Breath-print analysis by e-nose for classifying and monitoring chronic liver disease: a proof-of-concept study

Clinical applications of volatilomic assays

The study of metabolomics is revealing immense potential for diagnosis, therapy monitoring, and understanding of pathogenesis processes. Volatilomics is a subcategory of metabolomics interested in the detection of molecules that are small enough to be released in the gas phase. Volatile compounds produced by cellular processes are released into the blood and lymph, and can reach the external environment through different pathways, such as the blood-air interface in the lung that are detected in breath, or the blood-water interface in the kidney that leads to volatile compounds detected in urine. Besides breath and urine, additional sources of volatile compounds such as saliva, blood, feces, and skin are available. Volatilomics traces its roots back over fifty years to the pioneering investigations in the 1970s. Despite extensive research, the field remains in its infancy, hindered by a lack of standardization despite ample experimental evidence. The proliferation of analytical instrumentations, sample preparations and methods of volatilome sampling still make it difficult to compare results from different studies and to establish a common standard approach to volatilomics. This review aims to provide an overview of volatilomics' diagnostic potential, focusing on two key technical aspects: sampling and analysis. Sampling poses a challenge due to the susceptibility of human samples to contamination and confounding factors from various sources like the environment and lifestyle. The discussion then delves into targeted and untargeted approaches in volatilomics. Some case studies are presented to exemplify the results obtained so far. Finally, the review concludes with a discussion on the necessary steps to fully integrate volatilomics into clinical practice.

Prospect and Challenges of Volatile Organic Compound Breath Testing in Non-Cancer Gastrointestinal Disorders

Breath analysis, despite being an overlooked biomatrix, has a rich history in disease diagnosis. However, volatile organic compounds (VOCs) have yet to establish themselves as clinically validated biomarkers for specific diseases. As focusing solely on late-stage or malignant disease biomarkers may have limited relevance in clinical practice, the objective of this review is to explore the potential of VOC breath tests for the diagnosis of non-cancer diseases: (1) Precancerous conditions like gastro-esophageal reflux disease (GERD) and Barrett's esophagus (BE), where breath tests can complement endoscopic screening; (2) endoluminal diseases associated with autoinflammation and dysbiosis, such as inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), and coeliac disease, which currently rely on biopsy and symptom-based diagnosis; (3) chronic liver diseases like cirrhosis, hepatic encephalopathy, and non-alcoholic fatty liver disease, which lack non-invasive diagnostic tools for disease progression monitoring and prognostic assessment. A literature search was conducted through EMBASE, MEDLINE, and Cochrane databases, leading to an overview of 24 studies. The characteristics of these studies, including analytical platforms, disorder type and stage, group size, and performance evaluation parameters for diagnostic tests are discussed. Furthermore, how VOCs can be utilized as non-invasive diagnostic tools to complement existing gold standards is explored. By refining study designs, sampling procedures, and comparing VOCs in urine and blood, we can gain a deeper understanding of the metabolic pathways underlying VOCs. This will establish breath analysis as an effective non-invasive method for differential diagnosis and disease monitoring.

Breath biomarkers in Non-Carcinogenic diseases

The analysis of volatile organic compounds (VOCs) from human matrices like breath, perspiration, and urine has received increasing attention from academic and medical researchers worldwide. These biological-borne VOCs molecules have characteristics that can be directly related to physiologic and pathophysiologic metabolic processes. In this work, gathers a total of 292 analytes that have been identified as potential biomarkers for the diagnosis of various non-carcinogenic diseases. Herein we review the advances in VOCs with a focus on breath biomarkers and their potential role as minimally invasive tools to improve diagnosis prognosis and therapeutic monitoring.

Juice Quality Evaluation with Multisensor Systems-A Review

E-nose and e-tongue are advanced technologies that allow for the fast and precise analysis of smells and flavours using special sensors. Both technologies are widely used, especially in the food industry, where they are implemented, e.g., for identifying ingredients and product quality, detecting contamination, and assessing their stability and shelf life. Therefore, the aim of this article is to provide a comprehensive review of the application of e-nose and e-tongue in various industries, focusing in particular on the use of these technologies in the fruit and vegetable juice industry. For this purpose, an analysis of research carried out worldwide over the last five years, concerning the possibility of using the considered multisensory systems to test the quality and taste and aroma profiles of juices is included. In addition, the review contains a brief characterization of these innovative devices through information such as their origin, mode of operation, types, advantages and disadvantages, challenges and perspectives, as well as the possibility of their applications in other industries besides the juice industry.

Breath VOC analysis and machine learning approaches for disease screening: a review

Early disease detection is often correlated with a reduction in mortality rate and improved prognosis. Currently, techniques like biopsy and imaging that are used to screen chronic diseases are invasive, costly or inaccessible to a large population. Thus, a non-invasive disease screening technology is the need of the hour. Existing non-invasive methods like gas chromatography-mass spectrometry, selected-ion flow-tube mass spectrometry, and proton transfer reaction-mass-spectrometry are expensive. These techniques necessitate experienced operators, making them unsuitable for a large population. Various non-invasive sources are available for disease detection, of which exhaled breath is preferred as it contains different volatile organic compounds (VOCs) that reflect the biochemical reactions in the human body. Disease screening by exhaled breath VOC analysis can revolutionize the healthcare industry. This review focuses on exhaled breath VOC biomarkers for screening various diseases with a particular emphasis on liver diseases and head and neck cancer as examples of diseases related to metabolic disorders and diseases unrelated to metabolic disorders, respectively. Single sensor and sensor array-based (Electronic Nose) approaches for exhaled breath VOC detection are briefly described, along with the machine learning techniques used for pattern recognition.

Artificial olfactory sensor technology that mimics the olfactory mechanism: a comprehensive review

Artificial olfactory sensors that recognize patterns transmitted by olfactory receptors are emerging as a technology for monitoring volatile organic compounds. Advances in statistical processing methods and data processing technology have made it possible to classify patterns in sensor arrays. Moreover, biomimetic olfactory recognition sensors in the form of pattern recognition have been developed. Deep learning and artificial intelligence technologies have enabled the classification of pattern data from more sensor arrays, and improved artificial olfactory sensor technology is being developed with the introduction of artificial neural networks. An example of an artificial olfactory sensor is the electronic nose. It is an array of various types of sensors, such as metal oxides, electrochemical sensors, surface acoustic waves, quartz crystal microbalances, organic dyes, colorimetric sensors, conductive polymers, and mass spectrometers. It can be tailored depending on the operating environment and the performance requirements of the artificial olfactory sensor. This review compiles artificial olfactory sensor technology based on olfactory mechanisms. We introduce the mechanisms of artificial olfactory sensors and examples used in food quality and stability assessment, environmental monitoring, and diagnostics. Although current artificial olfactory sensor technology has several limitations and there is limited commercialization owing to reliability and standardization issues, there is considerable potential for developing this technology. Artificial olfactory sensors are expected to be widely used in advanced pattern recognition and learning technologies, along with advanced sensor technology in the future.

Sensors for Volatile Organic Compounds

This paper provides an overview of recent developments in the field of volatile organic compound (VOC) sensors, which are finding uses in healthcare, safety, environmental monitoring, food and agriculture, oil industry, and other fields. It starts by briefly explaining the basics of VOC sensing and reviewing the currently available and quickly progressing VOC sensing approaches. It then discusses the main trends in materials' design with special attention to nanostructuring and nanohybridization. Emerging sensing materials and strategies are highlighted and their involvement in the different types of sensing technologies is discussed, including optical, electrical, and gravimetric sensors. The review also provides detailed discussions about the main limitations of the field and offers potential solutions. The status of the field and suggestions of promising directions for future development are summarized.

Detection of Liver Dysfunction Using a Wearable Electronic Nose System Based on Semiconductor Metal Oxide Sensors

The purpose of this exploratory study was to determine whether liver dysfunction can be generally classified using a wearable electronic nose based on semiconductor metal oxide (MOx) gas sensors, and whether the extent of this dysfunction can be quantified. MOx gas sensors are attractive because of their simplicity, high sensitivity, low cost, and stability. A total of 30 participants were enrolled, 10 of them being healthy controls, 10 with compensated cirrhosis, and 10 with decompensated cirrhosis. We used three sensor modules with a total of nine different MOx layers to detect reducible, easily oxidizable, and highly oxidizable gases. The complex data analysis in the time and non-linear dynamics domains is based on the extraction of 10 features from the sensor time series of the extracted breathing gas measurement cycles. The sensitivity, specificity, and accuracy for distinguishing compensated and decompensated cirrhosis patients from healthy controls was 1.00. Patients with compensated and decompensated cirrhosis could be separated with a sensitivity of 0.90 (correctly classified decompensated cirrhosis), a specificity of 1.00 (correctly classified compensated cirrhosis), and an accuracy of 0.95. Our wearable, non-invasive system provides a promising tool to detect liver dysfunctions on a functional basis. Therefore, it could provide valuable support in preoperative examinations or for initial diagnosis by the general practitioner, as it provides non-invasive, rapid, and cost-effective analysis results.

Chemometric analysis of the global pattern of volatile organic compounds in the exhaled breath of patients with COVID-19, post-COVID and healthy subjects. Proof of concept for post-COVID assessment

The objective of this research was to evaluate the application of an electronic nose and chemometric analysis to discriminate volatile organic compounds between patients with COVID-19, post-COVID syndrome and controls in exhaled breath samples. A cross-sectional study was performed on 102 exhaled breath samples, 42 with COVID-19, 30 with the post-COVID syndrome and 30 control subjects. Breath-print analysis was performed by the Cyranose 320 electronic nose with 32 sensors. Group data were evaluated by Principal Component Analysis (PCA), Canonical Discriminant Analysis (CDA), and Support Vector Machine (SVM), and the test's diagnostic power was evaluated through a Receiver Operaring Characteristic curve(ROC curve). The results of the chemometric analysis indicate in the PCA a 97.6% (PC₁ = 95.9%, PC₂ = 1.0%, PC₃ = 0.7%) of explanation of the variability between the groups by means of 3 PCs, the CDA presents a 100% of correct classification of the study groups, SVM a 99.4% of correct classification, finally the PLS-DA indicates an observable separation between the groups and the 12 sensors that were related. The sensitivity, specificity of post-COVID vs. controls value reached 97.6% (87.4%–99.9%) and 100% (88.4%–100%) respectively, according to the ROC curve. As a perspective, we consider that this technology, due to its simplicity, low cost and portability, can support strategies for the identification and follow-up of post-COVID patients. The proposed classification model provides the basis for evaluating post-COVID patients; therefore, further studies are required to enable the implementation of this technology to support clinical management and mitigation of effects.

Machine learning analysis of volatolomic profiles in breath can identify non-invasive biomarkers of liver disease: A pilot study

Disease-related effects on hepatic metabolism can alter the composition of chemicals in the circulation and subsequently in breath. The presence of disease related alterations in exhaled volatile organic compounds could therefore provide a basis for non-invasive biomarkers of hepatic disease. This study examined the feasibility of using global volatolomic profiles from breath analysis in combination with supervised machine learning to develop signature pattern-based biomarkers for cirrhosis. Breath samples were analyzed using thermal desorption-gas chromatography-field asymmetric ion mobility spectroscopy to generate breathomic profiles. A standardized collection protocol and analysis pipeline was used to collect samples from 35 persons with cirrhosis, 4 with non-cirrhotic portal hypertension, and 11 healthy participants. Molecular features of interest were identified to determine their ability to classify cirrhosis or portal hypertension. A molecular feature score was derived that increased with the stage of cirrhosis and had an AUC of 0.78 for detection. Chromatographic breath profiles were utilized to generate machine learning-based classifiers. Algorithmic models could discriminate presence or stage of cirrhosis with a sensitivity of 88–92% and specificity of 75%. These results demonstrate the feasibility of volatolomic profiling to classify clinical phenotypes using global breath output. These studies will pave the way for the development of non-invasive biomarkers of liver disease based on volatolomic signatures found in breath.

Accuracy of the Electronic Nose Breath Tests in Clinical Application: A Systematic Review and Meta-Analysis

(1) Background: An electronic nose applies a sensor array to detect volatile biomarkers in exhaled breath to diagnose diseases. The overall diagnostic accuracy remains unknown. The objective of this review was to provide an estimate of the diagnostic accuracy of sensor-based breath tests for the diagnosis of diseases. (2) Methods: We searched the PubMed and Web of Science databases for studies published between 1 January 2010 and 14 October 2021. The search was limited to human studies published in the English language. Clinical trials were not included in this review. (3) Results: Of the 2418 records identified, 44 publications were eligible, and 5728 patients were included in the final analyses. The pooled sensitivity was 90.0% (95% CI, 86.3-92.8%, I² = 47.7%), the specificity was 88.4% (95% CI, 87.1-89.5%, I² = 81.4%), and the pooled area under the curve was 0.93 (95% CI 0.91-0.95). (4) Conclusion: The findings of our review suggest that a standardized report of diagnostic accuracy and a report of the accuracy in a test set are needed. Sensor array systems of electronic noses have the potential for noninvasiveness at the point-of-care in hospitals. Nevertheless, the procedure for reporting the accuracy of a diagnostic test must be standardized.

Comparative analysis of volatile organic compounds of breath and urine for distinguishing patients with liver cirrhosis from healthy controls by using electronic nose and voltammetric electronic tongue

Advanced stage detection of liver cirrhosis (LCi) would lead to high mortality rates in patients. Therefore, accurate and non-invasive tools for its early detection are highly needed using human emanations that may reflect this disease. Human breath, along with urine and blood, has long been one of the three main biological media for assessing human health and environmental exposure. The primary objective of this study was to explore the potential of using volatile organic compounds (VOCs) assay of exhaled breath and urine samples for the diagnosis of patients with LCi and healthy controls (HC). For this purpose, we used a hybrid electronic nose (E-nose) combining two sensor families, consisting of an array of five commercial chemical gas sensors and six interdigitated chemical gas sensors based on pristine or metal-doped WO₃ nanowires for sensing volatile gases in exhaled breath. A voltammetric electronic tongue (VE-tongue), composed of five working electrodes, was dedicated to the analysis of urinary VOCs using cyclic voltammetry as a measurement technique. 54 patients were recruited for this study, comprising 22 patients with LCi, and 32 HC. The two-sensing systems coupled with pattern recognition methods, namely Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), were trained to classify data clusters associated with the health status of the two groups. The diagnostic performances of the E-nose and VE-tongue systems were studied by using the receiver operating characteristic (ROC) method. The use of the E-nose or the VE-tongue separately, trained with these appropriate classifiers, showed a slight overlap indicating no clear discrimination between LCi patients and HC. To improve the performance of both electronic sensing devices, an emerging strategy, namely a multi-sensor data fusion technique, was proposed as a second aim to overcome this shortcoming. The data fusion approach of the two systems, at a medium level of abstraction, has demonstrated the ability to assess human health and disease status using non-invasive screening tools based on exhaled breath and urinary VOC analysis. This suggests that exhaled breath as well as urinary VOCs are specific to a disease state and could potentially be used as diagnostic methods.

Liver Impairment-The Potential Application of Volatile Organic Compounds in Hepatology

Liver diseases are currently diagnosed through liver biopsy. Its invasiveness, costs, and relatively low diagnostic accuracy require new techniques to be sought. Analysis of volatile organic compounds (VOCs) in human bio-matrices has received a lot of attention. It is known that a musty odour characterises liver impairment, resulting in the elucidation of volatile chemicals in the breath and other body fluids such as urine and stool, which may serve as biomarkers of a disease. Aims: This study aims to review all the studies found in the literature regarding VOCs in liver diseases, and to summarise all the identified compounds that could be used as diagnostic or prognostic biomarkers. The literature search was conducted on ScienceDirect and PubMed, and each eligible publication was qualitatively assessed by two independent evaluators using the SANRA critical appraisal tool. Results: In the search, 58 publications were found, and 28 were kept for inclusion: 23 were about VOCs in the breath, one in the bile, three in urine, and one in faeces. Each publication was graded from zero to ten. A graphical summary of the metabolic pathways showcasing the known liver disease-related VOCs and suggestions on how VOC analysis on liver impairment could be applied in clinical practice are given.

Gut Microbiota and Related Electronic Multisensorial System Changes in Subjects With Symptomatic Uncomplicated Diverticular Disease Undergoing Rifaximin Therapy

Background: Intestinal dysbiosis might play a pathogenetic role in subjects with symptomatic uncomplicated diverticular disease (SUDD), but the effect of rifaximin therapy has been scantly explored with regard to gut microbiota variations in patients with SUDD. Aims: To verify to which extent rifaximin treatment affects the gut microbiota and whether an electronic multisensorial assessment of stools and breath has the potential for detecting these changes. Methods: Breath and stool samples were collected from consecutive patients with SUDD before and after a 7 days' therapy with rifaximin. Stool microbiota was assessed, and the electronic multisensorial assessment was carried out by means of the BIONOTE electronic (e-)tongue in stools and (e-)nose in breath. Results: Forty-three subjects (female 60%, median age 66 years) were included, and 20 (47%) reported clinical improvement after rifaximin therapy. Alpha and beta diversity of stool microbiota did not significantly change after treatment, while a significant variation of selected taxa was shown (i.e., Citrobacter, Coprococcus, Anaerotruncus, Blautia, Eggerthella lenta, Dehalobacterium, SMB53, and Haemophilus parainfluenzae). Overall, the electronic multisensorial system suboptimally mirrored microbiota changes, but it was able to efficiently predict patients' clinical improvement after rifaximin with accuracies ranging from 0.81 to 0.98. Conclusions: In patients with SUDD, rifaximin administration is associated with significant variation of selected taxa. While inaccurate in predicting gut microbiota change, an electronic multisensorial system, made up of e-tongue and e-nose, was able to predict clinical improvement, thus potentially qualifying as an easy and cheap tool to forecast subjects taking most likely benefit from rifaximin therapy.

Characterization of inflammatory profile by breath analysis in chronic coronary syndromes

AIMS

Exhaled breath contains thousands of volatile organic compounds (VOCs) produced during various metabolic processes both in health and disease.Analysis of breath with electronic nose BIONOTE-V allows modifications of exhaled VOCs to be studied, which are clinically recognized to be a marker for several disorders, including heart failure. New noninvasive tests based on VOCs analysis might be a useful tool for early detection of chronic coronary syndromes (CCS).

METHODS

Exhaled air was collected and measured in individuals with an indication to perform invasive coronary angiography (ICA). All patients' samples were obtained before ICA.

RESULTS

Analysis with BIONOTE-V was performed in a total cohort of 42 patients consecutively enrolled, of whom 19 did not require myocardial revascularization and 23 with indication for myocardial revascularization. BIONOTE-V was able to correctly identify 18 out of 23 patients affected by severe coronary artery disease (sensitivity = 78.3% and specificity = 68.4%). Our predicted model had a tight correlation with SYNTAX score (error of the BIONOTE-V = 15).

CONCLUSION

CCS patients have a distinctive fingerprint of exhaled breath, and analysis by BIONOTE-V has the potential for identifying these patients. Moreover, it seems that this technique can correctly identify patients according to anatomical disease severity at ICA. If the preliminary data of this proof of concept study will be confirmed, this rapid and noninvasive diagnostic tool able to identify CCS might have an impact in routine clinical practice.

Thiol-Amine Functionalized Decorated Carbon Nanotubes for Biomarker Gases Detection

Thousands of gas molecules are expelled in exhaled breath, and some of them can reveal diseases and metabolomic disorders. For that reason, the development of fast, inexpensive, and reliable sensing devices has been attracting growing interest. Here, we present the development of different chemoresistors based on multi-walled carbon nanotubes (MWCNTs) decorated with platinum (MWCNT/Pt) and palladium (MWCNT/Pt) nanoparticles and also functionalized with a self-assembled monolayer (SAM) of 11-amino-1-undecanethiol (Thiol-amine). The nanocomposites developed are a proof-of-concept to detect some biomarker molecules. Specifically, the capability to identify and measure different concentrations of volatile organic compounds (VOCs), either aromatic (toluene and benzene) and non-aromatic (ethanol and methanol) was assessed. As a result, this paper reports the significant differences in sensing performance achieved according to the metal nanoparticle used, and the high sensitivity obtained when SAMs are grown on the sensitive film, acting as a receptor for biomarker vapours.

Voltammetric analysis for distinguishing portal hypertension-related from malignancy-related ascites: A proof of concept study

Background

Serum-ascites albumin gradient (SAAG) remains the most sensitive and specific marker for the differentiation of ascites due to portal hypertension from ascites due to other causes. SAAG has some limitations and may fail in selected conditions. Voltammetric analysis (VA) has been used for the detection of electroactive species of biological significance and has proven effective for detection infections in biological fluids.

Aims

In this study, we compared the accuracy of voltammetric analysis (VA) with that of SAAG to differentiate ascites due to portal hypertension from that having a different origin.

Methods

80 ascites samples were obtained from patients undergoing paracentesis at the Campus Bio-Medico Hospital of Rome. VA was performed using the BIONOTE device. The ability of VA to discriminate ascitic fluid etiology and biochemical parameters was evaluated using Partial Least Square Discriminant Analysis (PLS-DA), with ten-fold cross-validations.

Results

Mean age was 68.6 years (SD 12.5), 58% were male. Ascites was secondary to only portal hypertension in 72.5% of cases (58 subjects) and it was secondary to a baseline neoplastic disease in 27.5% of cases (22 subjects). Compared to SAAG≥1.1, e-tongue predicted ascites from portal hypertension with a better accuracy (92.5% Vs 87.5%); sensitivity (98.3% Vs 94.8%); specificity (77.3% Vs 68.2%); predictive values (PPV 91.9% Vs 88.7% and NPV 94.4% Vs 83.3%). VA correctly classified ascites etiology in 57/58 (98.2%) of cases with portal hypertension and in 17/22 (77.2%) of cases with malignancy. Instead, VA showed poor predictive capacities towards total white blood count and polymorphonuclear cell count.

Conclusions

According to this proof of concept study, VA qualifies as a promising low-cost and easy method to discriminate between ascites secondary to portal hypertension and ascites due to malignancy.

Exhaled breath analysis in hepatology: State-of-the-art and perspectives

Liver disease is characterized by breath exhalation of peculiar volatile organic compounds (VOCs). Thanks to the availability of sensitive technologies for breath analysis, this empiric approach has recently gained increasing attention in the context of hepatology, following the good results obtained in other fields of medicine. After the first studies that led to the identification of selected VOCs for pathophysiological purposes, subsequent research has progressively turned towards the comprehensive assessment of exhaled breath for potential clinical application. Specific VOC patterns were found to discriminate subjects with liver cirrhosis, to rate disease severity, and, eventually, to forecast adverse clinical outcomes even beyond existing scores. Preliminary results suggest that breath analysis could be useful also for detecting and staging hepatic encephalopathy and for predicting steatohepatitis in patients with nonalcoholic fatty liver disease. However, clinical translation is still hampered by a number of methodological limitations, including the lack of standardization and the consequent poor comparability between studies and the absence of external validation of obtained results. Given the low-cost and easy execution at bedside of the new technologies (e-nose), larger and well-structured studies are expected in order to provide the adequate level of evidence to support VOC analysis in clinical practice.

Main and side stream effects of electronic cigarettes

Over the last decade there has been a significant boost towards the use of electronic cigarettes (e-cigarettes), especially among youth. Different concentrations of propylene glycol (PG) or vegetable glycerin (VG), flavors and nicotine are mixed in plastic cartridges and commercially offered or privately produced by the vapers. During vaping, a mixture of air and vapors is inhaled to the lungs. Since the ingredients of the e-cigarettes are not burned but vaporized (heated), fewer chemicals are emitted. The levels of potentially toxic compounds (e.g. volatile organic compounds (VOCs), particulate matter (PM), metals, radicals, nitrosamines, etc.) emitted from vaping appear to be lower compared to that of tobacco smoking (from combustible cigarettes). Nevertheless, measurable toxic elements and VOCs are still released (e.g. acetaldehyde, formaldehyde, acrolein, benzene, etc.) along with other volatiles associated with e-liquid flavoring and device variability with PG and VG. The wide range of available flavors at various purities along with the heating temperature are important parameters affecting the evolution of VOCs and aerosols. There is lack of standardized short- and long-term epidemiological medical data (chronic exposure) on e-cigarettes effects to users, non-users and the human micro-environment (second- or third-hand exposure). Therefore, the potential health, safety and environmental effects of vaping are reviewed, examined and discussed.

Noninvasive biomarkers in NAFLD and NASH - current progress and future promise

Nonalcoholic fatty liver disease (NAFLD) affects 25% of the global adult population and is the most common chronic liver disease worldwide. Nonalcoholic steatohepatitis (NASH) is the active form of NAFLD, with hepatic necroinflammation and faster fibrosis progression. With an increasing number of patients developing NASH-related end-stage liver disease and pharmacological treatments on the horizon, there is a pressing need to develop NAFLD and NASH biomarkers for prognostication, selection of patients for treatment and monitoring. This requirement is particularly true as liver biopsy utility is limited by its invasive nature, poor patient acceptability and sampling variability. This article reviews current and potential biomarkers for different features of NAFLD, namely, steatosis, necroinflammation and fibrosis. For each biomarker, we evaluate its accuracy, reproducibility, responsiveness, feasibility and limitations. We cover biochemical, imaging and genetic biomarkers and discuss biomarker discovery in the omics era.

Autofluorescence-based optical biopsy: An effective diagnostic tool in hepatology

Autofluorescence emission of liver tissue depends on the presence of endogenous biomolecules able to fluoresce under suitable light excitation. Overall autofluorescence emission contains much information of diagnostic value because it is the sum of individual autofluorescence contributions from fluorophores involved in metabolism, for example, NAD(P)H, flavins, lipofuscins, retinoids, porphyrins, bilirubin and lipids, or in structural architecture, for example, fibrous proteins, in close relationship with normal, altered or diseased conditions of the liver. Since the 1950s, hepatocytes and liver have been historical models to study NAD(P)H and flavins as in situ, real-time autofluorescence biomarkers of energy metabolism and redox state. Later investigations designed to monitor organ responses to ischaemia/reperfusion were able to predict the risk of dysfunction in surgery and transplantation or support the development of procedures to ameliorate the liver outcome. Subsequently, fluorescent fatty acids, lipofuscin-like lipopigments and collagen were characterized as optical biomarkers of liver steatosis, oxidative stress damage, fibrosis and disease progression. Currently, serum AF is being investigated to improve non-invasive optical diagnosis of liver disease. Validation of endogenous fluorophores and in situ discrimination of cancerous from non-cancerous tissue belong to the few studies on liver in human subjects. These reports along with other optical techniques and the huge work performed on animal models suggest many optically based applications in hepatology. Optical diagnosis is currently offering beneficial outcomes in clinical fields ranging from the respiratory and gastrointestinal tracts, to dermatology and ophthalmology. Accordingly, this review aims to promote an effective bench to bedside transfer in hepatology.

Cluster analysis on breath print of newly diagnosed COPD patients: effects of therapy

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease and airflow limitation and symptoms only partially capture such heterogeneity. Since COPD is known to affect the production of volatile organic compounds (VOCs), we aimed to verify to which extent exhaled VOCs can characterize newly diagnosed COPD patients and changes in response to inhaled therapy.

MATERIALS AND METHODS

Fifty newly diagnosed COPD patients were consecutively recruited among those attending the pulmonary medicine outpatient clinic at 'Campus Bio-Medico' University Hospital. VOCs were collected using the Pneumopipe^® and analysed by the BIONOTE electronic nose both at baseline and after 12 weeks of inhaled therapy. Patients were grouped using K-mean cluster analysis on BIONOTE responses and the obtained clusters were compared via non-parametric tests.

RESULTS

We identified three clusters of subjects: (a) without remarkable comorbidities; (b) with air trapping and higher BODE index score (mean 1.2); (c) without air trapping and with a lower BODE index. Inhaled bronchodilators caused a quantitative reduction in the amound of VOCs, while inhaled steroids provided a qualitative modification of the breath profile.

CONCLUSION

VOCs patterns categorize newly diagnosed COPD subjects. VOCs production declines after bronchodilators administration and changes in quality after topic steroid treatment.

Study on Interference Suppression Algorithms for Electronic Noses: A Review

Electronic noses (e-nose) are composed of an appropriate pattern recognition system and a gas sensor array with a certain degree of specificity and broad spectrum characteristics. The gas sensors have their own shortcomings of being highly sensitive to interferences which has an impact on the detection of target gases. When there are interferences, the performance of the e-nose will deteriorate. Therefore, it is urgent to study interference suppression techniques for e-noses. This paper summarizes the sources of interferences and reviews the advances made in recent years in interference suppression for e-noses. According to the factors which cause interference, interferences can be classified into two types: interference caused by changes of operating conditions and interference caused by hardware failures. The existing suppression methods were summarized and analyzed from these two aspects. Since the interferences of e-noses are uncertain and unstable, it can be found that some nonlinear methods have good effects for interference suppression, such as methods based on transfer learning, adaptive methods, etc.

Radar plots: A novel modality for displaying disparate data on the efficacy of eluxadoline for the treatment of irritable bowel syndrome with diarrhea

BACKGROUND

Patients with irritable bowel syndrome with diarrhea (IBS-D) experience a range of abdominal and bowel symptoms; successful management requires alleviation of this constellation of symptoms. Eluxadoline, a locally active mixed μ- and κ-opioid receptor agonist and δ-opioid receptor antagonist, is approved for the treatment of IBS-D in adults based on the results of 2 Phase 3 studies. Radar plots can facilitate comprehensive, visual evaluation of diverse but interrelated efficacy endpoints.

METHODS

Two double-blind, placebo-controlled, Phase 3 trials (IBS-3001 and IBS-3002) randomized patients meeting Rome III criteria for IBS-D to twice-daily eluxadoline 75 or 100 mg or placebo. Radar plots were prepared showing pooled Weeks 1-26 response rates for the primary efficacy composite endpoint (simultaneous improvement in abdominal pain and stool consistency), stool consistency, abdominal pain, urgency-free days, and adequate relief, and change from baseline to Week 26 in IBS-D global symptom score, abdominal discomfort, abdominal pain, abdominal bloating, and daily number of bowel movements.

KEY RESULTS

The studies enrolled 2428 patients. Eluxadoline increased Weeks 1-26 responder proportions vs placebo for the composite endpoint, stool consistency, abdominal pain, urgency-free days, and adequate relief. Changes from baseline to Week 26 in IBS-D global symptom score, abdominal discomfort, abdominal pain, abdominal bloating, and number of bowel movements were greater with eluxadoline vs placebo.

CONCLUSIONS AND INFERENCES

Data presentation in radar plot format facilitates interpretation across multiple domains, demonstrating that eluxadoline treatment led to improvements vs placebo across 13 endpoints representing the range of symptoms experienced by patients with IBS-D.

Breathprinting and Early Diagnosis of Lung Cancer

The electronic nose (e-nose) is a promising technology as a useful addition to the currently available modalities to achieve lung cancer diagnosis. The e-nose can assess the volatile organic compounds detected in the breath and derived from the cellular metabolism. Volatile organic compounds can be analyzed to identify the individual chemical elements as well as their pattern of expression to reproduce a sensorial combination similar to a fingerprint (breathprint). The e-nose can be used alone, mimicking the combinatorial selectivity of the human olfactory system, or as part of a multisensorial platform. This review analyzes the progress made by investigators interested in this technology as well as the perspectives for its future utilization.

Analysis of volatile organic compounds: an innovative approach to heart failure characterization in older patients

BACKGROUND

Analysis of exhaled volatile organic compounds (VOCs) may be applied for diagnostic purposes in some chronic diseases, but there are no data on their role for discriminating people with congestive heart failure (CHF), particularly in older patients where natriuretic peptides have lower accuracy. We evaluated whether VOCs analysis can discriminate patients with or without CHF, stratify CHF severity and predict the response to therapy of decompensated CHF.

METHODS AND RESULTS

We recruited 89 subjects admitted to an acute care ward with acutely decompensated CHF, 117 healthy controls and 103 chronic obstructive pulmonary disease (COPD) controls. CHF patients performed echocardiography. VOCs were collected using the Pneumopipe^® and analyzed with the BIONOTE electronic nose. Partial least square analysis was used to evaluate the discriminative capacity of VOCs. Accuracy in discrimination of CHF versus healthy and COPD controls was 81% and 69%, respectively; accuracy did not decrease in a sensitivity analysis excluding subjects younger than 65 and older than 80 years. In CHF patients VOCs pattern could predict with fair precision ejection fraction and systolic pulmonary arterial pressure, but not changes in weight due to therapy.

CONCLUSIONS

VOCs pattern is able to discriminate older CHF patients from healthy people and COPD patients and correlates with cardiac function markers.

Breath-print analysis by e-nose may refine risk stratification for adverse outcomes in cirrhotic patients

BACKGROUND & AIMS

The spectrum of volatile organic compounds in the exhaled breath (breath-print, BP) has been shown to characterize patients with cirrhosis and with worse hepatic function. However, the association of different BPs with clinically relevant outcomes has not been described yet. Hence, we aimed to evaluate the association between BPs, mortality and hospitalization in cirrhotic patients and to compare it with that of the "classical" prognostic indices (Child-Pugh Classification [CPC] and MELD).

METHODS

Eighty-nine cirrhotic patients (M/F 59/30, mean age 64.8 ± 11.3, CPC A/B/C 37/33/19) were recruited and followed up for a median time of 23 months. Clinical and biochemical data were collected. Breath collection and analysis were obtained through Pneumopipe^® and BIONOTE e-nose respectively.

RESULTS

Four different BP clusters (A, B, C, D) were identified. BP clusters A and D were associated with a significantly increased risk of mortality (HR 2.9, 95% confidence intervals [CI] 1.5-5.6) and hospitalization (HR 2.6, 95% CI 1.4-4.6), even in multiple adjusted models including CPC and MELD score (adjusted [a]HR 2.8, 95% CI 1.1-7.0 for mortality and aHR 2.2, 95% CI 1.1-4.2 for hospitalization). CPC C maintained the strongest association with both mortality (aHR 17.6, 95% CI 1.8-174.0) and hospitalization (aHR 12.4, 95% CI 2.0-75.8).

CONCLUSIONS

This pilot study demonstrates that BP clusters are associated with significant clinical endpoints (mortality and hospitalization) even independently from "classical" prognostic indices. Even though further studies are warranted on this topic, our findings suggest that the e-nose may become an adjunctive aid to stratify the risk of adverse outcomes in cirrhotic patients.