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To comply with a more circular and environmentally friendly European common agricultural policy, while also valorising sunflower by-products, an ultrasound assisted extraction (UAE) was tested to optimise ethanol-wash solutes (EWS). Furthermore, the capabilities of DART-HRMS as a rapid and cost-effective tool for determining the biochemical changes after valorisation of these defatted sunflower EWS were investigated. Three batches of EWS were doubly processed into optimised EWS (OEWS) samples, which were analysed via DART-HRMS. Then, the metabolic profiles were submitted to a univariate analysis followed by a partial least square discriminant analysis (PLS-DA) allowing the identification of the 15 most informative ions. The assessment of the metabolomic fingerprinting characterising EWS and OEWS resulted in an accurate and well-defined spatial clusterization based on the retrieved pool of informative ions. The outcomes highlighted a significantly higher relative abundance of phenolipid hydroxycinnamoyl-glyceric acid and a lower incidence of free fatty acids and diglycerides due to the ultrasound treatment. These resulting biochemical changes might turn OEWS into a natural antioxidant supplement useful for controlling lipid oxidation and to prolong the shelf-life of foods and feeds. A standardised processing leading to a selective concentration of the desirable bioactive compounds is also advisable.

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Breast cancer, a complex disease with a significant prevalence to form metastases, necessitates novel therapeutic strategies to improve treatment outcomes. Here, we present the results of a comparative molecular study of primary breast tumours, their metastases, and the corresponding primary cell lines using Desorption Electrospray Ionisation (DESI) and Laser-Assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS) imaging. Our results show that ambient ionisation mass spectrometry technology is suitable for rapid characterisation of samples, providing a lipid- and metabolite-rich spectrum within seconds. Our study demonstrates that the lipidomic fingerprint of the primary tumour is not significantly distinguishable from that of its metastasis, in parallel with the similarity observed between their respective primary cell lines. While significant differences were observed between tumours and the corresponding cell lines, distinct lipidomic signatures and several phospholipids such as PA(36:2), PE(36:1), and PE(P-38:4)/PE(O-38:5) for LA-REIMS imaging and PE(P-38:4)/PE(O-38:5), PS(36:1), and PI(38:4) for DESI-MSI were identified in both tumours and cells. We show that the tumours' characteristics can be found in the corresponding primary cell lines, offering a promising avenue for assessing tumour responsiveness to therapeutic interventions. A comparative analysis by DESI-MSI and LA-REIMS imaging revealed complementary information, demonstrating the utility of LA-REIMS in the molecular imaging of cancer.

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Latent fingerprints at crime scenes are frequently recovered using forensic gel-lifters, which can help to preserve the crime scene and to enhance visualisation of traces such as blood or paint. In addition to providing fingerprint ridge detail, additional chemical information can also be recovered from gel lifts that may prove pertinent to an investigation. However, while DNA and metal ions have been shown to be able to be detected in gel-lifted fingerprints, the determination of other types of chemical information such as the presence of drugs in gel-lifted prints has not been previously shown. This study demonstrates the application of an ambient ionisation method, sheath flow probe electrospray ionisation-mass spectrometry (sfPESI-MS), to the direct analysis of gel-lifted fingerprints. A model drug compound (zolpidem) is successfully detected from gel-lifted prints from three different surface types: glass, metal, and paper. The surface activity-based separation associated with probe electrospray approaches is shown to resolve zolpidem ions from background phthalate species, significantly enhancing the response obtained from the gel-lifter. A depletion series experiment shows that the drug residue can be detected with up to 100% efficiency after eight consecutive contacts; however, detection efficiency drops to 20% after 30 contacts. The developed approach has potential application to analysis of historical gel-lifters to obtain additional chemical information.

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This article provides a comprehensive overview of the applications of methods of machine learning (ML) and artificial intelligence (AI) in ambient ionization mass spectrometry (AIMS). AIMS has emerged as a powerful analytical tool in recent years, allowing for rapid and sensitive analysis of various samples without the need for extensive sample preparation. The integration of ML/AI algorithms with AIMS has further expanded its capabilities, enabling enhanced data analysis. This review discusses ML/AI algorithms applicable to the AIMS data and highlights the key advancements and potential benefits of utilizing ML/AI in the field of mass spectrometry, with a focus on the AIMS community.

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Ambient ionisation mass spectrometry (AIMS) is a form of mass spectrometry whereby analyte ionisation occurs outside of a vacuum source under ambient conditions. This enables the direct analysis of samples in their native state, with little or no sample preparation and without chromatographic separation. The removal of these steps facilitates a much faster analytical process, enabling the direct analysis of samples within minutes if not seconds. Consequently, AIMS has gained rapid popularity across a diverse range of applications, in particular the analysis of drugs and toxins. Numerous fields rely upon mass spectrometry for the detection and identification of drugs, including clinical diagnostics, forensic chemistry, and food safety. However, all of these fields are hindered by the time-consuming and laboratory-confined nature of traditional techniques. As such, the potential for AIMS to resolve these challenges has resulted in a growing interest in ambient ionisation for drug and toxin analysis. Since the early 2000s, forensic science, diagnostic testing, anti-doping, pharmaceuticals, environmental analysis and food safety have all seen a marked increase in AIMS applications, foreshadowing a new future for drug testing. In this review, some of the most promising AIMS techniques for drug analysis will be discussed, alongside different applications of AIMS published over a 5-year period, to provide a summary of the recent research activity for ambient ionisation for drug and toxin analysis.

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The ability to determine the purity (% controlled compound) of drug-of-abuse samples is necessary for public health and law enforcement. Here, we describe the assessment of atmospheric solids analysis probe (ASAP) for the rapid determination of drug purity for a set of formulated pharmaceuticals, chosen due to their availability, uncontrolled status and consistency. Paracetamol and loratadine were used as models of high and low purity compounds being ~90% and ~10% active ingredient, respectively. Individual tablets were ground up and diluted in an internal standard solution. The resulting samples were analysed by ASAP coupled to a Waters QDa mass spectrometer followed by confirmatory testing by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The inclusion of a non-matched internal standard (quinine) improved linearity and repeatability of drug analysis by ASAP-MS. Levels of drug purity using formulated pharmaceutical tablets were found to be highly comparable with results produced by the 'gold standard' LC-MS/MS technique. Rapid determination of drug purity is therefore possible with ASAP-MS for highly concentrated samples with minimal sample preparation. It may be possible to use this deployable system to determine drug purity outside of a laboratory setting.

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Detection and prevention of fish food fraud are of ever-increasing importance, prompting the need for rapid, high-throughput fish speciation techniques. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) has quickly established itself as a powerful technique for the instant in situ analysis of foodstuffs. In the current study, a total of 1736 samples (2015-2021) - comprising 17 different commercially valuable fish species - were analysed using iKnife-REIMS, followed by classification with various multivariate and machine learning strategies. The results demonstrated that multivariate models, i.e. PCA-LDA and (O)PLS-DA, delivered accuracies from 92.5 to 100.0%, while RF and SVM-based classification generated accuracies from 88.7 to 96.3%. Real-time recognition on a separate test set of 432 samples (2022) generated correct speciation between 89.6 and 99.5% for the multivariate models, while the ML models underperformed (22.3-95.1%), in particular for the white fish species. As such, we propose a real-time validated modelling strategy using directly amenable PCA-LDA for rapid industry-proof large-scale fish speciation.

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Ambient ionisation mass spectrometry (AIMS) enables studying biological systems in their native state and direct high-throughput analyses. The ionisation occurs in the physical conditions of the surrounding environment. Simple spray or plasma-based AIMS devices allow the desorption and ionisation of molecules from solid, liquid and gaseous samples. 3D printing helps to implement new ideas and concepts in AIMS quickly. Here, we present examples of 3D printed AIMS sources and devices for ion transfer and manipulation. Further, we show the use of 3D printer parts for building custom AIMS sampling robots and imaging systems. Using 3D printing technology allows upgrading existing mass spectrometers with relatively low cost and effort.

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Due to favourable climate condition, Italy is a prominent producer of different wheat varieties. Several wheat baked goods are produced, but the most typical Italian foods, like pasta, pizza and bread, are made of durum and common wheat flour. Because of the great importance of wheat in the Italian food market, authenticity represents an essential quality parameter not only for the producers and regulatory bodies but also for consumers. The aim of our study was to test the effectiveness of an unconventional non-targeted method for the discrimination of Triticum species using direct analysis real time-high-resolution mass spectrometry (DART-HRMS). For this purpose, 60 wheat samples including durum, common and hulled wheat varieties were collected over two consecutive harvest years. Chemometric evaluation revealed an optimal sample clustering according to the wheat species and the presence of 18 significant markers able to discriminate the groups. The discrimination power obtained is promising since the use of DART-HRMS can significantly reduce the analysis time compared to chromatographic techniques. A plausible future commercial and industrial scenario could see the application of this analytical approach especially to evaluate the risk of substitution of higher value wheat species with lower value flours.

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INTRODUCTION: Medicinal plants are gaining increasing attention worldwide due to their empirical therapeutic efficacy and being a huge natural compound pool for new drug discovery and development. The efficacy, safety and quality of medicinal plants are the main concerns, which are highly dependent on the comprehensive analysis of chemical components in the medicinal plants. With the advances in mass spectrometry (MS) techniques, comprehensive analysis and fast identification of complex phytochemical components have become feasible, and may meet the needs, for the analysis of medicinal plants. OBJECTIVE: Our aim is to provide an overview on the latest developments in MS and its hyphenated technique and their applications for the comprehensive analysis of medicinal plants. METHODOLOGY: Application of various MS and its hyphenated techniques for the analysis of medicinal plants, including but not limited to one-dimensional chromatography, multiple-dimensional chromatography coupled to MS, ambient ionisation MS, and mass spectral database, have been reviewed and compared in this work. RESULTS: Recent advancs in MS and its hyphenated techniques have made MS one of the most powerful tools for the analysis of complex extracts from medicinal plants due to its excellent separation and identification ability, high sensitivity and resolution, and wide detection dynamic range. CONCLUSION: To achieve high-throughput or multi-dimensional analysis of medicinal plants, the state-of-the-art MS and its hyphenated techniques have played, and will continue to play a great role in being the major platform for their further research in order to obtain insight into both their empirical therapeutic efficacy and quality control.

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There is increasing appreciation of the role that vaginal microbiota play in health and disease throughout a woman's lifespan. This has been driven partly by molecular techniques that enable detailed identification and characterisation of microbial community structures. However, these methods do not enable assessment of the biochemical and immunological interactions between host and vaginal microbiota involved in pathophysiology. This review examines our current knowledge of the relationships that exist between vaginal microbiota and the host at the level of the vaginal mucosal interface. We also consider methodological approaches to microbiomic, immunologic and metabolic profiling that permit assessment of these interactions. Integration of information derived from these platforms brings the potential for biomarker discovery, disease risk stratification and improved understanding of the mechanisms regulating vaginal microbial community dynamics in health and disease.

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The application of on-line mass spectrometry for direct analysis of chemical and other types of process continues to grow in importance and impact. The ability of the technique to characterize many aspects of a chemical reaction such as product and impurity formation, along with reactant consumption in a single experiment is key to its adoption and development. Innovations in ionization techniques and mass spectrometry instrumentation are enabling this adoption. An increasing range of ambient ionization techniques make on-line mass spectrometry applicable to a large range of chemistries. The academic development and commercialization of small footprint portable/transportable mass spectrometers is providing technology that can be positioned with any process under investigation. These developments, coupled with research into new ways of sampling representatively from both the condensed and gaseous phases, are positioning mass spectrometry as an essential technology for on-line process optimization, understanding and intelligent control. It is recognized that quantitative capability of mass spectrometry in this application can cause some resistance to its adoption, but research activities to tackle this limitation are on-going.

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INTRODUCTION: The Salvia genus contains numerous economically important plants that have horticultural, culinary and nutraceutical uses. They are often similar in appearance, making species determination difficult. Species identification of dried Salvia products is also challenging since distinguishing plant morphological features are no longer present. OBJECTIVE: The development of a simple high-throughput method of analysis of fresh and dried Salvia leaves that would permit rapid species-level identification and detection of diagnostic biomarkers. METHODOLOGY: Plant leaves were analysed in their native form by DART-MS without the need for any sample preparation steps. This furnished chemical fingerprints characteristic of each species. In the same experiment, in-source collision-induced dissociation was used to identify biomarkers. Biomarker presence was also independently confirmed by GC-MS. Chemometric processing of DART-MS profiles was performed by kernel discriminant analysis (KDA) and soft independent modelling of class analogy (SIMCA) to classify the fingerprints according to species. RESULTS: The approach was successful despite the occurrence of diurnal cycle and plant-age related chemical profile variations within species. In a single rapid experiment, the presence of essential oil biomarkers such as 3-carene, α-pinene, ß-pinene, ß-thujone, ß-caryophyllene, camphor and borneol could be confirmed. The method was applied to rapid identification and differentiation of Salvia apiana, S. dominica, S. elegans, S. officinalis, S. farinacea and S. patens. CONCLUSION: Species-level identification of Salvia plant material could be accomplished by chemometric processing of DART-HRMS-derived chemical profiles of both fresh and dried Salvia material. Copyright © 2016 John Wiley & Sons, Ltd.

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Patulin is a mycotoxin commonly found in certain fruit and fruit products. For this reason many countries have established regulatory limits pertaining to, in particular, apple juice and apple products. Fruit leathers are produced by dehydrating fruit puree, leaving a sweet product that has a leathery texture. A recent report in the literature described the detection of patulin at substantial levels in fruit leathers. To investigate this further, an ultra-high-performance liquid chromatography-photodiode array (UPLC-PDA) method was developed for the sensitive detection of patulin in fruit leathers. Investigations were also made of the suitability of direct analysis in real time-mass spectrometry (DART-MS) for detection of patulin from the surface of fruit leathers. Results indicated DART-MS was insufficiently sensitive for quantification from the surface of home-style apple leathers, although patulin spiked onto the surface of leather or peel could be detected. The UPLC-PDA method was used to determine the fate of patulin during the preparation of home-made fruit leathers. Interestingly, when a home-style process was used, the patulin was not destroyed, but rather increased in concentration as the puree was dehydrated. The UPLC-PDA method was also used to screen for patulin in commercial fruit leathers. Of the 36 products tested, 14 were above the limit of detection (3.5 µg kg(-1)) and nine were above the limit of quantification (12 µg kg(-1)). Positive samples were confirmed by UPLC-MS/MS. Only one sample was found above the US regulatory limit for single-strength apple juice products (50 µg kg(-1)). These results suggest patulin can be concentrated during preparation and can be found in fruit leathers. The limited survey suggests that patulin is fairly prevalent in such commercial products, but that the levels are usually low.

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