ESI outcompetes other ion sources in LC/MS trace analysis

Quantification of chemicals in non-targeted analysis without analytical standards - Understanding the mechanism of electrospray ionization and making predictions

The constant creation and release of new chemicals to the environment is forming an ever-widening gap between available analytical standards and known chemicals. Developing non-targeted analysis (NTA) methods that have the ability to detect a broad spectrum of compounds is critical for research and analysis of emerging contaminants. There is a need to develop methods that make it possible to identify compound structures from their MS and MS/MS information and quantify them without analytical standards. Method refinements that utilize machine learning algorithms and chemical descriptors to estimate the instrument response of particular compounds have made progress in recent years. This narrative review seeks to summarize the current state of the field of non-targeted analysis (NTA) toward quantification of unknowns without the use of analytical standards. Despite the limited accumulation of validation studies on real samples, the ongoing enhancement in data processing and refinement of machine learning tools could lead to more comprehensive chemical coverage of NTA and validated quantitative NTA methods, thus boosting confidence in their usage and enhancing the utility of quantitative NTA.

Plasma-Excited Nebulizer Gas-Assisted Electrospray Ionization: Enhancing the Sensitivity of Pesticide in Mass Spectrometry

Liquid chromatography-mass spectrometry (LC-MS) is widely used in the detection of pesticide residues. However, the detection sensitivity of low-polarity pesticides by commonly used electrospray ionization may be severely suppressed, which greatly affects the limit of detection and repeatability. Herein, a plasma-excited nebulizer gas-assisted electrospray ionization (PENG-ESI) device has been developed. By introducing the discharge plasma formed by Tesla coil into the electrospray nebulizer gas channel, the sensitivity of low-polarity pesticides was significantly increased while maintaining sensitivity to polar pesticides. Under the optimized conditions, the limit of detection for S-bioallethrin was achieved at the level of 100 pg/g with good linearity (R2 > 0.99) and precision (RSD ≤ 4.61%). The matrix effect of a series of spiked matrix samples is less than 13.1%. Finally, different pyrethroid pesticide residues were successfully analyzed without separation, highlighting that the technology has potential application prospects in food quality control, environmental monitoring, and other fields.

Development of a QuEChERS method for simultaneous analysis of 3-Monochloropropane-1,2-diol monoesters and Glycidyl esters in edible oils and margarine by LC-APCI-MS/MS

A simple, fast and effective direct method based on HPLC-APCI-QqQ-MS/MS has been developed to simultaneously determine four 3-monochloropropane-1,2-diol monoesters (3-MCPDE) esterified with palmitic, linoleic, stearic, and oleic acid, and two glycidyl esters (GE) with palmitic and oleic acid in margarine and olive oil using a QuEChERS approach. Factors affecting the efficiency of the extraction process were assessed, including type and amount of salt, extraction solvent, test portion amount, and clean-up sorbent. The analytical method was validated according to Food and Drug Administration (FDA) guidelines using matrix-matched calibration with internal standards and showed good results in terms of linearity (r² > 0.9992), accuracy (80<Recovery<120%), and precision (RSD<15%). The method was successfully applied for the first time to 11 margarine samples for simultaneous analysis of 3-MCPDE and GE.

Chemical characterization and DPP-IV inhibitory activity evaluation of tripeptides from Gynura divaricata (L.) DC

ETHNOPHARMACOLOGICAL RELEVANCE

Gynura divaricata (L.) DC. (GD), a herbal medicine, has been used for the prevention and treatment of hyperglycemia in China. However, hypoglycemic ingredients within GD have not yet been well studied.

AIM OF THE STUDY

The aim of this study was to explore undiscovered compounds with dipeptidyl peptidase IV (DPP-IV) inhibitory activity within GD.

MATERIALS AND METHODS

A four-step strategy was developed to explore undiscovered DPP-IV inhibitors within GD. First, the components were preliminarily characterized using UHPLC-HRMS combined with a library search. Second, preliminarily characterized compounds were searched for potential bioactivity. Third, a mixture of these preliminarily characterized compounds was isolated and thoroughly characterized based on fragmentation patterns associated with molecular networking. Fourth, the activities of these compounds were verified using DPP-IV inhibitory assay and molecular docking.

RESULTS

Diprotin A, a tripeptide inhibitor against DPP-IV, was identified. Thereafter, a mixture of twenty-five diprotin A analogs was isolated and characterized, which exhibited IC₅₀ of 0.40 mg/mL for DPP-IV. Molecular docking results also confirmed the interactions between the tripeptide analogs and DPP-IV mainly via H-bonds and hydrophobic interactions.

CONCLUSIONS

This is the first report of DPP-IV inhibitors within GD. These findings demonstrate that the extract of GD might be beneficial for the treatment of type 2 diabetes mellitus, and is expected to promote further development and utilization of GD in herbal medicine.

Isolation of N-nitrosodimethylamine from drug substances using solid-phase extraction-liquid chromatography-tandem mass spectrometry

N-Nitrosodimethylamine (NDMA) has been detected in some drug substances and pharmaceutical products containing sartans, ranitidine and metformin, and a potential risk of NDMA contamination exists in other drug substances and their pharmaceutical products. To quantitate NDMA in various drugs having diverse physicochemical properties, a specific, sensitive, and reliable analytical method is required, in addition to methods that can be applied to a class of nitrosamines. We aimed to develop an off-line isolation method for NDMA in drug substances using SPE for quantification with LC-APCI-MS/MS. Impediments to accurate quantitation of NDMA in drug substances using LC-MS/MS and insufficient durability of the system are attributed to the extremely large amounts of active pharmaceutical ingredients (APIs) in sample solutions in comparison to the trace amount of NDMA. A reduced retention of NDMA and/or decreased separation from other substances in LC, matrix effect in MS detection, and undesirable contamination of instruments with API and other substances may be occasionally encountered, all of which consequently result in deterioration of system performance and generation of unreliable data, even in the cases where a divert valve is configured between the column and ion source of the MS instrument. To address these problems, an off-line NDMA isolation methodology from APIs exhibiting diverse physicochemical properties, namely ranitidine hydrochloride (ranitidine), metformin hydrochloride (metformin), nizatidine, valsartan, and telmisartan, was developed. The applicability of the method was confirmed by batch analysis of metformin and ranitidine. Furthermore, contrary to previous reports, NDMA was found to be stable over a wide pH range. The proposed methodology and data from this study would contribute to the control of NDMA contamination in various drugs to realize the safe delivery of pharmaceuticals to patients.