Application of LC-MS/MS and UHPLC-Q-Orbitrap methods for determining 54 steroids in illegal dietary supplements and other sample types

Dissecting the mechanisms of velvet antler extract against diabetic osteoporosis via network pharmacology and proteomics

ETHNOPHARMACOLOGICAL RELEVANCE

Velvet antler (VAE) is a famous traditional Chinese medicine (TCM), which has been used for thousands of years to treat bone-related diseases. Nonetheless, whether VAE has anti-diabetic osteoporosis (DOP) properties remains to be elucidated.

AIM OF THE STUDY

The therapeutic mechanism of VAE on DOP is based on integrated proteomics of network pharmacology strategies to study related targets and pathways.

MATERIALS AND METHODS

Liquid chromatography-mass spectrometry (LC/MS) was used to analyze the main molecular components present in the VAE. The DOP mouse model was created by combining a high-fat diet with streptozotocin (STZ). High glucose (HG) induced MC3T3-E1 cells were used as a cell model to evaluate the therapeutic effect of VAE. The mechanisms of VAE in treating DOP were predicted through proteomics. Molecular docking, molecular dynamics simulations, DARTS and functional experiments were employed to further verify its mechanisms.

RESULTS

Altogether 30 components were identified by LC-MS. In vitro and in vivo results were confirmed that VAE had a protective effect on DOP. Combined with network pharmacology, proteomics and functional experiments revealed that TNF/PI3K-AKT signaling pathway may be the potential biochemical pathway for VAE in treating DOP.

CONCLUSIONS

The innovation of this study was investigating the effectiveness of VAE in treating DOP in vivo and in vitro and suggested that VAE might exert anti-DOP effects through the TNF/PI3K-AKT signaling pathway by network pharmacology and proteomics and found that ATK1 was the core target of VAE, which provided valuable insights for the clinical application of VAE in DOP.

Simultaneous determination of total ergot alkaloids in wheat flour by Orbitrap mass spectrometry

The optimization screening methods for total ergot alkaloids in wheat extracts involve transforming them into a single compound, which is then analyzed via high-resolution Orbitrap mass spectrometry (Orbitrap MS). Orbitrap MS provides highly sensitive and accurate mass measurements, enhancing the selectivity and sensitivity of the analysis. Various hydrolysis and reduction methods have been investigated, and the use of superhydrides has emerged as the most effective method for transforming ergopeptine alkaloids. This study also focused on the epimerization of ergot alkaloids, particularly the differences between R- and S-epimers and their impact on the mass spectra. We validated our method by assessing the linearity, sensitivity, recovery, matrix effects, repeatability, and stability. The limits of detection and quantitation were set at 0.43 and 1.30 μg LSA/kg wheat, respectively. The proposed method offers a robust analytical approach for screening and quantifying total ergot alkaloids in wheat samples, addressing important concerns about their presence in food and feed.

Nontargeted screening method for detection of illicit adulterants in dietary supplements and herbal medicines using UHPLC-QTOF-MS with fine-tuned Spec2Vec-based spectral similarity and chemical classification filter

Liquid chromatography-mass spectrometry (LC-MS) is a widely utilized technique for inspecting adulteration. Unscrupulous businesses persistently introduce novel illegal adulterants, making it necessary to develop methods to screen compounds not present in the current library. Conventional cosine similarity for mass spectral libraries matching is limited in their ability to identify structurally similar compounds. In our previous study, comparison of performance among four advanced similarity algorithms revealed that Spec2Vec exhibited the best performance in terms of both detection capability and false discovery rate, making it the chosen method for identifying illegal adulterants. However, Spec2Vec still exhibited worse performance compared to MS2DeepScore and entropy similarity in the aspects of detection capability and false discovery rate, respectively. In this study, our objective was to optimize the performance of spectral similarity for a specific compound class by fine-tuning a pretrained Spec2Vec model. Additionally, we implemented the chemical classification tool CANOPUS to address the issue of similarities in backbone structures between illegal adulterants and compounds found in herbal medicine, which can lead to false positives. We utilized glucocorticoids as potentially illicit adulterants to provide a proof-of-concept, and the results demonstrated that the fine-tuned Spec2Vec model not only exhibits a significant improvement in detection ability compared to the original model but also achieves comparable performance to MS2Deepscore. Moreover, the fine-tuned Spec2Vec model shows notably fewer false positives in comparison to MS2Deepscore. Overall, this proposed pipeline demonstrates high effectiveness and competitiveness in inspecting illegal adulterants, enhancing the analysis of large-scale MS data.

Development, validation, and use of a monitoring method for fipronil and its metabolites in chicken eggs by QuEChERS with online-SPE-LC-Q/Orbitrap analysis

RATIONALE

The residues of fipronil and its metabolites in chicken eggs pose a threat to human health, so regular monitoring is necessary. However, the pretreatments of the existing detection methods are complex and time-consuming. A simple and streamlined pretreatment method is needed to improve the detection efficiency.

METHOD

A rapid, efficient, and facile approach employing the quick, easy, cheap, effective, rugged, and safe (QuEChERS) method with online solid-phase extraction liquid chromatography tandem Q Exactive Orbitrap high-resolution mass spectrometry (online-SPE-LC-HRMS) was established and evaluated for the determination of fipronil, fipronil-desulfinyl, fipronil-sulfone, and fipronil-sulfide in chicken eggs. An improved sample preparation technique combining QuEChERS and online-SPE was developed. Negative targeted ion fragmentation scanning and targeted-selected ion monitoring of HRMS were adopted to identify and quantify the target analytes.

RESULTS

The proposed pretreatment method took a few steps in <13 min to achieve excellent recoveries and negligible interference. High selectivity was acquired with the adoption of Q/Orbitrap HRMS. The limit of quantification (LOQ) of the analytes was 2.5 μg kg^-1 , meeting the detection requirements of the maximum residue level enacted by the Codex Alimentarius Commission, Japan, and the United States for the sum of fipronil and its metabolites. Extraction recoveries at three spiked concentration levels were within 84.56% to 93.84%, with relative standard deviation ≤5.87%.

CONCLUSION

The established method is efficient and easy to operate and displays satisfactory LOQs, recoveries, accuracy, and precision. This approach serves as a reference method for monitoring eggs while providing potential solutions for fipronil determination in more complicated matrices.