Clinical application of volatile organic compound analysis for detecting infectious diseases. Clin Microbiol Rev. 2013;26:462-475. [PMID: 23824368 DOI: 10.1128/cmr.00020-13]

Metal-Organic Frameworks in Surface Enhanced Raman Spectroscopy-Based Analysis of Volatile Organic Compounds

Volatile Organic Compounds (VOC) are a major class of environmental pollutants hazardous to human health, but also highly relevant in other fields including early disease diagnostics and organoleptic perception of aliments. Therefore, accurate analysis of VOC is essential, and a need for new analytical methods is witnessed for rapid on-site detection without complex sample preparation. Surface-Enhanced Raman Spectroscopy (SERS) offers a rapidly developing versatile analytical platform for the portable detection of chemical species. Nonetheless, the need for efficient docking of target analytes at the metallic surface significantly narrows the applicability of SERS. This limitation can be circumvented by interfacing the sensor surface with Metal-Organic Frameworks (MOF). These materials featuring chemical and structural versatility can efficiently pre-concentrate low molecular weight species such as VOC through their ordered porous structure. This review presents recent trends in the development of MOF-based SERS substrates with a focus on elucidating respective design rules for maximizing analytical performance. An overview of the status of the detection of harmful VOC is discussed in the context of industrial and environmental monitoring. In addition, a survey of the analysis of VOC biomarkers for medical diagnosis and emerging applications in aroma and flavor profiling is included.

The Potential of Fecal Volatile Organic Compound Analysis for the Early Diagnosis of Late-Onset Sepsis in Preterm Infants: A Narrative Review

Early diagnosis and treatment of late-onset sepsis (LOS) is crucial for survival, but challenging. Intestinal microbiota and metabolome alterations precede the clinical onset of LOS, and the preterm gut is considered an important source of bacterial pathogens. Fecal volatile organic compounds (VOCs), formed by physiologic and pathophysiologic metabolic processes in the preterm gut, reflect a complex interplay between the human host, the environment, and microbiota. Disease-associated fecal VOCs can be detected with an array of devices with various potential for the development of a point-of-care test (POCT) for preclinical LOS detection. While characteristic VOCs for common LOS pathogens have been described, their VOC profiles often overlap with other pathogens due to similarities in metabolic pathways, hampering the construction of species-specific profiles. Clinical studies have, however, successfully discriminated LOS patients from healthy individuals using fecal VOC analysis with the highest predictive value for Gram-negative pathogens. This review discusses the current advancements in the development of a non-invasive fecal VOC-based POCT for early diagnosis of LOS, which may potentially provide opportunities for early intervention and targeted treatment and could improve clinical neonatal outcomes. Identification of confounding variables impacting VOC synthesis, selection of an optimal detection device, and development of standardized sampling protocols will allow for the development of a novel POCT in the near future.

Smelly interactions: host-borne volatile organic compounds triggering behavioural responses in mosquitoes, sand flies, and ticks

Volatile organic compounds (VOCs) are chemicals emitted as products of cell metabolism, which reflects the physiological and pathological conditions of any living organisms. These compounds play a key role as olfactory cues for arthropod vectors such as mosquitoes, sand flies, and ticks, which act in the transmission of pathogens to many animal species, including humans. Some VOCs may influence arthropod behaviour, e.g., host preference and oviposition site selection for gravid females. Furthermore, deadly vector-borne pathogens such as Plasmodium falciparum and Leishmania infantum are suggested to manipulate the VOCs profile of the host to make them more attractive to mosquitoes and sand fly vectors, respectively. Under the above circumstances, studies on these compounds have demonstrated their potential usefulness for investigating the behavioural response of mosquitoes, sand flies, and ticks toward their vertebrate hosts, as well as potential tools for diagnosis of vector-borne diseases (VBDs). Herein, we provide an account for scientific data available on VOCs to study the host seeking behaviour of arthropod vectors, and their usefulness as attractants, repellents, or tools for an early diagnosis of VBDs.

Diagnostic performance of volatile organic compounds analysis and electronic noses for detecting colorectal cancer: a systematic review and meta-analysis

Introduction

The detection of Volatile Organic Compounds (VOCs) could provide a potential diagnostic modality for the early detection and surveillance of colorectal cancers. However, the overall diagnostic accuracy of the proposed tests remains uncertain.

Objective

This systematic review is to ascertain the diagnostic accuracy of using VOC analysis techniques and electronic noses (e-noses) as noninvasive diagnostic methods for colorectal cancer within the realm of clinical practice.

Methods

A systematic search was undertaken on PubMed, EMBASE, Web of Science, and the Cochrane Library to scrutinize pertinent studies published from their inception to September 1, 2023. Only studies conducted on human subjects were included. Meta-analysis was performed using a bivariate model to obtain summary estimates of sensitivity, specificity, and positive and negative likelihood ratios. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was deployed for quality assessment. The protocol for this systematic review was registered in PROSPERO, and PRISMA guidelines were used for the identification, screening, eligibility, and selection process.

Results

This review encompassed 32 studies, 22 studies for VOC analysis and 9 studies for e-nose, one for both, with a total of 4688 subjects in the analysis. The pooled sensitivity and specificity of VOC analysis for CRC detection were 0.88 (95% CI, 0.83-0.92) and 0.85 (95% CI, 0.78-0.90), respectively. In the case of e-nose, the pooled sensitivity was 0.87 (95% CI, 0.83-0.90), and the pooled specificity was 0.78 (95% CI, 0.62-0.88). The area under the receiver operating characteristic analysis (ROC) curve for VOC analysis and e-noses were 0.93 (95% CI, 0.90-0.95) and 0.90 (95% CI, 0.87-0.92), respectively.

Conclusion

The outcomes of this review substantiate the commendable accuracy of VOC analysis and e-nose technology in detecting CRC. VOC analysis has a higher specificity than e-nose for the diagnosis of CRC and a sensitivity comparable to that of e-nose. However, numerous limitations, including a modest sample size, absence of standardized collection methods, lack of external validation, and a notable risk of bias, were identified. Consequently, there exists an imperative need for expansive, multi-center clinical studies to elucidate the applicability and reproducibility of VOC analysis or e-nose in the noninvasive diagnosis of colorectal cancer.

Systematic review registration

https://www.crd.york.ac.uk/prospero/#recordDetails, identifier CRD42023398465.

Association between individual sensor behavior of an electronic nose and airways inflammation in children with asthma: a pilot study at alpine altitude climate

BACKGROUND

Markers of airway inflammation can be helpful in the management of childhood asthma. Residential activities, such as intensive asthma camps at alpine altitude climate (AAC), can help reduce bronchial inflammation in patients who fail to achieve optimal control of the disease. Analysis of volatile organic compounds (VOCs) can be obtained using electronic devices such as e-Noses. We aimed to identify alterations in urinary e-Nose sensors among children with asthma participating in an intensive camp at AAC and to investigate associations between urinary e-Nose analysis and airway inflammation.

METHODS

We analyzed data collected in children with asthma recruited between July and September 2020. All children were born and resided at altitudes below 600 m asl. Urinary VOCs (measured using the Cyranose 320® VOC analyzer), Fractional exhaled Nitric Oxide (FeNO) and spirometry were evaluated upon children's arrival at the Istituto Pio XII, Misurina (BL), Italy, at 1756 m asl (T0), and after 7 (T1) and 15 days (T2) of stay.

RESULTS

Twenty-two patients (68.2% males; median age: 14.5 years) were enrolled. From T0 to T1 and T2, the negative trend for FeNO was significant (p < .001). Significant associations were observed between e-Nose sensors S7 (p = .002), S12 (p = .013), S16 (p = .027), S17 (p = .017), S22 (p = .029), S29 (p = .021), S31 (p = .009) and ΔFeNO at T0-T1. ΔFeNO at T0-T2 was significantly associated with S17 (p = .015), S19 (p = .004), S21 (p = .020), S24 (p = .012), S25 (p = .018), S26 (p = .008), S27 (p = .002), S29 (p = .007), S30 (p = .013).

CONCLUSIONS

We showed that a decrease in FeNO levels after a short sojourn at AAC is associated with behaviors of individual urinary e-Nose sensors in children with asthma.

Breath of Health: spectroscopy-based breath test for the detection of SARS-CoV-2

BACKGROUND

Nucleic acid amplification tests (NAAT) are considered the gold standard for COVID-19 diagnosis. These tests require professional manpower and equipment, long processing and swab sampling which is unpleasant to the patients. Several volatile organic compounds (VOCs) have been identified in the breath of COVID-19 patients. Detection of these VOCs using a breath test could help rapidly identify COVID-19 patients.

OBJECTIVE

Assess the accuracy of 'Breath of Health' (BOH) COVID-19 Fourier-transform infra-red (FTIR) Spectroscopy-based breath test.

METHODS

Breath samples from patients with or without symptoms suggestive for COVID-19 who had NAAT results were collected using Tedlar bags and were blindly analysed using BOH FTIR spectroscopy. BOH Measures several VOCs simultaneously and differentiating positive and negative results. BOH results were compared to NAAT results as gold standard.

RESULTS

Breath samples from 531 patients were analysed. The sensitivity of BOH breath test was found to be 79.5% and specificity was 87.2%. Positive predictive value (PPV) was 74.7% and negative predictive value (NPV) 90.0%. Calculated accuracy rate was 84.8% and area under the curve 0.834. Subgroup analysis revealed that the NPV of patients without respiratory symptoms was superior over the NPV of symptomatic patients (94.7% vs 80.7%, P-value < 0.0001) and PPV of patients with respiratory symptoms outranks the PPV of individuals without symptoms (85.3% vs 69.2%, P-value 0.0196).

CONCLUSION

We found BOH COVID-19 breath test to be a patient-friendly, rapid, non-invasive diagnostic test with high accuracy rate and NPV that could efficiently rule out COVID-19 especially among individuals with low pre-test probability.

Highly sensitive serum volatolomic biomarkers for pancreatic cancer diagnosis

The discovery of new diagnostic tools for the early detection of diseases with poor prognosis such as pancreatic adenocarcinoma (PAC) is of high importance. The results from a control-case study (20 PAC patients, 19 healthy controls) for the search of new biomarkers of pancreatic cancer based in differences in the serum volatolome are presented in this work. Volatolomics were performed following a non-targeted HS-SPME-GC/MS approach, and a total of 433 volatile organic compounds (VOCs) was detected in the human serum samples. Of these, 125 VOC indexes showed a significant variation when controls and patients were compared (p-value < 0.05). Bonferroni corrected p-values < 0.05 were found for 40 features. PCA analysis showed the control-PAC discrimination capability of VOCs in serum, and PLS-DA was performed to select the best candidate biomarkers for the diagnosis of PAC. For the 40 selected VOCs, calculated areas under the curve (AUC) ranged from 0.98 to 0.85, and 11 of them were successfully validated using an independent set of samples (5 PAC patients, 5 healthy controls). Four of the proposed PAC biomarkers were identified as toluene, 2-ethyl-1-hexanol, pentylbenzene, and butoxymethylbenzene. Combinations of the identified PAC biomarkers were tested and showed AUC > 0.90, with the more promising candidate being butoxymethylbenzene (AUC = 0.98).

Understanding PFAS toxicity through cell culture metabolomics: Current applications and future perspectives

Per- and polyfluoroalkyl substances (PFAS), ubiquitous environmental contaminants, pose significant challenges to ecosystems and human health. While cell cultures have emerged as new approach methodologies (NAMs) in ecotoxicity research, metabolomics is an emerging technique used to characterize the small-molecule metabolites present in cells and to understand their role in various biological processes. Integration of metabolomics with cell cultures, known as cell culture metabolomics, provides a novel and robust tool to unravel the complex molecular responses induced by PFAS exposure. In vitro testing also reduces reliance on animal testing, aligning with ethical and regulatory imperatives. The current review summarizes key findings from recent studies utilizing cell culture metabolomics to investigate PFAS toxicity, highlighting alterations in metabolic pathways, biomarker identification, and the potential linkages between metabolic perturbations. Additionally, the paper discusses different types of cell cultures and metabolomics methods used for studies of environmental contaminants and particularly PFAS. Future perspectives on the combination of metabolomics with other advanced technologies, such as single-cell metabolomics (SCM), imaging mass spectrometry (IMS), extracellular flux analysis (EFA), and multi-omics are also explored, which offers a holistic understanding of environmental contaminants. The synthesis of current knowledge and identification of research gaps provide a foundation for future investigations that aim to elucidate the complexities of PFAS-induced cellular responses and contribute to the development of effective strategies for mitigating their adverse effects on human health.

GC-MS-based metabolomics of volatile organic compounds in exhaled breath: applications in health and disease. A review

Exhaled breath analysis, with particular emphasis on volatile organic compounds, represents a growing area of clinical research due to its obvious advantages over other diagnostic tests. Numerous pathologies have been extensively investigated for the identification of specific biomarkers in exhalates through metabolomics. However, the transference of breath tests to clinics remains limited, mainly due to deficiency in methodological standardization. Critical steps include the selection of breath sample types, collection devices, and enrichment techniques. GC-MS is the reference analytical technique for the analysis of volatile organic compounds in exhalates, especially during the biomarker discovery phase in metabolomics. This review comprehensively examines and compares metabolomic studies focusing on cancer, lung diseases, and infectious diseases. In addition to delving into the experimental designs reported, it also provides a critical discussion of the methodological aspects, ranging from the experimental design and sample collection to the identification of potential pathology-specific biomarkers.

Point-of-care detection devices for wound care and monitoring

Healthcare resources are heavily burdened by infections that impede the wound-healing process. A wide range of advanced technologies have been developed for detecting and quantifying infection biomarkers. Finding a timely, accurate, non-invasive diagnostic alternative that does not require a high level of training is a critical step toward arresting common clinical patterns of wound health decline. There is growing interest in the development of innovative diagnostics utilizing a variety of emerging technologies, and new biomarkers have been investigated as potential indicators of wound infection. In this review, we summarize diagnostics available for wound infection, including those used in clinics and still under development.

Distinct emissions of biogenic volatile organic compounds from temperate benthic taxa

INTRODUCTION

Biogenic volatile organic compounds (BVOCs) are emitted by all organisms as intermediate or end-products of metabolic processes. Individual BVOCs perform important physiological, ecological and climatic functions, and collectively constitute the volatilome-which can be reflective of organism taxonomy and health. Although BVOC emissions of tropical benthic reef taxa have recently been the focus of multiple studies, emissions derived from their temperate counterparts have never been characterised.

OBJECTIVES

Characterise the volatilomes of key competitors for benthic space among Australian temperate reefs.

METHODS

Six fragments/fronds of a temperate coral (Plesiastrea versipora) and a macroalga (Ecklonia radiata) from a Sydney reef site were placed within modified incubation chambers filled with seawater. Organism-produced BVOCs were captured on thermal desorption tubes using a purge-and-trap methodology, and were then analysed using GC × GC - TOFMS and multivariate tests.

RESULTS

Analysis detected 55 and 63 BVOCs from P. versipora and E. radiata respectively, with 30 of these common between species. Each taxon was characterised by a similar relative composition of chemical classes within their volatilomes. However, 14 and 10 volatiles were distinctly emitted by either E. radiata or P. versipora respectively, including the halogenated compounds iodomethane, tribromomethane, carbon tetrachloride and trichloromonofluoromethane. While macroalgal cover was 3.7 times greater than coral cover at the sampling site, P. versipora produced on average 17 times more BVOCs per cm2 of live tissue, resulting in an estimated contribution to local BVOC emission that was 4.7 times higher than E. radiata.

CONCLUSION

Shifts in benthic community composition could disproportionately impact local marine chemistry and affect how ecosystems contribute to broader BVOC emissions.

Detection of medically relevant volatile organic compounds with graphene field-effect transistors and separated by low-frequency spectral and time signatures

Exhaled human breath contains a mixture of gases including nitrogen, oxygen, carbon dioxide, water vapour and low molecular weight volatile organic compounds (VOCs). Different VOCs detected in human breath condensate have been recently related to several metabolic processes occurring inside body tissues in the pathological state, as candidate biomarkers for monitoring conditions such as lung injury, airway inflammation, immunity dysfunction, infection, and cancer. Current techniques for detecting these compounds include several types of mass spectroscopy, which are highly costly, time-consuming and dependent on trained personnel for sample analysis. The need for fast and label-free biosensors is paving the way towards the design of novel and portable electronic devices for point-of-care diagnosis with VOCs such as E-noses, and based on the measurement of signal signatures derived from their chemical composition. In this paper, we propose a device for VOC detection that was tested inside a controlled gas flow setup, resorting to graphene field-effect transistors (GFETs). Electrical measurements from graphene directly exposed to nitrogen plus VOC vapours involved cyclic measurements for the variation of graphene's resistance and low-frequency spectral noise in order to obtain distinctive signatures of the tested compounds in the time and frequency domains related, respectively, to Gutmann's theory for donor-acceptor chemical species and spectral sub-band analysis.

Electronic nose versus VITEK 2 system for the rapid diagnosis of bloodstream infections

Infectious diseases that spread through the bloodstream, known as bloodstream infections (BSIs), are a major global health problem. Positive outcomes for patients with sepsis are typically the result of prompt treatment started after an early diagnosis of BSIs. In this study, we evaluated the capabilities of a portable electronic nose (E-Nose) to detect BSIs with two commonly isolated Gram-negative bacterial species, E. coli and K. pneumonia. One hundred and five blood samples were randomly collected for blood culture examinations using BACTEC and VITEK 2 system, and headspace analysis by an E-Nose from June to December 2021. Classification accuracy of E. coli, K. pneumonia, and negative controls was measured using principal component analysis, area under the receiver operating characteristic curve, sensitivity, and specificity analysis. After incubation for 24 h, cluster plots generated using principal component analysis demonstrated that E-Nose could accurately diagnose the presence of E. coli and K. pneumonia in BACTEC blood culture bottles with a sensitivity and specificity of 100% in just 120 s. The E-Nose method has been shown to be an immediate, precise, and cost-effective alternative to automated blood culture BACTEC and VITEK 2 systems for the fast detection of the causative bacterial pathogens of BSIs in clinical practice. Thus, patients with such Gram-negative bacteremia can have guided empirical antimicrobial therapy on the same day of BSIs diagnosis, which can be lifesaving.

Detection of tuberculosis-associated compounds from human skin by GCxGC-TOFMS

Tuberculosis (TB) remains a global health concern. This study aimed to investigate the potential of human skin volatile organic compounds (VOCs) as prospective biomarkers for TB diagnosis. It employed a non-invasive approach using a wearable silicone rubber band for VOC sampling, comprehensive gas chromatography - time of flight mass spectrometry (GCxGC-TOFMS), and chemometric techniques. Both targeted and untargeted biochemical screening was utilized to explore biochemical differences between healthy individuals and those with TB infection. Results confirmed a correlation between compounds found in this study, and those reported for TB from other biofluids. In a comparison to known TB-associated compounds from other biofluids our analysis established the presence of 27 of these compounds emanating from human skin. Additionally, 16 previously unreported compounds were found as potential biomarkers. The diagnostic ability of the VOCs selected by statistical methods was investigated using predictive modelling techniques. Artificial neural network multi-layered perceptron (ANN) yielded two compounds, 1H-indene, 2,3 dihydro-1,1,3-trimethyl-3-phenyl; and heptane-3-ethyl-2-methyl, as the most discriminatory, and could differentiate between TB-positive (n = 15) and TB-negative (n = 23) individuals with an area under the receiver operating characteristic curve (AUROC) of 92 %, a sensitivity of 100 % and a specificity of 94 % for six targeted features. For untargeted analysis, ANN assigned 3-methylhexane as the most discriminatory between TB-positive and TB- negative individuals. An AUROC of 98.5 %, a sensitivity of 83 %, and a specificity of 88 % were obtained for 16 untargeted features as chosen by high performance variable selection. The obtained values compare highly favourable to alternative diagnostic methods such as breath analysis and GeneXpert. Consequently, human skin VOCs hold considerable potential as a TB diagnostic screening test.

Identification of a marker of infection in the breath using a porcine pneumonia model

Objective

Pneumonia, both in the community and the hospital setting, represents a significant cause of morbidity and mortality in the cardiothoracic patient population. Diagnosis of pneumonia can be masked by other disease processes and is often diagnosed after the patient is already experiencing the disease. A noninvasive, sensitive test for pneumonia could decrease hospitalizations and length of stay for patients. We have developed a porcine model of pneumonia and evaluated the exhaled breath of infected pigs for biomarkers of infection.

Methods

Anesthetized 60-kg adult pigs were intubated, and a bronchoscope was used to instill a solution containing 12 × 108 cfu of methicillin-sensitive Staphylococcus aureus or a control solution without bacteria (Sham) into the distal airways. The pigs were then reintubated on postoperative days 3, 6, and 9, with bronchoscopic bronchial lavages taken at each time point. At each time point, a 500-mL breath was captured from each pig. The breath was evacuated over a silicon microchip, with the volatile carbonyl compounds from the breath captured via oximation reaction, and the results of this capture were analyzed by ultra-high performance liquid chromatography mass spectrometry.

Results

A total of 64% of the pigs inoculated with methicillin-sensitive S. aureus demonstrated consolidation on chest radiography and increasing counts of methicillin-sensitive S. aureus in the bronchial lavages over the span of the experiment, consistent with development of pneumonia. Analysis of the exhaled breath demonstrated 1 carbonyl compound (2-pentenal) that increased 10-fold over the span of the experiment, from an average of 0.0294 nmol/L before infection to an average of 0.3836 nmol/L on postoperative day 9. The amount of 2-pentenal present was greater in the breath of infected pigs than in the noninfected pigs or the sham inoculated pigs at postoperative days 6 and 9. Using an elevated concentration of 2-pentenal as a marker of infection yielded a sensitivity of 88% and specificity of 92% at postoperative day 6, and a sensitivity and specificity of 100% at postoperative day 9.

Conclusions

We were able to successfully develop a clinical pneumonia in adult 60-kg pigs. The concentration of 2-pentenal correlated with the presence of pneumonia, demonstrating the potential for this compound to function as a biomarker for methicillin-sensitive S. aureus infection in pigs.

The Detection of Bacteria in the Maxillary Sinus Secretion of Patients With Acute Rhinosinusitis Using an Electronic Nose: A Pilot Study

OBJECTIVE

Detecting bacteria as a causative pathogen of acute rhinosinusitis (ARS) is a challenging task. Electronic nose technology is a novel method for detecting volatile organic compounds (VOCs) that has also been studied in association with the detection of several diseases. The aim of this pilot study was to analyze maxillary sinus secretion with differential mobility spectrometry (DMS) and to determine whether the secretion demonstrates a different VOC profile when bacteria are present.

METHODS

Adult patients with ARS symptoms were examined. Maxillary sinus contents were aspirated for bacterial culture and DMS analysis. k-Nearest neighbor and linear discriminant analysis were used to classify samples as positive or negative, using bacterial cultures as a reference.

RESULTS

A total of 26 samples from 15 patients were obtained. After leave-one-out cross-validation, k-nearest neighbor produced accuracy of 85%, sensitivity of 67%, specificity of 94%, positive predictive value of 86%, and negative predictive value of 84%.

CONCLUSIONS

The results of this pilot study suggest that bacterial positive and bacterial negative sinus secretion release different VOCs and that DMS has the potential to detect them. However, as the results are based on limited data, further conclusions cannot be made. DMS is a novel method in disease diagnostics and future studies should examine whether the method can detect bacterial ARS by analyzing exhaled air.

Putative volatile biomarkers of bovine tuberculosis infection in breath, skin and feces of cattle

Bovine tuberculosis (bTB) is an infectious disease with significant impact on animal health, public health and international trade. Standard bTB screening in live cattle consists in injecting tuberculin and measuring the swelling at the place of injection few days later. This procedure is expensive, time-consuming, logistically challenging, and is not conclusive before performing confirmatory tests and additional analysis. The analysis of the volatile organic compounds (VOCs) emitted by non-invasive biological samples can provide an alternative diagnostic approach suitable for bTB screening. In the present study, we analyzed VOC samples emitted through the breath, feces and skin of 18 cows diagnosed with bTB from three farms from Romania, as well as of 27 negative cows for bTB from the same farms. Analytical studies employing gas chromatography coupled to mass spectrometry revealed 80 VOCs emitted through the breath, 200 VOCs released by feces, and 80 VOCs emitted through the skin. Statistical analysis of these compounds allowed the identification of 3 tentative breath VOC biomarkers (acetone; 4-methyldecane; D-limonene), 9 tentative feces VOC biomarkers (toluene; [(1,1-dimethylethyl)thio]acetic acid; alpha-thujene; camphene; phenol; o-cymene; 3-(1,1-dimethylethyl)-2,2,4,4-tetramethyl-3-pentanol; 2,5-dimethylhexane-2,5-dihydroperoxide; 2,4-di-tert-butylphenol), and 3 tentative skin VOC biomarkers (ammonia; 1-methoxy-2-propanol; toluene). The possible pathway of these volatile biomarkers is discussed.

Sniffing out safety: canine detection and identification of SARS-CoV-2 infection from armpit sweat

Detection dogs were trained to detect SARS-CoV-2 infection based on armpit sweat odor. Sweat samples were collected using cotton pads under the armpits of negative and positive human patients, confirmed by qPCR, for periods of 15-30 min. Multiple hospitals and organizations throughout Belgium participated in this study. The sweat samples were stored at -20°C prior to being used for training purposes. Six dogs were trained under controlled atmosphere conditions for 2-3 months. After training, a 7-day validation period was conducted to assess the dogs' performances. The detection dogs exhibited an overall sensitivity of 81%, specificity of 98%, and an accuracy of 95%. After validation, training continued for 3 months, during which the dogs' performances remained the same. Gas chromatography/mass spectrometry (GC/MS) analysis revealed a unique sweat scent associated with SARS-CoV-2 positive sweat samples. This scent consisted of a wide variety of volatiles, including breakdown compounds of antiviral fatty acids, skin proteins and neurotransmitters/hormones. An acceptability survey conducted in Belgium demonstrated an overall high acceptability and enthusiasm toward the use of detection dogs for SARS-CoV-2 detection. Compared to qPCR and previous canine studies, the detection dogs have good performances in detecting SARS-CoV-2 infection in humans, using frozen sweat samples from the armpits. As a result, they can be used as an accurate pre-screening tool in various field settings alongside the PCR test.

Diagnostic potential of plasma biomarkers and exhaled volatile organic compounds in predicting the different stages of acute mesenteric ischaemia: protocol for a multicentre prospective observational study (TACTIC study)

INTRODUCTION

Acute mesenteric ischaemia (AMI) is a life-threatening condition with short-term mortality of up to 80%. The diagnosis of AMI has remained troublesome due to the non-specific clinical presentation, symptoms and laboratory findings. Early unambiguous diagnosis of AMI is critical to prevent progression from reversible to irreversible transmural intestinal damage, thereby decreasing morbidity and improving survival. The present study aims to validate a panel of plasma biomarkers and investigate volatile organic compound (VOC) profiles in exhaled air as a tool to timely and accurately diagnose AMI.

METHODS AND ANALYSIS

In this international multicentre prospective observational study, 120 patients (>18 years of age) will be recruited with clinical suspicion of AMI. Clinical suspicion is based on: (1) clinical manifestation, (2) physical examination, (3) laboratory measurements and (4) the physician's consideration to perform a CT scan. The patient's characteristics, repetitive blood samples and exhaled air will be prospectively collected. Plasma levels of mucosal damage markers intestinal fatty acid-binding protein and villin-1, as well as transmural damage marker smooth muscle protein 22-alpha, will be assessed by ELISA. Analysis of VOCs in exhaled air will be performed by gas chromatography time-of-flight mass spectrometry. Diagnosis of AMI will be based on CT, endovascular and surgical reports, clinical findings, and (if applicable) verified by histopathological examination.

ETHICS AND DISSEMINATION

The study protocol was approved by the Medical Research Ethics Committee (METC) of Maastricht University Medical Centre+ and Maastricht University (METC azM/UM), the Netherlands (METC19-010) and the Ethics Committee Research UZ/KU Leuven, Belgium (S63500). Executive boards and local METCs of other Dutch participating centres Gelre Ziekenhuizen (Apeldoorn), Medisch Spectrum Twente (Enschede), and University Medical Centre Groningen have granted permission to carry out this study. Study results will be disseminated via open-access peer-reviewed scientific journals and national/international conferences.

TRIAL REGISTRATION NUMBER

NCT05194527.

Volatile Organic Compound Assessment as a Screening Tool for Early Detection of Gastrointestinal Diseases

Gastrointestinal (GI) diseases have a high prevalence throughout the United States. Screening and diagnostic modalities are often expensive and invasive, and therefore, people do not utilize them effectively. Lack of proper screening and diagnostic assessment may lead to delays in diagnosis, more advanced disease at the time of diagnosis, and higher morbidity and mortality rates. Research on the intestinal microbiome has demonstrated that dysbiosis, or unfavorable alteration of organismal composition, precedes the onset of clinical symptoms for various GI diseases. GI disease diagnostic research has led to a shift towards non-invasive methods for GI screening, including chemical-detection tests that measure changes in volatile organic compounds (VOCs), which are the byproducts of bacterial metabolism that result in the distinct smell of stool. Many of these tools are expensive, immobile benchtop instruments that require highly trained individuals to interpret the results. These attributes make them difficult to implement in clinical settings. Alternatively, electronic noses (E-noses) are relatively cheaper, handheld devices that utilize multi-sensor arrays and pattern recognition technology to analyze VOCs. The purpose of this review is to (1) highlight how dysbiosis impacts intestinal diseases and how VOC metabolites can be utilized to detect alterations in the microbiome, (2) summarize the available VOC analytical platforms that can be used to detect aberrancies in intestinal health, (3) define the current technological advancements and limitations of E-nose technology, and finally, (4) review the literature surrounding several intestinal diseases in which headspace VOCs can be used to detect or predict disease.

Electronic Nose Development and Preliminary Human Breath Testing for Rapid, Non-Invasive COVID-19 Detection

We adapted an existing, spaceflight-proven, robust "electronic nose" (E-Nose) that uses an array of electrical resistivity-based nanosensors mimicking aspects of mammalian olfaction to conduct on-site, rapid screening for COVID-19 infection by measuring the pattern of sensor responses to volatile organic compounds (VOCs) in exhaled human breath. We built and tested multiple copies of a hand-held prototype E-Nose sensor system, composed of 64 chemically sensitive nanomaterial sensing elements tailored to COVID-19 VOC detection; data acquisition electronics; a smart tablet with software (App) for sensor control, data acquisition and display; and a sampling fixture to capture exhaled breath samples and deliver them to the sensor array inside the E-Nose. The sensing elements detect the combination of VOCs typical in breath at parts-per-billion (ppb) levels, with repeatability of 0.02% and reproducibility of 1.2%; the measurement electronics in the E-Nose provide measurement accuracy and signal-to-noise ratios comparable to benchtop instrumentation. Preliminary clinical testing at Stanford Medicine with 63 participants, their COVID-19-positive or COVID-19-negative status determined by concomitant RT-PCR, discriminated between these two categories of human breath with a 79% correct identification rate using "leave-one-out" training-and-analysis methods. Analyzing the E-Nose response in conjunction with body temperature and other non-invasive symptom screening using advanced machine learning methods, with a much larger database of responses from a wider swath of the population, is expected to provide more accurate on-the-spot answers. Additional clinical testing, design refinement, and a mass manufacturing approach are the main steps toward deploying this technology to rapidly screen for active infection in clinics and hospitals, public and commercial venues, or at home.

iOBPdb A Database for Experimentally Determined Functional Characterization of Insect Odorant Binding Proteins

Odorant binding proteins (OBPs) are extra-cellular proteins that solubilize and transport volatile organic compounds (VOCs). Thousands of OBPs have been identified through genome sequencing, and hundreds have been characterized by fluorescence ligand binding assays in individual studies. There is a limited understanding of the comparative structure-function relations of OBPs, primarily due to a lack of a centralized database that relates OBP binding affinity and structure. Combining 181 functional studies containing 382 unique OBPs from 91 insect species, we present a database, iOBPdb, of OBP binding affinities for 622 individual VOC targets. This initial database provides powerful search and associative capabilities for retrieving and analyzing OBP-VOC binding interaction data. We have validated this dataset using phylogenetic mapping to determine the authenticity of the collected sequences and whether they cluster according to their assigned subfamilies. Potential applications include developing molecular probes for biosensors, novel bioassays and drugs, targeted pesticides that inhibit VOC/OBP interactions, and understanding odor sensing and perception in the brain.

Evolution of tuberculosis diagnostics: From molecular strategies to nanodiagnostics

Tuberculosis has remained a global concern for public health affecting the lives of people for ages. Approximately 10 million people are affected by the disease and 1.5 million succumb to the disease worldwide annually. The COVID-19 pandemic has highlighted the role of early diagnosis to win the battle against such infectious diseases. Thus, advancement in the diagnostic approaches to provide early detection forms the foundation to eradicate and manage contagious diseases like tuberculosis. The conventional diagnostic strategies include microscopic examination, chest X-ray and tuberculin skin test. The limitations associated with sensitivity and specificity of these tests demands for exploring new techniques like probe-based assays, CRISPR-Cas and microRNA detection. The aim of the current review is to envisage the correlation between both the conventional and the newer approaches to enhance the specificity and sensitivity. A significant emphasis has been placed upon nanodiagnostic approaches manipulating quantum dots, magnetic nanoparticles, and biosensors for accurate diagnosis of latent, active and drug-resistant TB. Additionally, we would like to ponder upon a reliable method that is cost-effective, reproducible, require minimal infrastructure and provide point-of-care to the patients.

β-Propiolactone (BPL)-inactivation of SARS-Co-V-2: in vitro validation with focus on saliva from COVID-19 patients for scent dog training

β-Propiolactone (BPL) is an organic compound widely used as an inactivating agent in vaccine development and production, for example for SARS-CoV, SARS-CoV-2 and Influenza viruses. Inactivation of pathogens by BPL is based on an irreversible alkylation of nucleic acids but also on acetylation and cross-linking between proteins, DNA or RNA. However, the protocols for BPL inactivation of viruses vary widely. Handling of infectious, enriched SARS-CoV-2 specimens and diagnostic samples from COVID-19 patients is recommended in biosafety level (BSL)-3 or BSL-2 laboratories, respectively. We validated BPL inactivation of SARS-CoV-2 in saliva samples with the objective to use saliva from COVID-19 patients for training of scent dogs for the detection of SARS-CoV-2 positive individuals. Therefore, saliva samples and cell culture medium buffered with NaHCO₃ (pH 8.3) were comparatively spiked with SARS-CoV-2 and inactivated with 0.1% BPL for 1hour (h) or 71h (± 1h) at 2-8°C, followed by hydrolysis of BPL at 37°C for 1 or 2h, converting BPL into non-toxic beta-hydroxy-propionic acid. SARS-CoV-2 inactivation was demonstrated by a titre reduction of up to 10^4 TCID₅₀/ml in the spiked samples for both inactivation periods using virus titration and virus isolation, respectively. The validated method was confirmed by successful inactivation of pathogens in saliva samples from COVID-19 patients. Furthermore, we reviewed the currently available literature on SARS-CoV-2 inactivation by BPL. Accordingly, BPL-inactivated, hydrolysed samples can be handled in a non-laboratory setting. Furthermore, our BPL inactivation protocols can be adapted to validation experiments with other pathogens.

Microbial Epidemiology of the Cystic Fibrosis Airways: Past, Present, and Future

Progressive obstructive lung disease secondary to chronic airway infection, coupled with impaired host immunity, is the leading cause of morbidity and mortality in cystic fibrosis (CF). Classical pathogens found in the airways of persons with CF (pwCF) include Pseudomonas aeruginosa, Staphylococcus aureus, the Burkholderia cepacia complex, Achromobacter species, and Haemophilus influenzae. While traditional respiratory-tract surveillance culturing has focused on this limited range of pathogens, the use of both comprehensive culture and culture-independent molecular approaches have demonstrated complex highly personalized microbial communities. Loss of bacterial community diversity and richness, counteracted with relative increases in dominant taxa by traditional CF pathogens such as Burkholderia or Pseudomonas, have long been considered the hallmark of disease progression. Acquisition of these classic pathogens is viewed as a harbinger of advanced disease and postulated to be driven in part by recurrent and frequent antibiotic exposure driven by frequent acute pulmonary exacerbations. Recently, CF transmembrane conductance regulator (CFTR) modulators, small molecules designed to potentiate or restore diminished protein levels/function, have been successfully developed and have profoundly influenced disease course. Despite the multitude of clinical benefits, structural lung damage and consequent chronic airway infection persist in pwCF. In this article, we review the microbial epidemiology of pwCF, focus on our evolving understanding of these infections in the era of modulators, and identify future challenges in infection surveillance and clinical management.

Identification of volatile biomarkers of Trichomonas vaginalis infection in vaginal discharge and urine

Trichomoniasis, a disease caused by Trichomonas vaginalis, is the most common non-viral sexually transmitted infection worldwide. The importance of its diagnosis lies in its ease of transmission and the absence of symptoms in most cases, as occurs in men, which have a significant role as asymptomatic carriers. The most widely used diagnostic methods are the fresh examination of vaginal or urethral secretions and molecular techniques. However, as they have some disadvantages and, sometimes, low sensitivity, new trichomoniasis diagnostic methods are necessary. Volatile organic compounds in clinical samples are effective in the diagnosis of different diseases. This work aimed to study, for the first time, those present in vaginal discharge and urine of patients with Trichomonas vaginalis infection to look for volatile biomarkers. The results showed that volatile compounds such as 2-methyl-1-propanol and cyclohexanone could serve as biomarkers in vaginal discharge samples, as well as 2-octen-1-ol and 3-nonanone in urine. Moreover, 3-hydroxy-2,4,4-trimethylpentyl 2-methylpropanoate found in vaginal discharge, highly correlated to positive patients, is also highly related to urines of patients with trichomoniasis. The biomarkers described in this study might be a promising diagnostic tool. KEY POINTS: • The incidence of Trichomonas vaginalis infection is increasing • Trichomonas vaginalis VOC study in vaginal discharge and urine was performed • The identification of volatile biomarkers could allow a new diagnostic method.

Evaluation of prognostic inflammatory and systemic inflammatory response indices in auxiliary diagnosis of bacteria-negative pulmonary tuberculosis: A diagnostic accuracy study

Although molecular biology has made great progress in recent years, the detection rate of mycobacterium tuberculosis (MTB) is still not ideal. This study aimed to evaluate the role of prognostic inflammatory index (PII) and systemic inflammatory response index (SIRI) in the auxiliary diagnosis of bacteria-negative pulmonary tuberculosis (TB). Sixty patients diagnosed with bacteria-negative pulmonary TB at the Affiliated Hospital of Qinghai University between October 2019 and September 2022 were randomly selected as the case group, and seventy patients with nontuberculous pulmonary infection in the same department of the same hospital during the same period were randomly selected as the control group. Baseline data and values of erythrocyte sedimentation rate (ESR), lymphocyte count (LY), neutrophil count (NE), monocyte count (MO), albumin (ALB), prealbumin (PA), C-reactive protein (CRP), fibrinogen (FIB), neutrophil-to-lymphocyte ratio (NLR), PII, and SIRI were compared between the 2 groups. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy of PII and SIRI in the diagnosis of bacteria-negative pulmonary TB. No significant differences were found between the 2 groups in terms of sex and age (P > .05); however significant differences were observed in relation to body mass index (BMI), ESR, LY, NE, MO, ALB, PA, CRP, FIB, NLR, PII, and SIRI (P < .05). ROC curve analysis showed that area under curve (AUC) value {0.84 [95% CI (0.77, 0.90)]} and specificity {82.86% [95% CI (72.0, 90.8)]} of PII were the highest, while the sensitivity {86.67 [95% CI (75.4, 94.1)]} of NLR + PII was the highest. Pairwise comparison of the 7 indicators of ROC curve was performed, and only the diagnostic efficiency of NLR and NLR + PII was statistically significant (Z = 2.36, P = .02 < .05). NLR, PII, SIRI, pairwise combinations, and NLR + PII + SIRI showed auxiliary diagnostic values for bacteria-negative pulmonary TB, among which PII had the highest diagnostic value and specificity, while NLR + PII had the highest sensitivity.

Data-driven design of a multiplexed, peptide-sensitized transistor to detect breath VOC markers of COVID-19

Exhaled human breath contains a rich mixture of volatile organic compounds (VOCs) whose concentration can vary in response to disease or other stressors. Using simulated odorant-binding proteins (OBPs) and machine learning methods, we designed a multiplex of short VOC- and carbon-binding peptide probes that detect a characteristic "VOC fingerprint". Specifically, we target VOCs associated with COVID-19 in a compact, molecular sensor array that directly transduces vapor composition into multi-channel electrical signals. Rapidly synthesizable, chimeric VOC- and solid-binding peptides were derived from selected OBPs using multi-sequence alignment with protein database structures. Selective peptide binding to targeted VOCs and sensor surfaces was validated using surface plasmon resonance spectroscopy and quartz crystal microbalance. VOC sensing was demonstrated by peptide-sensitized, exposed-channel carbon nanotube transistors. The data-to-device pipeline enables the development of novel devices for non-invasive monitoring, diagnostics of diseases, and environmental exposure assessment.

Breath Analysis of COVID-19 Patients in a Tertiary UK Hospital by Optical Spectrometry: The E-Nose CoVal Study

Throughout the SARS-CoV-2 pandemic, diagnostic technology played a crucial role in managing outbreaks on a national and global level. One diagnostic modality that has shown promise is breath analysis, due to its non-invasive nature and ability to give a rapid result. In this study, a portable FTIR (Fourier Transform Infra-Red) spectrometer was used to detect chemical components in the breath from Covid positive symptomatic and asymptomatic patients versus a control cohort of Covid negative patients. Eighty-five patients who had a nasopharyngeal polymerase chain reaction (PCR) test for the detection of SARS-CoV-2 within the last 5 days were recruited to the study (36 symptomatic PCR positive, 23 asymptomatic PCR positive and 26 asymptomatic PCR negative). Data analysis indicated significant difference between the groups, with SARS-CoV-2 present on PCR versus the negative PCR control group producing an area under the curve (AUC) of 0.87. Similar results were obtained comparing symptomatic versus control and asymptomatic versus control. The asymptomatic results were higher than the symptomatic (0.88 vs. 0.80 AUC). When analysing individual chemicals, we found ethanol, methanol and acetaldehyde were the most important, with higher concentrations in the COVID-19 group, with symptomatic patients being higher than asymptomatic patients. This study has shown that breath analysis can provide significant results that distinguish patients with or without COVID-19 disease/carriage.

Tetrakis(4-pyridylphenyl)ethylene-based Zinc Metal-Organic Framework with Aggregation-Induced Chemiluminescence Emission on a Paper Platform for Formaldehyde Detection in Breath

Volatile formaldehyde (FA) in exhaled breath (EB) is considered as a biomarker for lung cancer (LC). On-the-spot selective and sensitive detection of gaseous FA is rather important for LC screening and diagnosis. Herein, a tetrakis(4-pyridylphenyl)ethylene (Py-TPE)-based zinc metal-organic framework (MOF) with excellent aggregation-induced emission (AIE) property was utilized for absorption and selective detection of FA in EB. The porous Zn-Py-TPE served as a gaseous confinement cavity for the adsorption of FA in EB. Interestingly, Zn-Py-TPE was aggregated on paper, and then aggregation-induced chemiluminescence (CL) emission can be triggered by only adding bis(2,4,6-trichlorophenyl)oxalate (TCPO). Though without H₂O₂, the CL of Zn-Py-TPE-TCPO was enhanced greatly by FA. FA promoted the aggregation of Zn-Py-TPE on paper by forming halogen bonding between FA and Zn-Py-TPE, which contributed to the better selectivity. FA can also stimulate the production of more singlet oxygen (¹O₂) in the Zn-Py-TPE-TCPO CL system. Hence, FA could be detected via the proposed Zn-Py-TPE-TCPO system with a quantification linear range of 1.0-100.0 ppb and detection limit of 0.3 ppb. This portable, low-cost, and sensitive paper-based platform can achieve trace FA detection in EB and is expected to provide an on-the-spot screening platform for lung cancer.

Ability of animals to detect cancer odors

The olfactory capacity of animals has long been used by humans to help with various activities, e.g., hunting, detecting mines, locating people, and diagnosing diseases. Cancer is among the leading diseases causing death worldwide. Several recent studies have underscored the benefit of using scent to detect cancer, and this paper will review the studies using animals to detect tumor scents. A large variety of animals have been used for this purpose-dogs, rodents, insects, and nematodes-and have shown their capacity to detect cancer, with a success rate close to 90%. Here we discuss these studies, their methodologies, and the animal models used. Finally, we discuss the medical perspectives for cancer diagnosis using odors.

Remote Medical Scent Detection of Cancer and Infectious Diseases With Dogs and Rats: A Systematic Review

BACKGROUND

Remote medical scent detection of cancer and infectious diseases with dogs and rats has been an increasing field of research these last 20 years. If validated, the possibility of implementing such a technique in the clinic raises many hopes. This systematic review was performed to determine the evidence and performance of such methods and assess their potential relevance in the clinic.

METHODS

Pubmed and Web of Science databases were independently searched based on PRISMA standards between 01/01/2000 and 01/05/2021. We included studies aiming at detecting cancers and infectious diseases affecting humans with dogs or rats. We excluded studies using other animals, studies aiming to detect agricultural diseases, diseases affecting animals, and others such as diabetes and neurodegenerative diseases. Only original articles were included. Data about patients' selection, samples, animal characteristics, animal training, testing configurations, and performances were recorded.

RESULTS

A total of 62 studies were included. Sensitivity and specificity varied a lot among studies: While some publications report low sensitivities of 0.17 and specificities around 0.29, others achieve rates of 1 sensitivity and specificity. Only 6 studies were evaluated in a double-blind screening-like situation. In general, the risk of performance bias was high in most evaluated studies, and the quality of the evidence found was low.

CONCLUSIONS

Medical detection using animals' sense of smell lacks evidence and performances so far to be applied in the clinic. What odors the animals detect is not well understood. Further research should be conducted, focusing on patient selection, samples (choice of materials, standardization), and testing conditions. Interpolations of such results to free running detection (direct contact with humans) should be taken with extreme caution. Considering this synthesis, we discuss the challenges and highlight the excellent odor detection threshold exhibited by animals which represents a potential opportunity to develop an accessible and non-invasive method for disease detection.

Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose

Currently, antibiotics are often prescribed to children without reason due to the inability to quickly establish the presence of a bacterial etiology of the disease. One way to obtain additional diagnostic information quickly is to study the volatile metabolome of biosamples using arrays of sensors. The goal of this work was to assess the possibility of using an array of chemical sensors with various sensitive coatings to determine the presence of a bacterial infection in children by analyzing the equilibrium gas phase (EGP) of urine samples. The EGP of 90 urine samples from children with and without a bacterial infection (urinary tract infection, soft tissue infection) was studied on the "MAG-8" device with seven piezoelectric sensors in a hospital. General urine analysis with sediment microscopy was performed using a Uriscan Pro analyzer and using an Olympus CX31 microscope. After surgical removal of the source of inflammation, the microbiological studies of the biomaterial were performed to determine the presence and type of the pathogen. The most informative output data of an array of sensors have been established for diagnosing bacterial pathology. Regression models were built to predict the presence of a bacterial infection in children with an error of no more than 15%. An indicator of infection is proposed to predict the presence of a bacterial infection in children with a high sensitivity of 96%.

Volatile biomarkers for non-invasive detection of American foulbrood, a threat to honey bee pollination services

Honey bees provide essential environmental services, pollinating both agricultural and natural ecosystems that are crucial for human health. However, these pollination services are under threat by outbreaks of the bacterial honey bee disease American foulbrood (AFB). Caused by the bacterium, Paenibacillus larvae, AFB kills honey bee larvae, converting the biomass to a foul smelling, spore-laden mass. Due to the bacterium's tough endospores, which are easily spread and extremely persistent, AFB management requires the destruction of infected colonies in many countries. AFB detection remains a significant problem for beekeepers: diagnosis is often slow, relying on beekeepers visually identifying symptoms in the colony and molecular confirmation. Delayed detection can result in large outbreaks during high-density beekeeping pollination events, jeopardising livelihoods and food security. In an effort to improve diagnostics, we investigated volatile compounds associated with AFB-diseased brood in vitro and in beehive air. Using Solid Phase Microextraction and Gas Chromatography Mass-Spectrometry, we identified 40 compounds as volatile biomarkers for AFB infections, including 16 compounds previously unreported in honey bee studies. In the field, we detected half of the biomarkers in situ (in beehive air) and demonstrated their sensitivity and accuracy for diagnosing AFB. The most sensitive volatile biomarker, 2,5-dimethylpyrazine, was exclusively detected in AFB-disease larvae and hives, and was detectable in beehives with <10 AFB-symptomatic larvae. These, to our knowledge, previously undescribed biomarkers are prime candidates to be targeted by a portable sensor device for rapid and non-invasive diagnosis of AFB in beehives.

Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis

Currently available urinalysis methods are often applied for screening and monitoring of several pathologies. However, traditionally analyzed biomarkers in urinalysis still lack sensitivity and specificity to accurately diagnose some diseases. Several studies have proposed the use of electronic noses (eNoses) for the analysis of volatile organic compounds in urine samples that may, directly or indirectly, correlate with certain pathologies. Hence, the aim of this study was to perform a systematic review and meta-analysis of studies concerning the use of portable electronic noses for diagnosis or monitoring of pathologies through analysis of urine samples. A systematic review of the literature was held according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Twenty-four articles met the inclusion criteria and were included in the analysis. The results of the revised studies showed that there are various volatile organic compound profiles, identified through eNose analysis, that may be applied for diagnosis or monitoring of several diseases, such as diabetes, urinary tract infection, inflammatory bowel disease, and kidney disease. A meta-analysis was conducted taking into consideration the data of 10 of the initial 24 articles. The pooled sensitivity, specificity, and diagnostic odds ratio were 84% (95% CI, 0.72-0.92), 85% (95% CI, 0.75-0.91), and 24.17 (95% CI: 7.85-74.41), respectively. The area under the receiver operating characteristic curve was 0.897. These results suggest that eNose technology has adequate diagnostic accuracy for several pathologies and could be a promising screening tool for clinical settings. However, more studies are needed to reduce heterogeneity between results.

Detection and Treatment of Helicobacter pylori: Problems and Advances

Helicobacter pylori (H. pylori) infection is chronic and etiologically linked to gastric cancer (GC) derived from gastric epithelium. The potential mechanism is complex, covering chronic inflammation, epithelial senescence, NF-κB activation, the cytotoxin-associated gene A protein translocation, and related abnormal signaling pathways. In clinical practice, the test-and-treat strategy, endoscopy-based strategy, and (family-based) screen-and-treat strategy are recommended to detect H. pylori and prevent GC. It has been demonstrated that the decreasing annual incidence of GC is largely attributable to the management of H. pylori. This study reviews the current clinical practice of H. pylori on the detection and eradication, alternative treatment strategies, and related problems and advances, and hopes to contribute to the better clinical management of H. pylori.

Rapid detection of Staphylococcus aureus and Streptococcus pneumoniae by real-time analysis of volatile metabolites

Early detection of pathogenic bacteria is needed for rapid diagnostics allowing adequate and timely treatment of infections. In this study, we show that secondary electrospray ionization–high resolution mass spectrometry (SESI-HRMS) can be used as a diagnostic tool for rapid detection of bacterial infections as a supportive system for current state-of-the-art diagnostics. Volatile organic compounds (VOCs) produced by growing S. aureus or S. pneumoniae cultures on blood agar plates were detected within minutes and allowed for the distinction of these two bacteria on a species and even strain level within hours. Furthermore, we obtained a fingerprint of clinical patient samples within minutes of measurement and predominantly observed a separation of samples containing live bacteria compared to samples with no bacterial growth. Further development of this technique may reduce the time required for microbiological diagnosis and should help to improve patient’s tailored treatment.

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Real-time mass spectrometry shows potential as a tool for microbiological diagnosis

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Bacterial volatile metabolites from 1 × 10³ CFUs are detected within minutes

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S. aureus and S. pneumoniae can be distinguished on species and even strain level

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Complex clinical samples cluster according to presence or absence of viable bacteria

First-Principles Insight into a B4C3 Monolayer as a Promising Biosensor for Exhaled Breath Analysis

Nanomaterial-based room temperature gas sensors are used as a screening tool for diagnosing various diseases through breath analysis. The stable planar structure of boron carbide (B₄C₃) is utilized as a base material for adsorption of human breath exhaled VOCs, namely formaldehyde, methanol, acetone, toluene along, with interfering gases of carbon dioxide and water. The adsorption energy, charge density, density of states, energy band gap variation, recovery time, sensitivity, and work function of adsorbed molecules on pristine B₄C₃ are analyzed by density functional theory. The computed adsorption energies of VOC are in the range of - 0.176 to - 0.238 eV, and a larger interaction distance validate the physisorption behavior of these VOCs biomarkers on pristine boron carbide monolayer. Minute changes are determined from the electronic band structure of all adsorbed systems conserving the semiconducting nature of the B₄C₃ monolayer. The band gap variation upon adsorption of VOCs and interfering gases is examined between 0.05 and 0.52%. The 13.63 × 10^-9 s recovery time of methanol is slower among VOCs, and 0.556 × 10^-9 s of carbon dioxide (CO₂) is faster for desorption. The results reveal that boron carbide can be utilized as a biosensor at room temperature for the analysis of exhaled VOCs from human breath.

Fx-Net and PureNet: Convolutional Neural Network architecture for discrimination of Chronic Obstructive Pulmonary Disease from smokers and healthy subjects through electronic nose signals

As one of the most reliable and significant indicators, Chronic Obstructive Pulmonary Disease (COPD) becomes a robust predictor of lung cancer early detection, the world's leading cause of cancer death. One of the methods is to analyze the Volatile Organic Compounds (VOCs) in exhaled breath using electronic noses (E-noses), which have become emerging tools for analyzing breath because of their potential and promising technology for diagnosing. However, the signal processing of the E-Nose sensor becomes vital in exposing information about the subject condition, which most researchers strive to accomplish. We proposed a Convolutional Neural Network (CNN) architecture to classify COPD in smokers and non-smokers, healthy subjects, and smokers from E-Nose signals to contribute to this field. Two models were constructed following E-Nose signal processing state-of-the-arts. One was by combined feature extraction and classifier, and the second was by CNN, which directly processed the raw signal. In addition, various feature extraction and classifier (Machine Learning and CNN) used in prior research were investigated. Using 3K and 5K Fold cross-validation results demonstrated that our proposed models outperformed in Kernel Principal Component Analysis (KPCA) with Fx-ConvNet and Pure-ConvNet. They all reached maximum F1-Score with zero standard deviation values indicating a consistent result. Further experiments also showed that KPCA contributed to the increasing performance of some classifiers with average F1-Score 0.933 and 0.068 as standard deviation values.

Metabolites From Trypanosome-Infected Cattle as Sensitive Biomarkers for Animal Trypanosomosis

Trypanosomes are important global livestock and human pathogens of public health importance. Elucidating the chemical mechanisms of trypanosome-relevant host interactions can enhance the design and development of a novel, next-generation trypanosomosis diagnostics. However, it is unknown how trypanosome infection affects livestock volatile odors. Here, we show that Trypanosoma congolense and Trypanosoma vivax infections induced dihydro-β- ionone and junenol, while abundance of dihydro-α-ionone, phenolics, p-cresol, and 3-propylphenol significantly elevated in cow urine. These biomarkers of trypanosome infection are conserved in cow breath and the urine metabolites of naturally infected cows, regardless of population, diet, or environment differences. Furthermore, treating trypanosome-infected cows reduced the levels of these indicators back to the pre-infection levels. Finally, we demonstrated that the potential of some specific biomarkers of phenolic origin may be used to detect active trypanosome infections, including low-level infections that are not detectable by microscopy. The sensitivity and specificity of biomarkers detection are suited for rapid, robust, and non-invasive trypanosomosis diagnosis under field conditions.

Diagnosing Tuberculosis: What Do New Technologies Allow Us to (Not) Do?

New tuberculosis (TB) diagnostics are at a crossroads: their development, evaluation, and implementation is severely damaged by resource diversion due to COVID-19. Yet several technologies, especially those with potential for non-invasive non-sputum-based testing, hold promise for efficiently triaging and rapidly confirming TB near point-of-care. Such tests are, however, progressing through the pipeline slowly and will take years to reach patients and health workers. Compellingly, such tests will create new opportunities for difficult-to-diagnose populations, including primary care attendees (all-comers in high burden settings irrespective of reason for presentation) and community members (with early stage disease or risk factors like HIV), many of whom cannot easily produce sputum. Critically, all upcoming technologies have limitations that implementers and health workers need to be cognizant of to ensure optimal deployment without undermining confidence in a technology that still offers improvements over the status quo. In this state-of-the-art review, we critically appraise such technologies for active pulmonary TB diagnosis. We highlight strengths, limitations, outstanding research questions, and how current and future tests could be used in the presence of these limitations and uncertainties. Among triage tests, CRP (for which commercial near point-of-care devices exist) and computer-aided detection software with digital chest X-ray hold promise, together with late-stage blood-based assays that detect host and/or microbial biomarkers; however, aside from a handful of prototypes, the latter category has a shortage of promising late-stage alternatives. Furthermore, positive results from new triage tests may have utility in people without TB; however, their utility for informing diagnostic pathways for other diseases is under-researched (most sick people tested for TB do not have TB). For confirmatory tests, few true point-of-care options will be available soon; however, combining novel approaches like tongue swabs with established tests like Ultra have short-term promise but first require optimizations to specimen collection and processing procedures. Concerningly, no technologies yet have compelling evidence of meeting the World Health Organization optimal target product profile performance criteria, especially for important operational criteria crucial for field deployment. This is alarming as the target product profile criteria are themselves almost a decade old and require urgent revision, especially to cater for technologies made prominent by the COVID-19 diagnostic response (e.g., at-home testing and connectivity solutions). Throughout the review, we underscore the importance of how target populations and settings affect test performance and how the criteria by which these tests should be judged vary by use case, including in active case finding. Lastly, we advocate for health workers and researchers to themselves be vocal proponents of the uptake of both new tests and those − already available tests that remain suboptimally utilized.

Volatile Organic Compounds Analysis as a Potential Novel Screening Tool for Breast Cancer: A Systematic Review

Introduction

An early diagnosis is crucial in reducing mortality among people who have breast cancer (BC). There is a shortfall of characteristic early clinical symptoms in BC patients, highlighting the importance of investigating new methods for its early detection. A promising novel approach is the analysis of volatile organic compounds (VOCs) produced and emitted through the metabolism of cancer cells.

Methods

The purpose of this systematic review is to outline the published research regarding BC-associated VOCs. For this, headspace analysis of VOCs was explored in patient-derived body fluids, animal model-derived fluids, and BC cell lines to identify BC-specific VOCs. A systematic search in PubMed and Web of Science databases was conducted according to the PRISMA guidelines.

Results

Thirty-two studies met the criteria for inclusion in this review. Results highlight that VOC analysis can be promising as a potential novel screening tool. However, results of in vivo, in vitro and case-control studies have delivered inconsistent results leading to a lack of inter-matrix consensus between different VOC sampling methods.

Discussion

Discrepant VOC results among BC studies have been obtained, highly due to methodological discrepancies. Therefore, methodological issues leading to disparities have been reviewed and recommendations have been made on the standardisation of VOC collection and analysis methods for BC screening, thereby improving future VOC clinical validation studies.

Challenges in Metabolomics-Based Tests, Biomarkers Revealed by Metabolomic Analysis, and the Promise of the Application of Metabolomics in Precision Medicine

Metabolomics helps identify metabolites to characterize/refine perturbations of biological pathways in living organisms. Pre-analytical, analytical, and post-analytical limitations that have hampered a wide implementation of metabolomics have been addressed. Several potential biomarkers originating from current targeted metabolomics-based approaches have been discovered. Precision medicine argues for algorithms to classify individuals based on susceptibility to disease, and/or by response to specific treatments. It also argues for a prevention-based health system. Because of its ability to explore gene-environment interactions, metabolomics is expected to be critical to personalize diagnosis and treatment. Stringent guidelines have been applied from the very beginning to design studies to acquire the information currently employed in precision medicine and precision prevention approaches. Large, prospective, expensive and time-consuming studies are now mandatory to validate old, and discover new, metabolomics-based biomarkers with high chances of translation into precision medicine. Metabolites from studies on saliva, sweat, breath, semen, feces, amniotic, cerebrospinal, and broncho-alveolar fluid are predicted to be needed to refine information from plasma and serum metabolome. In addition, a multi-omics data analysis system is predicted to be needed for omics-based precision medicine approaches. Omics-based approaches for the progress of precision medicine and prevention are expected to raise ethical issues.

Green Phosphorene as a Promising Biosensor for Detection of Furan and p-Xylene as Biomarkers of Disease: A DFT Study

In this work, Green Phosphorene (GP) monolayers are studied as an electronic sensing element for detecting prostate cancer biomarkers from human urine. The adsorption of furan, C₈H₁₀ (p-xylene), and H₂O on pristine GP and S- and Si-doped GP are investigated using the density functional theory (DFT) calculation. Furan and C₈H₁₀ molecules have been considered as important biomarkers of prostate cancer patients. First-principles DFT calculations are applied, and the results divulged that pristine GP could be a promising candidate for furan and C₈H₁₀ detection. It is manifested that furan and C₈H₁₀ are physisorbed on the S-, and Si-doped GP with small adsorption energy and negligible charge transfer. However, the calculations disclose that furan and C₈H₁₀ are chemically adsorbed on the pristine GP with adsorption energy of −0.73, and −1.46 eV, respectively. Moreover, we observe that a large charge is transferred from furan to the pristine GP with amount of −0.106 e. Additionally, pristine GP shows short recovery time of 1.81 s at room temperature under the visible light, which make it a reusable sensor device. Overall, our findings propose that the pristine GP sensor is a remarkable candidate for sensing of furan and other biomarkers of prostate cancer in the urine of patients.

Bees can be trained to identify SARS-CoV-2 infected samples

The COVID-19 pandemic has illustrated the need for the development of fast and reliable testing methods for novel, zoonotic, viral diseases in both humans and animals. Pathologies lead to detectable changes in the volatile organic compound (VOC) profile of animals, which can be monitored, thus allowing the development of a rapid VOC-based test. In the current study, we successfully trained honeybees (Apis mellifera) to identify SARS-CoV-2 infected minks (Neovison vison) thanks to Pavlovian conditioning protocols. The bees can be quickly conditioned to respond specifically to infected mink's odours and could therefore be part of a wider SARS-CoV-2 diagnostic system. We tested two different training protocols to evaluate their performance in terms of learning rate, accuracy and memory retention. We designed a non-invasive rapid test in which multiple bees are tested in parallel on the same samples. This provided reliable results regarding a subject's health status. Using the data from the training experiments, we simulated a diagnostic evaluation trial to predict the potential efficacy of our diagnostic test, which yielded a diagnostic sensitivity of 92% and specificity of 86%. We suggest that a honeybee-based diagnostics can offer a reliable and rapid test that provides a readily available, low-input addition to the currently available testing methods. A honeybee-based diagnostic test might be particularly relevant for remote and developing communities that lack the resources and infrastructure required for mainstream testing methods.

Summary: Honeybees can be quickly trained to identify SARS-CoV2 infected samples. SARS-CoV2 positive sample detection by bees reached a diagnostic sensitivity of 92% and a specificity of 86%. Honeybee-based diagnostics can offer a reliable and rapid test that provides a readily available, low-input addition to the currently available testing methods.