An environmental friendly, fast, easy and inexpensive pH-switchable hydrophobic deep eutectic solvent-based liquid phase microextraction procedure was developed and combined with HPLC-UV detection for the extraction and analysis of morphine and codeine in whole blood samples. In this method, seven deep eutectic solvents were synthesized and then their switchability with pH was investigated. Deep eutectic solvents that could be switched with pH were used as extractant. Under the optimum conditions, relative standard deviation values for intra-day and inter-day of the method based on seven replicate measurements of 50 μg L-1 of morphine and codeine in blood samples were in the range of 3.7-4.3% and 5.4-6.2%, respectively. The calibration graphs were linear in the range of 1.5-300 μg L-1 and limit of detection for both analytes was 0.5 μg L-1. The enrichment factor and the extraction recovery of morphine and codeine were in the ranges of 152-166, and 76-83%, respectively. The results showed that both morphine and codeine were detected in the blood sample of the addicted person. The relative recoveries of real blood samples which have been spiked with different levels of morphine and codeine were 91.8-107.0%. This article is protected by copyright. All rights reserved.
{"title":"Trace determination of morphine and codeine in whole blood samples using pH-switchable hydrophobic deep eutectic solvents based liquid phase microextraction followed by HPLC-UV.","authors":"Fuad Ameen","doi":"10.1002/jssc.202300336","DOIUrl":"https://doi.org/10.1002/jssc.202300336","url":null,"abstract":"<p><p>An environmental friendly, fast, easy and inexpensive pH-switchable hydrophobic deep eutectic solvent-based liquid phase microextraction procedure was developed and combined with HPLC-UV detection for the extraction and analysis of morphine and codeine in whole blood samples. In this method, seven deep eutectic solvents were synthesized and then their switchability with pH was investigated. Deep eutectic solvents that could be switched with pH were used as extractant. Under the optimum conditions, relative standard deviation values for intra-day and inter-day of the method based on seven replicate measurements of 50 μg L<sup>-1</sup> of morphine and codeine in blood samples were in the range of 3.7-4.3% and 5.4-6.2%, respectively. The calibration graphs were linear in the range of 1.5-300 μg L<sup>-1</sup> and limit of detection for both analytes was 0.5 μg L<sup>-1</sup>. The enrichment factor and the extraction recovery of morphine and codeine were in the ranges of 152-166, and 76-83%, respectively. The results showed that both morphine and codeine were detected in the blood sample of the addicted person. The relative recoveries of real blood samples which have been spiked with different levels of morphine and codeine were 91.8-107.0%. This article is protected by copyright. All rights reserved.</p>","PeriodicalId":17098,"journal":{"name":"Journal of separation science","volume":" ","pages":"e2300336"},"PeriodicalIF":2.8,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145743166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nathalie Le Bris, Axel Beringue, Johanna Rivas, David Renault, Marion Chorin, Hervé Colinet
The technical progress of metabolomics—the analysis of metabolite composition of cells, tissues, and biofluids—and its ability to unravel phenotypical responses of organisms to their environment was accompanied by the democratization of their use in a wide range of scientific fields. While the reliability of analytical procedures was thoroughly assessed, the effects of preanalytical processing on sample metabolic profiles (i.e., conditioning, storage, transportation, etc.) remain quite unclear. This uncertainty is especially notable for samples collected in the frame of ecological studies, which often involve field sampling and remote sample production, leading to extended transportation durations and suboptimal storage conditions. In this study, we evaluated the impact of storage duration and temperature, along with the effects of freeze-drying (or lyophilization; the process of stabilization through dehydration by sublimation), on the metabolic profiles of samples relevant to ecological studies. Specifically, we focused on the lesser mealworm (Alphitobius diaperinus), the fruit fly (Drosophila melanogaster), and the perennial ryegrass (Lolium perenne). The levels of 60 different metabolites were quantitatively analyzed using targeted metabolomics through gas chromatography–mass spectrometry (GC–MS). We report significant metabolic shifts associated with freeze-drying, resulting in both increases and decreases in the contents of more than half of the quantified metabolites across all assessed chemical families. Several amino acids exhibited more than a fourfold increase in all investigated matrices. Furthermore, while samples stored at −80°C exhibited profiles most similar to those of samples analyzed right after collection, the metabolic profiles of these samples gradually changed over the 6 months of storage. Interestingly, metabolic shifts related to sample preanalytical processing and storage were relatively consistent across the biological matrices studied, particularly between the two insect species. Based on these observations, we propose several recommendations for reliable preanalytical sample processing in ecological studies, considering logistical and economic constraints.
{"title":"How to Process Samples for Metabolomics in Ecology: A Comparative Study of Preanalytical Storage Methods","authors":"Nathalie Le Bris, Axel Beringue, Johanna Rivas, David Renault, Marion Chorin, Hervé Colinet","doi":"10.1002/jssc.70333","DOIUrl":"10.1002/jssc.70333","url":null,"abstract":"<p>The technical progress of metabolomics—the analysis of metabolite composition of cells, tissues, and biofluids—and its ability to unravel phenotypical responses of organisms to their environment was accompanied by the democratization of their use in a wide range of scientific fields. While the reliability of analytical procedures was thoroughly assessed, the effects of preanalytical processing on sample metabolic profiles (i.e., conditioning, storage, transportation, etc.) remain quite unclear. This uncertainty is especially notable for samples collected in the frame of ecological studies, which often involve field sampling and remote sample production, leading to extended transportation durations and suboptimal storage conditions. In this study, we evaluated the impact of storage duration and temperature, along with the effects of freeze-drying (or lyophilization; the process of stabilization through dehydration by sublimation), on the metabolic profiles of samples relevant to ecological studies. Specifically, we focused on the lesser mealworm (<i>Alphitobius diaperinus</i>), the fruit fly (<i>Drosophila melanogaster</i>), and the perennial ryegrass (<i>Lolium perenne</i>). The levels of 60 different metabolites were quantitatively analyzed using targeted metabolomics through gas chromatography–mass spectrometry (GC–MS). We report significant metabolic shifts associated with freeze-drying, resulting in both increases and decreases in the contents of more than half of the quantified metabolites across all assessed chemical families. Several amino acids exhibited more than a fourfold increase in all investigated matrices. Furthermore, while samples stored at −80°C exhibited profiles most similar to those of samples analyzed right after collection, the metabolic profiles of these samples gradually changed over the 6 months of storage. Interestingly, metabolic shifts related to sample preanalytical processing and storage were relatively consistent across the biological matrices studied, particularly between the two insect species. Based on these observations, we propose several recommendations for reliable preanalytical sample processing in ecological studies, considering logistical and economic constraints.</p>","PeriodicalId":17098,"journal":{"name":"Journal of separation science","volume":"48 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12690189/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145714502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Obtaining an insight into the composition of fuel and process intermediates samples is important for monitoring of the product quality, production and exploitation process improvement and complying with industry and environmental regulations. A broadband vacuum ultraviolet (VUV) spectroscopy detector has been successfully hyphenated with both GC and comprehensive two-dimensional gas chromatography (GC×GC) for the analysis of various fuel samples. This detector possesses both qualitative and quantitative capabilities. Most compounds absorb in the vacuum ultraviolet spectral range, and they exhibit rich and distinctive spectral features. Main constituents of fuel samples, hydrocarbons, such as paraffins, olefins, naphthenes, aromatics are identified with the VUV with very good selectivity. As data obtained from the GC×GC-VUV analysis of fuels can be challenging to exploit due to the sample complexity, it can be useful to employ chemometric methods for fuel composition exploration in a fast and efficient manner. In this work, 14 gas oil samples were analysed by GC×GC-VUV and after suitable data preprocessing, a pixel-based approach combined with k-means clustering was applied in order to classify compounds’ spectra into major hydrocarbon families in each sample and obtain a semi-quantification result which was then compared with the results of mass spectrometry analysis and quantitative GC×GC-VUV that involved application of detailed identification templates and response factors. It was demonstrated that due to hydrocarbon families exhibiting similar VUV absorbance spectra, the proposed workflow for GC×GC-VUV data preprocessing and analysis can be a fast and efficient way for gas oils global composition exploration.
{"title":"Spectral Pixel-Based Analysis and Clustering Workflow for the Exploration of the Composition of Gas Oil Samples by Comprehensive Two-dimensional Gas Chromatography Vacuum Ultraviolet Spectroscopy","authors":"Aleksandra Lelevic","doi":"10.1002/jssc.70318","DOIUrl":"10.1002/jssc.70318","url":null,"abstract":"<p>Obtaining an insight into the composition of fuel and process intermediates samples is important for monitoring of the product quality, production and exploitation process improvement and complying with industry and environmental regulations. A broadband vacuum ultraviolet (VUV) spectroscopy detector has been successfully hyphenated with both GC and comprehensive two-dimensional gas chromatography (GC×GC) for the analysis of various fuel samples. This detector possesses both qualitative and quantitative capabilities. Most compounds absorb in the vacuum ultraviolet spectral range, and they exhibit rich and distinctive spectral features. Main constituents of fuel samples, hydrocarbons, such as paraffins, olefins, naphthenes, aromatics are identified with the VUV with very good selectivity. As data obtained from the GC×GC-VUV analysis of fuels can be challenging to exploit due to the sample complexity, it can be useful to employ chemometric methods for fuel composition exploration in a fast and efficient manner. In this work, 14 gas oil samples were analysed by GC×GC-VUV and after suitable data preprocessing, a pixel-based approach combined with k-means clustering was applied in order to classify compounds’ spectra into major hydrocarbon families in each sample and obtain a semi-quantification result which was then compared with the results of mass spectrometry analysis and quantitative GC×GC-VUV that involved application of detailed identification templates and response factors. It was demonstrated that due to hydrocarbon families exhibiting similar VUV absorbance spectra, the proposed workflow for GC×GC-VUV data preprocessing and analysis can be a fast and efficient way for gas oils global composition exploration.</p>","PeriodicalId":17098,"journal":{"name":"Journal of separation science","volume":"48 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12683198/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145701235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}