On the performance of multivariate curve resolution to resolve highly complex liquid chromatography–full scan mass spectrometry data for quantification of selected immunosuppressants in blood and water samples

Enhanced efficiency of MS/MS all-ion fragmentation for non-targeted analysis of trace contaminants in surface water using multivariate curve resolution and data fusion

Data-independent acquisition-all-ion fragmentation (DIA-AIF) mode of mass spectrometry can facilitate wide-scope non-target analysis of contaminants in surface water due to comprehensive spectral identification. However, because of the complexity of the resulting MS2 AIF spectra, identifying unknown pollutants remains a significant challenge, with a significant bottleneck in translating non-targeted chemical signatures into environmental impacts. The present study proposes to process fused MS1 and MS2 data sets obtained from LC-HRMS/MS measurements in non-targeted AIF workflows on surface water samples using multivariate curve resolution-alternating least squares (MCR-ALS). This enables straightforward assignment between precursor ions obtained from resolved MS1 spectra and their corresponding MS2 spectra. The method was evaluated for two sets of tap water and surface water contaminated with 14 target chemicals as a proof of concept. The data set of surface water samples consisting of 3506 MS1 and 2170 MS2 AIF mass spectral features was reduced to 81 components via a fused MS1-MS2 MCR model that describes at least 98.8% of the data. Each component summarizes the distinct chromatographic elution of components together with their corresponding MS1 and MS2 spectra. MS2 spectral similarity of more than 82% was obtained for most target chemicals. This highlights the potential of this method for unraveling the composition of MS/MS complex data in a water environment. Ultimately, the developed approach was applied to the retrospective non-target analysis of an independent set of surface water samples.

Extractability, selectivity, and comprehensiveness in supercritical fluid extraction of seaweed using ternary mixtures of carbon dioxide, ethanol, and water

It is well-known that an ideal extraction method enabling quantitative analysis should give complete extraction of the target analytes as well as minimal co-extraction of unwanted matrix substances. If the extraction method is part of a nontarget screening protocol, the desired analytes can differ widely in terms of chemical properties. In chromatography, terminologies such as recovery, selectivity, and comprehensiveness are well-established and can easily be determined. However, in extraction, these concepts are much less developed. Hence, the aim of our research is to develop and scrutinize theory in extraction with respect to numerical descriptors for extractability, selectivity, and comprehensiveness. Our approach is based on experiments determining the extractability of target analytes and selected interferences. As a case study, we use a pooled sample of three species of seaweed (Alaria esculenta, Laminaria digitata and Ascophyllum nodosum). Target analytes are β-carotene, fucoxanthin, δ-tocopherol, and phloroglucinol; and selected interferences are carbohydrates, proteins, ash, arsenic, and chlorophyll a. As a "green and clean" extraction technique, supercritical fluid extraction (SFE) using mixtures of CO2, ethanol and water were explored using a design of experiment. The temperature was varied between 40-80°C, and the pressure was held constant at 300 bar. Obtained results clearly demonstrate that highest relative selectivity was achieved with CO2 containing only 5 vol% of ethanol and no water, which primarily enabled high extractability of β-carotene, and yielding an extract free of carbohydrates, proteins, and toxic metals such as arsenic. Best methods for highest extractability of the other target analytes varied quite widely. Analytes requiring the highest water content (fucoxanthin and phloroglucinol), also resulted in the lowest relative selectivity. Maximum relative comprehensiveness was achieved using CO2/ethanol/water (40/55/5, v/v/v) at 70°C and 300 bar. Our study demonstrates the feasibility of using relative quantitative descriptors for extractability, selectivity, and comprehensiveness, in optimization strategies for analytical extractions.

Untargeted Metabolomics Analysis of Crocus cancellatus subsp. damascenus (Herb.) B. Mathew Stigmas and Their Anticarcinogenic Effect on Breast Cancer Cells

Safranal, crocin, crocetin, and picrocrocin are major known compounds in the stigma extract of Crocus sativus with various medicinal properties. Crocus cancellatus is another Crocus species that grows extensively in Iran’s various regions, such as the Kurdistan province. The predominant metabolites and biological properties of C. cancellatus have not yet been investigated. The ingredients of the stigma ethanol extract of C. cancellatus were investigated using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography with tandem mass spectrometry (LC-MS). The ROIMCR approach was performed to analyze the LC-MS full scan data sets. This method searches the MS regions of interest (ROI) data in the m/z domain and analyses the results using the multivariate curve-resolution alternating least squares (MCR-ALS) chemometrics technique for simultaneous resolution of two extracts. Also, the antiproliferative properties of C. cancellatus against MDA-MB-231 and MCF-7 cancer cells were examined by MTT, dual acridine orange/ethidium bromide test, Annexin V-FITC/PI, and zymography. The GC-MS and LC-MS untargeted metabolomics data analysis of the extract indicated the presence of cytotoxic agents including safranal, crocin, picrocrocin, and crocetin in the stigma ethanol extract of C. cancellatus. Biological tests showed that the viability of MDA-MB-231 and MCF-7 cancer cells is decreased following C. cancellatus treatment in a time- and dose-dependent way in both monolayer and 3D cell cultures. The MCF-7 cell spheroids had greater resistance to the cytotoxic activity of the extract in 3D cell culture than the MDA-MB-231 cell spheroids. The morphological changes of the cells treated with C. cancellatus stigmas extract were indicative of apoptosis. Zymography analysis revealed a similar trend of matrix metallopeptidase-2 (MMP-2) and matrix metallopeptidase-9 (MMP-9) activity in the treated cells with C. cancellatus extract in comparison with doxorubicin treatment as a positive control. The findings of this research indicate that the ethanolic extract of C. cancellatus stigmas was a good source of bioactive metabolites with anticancer activity.

Multiplex Detection of Antibiotic Residues in Milk: Application of MCR-ALS on Excitation-Emission Matrix Fluorescence (EEMF) Data Sets

The presence of antibiotics and their metabolites in milk and dairy products is a serious concern because of their harmful effects on human health. In the current study, a novel synergistic bimetallic nanocluster with gold and silver as an emission fluorescence probe was investigated for the simultaneous determination of tetracycline (TC), ampicillin (AMP), and sulfacetamide (SAC) antibiotics in the milk samples using excitation-emission matrix fluorescence (EEMF) spectroscopy. The multivariate curve resolution-alternating least squares (MCR-ALS) method was implemented to analyze augmented EEMF data sets to quantify the multicomponent systems in the presence of interferences with considerable spectral overlap. A pseudo-univariate calibration curve of the resolved emission spectra intensity against the concentration of the mentioned antibiotics was linear in the range of 5-5000 ng mL^-1 for AMP and 50-5000 ng mL^-1 for TC and SAC. The calculated values of the limit of detection ranged between 1.4 and 14.6 ng mL^-1 with a relative standard deviation (RSD) of less than 4.9%. The obtained results show that the EEMF/MCR-ALS methodology using an emission fluorescence probe is a powerful tool for the simultaneous quantification of TC, AMP, and SAC in complex matrices with highly overlapped spectra.

Chromatographic Applications in the Multi-Way Calibration Field

In this review, recent advances and applications using multi-way calibration protocols based on the processing of multi-dimensional chromatographic data are discussed. We first describe the various modes in which multi-way chromatographic data sets can be generated, including some important characteristics that should be taken into account for the selection of an adequate data processing model. We then discuss the different manners in which the collected instrumental data can be arranged, and the most usually applied models and algorithms for the decomposition of the data arrays. The latter activity leads to the estimation of surrogate variables (scores), useful for analyte quantitation in the presence of uncalibrated interferences, achieving the second-order advantage. Recent experimental reports based on multi-way liquid and gas chromatographic data are then reviewed. Finally, analytical figures of merit that should always accompany quantitative calibration reports are described.

Overview of therapeutic drug monitoring of immunosuppressive drugs: Analytical and clinical practices

Immunosuppressant drugs (ISDs) play a key role in short-term patient survival together with very low acute allograft rejection rates in transplant recipients. Due to the narrow therapeutic index and large inter-patient pharmacokinetic variability of ISDs, therapeutic drug monitoring (TDM) is needed to dose adjustment for each patient (personalized medicine approach) to avoid treatment failure or side effects of the therapy. To achieve this, TDM needs to be done effectively. However, it would not be possible without the proper clinical practice and analytical tools. The purpose of this review is to provide a guide to establish reliable TDM, followed by a critical overview of the current analytical methods and clinical practices for the TDM of ISDs, and to discuss some of the main practical aspects of the TDM.