Non-Invasive Assessment of Metabolic Adaptation in Paediatric Patients Suffering from Type 1 Diabetes Mellitus

An inexpensive UV-LED photoacoustic based real-time sensor-system detecting exhaled trace-acetone

In this research we present a low-cost system for breath acetone analysis based on UV-LED photoacoustic spectroscopy. We considered the end-tidal phase of exhalation, which represents the systemic concentrations of volatile organic compounds (VOCs) - providing clinically relevant information about the human health. This is achieved via the development of a CO2-triggered breath sampling system, which collected alveolar breath over several minutes in sterile and inert containers. A real-time mass spectrometer is coupled to serve as a reference device for calibration measurements and subsequent breath analysis. The new sensor system provided a 3σ detection limit of 8.3 ppbV and an NNEA of 1.4E-9 Wcm-1Hz-0.5. In terms of the performed breath analysis measurements, 12 out of 13 fell within the error margin of the photoacoustic measurement system, demonstrating the reliability of the measurements in the field.

Advanced Mass Spectrometry-Based Biomarker Identification for Metabolomics of Diabetes Mellitus and Its Complications

Over the years, there has been notable progress in understanding the pathogenesis and treatment modalities of diabetes and its complications, including the application of metabolomics in the study of diabetes, capturing attention from researchers worldwide. Advanced mass spectrometry, including gas chromatography-tandem mass spectrometry (GC-MS/MS), liquid chromatography-tandem mass spectrometry (LC-MS/MS), and ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS), etc., has significantly broadened the spectrum of detectable metabolites, even at lower concentrations. Advanced mass spectrometry has emerged as a powerful tool in diabetes research, particularly in the context of metabolomics. By leveraging the precision and sensitivity of advanced mass spectrometry techniques, researchers have unlocked a wealth of information within the metabolome. This technology has enabled the identification and quantification of potential biomarkers associated with diabetes and its complications, providing new ideas and methods for clinical diagnostics and metabolic studies. Moreover, it offers a less invasive, or even non-invasive, means of tracking disease progression, evaluating treatment efficacy, and understanding the underlying metabolic alterations in diabetes. This paper summarizes advanced mass spectrometry for the application of metabolomics in diabetes mellitus, gestational diabetes mellitus, diabetic peripheral neuropathy, diabetic retinopathy, diabetic nephropathy, diabetic encephalopathy, diabetic cardiomyopathy, and diabetic foot ulcers and organizes some of the potential biomarkers of the different complications with the aim of providing ideas and methods for subsequent in-depth metabolic research and searching for new ways of treating the disease.

Protocol for visualizing complex volatile metabolomics data in clinical setups using EDaViS software

Here, we present a protocol for using Early Data Visualization Script, a user-friendly software tool to visualize complex volatile metabolomics data in clinical setups. We describe steps for tabulating data and adjusting visual output to visualize complex time-resolved volatile omics data using simple charts and graphs. We then demonstrate possible modifications by detailing procedures for the adaptation of four basic functions. For complete details on the use and execution of this protocol, please refer to Sukul et al. (2022)1 and Remy et al. (2022).2.

Effects of Contagious Respiratory Pathogens on Breath Biomarkers

Due to their immediate exhalation after generation at the cellular/microbiome levels, exhaled volatile organic compounds (VOCs) may provide real-time information on pathophysiological mechanisms and the host response to infection. In recent years, the metabolic profiling of the most frequent respiratory infections has gained interest as it holds potential for the early, non-invasive detection of pathogens and the monitoring of disease progression and the response to therapy. Using previously unpublished data, randomly selected individuals from a COVID-19 test center were included in the study. Based on multiplex PCR results (non-SARS-CoV-2 respiratory pathogens), the breath profiles of 479 subjects with the presence or absence of flu-like symptoms were obtained using proton-transfer-reaction time-of-flight mass spectrometry. Among 223 individuals, one respiratory pathogen was detected in 171 cases, and more than one pathogen in 52 cases. A total of 256 subjects had negative PCR test results and had no symptoms. The exhaled VOC profiles were affected by the presence of Haemophilus influenzae, Streptococcus pneumoniae, and Rhinovirus. The endogenous ketone, short-chain fatty acid, organosulfur, aldehyde, and terpene concentrations changed, but only a few compounds exhibited concentration changes above inter-individual physiological variations. Based on the VOC origins, the observed concentration changes may be attributed to oxidative stress and antioxidative defense, energy metabolism, systemic microbial immune homeostasis, and inflammation. In contrast to previous studies with pre-selected patient groups, the results of this study demonstrate the broad inter-individual variations in VOC profiles in real-life screening conditions. As no unique infection markers exist, only concentration changes clearly above the mentioned variations can be regarded as indicative of infection or colonization.

Artificial Neural Processing-Driven Bioelectronic Nose for the Diagnosis of Diabetes and Its Complications

Diabetes and its complications affect the younger population and are associated with a high mortality rate; however, early diagnosis can contribute to the selection of appropriate treatment regimens that can reduce mortality. Although diabetes diagnosis via exhaled breath has great potential for early diagnosis, research on such diagnosis is restricted to disease detection, requiring in-depth examination to diagnose and classify diseases and their complications. This study demonstrates the use of an artificial neural processing-based bioelectronic nose to accurately diagnose diabetes and classify diabetic types (type I and II) and their complications, such as heart disease. Specifically, an M13 phage-based electronic nose (e-nose) is used to explore the features of subjects with diabetes at various levels of cellular and organismal organization (cells, liver organoids, and mice). Exhaled breath samples are collected during culturing and exposed to the phage-based e-nose. Compared with cells, liver organoids cultured under conditions mimicking a diabetic environment display properties that closely resemble the characteristics of diabetic mice. Using neural pattern separation, the M13 phage-based e-nose achieves a classification success rate of over 86% for four conditions in mice, namely, type 1 diabetes, type 2 diabetes, diabetic cardiomyopathy, and cardiomyopathy.

The Role of Nano-Sensors in Breath Analysis for Early and Non-Invasive Disease Diagnosis

Early-stage, precise disease diagnosis and treatment has been a crucial topic of scientific discussion since time immemorial. When these factors are combined with experience and scientific knowledge, they can benefit not only the patient, but also, by extension, the entire health system. The development of rapidly growing novel technologies allows for accurate diagnosis and treatment of disease. Nanomedicine can contribute to exhaled breath analysis (EBA) for disease diagnosis, providing nanomaterials and improving sensing performance and detection sensitivity. Through EBA, gas-based nano-sensors might be applied for the detection of various essential diseases, since some of their metabolic products are detectable and measurable in the exhaled breath. The design and development of innovative nanomaterial-based sensor devices for the detection of specific biomarkers in breath samples has emerged as a promising research field for the non-invasive accurate diagnosis of several diseases. EBA would be an inexpensive and widely available commercial tool that could also be used as a disease self-test kit. Thus, it could guide patients to the proper specialty, bypassing those expensive tests, resulting, hence, in earlier diagnosis, treatment, and thus a better quality of life. In this review, some of the most prevalent types of sensors used in breath-sample analysis are presented in parallel with the common diseases that might be diagnosed through EBA, highlighting the impact of incorporating new technological achievements in the clinical routine.

Smelling the Disease: Diagnostic Potential of Breath Analysis

Breath analysis is a relatively recent field of research with much promise in scientific and clinical studies. Breath contains endogenously produced volatile organic components (VOCs) resulting from metabolites of ingested precursors, gut and air-passage bacteria, environmental contacts, etc. Numerous recent studies have suggested changes in breath composition during the course of many diseases, and breath analysis may lead to the diagnosis of such diseases. Therefore, it is important to identify the disease-specific variations in the concentration of breath to diagnose the diseases. In this review, we explore methods that are used to detect VOCs in laboratory settings, VOC constituents in exhaled air and other body fluids (e.g., sweat, saliva, skin, urine, blood, fecal matter, vaginal secretions, etc.), VOC identification in various diseases, and recently developed electronic (E)-nose-based sensors to detect VOCs. Identifying such VOCs and applying them as disease-specific biomarkers to obtain accurate, reproducible, and fast disease diagnosis could serve as an alternative to traditional invasive diagnosis methods. However, the success of VOC-based identification of diseases is limited to laboratory settings. Large-scale clinical data are warranted for establishing the robustness of disease diagnosis. Also, to identify specific VOCs associated with illness states, extensive clinical trials must be performed using both analytical instruments and electronic noses equipped with stable and precise sensors.

Physio-metabolic and clinical consequences of wearing face masks—Systematic review with meta-analysis and comprehensive evaluation

Background

As face masks became mandatory in most countries during the COVID-19 pandemic, adverse effects require substantiated investigation.

Methods

A systematic review of 2,168 studies on adverse medical mask effects yielded 54 publications for synthesis and 37 studies for meta-analysis (on n = 8,641, m = 2,482, f = 6,159, age = 34.8 ± 12.5). The median trial duration was only 18 min (IQR = 50) for our comprehensive evaluation of mask induced physio-metabolic and clinical outcomes.

Results

We found significant effects in both medical surgical and N95 masks, with a greater impact of the second. These effects included decreased SpO2 (overall Standard Mean Difference, SMD = −0.24, 95% CI = −0.38 to −0.11, p < 0.001) and minute ventilation (SMD = −0.72, 95% CI = −0.99 to −0.46, p < 0.001), simultaneous increased in blood-CO2 (SMD = +0.64, 95% CI = 0.31–0.96, p < 0.001), heart rate (N95: SMD = +0.22, 95% CI = 0.03–0.41, p = 0.02), systolic blood pressure (surgical: SMD = +0.21, 95% CI = 0.03–0.39, p = 0.02), skin temperature (overall SMD = +0.80 95% CI = 0.23–1.38, p = 0.006) and humidity (SMD +2.24, 95% CI = 1.32–3.17, p < 0.001). Effects on exertion (overall SMD = +0.9, surgical = +0.63, N95 = +1.19), discomfort (SMD = +1.16), dyspnoea (SMD = +1.46), heat (SMD = +0.70), and humidity (SMD = +0.9) were significant in n = 373 with a robust relationship to mask wearing (p < 0.006 to p < 0.001). Pooled symptom prevalence (n = 8,128) was significant for: headache (62%, p < 0.001), acne (38%, p < 0.001), skin irritation (36%, p < 0.001), dyspnoea (33%, p < 0.001), heat (26%, p < 0.001), itching (26%, p < 0.001), voice disorder (23%, p < 0.03), and dizziness (5%, p = 0.01).

Discussion

Masks interfered with O2-uptake and CO2-release and compromised respiratory compensation. Though evaluated wearing durations are shorter than daily/prolonged use, outcomes independently validate mask-induced exhaustion-syndrome (MIES) and down-stream physio-metabolic disfunctions. MIES can have long-term clinical consequences, especially for vulnerable groups. So far, several mask related symptoms may have been misinterpreted as long COVID-19 symptoms. In any case, the possible MIES contrasts with the WHO definition of health.

Conclusion

Face mask side-effects must be assessed (risk-benefit) against the available evidence of their effectiveness against viral transmissions. In the absence of strong empirical evidence of effectiveness, mask wearing should not be mandated let alone enforced by law.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021256694, identifier: PROSPERO 2021 CRD42021256694.

Advanced setup for safe breath sampling and patient monitoring under highly infectious conditions in the clinical environment

Being the proximal matrix, breath offers immediate metabolic outlook of respiratory infections. However, high viral load in exhalations imposes higher transmission risk that needs improved methods for safe and repeatable analysis. Here, we have advanced the state-of-the-art methods for real-time and offline mass-spectrometry based analysis of exhaled volatile organic compounds (VOCs) under SARS-CoV-2 and/or similar respiratory conditions. To reduce infection risk, the general experimental setups for direct and offline breath sampling are modified. Certain mainstream and side-stream viral filters are examined for direct and lab-based applications. Confounders/contributions from filters and optimum operational conditions are assessed. We observed immediate effects of infection safety mandates on breath biomarker profiles. Main-stream filters induced physiological and analytical effects. Side-stream filters caused only systematic analytical effects. Observed substance specific effects partly depended on compound's origin and properties, sampling flow and respiratory rate. For offline samples, storage time, -conditions and -temperature were crucial. Our methods provided repeatable conditions for point-of-care and lab-based breath analysis with low risk of disease transmission. Besides breath VOCs profiling in spontaneously breathing subjects at the screening scenario of COVID-19/similar test centres, our methods and protocols are applicable for moderately/severely ill (even mechanically-ventilated) and highly contagious patients at the intensive care.

Profiling of exhaled volatile organics in the screening scenario of a COVID-19 test center

Breath volatile organics (VOCs) may provide immediate information on infection mechanisms and host response. We conducted real-time mass spectrometry-based breath profiling in 708 non-preselected consecutive subjects in the screening scenario of a COVID-19 test center. Recruited subjects were grouped based on PCR-confirmed infection status and presence or absence of flu-like symptoms. Exhaled VOC profiles of SARS-CoV-2-positive cases (n = 36) differed from healthy (n = 256) and those with other respiratory infections (n = 416). Concentrations of most VOCs were suppressed in COVID-19. VOC concentrations also differed between symptomatic and asymptomatic cases. Breath markers mirror effects of infections onto host's cellular metabolism and microbiome. Downregulation of specific VOCs was attributed to suppressive effects of SARS-CoV-2 onto gut or pulmonary microbial metabolism. Breath analysis holds potential for monitoring SARS-CoV-2 infections rather than for primary diagnosis. Breath profiling offers unconventional insight into host-virus cross-talk and infection microbiology and enables non-invasive assessment of disease manifestation.

Real-time metabolic monitoring under exhaustive exercise and evaluation of ventilatory threshold by breathomics: Independent validation of evidence and advances

Breath analysis was coupled with ergo-spirometry for non-invasive profiling of physio-metabolic status under exhaustive exercise. Real-time mass-spectrometry based continuous analysis of exhaled metabolites along with breath-resolved spirometry and heart rate monitoring were executed while 14 healthy adults performed ergometric ramp exercise protocol until exhaustion. Arterial blood lactate level was analyzed at defined time points. Respiratory-cardiac parameters and exhalation of several blood-borne volatiles changed continuously with the course of exercise and increasing workloads. Exhaled volatiles mirrored ventilatory and/or hemodynamic effects and depended on the origin and/or physicochemical properties of the substances. At the maximum workload, endogenous isoprene, methanethiol, dimethylsulfide, acetaldehyde, butanal, butyric acid and acetone concentrations decreased significantly by 74, 25, 35, 46, 21, 2 and 2%, respectively. Observed trends in exogenous cyclohexadiene and acetonitrile mimicked isoprene profile due to their similar solubility and volatility. Assignment of anaerobic threshold was possible via breath acetone. Breathomics enabled instant profiling of physio-metabolic effects and anaerobic thresholds during exercise. Profiles of exhaled volatiles indicated effects from muscular vasoconstriction, compartmental distribution of perfusion, extra-alveolar gas-exchange and energy homeostasis. Sulfur containing compounds and butyric acid turned out to be interesting for investigations of combined diet and exercise programs. Reproducible metabolic breath patterns have enhanced scopes of breathomics in sports science/medicine.

Effects of COVID-19 protective face-masks and wearing durations onto respiratory-haemodynamic physiology and exhaled breath constituents

Background

While assumed to protect against coronavirus transmission, face masks may have effects on respiratory–haemodynamic parameters. Within this pilot study, we investigated immediate and progressive effects of FFP2 and surgical masks on exhaled breath constituents and physiological attributes in 30 adults at rest.

Methods

We continuously monitored exhaled breath profiles within mask space in older (age 60–80 years) and young to middle-aged (age 20–59 years) adults over the period of 15 and 30 min by high-resolution real-time mass-spectrometry. Peripheral oxygen saturation (S_pO2) and respiratory and haemodynamic parameters were measured (noninvasively) simultaneously.

Results

Profound, consistent and significant (p≤0.001) changes in S_pO2 (≥60_FFP2-15 min: 5.8±1.3%↓, ≥60_surgical-15 min: 3.6±0.9%↓, <60_FFP2-30 min: 1.9±1.0%↓, <60_surgical-30 min: 0.9±0.6%↓) and end-tidal carbon dioxide tension (P_ETCO2) (≥60_FFP2-15 min: 19.1±8.0%↑, ≥60_surgical-15 min: 11.6±7.6%↑, <60_FFP2- 30 min: 12.1±4.5%↑, <60_surgical- 30 min: 9.3±4.1%↑) indicate ascending deoxygenation and hypercarbia. Secondary changes (p≤0.005) to haemodynamic parameters (e.g. mean arterial pressure (MAP) ≥60_FFP2-15 min: 9.8±10.4%↑) were found. Exhalation of bloodborne volatile metabolites, e.g. aldehydes, hemiterpene, organosulfur, short-chain fatty acids, alcohols, ketone, aromatics, nitrile and monoterpene mirrored behaviour of cardiac output, MAP, S_pO2, respiratory rate and P_ETCO2. Exhaled humidity (e.g. ≥60_FFP2-15 min: 7.1±5.8%↑) and exhaled oxygen (e.g. ≥60_FFP2-15 min: 6.1±10.0%↓) changed significantly (p≤0.005) over time.

Conclusions

Breathomics allows unique physiometabolic insights into immediate and transient effects of face mask wearing. Physiological parameters and breath profiles of endogenous and/or exogenous volatile metabolites indicated putative cross-talk between transient hypoxaemia, oxidative stress, hypercarbia, vasoconstriction, altered systemic microbial activity, energy homeostasis, compartmental storage and washout. FFP2 masks had a more pronounced effect than surgical masks. Older adults were more vulnerable to FFP2 mask-induced hypercarbia, arterial oxygen decline, blood pressure fluctuations and concomitant physiological and metabolic effects.

While assumed to protect against SARS-CoV-2 transmission, face masks cause various physiometabolic side-effects and changes in exhaled VOC profiles. Effects are more pronounced in FFP2 masks and are profound at age ≥60 years.https://bit.ly/33fzOMA

Exhaled Breath Analysis for Diabetes Diagnosis and Monitoring: Relevance, Challenges and Possibilities

With the global population prevalence of diabetes surpassing 463 million cases in 2019 and diabetes leading to millions of deaths each year, there is a critical need for feasible, rapid, and non-invasive methodologies for continuous blood glucose monitoring in contrast to the current procedures that are either invasive, complicated, or expensive. Breath analysis is a viable methodology for non-invasive diabetes management owing to its potential for multiple disease diagnoses, the nominal requirement of sample processing, and immense sample accessibility; however, the development of functional commercial sensors is challenging due to the low concentration of volatile organic compounds (VOCs) present in exhaled breath and the confounding factors influencing the exhaled breath profile. Given the complexity of the topic and the skyrocketing spread of diabetes, a multifarious review of exhaled breath analysis for diabetes monitoring is essential to track the technological progress in the field and comprehend the obstacles in developing a breath analysis-based diabetes management system. In this review, we consolidate the relevance of exhaled breath analysis through a critical assessment of current technologies and recent advancements in sensing methods to address the shortcomings associated with blood glucose monitoring. We provide a detailed assessment of the intricacies involved in the development of non-invasive diabetes monitoring devices. In addition, we spotlight the need to consider breath biomarker clusters as opposed to standalone biomarkers for the clinical applicability of exhaled breath monitoring. We present potential VOC clusters suitable for diabetes management and highlight the recent buildout of breath sensing methodologies, focusing on novel sensing materials and transduction mechanisms. Finally, we portray a multifaceted comparison of exhaled breath analysis for diabetes monitoring and highlight remaining challenges on the path to realizing breath analysis as a non-invasive healthcare approach.

Deficiency and absence of endogenous isoprene in adults, disqualified its putative origin

Background

Isoprene (C₅H₈) is a clinically important breath metabolite. Although, hundreds of studies have reported differential expressions in isoprene exhalation as breath biomarker for diverse diseases, the substance couldn't enter to clinical practice as diagnostic marker. Moreover, many experimental/basic observations upon breath isoprene remained unrelated to the corresponding pathophysiological effects on its putative metabolic origin (i.e. mevalonate pathway). Here, we investigated the fundamental reason that hindered the rational interpretation and translation of this marker from basic to clinical science.

Methods

Via high-resolution mass-spectrometry based breathomics in 1026 human subjects, we discovered adults with significant deficiency (order of magnitude lower than the normal) and complete absence of breath isoprene. We prospectively applied real-time breathomics, quantitative gene expression analysis of the mevalonate pathway enzymes, lipid-profiling and hemodynamic monitoring on those isoprene deficient subjects and controls. Additionally, the subject with absence of isoprene was followed up throughout different phases of her womanhood.

Results

In contrast to convention, we witnessed that adults can live healthy without exhaling isoprene or with significant deficiency. This rare phenotype represents a recessive inheritance. Despite physio-metabolic changes during menstrual cycle (that is known to profoundly affect isoprene exhalation) and profoundly increased plasma cholesterol during pregnancy and after childbirth, isoprene remained absent. All genes of mevalonate pathway enzymes were normally expressed in all participants, without any down-regulation or compensatory up-regulation.

Conclusions

Absence/deficiency of isoprene despite normal lipid profiles and no mevalonate pathway malfunction disqualifies the long-believed metabolic origin of isoprene from cholesterol biosynthesis. Thus, clinical translation of breath isoprene expressions should not be generally attributed to corresponding pathophysiological effects onto mevalonate/cholesterol pathway. Our finding has refined and optimized the clinical interpretation of isoprene as biomarker in volatile metabolomics and breathomics. Future studies will address the correct metabolic origin of isoprene to imply this important marker to routine practice.

The correlation between breath acetone and blood betahydroxybutyrate in individuals with type 1 diabetes

Ketone testing is an important element of the self-management of illness in type 1 diabetes. The aim of the present study was to see if a breath test for acetone could be used to predict quantitatively the levels of the ketone betahydroxybutyrate in the blood of those with type 1 diabetes, and thus be used as an alternative to capillary testing for ketones. Simultaneous capillary ketones and breath acetone were measured in 72 individuals with type 1 diabetes attending a diabetes clinic and on 9 individuals admitted to hospital with diabetic ketoacidosis. Capillary blood measurements ranged from 0.1 mmol l^-1 (the lower limit of the ketone monitor) to over 7 mmol l^-1, with breath acetone varying between 0.25 and 474 parts per million by volume. The two variables were found to be correlated and allowed modelling to be carried out which separated breath acetone levels into three categories corresponding to normal, elevated and 'at risk' levels of blood ketones. The results on this limited set of participants suggest that a breath acetone test could be a simple, non-invasive substitute for capillary ketone measurement in type 1 diabetes.

Changes of Exhaled Volatile Organic Compounds in Postoperative Patients Undergoing Analgesic Treatment: A Prospective Observational Study

Assessment and treatment of postoperative pain can be challenging as objective examination techniques to detect and quantify pain are lacking. We aimed to investigate changes of exhaled volatile organic compounds (VOCs) in patients with postoperative pain before and after treatment with opioid analgesics. In an observational study in 20 postoperative patients, we monitored for postoperative pain, hemodynamic parameters, and catecholamines before and during treatment. VOCs in the patients were determined by direct real-time proton transfer reaction time-of-flight mass spectrometry prior (0 min) and after piritramide application (15 min as well as 30 min). Cardiovascular variables changed and norepinephrine levels decreased during treatment. The VOCs acetonitrile (<0.001), acetaldehyde (p = 0.002), benzopyran (p = 0.004), benzene (p < 0.001), hexenal (p = < 0.001), 1-butanethiol (p = 0.004), methanethiol (p < 0.001), ethanol (p = 0.003), and propanol (p = < 0.001) changed significantly over time. Patients with Numeric Rating Scale (NRS) < 4 showed a significantly lower concentration of hexenal compared to patients with NRS > 4 at the time points 15 min (45.0 vs. 385.3 ncps, p = 0.047) and 30 min (38.3 vs. 334.6 ncps, p = 0.039). Breath analysis can provide additional information for noninvasive monitoring for analgesic treatment in postoperative patients.

The Effects of Prebiotic Supplementation with OMNi-LOGiC® FIBRE on Fecal Microbiome, Fecal Volatile Organic Compounds, and Gut Permeability in Murine Neuroblastoma-Induced Tumor-Associated Cachexia

Malignant diseases can cause tumor-associated cachexia (TAC). Supplementation with prebiotic non-digestible carbohydrates exerts positive metabolic effects in experimental oncologic diseases. The aim of this project was to assess the effect of prebiotic supplementation with OMNi-LOGiC^® FIBRE on intestinal microbiome, bacterial metabolism, gut permeability, and inflammation in a murine model of neuroblastoma (NB)-associated TAC. For this study, 2,000,000 NB cells (MHH-NB11) were implanted into athymic mice followed by daily supplementation with water or 200 mg prebiotic oligosaccharide (POS) OMNi-LOGiC^® FIBRE (NB-Aqua, n = 12; NB-POS, n = 12). Three animals of each tumor group did not develop NB. The median time of tumor growth (first visibility to euthanasia) was 37 days (IQR 12.5 days) in the NB-Aqua group and 37 days (IQR 36.5 days) in the NB-POS group (p = 0.791). At euthanasia, fecal microbiome and volatile organic compounds (VOCs), gut permeability (fluorescein isothiocyanate-dextran (FITC-dextran), and gut barrier markers were measured. Values were compared to sham animals following injection of culture medium and gavage of either water or OMNi-LOGiC^® FIBRE (SH-Aqua, n = 10; SH-POS, n = 10). Alpha diversity did not differ significantly between the groups. Principal coordinate analysis (PCoA) revealed clustering differences between Aqua and POS animals. Both NB and POS supplementation led to taxonomic alterations of the fecal microbiome. Of 49 VOCs, 22 showed significant differences between the groups. NB animals had significantly higher gut permeability than Aqua animals; POS did not ameliorate these changes. The pore and leak pathways of tight junctions did not differ between groups. In conclusion, our results suggest that NB-induced TAC causes increased gut permeability coupled with compositional changes in the fecal microbiome and VOC profile. Prebiotic supplementation with OMNi-LOGiC^® FIBRE seemed to induce modifications of the fecal microbiome and VOC profile but did not improve gut permeability.

Unravelling the Potential of Salivary Volatile Metabolites in Oral Diseases. A Review

Fostered by the advances in the instrumental and analytical fields, in recent years the analysis of volatile organic compounds (VOCs) has emerged as a new frontier in medical diagnostics. VOCs analysis is a non-invasive, rapid and inexpensive strategy with promising potential in clinical diagnostic procedures. Since cellular metabolism is altered by diseases, the resulting metabolic effects on VOCs may serve as biomarkers for any given pathophysiologic condition. Human VOCs are released from biomatrices such as saliva, urine, skin emanations and exhaled breath and are derived from many metabolic pathways. In this review, the potential of VOCs present in saliva will be explored as a monitoring tool for several oral diseases, including gingivitis and periodontal disease, dental caries, and oral cancer. Moreover, the analytical state-of-the-art for salivary volatomics, e.g., the most common extraction techniques along with the current challenges and future perspectives will be addressed unequivocally.