Field Asymmetric Ion Mobility Spectrometry Research Articles

Non-Invasive Diagnosis of Diabetes by Volatile Organic Compounds in Urine Using FAIMS and Fox4000 Electronic Nose

The electronic nose (eNose) is an instrument designed to mimic the human olfactory system. Usage of eNose in medical applications is more popular than ever, due to its low costs and non-invasive nature. The eNose sniffs the gases and vapours that emanate from human waste (urine, breath, and stool) for the diagnosis of variety of diseases. Diabetes mellitus type 2 (DM2) affects 8.3% of adults in the world, with 43% being underdiagnosed, resulting in 4.9 million deaths per year. In this study, we investigated the potential of urinary volatile organic compounds (VOCs) as novel non-invasive diagnostic biomarker for diabetes. In addition, we investigated the influence of sample age on the diagnostic accuracy of urinary VOCs. We analysed 140 urine samples (73 DM2, 67 healthy) with Field-Asymmetric Ion Mobility Spectrometry (FAIMS); a type of eNose; and FOX 4000 (AlphaM.O.S, Toulouse, France). Urine samples were collected at UHCW NHS Trust clinics over 4 years and stored at −80 °C within two hours of collection. Four different classifiers were used for classification, specifically Sparse Logistic Regression, Random Forest, Gaussian Process, and Support Vector on both FAIMS and FOX4000. Both eNoses showed their capability of diagnosing DM2 from controls and the effect of sample age on the discrimination. FAIMS samples were analysed for all samples aged 0–4 years (AUC: 88%, sensitivity: 87%, specificity: 82%) and then sub group samples aged less than a year (AUC (Area Under the Curve): 94%, Sensitivity: 92%, specificity: 100%). FOX4000 samples were analysed for all samples aged 0–4 years (AUC: 85%, sensitivity: 77%, specificity: 85%) and a sub group samples aged less than 18 months: (AUC: 94%, sensitivity: 90%, specificity: 89%). We demonstrated that FAIMS and FOX 4000 eNoses can discriminate DM2 from controls using urinary VOCs. In addition, we showed that urine sample age affects discriminative accuracy.

LESA MS Imaging of Heat-Preserved and Frozen Tissue: Benefits of Multistep Static FAIMS.

We have previously demonstrated liquid extraction surface analysis (LESA) high field asymmetric waveform ion mobility spectrometry (FAIMS) mass spectrometry imaging of proteins in thin tissue sections of brain and liver. Here, we present an improved approach that makes use of multiple static FAIMS parameters at each sampled location and allows a significant improvement in the number of proteins, lipids, and drugs that can be imaged simultaneously. The approach is applied to the mass spectrometry imaging of control and cassette-dosed rat kidneys. Mass spectrometry imaging of kidneys typically requires washing to remove excess hemoglobin; however, that is not necessary with this approach. Multistep static FAIMS mass spectrometry resulted in a 6- to 16-fold increase in the number of proteins detected in the absence of FAIMS, in addition to smaller increases over single step static FAIMS (chosen for optimum transmission of total protein ions). The benefits of multistep static FAIMS mass spectrometry for protein detection are also shown for sections of testes. The numbers of proteins detected following multistep FAIMS increased between 2- and 3-fold over single step FAIMS and between 2- and 14-fold over LESA alone. Finally, to date, LESA mass spectrometry of proteins in tissue has been undertaken solely on fresh frozen samples. In this work, we demonstrate that heat-preserved tissues are also suitable for these analyses. Heat preservation of tissue improved the number of proteins detected by LESA MS for both kidney and testes tissue (by between 2- and 4-fold). For both tissue types, the majority of the proteins additionally detected in the heat-treated samples were subsequently detected in the frozen samples when FAIMS was incorporated. Improvements in the numbers of proteins detected were observed for LESA FAIMS MS for the kidney tissue; for testes tissue, fewer total proteins were detected following heat preservation; however, approximately one-third were unique to the heat-preserved samples.

A Novel Differential Ion Mobility Device Expands the Depth of Proteome Coverage and the Sensitivity of Multiplex Proteomic Measurements

The depth of proteomic analyses is often limited by the overwhelming proportion of confounding background ions that compromise the identification and quantification of low abundance peptides. To alleviate these limitations, we present a new high field asymmetric waveform ion mobility spectrometry (FAIMS) interface that can be coupled to the Orbitrap Tribrid mass spectrometers. The interface provides several advantages over previous generations of FAIMS devices, including ease of operation, robustness, and high ion transmission. Replicate LC-FAIMS-MS/MS analyses (n = 100) of HEK293 protein digests showed stable ion current over extended time periods with uniform peptide identification on more than 10,000 distinct peptides. For complex tryptic digest analyses, the coupling of FAIMS to LC-MS/MS enabled a 30% gain in unique peptide identification compared with non-FAIMS experiments. Improvement in sensitivity facilitated the identification of low abundance peptides, and extended the limit of detection by almost an order of magnitude. The reduction in chimeric MS/MS spectra using FAIMS also improved the precision and the number of quantifiable peptides when using isobaric labeling with tandem mass tag (TMT) 10-plex reagent. We compared quantitative proteomic measurements for LC-MS/MS analyses performed using synchronous precursor selection (SPS) and LC-FAIMS-MS/MS to profile the temporal changes in protein abundance of HEK293 cells following heat shock for periods up to 9 h. FAIMS provided 2.5-fold increase in the number of quantifiable peptides compared with non-FAIMS experiments (30,848 peptides from 2,646 proteins for FAIMS versus 12,400 peptides from 1,229 proteins with SPS). Altogether, the enhancement in ion transmission and duty cycle of the new FAIMS interface extended the depth and comprehensiveness of proteomic analyses and improved the precision of quantitative measurements.

An improved machine learning pipeline for urinary volatiles disease detection: Diagnosing diabetes.

MotivationThe measurement of disease biomarkers in easily–obtained bodily fluids has opened the door to a new type of non–invasive medical diagnostics. New technologies are being developed and fine–tuned in order to make this possibility a reality. One such technology is Field Asymmetric Ion Mobility Spectrometry (FAIMS), which allows the measurement of volatile organic compounds (VOCs) in biological samples such as urine. These VOCs are known to contain a range of information on the relevant person’s metabolism and can in principle be used for disease diagnostic purposes. Key to the effective use of such data are well–developed data processing pipelines, which are necessary to extract the most useful data from the complex underlying biological structure.ResultsIn this study, we present a new data analysis pipeline for FAIMS data, and demonstrate a number of improvements over previously used methods. We evaluate the effect of a series of candidate operational steps during data processing, such as the use of wavelet transforms, principal component analysis (PCA), and classifier ensembles. We also demonstrate the use of FAIMS data in our pipeline to diagnose diabetes on the basis of a simple urine sample using machine learning classifiers. We present results for data generated from a case-control study of 115 urine samples, collected from 72 type II diabetic patients, with 43 healthy volunteers as negative controls. The resulting pipeline combines the steps that resulted in the best classification model performance. These include the use of a two–dimensional discrete wavelet transform, and the Wilcoxon rank–sum test for feature selection. We are able to achieve a best ROC curve AUC of 0.825 (0.747–0.9, 95% CI) for classification of diabetes vs control. We also note that this result is robust to changes in the data pipeline and different analysis runs, with AUC > 0.80 achieved in a range of cases. This is a substantial improvement in performance over previously used data processing methods in this area. Our ability to make strong statements about FAIMS ability to diagnose diabetes is sadly limited, as we found confounding effects from the demographics when including these data in the pipeline. The demographics alone produced a best AUC of 0.87 (0.795–0.94, 95% CI). While the combination of the demographics and FAIMS data resulted in an improvement on the AUC (0.907; 0.848–0.97, 95% CI), it did not prove to be a significant difference. Nevertheless, the pipeline itself shows a significant improvement in performance over more basic methods which have been used with FAIMS data in the past.

FAIMS analysis of urine gaseous headspace is capable of differentiating ovarian cancer

AimWe hypothesized that field asymmetric waveform ion mobility spectrometry (FAIMS) as a novel artificial olfactory technology could differentiate urine of women with malignant ovarian tumors from controls and women with benign tumors, based on previous findings on the ability of canine olfactory system to “smell” cancer. Patients and methodsPreoperative urine samples from 51 women with ovarian tumors, both benign and malignant, and from 18 women with genital prolapse, as controls, were collected. The samples were analyzed by FAIMS device. Data analysis was processed by quadratic data analysis (QDA) and linear discriminant analysis (LDA), and cross-validated using 10-fold cross-validation. ResultsThirty-three women had malignant ovarian tumors, of which 18 were high-grade cancers. FAIMS distinguished controls from malignancies with the accuracy of 81.3% (sensitivity 91.2% and specificity 63.1%), and benign tumors from malignancies with the accuracy of 77.3% (sensitivity 91.5% and specificity 51.4%). Moreover, low grade tumors were also separated from high grade cancers and benign ovarian tumors with accuracies of 88.7% (sensitivity 87.8% and specificity 89.6%) and 83.9% (sensitivity 73.1% and specificity 92.9%), respectively. ConclusionsThis proof of concept-study indicates that the FAIMS from urine has potential to discriminate malignant ovarian tumors from no tumor-bearing controls and benign tumors.

Non-Invasive Detection of Anastomotic Leakage Following Esophageal and Pancreatic Surgery by Urinary Analysis

Background: Esophagectomy or pancreaticoduodenectomy is the standard surgical approach for patients with tumors of the esophagus or pancreatic head. Postoperative mortality is strongly correlated with the occurrence of anastomotic leakage (AL). Delay in diagnosis leads to delay in treatment, which ratifies the need for development of novel and accurate non-invasive diagnostic tests for detection of AL. Urinary volatile organic compounds (VOCs) reflect the metabolic status of an individual, which is associated with a systemic immunological response. The aim of this study was to determine the diagnostic accuracy of urinary VOCs to detect AL after esophagectomy or pancreaticoduodenectomy. Methods: In the present study, urinary VOCs of 63 patients after esophagectomy (n = 31) or pancreaticoduodenectomy (n = 32) were analyzed by means of field asymmetric ion mobility spectrometry. AL was defined according to international study groups. Results: AL was observed in 15 patients (24%). Urinary VOCs of patients with AL after pancreaticoduodenectomy could be distinguished from uncomplicated controls, area under the curve 0.85 (95% CI 0.76–0.93), sensitivity 76%, and specificity 77%. However, this was not observed following esophagectomy, area under the curve 0.51 (95% CI 0.37–0.65). Conclusion: In our study population AL following pancreaticoduodenectomy could be discriminated from uncomplicated controls by means of urinary VOC analysis, NTC03203434.

Analyzing the Photo-oxidation of 2-propanol at Indoor Air Level Concentrations Using Field Asymmetric Ion Mobility Spectrometry

We demonstrate a versatile protocol to be used for determining the effectiveness of photocatalysts in degrading indoor air concentration (ppb) volatile organic carbons (VOCs), illustrating this with a titanium dioxide based catalyst, and the VOC 2-propanol. The protocol takes advantage of field asymmetric ion mobility spectroscopy (FAIMS), an analysis tool that is capable of continuously identifying and monitoring the concentration of VOCs such as 2-propanol and acetone at the ppb level. The continuous nature of FAIMS allows detailed kinetic analysis, and long-term reactions, offering a significant advantage over gas chromatography, a batch process traditionally used in air purification characterization. The use of FAIMS in photocatalytic air purification has only recently been used for the first time, and with the protocol illustrated here, the flexibility in allowing alternative VOCs and photocatalysts to be tested using comparable protocols offers a unique system to elucidate photocatalytic air purification reactions at low concentrations.

Analyzing the Photo-oxidation of 2-propanol at Indoor Air Level Concentrations Using Field Asymmetric Ion Mobility Spectrometry.

We demonstrate a versatile protocol to be used for determining the effectiveness of photocatalysts in degrading indoor air concentration (ppb) volatile organic carbons (VOCs), illustrating this with a titanium dioxide based catalyst, and the VOC 2-propanol. The protocol takes advantage of field asymmetric ion mobility spectroscopy (FAIMS), an analysis tool that is capable of continuously identifying and monitoring the concentration of VOCs such as 2-propanol and acetone at the ppb level. The continuous nature of FAIMS allows detailed kinetic analysis, and long-term reactions, offering a significant advantage over gas chromatography, a batch process traditionally used in air purification characterization. The use of FAIMS in photocatalytic air purification has only recently been used for the first time, and with the protocol illustrated here, the flexibility in allowing alternative VOCs and photocatalysts to be tested using comparable protocols offers a unique system to elucidate photocatalytic air purification reactions at low concentrations.

Optimized Sampling Conditions for Fecal Volatile Organic Compound Analysis by Means of Field Asymmetric Ion Mobility Spectrometry.

Fecal volatile organic compounds (VOCs) are increasingly considered to be potential noninvasive, diagnostic biomarkers for various gastrointestinal diseases. Knowledge of the influence of sampling conditions on VOC outcomes is limited. We aimed to evaluate the effects of sampling conditions on fecal VOC profiles and to assess under which conditions an optimal diagnostic accuracy in the discrimination between pediatric inflammatory bowel disease (IBD) and controls could be obtained. Fecal samples from de novo treatment-naïve pediatric IBD patients and healthy controls (HC) were used to assess the effects of sampling conditions compared to the standard operating procedure (reference standard), defined as 500 mg of sample mass diluted with 10 mL tap water, using field asymmetric ion mobility spectrometry (FAIMS). A total of 17 IBD (15 CD (Crohn's disease) and 2 UC (ulcerative colitis)) and 25 HC were included. IBD and HC could be discriminated with high accuracy (accuracy = 0.93, AUC = 0.99, p < 0.0001). A smaller fecal sample mass resulted in a decreased diagnostic accuracy (300 mg accuracy = 0.77, AUC = 0.69, p = 0.02; 100 mg accuracy = 0.70, AUC = 0.74, p = 0.003). A loss of diagnostic accuracy was seen toward increased numbers of thaw–freeze cycles (one cycle, accuracy = 0.61, AUC = 0.80, p = 0.0004; two cycles, accuracy = 0.64, AUC = 0.56, p = 0.753; and three cycles, accuracy = 0.57, AUC = 0.50, p = 0.5101) and when samples were kept at room temperature for 180 min prior to analysis (accuracy = 0.60, AUC = 0.51, p = 0.46). Diagnostic accuracy of VOC profiles was not significantly influenced by storage duration differences of 20 months. The application of a 500 mg sample mass analyzed after one thaw–freeze cycle showed the best discriminative accuracy for the differentiation of IBD and HC. VOC profiles and diagnostic accuracy were significantly affected by sampling conditions, underlining the need for the implementation of standardized protocols in fecal VOC analysis.

Ambient ionisation mass spectrometry for in situ analysis of intact proteins.

Ambient surface mass spectrometry is an emerging field which shows great promise for the analysis of biomolecules directly from their biological substrate. In this article, we describe ambient ionisation mass spectrometry techniques for the in situ analysis of intact proteins. As a broad approach, the analysis of intact proteins offers unique advantages for the determination of primary sequence variations and posttranslational modifications, as well as interrogation of tertiary and quaternary structure and protein‐protein/ligand interactions. In situ analysis of intact proteins offers the potential to couple these advantages with information relating to their biological environment, for example, their spatial distributions within healthy and diseased tissues. Here, we describe the techniques most commonly applied to in situ protein analysis (liquid extraction surface analysis, continuous flow liquid microjunction surface sampling, nano desorption electrospray ionisation, and desorption electrospray ionisation), their advantages, and limitations and describe their applications to date. We also discuss the incorporation of ion mobility spectrometry techniques (high field asymmetric waveform ion mobility spectrometry and travelling wave ion mobility spectrometry) into ambient workflows. Finally, future directions for the field are discussed.

The determination of salivary oxypurines before and after exercise by combined liquid chromatography-field asymmetric waveform ion mobility spectrometry-time-of-flight mass spectrometry

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.

High Field Asymmetric Waveform Ion Mobility Spectrometry in Nontargeted Bottom-up Proteomics of Dried Blood Spots.

Despite the great potential of dried blood spots (DBS) as a source of endogenous proteins for biomarker discovery, the literature relating to nontargeted bottom-up proteomics of DBS is sparse, primarily due to the inherent complexity and very high dynamic range associated with these samples. Here, we present proof-of-concept results in which we have coupled high field asymmetric waveform ion mobility spectrometry (FAIMS) with liquid chromatography-tandem mass spectrometry (LC-MS/MS) for nontargeted bottom-up proteomics of DBS with the aim of addressing these challenges. We, and others, have previously demonstrated the benefits of FAIMS more generally in proteomics including improved signal-to-noise and extended proteome coverage, and the aim of the current work was to extend those benefits specifically to DBS. The DBS samples were either extracted by the more traditional manual "punch and elute" approach or by an automated liquid surface extraction (LESA) approach prior to trypsin digestion. The resulting samples were analyzed by LC-MS/MS and LC-FAIMS-MS/MS analysis. The results show that the total number of proteins identified increased by ∼50% for the punch and elute samples and ∼45% for the LESA samples in the LC-FAIMS-MS/MS analysis. For both the punch and elute samples and the LESA samples, ∼30% of the total proteins identified were observed in both the LC-MS/MS and the LC-FAIMS-MS/MS data sets, illustrating the complementarity of the approaches. Overall, this work demonstrates the benefits of inclusion of FAIMS for nontargeted proteomics of DBS.

Can Mutational Analysis Be Used To Assist Structure Determination of Peptides?

Mutational analysis is widely used to study the relationship between sequence and structure of proteins and peptides. It is often assumed that substituting a proline with another amino acid "locks" the peptide bond in the trans conformation, allowing only a subset of the initial molecular geometries to be observed. To test this assumption, we assess the result of substituting two prolines in the bradykinin sequence with alanine using field-asymmetric ion mobility spectrometry combined with cryogenic ion spectroscopy in the gas phase. While the structure of the mutant coincides with a part of the conformational space of the original peptide, the higher flexibility of the alanine backbone compared to proline allows it to access additional structures. We conclude that proline-to-nonproline substitutions are helpful to assign structures, but they should be used in conjunction with spectroscopic techniques that allow detailed comparison of the structures of the mutant and the native peptide.

Fast Orthogonal Separation by Superposition of Time of Flight and Field Asymmetric Ion Mobility Spectrometry.

Ion mobility spectrometry is a powerful and low-cost technique for the identification of chemical warfare agents, toxic chemicals, or explosives in air. Drift tube ion mobility spectrometers (DT-IMS) separate ions by the absolute value of their low field ion mobility, while field asymmetric ion mobility spectrometers (FAIMS) separate them by the change of their ion mobility at high fields. However, using one of these devices alone, some common and harmless substances show the same response as the hazardous target substances. In order to increase the selectivity, orthogonal data are required. Thus, in this work, we present for the first time an ambient pressure ion mobility spectrometer which is able to separate ions both by their differential and low field mobility, providing additional information for selectivity enhancement. This novel field asymmetric time of flight ion mobility spectrometer (FAT-IMS) allows high repetition rates and reaches limits of detection in the low ppb range common for DT-IMS. The device consists of a compact 44 mm drift tube with a tritium ionization source and a resolving power of 70. An increased separation of four substances with similar low field ion mobility is shown: phosgene (K0 = 2.33 cm2/(V s)), 1,1,2-trichlorethane (K0 = 2.31 cm2/(V s)), chlorine (K0 = 2.24 cm2/(V s)), and nitrogen dioxide (K0 = 2.25 cm2/(V s)). Furthermore, the behavior and limits of detection for acetonitrile, dimethyl methylphosphonate, diisopropyl methyl phosphonate in positive polarity and carbon dioxide, sulfur dioxide, hydrochloric acid, cyanogen chloride, and hydrogen cyanide in negative polarity are investigated.

Faecal volatile organic compounds analysis using field asymmetric ion mobility spectrometry: non-invasive diagnostics in paediatric inflammatory bowel disease

Background and Objectives: Inflammatory bowel disease (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), remains challenging to diagnose. Diagnostic work-up carries a high burden, especially in paediatric patients, due to invasive endoscopic procedures. IBD is associated with alterations in intestinal microbiota composition. Faecal volatile organic compounds (VOCs) reflect gut microbiota composition. The aim of this study was to assess the diagnostic accuracy of faecal VOC profiling as a non-invasive diagnostic biomarker for paediatric IBD. Methods: In this diagnostic accuracy study performed in two tertiary centres in the Netherlands, faecal VOC profiles of 36 de novo, treatment-naïve paediatric IBD patients (23 CD, 13 UC), and 24 healthy, matched controls were measured by field asymmetric ion mobility spectrometry (Owlstone Ltd, Lonestar®, UK). Results: Faecal VOC profiles of de novo paediatric IBD patients could be differentiated from healthy controls (AUC ± 95% CI, p-value, sensitivity, specificity; 0.76 ± 0.14, p < 0.001, 79%, 78%). This discrimination from controls was observed in both CD (0.90 ± 0.10, p < 0.0001, 83%, 83%) and UC (0.74 ± 0.19, p = 0.02, 77%, 75%). VOC profiles from UC could not be discriminated from CD (0.67 ± 0.19, p = 0.0996, 65%, 62%). Conclusion: Field asymmetric ion mobility spectrometry allowed for discrimination between faecal VOC profiles of de novo paediatric IBD patients and healthy controls, confirming the potential of faecal VOC analysis as a non-invasive diagnostic biomarker for paediatric IBD. This method may serve as a complementary, non-invasive technique in the diagnosis of IBD, possibly limiting the number of endoscopies needed in children suspected for IBD.

FAIMS based volatile fingerprinting for real-time postharvest storage infections detection in stored potatoes and onions

Field asymmetric ion mobility spectrometry (FAIMS) was evaluated towards rapid and non-destructive detection of storage infections under varied storage conditions. Potato tubers and onion bulbs were inoculated with P. carotovorum subsp. carotovorum (causing soft rot) and B. cepacia (causing sour skin), respectively; and were incubated at room (around 25°C) and reduced temperature condition (4°C). Additional tubers and bulbs were inoculated with sterile water, which served as healthy controls. At room temperature, FAIMS could detect potato soft rot and onion sour skin pertinent volatile organic compounds (VOCs) as early as 1 and 3day(s) after inoculation (DAI) for potato tubers and onion bulbs, respectively. At a reduced temperature (4°C), the respective detection time frames were 11 and 16 DAI. Principal component analysis (PCA) based contribution analysis on FAIMS dispersion field data revealed a significant range of dispersion field (DF) intensity (52%–72%) and compensation voltage (CV) (−1.30V to −0.90V) that can potentially be used to train FAIMS for triggering an alarm during real-time monitoring of soft rot pertinent VOCs. This critical range was 47%–77% DF and −0.24V to 0.48V CV for sour skin pertinent VOCs. Naïve Bayes (NB) and linear discriminant analysis (LDA) classifiers tested on PCA datasets reported overall accuracies in the range of 71–100% and 69–100% for soft rot and 63–97% and 58–100% for sour skin, respectively. Higher accuracies were reported as days after inoculation progressed. Baseline sensing of different VOCs using FAIMS revealed that ethanol, acetone, 2-butanone and ethyl acetate were specifically contributing to P. carotovorum subsp. carotovorum caused soft rot peaks whereas pentane and 1-butanol were associated with healthy as well as inoculated tubers. Dimethyl disulfide, dipropyl disulfide, methyl propyl disulfide, undecane and 2-undecanone were found to be associated with healthy controls as well as with sour skin infected onion bulbs.

Abstract 5303: FAIMS technology in urinary volatile organic compound analysis to detect colorectal cancer

Abstract Introduction This is an investigation of the capability of FAIMS (Field Asymmetric Ion Mobility Spectrometry) technology as a tool for non-invasive detection of Colorectal Cancer (CRC) through urinary volatile organic compound analysis. It expands on "Detection of Colorectal Cancer (CRC) by Urinary Volatile Organic Compound Analysis" (Ramesh P. Arasaradnam et al, 2014) with an increased sample population and local to Japan, also comparing in-house data of CA19-9 and carcinoembryonic antigen (CEA) markers. Experiment Conducted at Nippon Medical School Chiba Hokusoh Hospital, urine samples were collected and frozen at -80°C from 139 patients at various stages of CRC and 78 healthy control samples. The samples were thawed in batches and placed in ice hours prior to testing. 2 ml of each urine sample was aliquoted into 10 ml vials for processing with the commercial FAIMS device (Lonestar, Owlstone, UK). Each vial was heated in the device to 40°C to create headspace with sufficient VOCs then a carrier gas (clean dry air) delivered the headspace (0.5 L/min) diluted with a make-up flow (2 L/min). The FAIMS device was set to scan at 0 to 100% electric dispersion field in 51 steps and compensation voltage between -6 V and +6 V in 512 steps, producing data matrices for each sample's analysis. Principal Component Analysis (PCA) followed by Partial Least Squares Discriminant Analysis (PLS-DA) of each sample was conducted using SIMCA 13 (Umetrics, Sweden). See Table Conclusions FAIMS technology achieved a high rate of separation between the CRC and healthy control urine samples with 64.7% sensitivity and 82.1% specificity overall. As the CRC stage advances the sensitivity increased from 27.3% to 100%. Results show excellent potential to use FAIMS technology as an early screening tool for CRC, particularly impressive compared to in-house sensitivity data of CA19-9 and CEA markers. Further research into FAIMS screening of other cancer types through VOC biomarker analysis of urine, breath, and feces is recommended. &amp;gt;Detection ResultsCRC STAGEFAIMSOTHER MARKERSCA19-9CEATrue PositiveFalse NegativeSensitivityFalse PositiveTrue NegativeSpecificityNo. of SamplesSensitivitySensitivityI123227.3%146482.1%434.7%18.6%II181260.0%146482.1%3116.1%32.3%III45590.0%146482.1%5219.2%36.5%IV150100%146482.1%1735.3%64.7%ALL904964.7%146482.1%14316.1%33.6% Citation Format: Christopher Psutka, Marina Yamada, Akihisa Matsuda, Kazuya Yamahatsu, Satoshi Matsumoto, Toshihiko Kitayama, Nobuo Nakano, Jyunichi Koyano, Tohru Mikoshiba, Masao Miyashita. FAIMS technology in urinary volatile organic compound analysis to detect colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5303. doi:10.1158/1538-7445.AM2017-5303

Rapid Analysis of Anabolic Steroid Metabolites in Urine by Combining Field Asymmetric Waveform Ion Mobility Spectrometry with Liquid Chromatography and Mass Spectrometry.

The combination of field asymmetric waveform ion mobility spectrometry with liquid chromatography-mass spectrometry (LC-FAIMS-MS) has been developed for the analysis of glucuronide and sulfate metabolites of seven anabolic-androgenic steroids in urine. Separation by FAIMS-MS was investigated in positive ion mode for selected cationic adducts (H+, NH4+, Na+, K+, and Cs+). LC-FAIMS-MS analysis of the doubly sodiated adducts ([M + 2Na - H]+) of isobaric and coeluting steroid metabolites allowed their rapid (8 min) qualitative and quantitative determination in spiked urine using hydrophilic interaction liquid chromatography prior to FAIMS-MS separation, with discrimination >95% achieved between the steroids investigated. A quantitative evaluation of the LC-FAIMS-MS method was performed giving limits of detection in the range 1-6 ng mL-1, limits of quantification in the range 3-20 ng mL-1, with reproducibility (%RSD < 10%; n = 6) and linearity (R2 > 0.99). The LC-FAIMS-MS method demonstrates increases in signal-to-noise ratios for the doubly sodiated steroid metabolites in unspiked urine (>250%) by the reduction of isobaric interferences from the matrix. An alternative or additional tool for identification of the steroid metabolites is based on the observations of different patterns of sodium acetate clusters that are characteristic for each metabolite.

Laser-stimulated desorption of organic molecules from surfaces, as a method of increasing the efficiency of ion mobility spectrometry analysis.

Application of laser-induced desorption was investigated as a method of increasing the efficiency of gas phase analyzers on principles of field asymmetric ion mobility spectrometry. Mass spectrometric data of investigations of laser desorption of pentaerythritoltetranitrate molecules and cyclotetramethylenetetranitramine molecules from quartz substrate under vacuum were obtained. Laser sources a Nd3+:YAG with nanosecond pulse duration (λ = 532 nm) and a continuous wave diode laser (λ = 440 nm) were used. It was shown that both laser sources have different desorption abilities. This is expressed in various time of appearance of desorbed products that is caused by different heating mechanisms of surface layer. The desorbed quantity under action of both laser sources exceeds the detection threshold for all modern gas phase analyzers. It should be noted that despite the presence of surface dissociation of explosives under laser radiation, the quantity of nondissociated molecules is large enough for detection by ion mobility and field asymmetric ion mobility spectrometers. The optimal parameters of laser radiation for effective removal (evaporation) molecules of low-volatile compounds from surfaces are defined. The conclusion about preferable use of a Nd3+:YAG laser for increasing the detection ability of detectors based on ion mobility spectrometry was made.

FAIMS based sensing of Burkholderia cepacia caused sour skin in onions under bulk storage condition

Onion (Allium cepa L.) is one of the most important vegetable crops in the Pacific Northwestern states of the U.S., and is stored for 9–12 months under bulk storage condition. Portable non-contact sensing technologies are needed to effectively detect pathogenic infections to the onion bulbs during bulk storage periods for real-time crop loss management. Therefore, portable field asymmetric ion mobility spectrometry (FAIMS) was evaluated towards detection of onion sour skin caused by Burkholderia cepacia, an important postharvest disease under bulk storage conditions. Studied were onions stored at 25 °C under two treatment conditions, inoculated with B. cepacia and with sterile water (as control), during 21-days temporal storage. Results confirmed applicability of FAIMS to detect volatile organic compounds pertinent to B. cepacia caused sour skin as early as 3 days after inoculation. Principal component analysis (PCA) score plots for FAIMS extracted data illustrated distinct clusters corresponding to inoculated and healthy treatments. PCA also suggested a significant range of dispersion field intensity (47–77%) and compensation voltage (−0.24 to 0.48 V), which could potentially be used to train portable FAIMS for real-time detection of sour skin under bulk storage conditions.