolic pathways: (1) O-demethylation, (2) hydroxylation, (3) N-oxidation, and (4) N-debenzylation. This study indicates that a non-targeted metabolomics approach combined with molecular networking is a reliable tool to identify and detect unknown drug metabolites.