Increased breath biomarkers of oxidative stress in diabetes mellitus

The smell of sepsis: Electronic nose measurements improve early recognition of sepsis in the ED

OBJECTIVE

Early recognition of sepsis is essential for timely initiation of adequate care. However, this is challenging as signs and symptoms may be absent or nonspecific. The cascade of events leading to organ failure in sepsis is characterized by immune-metabolic alterations. Volatile organic compounds (VOCs) are metabolic byproducts released in expired air. We hypothesize that measuring the VOC profile using electronic nose technology (eNose) could improve early recognition of sepsis.

MATERIAL AND METHODS

In this cohort study, bedside eNose measurements were collected prospectively from ED patients with suspected infections. Sepsis diagnosis was retrospectively defined based on Sepsis-3 criteria. eNose sensor data were used in a discriminant analysis to evaluate the predictive performance for early sepsis recognition. The dataset was randomly split into training (67 %) and validation (33 %) subsets. The derived discriminant function from the training subset was then applied to classify new observations in the validation subset. Model performance was evaluated using receiver operating characteristic (ROC) curves and predictive values.

RESULTS

We analyzed a total of 160 eNose measurements. The eNose measurements had an area under the ROC (AUROC) of 0.78 (95 % CI: 0.69-0.87) for diagnosing sepsis, with a sensitivity of 72 %, specificity of 73 %, and an overall accuracy of 73 %. The validation model showed an AUC of 0.83 (95 % CI: 0.71-0.94), sensitivity of 71 %, specificity of 83 %, and an accuracy of 80 %.

CONCLUSION

eNose measurements can identify sepsis among patients with a suspected infection at the ED.

CLINICAL TRIAL REGISTRATION

The study is embedded in the Acutelines data-biobank (www.acutelines.nl), registered in Clinicaltrials.gov (NCT04615065).

Selected ion flow tube studies of the reactions of H3O+, NO+, O2+˙ and O-˙ ions with alkanes in He and N2 carrier gases at different temperatures

The kinetics of the reactions of H3O+, NO+, O2+˙ and O-˙ with n-hexane, 3-methylpentane, 2,5-dimethylhexane and 2,3-dimethylheptane were studied experimentally under several selected ion flow tube (SIFT) conditions: in a Profile 3 instrument in He and N2 carrier gases at 300 K and in the Voice200 instrument in N2 carrier gas at 300 and 393 K - where the effect of the extraction lens voltage was also assessed. It was found that H3O+ ions react differently than expected, with reaction rates slower than collisional. Instead of transferring a proton, they associate and form fragment product ions [M-H]+. NO+ ions react via hydride ion transfer. O2+˙ ions react via charge transfer followed by fragmentation that is highly sensitive to the temperature and the ion extraction lens voltage. Negative ions did not react, except for the O-˙ ion, which reacted via an associative detachment process. Computational analysis using Density Functional Theory (DFT) provided insights into the exothermicities and exergodicities of these reactions. A notable result is that proton transfer from H3O+ does not take place despite its potential exothermicity; this is important for the interpretation of proton transfer reaction (PTR) and SIFT mass spectrometry data.

Stimulated C2C12 Myotube Headspace Volatile Organic Compound Analysis

Understanding exercise metabolism and the relationship with volatile organic compounds (VOCs) holds potential in both health care and sports performance. Exercise metabolism can be investigated using whole body exercise testing (in vivo) or through the culture and subsequent electrical pulse stimulation (EPS) of myotubes (in vitro). This research investigates the novel headspace (HS) analysis of EPS skeletal muscle myotubes. An in vitro system was built to investigate the effect of EPS on the volatile constituents in the HS above EPS skeletal muscle. The C2C12 immortalised cell line was chosen. EPS was applied to the system to induce myotube contraction. The in vitro system was applied to the analysis of VOCs using thermal desorption (TD) sampling. Samples were collected under four conditions: environmental samples (enviro), acellular media HS samples (blank), skeletal muscle myotubes without stimulation HS samples (baseline) and EPS of skeletal muscle myotube HS samples (stim). TD sampling combined with gas-chromatography mass spectrometry (GC-MS) detected two compounds that, after multivariate and univariate statistical analysis, were identified as changing due to EPS (p < 0.05). These compounds were tentatively assigned as 1,4-Dioxane-2,5-dione, 3,6-dimethyl- and 1-pentene. The former is a known lactide and the latter has been reported as a marker of oxidative stress. Further research should focus on improvements to the EPS system, including the use of more relevant cell lines, quantification of myotube contractions, and the application of targeted analysis, metabolic assays and media analysis.

Establishing Healthy Breath Baselines With Tin Oxide Sensors: Fundamental Building Blocks for Noninvasive Health Monitoring

INTRODUCTION

Volatile organic compounds (VOCs) in breath serve as a source of biomarkers for medical conditions relevant to warfighter health including Corona Virus Disease and other potential biological threats. Electronic noses are integrated arrays of gas sensors that are cost-effective and miniaturized devices that rapidly respond to VOCs in exhaled breath. The current study seeks to qualify healthy breath baselines of exhaled VOC profiles through analysis using a commercialized array of metal oxide (MOX) sensors.

MATERIALS AND METHODS

Subjects were recruited/consented through word of mouth and using posters. For each sample, breath was analyzed using an array of MOX sensors with parameters that were previously established. Data were also collected using a lifestyle questionnaire and from a blood test to assess markers of general health. Sensor data were processed using a feature extraction algorithm, which were analyzed through statistical approaches to identify correlations with confounding factors. Reproducibility was also assessed through relative standard deviation values of sensor features within a single subject and between different volunteers.

RESULTS

A total of 164 breath samples were collected from different individuals, and 10 of these volunteers provided an additional 9 samples over 6 months for the longitudinal study. First, data from different subjects were analyzed, and the trends of the 17 extracted features were elucidated. This revealed not only a high degree of correlation between sensors within the array but also between some of the features extracted within a single sensor. This helped guide the removal of multicollinear features for multivariate statistical analyses. No correlations were identified between sensor features and confounding factors of interest (age, body mass index, smoking, and sex) after P-value adjustment, indicating that these variables have an insignificant impact on the observed sensor signal. Finally, the longitudinal replicates were analyzed, and reproducibility assessment showed that the variability between subjects was significantly higher than within replicates of a single volunteer (P-value = .002). Multivariate analyses within the longitudinal data displayed that subjects could not be distinguished from one another, indicating that there may be a universal healthy breath baseline that is not specific to particular individuals.

CONCLUSIONS

The current study sought to qualify healthy baselines of VOCs in exhaled breath using a MOX sensor array that can be leveraged in the future to detect medical conditions relevant to warfighter health. For example, the results of the study will be useful, as the healthy breath VOC data from the sensor array can be cross-referenced in future studies aiming to use the device to distinguish disease states. Ultimately, the sensors may be integrated into a portable breathalyzer or current military gear to increase warfighter readiness through rapid and noninvasive health monitoring.

Partial role of volatile organic compounds in behavioural responses of mice to bedding from cancer-affected congeners

Tumours induce changes in body odours. We compared volatile organic compounds (VOCs) in soiled bedding of a lung adenocarcinoma male mouse model in which cancer had (CC) versus had not (NC) been induced by doxycycline at three conditions: before (T0), after 2 weeks (T2; early tumour development), after 12 weeks (T12; late tumour development) of the induction. In an earlier study, wild-derived mice behaviourally discriminated between CC and NC soiled bedding at T2 and T12. Here, we sought to identify VOCs present in the same soiled bedding that could have triggered the behavioural discrimination. Solid phase micro-extraction was performed to extract VOCs from 3 g-sample stimuli. While wild-derived mice could discriminate the odour of cancerous mice at a very early stage of tumour development (T2), the present study did not identify VOCs that could explain this behaviour. However, consistent with the earlier behavioural study, four VOCs, including two well-known male mouse sex pheromones, were found to be present in significantly different proportions in soiled bedding of CC as compared to NC at T12. We discuss the potential involvement of non-volatile molecules such as proteins and peptides in behavioural discrimination of early tumour development (T2), and point-out VOCs that could help diagnose cancer.

The role of volatile organic compounds for assessing characteristics and severity of non-cystic fibrosis bronchiectasis: an observational study

Background

Hypoxic conditions and Pseudomonas aeruginosa (P. aeruginosa) infection are significant factors influencing the prognosis and treatment of patients with bronchiectasis. This study aimed to explore the potential for breath analysis to detect hypoxic conditions and P. aeruginosa infection in bronchiectasis patients by analyzing of volatile organic compounds (VOCs) in exhaled breath condensate (EBC).

Methods

EBC samples were collected from stable bronchiectasis patients and analyzed using solid phase microextraction-gas chromatography-mass spectrometry (SPME-GCMS). The association of VOCs with bronchiectasis patients' phenotypes including hypoxic conditions and P. aeruginosa isolation was analyzed, which may relate to the severity of bronchiectasis disease.

Results

Levels of 10-heptadecenoic acid, heptadecanoic acid, longifolene, and decanol in the hypoxia group were higher compared to the normoxia group. Additionally, the levels of 13-octadecenoic acid, octadecenoic acid, phenol, pentadecanoic acid, and myristic acid were increased in P. aeruginosa (+) group compared to the P. aeruginosa (-) group. Subgroup analysis based on the bronchiectasis severity index (BSI)reveled that the levels of 10-heptadecenoic acid, heptadecanoic acid, decanol, 13-octadecenoic acid, myristic acid, and pentadecanoic acid were higher in the severe group compared to the moderate group. Multivariate linear regression showed that 10-heptadecenoic acid and age were independent prognostic factors for bronchiectasis patients with hypoxia. Furthermore, octadecenoic acid, phenol and gender were identified as independent prognostic factors for bronchiectasis patients with P. aeruginosa isolation.

Conclusion

The study provides evidence that specific VOCs in EBC are correlated with the severity of bronchiectasis, and 10-heptadecenoic acid is shown to be a predictive marker for hypoxia condition in bronchiectasis patients.

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

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

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.

Vitamin C supplementation for diabetes management: A comprehensive narrative review

Growing evidence suggests that vitamin C supplementation may be an effective adjunct therapy in the management of people with diabetes. This paper critically reviews the current evidence on effects of vitamin C supplementation and its potential mechanisms in diabetes management. Evidence from meta-analyses of randomized controlled trials (RCTs) show favourable effects of vitamin C on glycaemic control and blood pressure that may be clinically meaningful, and mixed effects on blood lipids and endothelial function. However, evidence is mostly of low evidence certainty. Emerging evidence is promising for effects of vitamin C supplementation on some diabetes complications, particularly diabetic foot ulcers. However, there is a notable lack of robust and well-designed studies exploring effects of vitamin C as a single compound supplement on diabetes prevention and patient-important outcomes (i.e. prevention and amelioration of diabetes complications). RCTs are also required to investigate potential preventative or ameliorative effects of vitamin C on gestational diabetes outcomes. Oral vitamin C doses of 500-1000 mg per day are potentially effective, safe, and affordable for many individuals with diabetes. However, personalisation of supplementation regimens that consider factors such as vitamin C status, disease status, current glycaemic control, vitamin C intake, redox status, and genotype is important to optimize vitamin C's therapeutic effects safely. Finally, given a high prevalence of vitamin C deficiency in patients with complications, it is recommended that plasma vitamin C concentration be measured and monitored in the clinic setting.

The effect of acupuncture on oxidative stress: A systematic review and meta-analysis of animal models

Introduction

Oxidative stress is involved in the occurrence and development of multiple diseases. Acupuncture shows an excellent clinical efficacy in practical application but its mechanism remains unclear. This systematic review and meta-analysis was aimed at assessing the effect of acupuncture on oxidative stress in animal models.

Methods

PubMed, Embase, and Web of Science database were retrieved for randomized controlled trials about acupuncture on oxidative stress in animal models from inception to August 2021. Two reviewers independently screened and extracted articles according to inclusion and exclusion criteria. We used the mean difference (MD)/standardized mean difference (SMD) to perform an effect size analysis and selected fixed-effect or random-effect models to pool the data, depending on a 95% confidence interval (CI).

Results

A total of 12 studies comprising 125 samples were included in the quantitative meta-analysis. Compared with sham acupuncture, acupuncture (manual acupuncture, electropuncture, and laser acupuncture) reduced the level of malondialdehyde (SMD, −3.03; CI, −4.40, −1.65; p < 0.00001) and increased the levels of superoxide dismutase (SMD, 3.39; CI, 1.99, 4.79; p < 0.00001), glutathione peroxidase (SMD, 2.21; CI, 1.10, 3.32; p < 0.00001), and catalase (SMD, 2.80; CI, 0.57, 5.03; p = 0.01).

Conclusion

This meta-analysis indicated that acupuncture can regulate oxidative stress by lowering the lipid peroxidation and activating the antioxidant enzyme system. In consideration of heterogeneity between studies, future studies should be performed by complying with strict standards and increasing sample size in animal experiments to reduce bias.

Sigesbeckia orientalis Extract Ameliorates the Experimental Diabetic Nephropathy by Downregulating the Inflammatory and Oxidative Stress Signaling Pathways

Diabetes in children and its complications are on the rise globally, which is accompanied by increasing in diabetes-related complications. Oxidative stress and inflammation induced by elevated blood sugar in diabetic patients are considered risk factors associated with the development of diabetes complications, including chronic kidney disease and its later development to end-stage renal disease. Microvascular changes within the kidneys of DM patients often lead to chronic kidney disease, which aggravates the illness. Sigesbeckia orientalis extract (SOE), reported to have strong antioxidative and excellent anti-inflammatory activities, is used in the modern practice of traditional Chinese medicine. Kidneys from three groups of control mice (CTR), mice with streptozotocin (STZ)-induced diabetes (DM), and mice with STZ-induced DM treated with SOE (DMRx) were excised for morphological analyses and immunohistochemical assessments. Only mice in the DM group exhibited significantly lower body weight, but higher blood sugar was present. The results revealed more obvious renal injury in the DM group than in the other groups, which appeared as greater glomerular damage and tubular injury, sores, and plenty of connective tissues within the mesangium. Not only did the DM group have a higher level of cytokine, tumor necrosis factor, and the oxidative stress marker, 8-hydroxyguanosine expression, but also factors of the nuclear factor pathway and biomarkers of microvascular status had changed. Disturbances to the kidneys in DMRx mice were attenuated compared to the DM group. We concluded that SOE is an effective medicine, with antioxidative and anti-inflammatory abilities, to protect against or attenuate diabetic nephropathy from inflammatory disturbances by oxidative stress and to cure vessel damage in a hyperglycemic situation.

Changes in the urine volatile metabolome throughout growth of transplanted hepatocarcinoma

Trained detection dogs distinguish between urine samples from healthy organisms and organisms with malignant tumors, suggesting that the volatile urine metabolome contains information about tumor progression. The aim of this study was to determine whether the stage of tumor growth affects the chemical differences in the urine of mice and to what extent the "olfactory image of disease" perceived by dogs coincides with the "image of disease" recorded by the mass spectrometer. We used a novel laser ionization mass spectrometry method and propose a mass spectrometric analysis without detailed interpretation of the spectrum of volatile metabolomes in urine. The mass spectrometer we use works without sample preparation and registers volatile organic compounds in air at room temperature without changing the pH of the sample, i.e. under conditions similar to those in which dogs solve the same problem. The experimental cancer models were male BDF-f1 hybrid mice transplanted with hepatocarcinoma tissue, and similar mice transplanted with healthy liver tissue were used as controls. Our data show that both dogs and our proposed laser mass spectrometry method are able to detect both the entire spectrum of volatile organic compounds associated with the disease and minor changes in this spectrum during its course.

Odours of cancerous mouse congeners: detection and attractiveness

Chemical communication plays a major role in social interactions. Cancer, by inducing changes in body odours, may alter interactions between individuals. In the framework of research targeting non-invasive methods to detect early stages of cancer development, this study asked whether untrained mice could detect odour changes in cancerous congeners. If yes, were they able to detect cancer at an early developmental stage? Did it influence female preference? Did variations in volatile organic components of the odour source paralleled mice behavioural responses? We used transgenic mice strains developing or not lung cancer upon antibiotic ingestion. We sampled soiled bedding of cancerous mice (CC) and not cancerous mice (NC), at three experimental conditions: before (T0), early stage (T2) and late stage (T12) of cancer development. Habituation/generalisation and two-way preference tests were performed where soiled beddings of CC and NC mice were presented to wild-derived mice. The composition and relative concentration of volatile organic components (VOC) in the two stimuli types were analysed. Females did not show directional preference at any of the experimental conditions, suggesting that cancer did not influence their choice behaviour. Males did not discriminate between CC and NC stimuli at T0 but did so at T2 and T12, indicating that wild-derived mice could detect cancer at an early stage of development. Finally, although the VOC bouquet differed between CC and NC it did not seem to parallel the observed behavioural response suggesting that other types of odorant components might be involved in behavioural discrimination between CC and NC mice.

Summary: Male mice could discriminate the smell of cancerous congeners even when the tumour was hardly detectable by other means; however, females did not discriminate against the smell of males carrying cancerous tumours. Odorant molecules other than volatile organic compounds analysed here might explain the observed behaviour.

Does Oxidative Stress Management Help Alleviation of COVID-19 Symptoms in Patients Experiencing Diabetes?

Severe acute respiratory syndrome (SARS)-CoV-2 virus causes novel coronavirus disease 2019 (COVID-19) with other comorbidities such as diabetes. Diabetes is the most common cause of diabetic nephropathy, which is attributed to hyperglycemia. COVID-19 produces severe complications in people with diabetes mellitus. This article explains how SARS-CoV-2 causes more significant kidney damage in diabetic patients. Importantly, COVID-19 and diabetes share inflammatory pathways of disease progression. SARS-CoV-2 binding with ACE-2 causes depletion of ACE-2 (angiotensin-converting enzyme 2) from blood vessels, and subsequently, angiotensin-II interacts with angiotensin receptor-1 from vascular membranes that produce NADPH (nicotinamide adenine dinucleotide hydrogen phosphate) oxidase, oxidative stress, and constriction of blood vessels. Since diabetes and COVID-19 can create oxidative stress, we hypothesize that COVID-19 with comorbidities such as diabetes can synergistically increase oxidative stress leading to end-stage renal failure and death. Antioxidants may therefore prevent renal damage-induced death by inhibiting oxidative damage and thus can help protect people from COVID-19 related comorbidities. A few clinical trials indicated how effective the antioxidant therapy is against improving COVID-19 symptoms, based on a limited number of patients who experienced COVID-19. In this review, we tried to understand how effective antioxidants (such as vitamin D and flavonoids) can act as food supplements or therapeutics against COVID-19 with diabetes as comorbidity based on recently available clinical, preclinical, or in silico studies.

Review of the algorithms used in exhaled breath analysis for the detection of diabetes

Currently, intensive work is underway on the development of truly noninvasive medical diagnostic systems, including respiratory analysers based on the detection of biomarkers of several diseases including diabetes. In terms of diabetes, acetone is considered as a one of the potential biomarker, although is not the single one. Therefore, the selective detection is crucial. Most often, the analysers of exhaled breath are based on the utilization of several commercially available gas sensors or on specially designed and manufactured gas sensors to obtain the highest selectivity and sensitivity to diabetes biomarkers present in the exhaled air. An important part of each system are the algorithms that are trained to detect diabetes based on data obtained from sensor matrices. The prepared review of the literature showed that there are many limitations in the development of the versatile breath analyser, such as high metabolic variability between patients, but the results obtained by researchers using the algorithms described in this paper are very promising and most of them achieve over 90% accuracy in the detection of diabetes in exhaled air. This paper summarizes the results using various measurement systems, feature extraction and feature selection methods as well as algorithms such as Support Vector Machines, k-Nearest Neighbours and various variations of Neural Networks for the detection of diabetes in patient samples and simulated artificial breath samples.

Effect of chiglitazar and sitagliptin on glucose variations, insulin resistance and inflammatory-related biomarkers in untreated patients with type 2 diabetes

AIMS

To evaluate glycemic variations, changes in insulin resistance and oxidative stress after chiglitazar or sitagliptin treatment in untreated patients with type 2 diabetes mellitus (T2DM).

METHODS

Based on the study inclusion and exclusion criteria, 81 patients with T2DM were randomly divided to receive chiglitazar or sitagliptin treatment for 24 weeks. Continuous glucose monitoring (CGM) systems were conducted for 72 h in eligible patients. We analyzed the following glycemic variation parameters derived from the CGM data and measured the serum levels of hemoglobin A1c (HbA1c), fasting blood glucose (FBG), 2-h postprandial blood glucose (2-h PBG), fasting insulin (Fins) and inflammatory-related indicators at baseline and the end of the study.

RESULTS

After treatment for 24 weeks, our data showed a similar reduction in HbA1c between chiglitazar and sitagliptin. The 24-h mean blood glucose (MBG), standard deviation (SD) and mean amplitude of glycemic excursion (MAGE) were significantly decreased, and the time in range (TIR) was increased after chiglitazar and sitagliptin therapy. Chiglitazar administration led to significant improvement in insulin resistance/insulin secretion (HOMA-IR, HOMA-IS), interleukin-6 (IL-6), prostaglandin F2α (PGF-2α), 17-hydroxyprogesterone (17-OHP) and adiponectin (ADP) score values compared with sitagliptin administration.

CONCLUSIONS

Chiglitazar therapy effectively reduced glucose variation and showed a larger improvement in insulin resistance and inflammatory parameters than sitagliptin.

Plukenetia conophora seed oil ameliorates streptozotocin-induced hyperglycemia and oxidative stress in rats

PURPOSE

Plukenetia conophora (African walnut) is an edible seed, widely cultivated for its ethnomedicinal and nutritional purposes. Consumption of African walnuts has been linked with blood sugar lowering effect.

OBJECTIVE

The effects of P. conophora seed oil treatment on hyperglycemia and oxidative stress were investigated in plasma, liver and kidney of streptozotocin (STZ)-induced diabetic rats.

MATERIALS AND METHODS

Plukenetia conophora seed oil (PCO) was obtained by extraction of pulverized dried seed in n-hexane. Diabetes was induced by STZ injection (65 mg/kg, i.p). Rats were assigned into non-diabetic control and diabetic control (treated with vehicle), PCO (200 mg/kg) and pioglitazone (10 mg/kg). Fasting blood sugar (FBS) was taken from overnight fasted animals on day 7 and 14 respectively. Plasma, liver and kidney samples were obtained on day 14 for the determination of oxidative stress parameters malondialdehyde (MDA), reduced glutathione (GSH), catalase and superoxide dismutase (SOD).

RESULTS

PCO treatment significantly (p < 0.05) reduced STZ-induced hyperglycaemia by lowering the elevated FBS. PCO significantly reduced MDA level and attenuated STZ-induced depletion of GSH, catalase and SOD in the diabetic rats' plasma, liver and kidneys.

CONCLUSION

These results suggest that consumption of Plukenetia conophora seed might offer protection against diabetes-induced hepatic and renal damage.

Odors and cancer: Current status and future directions

Cancer is the second leading cause of death in the world. Because tumors detected at early stages are easier to treat, the search for biomarkers-especially non-invasive ones-that allow early detection of malignancies remains a central goal to reduce cancer mortality. Cancer, like other pathologies, often alters body odors, and much has been done by scientists over the last few decades to assess the value of volatile organic compounds (VOCs) as signatures of cancers. We present here a quantitative review of 208 studies carried out between 1984 and 2020 that explore VOCs as potential biomarkers of cancers. We analyzed the main findings of these studies, listing and classifying VOCs related to different cancer types while considering both sampling methods and analysis techniques. Considering this synthesis, we discuss several of the challenges and the most promising prospects of this research direction in the war against cancer.

PCB118 Induces Inflammation of Islet Beta Cells via Activating ROS-NLRP3 Inflammasome Signaling

Background

Diabetes mellitus is a clinical syndrome caused by genetic and environmental factors. Growing evidence suggests that exposure to environmental endocrine disruptors and activation of NLRP3 inflammasome signaling play a vital role in diabetes. However, it is unclear how PCB118, a common environmental endocrine disruptor, contributes to the incidence of diabetes, and its specific mechanism of action is unknown. In this study, we explored whether ROS-induced NLRP3 inflammasome priming and activation were related to PCB118 exposure in mouse islet β-TC-6 cells and the mechanisms of diabetes.

Methods

Mouse islet β-TC-6 cells were cultured with PCB118 as a stimulating factor and ROS inhibitor N-acetyl cysteine (NAC) as an intervention. Cellular toxicity due to PCB118 was detected using the Cell Counting Kit-8; ROS was measured using DCFH-DA; the expressions of NLRP3, procaspase-1, caspase-1, pro-IL-1β, and IL-1β protein were detected by western blot; and IL-6, IL-18, and C-C chemokine ligand 2 (CCL-2) were measured by ELISA.

Results

PCB118 caused significant toxicity to the cells when the stimulation concentration was equal to or greater than 80 nmol/L at 72 hours (p < 0.05) and increased the levels of ROS, NLRP3, caspase-1, IL-1β, IL-6, IL-18, and CCL-2 (p < 0.05); the expressions of procaspase-1 and pro-IL-1β were downregulated in a dose-dependent manner after PCB118 exposure (p < 0.05), which was prevented by pretreatment with NAC (p < 0.05).

Conclusions

PCB118 can activate NLRP3 inflammasome signaling in islet beta cells via the oxidative stress pathway and cause inflammation in islet beta cells. It suggests that environmental endocrine disruptors play an important role in the inflammation of islet beta cells and may contribute to the development of diabetes through NLRP3 inflammatory signaling.

Therapeutic Effects of Gallic Acid in Regulating Senescence and Diabetes; an In Vitro Study

Gallic acid (GA), a plant-derived ubiquitous secondary polyphenol metabolite, can be a useful dietary supplement. This in vitro study’s primary purpose was to assess the anti-aging properties of GA using rat embryonic fibroblast (REF) cells, antidiabetic effects via pancreatic islet cells, and finally, elucidating the molecular mechanisms of this natural compound. REF and islet cells were isolated from fetuses and pancreas of rats, respectively. Then, several senescence-associated molecular and biochemical parameters, along with antidiabetic markers, were investigated. GA caused a significant decrease in the β-galactosidase activity and reduced inflammatory cytokines and oxidative stress markers in REF cells. GA reduced the G0/G1 phase in senescent REF cells that led cells to G2/M. Besides, GA improved the function of the β cells. Flow cytometry and spectrophotometric analysis showed that it reduces apoptosis via inhibiting caspase-9 activity. Taken together, based on the present findings, this polyphenol metabolite at low doses regulates different pathways of senescence and diabetes through its antioxidative stress potential and modulation of mitochondrial complexes activities.

Diagnosis of ventilator-associated pneumonia using electronic nose sensor array signals: solutions to improve the application of machine learning in respiratory research

Background

Ventilator-associated pneumonia (VAP) is a significant cause of mortality in the intensive care unit. Early diagnosis of VAP is important to provide appropriate treatment and reduce mortality. Developing a noninvasive and highly accurate diagnostic method is important. The invention of electronic sensors has been applied to analyze the volatile organic compounds in breath to detect VAP using a machine learning technique. However, the process of building an algorithm is usually unclear and prevents physicians from applying the artificial intelligence technique in clinical practice. Clear processes of model building and assessing accuracy are warranted. The objective of this study was to develop a breath test for VAP with a standardized protocol for a machine learning technique.

Methods

We conducted a case-control study. This study enrolled subjects in an intensive care unit of a hospital in southern Taiwan from February 2017 to June 2019. We recruited patients with VAP as the case group and ventilated patients without pneumonia as the control group. We collected exhaled breath and analyzed the electric resistance changes of 32 sensor arrays of an electronic nose. We split the data into a set for training algorithms and a set for testing. We applied eight machine learning algorithms to build prediction models, improving model performance and providing an estimated diagnostic accuracy.

Results

A total of 33 cases and 26 controls were used in the final analysis. Using eight machine learning algorithms, the mean accuracy in the testing set was 0.81 ± 0.04, the sensitivity was 0.79 ± 0.08, the specificity was 0.83 ± 0.00, the positive predictive value was 0.85 ± 0.02, the negative predictive value was 0.77 ± 0.06, and the area under the receiver operator characteristic curves was 0.85 ± 0.04. The mean kappa value in the testing set was 0.62 ± 0.08, which suggested good agreement.

Conclusions

There was good accuracy in detecting VAP by sensor array and machine learning techniques. Artificial intelligence has the potential to assist the physician in making a clinical diagnosis. Clear protocols for data processing and the modeling procedure needed to increase generalizability.

Can oral health and oral-derived biospecimens predict progression of dementia?

Growing evidence indicates that oral health and brain health are interconnected. Declining cognition and dementia coincide with lack of self‐preservation, including oral hygiene. The oral microbiota plays an important role in maintaining oral health. Emerging evidence suggests a link between oral dysbiosis and cognitive decline in patients with Alzheimer's disease. This review showcases the recent advances connecting oral health and cognitive function during aging and the potential utility of oral‐derived biospecimens to inform on brain health. Collectively, experimental findings indicate that the connection between oral health and cognition cannot be underestimated; moreover, oral biospecimens are abundant and readily obtainable without invasive procedures, which may help inform on cognitive health.

Targeting microRNAs as a Therapeutic Strategy to Reduce Oxidative Stress in Diabetes

Diabetes mellitus is a group of heterogeneous metabolic disorders characterized by chronic hyperglycaemia as a consequence of pancreatic β cell loss and/or dysfunction, also caused by oxidative stress. The molecular mechanisms involved inβ cell dysfunction and in response to oxidative stress are also regulated by microRNAs (miRNAs). miRNAs are a class of negative gene regulators, which modulate pathologic mechanisms occurring in diabetes and its complications. Although several pharmacological therapies specifically targeting miRNAs have already been developed and brought to the clinic, most previous miRNA-based drug delivery methods were unable to target a specific miRNA in a single cell type or tissue, leading to important off-target effects. In order to overcome these issues, aptamers and nanoparticles have been described as non-cytotoxic vehicles for miRNA-based drug delivery. These approaches could represent an innovative way to specifically target and modulate miRNAs involved in oxidative stress in diabetes and its complications. Therefore, the aims of this review are: (i) to report the role of miRNAs involved in oxidative stress in diabetes as promising therapeutic targets; (ii) to shed light onto the new delivery strategies developed to modulate the expression of miRNAs in diseases.

Exhaled volatile substances in children suffering from type 1 diabetes mellitus: results from a cross-sectional study

Monitoring metabolic adaptation to type 1 diabetes mellitus in children is challenging. Analysis of volatile organic compounds (VOCs) in exhaled breath is non-invasive and appears as a promising tool. However, data on breath VOC profiles in pediatric patients are limited. We conducted a cross-sectional study and applied quantitative analysis of exhaled VOCs in children suffering from type 1 diabetes mellitus (T1DM) (n = 53) and healthy controls (n = 60). Both groups were matched for sex and age. For breath gas analysis, a very sensitive direct mass spectrometric technique (PTR-TOF) was applied. The duration of disease, the mode of insulin application (continuous subcutaneous insulin infusion vs. multiple daily insulin injection) and long-term metabolic control were considered as classifiers in patients. The concentration of exhaled VOCs differed between T1DM patients and healthy children. In particular, T1DM patients exhaled significantly higher amounts of ethanol, isopropanol, dimethylsulfid, isoprene and pentanal compared to healthy controls (171, 1223, 19.6, 112 and 13.5 ppbV vs. 82.4, 784, 11.3, 49.6, and 5.30 ppbV). The most remarkable differences in concentrations were found in patients with poor metabolic control, i.e. those with a mean HbA1c above 8%. In conclusion, non-invasive breath testing may support the discovery of basic metabolic mechanisms and adaptation early in the progress of T1DM.

Antidiabetic and antioxidative properties of the hydro-methanolic extract (60:40) of rhizomes of Curcuma amada roxb. (Zingiberaceae) in streptozotocin-induced diabetic male albino rat: a dose-dependent study through biochemical and genomic approaches

Background Curcuma amada is the most popular traditional medicine in India for the treatment of diabetes. The present study aimed to focus the antidiabetic and antioxidative activity of C. amada through the analysis of biochemical and genomic levels in a dose-dependent manner in streptozotocin-induced male adult rat. Method Streptozotocin-induced diabetic rats were administered orally with hydro-methanolic extract of C. amada at the dose of 10, 20, 40 and 80 mg/100 g body weight of rats for 28 days. The antidiabetic and antioxidative efficacy of the extract on glycemic, enzymatic, genomic and histological sensors along with toxicity study was investigated. Results The result showed a significant antidiabetic and antioxidative effect of the extract at dose-dependent manner. The significant recovery of fasting blood glucose level, serum insulin, activity of carbohydrate metabolic enzymes and antioxidative enzymes in extract-treated diabetic group as compared to untreated diabetic group were noted. After the extract treatment, the size of pancreatic islet and cell population densities were significantly increased. Activities of glutamate oxaloacetate transaminase and glutamate pyruvate transaminase in liver were significantly recovered along with the correction of Bax and Bcl-2 gene expression in hepatic tissue after the extract treatment in diabetic rats in respect to untreated diabetic group. Out of all the doses, the significant effects were noted at the dose of 20 mg/100 g body weight which has been considered as threshold dose in the concern. Conclusion It may be concluded that the significant and corrective effect in most of the sensors was noted at the minimum dose of 20 mg/100 g body weight of hydro-methanolic extract of C. amada without producing any toxicity.

The Use of Selected Ion Flow Tube-Mass Spectrometry Technology to Identify Breath Volatile Organic Compounds for the Detection of Head and Neck Squamous Cell Carcinoma: A Pilot Study

Background: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common form of cancer worldwide, with approximately 630,000 new cases diagnosed each year. The development of low-cost and non-invasive tools for the detection of HNSCC using volatile organic compounds (VOCs) in the breath could potentially improve patient care. The aim of this study was to investigate the feasibility of selected ion flow tube mass spectrometry (SIFT-MS) technology to identify breath VOCs for the detection of HNSCC. Materials and Methods: Breath samples were obtained from HNSCC patients (N = 23) and healthy volunteers (N = 21). Exhaled alveolar breath samples were collected into FlexFoil^® PLUS (SKC Limited, Dorset, UK) sampling bags from newly diagnosed, histologically confirmed, untreated patients with HNSCC and from non-cancer participants. Breath samples were analyzed by Selected Ion Flow Tube-Mass Spectrometry (SIFT-MS) (Syft Technologies, Christchurch, New Zealand) using Selective Ion Mode (SIM) scans that probed for 91 specific VOCs that had been previously reported as breath biomarkers of HNSCC and other malignancies. Results: Of the 91 compounds analyzed, the median concentration of hydrogen cyanide (HCN) was significantly higher in the HNSCC group (2.5 ppb, 1.6–4.4) compared to the non-cancer group (1.1 ppb, 0.9–1.3; Benjamini–Hochberg adjusted p < 0.05). A receiver operating curve (ROC) analysis showed an area under the curve (AUC) of 0.801 (95% CI, 0.65952–0.94296), suggesting moderate accuracy of HCN in distinguishing HNSCC from non-cancer individuals. There were no statistically significant differences in the concentrations of the other compounds of interest that were analyzed. Conclusions: This pilot study demonstrated the feasibility of SIFT-MS technology to identify VOCs for the detection of HNSCC.

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

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

Glycation profile of minor abundant erythrocyte proteome across varying glycemic index in diabetes mellitus

PURPOSE

Long-term glycemic index in patients with diabetes mellitus (DM) is measured by glycated hemoglobin (HbA_1c) besides blood glucose. In DM, the primary amino groups of proteins get glycated via non-enzymatic post-translational modification. This study aims at identifying and characterizing site-specific glycation of erythrocyte proteome across varying glycemic index in patients with DM.

EXPERIMENTS

We isolated the glycated erythrocyte proteome devoid of hemoglobin from control and diabetic samples using boronate affinity chromatography. Proteomic analysis was performed using nanoLC/ESI-MS proteomics platform. The site-specific modification on different proteins was deciphered using a customized database.

RESULTS

We report 37 glycated proteins identified and characterized from samples with HbA_1c of 6%, 8%, 12%, and 16%. Our results show that both extent and site-specific modification of proteins increased with increasing HbA_1c. The observed residue-specific modifications of catalase, peroxiredoxin, carbonic anhydrase, lactate dehydrogenase B and delta-aminolevulinic acid dehydratase were correlated with the literature report on their functional disorder in DM.

CONCLUSIONS

and clinical relevance: 37 glycated erythrocyte proteins apart from hemoglobin were characterized from DM patient samples with varying HbA_1c values. We correlated the site-specific glycation and associated functional disorder of five representative proteins. However, the clinical correlation with the observed modifications needs further investigation.

Therapeutic effects of ethanolic extract from the green cocoon shell of silkworm Bombyx mori on type 2 diabetic mice and its hypoglycaemic mechanism

Diabetes mellitus is a clinically complex disease characterized by hyperglycaemia with disturbances in carbohydrate, fat and protein metabolism. The aim of this study was to determine the therapeutic effect of ethanolic extract (EE) from the green cocoon sericin layer of silkworm Bombyx mori on mice with type 2 diabetes mellitus (T2DM) and its hypoglycaemic mechanisms. The results showed that oral EE for 7 weeks had significant ameliorative effects on all the biochemical parameters studied in vivo. The levels of oral glucose tolerance and insulin tolerance were significantly improved. The hypoglycaemic rate in the 350 mg kg^-1 high dosage group was 39.38%. The levels of nuclear factor kappa B (NFκB), interleukin 6 (IL-6) and tumour necrosis factor alpha (TNF-α) in the high dosage EE-treated group were significantly reduced, while activities of antioxidant enzymes superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) were obviously increased. The islet area and the number of insulin-positive beta cells increased significantly in the high dose group. Furthermore, expression levels of insulin receptor (IR), insulin receptor substrate (IRS), phosphatidylinositide 3-kinase (PI3K), p-Akt and phospho-glycogen synthase kinase-3β (p-GSK3β) involved in insulin signalling were increased. Adenosine 5'-monophosphate-activated protein kinase (AMPK) and glucose transporter 4 (GLUT4) also were activated to regulate glucose metabolism in EE-treated groups. The levels of glucose 6-phosphatase (G6pase) and phosphoenolpyruvate carboxykinase (PEPCK) decreased, while the glucokinase (GK) level increased to promote glycolysis. The results clearly indicated that oral EE, especially at a high dose, could improve the glucose metabolism of T2DM by reducing inflammatory reactions, enhancing the antioxidant capacity and insulin sensitivity, and regulating the balance between glycolysis and gluconeogenesis, which means that EE has potential ameliorative effects on T2DM mice.

Exhaled breath testing - A tool for the clinician and researcher

Exhaled breath is a robust matrix of biomarkers divided between three fractions - gaseous breath, volatile breath, and breath condensate. Breath is collected non-invasively through bags (for gaseous breath), cold condensation chambers (breath condensate), and adsorbent traps (volatile breath). Due to the incredibly dilute nature of breath matrices, breath biomarker analysis requires precise analytical techniques, highly sensitive technology and often challenges the limit of detection of even the most advanced assays. Interest and advances in breath collection, analysis, and use have increased in recent years largely due to advances in analytical technology. Approved and validated breath tests are available as tools for researchers and clinicians. Novel development is ongoing. This article reviews the current applications for exhaled breath biomarkers.

Influence of Water Molecules on the Detection of Volatile Organic Compounds (VOC) Cancer Biomarkers by Nanocomposite Quantum Resistive Vapor Sensors vQRS

The anticipated diagnosis of various fatal diseases from the analysis of volatile organic compounds (VOC) biomarkers of the volatolome is the object of very dynamic research. Nanocomposite-based quantum resistive vapor sensors (vQRS) exhibit strong advantages in the detection of biomarkers, as they can operate at room temperature with low consumption and sub ppm (part per million) sensitivity. However, to meet this application they need to detect some ppm or less amounts of biomarkers in patients' breath, skin, or urine in complex blends of numerous VOC, most of the time hindered by a huge amount of water molecules. Therefore, it is crucial to analyze the effects of moisture on the chemo-resistive sensing behavior of carbon nanotubes based vQRS. We show that in the presence of water molecules, the sensors cannot detect the right amount of VOC molecules present in their environment. These perturbations of the detection mechanism are found to depend on the chemical interactions between water and other VOC molecules, but also on their competitive absorption on sensors receptive sites, located at the nanojunctions of the conductive architecture. This complex phenomenon studied with down to 12.5 ppm of acetone, ethanol, butanone, toluene, and cyclohexane mixed with 100 ppm of water was worth to investigate in the prospect of future developments of devices analysing real breath samples in which water can reach a concentration of 6%.

Nrf2, a novel molecular target to reduce type 1 diabetes associated secondary complications: The basic considerations

Oxidative stress and inflammation are the mediators of diabetes and related secondary complications. Oxidative stress arises because of the excessive production of reactive oxygen species and diminished antioxidant production due to impaired Nrf2 activation, the master regulator of endogenous antioxidant. It has been established from various animal models that the transcription factor Nrf2 provides cytoprotection, ameliorates oxidative stress, inflammation and delays the progression of diabetes and its associated complications. Whereas, deletion of the transcription factor Nrf2 amplifies tissue level pathogenic alterations. In addition, Nrf2 also regulates the expression of numerous cellular defensive genes and protects against oxidative stress-mediated injuries in diabetes. The present review provides an overview on the role of Nrf2 in type 1 diabetes and explores if it could be a potential target for the treatment of diabetes and related complications. Further, the rationality of different agent's intervention has been discussed to mitigate organ damages induced by diabetes.

Oxidative stress, eryptosis and anemia: a pivotal mechanistic nexus in systemic diseases

The average lifespan of circulating erythrocytes usually exceeds hundred days. Prior to that, however, erythrocytes may be exposed to oxidative stress in the circulation which could cause injury and trigger their suicidal death or eryptosis. Oxidative stress activates Ca²⁺ -permeable nonselective cation channels in the cell membrane, thus, stimulating Ca²⁺ entry and subsequent cell membrane scrambling resulting in phosphatidylserine exposure and activation of Ca²⁺ -sensitive K⁺ channels leading to K⁺ exit, hyperpolarization, Cl^- exit, and ultimately cell shrinkage due to loss of KCl and osmotically driven water. While the mechanistic link between oxidative stress and anemia remains ill-defined, several diseases such as diabetes, hepatic failure, malignancy, chronic kidney disease and inflammation have been identified to display both increased oxidative stress as well as eryptosis. Recent compelling evidence suggests that oxidative stress is an important perpetrator in accelerating erythrocyte loss in different systemic conditions and an underlying mechanism for anemia associated with these pathological states. In the present review, we discuss the role of oxidative stress in reducing erythrocyte survival and provide novel insights into the possible use of antioxidants as putative antieryptotic and antianemic agents in a variety of systemic diseases.

Metabolomics applied to the discovery of tuberculosis and diabetes mellitus biomarkers

Tuberculosis (TB) and diabetes mellitus Type 2 (DM2) are two diseases as ancient as they are harmful to human health. The outcome for both diseases in part depends on immune and metabolic individual responses. DM2 is increasing yearly, mainly due to environmental, genetic and lifestyle habits. There are multiple evidence that DM2 is one of the most important risk factor of becoming infected with TB or reactivating latent TB. Mass spectrometry-based metabolomics is an important tool for elucidating the metabolites and metabolic pathways that influence the immune responses to M. tuberculosis infection during diabetes. We provide an up-to-date review highlighting the importance and benefit of metabolomics for identifying biomarkers as candidate molecules for diagnosis, disease activity or prognosis.

Diagnostic accuracy of breath tests for pneumoconiosis using an electronic nose

Breath analyses have attracted substantial attention as screens for occupational environmental lung disease. The objective of this study was to develop breath tests for pneumoconiosis by analysing volatile organic compounds using an electronic nose. A case-control study was designed. We screened 102 subjects from a cohort of stone workers. After excluding three subjects with poorly controlled diabetes mellitus and one subject with asthma, 98 subjects were enrolled, including 34 subjects with pneumoconiosis and 64 healthy controls. We analysed the subjects' breath using an electronic nose with 32 nanocomposite sensors. Data were randomly split into 80% for model building and 20% for validation. Using a linear discriminate analysis, the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUROC) were 67.9%, 88.0%, 80.8%, and 0.91, respectively, in the training set and 66.7%, 71.4%, 70.0%, and 0.86, respectively, in the test set. In subgroup analysis divided by smoking status, the AUROCs for current smokers, former smokers, and subjects who never smoked were 0.94, 0.93, and 0.99, respectively. In subgroup analysis divided by gender, the AUROCs for males and females were 0.95 and 0.99, respectively. Breath tests may have potential as a screen for pneumoconiosis. A multi-centre study is warranted, and the procedures must be standardized before clinical application.

A Prediction Model with a Combination of Variables for Diagnosis of Lung Cancer

Background

Multivariate models with a combination of variables can predict disease more accurately than a single variable employed alone. We developed a logistic regression model with a combination of variables and evaluated its ability to predict lung cancer.

Material/Methods

The exhaled breath from 57 patients with lung cancer and 72 healthy controls without cancer was collected. The VOCs of exhaled breath were examined qualitatively and quantitatively by a novel electronic nose (Z-nose4200 equipment). The VOCs in the 2 groups were compared using the Mann-Whitney U test, and the baseline data were compared between the 2 groups using the chi-square test or ANOVA. Variables from VOCs and baseline data were selected by stepwise logistic regression and subjected to a prediction model for the diagnosis of lung cancer as combined factors. The receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of this prediction model.

Results

Nine VOCs in exhaled breath of lung cancer patients differed significantly from those of healthy controls. Four variables – age, hexane, 2,2,4,6,6-pentamethylheptane, and 1,2,6-trimethylnaphthalene – were entered into the prediction model, which could effectively separate the lung cancer samples from the control samples with an accuracy of 82.8%, a sensitivity of 76.0%, and a specificity of 94.0%.

Conclusions

The profile of VOCs in exhaled breath contained distinguishable biomarkers in the patients with lung cancers. The prediction model with 4 variables appears to provide a new technique for lung cancer detection.

Development of breath test for pneumoconiosis: a case-control study

Background

Lipid peroxidation plays an important role in the pathogenesis of pneumoconiosis. Volatile organic compounds (VOCs) generated from lipid peroxidation might be used to detect pneumoconiosis. The objective of this study was to develop a breath test for pneumoconiosis.

Methods

A case-control study was designed. Breath and ambient air were analysed by gas chromatography/mass spectrometry. After blank correction to prevent contamination from ambient air, we used canonical discriminant analysis (CDA) to assess the discrimination accuracy and principal component analysis (PCA) to generate a prediction score. The prediction accuracy was calculated and validated using the International Classification of Radiographs of the Pneumoconiosis criteria combined with an abnormal pulmonary function test as a reference standard. We generated a receiver operator characteristic (ROC) curve and calculated the area under the ROC curve (AUC) to estimate the screening accuracy of the breath test.

Results

We enrolled 200 stone workers. After excluding 5 subjects with asthma and 16 subjects who took steroids or nonsteroidal anti-inflammatory drugs, a total of 179 subjects were used in the final analyses, which included 25 cases and 154 controls. By CDA, 88.8% of subjects were correctly discriminated by their exposure status and the presence of pneumoconiosis. After excluding the VOCs of automobile exhaust and cigarette smoking, pentane and C5-C7 methylated alkanes constituted the major VOCs in the breath of persons with pneumoconiosis. Using the prediction score generated from PCA, the ROC-AUC was 0.88 (95% CI = 0.80—0.95), and the mean ROC-AUC of 5-fold cross-validation was 0.90. The breath test had good accuracy for pneumoconiosis diagnosis.

Conclusion

The analysis of breath VOCs has potential in the screening of pneumoconiosis for its non-invasiveness and high accuracy. We suggest that a multi-centre study is warranted and that all procedures must be standardized before clinical application.

Screening of Obstructive Sleep Apnea Syndrome by Electronic-Nose Analysis of Volatile Organic Compounds

Obstructive Sleep Apnea Syndrome (OSAS) carries important social and economic implications. Once the suspicion of OSAS has arisen, Polysomnography (PSG) represents the diagnostic gold standard. However, about 45% of people who have undergone PSG are free from OSAS. Thus, efforts should be made to improve the selection of subjects. We verified whether the pattern of Volatile Organic Compounds (VOCs) helps to select patients amenable to PSG. We studied 136 subjects (20 obese non-OSAS, 20 hypoxic OSAS, 20 non-hypoxic OSAS, and 20 non-hypoxic Chronic Obstructive Pulmonary Disease (COPD) vs 56 healthy controls) without any criteria of exclusion for comorbidity to deal with a real-life population. VOCs patterns were analyzed using electronic-nose (e-nose) technology. A Discriminant Analysis (Partial Least Square-Discriminant Analysis) was performed to predict respiratory functions and PSG parameters. E-nose distinguished controls (100% correct classification) from others and identified 60% of hypoxic, and 35% of non-hypoxic OSAS patients. Similarly, it identified 60% of COPD patients. One-by-one group comparison yielded optimal discrimination of OSAS vs controls and of COPD vs controls (100% correct classification). In conclusion, e-nose technology applied to breath-analysis can discriminate non-respiratory from respiratory diseased populations in real-life multimorbid populations and exclude OSAS. If confirmed, this evidence may become pivotal for screening purposes.

Inflammatory bowel disease and patterns of volatile organic compounds in the exhaled breath of children: A case-control study using Ion Molecule Reaction-Mass Spectrometry

Inflammatory bowel diseases (IBD) profoundly affect quality of life and have been gradually increasing in incidence, prevalence and severity in many areas of the world, and in children in particular. Patients with suspected IBD require careful history and clinical examination, while definitive diagnosis relies on endoscopic and histological findings. The aim of the present study was to investigate whether the alveolar air of pediatric patients with IBD presents a specific volatile organic compounds’ (VOCs) pattern when compared to controls. Patients 10–17 years of age, were divided into four groups: Crohn’s disease (CD), ulcerative colitis (UC), controls with gastrointestinal symptomatology, and surgical controls with no evidence of gastrointestinal problems. Alveolar breath was analyzed by ion molecule reaction mass spectrometry. Four models were built starting from 81 molecules plus the age of subjects as independent variables, adopting a penalizing LASSO logistic regression approach: 1) IBDs vs. controls, finally based on 18 VOCs plus age (sensitivity = 95%, specificity = 69%, AUC = 0.925); 2) CD vs. UC, finally based on 13 VOCs plus age (sensitivity = 94%, specificity = 76%, AUC = 0.934); 3) IBDs vs. gastroenterological controls, finally based on 15 VOCs plus age (sensitivity = 94%, specificity = 65%, AUC = 0.918); 4) IBDs vs. controls, built starting from the 21 directly or indirectly calibrated molecules only, and finally based on 12 VOCs plus age (sensitivity = 94%, specificity = 71%, AUC = 0.888). The molecules identified by the models were carefully studied in relation to the concerned outcomes. This study, with the creation of models based on VOCs profiles, precise instrumentation and advanced statistical methods, can contribute to the development of new non–invasive, fast and relatively inexpensive diagnostic tools, with high sensitivity and specificity. It also represents a crucial step towards gaining further insights on the etiology of IBD through the analysis of specific molecules which are the expression of the particular metabolism that characterizes these patients.

Estimation of clinical parameters of chronic kidney disease by exhaled breath full-scan mass spectrometry data and iterative PCA with intensity screening algorithm

Breath mass spectrometry is a useful tool for identifying important compounds associated with health. However, there have been few studies that have explored human exhaled breath by full-scan mass spectrometry as a non-invasive method for medical diagnosis, which may be attributed to the difficulties resulting from multicollinearity and small sample sizes relative to a large number of product ions. In this study, breath samples from 54 chronic kidney disease patients were analyzed by selected ion flow tube mass spectrometry in the full-scan mode. With the signal intensities of product ions, we developed a novel and robust algorithm, iterative PCA with intensity screening (IPS), to build linear models for estimating important clinical parameters of chronic kidney disease. It has been shown that IPS provided good estimations in cross-validated samples, and furthermore the identified product ions could have direct medical relevance to the disease. The study demonstrated the potential of quantitative breath analysis using mass spectrometry for medical diagnosis, and the importance of applying appropriate statistical tools to unveil the rich information in this type of data.

Molecular mechanisms of ROS production and oxidative stress in diabetes

Oxidative stress and chronic inflammation are known to be associated with the development of metabolic diseases, including diabetes. Oxidative stress, an imbalance between oxidative and antioxidative systems of cells and tissues, is a result of over production of oxidative-free radicals and associated reactive oxygen species (ROS). One outcome of excessive levels of ROS is the modification of the structure and function of cellular proteins and lipids, leading to cellular dysfunction including impaired energy metabolism, altered cell signalling and cell cycle control, impaired cell transport mechanisms and overall dysfunctional biological activity, immune activation and inflammation. Nutritional stress, such as that caused by excess high-fat and/or carbohydrate diets, promotes oxidative stress as evident by increased lipid peroxidation products, protein carbonylation and decreased antioxidant status. In obesity, chronic oxidative stress and associated inflammation are the underlying factors that lead to the development of pathologies such as insulin resistance, dysregulated pathways of metabolism, diabetes and cardiovascular disease through impaired signalling and metabolism resulting in dysfunction to insulin secretion, insulin action and immune responses. However, exercise may counter excessive levels of oxidative stress and thus improve metabolic and inflammatory outcomes. In the present article, we review the cellular and molecular origins and significance of ROS production, the molecular targets and responses describing how oxidative stress affects cell function including mechanisms of insulin secretion and action, from the point of view of possible application of novel diabetic therapies based on redox regulation.

Analyzing breath samples of hypoglycemic events in type 1 diabetes patients: towards developing an alternative to diabetes alert dogs

Diabetes is a disease that involves dysregulation of metabolic processes. Patients with type 1 diabetes (T1D) require insulin injections and measured food intake to maintain clinical stability, manually tracking their results by measuring blood glucose levels. Low blood glucose levels, hypoglycemia, can be extremely dangerous and can result in seizures, coma, or even death. Canines trained as diabetes alert dogs (DADs) have demonstrated the ability to detect hypoglycemia from breath, which led us to hypothesize that hypoglycemia, a metabolic dysregulation leading to low blood glucose levels, could be identified through analyzing volatile organic compounds (VOCs) contained within breath. We hoped to replicate the canines' detection ability and success by analytically using gas chromatography/mass spectrometry of VOCs in 128 breath samples collected from 52 youths with T1D at two different diabetes camps. We used different tests for significance including Ranksum, Student's T-test, and difference between means, and found a subset of 56 traces of potential metabolites. Principle component and linear discriminant analysis (LDA) confirmed a hypoglycemic signature likely resides within this group. Supervised machine learning combined with LDA narrowed the list of likely components to seven. The technique of leave one out cross validation demonstrated the model thus developed has a sensitivity of 91% (95% confidence interval (CI) [57.1, 94.7]) and a specificity of 84% (95% CI [73.0, 92.7]) at identifying hypoglycemia. Confidence intervals were obtained by bootstrapping. These results demonstrate that it is possible to differentiate breath samples obtained during hypoglycemic events from all other breath samples by analytical means and could lead to developing a simple analytical monitoring device as an alternative to using DADs.