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Lung cancer, chronic obstructive pulmonary disease (COPD) and asthma are inflammatory diseases that have risen worldwide, posing a major public health issue, encompassing not only physical and psychological morbidity and mortality, but also incurring significant societal costs. The leading cause of death worldwide by cancer is that of the lung, which, in large part, is a result of the disease often not being detected until a late stage. Although COPD and asthma are conditions with considerably lower mortality, they are extremely distressful to people and involve high healthcare overheads. Moreover, for these diseases, diagnostic methods are not only costly but are also invasive, thereby adding to people’s stress. It has been appreciated for many decades that the analysis of trace volatile organic compounds (VOCs) in exhaled breath could potentially provide cheaper, rapid, and non-invasive screening procedures to diagnose and monitor the above diseases of the lung. However, after decades of research associated with breath biomarker discovery, no breath VOC tests are clinically available. Reasons for this include the little consensus as to which breath volatiles (or pattern of volatiles) can be used to discriminate people with lung diseases, and our limited understanding of the biological origin of the identified VOCs. Lung disease diagnosis using breath VOCs is challenging. Nevertheless, the numerous studies of breath volatiles and lung disease provide guidance as to what volatiles need further investigation for use in differential diagnosis, highlight the urgent need for non-invasive clinical breath tests, illustrate the way forward for future studies, and provide significant guidance to achieve the goal of developing non-invasive diagnostic tests for lung disease. This review provides an overview of these issues from evaluating key studies that have been undertaken in the years 2010–2019, in order to present objective and comprehensive updated information that presents the progress that has been made in this field. The potential of this approach is highlighted, while strengths, weaknesses, opportunities, and threats are discussed. This review will be of interest to chemists, biologists, medical doctors and researchers involved in the development of analytical instruments for breath diagnosis.

Simple tests using sniff analysis that have the ability of diagnosing and rapidly distinguishing between infections due to different bacteria are urgently required by medical community worldwide. Professionals interested in this topic wish for these tests to be simultaneously cheap, fast, easily applicable, non-invasive, robust, reliable, and sensitive. Current analytical instrumentation has already the ability for performing real time (minutes or a few dozens of minutes) analysis of volatile bacterial biomarkers (the VOCs emitted by bacteria). Although many articles are available, a review displaying an objective evaluation of the current status in the field is still needed. This review tries to present an overview regarding the bacterial biomarkers released from

Sensitive real-time detection of vapors produced by the precursors, reagents and solvents used in the illegal drugs manufacture represents a priority nowadays. Acetic anhydride (AA) is the key chemical used as acetylation agent in producing the illegal drugs heroin and methaqualone. This study was directed towards quick detection and quantification of AA in air, using two fast and very sensitive analytical techniques: photoionization detection (PID) and ion mobility spectrometry (IMS). Results obtained indicated that both PID and IMS can sense AA at ultra-trace levels in air, but while PID produces a non-selective response, IMS offers richer information. Ion mobility spectrometric response in the positive ion mode presented one product ion, at reduced ion mobility K0 of 1.89 cm2 V&minus, 1 s&minus, 1 (almost overlapped with positive reactant ion peak), while in the negative ion mode two well separated product ions, with K0 of 1.90 and 1.71 cm2 V&minus, 1, were noticed. Our study showed that by using a portable, commercial IMS system (model Mini IMS, I.U.T. GmbH Berlin) AA can be easily measured at concentrations of 0.05 ppmv (0.2 mg m&minus, 3) in negative ion mode. Best selectivity and sensitivity of the IMS response were therefore achieved in the negative operation mode.

The objective of our study was to investigate whether one may quickly and reliably discriminate different microorganism strains by direct monitoring of the headspace atmosphere above their cultures. Headspace samples above a series of in vitro bacterial cultures were directly interrogated using an aspiration type ion mobility spectrometer (a-IMS), which produced distinct profiles (“fingerprints”) of ion currents generated simultaneously by the detectors present inside the ion mobility cell. Data processing and analysis using principal component analysis showed net differences in the responses produced by volatiles emitted by various bacterial strains. Fingerprint assignments were conferred on the basis of product ion mobilities; ions of differing size and mass were deflected in a different degree upon their introduction of a transverse electric field, impacting finally on a series of capacitors (denominated as detectors, or channels) placed in a manner analogous to sensor arrays. Three microorganism strains were investigated – Escherichia coli, Bacillus subtilis and Staphylococcus aureus; all strains possess a relatively low pathogenic character. Samples of air with a 5 cm3 volume from the headspace above the bacterial cultures in agar growth medium were collected using a gas-tight chromatographic syringe and injected inside the closed-loop pneumatic circuit of the breadboard a-IMS instrument model ChemPro-100i (Environics Oy, Finland), at a distance of about 1 cm from the ionization source. The resulting chemical fingerprints were produced within two seconds from the moment of injection. The sampling protocol involved to taking three replicate samples from each of 10 different cultures for a specific strain, during a total period of 72 h after the initial incubation – at 24, 48 and 72 h, respectively. Principal component analysis (PCA) was used to discriminate between the IMS fingerprints. PCA was found to successfully discriminate between bacteria at three levels in the experimental campaign: 1) between blank samples from growth medium and samples from bacterial cultures, 2) between samples from different bacterial strains, and 3) between time evolutions of headspace samples from the same bacterial strain over the 3-day sampling period. Consistent classification between growth medium samples and growth medium inoculated with bacteria was observed in both positive and negative detection/ionization modes. In parallel, headspace air samples of 1 dm3 were collected from each bacterial culture and loaded onto Tenax™-Carbograph desorption tubes, using a custom built sampling unit based on a portable sampling pump. One sample was taken for each of 10 different cultures of a strain, at 24, 48 and 72 h after the initial incubation. These adsorption tubes were subsequently analyzed using thermal desorption – gas chromatography – mass spectrometry (TD-GC-MS). This second dataset was intended to produce a qualitative analysis of the volatiles present in the headspace above the bacterial cultures.

Bacteria are the main cause of many human diseases. Typical bacterial identification methods, for example culture-based, serological and genetic methods, are time-consuming, delaying the potential for an early and accurate diagnosis and the appropriate subsequent treatment. Nevertheless, there is a stringent need for in situ tests that are rapid, noninvasive and sensitive, which will greatly facilitate timely treatment of the patients. This review article presents volatile organic metabolites emitted from various micro-organism strains responsible for common bacterial infections in humans. Additionally, the manuscript shows the application of different analytical techniques for fast bacterial identification. Details of these techniques are given, which focuses on their advantages and drawbacks in using for volatile organic components analysis.

The possibility of achieving bacterial discrimination using a miniaturized aspiration ion mobility spectrometer model ChemPro-100i (Environics Oy) has been tested by interrogating the headspace air samples above in vitro bacterial cultures of three species – Escherichia coli, Bacillus subtilis and Staphylococcus aureus, respectively. The ChemPro-100i highly integrated seven sensor array, composed of one a-IMS cell, three MOS (metal oxide sensors), one FET (field effect transistor) sensor and two SC (semiconductor) sensors, provided enough analytical information to discriminate between the three bacterial species. Statistical data processing using either principal component analysis (PCA) or partial least squares discriminant analysis (PLS-DA) was accomplished. We concluded that although the data from the aspiration-type ion mobility sensor, with its 16 ion detectors, is absolutely sufficient to discriminate between various bacteria using their volatile compounds’ chemical profile, the other six sensors deliver additional, valuable information.

Sensitive real-time detection of vapors produced by toxic industrial chemicals (TICs) represents a stringent priority nowadays. Carbon disulfide (CS2) is such a chemical, being widely used in manufacturing synthetic textile fibers and as a solvent. CS2 is simultaneously a very reactive, highly flammable, irritant, corrosive, and highly toxic compound, affecting the central nervous system, cardiovascular system, eyes, kidneys, liver, skin, and reproductive system. This study was directed towards quick detection and quantification of CS2 in air, using time-of-flight ion mobility spectrometry (IMS); photoionization detection (PID) was also used as confirmatory technique. Results obtained indicated that IMS can detect CS2 at trace levels in air. The ion mobility spectrometric response was in the negative ion mode and presented one product ion, at a reduced ion mobility (K0) of 2.25 cm2 V−1 s−1. Our study demonstrated that by using a portable, commercial IMS system (model Mini IMS, I.U.T. GmbH Berlin Germany) one can easily measure CS2 at concentrations of 0.1 ppmv (0.3 mg m−3) in the negative ion mode, which is below the lowest threshold value of 1 ppmv given for industrial hygiene. A limit of detection (LOD) of ca. 30 ppbv (0.1 mg m−3) was also estimated.

Volatile organic compounds (VOCs) released into the headspace air over human tissues infected with different bacteria were investigated in this work. The above-mentioned VOCs result both from bacterial metabolic processes (pathogen-specific signals) and from the matrix (tissue samples themselves). The objective of this study was to investigate whether one could reliably identify various microorganism strains that exist inside infected tissue samples by direct monitoring of the headspace atmosphere above their cultures. Headspace samples were directly interrogated using a GC-MS system, which produced distinct profiles for samples contaminated with single bacterial strains or with multiple strains (mixed infections). Principal component analysis (PCA) and predictive analysis based on receiver operating characteristics curves (ROC) were the statistical procedures utilized for differentiating between infected and uninfected samples, while network analysis and heat-mapping were used to highlight the connections between emitted volatiles and infectious pathogens. By using ROC curves, obtained results demonstrated that the area under the ROC (95% probability interval) was 0.86 in case of infected samples and 0.48 for uninfected samples. On the other hand, PCA highlighted separation between components coming from infected and uninfected patients, where 67% of variance was described from the first 2 principal components. The biomarker chemicals documented from this work, as well as the developed methodology may ultimately be applied to identify bacterial infections by analyzing exhaled breath.

Escherichia coli (E. coli) is a Gram-negative bacterium commonly found in the lower intestine of warm-blooded organisms, including humans. Although the majority of the strains are considerably harmless, some serotypes are pathogenic, frequently causing diarrhea and other illnesses outside the intestinal tract. The standard antidote against bacteria is the use of antibiotics. Depending on their type, the antibiotics have various mechanisms of action on bacteria. Moreover, in case of in-vitro cultivation of bacteria, the used growth media plays a crucial role, since it influences bacterial inhibition as well. In the present study, we emphasize the importance of cultivability in bacterial inhibition under the treatment with five different antibiotics belonging to different classes. Consequently, E. coli was cultivated in three different growth media: trypcase soy broth (TSB), Mueller Hinton (MH), and minimal salts (M9) enriched with glucose, respectively. MALDI-TOF MS (matrix-assisted laser desorption ionization time-of-flight mass spectrometry) analyses, that were used for fast characterization of changes that occur in ribosomal protein profiles, revealed differentiation and similarities between investigated cases, while flow cytometry (FCM) tests better explained the given changes that occurred in the analyzed samples after 3, 24 and 48 h of experimental campaign.

Being involved in the synthesis of precursors for amphetamine and amphetamine-like drugs, pyridine (Py) may be also regarded as a by-product found when these drugs are obtained via the Leuckart method. Also, pyridine is well known as a biomarker of microorganisms, when those are subjected to pyrolysis before analysis by various instrumental techniques. Consequently, since Py is not commonly found in the air, its presence as a contaminant at trace levels in a room could indicate the existence of a clandestine laboratory. In this work, standard atmospheres containing known, low levels of pyridine vapors in air were analyzed using IMS (Ion Mobility Spectrometry) and PID (Photoionization Detection). Both techniques were extremely sensitive and rapid. Pyridine concentrations as low as 5 ppbv were measured in semi-purified air in several seconds; hence a real time detection. Quantitative ion mobility spectrometric response between 5 and 315 ppbv of pyridine has been investigated. Also, the reduced mobility of pyridine product ion peak in the positive mode was calculated to be K0= 1.75 cm2V-1s-1, using 2,6-lutidine as chemical standard for ion mobility. Confirmatory analysis by PID has been accomplished for every standard atmosphere with pyridine in order to check and back up the IMS responses. We conclude that IMS has a very good sensitivity in real-life conditions and is a useful tool in detecting pyridine as an important building brick in illegal drugs synthesis and in protecting health of law enforcement officers that investigate the location of a clandestine laboratory.

A fast quantitative assay for the selective and sensitive measurement of methanol and ethanol in human saliva has been developed. A hyphenated thermal desorption (TD) – gas chromatography (GC) – differential mobility spectrometry (DMS) technique was developed to characterise methanol in human saliva at concentrations between 25 mg dm−3 and 1000 mg dm−3, in the presence of elevated ethanol concentrations. A temperature-controlled polydimethylsilicone capillary membrane was used in the sampling procedure to extract methanol in the presence of elevated ethanol concentrations. A flow of nitrogen through the central channel of the membrane swept the volatile analytes into an adsorbent trap. TD-GC-DMS was used to isolate, detect and identify each compound with an analysis time of less than 3 min. The method was optimised using a 2 factor (temperature and dispersion field strength), 2 centroid point, central composite design, to enhance the resolution and sensitivity of DMS responses to methanol and ethanol. The optimum DMS cell temperature was found to be 80 °C with an optimum dispersion field strength of 24 kV cm−1. A linear response was obtained for methanol over the range 25 to 500 mg dm−3 (R2 = 0.998) The development of this method to provide point-of-care testing for ethanol and methanol exposure is discussed.

A thermal desorption unit has been interfaced to an electrospray ionization-ion mobility-time-of-flight mass spectrometer. The interface was evaluated using a mixture of six model volatile organic compounds which showed detection limits of1 ng sample loaded onto a thermal desorption tube packed with Tenax, equivalent to sampled concentrations of 4 microg L(-1). Thermal desorption profiles were observed for all of the compounds, and ion mobility-mass spectrometry separations were used to resolve the probe compound responses from each other. The combination of temperature programmed thermal desorption and ion mobility improved the response of selected species against background ions. Analysis of breath samples resulted in the identification of breath metabolites, based on ion mobility and accurate mass measurement using siloxane peaks identified during the analysis as internal lockmasses.

Ion mobility spectrometry (IMS), using stand-alone instrumentation and hyphenated with mass spectrometry (IM-MS), has recently undergone significant expansion in the numbers of users and applications, particularly in sectors outside its established user base; predominantly military and security applications. Although several IMS reference standards have been proposed, there are no currently universally recognised reference standards for the calibration and evaluation of mobility spectrometers. This review describes current practices and the literature on chemical standards for validating IMS systems in positive and negative ion modes. The key qualities and requirements an ‘ideal’ reference standard must possess are defined, together with the instrumental and environmental factors such as temperature, electric field, humidity and drift gas composition that may need to be considered. Important challenges that have yet to be resolved are also identified and proposals for future development presented.

Escherichia coli (E. coli) is a Gram-negative coliform bacterium that is commonly found in the lower intestine of warm-blooded organisms. Most of the strains are harmless but some serotypes are pathogenic, meaning they can cause illness, either diarrhea or illness outside the intestinal tract. The aim of this work is to assess which components are generated for the purpose of E. coli target analysis. In this study, we intend to emphasize the importance of cultivability and to prove that growth media plays a crucial role in bacteria growth. To do this, E. coli was cultivated in three different growth mediums: (a) trypcase soy broth (TSB), (b) Mueller Hinton (MH), and (c) minimal salts (M9) enriched with glucose, respectively. Solid phase micro extraction was used as a sampling method, followed by gas chromatography-mass spectrometry for subsequent analysis. The relevant microbial volatile organic compounds (MVOCs) released in the headspace over the cultures of the E. coli bacteria and the afferent metabolic processes that occur in order to generate these compounds are presented in this work. The characteristic volatile compounds found in E. coli strain emissions were indole, phenylethyl alcohol and a series of esters when it was grown in TSB. Different pyrazines were found (pyrazine, 2-ethyl-3,5-dimethyl-, pyrazine, 2,5-dimethyl- and pyrazine, trimethyl-) when it was cultivated in MH. Long-chain alcohols such as 2-pentadecanol, 9-tetradecen-1-ol and 11-hexadecenol occurred in M9. Dimethyl disulfide, dimethyl trisulfide and a consistent number of alcohols and ketones were observed for E. coli cultivated in all three growth mediums. The occurrence and biosynthesis of these MVOCs clearly denote that the growth media used plays a crucial role in bacterial cultivation. The biomarker chemicals documented from this work may ultimately be used to identify bacterial infections by analyzing exhaled breath.

The negative mode response of a membrane inlet ion mobility spectrometer, interfaced to an Extrel-C150 mass spectrometer, to chlorine in dry air over the range of concentrations 0–200 mg m−3 was characterised. Three distinct product ions were observed: an assembly of [Cl2(H2O)n]− and [Cl(H2O)n]− entities with a reduced mobility of 2.19 cm2 V−1 s−1, a carbon dioxide based cluster, [Cl2(CO2)(H2O)3]− with a reduced mobility of 1.93 cm2 V−1 s−1 and a dimer product thought to be [(Cl2)2(H2O)]− with a reduced mobility of 1.70 cm2 V−1 s−1. The response to chlorine was found to be sensitive with a limit of detection significantly less than 1 mg m−3. Further exposures to chlorine were also undertaken with 5 and 10% by mass of water added to the adsorbent traps used to purify the drift and source gases within the instrument. This was done to simulate ageing of the air purification media. No changes in the chemistry of the product ions were observed with increasing levels of water contamination of the adsorbent media. The sensitivity was reduced and the observed drift times increased with increasing levels of water contamination with the reduced mobilities for the three product ion groups above found to vary across the ranges: 2.10–2.19, 1.84–1.93 and 1.66–1.70 cm2 V−1 s−1, respectively.

A membrane inlet 63Ni ion mobility spectrometer interfaced to a quadrupole mass spectrometer with permeation, exponential dilution approaches and syringe-based systems were used to characterise the ion mobility spectrometry (IMS) response to phosgene in dry air (water concentration less than 16.5 mg m(-3)). Phosgene produced a principle product ion in the negative mode with a reduced mobility of 2.16 cm2 V(-1) s(-1), with an unresolved artefact at higher concentrations having a reduced mobility of 2.32 cm2 V(-1) s(-1). The limit of detection of the system with a membrane inlet fitted was estimated to be less than 1 mg m(-3), with an upper limit to the dynamic range of 32 mg m(-3). Mass spectrometric data indicated the existence of [(H2O)nCl]-, [(H2O)nCl2]-; [(H2O)n(O2)Cl]-; [(H2O)n(O)Cl]-; and, [(H2O)n(CO2)Cl]-. The existence of two possible mechanisms for product ion formation is proposed: dissociative electron capture, as well as hydrolysis followed by electron capture. The effect of water contamination of the drying media within the ion mobility spectrometer was also investigated, and the effects were similar to those observed previously with studies on chlorine. Reduced mobility of the product ions was observed to decrease with increasing water contamination of the drying media used within the instrument, while limits of detection increased slightly to less than 2.4 mg m(-3), with no significant effect on dynamic ranges of response or resolution. Preliminary results also indicated a positive mode response for phosgene, albeit at significantly higher concentrations to those observed in the negative mode.

A descriptive model to characterize a physiological property called receptive field, which is fundamental in deciphering how particular neurons encode the incoming visual stimulus, was built to accurately predict the direction of stimulus motion based on recorded directional selective retinal ganglion cells (DSRGCs) neural response. Briefly, building the model, space-time inseparability of the receptive fields of ON-OFF DSRGCs together with additional static non-linearity provided the principal key. The main steps we used were: analysis of the extracellularly recorded data from ON-OFF DSRGCs stimulated with white noise stimulus; calculation of spike triggered average in response to white noise stimulus and extracting the kernel; finding the optimal kernel by adjusting the estimated firing rate to the recorded firing rate; analysis of the extracellularly recorded data using new stimulus, consisting in drifting grating bars moving 45 degrees apart over the RFs of the ON-OFF DSRGCs; construction of the linear model; adding static non-linearity (i.e. spike threshold and saturation); comparing predicted data with recorded data. Similar methodology was used to test different scientific hypothesis [1], [2]. The optimal kernel needed to describe direction selectivity of ON-OFF DSRGCs was first extracted using white noise stimulus and produces an estimate of the firing rate that is a linear filter of the stimulus to which a nonlinear function was added. This is a function of the linear filter value instantaneously evaluated at the time of the rate estimation. Half wave rectification and saturation limit negative or unrealistically large values of the function. Static nonlinearity is then used to introduce firing thresholds into estimates of neural responses of ON-OFF DSRGCs. The direction of stimulus motion was accurately predicted for different preferred directions of the recorded cells by our model, as exemplified in Figure ​Figure1.1. However, the degree of direction selectivity (DSi) calculated from the tuning curves [3] was not 100% predicted. This slight underestimation of the direction selectivity degree (see Figure 1.B) suggests that for complex tasks, such as direction of stimulus motion, higher order non-linearity should be taken into account to improve the model performance. Intrinsic properties of ON-OFF DSRGCs like bursting or paired spiking activity can presumably improve the model accuracy. These results are in accordance with other scientific work related to different types of neurons and to different stimuli [1], [2]. Figure 1 A. Normalized tuning curves for 10 ON-OFF DSRGCs. Recorded responses (red plots) and predicted responses (blue plots) are indicating the same direction of stimulus motion. B. DSis for predicted responses are slightly underestimating the DSis for recorded ...