Volatile metabolic monitoring of glycemic status in diabetes using electronic olfaction

Fasting blood glucose in a Ghanaian adult is causally affected by malaria parasite load: a mechanistic case study using convergent cross mapping

BACKGROUND

Adults with diabetes mellitus (DM) in malaria-endemic areas might be more susceptible to Plasmodium infection than healthy individuals. Herein, the study was aimed at verifying the hypothesis that increased fasting blood glucose (FBG) promotes parasite growth as reflected by increased parasite density.

METHODS

Seven adults without DM were recruited in rural Ghana to determine the relationships between FBG and malaria parasite load. Socio-economic data were recorded in questionnaire-based interviews. Over a period of 6 weeks, FBG and Plasmodium sp. Infection were measured in peripheral blood samples photometrically and by polymerase chain reaction (PCR)-assays, respectively. Daily physical activity and weather data were documented via smartphone recording. For the complex natural systems of homeostatic glucose control and Plasmodium sp. life cycle, empirical dynamic modelling was applied.

RESULTS

At baseline, four men and three women (median age, 33 years; interquartile range, 30-48) showed a median FBG of 5.5 (5.1-6.0 mmol/L); one participant had an asymptomatic Plasmodium sp. infection (parasite density: 240/µL). In this participant, convergent cross mapping (CCM) for 34 consecutive days, showed that FBG was causally affected by parasite density (p < 0.02), while the reciprocal relationship was not discernible (p > 0.05). Additionally, daily ambient temperature affected parasite density (p < 0.01).

CONCLUSION

In this study population living in a malaria-endemic area, time series analyses were successfully piloted for the relationships between FBG and Plasmodium sp. density. Longer observation periods and larger samples are required to confirm these findings and determine the direction of causality.

Micromachined Optical Fiber Sensors for Biomedical Applications

Optical fibers revolutionized the rate of information reception and transmission in telecommunications. The revolution has now extended to the field of physicochemical sensing. Optical fiber sensors (OFSs) have found a multitude of applications, spanning from structural health monitoring to biomedical and clinical measurements due to their unique physical and functional advantages, such as small dimensions, light weight, immunity to electromagnetic interference, high sensitivity and resolution, multiplexing, and remote operation. OFSs generally rely on the detection of measurand-induced changes in the optical properties of the light propagating in the fiber, where the OFS essentially functions as the conduit and physical link between the probing light waves and the physicochemical parameters under investigation. Several advanced micromachining techniques have been developed to optimize the structure of OFSs, thus improving their sensing performance. These techniques include fusion splicing, tapering, polishing, and more complicated femtosecond laser micromachining methods. This chapter discusses and reviews the most recent developments in micromachined OFSs specifically for biomedical applications. Step-by-step procedures for several optical fiber micromachining techniques are detailed.

The electronic nose technology in clinical diagnosis: A systematic review

Supplemental Digital Content is available in the text

Background:

Volatile organic compounds (VOC) are end products of human metabolism (normal and disease-associated) that can be mainly excreted in breath, urine, and feces. Therefore, VOC can be very useful as markers of diseases and helpful for clinicians since its sampling is noninvasive, inexpensive, and painless. Electronic noses, or eNoses, provide an easy and inexpensive way to analyze gas samples. Thus, this device may be used for diagnosis, monitoring or phenotyping diseases according to specific breathprints (breath profile).

Objective:

In this review, we summarize data showing the ability of eNose to be used as a noninvasive tool to improve diagnosis in clinical settings.

Methods:

A PRISMA-oriented search was performed in PubMed and Cochrane Library. Only studies performed in humans and published since 2000 were included.

Results:

A total of 48 original articles, 21 reviews, and 7 other documents were eligible and fully analyzed. The quality assessment of the selected studies was conducted according to the Standards for Reporting of Diagnostic Accuracy. Airway obstructive diseases were the most studied and Cyranose 320 was the most used eNose.

Conclusions:

Several case–control studies were performed to test this technology in diverse fields. More than a half of the selected studies showed good accuracy. However, there are some limitations regarding sampling methodology, analysis, reproducibility, and external validation that need to be standardized. Additionally, it is urgent to test this technology in intend-to-treat populations. Thus, it is possible to think in the contribution of VOC analysis by eNoses in a clinical setting.

Biosensors to Monitor Water Quality Utilizing Insect Odorant-Binding Proteins as Detector Elements

In the developing world, the identification of clean, potable water continues to pose a pervasive challenge, and waterborne diseases due to fecal contamination of water supplies significantly threaten public health. The ability to efficiently monitor local water supplies is key to water safety, yet no low-cost, reliable method exists to detect contamination quickly. We developed an in vitro assay utilizing an odorant-binding protein (OBP), AgamOBP1, from the mosquito, Anopheles gambiae, to test for the presence of a characteristic metabolite, indole, from harmful coliform bacteria. We demonstrated that recombinantly expressed AgamOBP1 binds indole with high sensitivity. Our proof-of-concept assay is fluorescence-based and demonstrates the usefulness of insect OBPs as detector elements in novel biosensors that rapidly detect the presence of bacterial metabolic markers, and thus of coliform bacteria. We further demonstrated that rAgamOBP1 is suitable for use in portable, inexpensive "dipstick" biosensors that improve upon lateral flow technology since insect OBPs are robust, easily obtainable via recombinant expression, and resist detector "fouling." Moreover, due to their wide diversity and ligand selectivity, insect chemosensory proteins have other biosensor applications for various analytes. The techniques presented here therefore represent platform technologies applicable to various future devices.

Machine Learning Methods Applied to Predict Ventilator-Associated Pneumonia with Pseudomonas aeruginosa Infection via Sensor Array of Electronic Nose in Intensive Care Unit

One concern to the patients is the off-line detection of pneumonia infection status after using the ventilator in the intensive care unit. Hence, machine learning methods for ventilator-associated pneumonia (VAP) rapid diagnose are proposed. A popular device, Cyranose 320 e-nose, is usually used in research on lung disease, which is a highly integrated system and sensor comprising 32 array using polymer and carbon black materials. In this study, a total of 24 subjects were involved, including 12 subjects who are infected with pneumonia, and the rest are non-infected. Three layers of back propagation artificial neural network and support vector machine (SVM) methods were applied to patients’ data to predict whether they are infected with VAP with Pseudomonas aeruginosa infection. Furthermore, in order to improve the accuracy and the generalization of the prediction models, the ensemble neural networks (ENN) method was applied. In this study, ENN and SVM prediction models were trained and tested. In order to evaluate the models’ performance, a fivefold cross-validation method was applied. The results showed that both ENN and SVM models have high recognition rates of VAP with Pseudomonas aeruginosa infection, with 0.9479 ± 0.0135 and 0.8686 ± 0.0422 accuracies, 0.9714 ± 0.0131, 0.9250 ± 0.0423 sensitivities, and 0.9288 ± 0.0306, 0.8639 ± 0.0276 positive predictive values, respectively. The ENN model showed better performance compared to SVM in the recognition of VAP with Pseudomonas aeruginosa infection. The areas under the receiver operating characteristic curve of the two models were 0.9842 ± 0.0058 and 0.9410 ± 0.0301, respectively, showing that both models are very stable and accurate classifiers. This study aims to assist the physician in providing a scientific and effective reference for performing early detection in Pseudomonas aeruginosa infection or other diseases.

Cutting Edge Methods for Non-Invasive Disease Diagnosis Using E-Tongue and E-Nose Devices

Biomimetic cross-reactive sensor arrays (B-CRSAs) have been used to detect and diagnose a wide variety of diseases including metabolic disorders, mental health diseases, and cancer by analyzing both vapor and liquid patient samples. Technological advancements over the past decade have made these systems selective, sensitive, and affordable. To date, devices for non-invasive and accurate disease diagnosis have seen rapid improvement, suggesting a feasible alternative to current standards for medical diagnostics. This review provides an overview of the most recent B-CRSAs for diagnostics (also referred to electronic noses and tongues in the literature) and an outlook for future technological development.

The nematode Caenorhabditis elegans displays a chemotaxis behavior to tuberculosis-specific odorants

A simple, affordable diagnostic test for pulmonary tuberculosis (TB) is urgently needed to improve detection of active Mycobacterium tuberculosis. Recently, it has been suggested that animal behavior can be used as a biosensor to signal the presence of human disease. For example, the giant African pouched rats can detect tuberculosis by sniffing sputum specimens while trained honeybees respond to three of the volatile organic compounds (VOCs) detected in the breath of TB positive patients by proboscis extension. However, both rats and honeybees require animal housing facilities and professional trainers, which are outside the scope of most disease testing facilities. Here, we report that the innate olfactory behavioral response of the roundworm nematode Caenorhabditis elegans can be used to detect the TB-specific VOCs methyl p-anisate, methyl nicotinate, methyl phenylacetate and o-phenylanisole, in chemotaxis assays. Dauer larvae, a long-lived stress resistant alternative development state of C. elegans in which the animals can survive for extended periods of time in dry conditions with no food, were also demonstrated to detect the VOCs. We propose that exposing naive dauer larvae to TB-related VOCs and recording their response in this behavioral assay could lead to the development of a new method for TB diagnostics using breath as the sample type.

Identification of biomarkers in the hair of dogs: new diagnostic possibilities in the study and control of visceral leishmaniasis

Visceral leishmaniasis (VL) is a zoonosis whose etiologic agent in the Americas is Leishmania infantum, and dogs are the main host. Research and innovation in diagnostic techniques are essential to improve the surveillance and control of VL in endemic areas. The present study investigates the profile of the volatile organic compounds (VOCs) emitted by healthy dogs and by dogs infected by L. infantum to detect variations in the VOCs that may be used as biomarkers in the diagnosis of VL. In total, 36 dogs were selected from an endemic area and divided into three groups: G1, not infected with L. infantum; G2, infected without clinical signs of VL; and G3, infected with clinical signs of VL. To analyze the profiles of the VOCs emitted by dogs from the three groups, solid-phase microextraction (SPME) combined with gas chromatography-mass spectrometry (GC-MS) was used. Variations were observed between the profiles of the VOCs emitted in the three groups studied, and they also differentiated infected animals with or without clinical signs. Six VOCs were identified as potential biomarkers of infection, with significant variations between healthy dogs (G1) and infected dogs (G2 + G3). The detection of variations between groups G2 and G3 suggested that the profiles of some VOCs may be related to the type of immune response and the parasite load of the infected dogs. This study demonstrated the possibility of analysis of VOCs as biomarkers of VL in diagnostic, clinical, and epidemiological work.

Glucose prediction by analysis of exhaled metabolites - a systematic review

Background

In critically ill patients, glucose control with insulin mandates time– and blood–consuming glucose monitoring. Blood glucose level fluctuations are accompanied by metabolomic changes that alter the composition of volatile organic compounds (VOC), which are detectable in exhaled breath. This review systematically summarizes the available data on the ability of changes in VOC composition to predict blood glucose levels and changes in blood glucose levels.

Methods

A systematic search was performed in PubMed. Studies were included when an association between blood glucose levels and VOCs in exhaled air was investigated, using a technique that allows for separation, quantification and identification of individual VOCs. Only studies on humans were included.

Results

Nine studies were included out of 1041 identified in the search. Authors of seven studies observed a significant correlation between blood glucose levels and selected VOCs in exhaled air. Authors of two studies did not observe a strong correlation. Blood glucose levels were associated with the following VOCs: ketone bodies (e.g., acetone), VOCs produced by gut flora (e.g., ethanol, methanol, and propane), exogenous compounds (e.g., ethyl benzene, o–xylene, and m/p–xylene) and markers of oxidative stress (e.g., methyl nitrate, 2–pentyl nitrate, and CO).

Conclusion

There is a relation between blood glucose levels and VOC composition in exhaled air. These results warrant clinical validation of exhaled breath analysis to monitor blood glucose levels.

Cellular scent of influenza virus infection

Volatile organic compounds (VOCs) emanating from humans have the potential to revolutionize non-invasive diagnostics. Yet, little is known about how these compounds are generated by complex biological systems, and even less is known about how these compounds are reflective of a particular physiological state. In this proof-of-concept study, we examined VOCs produced directly at the cellular level from B lymphoblastoid cells upon infection with three live influenza virus subtypes: H9N2 (avian), H6N2 (avian), and H1N1 (human). Using a single cell line helped to alleviate some of the complexity and variability when studying VOC production by an entire organism, and it allowed us to discern marked differences in VOC production upon infection of the cells. The patterns of VOCs produced in response to infection were unique for each virus subtype, while several other non-specific VOCs were produced after infections with all three strains. Also, there was a specific time course of VOC release post infection. Among emitted VOCs, production of esters and other oxygenated compounds was particularly notable, and these may be attributed to increased oxidative stress resulting from infection. Elucidating VOC signatures that result from the host cells response to infection may yield an avenue for non-invasive diagnostics and therapy of influenza and other viral infections.

Exhaled breath analysis by electronic nose in airways disease. Established issues and key questions

Exhaled air contains many volatile organic compounds (VOCs) that are the result of normal and disease-associated metabolic processes anywhere in the body. Different omics techniques can assess the pattern of these VOCs. One such omics technique suitable for breath analysis is represented by electronic noses (eNoses), providing fingerprints of the exhaled VOCs, called breathprints. Breathprints have been shown to be altered in different disease states, including in asthma and COPD. This review describes the current status on clinical validation and application of breath analysis by electronic noses in the diagnosis and monitoring of chronic airways diseases. Furthermore, important methodological issues including breath sampling, modulating factors and incompatibility between eNoses are raised and discussed. Next steps towards clinical application of electronic noses are provided, including further validation in suspected disease, assessment of the influence of different comorbidities, the value in longitudinal monitoring of patients with asthma and COPD and the possibility to predict treatment responses. Eventually, a Breath Cloud may be constructed, a large database containing disease-specific breathprints. When collaborative efforts are put into optimization of this technique, it can provide a rapid and non-invasive first line diagnostic test.

Neurologic infections in diabetes mellitus

Even at a time when HIV/AIDS and immunosuppressive therapy have increased the number of individuals living with significant immunocompromise, diabetes mellitus (DM) remains a major comorbid disorder for several rare but potentially lethal infections, including rhino-orbital-cerebral mucormycosis and malignant external otitis. DM is also a commonly associated condition in patients with nontropical pyomyositis, pyogenic spinal infections, Listeria meningitis, and blastomycosis. As West Nile virus spread to and across North America over a decade ago, DM appeared in many series as a risk factor for death or neuroinvasive disease. More recently, in several large international population-based studies, DM was identified as a risk factor for herpes zoster. The relationships among infection, DM, and the nervous system are multidirectional. Viral infections have been implicated in the pathogenesis of type 1 and type 2 DM, while parasitic infections have been hypothesized to protect against autoimmune disorders, including type 1 DM. DM-related neurologic disease can predispose to systemic infection - polyneuropathy is the predominant risk factor for diabetic foot infection. Because prognosis for many neurologic infections depends on timely institution of antimicrobial and sometimes surgical therapy, neurologists caring for diabetic patients should be familiar with the clinical features of the neuroinfectious syndromes associated with DM.

Can volatile compounds in exhaled breath be used to monitor control in diabetes mellitus?

Although it has been known for centuries that there are compounds in exhaled breath that are altered in disease, it is only in the last few decades that it has been possible to measure them with sufficient accuracy and precision to make them clinically useful. The clinical utility of breath analysis has also been limited by the practical difficulties of collecting representative breath samples, free from contaminants. More recent methods of breath analysis have allowed real-time analysis of breath, eliminating the need for sample collection, and therefore potentially allowing the rapid feedback of results to patient and clinician. One possible future application of breath analysis may be the monitoring of metabolic control in patients with diabetes mellitus. This perspective article provides an overview of the studies of breath analysis in diabetes, focusing on the breath metabolites; acetone, isoprene and also methyl nitrate that have previously been reported to be altered in diabetes, highlighting the factors that may potentially confound their interpretation. Specific attention is given to selected ion flow tube mass spectrometry (SIFT-MS) and proton transfer reaction mass spectrometry (PTR-MS), because they are techniques that have been developed specifically for the absolute quantification of breath metabolites in real time, although reference is made to some of the alternative techniques, including sensors and optical devices. Whilst breath analysis, using SIFT-MS, PTR-MS and other sensitive techniques, can potentially be used for the non-invasive monitoring of metabolic conditions that may include diabetes mellitus, further work is required in terms of the clinical and analytical validation. Furthermore, it is unclear at present what breath metabolites should be monitored and what factors may confound their interpretation. Although a non-invasive method of monitoring glycaemic control is clearly desirable, it will be important to demonstrate its analytical comparability with the well-established and validated methods for blood glucose measurement.

Type 2 diabetes mellitus and increased risk for malaria infection

A case–control study of 1,466 urban adults in Ghana found that patients with type 2 diabetes mellitus had a 46% increased risk for infection with Plasmodium falciparum. Increase in diabetes mellitus prevalence may put more persons at risk for malaria infection.

Differences in exhaled gas profiles between patients with type 2 diabetes and healthy controls

AIMS

Recent advances in analytical technology allow the detection of several hundred volatile organic compounds (VOCs) in human exhaled air, many of which reflect unidentified endogenous pathways. This study was performed to determine whether a breath gas analysis using proton transfer reaction-mass spectrometry (PTR-MS) could serve as a noninvasive method to distinguish between patients with type 2 diabetes mellitus and healthy controls.

METHODS

Breath and room air samples were measured from 21 patients with insulin-treated type 2 diabetes and 26 healthy controls. VOCs in the mass range of 20-200 atomic mass units were analyzed using PTR-MS.

RESULTS

We identified eight masses characteristic of endogenous VOCs that showed significant differences in the gas profiles of patients with type 2 diabetes and healthy control subjects. Using these VOCs for linear discriminant analysis, the sensitivity and specificity were found to be 90% and 92%, respectively.

CONCLUSIONS

These results suggest that it is possible to separate patients with diabetes mellitus type 2 from healthy controls by multivariate analysis of exhaled endogenous VOCs. This is a first step towards the development of a noninvasive test using breath gas of at-risk persons and making it an attractive option for large-scale testing of at-risk populations. However, the establishment of exhaled volatiles as metabolic markers requires additional confirmatory investigations.

Extra-oral halitosis: an overview

Halitosis can be subdivided into intra-oral and extra-oral halitosis, depending on the place where it originates. Most reports now agree that the most frequent sources of halitosis exist within the oral cavity and include bacterial reservoirs such as the dorsum of the tongue, saliva and periodontal pockets, where anaerobic bacteria degrade sulfur-containing amino acids to produce the foul smelling volatile sulfur compounds (VSCs), especially hydrogen sulfide (H(2)S) and methyl mercaptan (CH(3)SH). Tongue coating is considered to be the most important source of VSCs. Oral malodor can now be treated effectively. Special attention in this overview is given to extra-oral halitosis. Extra-oral halitosis can be subdivided into non-blood-borne halitosis, such as halitosis from the upper respiratory tract including the nose and from the lower respiratory tract, and blood-borne halitosis. The majority of patients with extra-oral halitosis have blood-borne halitosis. Blood-borne halitosis is also frequently caused by odorous VSCs, in particular dimethyl sulfide (CH3SCH3). Extra-oral halitosis, covering about 5-10% of all cases of halitosis, might be a manifestation of a serious disease for which treatment is much more complicated than for intra-oral halitosis. It is therefore of utmost importance to differentiate between intra-oral and extra-oral halitosis. Differences between intra-oral and extra-oral halitosis are discussed extensively. The importance of applying odor characterization of various odorants in halitosis research is also highlighted in this article. The use of the odor index, odor threshold values and simulation of bad breath samples is explained.

Volatile compounds characteristic of sinus-related bacteria and infected sinus mucus: analysis by solid-phase microextraction and gas chromatography-mass spectrometry

Volatile compounds from human breath are a potential source of information for disease diagnosis. Breath may include volatile organic compounds (VOCs) originating in the nasal sinuses. If the sinuses are infected, disease-specific volatiles may enter exhaled air. Sinus infections are commonly caused by several known bacteria. We examined the volatiles characteristic of infectious bacteria in culture using solid-phase microextraction to collect and gas chromatography-mass spectrometry as well as gas chromatography with flame photometric detection to separate and analyze the resulting VOCs. Infected sinus mucus samples were also collected and their VOCs examined. Similar characteristic volatiles were seen from both cultures of individual "pure" bacteria and several mucus samples. However, the relative amounts of characteristic VOCs from individual bacteria differ greatly between cultures and sinus mucus. New compounds, not seen in culture were also seen in some mucus samples. Our results suggest an important role for growth substrate and environment. Our data further suggests that in some sinus mucus samples identification of bacteria-specific volatiles is possible and can suggest the identity of an infecting organism to physicians. Knowledge of these bacteria-related volatiles is necessary to create electronic nose-based, volatile-specific sensors for non-invasive examination for suspected sinus infection.

Solid-state, dye-labeled DNA detects volatile compounds in the vapor phase

This paper demonstrates a previously unreported property of deoxyribonucleic acid—the ability of dye-labeled, solid-state DNA dried onto a surface to detect odors delivered in the vapor phase by changes in fluorescence. This property is useful for engineering systems to detect volatiles and provides a way for artificial sensors to emulate the way cross-reactive olfactory receptors respond to and encode single odorous compounds and mixtures. Recent studies show that the vertebrate olfactory receptor repertoire arises from an unusually large gene family and that the receptor types that have been tested so far show variable breadths of response. In designing biomimetic artificial noses, the challenge has been to generate a similarly large sensor repertoire that can be manufactured with exact chemical precision and reproducibility and that has the requisite combinatorial complexity to detect odors in the real world. Here we describe an approach for generating and screening large, diverse libraries of defined sensors using single-stranded, fluorescent dye–labeled DNA that has been dried onto a substrate and pulsed with brief exposures to different odors. These new solid-state DNA-based sensors are sensitive and show differential, sequence-dependent responses. Furthermore, we show that large DNA-based sensor libraries can be rapidly screened for odor response diversity using standard high-throughput microarray methods. These observations describe new properties of DNA and provide a generalized approach for producing explicitly tailored sensor arrays that can be rationally chosen for the detection of target volatiles with different chemical structures that include biologically derived odors, toxic chemicals, and explosives.

Biological systems can provide engineering guidance on how evolution has solved particular problems. In the context of detecting chemicals in either the aqueous or vapor phase, two general biological approaches have emerged. The first relies on individual highly specific single receptors (sensors), each tuned to detect a single molecular species—examples include the receptors that mediate pheromone detection in insects or those that function in neurotransmission. Specificity is achieved by narrow band design. The second approach is implemented by arrays of receptors with relatively broad responses. In this case, specificity emerges from a constellation of receptor types that recognizes the molecule of interest—the canonical example here is the olfactory receptors in the main olfactory system of vertebrates. Specificity is achieved by a “one chemical–many broadly responsive detectors” paradigm. While trying to mimic the enormous odor coding ability of biological olfaction in an “artificial nose,” we searched for molecules with the requisite combinatorial capacity to serve as odor detectors. Here we show that single-stranded DNA molecules tagged with a fluorescent reporter and deposited onto solid surfaces can respond to vapor phase odor pulses in a sequence-selective manner. These findings demonstrate new properties of nucleotide molecules that can be exploited in engineered odor detection devices. In addition, this broadband responsivity to small molecules should be explored as a functional aspect of DNA (and RNA) as they exist in the normal cellular milieu.

Short sequences of solid-state DNA can selectively signal their interactions with small molecules in the vapor phase. These observations have been implemented in odor sensing in an electronic "nose" and further suggest that in vivo responses to small molecules may represent new, nongenetic attributes of DNA.

Medical applications of electronic nose technology

Electronic nose technology has been developed over the past 15 years in the field of chemistry as an electronic equivalent of the biologic mechanism of smell. Since its inception, it has been well recognized that there is great potential in applying this technology to the field of medicine. This review discusses those areas of medicine in which electronic nose technology has been applied. For each area, this review addresses the scope of the medical problem that has been studied, how the electronic nose technology may help address the medical problem, and the results of such studies to date. Next generation electronic noses will be refined to better analyze specific disease states. This will require further evaluation of the specific volatiles to be tested. This information may then be brought to bear on refinement of the chemistry of the electronic nose sensors, making them more sensitive and specific for the particular disease of interest. The ultimate goal of work in this arena is to make an electronic nose that is portable, fast, inexpensive and, therefore, suitable for use in the examination room or at the bedside, making it facile as a diagnostic tool.

Detection of lung cancer by sensor array analyses of exhaled breath

RATIONALE

Electronic noses are successfully used in commercial applications, including detection and analysis of volatile organic compounds in the food industry.

OBJECTIVES

We hypothesized that the electronic nose could identify and discriminate between lung diseases, especially bronchogenic carcinoma.

METHODS

In a discovery and training phase, exhaled breath of 14 individuals with bronchogenic carcinoma and 45 healthy control subjects or control subjects without cancer was analyzed. Principal components and canonic discriminant analysis of the sensor data was used to determine whether exhaled gases could discriminate between cancer and noncancer. Discrimination between classes was performed using Mahalanobis distance. Support vector machine analysis was used to create and apply a cancer prediction model prospectively in a separate group of 76 individuals, 14 with and 62 without cancer.

MAIN RESULTS

Principal components and canonic discriminant analysis demonstrated discrimination between samples from patients with lung cancer and those from other groups. In the validation study, the electronic nose had 71.4% sensitivity and 91.9% specificity for detecting lung cancer; positive and negative predictive values were 66.6 and 93.4%, respectively. In this population with a lung cancer prevalence of 18%, positive and negative predictive values were 66.6 and 94.5%, respectively.

CONCLUSION

The exhaled breath of patients with lung cancer has distinct characteristics that can be identified with an electronic nose. The results provide feasibility to the concept of using the electronic nose for managing and detecting lung cancer.

The development of minimally invasive continuous Metabolic Monitoring Technologies in the U.S. Army TMM Research Program

The Technologies for Metabolic Monitoring and Julia Weaver Fund Research Program (TMM) promotes the development of minimally invasive, innovative technologies for the monitoring and assessment of metabolic changes that are important to the management of diabetes. This program also promotes the advancement of biological monitoring technologies for healthy individuals operating in extreme environments, such as soldiers and astronauts. These technologies have focused on measurements of analytes in interstitial fluids and functional outcomes related to glucose regulation. TMM investigators have advanced new sensing methods and are working to overcome technological barriers to long-term implants. This paper reviews the current goals, research areas, and future direction of the program.