Microscale differential ion mobility spectrometry for field deployable chemical analysis

Design and experiment of high-field asymmetric waveform ion mobility spectrometry chip based on an integrated temperature control printed circuit board structure

RATIONALE

During the detection of volatile organic compounds (VOC) using high-field asymmetric waveform ion mobility spectrometry (FAIMS), the ambient temperature significantly impacts the accuracy of planar FAIMS. To mitigate the influence of ambient temperature on detection accuracy and enhance resolution, a FAIMS system based on the inner impedance characteristics of a printed circuit board (PCB) was designed for temperature control.

METHODS

This study, conducted under standard atmospheric pressure, aimed to assess the signal stability of a planar FAIMS instrument with and without temperature control, and the effect of temperature change on the detection ability of acetone, ethanol, and their mixture was studied using PCB self-heating.

RESULTS

Experimental results demonstrated that the base noise in FAIMS with temperature control was 0.2 pA, whereas that in FAIMS without temperature control was 1.8 pA. Notably, with increasing temperature, the detection ability of FAIMS changes accordingly. The optimal relative detection ability of acetone was observed when the electrode plate was heated to 45°C under an electric field of 15 kV/cm.

CONCLUSIONS

This study provides a novel approach to improve the resolving power of FAIMS systems and their signal-to-noise ratio. The utilization of a PCB-based temperature control proved effective in stabilizing FAIMS signal characteristics and optimizing detection capabilities, particularly for VOCs such as acetone. These findings have significant implications for improving the accuracy and resolving power of FAIMS systems in VOC detection applications.

Triboelectric-induced ion mobility for artificial intelligence-enhanced mid-infrared gas spectroscopy

Isopropyl alcohol molecules, as a biomarker for anti-virus diagnosis, play a significant role in the area of environmental safety and healthcare relating volatile organic compounds. However, conventional gas molecule detection exhibits dramatic drawbacks, like the strict working conditions of ion mobility methodology and weak light-matter interaction of mid-infrared spectroscopy, yielding limited response of targeted molecules. We propose a synergistic methodology of artificial intelligence-enhanced ion mobility and mid-infrared spectroscopy, leveraging the complementary features from the sensing signal in different dimensions to reach superior accuracy for isopropyl alcohol identification. We pull in "cold" plasma discharge from triboelectric generator which improves the mid-infrared spectroscopic response of isopropyl alcohol with good regression prediction. Moreover, this synergistic methodology achieves ~99.08% accuracy for a precise gas concentration prediction, even with interferences of different carbon-based gases. The synergistic methodology of artificial intelligence-enhanced system creates mechanism of accurate gas sensing for mixture and regression prediction in healthcare.

Detection and prediction of Botrytis cinerea infection levels in wine grapes using volatile analysis

Infection of grape berries (Vitis vinifera) by the fungus Botrytis cinerea (grey mould) frequently occurs in vineyards, resulting in off-flavours and other odours in wine and potential yield losses. In this study, volatile profiles of four naturally infected grape cultivars, and laboratory-infected grapes were analysed to identify potential markers for B. cinerea infection. Selected volatile organic compounds (VOCs) were highly correlated with two independent measures of B. cinerea infection levels, demonstrating that ergosterol measurements provide accurate quantification of lab-inoculated samples, while B. cinerea antigen detection is more suitable for naturally infected grapes. Excellent predictive models of infection level were confirmed (Q²Y of 0.784-0.959) using selected VOCs. A time course experiment confirmed that selected VOCs 1,5-dimethyltetralin, 1,5-dimethylnaphthalene, phenylethyl alcohol and 3-octanol are good markers for B. cinerea quantification and 2-octen-1-ol could be considered as an early marker of the infection.

Dogs can discriminate between human baseline and psychological stress condition odours

Previous research suggests that dogs can detect when humans are experiencing stress. This study tested whether baseline and stress odours were distinguishable to dogs, using a double-blind, two-phase, three-alternative forced-choice procedure. Combined breath and sweat samples were obtained from participants at baseline, and after a stress-inducing (mental arithmetic) task. Participants’ stress was validated with self-report and physiological measures recorded via a Biopac MP150 system. Thirty-six participants’ samples were presented to four dogs across 36 sessions (16, 11, 7 and 2 sessions, respectively). Each session consisted of 10 Phase One training trials and 20 Phase Two discrimination trials. In Phase One, the dog was presented with a participant’s stress sample (taken immediately post-task) alongside two blanks (the sample materials without breath or sweat), and was required to identify the stress sample with an alert behaviour. In Phase Two, the dog was presented with the stress sample, the same participant’s baseline sample (taken pre-task), and a blank. Which sample (blank, baseline, or stress) the dog performed their alert behaviour on was measured. If dogs can correctly alert on the stress sample in Phase Two (when the baseline sample was present), it suggests that baseline and stress odours are distinguishable. Performance ranged from 90.00% to 96.88% accuracy with a combined accuracy of 93.75% (N trials = 720). A binomial test (where probability of success on a single trial was 0.33, and alpha was 0.05) showed that the proportion of correct trials was greater than that expected by chance (p < 0.001). Results indicate that the physiological processes associated with an acute psychological stress response produce changes in the volatile organic compounds emanating from breath and/or sweat that are detectable to dogs. These results add to our understanding of human-dog relationships and could have applications to Emotional Support and Post Traumatic Stress Disorder (PTSD) service dogs.

An atmospheric pressure ion funnel with a slit entrance for enhancing signal and resolution in high resolution differential ion mobility mass spectrometry

Differential ion mobility (DMS) is a versatile ion separation method that is often integrated with mass spectrometry (MS). In DMS, extremely high electric fields are used such that ion mobility depends non-linearly on electric field and thus, ion separations can be more orthogonal to MS than lower field ion mobility-based methods. DMS can have sufficiently high resolution to be used for enantiomer analysis of small molecules and to separate protein ions with peak widths comparable to those obtained for peptides. However, the performance of high resolution DMS-MS can be limited owing to the substantial loss of ions (>10-fold) that can occur upon their transfer from atmospheric pressure (where DMS separation typically occurs) to vacuum through a narrow conductance limited inlet (e.g. capillary) to the MS. Here, results from simulated ion trajectory simulations suggest that in high resolution DMS most ions can be lost by 'crashing' onto the narrow capillary inlet after exiting the DMS separation channel. To enhance DMS sensitivity and resolving power, an integrated DMS-MS interface concept is reported that consists of a slit electrode and a 12-electrode atmospheric pressure ion funnel (APIF). By using an APIF with slit entrance, the simulated ion transmission efficiencies increase by up to 257% for singly charged ions ([DMMP + H]⁺, [tryptophan + H]⁺, and [(2-dodecanone)₂ + H]⁺) and by 209% for [ubiquitin + 12H]¹²⁺, without compromising resolving power. The use of APIF improves the ion focussing from the DMS exit to the MS capillary to improve sensitivity, and the slit ensures that ion dispersion in the analytically relevant direction perpendicular to the DMS electrodes is restricted to enhance resolution. By narrowing the slit of the DMS-Slit-APIF interface, the DMS resolving power can be increased further by at least 20%. Overall, these results indicate that the integrated DMS-Slit-APIF interface is promising for improving the sensitivity and resolution for many different types of DMS-MS experiments.

Protein-Small Molecule Interactions in Native Mass Spectrometry

Small molecule drug discovery has been propelled by the continual development of novel scientific methodologies to occasion therapeutic advances. Although established biophysical methods can be used to obtain information regarding the molecular mechanisms underlying drug action, these approaches are often inefficient, low throughput, and ineffective in the analysis of heterogeneous systems including dynamic oligomeric assemblies and proteins that have undergone extensive post-translational modification. Native mass spectrometry can be used to probe protein-small molecule interactions with unprecedented speed and sensitivity, providing unique insights into polydisperse biomolecular systems that are commonly encountered during the drug discovery process. In this review, we describe potential and proven applications of native MS in the study of interactions between small, drug-like molecules and proteins, including large multiprotein complexes and membrane proteins. Approaches to quantify the thermodynamic and kinetic properties of ligand binding are discussed, alongside a summary of gas-phase ion activation techniques that have been used to interrogate the structure of protein-small molecule complexes. We additionally highlight some of the key areas in modern drug design for which native mass spectrometry has elicited significant advances. Future developments and applications of native mass spectrometry in drug discovery workflows are identified, including potential pathways toward studying protein-small molecule interactions on a whole-proteome scale.

Moving toward a Handheld "Plasma" Spectrometer for Elemental Analysis, Putting the Power of the Atom (Ion) in the Palm of Your Hand

Many of the current innovations in instrument design have been focused on making them smaller, more rugged, and eventually field transportable. The ultimate application is obvious, carrying the instrument to the field for real time sample analysis without the need for a support laboratory. Real time data are priceless when screening either biological or environmental samples, as mitigation strategies can be initiated immediately upon the discovery that contaminant metals are present in a location they were not intended to be. Additionally, smaller "handheld" instruments generally require less sample for analysis, possibly increasing sensitivity, another advantage to instrument miniaturization. While many other instruments can be made smaller just by using available micro-technologies (e.g., eNose), shrinking an ICP-MS or AES to something someone might carry in a backpack or pocket is now closer to reality than in the past, and can be traced to its origins based on a component-by-component evaluation. While the optical and mass spectrometers continue to shrink in size, the ion/excitation source remains a challenge as a tradeoff exists between excitation capabilities and the power requirements for the plasma's generation. Other supporting elements have only recently become small enough for transport. A systematic review of both where the plasma spectrometer started and the evolution of technologies currently available may provide the roadmap necessary to miniaturize the spectrometer. We identify criteria on a component-by-component basis that need to be addressed in designing a miniaturized device and recognize components (e.g., source) that probably require further optimization. For example, the excitation/ionization source must be energetic enough to take a metal from a solid state to its ionic state. Previously, a plasma required a radio frequency generator or high-power DC source, but excitation can now be accomplished with non-thermal (cold) plasma sources. Sample introduction, for solids, liquids, and gasses, presents challenges for all sources in a field instrument. Next, the interface between source and a mass detector usually requires pressure reduction techniques to get an ion from plasma to the spectrometer. Currently, plasma mass spectrometers are field ready but not necessarily handheld. Optical emission spectrometers are already capable of getting photons to the detector but could eventually be connected to your phone. Inert plasma gas generation is close to field ready if nitrogen generators can be miniaturized. Many of these components are already commercially available or at least have been reported in the literature. Comparisons to other "handheld" elemental analysis devices that employ XRF, LIBS, and electrochemical methods (and their limitations) demonstrate that a "cold" plasma-based spectrometer can be more than competitive. Migrating the cold plasma from an emission only source to a mass spectrometer source, would allow both analyte identification and potentially source apportionment through isotopic fingerprinting, and may be the last major hurdle to overcome. Finally, we offer a possible design to aid in making the cold plasma source more applicable to a field deployment.

Medical diagnosis at the point-of-care by portable high-field asymmetric waveform ion mobility spectrometry: a systematic review and meta-analysis

Non-invasive medical diagnosis by analysing volatile organic compounds (VOCs) at the point-of-care is becoming feasible owing to recent advances in portable instrumentation. A number of studies have assessed the performance of a state-of-the-art VOC analyser (micro-chip high-field asymmetric waveform ion mobility spectrometry, FAIMS) for medical diagnosis. However, a comprehensive meta-analysis is needed to investigate the overall diagnostic performance of these novel methods across different medical conditions. An electronic search was performed using the CAplus and MEDLINE database through the SciFinder platform. The review identified a total of 23 studies and 2312 individuals. Eighteen studies were used for meta-analysis. A pooled analysis found an overall sensitivity of 80% (95% CI, 74%-85%,I2= 62%), and specificity of 78% (95% CI, 70%-84%,I2= 80%), which corresponds to the overall diagnostic performance of micro-chip FAIMS across many different medical conditions. The diagnostic accuracy was particularly high for coeliac and inflammatory bowel disease (sensitivity and specificity from 74% to 97%). The overall diagnostic performance was similar across breath, urine, and faecal matrices with sparse logistic regression and random forests algorithms resulting in higher diagnostic accuracy. Sources of variability likely arise from differences in sample storage, sampling protocol, method of data analysis, type of disease, sample matrix, and potentially to clinical and disease factors. The results of this meta-analysis indicate that micro-chip FAIMS is a promising candidate for disease screening at the point-of-care, particularly for gastroenterology diseases. This review provides recommendations that should improve the techniques relevant to diagnostic accuracy of future VOC and point-of-care studies.

Volatile organic compounds sensing based on Bennet doubler-inspired triboelectric nanogenerator and machine learning-assisted ion mobility analysis

Ion mobility analysis is a well-known analytical technique for identifying gas-phase compounds in fast-response gas-monitoring systems. However, the conventional plasma discharge system is bulky, operates at a high temperature, and inappropriate for volatile organic compounds (VOCs) concentration detection. Therefore, we report a machine learning (ML)-enhanced ion mobility analyzer with a triboelectric-based ionizer, which offers good ion mobility selectivity and VOC recognition ability with a small-sized device and non-strict operating environment. Based on the charge accumulation mechanism, a multi-switched manipulation triboelectric nanogenerator (SM-TENG) can provide a direct current (DC) bias at the order of a few hundred, which can be further leveraged as the power source to obtain a unique and repeatable discharge characteristic of different VOCs, and their mixtures, with a special tip-plate electrode configuration. Aiming to tackle the grand challenge in the detection of multiple VOCs, the ML-enhanced ion mobility analysis method was successfully demonstrated by extracting specific features automatically from ion mobility spectrometry data with ML algorithms, which significantly enhance the detection ability of the SM-TENG based VOC analyzer, showing a portable real-time VOC monitoring solution with rapid response and low power consumption for future internet of things based environmental monitoring applications.

Rapid on-site identification of hazardous organic compounds at fire scenes using person-portable gas chromatography-mass spectrometry (GC-MS)-part 1: air sampling and analysis

Recent advancements in person-portable instrumentation have resulted in the potential to provide contemporaneous results through rapid in-field analyses. These technologies can be utilised in emergency response scenarios to aid first responders in appropriate site risk assessment and management. Large metropolitan fires can pose great risk to human and environmental health due to the rapid release of hazardous compounds into the atmosphere. Understanding the release of these hazardous organics is critical in understanding their associated risks. Person-portable gas chromatography-mass spectrometry (GC-MS) was evaluated for its potential to provide rapid on-site analysis for real-time monitoring of hazardous organic compounds at fire scenes. Air sampling and analysis methods were developed for scenes of this nature. Controlled field testing demonstrated that the portable GC-MS was able to provide preliminary analytical results on the volatile organic compounds present in air samples collected from both active and extinguished fires. In-field results were confirmed using conventional laboratory-based air sampling and analysis procedures. The deployment of portable instrumentation could provide first responders with a rapid on-site assessment tool for the appropriate management of scenes, thereby ensuring environmental and human health is proactively protected and scientifically informed decisions are made for the provision of timely advice to stakeholders.

Differential mobility spectrometry imaging for pathological applications

Pathologic examination of clinical tissue samples is time consuming and often does not involve the comprehensive analysis of the whole specimen. Automated tissue analysis systems have potential to make the workflow of a pathologist more efficient and to support in clinical decision-making. So far, these systems have been based on application of mass spectrometry imaging (MSI). MSI provides high fidelity and the results in tissue identification are promising. However, the high cost and need for maintenance limit the adoption of MSI in the clinical setting. Thus, there is a need for new innovations in the field of pathological tissue imaging. In this study, we show that differential ion mobility spectrometry (DMS) is a viable option in tissue imaging. We demonstrate that a DMS-driven solution performs with up to 92% accuracy in differentiating between two grossly distinct animal tissues. In addition, our model is able to classify the correct tissue with 81% accuracy in an eight-class setting. The DMS-based system is a significant innovation in a field dominated by mass-spectrometry-based solutions. By developing the presented platform further, DMS technology could be a cost-effective and helpful tool for automated pathological analysis.

Ultrasensitive xylene gas sensor based on flower-like SnO2/Co3O4 nanorods composites prepared by facile two-step synthesis method

Xylene is a volatile organic compound which is harmful to the human health and requires precise detection. The detection of xylene by an oxide semiconductor gas sensor is an important research direction. In this work, Co₃O₄ decorated flower-like SnO₂ nanorods (SnO₂/Co₃O₄ NRs) were synthesized by a simple and effective two-step method. The SnO₂/Co₃O₄ NRs show high xylene response (R _g/R _a = 47.8 for 100 ppm) and selectivity at the operating temperature of 280 °C, and exhibit high stability in continuous testing. The resulting SnO₂/Co₃O₄ NRs nanocomposites show superior sensing performance towards xylene in comparison with pure SnO₂ nanorods. The remarkable enhancement in the gas-sensing properties of SnO₂/Co₃O₄ NRs are attributed to larger specific surface area and the formation of p-n heterojunction between Co₃O₄ and SnO₂. These results demonstrate that particular nanostructures and synergistic effect of SnO₂ and Co₃O₄ enable gas sensors to selectively detect xylene.

Understanding Nontraditional Differential Mobility Behavior: A Case Study of the Tricarbastannatrane Cation, N(CH2CH2CH2)3Sn. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2020;31:796-802. [PMID: 32129991 DOI: 10.1021/jasms.9b00042]

The effect of strong ion-solvent interactions on the differential mobility behavior of the tricarbastannatrane cation, N(CH₂CH₂CH₂)₃Sn⁺, has been investigated. Exotic "type D" dispersion behavior, which is intermediate to the more common types C and A behavior, is observed for gaseous N₂ environments that are seeded with acetone and acetonitrile vapor. Quantum chemical calculations and first-principles modeling show that under low-field conditions [N(CH₂CH₂CH₂)₃Sn + solvent]⁺ complexes containing a single solvent molecule survive the entire separation waveform duty cycle and interact weakly with the chemically modified environment. However, at high separation voltages, the ion-solvent bond dissociates and dynamic clustering ensues.

Field induced fragmentation spectra from reactive stage-tandem differential mobility spectrometry

A planar tandem differential mobility spectrometer was integrated with a middle reactive stage to fragment ions which were mobility selected in a first analyzer stage using characteristic compensation and separation fields.

Identification of Active Sites and Structural Characterization of Reactive Ionic Intermediates by Cryogenic Ion Trap Vibrational Spectroscopy

Cryogenic ion trap vibrational spectroscopy paired with quantum chemistry currently represents the most generally applicable approach for the structural investigation of gaseous cluster ions that are not amenable to direct absorption spectroscopy. Here, we give an overview of the most popular variants of infrared action spectroscopy and describe the advantages of using cryogenic ion traps in combination with messenger tagging and vibrational predissociation spectroscopy. We then highlight a few recent studies that apply this technique to identify highly reactive ionic intermediates and to characterize their reactive sites. We conclude by commenting on future challenges and potential developments in the field.

Resolution of co-eluting isomers of anti-inflammatory drugs conjugated to carbonic anhydrase inhibitors from plasma in liquid chromatography by energy-resolved tandem mass spectrometry

Rheumatoid arthritis (RA) is a chronic inflammatory disease caused by a faulty autoimmune response. Recently, it was reported that some human carbonic anhydrases (CAs) isoforms are overexpressed in inflamed synovium of RA patients. New CA inhibitors (CAIs) incorporating CA-binding moiety and the cyclooxygenase inhibitor tail (nonsteroidal anti-inflammatory drug [NSAID] type) were studied. The aim of this work is the evaluation of the chemical stability of NSAID - CAI hybrids towards spontaneous or enzymatic hydrolysis by LC-MS/MS. The analytes are isomer pairs of 6- or 7-hydroxycoumarin, their different fragment ions abundances allowed the development of a mathematical tool (LEDA) to distinguish them. LEDA reliability at ng mL-1 level was checked (>90%), being proved the effectiveness in the correct assignment of the isomer present in the sample. The hybrids resulted stable in all tested matrices allowing us to conclude that these compounds reach the target tissues unmodified, opening perspectives for their development in the treatment of inflammation.

Cancer breath testing: a patent review

INTRODUCTION

Human breath can contain thousands of volatile organic compounds (VOCs) and semi-volatile compounds that are related to metabolism and other biochemical processes. The presence of cancer cells can affect the identity and abundances of chemicals in breath when compared to those in healthy control subjects, which can be used to indicate the likelihood of a patient having cancer. Recently, the chemical analysis of exhaled breath from patients has been shown to be promising for diagnosing many different types of cancers, including lung, breast, colon, head, neck, and prostate, along with pre-cancerous conditions (dysplasia).

AREAS COVERED

Here, we reviewed the sampling, analytical and data analysis methods reported in the recent patent literature related to cancer breath testing (2014-2017). In addition, the different types of cancer biomarkers that were disclosed are discussed.

EXPERT OPINION

The major advantages of breath testing compared to conventional X-ray and imaging based methods includes simplicity of use, non-invasiveness, and the potential to detect cancer at a relatively early stage. Such methods are also suitable to perform population screening because of their non-invasiveness. However, the establishment of standard sampling, detection and quantification methods for breath testing is required before the methods can be employed for clinical diagnosis.