Diabetes noninvasive diagnostics and monitoring through volatile biomarkers analysis in the exhaled breath using optical absorption spectroscopy

The review is aimed on the analysis the abilities of noninvasive diagnostics and monitoring of diabetes mellitus (DM) and DM-associated complications through volatile molecular biomarkers detection in the exhaled breath. The specific biochemical reactions in the body of DM patients and their associations with volatile molecular biomarkers in the breath are considered. The applications of optical spectroscopy methods, including UV, IR, and terahertz spectroscopy for DM-associated volatile molecular biomarkers measurements, are described. The applications of similar technique combined with machine learning methods in DM diagnostics using the profile of DM-associated volatile molecular biomarkers in exhaled air or "pattern-recognition" approach are discussed.

The State of the Art on Graphene-Based Sensors for Human Health Monitoring through Breath Biomarkers

The field of organic-borne biomarkers has been gaining relevance due to its suitability for diagnosing pathologies and health conditions in a rapid, accurate, non-invasive, painless and low-cost way. Due to the lack of analytical techniques with features capable of analysing such a complex matrix as the human breath, the academic community has focused on developing electronic noses based on arrays of gas sensors. These sensors are assembled considering the excitability, sensitivity and sensing capacities of a specific nanocomposite, graphene. In this way, graphene-based sensors can be employed for a vast range of applications that vary from environmental to medical applications. This review work aims to gather the most relevant published papers under the scope of "Graphene sensors" and "Biomarkers" in order to assess the state of the art in the field of graphene sensors for the purposes of biomarker identification. During the bibliographic search, a total of six pathologies were identified as the focus of the work. They were lung cancer, gastric cancer, chronic kidney diseases, respiratory diseases that involve inflammatory processes of the airways, like asthma and chronic obstructive pulmonary disease, sleep apnoea and diabetes. The achieved results, current development of the sensing sensors, and main limitations or challenges of the field of graphene sensors are discussed throughout the paper, as well as the features of the experiments addressed.

Diagnosis of Carcinogenic Pathologies through Breath Biomarkers: Present and Future Trends

The assessment of volatile breath biomarkers has been targeted with a lot of interest by the scientific and medical communities during the past decades due to their suitability for an accurate, painless, non-invasive, and rapid diagnosis of health states and pathological conditions. This paper reviews the most relevant bibliographic sources aiming to gather the most pertinent volatile organic compounds (VOCs) already identified as putative cancer biomarkers. Here, a total of 265 VOCs and the respective bibliographic sources are addressed regarding their scientifically proven suitability to diagnose a total of six carcinogenic diseases, namely lung, breast, gastric, colorectal, prostate, and squamous cell (oesophageal and laryngeal) cancers. In addition, future trends in the identification of five other forms of cancer, such as bladder, liver, ovarian, pancreatic, and thyroid cancer, through perspective volatile breath biomarkers are equally presented and discussed. All the results already achieved in the detection, identification, and quantification of endogenous metabolites produced by all kinds of normal and abnormal processes in the human body denote a promising and auspicious future for this alternative diagnostic tool, whose future passes by the development and employment of newer and more accurate collection and analysis techniques, and the certification for utilisation in real clinical scenarios.

Increased breath naphthalene in children with asthma and wheeze of the All Age Asthma Cohort (ALLIANCE)

Exhaled breath contains numerous volatile organic compounds (VOCs) known to be related to lung disease like asthma. Its collection is non-invasive, simple to perform and therefore an attractive method for the use even in young children. We analysed breath in children of the multicenter All Age Asthma Cohort (ALLIANCE) to evaluate if 'breathomics' have the potential to phenotype patients with asthma and wheeze, and to identify extrinsic risk factors for underlying disease mechanisms. A breath sample was collected from 142 children (asthma: 51, pre-school wheezers: 55, healthy controls: 36) and analysed using gas chromatography-mass spectrometry (GC/MS). Children were diagnosed according to Global Initiative for Asthma guidelines and comprehensively examined each year over up to seven years. Forty children repeated the breath collection after 24 or 48 months. Most breath VOCs differing between groups reflect the exposome of the children. We observed lower levels of lifestyle-related VOCs and higher levels of the environmental pollutants, especially naphthalene, in children with asthma or wheeze. Naphthalene was also higher in symptomatic patients and in wheezers with recent inhaled corticosteroid use. No relationships with lung function or TH2 inflammation were detected. Increased levels of naphthalene in asthmatics and wheezers and the relationship to disease severity could indicate a role of environmental or indoor air pollution for the development or progress of asthma. Breath VOCs might help to elucidate the role of the exposome for the development of asthma. The study was registered at ClinicalTrials.gov (NCT02496468).

An explorative study on respiratory health among operators working in polymer additive manufacturing

Additive manufacturing (AM), or 3D printing, is a growing industry involving a wide range of different techniques and materials. The potential toxicological effects of emissions produced in the process, involving both ultrafine particles and volatile organic compounds (VOCs), are unclear, and there are concerns regarding possible health implications among AM operators. The objective of this study was to screen the presence of respiratory health effects among people working with liquid, powdered, or filament plastic materials in AM.

Methods

In total, 18 subjects working with different additive manufacturing techniques and production of filament with polymer feedstock and 20 controls participated in the study. Study subjects filled out a questionnaire and underwent blood and urine sampling, spirometry, impulse oscillometry (IOS), exhaled NO test (FeNO), and collection of particles in exhaled air (PEx), and the exposure was assessed. Analysis of exhaled particles included lung surfactant components such as surfactant protein A (SP-A) and phosphatidylcholines. SP-A and albumin were determined using ELISA. Using reversed-phase liquid chromatography and targeted mass spectrometry, the relative abundance of 15 species of phosphatidylcholine (PC) was determined in exhaled particles. The results were evaluated by univariate and multivariate statistical analyses (principal component analysis).

Results

Exposure and emission measurements in AM settings revealed a large variation in particle and VOC concentrations as well as the composition of VOCs, depending on the AM technique and feedstock. Levels of FeNO, IOS, and spirometry parameters were within clinical reference values for all AM operators. There was a difference in the relative abundance of saturated, notably dipalmitoylphosphatidylcholine (PC16:0_16:0), and unsaturated lung surfactant lipids in exhaled particles between controls and AM operators.

Conclusion

There were no statistically significant differences between AM operators and controls for the different health examinations, which may be due to the low number of participants. However, the observed difference in the PC lipid profile in exhaled particles indicates a possible impact of the exposure and could be used as possible early biomarkers of adverse effects in the airways.

Bacterial and fungal communities in indoor aerosols from two Kuwaiti hospitals

The airborne transmission of COVID-19 has drawn immense attention to bioaerosols. The topic is highly relevant in the indoor hospital environment where vulnerable patients are treated and healthcare workers are exposed to various pathogenic and non-pathogenic microbes. Knowledge of the microbial communities in such settings will enable precautionary measures to prevent any hospital-mediated outbreak and better assess occupational exposure of the healthcare workers. This study presents a baseline of the bacterial and fungal population of two major hospitals in Kuwait dealing with COVID patients, and in a non-hospital setting through targeted amplicon sequencing. The predominant bacteria of bioaerosols were Variovorax (9.44%), Parvibaculum (8.27%), Pseudonocardia (8.04%), Taonella (5.74%), Arthrospira (4.58%), Comamonas (3.84%), Methylibium (3.13%), Sphingobium (4.46%), Zoogloea (2.20%), and Sphingopyxis (2.56%). ESKAPEE pathogens, such as Pseudomonas, Acinetobacter, Staphylococcus, Enterococcus, and Escherichia, were also found in lower abundances. The fungi were represented by Wilcoxinia rehmii (64.38%), Aspergillus ruber (9.11%), Penicillium desertorum (3.89%), Leptobacillium leptobactrum (3.20%), Humicola grisea (2.99%), Ganoderma sichuanense (1.42%), Malassezia restricta (0.74%), Heterophoma sylvatica (0.49%), Fusarium proliferatum (0.46%), and Saccharomyces cerevisiae (0.23%). Some common and unique operational taxonomic units (OTUs) of bacteria and fungi were also recorded at each site; this inter-site variability shows that exhaled air can be a source of this variation. The alpha-diversity indices suggested variance in species richness and abundance in hospitals than in non-hospital sites. The community structure of bacteria varied spatially (ANOSIM r 2 = 0.181-0.243; p < 0.05) between the hospital and non-hospital sites, whereas fungi were more or less homogenous. Key taxa specific to the hospitals were Defluvicoccales, fungi, Ganodermataceae, Heterophoma, and H. sylvatica compared to Actinobacteria, Leptobacillium, L. leptobacillium, and Cordycipitaceae at the non-hospital site (LefSe, FDR q ≤ 0.05). The hospital/non-hospital MD index > 1 indicated shifts in the microbial communities of indoor air in hospitals. These findings highlight the need for regular surveillance of indoor hospital environments to prevent future outbreaks.

Detection of differentiated thyroid carcinoma in exhaled breath with an electronic nose

This proof-of-principle study investigates the diagnostic performance of the Aeonose in differentiating malignant from benign thyroid diseases based on volatile organic compound analysis in exhaled breath. All patients with a suspicious thyroid nodule planned for surgery, exhaled in the Aeonose. Definitive diagnosis was provided by histopathological determination after surgical resection. Breath samples were analyzed utilizing artificial neural networking. About 133 participants were included, 48 of whom were diagnosed with well-differentiated thyroid cancer. A sensitivity of 0.73 and a negative predictive value (NPV) of 0.82 were found. The sensitivity and NPV improved to 0.94 and 0.95 respectively after adding clinical variables via multivariate logistic regression analysis. This study demonstrates the feasibility of the Aeonose to discriminate between malignant and benign thyroid disease. With a high NPV, low cost, and non-invasive nature, the Aeonose may be a promising diagnostic tool in the detection of thyroid cancer.

Application of machine learning and laser optical-acoustic spectroscopy to study the profile of exhaled air volatile markers of acute myocardial infarction

Conventional acute myocardial infarction (AMI) diagnosis is quite accurate and has proved its effectiveness. However, despite this, discovering more operative methods of this disease detection is underway. From this point of view, the application of exhaled air analysis for a similar diagnosis is valuable. The aim of the paper is to research effective machine learning algorithms for the predictive model for AMI diagnosis constructing, using exhaled air spectral data. The target group included 30 patients with primary myocardial infarction. The control group included 42 healthy volunteers. The 'LaserBreeze' laser gas analyzer (Special Technologies Ltd, Russia), based on the dual-channel resonant photoacoustic detector cell and optical parametric oscillator as the laser source, had been used. The pattern recognition approach was applied in the same manner for the set of extracted concentrations of AMI volatile markers and the set of absorption coefficients in a most informative spectral range 2.900 ± 0.125µm. The created predictive model based on the set of absorption coefficients provided 0.86 of the mean values of both the sensitivity and specificity when linear support vector machine (SVM) combined with principal component analysis was used. The created predictive model based on using six volatile AMI markers (C₅H₁₂, N₂O, NO₂, C₂H₄, CO, CO₂) provided 0.82 and 0.93 of the mean values of the sensitivity and specificity, respectively, when linear SVM was used.

Non-Invasive Diagnosis of Malignancies Based on the Analysis of Markers in Exhaled Air

Novel non-invasive methods for the diagnosis of malignancies should be effective for early diagnosis, reproducible, inexpensive, and independent from the human factor. Our aim was to establish the applicability of the non-invasive method, based on the analysis of air exhaled by patients who are at different stages of oropharyngeal, larynx and lung cancer. The diagnostic device includes semiconductor sensors capable of measuring the concentrations of gas components in exhaled air, with the high sensitivity of 1 ppm. The neural network uses signals from these sensors to perform classification and identify cancer patients. Prior to the diagnostic procedure of the non-invasive method, we clarified the extent and stage of the tumor according to current international standards and recommendations for the diagnosis of malignancies. The statistical dataset for neural network training and method validation included samples from 121 patients with the most common tumor localizations (lungs, oropharyngeal region and larynx). The largest number of cases (21 patients) were lung cancer, while the number of patients with oropharyngeal or laryngeal cancer varied from 1 to 9, depending on tumor localization (oropharyngeal, tongue, oral cavity, larynx and mucosa of the lower jaw). In the case of lung cancer, the parameters of the diagnostic device are determined as follows: sensitivity—95.24%, specificity—76.19%. For oropharyngeal cancer and laryngeal cancer, these parameters were 67.74% and 87.1%, respectively. This non-invasive method could lead to relevant medicinal findings and provide an opportunity for clinical utility and patient benefit upon early diagnosis of malignancies.

Reference Ranges of 8-Isoprostane Concentrations in Exhaled Breath Condensate (EBC): A Systematic Review and Meta-Analysis

Isoprostanes are physiopathologic mediators of oxidative stress, resulting in lipid peroxidation. 8-isoprostane seems particularly useful for measuring oxidative stress damage. However, no reference range values are available for 8-isoprosante in exhaled breath condensate (EBC) of healthy adults, enabling its meaningful interpretation as a biomarker. We conducted this systematic review and meta-analysis according to the protocol following PROSPERO (CRD42020146623). After searching and analyzing the literature, we included 86 studies. After their qualitative synthesis and risk of bias assessment, 52 studies were included in meta-analysis. The latter focused on studies using immunological analytical methods and investigated how the concentrations of 8-isoprostane differ based on gender. We found that gender had no significant effect in 8-isoprostane concentration. Among other studied factors, such as individual characteristics and factors related to EBC collection, only the device used for EBC collection significantly affected measured 8-isoprostane concentrations. However, adjustment for the factors related to EBC collection, yielded uncertainty whether this effect is due to the device itself or to the other factors. Given this uncertainty, we estimated the reference range values of 8-isoprostane stratified by gender and EBC collection device. A better standardization of EBC collection seems necessary; as well more studies using chemical analytical methods to extend this investigation.

Sugar Beet Pectin Supplementation Did Not Alter Profiles of Fecal Microbiota and Exhaled Breath in Healthy Young Adults and Healthy Elderly

Aging is accompanied with increased frailty and comorbidities, which is potentially associated with microbiome perturbations. Dietary fibers could contribute to healthy aging by beneficially impacting gut microbiota and metabolite profiles. We aimed to compare young adults with elderly and investigate the effect of pectin supplementation on fecal microbiota composition, short chain fatty acids (SCFAs), and exhaled volatile organic compounds (VOCs) while using a randomized, double-blind, placebo-controlled parallel design. Fifty-two young adults and 48 elderly consumed 15 g/day sugar beet pectin or maltodextrin for four weeks. Fecal and exhaled breath samples were collected before and after the intervention period. Fecal samples were used for microbiota profiling by 16S rRNA gene amplicon sequencing, and for analysis of SCFAs by gas chromatography (GC). Breath was used for VOC analysis by GC-tof-MS. Young adults and elderly showed similar fecal SCFA and exhaled VOC profiles. Additionally, fecal microbiota profiles were similar, with five genera significantly different in relative abundance. Pectin supplementation did not significantly alter fecal microbiota, SCFA or exhaled VOC profiles in elderly or young adults. In conclusion, aside from some minor differences in microbial composition, healthy elderly and young adults showed comparable fecal microbiota composition and activity, which were not altered by pectin supplementation.

Non-invasive lung disease diagnostics from exhaled microdroplets of lung fluid: perspectives and technical challenges

The combination of ultra-sensitive assay techniques and recent improvements in the instrumentation used to collect microdroplets of lung fluid (MLF) from exhaled breath has enabled the development of non-invasive lung disease diagnostics that are based on MLF analysis. In one example of this approach, electrospun nylon filters were used to collect MLFs from patients with pulmonary tuberculosis. The filters were washed to obtain liquid probes, which were then tested for human immunoglobulin A (h-IgA) and fractions of h-IgA specific to ESAT-6 and Psts-1, two antigens secreted by Mycobacterium tuberculosis. Probes collected for 10 min contained 100-1500 fg of h-IgA and, in patients with pulmonary tuberculosis, a portion of these h-IgA molecules showed specificity to the secreted antigens. Separate MLFs and their dry residues were successfully collected using an electrostatic collector and impactor developed especially for this purpose. Visualization of MLF dry residues by atomic force microscopy made it possible to estimate the lipid content in each MLF and revealed mucin molecules in some MLFs. This exciting new approach will likely make it possible to detect biomarkers in individual MLFs. MLFs emerging from an infection site ('hot' microdroplets) are expected to be enriched with infection biomarkers. This paper discusses possible experimental approaches to detecting biomarkers in single MLFs, as well as certain technological problems that need to be resolved in order to develop new non-invasive diagnostics based on analysing biomarkers in separate MLFs.

Diagnosis by Volatile Organic Compounds in Exhaled Breath from Lung Cancer Patients Using Support Vector Machine Algorithm

Monitoring exhaled breath is a very attractive, noninvasive screening technique for early diagnosis of diseases, especially lung cancer. However, the technique provides insufficient accuracy because the exhaled air has many crucial volatile organic compounds (VOCs) at very low concentrations (ppb level). We analyzed the breath exhaled by lung cancer patients and healthy subjects (controls) using gas chromatography/mass spectrometry (GC/MS), and performed a subsequent statistical analysis to diagnose lung cancer based on the combination of multiple lung cancer-related VOCs. We detected 68 VOCs as marker species using GC/MS analysis. We reduced the number of VOCs and used support vector machine (SVM) algorithm to classify the samples. We observed that a combination of five VOCs (CHN, methanol, CH₃CN, isoprene, 1-propanol) is sufficient for 89.0% screening accuracy, and hence, it can be used for the design and development of a desktop GC-sensor analysis system for lung cancer.

Advances in gas chromatographic methods for the identification of biomarkers in cancer

Screening complex biological specimens such as exhaled air, tissue, blood and urine to identify biomarkers in different forms of cancer has become increasingly popular over the last decade, mainly due to new instruments and improved bioinformatics. However, despite some progress, the identification of biomarkers has shown to be a difficult task with few new biomarkers (excluding recent genetic markers) being considered for introduction to clinical analysis. This review describes recent advances in gas chromatographic methods for the identification of biomarkers in the detection, diagnosis and treatment of cancer. It presents a general overview of cancer metabolism, the current biomarkers used for cancer diagnosis and treatment, a background to metabolic changes in tumors, an overview of current GC methods, and collectively presents the scope and outlook of GC methods in oncology.

Effects of Hypoxia on Nitric Oxide (NO) in Skin Gas and Exhaled Air

This study confirmed the effects of hypoxia on nitric oxide (NO) concentrations in skin gas and exhaled air. NO concentrations in skin gas and exhaled air were measured by a chemiluminescence analyzer. Arterial oxygen saturation (SpO2) of the right forefinger was determined using an oxygen saturation monitor. The M ± SEM of NO concentrations in skin gas at 20.93% (control), 15.1% and 14.8% oxygen concentrations were 23.7 ± 3.6, 32.3 ± 4.7 and 36.2 ± 5.2 ppb, respectively. M ± SEM of NO concentrations in exhaled air at 20.93% (control), 15.1%, and 14.8% were 25.0 ± 5.1, 35.01 ± 5.6 and 44.9 ± 7.2 ppb, respectively. There was no significant difference in NO concentration at the absolute value of skin gas and exhaled air between normoxia and hypoxia. But significant increase was found at relative changes in skin gas at 15.1% (p<0.01) and 14.8% (p<0.01) oxygen content compared with control. Significant increase was also found at relative changes in exhaled air at 15.1% (p<0.01) and 14.8% (p<0.01) oxygen content compared with control. In conclusion, we confirmed that exposure to hypoxia elicits an increase in NO concentrations at relative changes of skin gas and exhaled air compared to normoxia.