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Phospholipids are the main building components of cell membranes and are also used for cell signaling and as energy storages. Cancer cells alter their lipid metabolism, which ultimately leads to an increase in phospholipids in cancer tissue. Surgical energy instruments use electrical or vibrational energy to heat tissues, which causes intra- and extracellular water to expand rapidly and degrade cell structures, bursting the cells, which causes the formation of a tissue aerosol or smoke depending on the amount of energy used. This gas phase analyte can then be analyzed via gas analysis methods. Differential mobility spectrometry (DMS) is a method that can be used to differentiate malignant tissue from benign tissues in real time via the analysis of surgical smoke produced by energy instruments. Previously, the DMS identification of cancer tissue was based on a 'black box method' by differentiating the 2D dispersion plots of samples. This study sets out to find datapoints from the DMS dispersion plots that represent relevant target molecules. We studied the ability of DMS to differentiate three subclasses of phospholipids (phosphatidylcholine, phosphatidylinositol, and phosphatidylethanolamine) from a control sample using a bovine skeletal muscle matrix with a 5 mg addition of each phospholipid subclass to the sample matrix. We trained binary classifiers using linear discriminant analysis (LDA) and support vector machines (SVM) for sample classification. We were able to identify phosphatidylcholine, -inositol, and -ethanolamine with SVM binary classification accuracies of 91%, 73%, and 66% and with LDA binary classification accuracies of 82%, 74%, and 72%, respectively. Phosphatidylcholine was detected with a reliable classification accuracy, but ion separation setups should be adjusted in future studies to reliably detect other relevant phospholipids such as phosphatidylinositol and phosphatidylethanolamine and improve DMS as a microanalysis method and identify other phospholipids relevant to cancer tissue. [ABSTRACT FROM AUTHOR]

Utilizing a data‐driven approach, this study investigates modifier effects on compensation voltage in differential mobility spectrometry–mass spectrometry (DMS‐MS) for metabolites and peptides. Our analysis uncovers specific factors causing signal suppression in small molecules and pinpoints both signal suppression mechanisms and the analytes involved. In peptides, machine learning models discern a relationship between molecular weight, topological polar surface area, peptide charge, and proton transfer‐induced signal suppression. The models exhibit robust performance, offering valuable insights for the application of DMS to metabolites and tryptic peptides analysis by DMS‐MS. [ABSTRACT FROM AUTHOR]

Introduction: Brain tumors are a major source of disease burden in pediatric population, with the most common tumor types being pilocytic astrocytoma, ependymoma and medulloblastoma. In every tumor entity, surgery is the cornerstone of treatment, but the importance of gross-total resection and the corresponding patient prognosis is highly variant. However, real-time identification of pediatric CNS malignancies based on the histology of the frozen sections alone is especially troublesome. We propose a novel method based on differential mobility spectrometry (DMS) analysis for rapid identification of pediatric brain tumors. Methods: We prospectively obtained tumor samples from 15 pediatric patients (5 pilocytic astrocytomas, 5 ependymomas and 5 medulloblastomas). The samples were cut into 36 smaller specimens that were analyzed with the DMS. Results: With linear discriminant analysis algorithm, a classification accuracy (CA) of 70% was reached. Additionally, a 75% CA was achieved in a pooled analysis of medulloblastoma vs. gliomas. Discussion: Our results show that the DMS is able to differentiate most common pediatric brain tumor samples, thus making it a promising additional instrument for real-time brain tumor diagnostics. [ABSTRACT FROM AUTHOR]

Classification of volatile organic compounds (VOCs) is of interest in many fields. Examples include but are not limited to medicine, detection of explosives, and food quality control. Measurements collected with so-called electronic noses can be used for classification and analysis of VOCs. One type of electronic noses that has seen considerable development in recent years is Differential Mobility Spectrometry (DMS). DMS yields measurements that are visualized as dispersion plots that contain traces, also known as alpha curves. Current methods used for analyzing DMS dispersion plots do not usually utilize the information stored in the continuity of these traces, which suggests that alternative approaches should be investigated. In this work, for the first time, dispersion plots were interpreted as a series of measurements evolving sequentially. Thus, it was hypothesized that time-series classification algorithms can be effective for classification and analysis of dispersion plots. An extensive dataset of 900 dispersion plots for five chemicals measured at five flow rates and two concentrations was collected. The data was used to analyze the classification performance of six algorithms. The highest classification accuracy of 88% was achieved by a Long-Short Term Memory neural network, which supports the hypothesis that interpreting DMS measurements as sequential data is beneficial and outperformed classification algorithms traditionally used for DMS-based VOC identification.

IntroductionBrain tumors are a major source of disease burden in pediatric population, with the most common tumor types being pilocytic astrocytoma, ependymoma and medulloblastoma. In every tumor entity, surgery is the cornerstone of treatment, but the importance of gross-total resection and the corresponding patient prognosis is highly variant. However, real-time identification of pediatric CNS malignancies based on the histology of the frozen sections alone is especially troublesome. We propose a novel method based on differential mobility spectrometry (DMS) analysis for rapid identification of pediatric brain tumors.MethodsWe prospectively obtained tumor samples from 15 pediatric patients (5 pilocytic astrocytomas, 5 ependymomas and 5 medulloblastomas). The samples were cut into 36 smaller specimens that were analyzed with the DMS.ResultsWith linear discriminant analysis algorithm, a classification accuracy (CA) of 70% was reached. Additionally, a 75% CA was achieved in a pooled analysis of medulloblastoma vs. gliomas.DiscussionOur results show that the DMS is able to differentiate most common pediatric brain tumor samples, thus making it a promising additional instrument for real-time brain tumor diagnostics.

Introduction: Steroid measurements are important for diagnosis and monitoring of many conditions and treatment regiments; however, due to structural and chemical similarities amongst steroids, these analyses are challenging, even for highly specific techniques such as liquid chromatography-tandem mass spectrometry (LC-MS/MS). Differential mobility spectrometry (DMS) has the potential to improve these analyses by providing an orthogonal and complementary separation technique. Methods: Initially, the potential for DMS to improve signal-to-noise ratio (S/N) and reduce interference was tested by comparing chromatograms acquired with and without DMS when performing measurements of six different steroids. Subsequently, a full clinical validation of cortisol and cortisone in urine was performed with the LC-DMS-MS/MS method. Results and Discussion: DMS significantly reduced interferences observed in the chromatograms and boosted S/N by between 1.6 and 13.8 times. Additionally, DMS improved the agreement between quantifier/qualifier fragment ion results for cortisol and cortisone as indicated by the increase in R2 from approximately 0.81 to 0.98. All validation studies met acceptance criteria and we observed exceptional analytical performance in terms of precision, with % CVs less than 8%. Conclusions: DMS improved the specificity of the steroid measurements by reducing interferences and improving S/N. The validation studies prove that these benefits did not come at the expense of other aspects of analytical performance. This study indicates that DMS has the potential to benefit not just clinical measurements of challenging analytes, but many clinical LC-MS/MS analyses.

Analysis of volatile organic compounds (VOCs) can be an effective strategy to inspect the quality of horticultural commodities and following their degradation. In this work, we report that VOCs emitted by walnuts can be studied using gas chromatography-differential mobility spectrometry (GC-DMS), and those GC-DMS data can be analyzed to predict the rancidity of walnuts, i.e., classify walnuts into grades of freshness. Walnut kernels were assigned a class n depending on their level of freshness as determined by a peroxide assay. VOC samples were analyzed using GC-DMS. From these VOC data, a partial least square regression (PLSR) model provided a freshness prediction value m, which corresponded to the rancid class n when m=n±0.5. The PLSR model had an accuracy of 80% to predict walnut grade and demonstrated a minimal root mean squared error of 0.42 for the m response variables (representative of walnut grade) with the GC-DMS data. We also conducted gas chromatography-mass spectrometry (GC–MS) experiments to identify volatiles that emerged or were enhanced with more rancid walnuts. The findings of the GC–MS study of walnut VOCs align excellently with the GC-DMS study. Based on our results, we conclude that a GC-DMS device deployed with a pre-trained machine learning model can be a very effective device for classifying walnut grades in the industry.

Glucose tetrasaccharide (Glc4) and maltotetraose (M4) are important biomarkers for Pompe disease and other glycogen storage diseases (GSDs). With the development of new treatments for GSDs, more specific and sensitive bioanalytical methods are needed to determine biomarkers. In recent years, differential mobility spectrometry (DMS) has become an effective analytical technique with high selectivity and specificity. This study aimed to develop an efficient analytical method for the two urinary tetrasaccharide metabolites using DMS and apply it to patients with GSDs (type Ib and II). Urine samples were directly diluted and injected into liquid chromatography-differential mobility spectrometry tandem mass spectrometry (LC-DMS-MS/MS). Chromatographic separation was performed on an Acquity™ UPLC BEH Amide column (2.1 × 50 mm, 1.7 μm) with a short gradient elution of 2.6 min. DMS-MS/MS was used to detect two urinary tetrasaccharide metabolites in a negative multiple reaction monitoring mode with isopropanol as a modifier. A total of 20 urine samples from 6 healthy volunteers and 10 patients with GSDs (type Ib and II) were collected for analysis. The method was linear over a concentration range of 0.5~100.0 µg/mL for each urinary tetrasaccharide (r≥0.99). The intra- and inter-day precision RSD% were less than 14.3%, and the accuracy RE% were in the range of −14.3~13.4%. The relative matrix effect was between 86.6 and 114.3%. No carryover or interference was observed. Patients with GSDs (type Ib and II) had significantly higher median urinary Glc4 (P=0.001) and M4 (P=0.012) excretion than healthy subjects. The developed method was simple, rapid, sensitive, and specific. It was successfully applied to healthy volunteers and patients with GSDs (type Ib and II). DMS technology greatly improved analysis efficiency and provided high sensitivity and specificity. [ABSTRACT FROM AUTHOR]

While developing a DMS-based separation method for beer's bittering compounds, we observed that the argentinated forms of humulone tautomers (i.e., [Hum + Ag]+) were partially resolvable in a N2 environment seeded with 1.5 mol % of isopropyl alcohol (IPA). Attempting to improve the separation by introducing resolving gas unexpectedly caused the peaks for the cis-keto and trans-keto tautomers of [Hum + Ag]+ to coalesce. To understand why resolution loss occurred, we first confirmed that each of the tautomeric forms (i.e., dienol, cis-keto, and trans-keto) responsible for the three peaks in the [Hum + Ag]+ ionogram were assigned to the correct species by employing collision-induced dissociation, UV photodissociation spectroscopy, and hydrogen–deuterium exchange (HDX). The observation of HDX indicated that proton transfer was stimulated by dynamic clustering processes between IPA and [Hum + Ag]+ during DMS transit. Because IPA accretion preferentially occurs at Ag+, which can form pseudocovalent bonds with a suitable electron donor, solvent clustering also facilitated the formation of exceptionally stable microsolvated ions. The exceptional stability of these microsolvated configurations disproportionately impacted the compensation voltage (CV) required to elute each tautomer when the temperature within the DMS cell was varied. The disparity in CV response caused the peaks for the cis- and trans-keto species to merge when a temperature gradient was induced by the resolving gas. Moreover, simulations showed that microsolvation with IPA mediates dienol to trans-keto tautomerization during DMS transit, which, to the best of our knowledge, is the first observation of keto/enol tautomerization occurring within an ion-mobility device. [ABSTRACT FROM AUTHOR]

Polylactic acids (PLAs) are synthetic polymers composed of repeating lactic acid subunits. For their good biocompatibility, PLAs have been approved and widely applied as pharmaceutical excipients and scaffold materials. Liquid chromatography-tandem mass spectrometry is a powerful analytical tool not only for pharmaceutical ingredients but also for pharmaceutical excipients. However, the characterization of PLAs presents particular problems for mass spectrometry techniques. In addition to their high molecular weights and wide polydispersity, multiple charging and various adductions are intrinsic features of electrospray ionization. In the present study, a strategy combining of differential mobility spectrometry (DMS), multiple ion monitoring (MIM) and in-source collision-induced dissociation (in source-CID) has been developed and applied to the characterization and quantitation of PLAs in rat plasma. First, PLAs will be fragmented into characteristic fragment ions under high declustering potential in the ionization source. The specific fragment ions are then screened twice by quadrupoles to ensure a high signal intensity and low interference for mass spectrometry detection. Subsequently, DMS technique has been applied to further reduce the background noise. The appropriately chosen surrogate specific precursor ions could be utilized for the qualitative and quantitative analysis of PLAs, which provided results with the advantages of low endogenous interference, sufficient sensitivity and selectivity for bioassay. The linearity of the method was evaluated over the concentration range 3–100 μg/mL (r2 = 0.996) for PLA 20,000. The LC-DMS-MIM coupled with in source-CID strategy may contribute to the pharmaceutical studies of PLAs and the possible prospects of other pharmaceutical excipients. [ABSTRACT FROM AUTHOR]

The benefits of combining drift time ion mobility (DTIMS) with liquid chromatography–high-resolution mass spectrometry (HRMS) have been reported for metabolomics but the use of differential time mobility spectrometry (DMS) is less obvious due to the need for rapid scanning of the DMS cell. Drift DTIMS provides additional precursor ion selectivity and collisional cross-section information but the separation resolution between analytes remains cell- and component-dependent. With DMS, the addition of 2-propanol modifier can improve the selectivity but on cost of analyte MS response. In the present work, we investigate the liquid chromatography–mass spectrometry (LC–MS) analysis of a mix of 50 analytes, representative for urine and plasma metabolites, using scanning DMS with the single modifiers cyclohexane (Ch), toluene (Tol), acetonitrile (ACN), ethanol (EtOH), and 2-propanol (IPA), and a binary modifier mixture (cyclohexane/2-propanol) with emphasis on selectivity and signal sensitivity. 1.5% IPA in the N2 stream was found to suppress the signal of 50% of the analytes which could be partially recovered with the use of IPA to 0.05% as a Ch/IPA mixture. The potential to use the separation voltage/compensation voltage/modifier (SV/CoV/Mod) feature as an additional analyte identifier for qualitative analysis is also presented and applied to a data-independent LCxDMS-SWATH-MS workflow for the analysis of endogenous metabolites and drugs of abuse in human urine samples from traffic control. [ABSTRACT FROM AUTHOR]

Due to the versatility of present day microcontroller boards and open source development environments, new analytical chemistry devices can now be built outside of large industry and instead within smaller individual groups. While there are a wide range of commercial devices available for detecting and identifying volatile organic compounds (VOCs), most of these devices use their own proprietary software and complex custom electronics, making modifications or reconfiguration of the systems challenging. The development of microprocessors for general use, such as the Arduino prototyping platform, now enables custom chemical analysis instrumentation. We have created an example system using commercially available parts, centered around on differential mobility spectrometer (DMS) device. The Modular Reconfigurable Gas Chromatography - Differential Mobility Spectrometry package (MR-GC-DMS) has swappable components allowing it to be quickly reconfigured for specific application purposes as well as broad, generic use. The MR-GC-DMS has a custom user-friendly graphical user interface (GUI) and precisely tuned proportional-integral-derivative controller (PID) feedback control system managing individual temperature-sensitive components. Accurate temperature control programmed into the microcontroller greatly increases repeatability and system performance. Together, this open-source platform enables researchers to quickly combine DMS devices in customized configurations for new chemical sensing applications.

Isocitrate dehydrogenase (IDH) mutation status is an important factor for surgical decision-making: patients with IDH-mutated tumors are more likely to have a good long-term prognosis, and thus favor aggressive resection with more survival benefit to gain. Patients with IDH wild-type tumors have generally poorer prognosis and, therefore, conservative resection to avoid neurological deficit is favored. Current histopathological analysis with frozen sections is unable to identify IDH mutation status intraoperatively, and more advanced methods are therefore needed. We examined a novel method suitable for intraoperative IDH mutation identification that is based on the differential mobility spectrometry (DMS) analysis of the tumor. We prospectively obtained tumor samples from 22 patients, including 11 IDH-mutated and 11 IDH wild-type tumors. The tumors were cut in 88 smaller specimens that were analyzed with DMS. With a linear discriminant analysis (LDA) algorithm, the DMS was able to classify tumor samples with 86% classification accuracy, 86% sensitivity, and 85% specificity. Our results show that DMS is able to differentiate IDH-mutated and IDH wild-type tumors with good accuracy in a setting suitable for intraoperative use, which makes it a promising novel solution for neurosurgical practice.

Limaprost, an orally administered analogue of prostaglandin E1, possesses potent vasodilatory, antiplatelet, and cytoprotective properties. Due to its extremely low therapeutic doses and exceedingly low plasma concentrations, the pharmacokinetic and bioequivalence studies of limaprost necessitate a highly sensitive quantitative method with a sub-pg/mL level of lower limit of quantification. Moreover, the intensity of endogenous interferences can even exceed the maximum concentration level of limaprost in human plasma, presenting further challenge to the quantification of limaprost. As a result, existing methods have not yet met the necessary level of sensitivity, selectivity, and throughput needed for the quantitative analysis of limaprost in pharmacokinetic and bioequivalence investigations. This study presents a new methodology that combines differential mobility spectrometry (DMS) with liquid chromatography-tandem mass spectrometry (LC-MS/MS) and utilizes a distinctive strategy to achieve more accurate DMS conditions. This integration yields a method that is currently the most sensitive and features the shortest analytical time, making it the sole technique capable of meeting the requirements for limaprost pharmacokinetic and bioequivalence investigations. This method demonstrates robustness and is successfully employed in a pharmacokinetic investigation of limaprost in human subjects, underscoring that the combination of DMS with LC-MS/MS serves as an efficacious strategy for overcoming the challenges inherent in analyzing biological samples afflicted by multiple interferences. [Display omitted] • LC-DMS-MS/MS for quantification of limaprost with ultra-high sensitivity. • Innovative on-column DMS optimization with post-extracted matrix spiked with analytes. • Significant reduction in analytical time compared to 2D-LC-MS/MS method. • Overcoming the challenges of high sensitivity and strong interference in bioanalysis. • Successful application in a pharmacokinetic study in human. [ABSTRACT FROM AUTHOR]

The lipid composition of lipoprotein particles is determinative of their respective formation and function. In turn, the combination and correlation of nuclear magnetic resonance (NMR)-based lipoprotein measurements with mass spectrometry (MS)-based lipidomics is an appealing technological combination for a better understanding of lipid metabolism in health and disease. Here, we developed a combined workflow for subsequent NMR- and MS-based analysis on single sample aliquots of human plasma. We evaluated the quantitative agreement of the two platforms for lipid quantification and benchmarked our combined workflow. We investigated the congruence and complementarity between the platforms in order to facilitate a better understanding of patho-physiological lipoprotein and lipid alterations. We evaluated the correlation and agreement between the platforms. Next, we compared lipid class concentrations between healthy controls and rheumatoid arthritis patient samples to investigate the consensus among the platforms on differentiating the two groups. Finally, we performed correlation analysis between all measured lipoprotein particles and lipid species. We found excellent agreement and correlation (r > 0.8) between the platforms and their respective diagnostic performance. Additionally, we generated correlation maps detailing lipoprotein/lipid interactions and describe disease-relevant correlations. [ABSTRACT FROM AUTHOR]

The effect of LC mobile phase composition and flow rate (2–50 µL/min) on mobility behavior in vacuum differential mobility spectrometry (vDMS) was investigated for electrosprayed isobaric antidepressant drugs (AD); amitriptyline, maprotiline, venlafaxine; and structurally related antidepressants nortriptyline, imipramine, and desipramine. While at 2 µL/min, no difference in compensation voltage was observed with methanol and acetonitrile, at 50 µL/min, acetonitrile used for LC elution of analytes enabled the selectivity of the mobility separation to be improved. An accurate and sensitive method could be developed for the quantification of six AD drugs in human plasma using trap/elute micro-LC setup hyphenated to vDMS with mass spectrometric detection in the selected ion monitoring mode. The assay was found to be linear over three orders of magnitude, and the limit of quantification was of 25 ng/mL for all analytes. The LC-vDMS-SIM/MS method was compared to a LC-MRM/MS method, and in both cases, inter-assay precisions were lower than 12.5 and accuracies were in the range 91.5–110%, but with a four times reduced analysis time (2 min) for the LC-vDMS-SIM/MS method. This work illustrates that with vDMS, the LC mobile phase composition can be used to tune the ion mobility separation and to improve assay selectivity without additional hardware. [ABSTRACT FROM AUTHOR]

Polylactic acids (PLAs) are synthetic polymers composed of repeating lactic acid subunits. For their good biocompatibility, PLAs have been approved and widely applied as pharmaceutical excipients and scaffold materials. Liquid chromatography-tandem mass spectrometry is a powerful analytical tool not only for pharmaceutical ingredients but also for pharmaceutical excipients. However, the characterization of PLAs presents particular problems for mass spectrometry techniques. In addition to their high molecular weights and wide polydispersity, multiple charging and various adductions are intrinsic features of electrospray ionization. In the present study, a strategy combining of differential mobility spectrometry (DMS), multiple ion monitoring (MIM) and in-source collision-induced dissociation (in source-CID) has been developed and applied to the characterization and quantitation of PLAs in rat plasma. First, PLAs will be fragmented into characteristic fragment ions under high declustering potential in the ionization source. The specific fragment ions are then screened twice by quadrupoles to ensure a high signal intensity and low interference for mass spectrometry detection. Subsequently, DMS technique has been applied to further reduce the background noise. The appropriately chosen surrogate specific precursor ions could be utilized for the qualitative and quantitative analysis of PLAs, which provided results with the advantages of low endogenous interference, sufficient sensitivity and selectivity for bioassay. The linearity of the method was evaluated over the concentration range 3–100 μg/mL (r2 = 0.996) for PLA 20,000. The LC-DMS-MIM coupled with in source-CID strategy may contribute to the pharmaceutical studies of PLAs and the possible prospects of other pharmaceutical excipients.

The diagnosis of chronic rhinosinusitis (CRS) is a complicated procedure. An electronic nose (eNose) is a novel method that detects disease from gas-phase mixtures, such as human breath. To determine whether an eNose based on differential mobility spectrometry (DMS) can detect chronic rhinosinusitis without nasal polyps (CRSsNP) by analyzing aspirated nasal air. Adult patients with CRSsNP were examined. The control group consisted of patients with septal deviation. Nasal air was aspirated into a collection bag and analyzed with DMS. The DMS data were classified using regularized linear discriminant analysis (LDA) models with 10-fold cross-validation. The accuracy of the DMS to distinguish CRSsNP from patients with septal deviation was 69%. Sensitivity and specificity were 67 and 70%, respectively. Bonferroni-corrected statistical differences were clearly noted. When a subgroup with more severe inflammatory disease was compared to controls, the classification accuracy increased to 82%. The results of this feasibility study demonstrate that CRSsNP can potentially be differentiated distinguished from patients with similar nasal symptoms by analyzing the aspirated nasal air using DMS. Further research is warranted to evaluate the ability of this novel method in the differential diagnostics of CRS. [ABSTRACT FROM AUTHOR]

Isocitrate dehydrogenase (IDH) mutation status is an important factor for surgical decision-making: patients with IDH-mutated tumors are more likely to have a good long-term prognosis, and thus favor aggressive resection with more survival benefit to gain. Patients with IDH wild-type tumors have generally poorer prognosis and, therefore, conservative resection to avoid neurological deficit is favored. Current histopathological analysis with frozen sections is unable to identify IDH mutation status intraoperatively, and more advanced methods are therefore needed. We examined a novel method suitable for intraoperative IDH mutation identification that is based on the differential mobility spectrometry (DMS) analysis of the tumor. We prospectively obtained tumor samples from 22 patients, including 11 IDH-mutated and 11 IDH wild-type tumors. The tumors were cut in 88 smaller specimens that were analyzed with DMS. With a linear discriminant analysis (LDA) algorithm, the DMS was able to classify tumor samples with 86% classification accuracy, 86% sensitivity, and 85% specificity. Our results show that DMS is able to differentiate IDH-mutated and IDH wild-type tumors with good accuracy in a setting suitable for intraoperative use, which makes it a promising novel solution for neurosurgical practice. [ABSTRACT FROM AUTHOR]

Peptide and protein O-glycosylation can occur mostly on any serine or threonine and could generate several positional isomers, which may coelute during liquid chromatography (LC) separation, challenging their characterization. Ion mobility has emerged as a technique of interest to separate isomeric compounds. In the different ion mobility techniques, differential ion mobility (DMS) includes the particular interest to tune ion separation by the possible addition of an organic modifier. Different microflow liquid chromatography coupled to mass spectrometry (μLC-MS) workflows were investigated for the analysis of a set of four model peptides made of three isomeric glycopeptides and a corresponding nonglycosylated peptide using differential mobility spectrometry (DMS), collision induced dissociation (CID), and electron capture dissociation (ECD). Neither DMS nor LC provided sufficient separation of the three isomeric O-glycopeptides while the nonmodified one was clearly separated by LC. The hyphenation of LC with DMS led to differentiating the three glycopeptides, and further detection and characterization (ECD/CID) with a chimeric collision cell were achieved in a single LC run. The position of the modification was determined from ECD data, while CID data characterized the sugar through its distinctive oxoniums ions in the low mass range. [ABSTRACT FROM AUTHOR]

The increasing number of breast cancer survivors and their longevity has emphasized the importance of esthetic and functional outcomes of cancer surgery and increased pressure for the surgical treatment to achieve negative margins with minimal removal of healthy tissue. Surgical smoke has been successfully utilized in tissue identification in laboratory conditions by using a system based on differential mobility spectrometry (DMS) that could provide a seamless margin assessment method. In this study, a DMS-based tissue analysis system was used intraoperatively in 20 breast cancer surgeries to assess its feasibility in tissue identification. The effect of the system on complications and duration of surgeries was also studied. The surgeries were recorded with a head-worn camera system for visual annotation of the operated tissue types to enable classification of the measurement files by supervised learning. There were statistically significant differences among the DMS spectra of the tissue types. The classification of four tissue types (skin, fat, glandular tissue, and connective tissue) yielded a cross-validated accuracy of 44% and exhibited high variation between surgeries. The low accuracies can be attributed to the limitations and uncertainty of the visual annotation, high-within class variance due to the heterogeneity of tissues as well as environmental conditions, and delays of the real-time analysis of the smoke samples. Differences between tissues encountered in breast surgery were identified and the technology can be implemented in surgery workflow. However, in its current state, the DMS-based system is not yet applicable to a clinical setting to aid in margin assessment.

Cardiolipins (CL) are special lipids in many respects. First of all, CL are composed of four fatty acids linked by two phosphatidic acids, which provide CL a unique molecular structure. Secondly, in eukaryotic cells they are specific to a single organelle, mitochondria, where they are also synthetized. CL are one of the most abundant lipid classes in mitochondria, mainly localized in the inner membrane. They are key determinants of mitochondrial health and homeostasis by modulating membrane integrity and fluidity, mitochondrial shapes, and metabolic pathways. Disturbances in mitochondrial CL composition can lead to tissue malfunction and diseases. It is therefore important to develop analytical tools to study the mitochondrial lipidome, and more particularly the CL. The method described here allows the quantification of cardiolipins at the sum composition level in isolated mitochondria or in liver tissue by flow injection analysis coupled to differential mobility spectrometry (FIA-DMS), also known as DMS-based shotgun lipidomics., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities.

The use of differential mobility spectrometry at low pressure coupled to liquid chromatography-mass spectrometry (LC-vDMS-MS) was investigated for the analysis of 13 drugs of abuse (DoA) including the following: cocaine, ecgonine methyl ester, cocaethylene, benzoylecgonine, norcocaine, tramadol, isomeric pairs of metabolites; O-desmethyl-cis-tramadol and N-desmethyl-cis-tramadol, and cannabinoids: Δ 9 -tetrahydrocannabinol, Δ 9 -tetrahydrocannabidiol, 11-hydroxy-Δ 9 -tetrahydrocannabinol, 11-nor-9carboxy-Δ 9 -tetrahydrocannabinol, and 11-nor-9carboxy-Δ 9 -tetrahydrocannabinol glucuronide. Different parameters were optimized for isomeric separation, such as LC mobile phase composition (20%-100% methanol acetonitrile and isopropanol, flow rate: 8-100 μL/min) and DMS separation voltage. Methanol and acetonitrile significantly affected the compensation voltage of the analytes and improved DMS separation. A short trap/elute LC-vDMS-SIM/MS screening method of 1 min was developed to quantify 11 drugs of abuse (except THC/CBD), in addition to a 4-min LC-vDMS-SIM/MS method to identify and quantify five cannabinoids including the isomers THC/CBD and three THC metabolites. THC is the principal psychoactive constituent of cannabis and is a controlled substance in comparison to its isomeric counterpart CBD; this highlights the importance and challenges to resolve these isomeric pairs by analytical techniques. The signal responses were linear over a concentration range of 0.005-10 μg/mL for the DoA and 1-1000 ng/mL for cannabinoids. The intraday and interday precision were better than 12.2% and accuracy better than 115%. Urine samples from subjects who tested positive for THC and/or cocaine during roadside drug testing were evaluated to assess the performance of the methods LC-vDMS-SIM/MS and LC-MRM/MS. Results show that the developed LC-vDMS-SIM/MS method presents similar performance to LC-MRM/MS with improved sample throughput., (© 2024 The Author(s). Drug Testing and Analysis published by John Wiley & Sons Ltd.)

The lipid composition of lipoprotein particles is determinative of their respective formation and function. In turn, the combination and correlation of nuclear magnetic resonance (NMR)-based lipoprotein measurements with mass spectrometry (MS)-based lipidomics is an appealing technological combination for a better understanding of lipid metabolism in health and disease. Here, we developed a combined workflow for subsequent NMR- and MS-based analysis on single sample aliquots of human plasma. We evaluated the quantitative agreement of the two platforms for lipid quantification and benchmarked our combined workflow. We investigated the congruence and complementarity between the platforms in order to facilitate a better understanding of patho-physiological lipoprotein and lipid alterations. We evaluated the correlation and agreement between the platforms. Next, we compared lipid class concentrations between healthy controls and rheumatoid arthritis patient samples to investigate the consensus among the platforms on differentiating the two groups. Finally, we performed correlation analysis between all measured lipoprotein particles and lipid species. We found excellent agreement and correlation (r > 0.8) between the platforms and their respective diagnostic performance. Additionally, we generated correlation maps detailing lipoprotein/lipid interactions and describe disease-relevant correlations.

[Display omitted] • Measurements of BPG are useful for screening for mast cell disorders. • DMS reduces interferences and discrepancies in fragment ion ratios. • Validation of BPG in urine demonstrated the viability of DMS for clinical testing. 2,3-dinor 11β-Prostaglandin F2α (BPG) is an arachidonic acid derivative and the most abundant metabolic byproduct of prostaglandin D2, which is released during mast cell activation. Therefore, measurements of BPG in urine using liquid chromatography-tandem mass spectrometry (LC-MS/MS) provide a noninvasive method for evaluation and management of mast cell disorders. Measurements obtained by LC-MS/MS exhibit a high prevalence of chromatographic interferences resulting in challenges with optimal determination of BGP. In this investigation, differential mobility spectrometry (DMS) is utilized to overcome the limitations of current testing. Urine samples were extracted using an automated solid-phase extraction method. Samples were then analyzed with and without DMS devices installed on two commercially available mass spectrometry platforms to assess the benefits of DMS. Following promising results from a preliminary analytical evaluation, LC-DMS-MS/MS measurements of BPG in urine were fully validated to assess the analytical implications of using this technology. The addition of DMS devices to the LC-MS/MS systems evaluated in this investigation significantly reduced interferences observed in the chromatograms. Concomitantly, DMS reduced the number of discordant quantifier/qualifier fragment ion results that significantly exceeded the ± 20 % limits, suggesting greater analytical specificity. The validation studies yielded low interday imprecision, with %CVs less than 6.5 % across 20 replicate measurements. Validation studies assessing other aspects of analytical performance also met acceptance criteria. Incorporating DMS devices greatly improved the specificity of BPG measurements by LC-MS/MS, as evidenced by the comparison of chromatograms and fragment ion results. Validation studies showed exceptional performance for established analytical metrics, indicating that this technology can be used to minimize the impact of interferences without adversely impacting other aspects of analytical or clinical performance. [ABSTRACT FROM AUTHOR]

Current methods for intraoperative surgical margin assessment are inadequate in terms of diagnostic accuracy, ease-of-use, and speed of analysis. Molecular analysis of tissues could potentially overcome these issues. A system based on differential ion mobility spectrometry (DMS) analysis of surgical smoke has been proposed as one potential method, but to date, it has been able to function in a relatively slow and heavily controlled manner that is inadequate for clinical use. In this study, we present an integrated sensor system that can measure a surgical smoke sample in seconds and relay the information of the tissue type to the user in near real time in simulated surgical use. The system was validated by operating porcine adipose tissue and muscle tissue. The differentiation of these tissues based on their surgical smoke profile with a cross-validated linear discriminant analysis model produced a classification accuracy of 93.1% (N = 1059). The measurements were also classified with a convolutional neural network model, resulting in a classification accuracy of 93.2%. These results indicate that the DMS-based smoke analysis system is capable of rapid tissue identification from surgical smoke produced in freehand surgery. [ABSTRACT FROM AUTHOR]

The separation and analysis of chiral compounds, especially enantiomers, presents a great challenge to modern analytical chemistry, particularly to mass spectrometry (MS). As a result, integrated orthogonal separations, such as chiral liquid chromatography (chiral LC), gas chromatography (GC), or capillary electrophoresis (CE), are often employed to separate enantiomers prior to MS analysis. Here, we combine chemical derivatization with differential mobility spectrometry (DMS) and MS to separate and quantitate the transformed enantiomeric pairs R‐ and S‐amphetamine, as well as R‐ and S‐methamphetamine. We also demonstrate separation of these drugs by using reverse‐phase LC. However, while the LC method requires ∼5 min to provide separation, we have developed a flow‐injection analysis (FIA) method using DMS as the exclusive mode of separation (FIA‐DMS), requiring only ∼1.5 min with equivalent quantitative metrics (1‐1000 ng/mL range) to the LC method. The DMS‐based separation of each diastereomeric pair is driven by differences in binding energies between the analyte ions and the chemical modifier molecules (acetonitrile) added to the DMS environment. [ABSTRACT FROM AUTHOR]

Differential Mobility Spectrometry (DMS), also called as FAIMS is a variation of atmospheric pressure ion mobility measurement techniques and is capable of providing information about the electric field - mobility dependence of ions. In this method, a combined electric field is used. This field consists of asymmetric oscillating electric field of high intensity and low static field component. Analytical information in DMS is 2-dimensional dependence of ionic current on oscillating field amplitude and the value of static field intensity. The measurement of DMS signal for whole ranges of both variables is time consuming and also generates lot of data. It is a disadvantage of DMS method, which limits the use of this otherwise powerful technology in real time applications that require a response time of few seconds. This paper presents a way to limit measurement time by heuristic knowledge of the properties of the data space and another method based on the concept of Shannon Entropy to find operating parameters satisfying both separation and signal to noise ratio requirements. [ABSTRACT FROM AUTHOR]

Analysis of volatile organic compounds (VOCs) can be an effective strategy to inspect the quality of horticultural commodities and following their degradation. In this work, we report that VOCs emitted by walnuts can be studied using gas chromatography-differential mobility spectrometry (GC-DMS), and those GC-DMS data can be analyzed to predict the rancidity of walnuts, i.e., classify walnuts into grades of freshness. Walnut kernels were assigned a class n depending on their level of freshness as determined by a peroxide assay. VOC samples were analyzed using GC-DMS. From these VOC data, a partial least square regression (PLSR) model provided a freshness prediction value m , which corresponded to the rancid class n when m = n ± 0.5 . The PLSR model had an accuracy of 80% to predict walnut grade and demonstrated a minimal root mean squared error of 0.42 for the m response variables (representative of walnut grade) with the GC-DMS data. We also conducted gas chromatography-mass spectrometry (GC-MS) experiments to identify volatiles that emerged or were enhanced with more rancid walnuts. The findings of the GC-MS study of walnut VOCs align excellently with the GC-DMS study. Based on our results, we conclude that a GC-DMS device deployed with a pre-trained machine learning model can be a very effective device for classifying walnut grades in the industry.

Up-front CID fragmentation is a phenomenon where molecular ions are activated and fragment as they enter the atmosphere-to-vacuum region of the mass spectrometer, and consequently can complicate the mass spectra and their analysis. This phenomenon can be minimized by controlling the voltages on lens/optic elements where ions are sampled from the atmospheric region, but this approach can also have a negative effect on overall ion sensitivity. In this study, we introduce gas-phase modifiers (acetonitrile, acetone, cyclohexane, water, and methanol) to the curtain gas to mitigate up-front CID fragmentation. These modifiers cluster with incoming ions, increasing the energy barrier to fragmentation and consequently reducing the complexity of mass spectra. The clustering is monitored by differential mobility spectrometry-mass spectrometry (DMS-MS) and precursor mass spectrum-scanning. Unlike typical singly charged species, peptide ion-modifier clusters were found to survive through the atmosphere-to-vacuum interface of the mass spectrometer, showing that highly charged peptides cluster most strongly with acetonitrile and acetone. In addition, when peptides cluster with acetonitrile, they produce a large increase in signal intensity for the most highly charged and fragile ions. This results in a significant reduction, up to 90% with some modifiers, in up-front CID fragmentation for these fragile highly charged peptides, increasing the overall analytical sensitivity and decreasing the limits of detection by up to 82% depending on the analyte. The proposed technique has no significant detrimental effect on the peptide mass fingerprinting of a BSA or mAb protein digest, but it does reduce the amount of redundant and data-deficient spectra needed to produce adequate sequence coverage using information-dependent acquisition methods by ~ 40%. We propose that this technique could have a benefit in the fields of proteomics and peptidomics where up-front CID fragmentation and chemical noise routinely mask targets of biological importance. [ABSTRACT FROM AUTHOR]

Differential mobility spectrometry (DMS) has been gaining popularity in small molecule analysis over the last few years due to its selectivity towards a variety of isomeric compounds. While DMS has been utilized in targeted liquid chromatography-mass spectrometry (LC-MS), its use in untargeted discovery workflows has not been systematically explored. In this contribution, we propose a novel workflow for untargeted metabolomics based solely on DMS separation in a clinically relevant chronic kidney disease (CKD) patient population. We analyzed ten plasma samples from early- and late-stage CKD patients. Peak finding, alignment, and filtering steps performed on the DMS-MS data yielded a list of 881 metabolic features (unique mass-to-charge and migration time combinations). Differential analysis by CKD patient group revealed three main features of interest. One of them was putatively identified as bilirubin based on high-accuracy MS data and comparison of its optimum compensation voltage (COV) with that of an authentic standard. The DMS-MS analysis was four times faster than a typical HPLC-MS run, which suggests a potential for the utilization of this technique in screening studies. However, its lower separation efficiency and reduced signal intensity make it less suitable for low-abundant features. Fewer features were detected by the DMS-based platform compared with an HPLC-MS-based approach, but importantly, the two approaches resulted in different features. This indicates a high degree of orthogonality between HPLC- and DMS-based approaches and demonstrates the need for larger studies comparing the two techniques. The workflow described here can be adapted for other areas of metabolomics and has a value as a prescreening method to develop semi-targeted workflows and as a faster alternative to HPLC in large biomedical studies. [ABSTRACT FROM AUTHOR]

Metabolomics strongly relies on liquid chromatography hyphenated to tandem mass spectrometry (LC-MS/MS) for the separation and identification of metabolites. Retention times and fragmentation mass spectra are used as identification parameters. A complementary approach is proposed here based on alternative approaches for both the separation and identification, and is illustrated in the case of isomeric forms of aminobutyric acids (C 4 H 9 NO 2). Differential mobility spectrometry (DMS), a very efficient method for the separation of isomers of small molecules, is coupled with high resolution tandem mass spectrometry Fourier transform ion cyclotron resonance (FT-ICR). Identification of the DMS peaks associated with the various isomers is based on isomer-specific infrared multiple photon dissociation (IRMPD) in the mid-infrared range. Two operation modes of the DMS-MS/MS(IRMPD) are used. Structural identification of the various isomers is first achieved based on the comparison of IRMPD spectra of DMS- and mass-selected ions with IR absorption spectra of candidate structures derived from quantum chemical calculations. For this purpose, the DMS device is used in selective mode. Alternatively, when the DMS is using in scanning mode, identification can also be achieved based on specific depletion of DMS peaks at selected IR wavelength. These two operation modes for identification of isomers are illustrated in conjunction with the use of modifier-assisted DMS separation. Image 1 • First coupling of DMS and IRMPD spectroscopy with high resolution FT-ICR mass spectrometry. • Two DMS-MS/MS(IRMPD) workflows are illustrated for the structural assignment of DMS peaks associated with three isomers. • Peak assignment and structural identification is performed through IRMPD spectroscopy of DMS- and mass-selected ions. • Peak assignment and structural characterization can also be based on selected DMS peak depletion at selected IR wavelengths. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • A Hybrid Flowing Atmospheric PressureAfterglow(FAPA)-Differential Mobility Spectrometry (DMS) device is constructed. • Cobalt and nickel acetylacetonate complexes are deposited on mesh substrates for solid surface analysis by FAPA-DMS. • Rapid separation is achieved between complexes with different oxidation states. • FAPA-DMS permits speciation in a binary mixture of isobaric complexes of metal acetylacetonates. • FAPA-DMS demonstrates quantitative analysis of nickel acetylacetonate. Abstract Metal-ligand complexes are important analytical targets across environmental, industrial, security, and biological investigations. The various complex forms of these species calls for analytical techniques that can selectively detect them in their native (in-situ) environment. Fieldable screening technologies based on portable mass spectrometry (MS) require simplified sample-preparation and ionization methods. Therefore, various direct ambient desorption/ionization sampling methods, such as the flowing atmospheric-pressure afterglow (FAPA), are of high interest as portable tools and possess the capability to desorb/ionize complexed elemental species. With such sample introduction, matrix from ambient chemicals may interfere with the analyte of interest leading to false-positive detection. Differential mobility spectrometry (DMS) can provide additional post-ionization separation and reduction of interferences. Herein, we explore coupling a FAPA desorption/ionization source with DMS for the first time for metal-ion speciation. The FAPA-DMS hybrid was used for separation and detection of individual ionic species from cobalt and nickel complexes with acetylacetonate in standard mixtures. We observe a concentration dependence of the DMS separation in mixtures. Altered DMS dispersion behavior is attributed to high concentrations of desorbed neutral complexes acting as a gas-phase modifier. For the case of Ni(AcAc) 2 , solutions deposited from 100 to 1000 μg/mL exhibit good linearity when the DMS is employed. The results described herein suggest a method which may be used in in situ applications for inorganic complex analyses. [ABSTRACT FROM AUTHOR]

Abstract Electron capture detectors (ECDs) and detectors used in ion mobility spectrometry (IMS) have been successfully used for the detection of numerous compounds including hazardous substances. The general principles of their operations are similar and based on sample component ionization and measurement of the signal using the differences in the mobility of electric charge carriers. Differences in sensitivity result from various parameters of these instruments. Value of electric field intensity in ionic reactors have an influence on ionization process. The main goal of the performed tests was to compare the analytical properties of ECD and two types of IMS detectors: a drift tube spectrometer (DT IMS) and a differential mobility spectrometer (DMS). In the work performed, the efficiency of ionization and the response of detectors to selected analytes were compared. ECD, DT IMS and DMS were equipped with 63-Ni radioactive sources. Analytes have been ionized via electron capture process or dissociative electron transfer. Results obtained for oxygen and chloro-substituted organic compounds (carbon tetrachloride, benzyl chloride, chloroform, 2-chloroethyl ethyl sulfide) were used to calculate the relative signal and to compare the ionization efficiency for three detectors. The phenomena observed experimentally were related to energy dependencies and electron capture cross-sections of analytes. The efficiency of ionization in DT IMS was also compared for electron capture when nitrogen was used as the carrier gas, and when the ionization process was based on the collisions of the analyte molecules with the O 2 - with the use of air. Graphical abstract fx1 Highlights • Electron capture is effective method of ionization in ion mobility spectrometry. • Different types of detectors are compared. • Limits of detection of below 1 ppb level are achieved. • Electron energy is the factor determining ionization efficiency. • In some cases dissociative charge transfer is the effective way for ionization. [ABSTRACT FROM AUTHOR]

Introduction: Steroid measurements are important for diagnosis and monitoring of many conditions and treatment regiments; however, due to structural and chemical similarities amongst steroids, these analyses are challenging, even for highly specific techniques such as liquid chromatography-tandem mass spectrometry (LC-MS/MS). Differential mobility spectrometry (DMS) has the potential to improve these analyses by providing an orthogonal and complementary separation technique., Methods: Initially, the potential for DMS to improve signal-to-noise ratio (S/N) and reduce interference was tested by comparing chromatograms acquired with and without DMS when performing measurements of six different steroids. Subsequently, a full clinical validation of cortisol and cortisone in urine was performed with the LC-DMS-MS/MS method., Results and Discussion: DMS significantly reduced interferences observed in the chromatograms and boosted S/N by between 1.6 and 13.8 times. Additionally, DMS improved the agreement between quantifier/qualifier fragment ion results for cortisol and cortisone as indicated by the increase in R 2 from approximately 0.81 to 0.98. All validation studies met acceptance criteria and we observed exceptional analytical performance in terms of precision, with % CVs less than 8%., Conclusions: DMS improved the specificity of the steroid measurements by reducing interferences and improving S/N. The validation studies prove that these benefits did not come at the expense of other aspects of analytical performance. This study indicates that DMS has the potential to benefit not just clinical measurements of challenging analytes, but many clinical LC-MS/MS analyses., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 THE AUTHORS.)

Currently, the measure of the oxidative stress, from oxidized and reduced glutathione (GSSG and GSH respectively), for large cohorts of samples, is generally limited to spectrometric methods. In this study, a high-throughput assay for GSH after derivatization with N-ethylmaleimide and GSSG in blood sample was developed with an analysis time of 1.5 min. The method combines protein precipitation and a short LC (10-mm length) column where compounds were trapped in front-flush mode and eluted in back-flush mode. This setup is combined with modifier-assisted differential ion mobility spectrometry (DMS, SelexIon) and detection is performed in the selected reaction monitoring mode using positive electrospray ionization. In DMS, various modifiers were investigated including N2, methanol, toluene, ethanol, acetonitrile, and isopropanol to improve assay selectivity. Using EtOH as modifier, the limit of quantification (LOQ) was found to be 0.4 μM for GSSG and 3.2 μM for GS-N-ethylmaleimide (NEM) using a blood volume of 60 μL. The method is linear over a wide dynamic concentration range of 0.4 to 400 μM for GSSG and from 3.2 to 3200 μM for GS-NEM. The inter-assay precision of QC samples were ≤ 6.7%, with accuracy values between 98.3 and 103%. The method was further cross-validated with a LC Hypercarb-DMS-MS/MS method by the analysis of human blood samples. The bias between both assays ranged from − 0.3 to 0.2%.ᅟ [ABSTRACT FROM AUTHOR]

Highlights • Compact, transportable analytical system comprising three detectors coupled to a micromachined gas chromatograph. • Universal and selective detectors provide enhanced selectivity, sensitivity, and confirmatory capability. • Relevant and difficult analyses of volatile organic compounds are demonstrated. Abstract An effective analytical strategy for targeted analysis of volatile organic compounds which combines two orthogonal separation mechanisms and multiple tunable detection in a compact transportable analytical system is introduced. This strategy uses a commercially available micromachined gas chromatograph comprising a micromachined on-board thermal conductivity detector. The chromatograph capability is enhanced by incorporating a modified diode array detector and a radio frequency modulated ion mobility spectrometry microfabricated electromechanical system. The analytical platform offers powerful detection capabilities of individual compounds and various classes of volatile organic compounds with improved provisional confirmatory capability. The transportable micromachined gas chromatograph employs field replaceable conventional capillary columns for the separation of analytes. The use of a silicon micromachined sample introduction device affords fast injection to minimize band broadening with fast chromatographic separation rendered in the order of minutes. Advantaged synergy also includes leveraging the resolving power of gas chromatography to minimize charge exchange in the ionization chamber of the differential mobility spectrometer for improved detector performance. Performance of this scalable and transportable analytical system is demonstrated with relevant volatile compounds such as acetaldehyde, acetone, carbon disulfide, benzene, and ethyl butyrate having a day-to-day variability less than 5% and with a high degree of reliability. [ABSTRACT FROM AUTHOR]

Acute rhinosinusitis (ARS) is a sudden, symptomatic inflammation of the nasal and paranasal mucosa. It is usually caused by respiratory virus infection, but bacteria complicate for a small number of ARS patients. The differential diagnostics between viral and bacterial pathogens is difficult and currently no rapid methodology exists, so antibiotics are overprescribed. The electronic nose (eNose) has shown the ability to detect diseases from gas mixtures. Differential mobility spectrometry (DMS) is a next-generation device that can separate ions based on their different mobility in high and low electric fields. Five common rhinosinusitis bacteria (Streptococcus pneumoniae, Haemophilus influenzae, Moraxella catarrhalis, Staphylococcus aureus, and Pseudomonas aeruginosa) were analysed in vitro with DMS. Classification was done using linear discriminant analysis (LDA) and k-nearest neighbour (KNN). The results were validated using leave-one-out cross-validation and separate train and test sets. With the latter, 77% of the bacteria were classified correctly with LDA. The comparative figure with KNN was 79%. In one train-test set, P. aeruginosa was excluded and the four most common ARS bacteria were analysed with LDA and KNN; the correct classification rate was 83 and 85%, respectively. DMS has shown its potential in detecting rhinosinusitis bacteria in vitro. The applicability of DMS needs to be studied with rhinosinusitis patients. [ABSTRACT FROM AUTHOR]

A method combining field asymmetric waveform ion mobility spectrometry with liquid chromatography-mass spectrometry (LC-FAIMS-MS) has been developed for the analysis of the oxypurine compounds hypoxanthine (HX) and xanthine (XA) in saliva. Separation of the oxypurines from interfering matrix components was investigated using FAIMS-MS. The selected FAIMS parameters were then applied to the rapid LC-FAIMS-MS analysis of HX and XA using a short chromatographic separation method (7 min). A comparison of the LC-MS method with and without FAIMS applied, resulted in improved discrimination from saliva matrix interferences and improved chromatographic peak integration for both HX and XA using a FAIMS separation. A quantitative evaluation of the LC-FAIMS-MS method was performed giving limits of detection of 2.0 ng mL−1 for HX and 1.8 ng mL−1 for XA, and limits of quantification of 6.6 ng mL−1 for HX and 6.0 ng mL−1 for XA. The developed LC-FAIMS-MS method was applied to the targeted analysis of the oxypurine metabolites in saliva collected from healthy male athletes (n = 11) before and after exercise designed to induce oxidative stress; post-exercise collection time-points included immediately after exercise, one hour and twenty-four hours’ post-exercise. The salivary concentrations of both HX and XA were lower after physical exercise, compared to the pre-exercise (rest) concentrations and returned to approximately pre-exercise levels after twenty-four hours. The method reported has the potential for monitoring the salivary oxypurines, HX and XA, as biomarkers of oxidative stress and in other clinical applications. [ABSTRACT FROM AUTHOR]

Differential mobility spectrometry (DMS) is a method for identification of ions based on the nonlinear dependence of ion velocity on electric field intensity. The most important parameters characterising sensitivity and selectivity of DMS detectors are signal intensity, position of the peak in the DMS spectrum and the width of the peak. These parameters depend on the detector construction and on its control method. The shape and amplitude of the supplying (separation) voltage waveform are also very important. In this work, four different models of a DMS detector are studied. The models are based on simple algebra, partial differential equations, finite elements method and a statistical approach. All considered models give an opportunity for determining the key DMS parameters. Theoretical data are compared with the results of measurements performed with a detector of a simple structure for which tuning the parameters of separation voltage is possible. [ABSTRACT FROM AUTHOR]

High-throughput methods to assess radiation exposure are a priority due to concerns that include nuclear power accidents, the spread of nuclear weapon capability, and the risk of terrorist attacks. Metabolomics, the assessment of small molecules in an easily accessible sample, is the most recent method to be applied for the identification of biomarkers of the biological radiation response with a useful dose-response profile. Profiling for biomarker identification is frequently done using an LC-MS platform which has limited throughput due to the time-consuming nature of chromatography. We present here a chromatography-free simplified method for quantitative analysis of seven metabolites in urine with radiation dose-response using urine samples provided from the Pannkuk et al. (2015) study of long-term (7-day) radiation response in nonhuman primates (NHP). The stable isotope dilution (SID) analytical method consists of sample preparation by strong cation exchange-solid phase extraction (SCX-SPE) to remove interferences and concentrate the metabolites of interest, followed by differential mobility spectrometry (DMS) ion filtration to select the ion of interest and reduce chemical background, followed by mass spectrometry (overall SID-SPE-DMS-MS). Since no chromatography is used, calibration curves were prepared rapidly, in under 2 h (including SPE) for six simultaneously analyzed radiation biomarkers. The seventh, creatinine, was measured separately after 2500× dilution. Creatinine plays a dual role, measuring kidney glomerular filtration rate (GFR), and indicating kidney damage at high doses. The current quantitative method using SID-SPE-DMS-MS provides throughput which is 7.5 to 30 times higher than that of LC-MS and provides a path to pre-clinical radiation dose estimation.Graphical Abstract [ABSTRACT FROM AUTHOR]

The protonated nucleobases (C + H) + , (T + H) + , (U + H) + , (A + H) + , and (G + H) + are investigated in a combined experimental and computational study using differential mobility spectrometry (DMS), mass spectrometry, and electronic structure calculations. DMS is used to isolate individual tautomeric forms for each protonated nucleobase prior to characterization with HDX or CID. The population distributions of each protonated nucleobase formed by electrospray ionization (ESI) are dominated by a single tautomeric form, as is predicted by our calculations. However, all nucleobases present additional tautomers upon ESI, with these minor contributions to the ensemble populations attributed to additional higher energy metastable species. In addition to the tautomer-derived species, additional ion signals in the DMS data are attributed to larger nucleobase-containing clusters, which fragment post-DMS to yield bare ion and fragment ion signals that are consistent with those expected for the bare protonated nucleobases. Contributions from larger clustered species are instead distinguished by monitoring DMS ion signal as declustering potential voltages are ramped. [ABSTRACT FROM AUTHOR]

Metabolomics applications of differential mobility spectrometry (DMS)-mass spectrometry (MS) have largely concentrated on targeted assays and the removal of isobaric or chemical interferences from the signals of a small number of analytes. In the work reported here, we systematically investigated the application range of a DMS-MS method for metabolomics using more than 800 authentic metabolite standards as the test set. The coverage achieved with the DMS-MS platform was comparable to that achieved with chromatographic methods. High orthogonality was observed between hydrophilic interaction liquid chromatography and the 2-propanol-mediated DMS separation, and previously observed similarities were confirmed for the DMS platform and reversed-phase liquid chromatography. We describe the chemical selectivity observed for selected subsets of the metabolite test set, such as lipids, amino acids, nucleotides, and organic acids. Furthermore, we rationalize the behavior and separation of isomeric aromatic acids, bile acids, and other metabolites.Differential mobility spectrometry-mass spectrometry (DMS-MS) facilitates rapid separation of metabolites of similar mass-to-charge ratio by distributing them across the compensation voltage range on the basis of their different molecular structures. [ABSTRACT FROM AUTHOR]

Eptifibatide is a therapeutic cyclic peptide with poor collision-induced dissociation (CID) efficiency for multiple reaction monitoring (MRM), which limits the development of a traditional liquid chromatography-tandem mass spectrometry (LC–MS/MS) bioassay with MRM. In this study, a method combining differential mobility spectrometry (DMS) with liquid chromatography-multiple ion monitoring (LC-DMS-MIM) was developed for the quantitation of eptifibatide in rat plasma. After solid phase extraction (SPE) of 100 μL plasma on an Oasis ® HLB cartridge, the analyte and I.S. (octreotide) were analyzed using a SCIEX QTRAP 6500 operated in the positive ion mode and preceded by a DMS device. The lower limit of quantitation (LLOQ) for eptifibatide was 0.5 ng/mL using only 100 μL plasma. The method was linear in the concentration range 0.5–300 ng/mL with good precision and accuracy. Compared to regulated quantitative LC–MS/MS bioanalysis of eptifibatide, the LC-DMS-MIM method effectively overcomes the sensitivity challenge in the LC-MRM method and reduces the high background noise and matrix interference in LC-MIM method without DMS. The method was successfully applied to a pharmacokinetic study involving intravenous injection of eptifibatide to Wistar rats. [ABSTRACT FROM AUTHOR]

Because many therapeutic agents are contaminated by epimeric impurities or form epimers as a result of metabolism, analytical tools capable of determining epimers are increasingly in demand. This article is a proof-of-principle report of a novel DMS–MS/MS method to separate and simultaneously quantify epimers, taking PGF2 α and its 8-epimer, 8- iso -PGF2 α , as an example. Good accuracy and precision were achieved in the range of 10–500 ng/mL with a run time of only 1.5 min. Isopropanol as organic modifier facilitated a good combination of sensitivity and separation. The method is the first example of the quantitation of epimers without chromatographic separation. [ABSTRACT FROM AUTHOR]

• pyrrolizidine alkaloids using differential mobility spectrometry (vDMS-MS) at low pressure. • LC-DMS-SIM/MS (vDMS) with a short LC column in trap/elute mode. • LC-vDMS-SIM/MS versus LC-MRM/MS and SFC-MRM/MS assays. • Combination of supercritical fluid chromatography with vDMS-MS. The benefit of combining liquid chromatography (LC), supercritical fluid chromatography (SFC) and vacuum Differential Mobility Spectrometry – Mass Spectrometry (vDMS-MS) was investigated for the analysis of fourteen diastereomeric pyrrolizidine alkaloids (PA); intermedine, echinatine, lycopsamine, indicine, intermedine-N-oxide, echinatine-N-oxide, indicine-N-oxide, lycopsamine-N-oxide, senecivernine, senecionine, jacobine, senecivernine-N-oxide, senecionine-N-oxide, retrorsine. The mobile phase composition (15–100% MeOH and ACN), flow rate (8–100 µL/min), vDMS cell pressure, and F value showed an effect on the mobility behavior of the analytes. At 15% MeOH with a flow rate of 100 µL/min and 33 mbar vDMS pressure, 8 out 14 PA could be partially or totally separated by vDMS-MS. As well as providing an additional separation dimension vDMS improved the selectivity and a 5-minute assay method was developed for the quantification of 10 out of 14 single diastereomeric PA in tea samples, using a short LC column-switching and hyphenated to vDMS-MS in the selected ion monitoring mode. The performance of the method was found to be comparable with a 12-minute standard LC-MS/MS method using detection in the selected reaction monitoring mode. Additionally, the combination of vDMS and SFC-MS was investigated and suggests that the mixture of CO 2 /MeOH influences the CV shifting of the PA to more negative compensation voltage, and the signal-to-noise ratio is improved by a factor of three compared to SFC-MS without vDMS. [ABSTRACT FROM AUTHOR]