The authors investigate whether WGW and WGR improve gut health in different ways compared to RW, with the primary outcomes of microbiota composition and gastrointestinal (GI) symptoms
70 healthy adults (in means 6 SDs; aged 51.0–69.4 y, body mass index (BMI (in kg/m2)) 27.8–61.9, 32 : 38 men : women)
Healthy adults replaced cereal foods from their habitual diet with WGR, WGW, or RW; before and after a 6-wk intervention, the stool sample was collected and analyzed for short-chain fatty acids and microbiota composition use of 16S ribosomal RNA gene-targeted high-throughput amplicon sequencing
6-week intervention
Intakes of whole grains were 145.2 6 75.9, 124.2 6 57.3, and 5.4 6 3.2 g/d in the WGW, WGR, and RW groups, respectively. Gut microbiota composition was not affected by diet. The relative change in fecal butyrate decreased in the RW (238%) group compared to the WGW (25%, ) and WGR groups (21%, ). Other short-chain fatty acids were unaffected.
The aim was to examine the potential of exhaled breath analysis to study the metabolic effects of DF
7 men
Alveolar exhaled breath samples were analyzed at fasting state and 30, 60, and 120 minutes after this meal parallel to plasma glucose, insulin, and serum lipids; we used solid-phase microextraction and gas chromatography-mass spectrometry for detecting changes in 15 VOCs
30, 60, and 120 minutes after this meal
Exhaled breath 2-methylbutyric acid in the fasting state and 1-propanol at 120 minutes decreased ( for both) after an HFD. Ingestion of the test meal increased ethanol, 1-propanol, acetoin, propionic acid, and butyric acid levels while reducing acetone, 1-butanol, diacetyl, and phenol levels. Both DF diet content and having a single meal affected breath VOCs.
Follow volatile organic compounds excreted in exhaled breath of individuals while adhering to a gluten-free diet for 4 weeks prior to adherence to a normal diet
20 participants without any known food intolerance (female: 12, male: 9, age 16–61 years (average 36 years), BMI 18.9–35.3 (average 24)
TD-GC-tof-MS in combination with chemometric analysis to detect an array of VOCs in exhaled breath; dietary intake was assessed to verify adherence to the diet and to get insight into macronutrient intake during the intervention period
4 weeks
The study shows that the composition of VOCs in exhaled breath changes as a result of a dietary intervention, a gluten-free diet. The paper share a new potential use of exhaled air analysis and might become a useful tool in fields of nutrition and metabolism.
The aim of this study was to evaluate the VOCs profile in the urine
21 OW/Ob (10 females and 11 males, age 12.4 ± 1.2 years, BMI 26.7 ± 4.2 kg/m2) and 28 NW (16 females and 12 males, age 12.9 ± 1.5 years, BMI 19.5 ± 1.8 kg/m2)
Urine samples were analyzed by SPME-GC-MS under both acidic and alkaline conditions, in order to profile a wider range of urinary volatiles with different physicochemical properties; multivariate statistics techniques were applied to bioanalytical data to visualize clusters of cases and detect the VOCs able to differentiate OW/Ob from NW children
6 years
Results suggest that VOCs signatures differ between OW/Ob and NW children; the levels of 2-pentanone, 3-hexanone, 5-methyl-3-hexanone, 4-methyl-2-heptanone, 3-octanone, 2,4,4-trimethyl-1-pentanol, 1-hexanol, 2-hexanol, 1-heptanol, dimethyl sulfone, 2,4,6-trimethyl-pyridine, and formamide N,N-dibutyl are higher in the urine of OW/Ob children than in NW. In contrast, 1 H pyrrole-2-methyl and 1-methyl-2-piperidone have a lower concentration in OW/Ob children compared to NW.
This work describes a quantitative high-throughput analytical method for the simultaneous measurement of small aliphatic nitrogenous biomarkers, in human urine
Human urine
The authors report on the development of (UPLC-ESI-MS/MS) method for the simultaneous measurement of these biomarkers in human urine; chromatographic separation was optimized using heptafluorobutyric acid- (HFBA-) based mobile phase and a reversed-phase C18 column
This method can be implemented to assess human exposure to HDI, IPDI, BMAA, and carnitine/choline in population-based studies, such as the nationalHealth and nutritional examination survey (NHANES) as well as other clinical studies that desire noninvasive urine sampling.
The objective of this study was to investigate changes in volatile organic compounds (VOCs) in exhaled breath in overweight/obese children compared to their lean counterparts
Overweight and obese children between the ages of 6 to 18 years were recruited as healthy controls (6–18 years of age)
The exhaled breath samples gas analysis was performed by SIFT-MS on a VOICE200® SIFT-MS instrument
Compared to the lean group, the obese group was significantly older (14.1 ± 2.8 vs. 12.1 ± 3.0 years), taller (164.8 ± 10.9 vs. 153.3 ± 17.1 cm), and more likely to be caucasian (60% vs. 35.2%); for all. A comparison of the SIFT-MS results of the obese group to the lean group revealed differences in concentration of more than 50 compounds. A panel of four VOCs can identify the presence of overweight/obesity with excellent accuracy. Further analysis revealed that breath isoprene, 1- decene, 1-octene, ammonia, and hydrogen sulphide were significantly higher in the obese group compared to lean group ( value < 0.01 for all). Obese children have a unique pattern of exhaled VOCs.
The authors describe the development and validation of methods for collecting, storing, and analyzing 36 volatile organic compounds (VOCs) in breast milk to assess VOC exposure of lactating women and nursing infants
Aliquots (3 mL) of breast milk collected from 12 women at 30 days postpartum
Milk was collected by one of three methods: 1, Manual expression directly into a vacutainer;2, manual expression into a 30 mL glass jar then immediate transfer into a vacutainer; 3, Breast-pump (Hollister, Inc., Libertyville, IL) expression then immediate transfer into a vacutainer; the method used in this study was SPME-GC-MS
10 weeks
Analysis of 12 breast-milk specimens revealed varying levels of 36 different analytes; using the methods described in this paper, a broad range of VOCs can be accurately quantified in human milk.
Clinical activity index, blood, fecal, and breath samples were collected at each out-patient visit;non-UC colitis was confirmed by stool culture or radiological evaluation;breath samples were analyzed by gas chromatography time-of-flight mass spectrometry and kernel-based method to identify discriminating VOCs
15 months
Eleven VOCs predicted active vs. Inactive UC in an independent internal validation set with 92% sensitivity and 77% specificity (AUC 0.94). Non-UC colitis patients could be clearly separated from active and inactive UC patients with principal component analysis.
The aim of this work was to define the volatiles emitted from the feces of healthy donors and patients with gastrointestinal disease
30 asymptomatic donors (aged 20–65 y, 15 male), 10 asymptomatic donors (aged 23–65 y, 5 male with ulcerative colitis (n 18)
Volatiles from feces were collected by solid-phase microextraction and analyzed by gas chromatography/mass spectrometry
Analyses were undertaken within 7 d of freezing
In the cohort study, 297 volatiles were identified. In all samples, ethanoic, butanoic, pentanoic acids, benzaldehyde, ethanal, carbon disulfide, dimethyldisulfide, acetone, 2-butanone, 2,3-butanedione, 6-methyl-5-hepten- 2-one, indole, and 4-methylphenol were found. Forty-four compounds were shared by 80% of subjects. In the longitudinal study, 292 volatiles were identified, with some inter- and intrasubject variations in VOC concentrations with time. When compared to healthy donors, Volatile patterns from feces of patients with ulcerative colitis, C. difficile, and C. jejuni were each significantly different.
The aim of this study was utilize gas chromatography/mass spectrometry (GS/MS) and multivariate analysis to compare the VOCs in blood samples from individuals in a healthy physiological state with the VOCs in blood samples from CRC patients in a phathological state thereby allowing for the identification of CRC specific VOCs in the blood
16 colorectal cancer patients and 20 healthy controls
SPME/GS-MS was used to analysis the exhaled VOCs; the statistical methods principal component analysis (PCA) and partial least-squares discriminant analysis (PLSDA) were performed to deal with the final data
Three metabolic biomarkers were found at significantly lower levels in the group of CRC patients than in the normal control group (): Phenyl methylcarbamate, ethylhexanol, and 6-t-butyl-2,2,9,9-tetramethyl-3,5- decadien-7-yne. In addition, significantly higher levels of 1,1,4,4-tetramethyl-2,5-dimethylene-cyclohexane were found in the group of CRC patients than in the normal control group (). Compared with healthy individuals, patients with colorectal adenocarcinoma exhibited a distinct blood metabolic profile with respect to VOCs.
The objective was to assess the reproducibility of VOCs in gastric cancer (GC) and the effects of conditions modifying gut microbiome on the test results
Ten patients with GC; 17 patients before and after H. pylori eradication therapy; 61 patients before and after bowel cleansing
The samples were analyzed by (1) gas chromatography linked to mass spectrometry (GC-MS), applying the nonparametricWilcoxon test (level of significance ); (2) by cross-reactive nanoarrays combined with pattern recognition
Was sampled for volatile markers for three consecutive days
Exhaled VOCs profiles were stable for GC patients over a three-day period. Alpha pinene m () and ethyl acetate () increased after the antibiotic containing eradication regimen; acetone () increased following bowel cleansing prior to colonoscopy.
The present study assessed whether exhaled breath analysis using selected ion flow tube Mass spectrometry could distinguish esophageal and gastric adenocarcinoma from noncancer controls
81 patients with esophageal (N = 48) or gastric adenocarcinoma (N = 33) and 129 controls including Barrett’s metaplasia (N = 16), benign upper gastrointestinal diseases (N = 62), or a normal upper gastrointestinal tract (N = 51)
Flow tube Mass spectrmetry instrument was used for analysis of volatile organic compounds (VOCs) within exhaled breath samples; all study participants had undergone upper gastrointestinal endoscopy on the day of breath sampling
2 years
12 VOCs—pentanoic acid, hexanoic acid, phenol, methyl phenol, ethyl phenol, butanal, pentanal, hexanal, heptanal, octanal, nonanal, and decanal—were present at significantly higher concentrations () in the cancer groups than in the noncancer controls. Distinct exhaled breath VOC profiles can distinguish patients with esophageal and gastric adenocarcinoma from noncancer controls.
Prospective observational study designed in two phases.
The aim of the initial trial phase was to identify and select VOCs of interest and to set up a VOC pattern potentially capable of discriminating between patients with colorectal cancer and normal controls using an appropriate statistical model; the aim of the subsequent validation phase was prospectively to validate the model in a blinded fashion on a further series of patients and healthy controls; these subjects were not included in the previous phase
The patients with colorectal cancer had histologically proven disease and were admitted to the surgicalDepartment; healthy controls were chosen from patients undergoing screening colonoscopy and found to be disease-free
Exhaled breath was collected in an inert bag from patients with colorectal cancer and healthy controls (negative at colonoscopy) and processed offline by thermal-desorber gas chromatography-mass spectrometry to evaluate the VOC profile; during the trial phase, VOCs of interest were identified and selected, and VOC patterns able to discriminate patients from controlswere set up; in the validation phase, their discriminant performance was tested on blinded samples; a Probabilistic neural network (PNN) was used to identify the pattern of VOCs
6 months
Application of a PNN to a pattern of 15 compounds showed a discriminant performance with a sensitivity of 86 per cent, a Specificity of 83 per cent and an accuracy of 85 per cent (area under the receiver operating characteristic (ROC) curve 0·852). The accuracy of PNN analysis was confirmed in the validation phase on a further 25 subjects; the model correctly assigned 19 patients, giving an overall accuracy of 76 per cent.
Summarizes the recent progress made in noninvasive monitoring of volatile compounds in exhaled breath and above biological liquids, as they are becoming increasingly important in assessing the nutritional and clinical status and beginning to provide support to conventional clinical diagnostics and therapy
The significance of the following breath gases and their concentrations are reported: acetone and the influence of diet; ammonia confirmed as an indicator of dialysis efficacy; hydrogen and the 13CO2/12CO2 ratio (following the ingestion of 13C-labeled compounds) as related to gastric emptying and bowel transit times; hydrogen cyanide released by Pseudomonas and its detection in breath of children with cystic fibrosis; and multiple trace compounds in breath of patients with specific pathophysiological conditions and ‘metabolic profiling.
Compendium of all the volatile organic compounds (VOCs) emanating from the human (the volatolome) is for the first time reported
1840 VOCs have been assigned from breath (872), saliva (359), blood (154), milk (256), skin secretions (532) urine (279), and feces (381)
The authors’ intention that this database will not only be a useful database of VOCs listed in the literature but will stimulate further study of VOCs from healthy individuals. Establishing a list of volatiles emanating from healthy individuals and increased understanding of VOC metabolic pathways is an important step for differentiating between diseases using VOCs.
Assess the influence of obesity in the composition of exhaled VOCs by comparing obese subjects with and without OSA and identify the discriminant VOCs in the two groups
19 obese patients OSA (OO; age 51.2 ± 6.8; body mass index (BMI) 34.3 ± 3.5); 14 obese without OSA (ONO; age 46.5 ± 7.6; BMI 33.5 ± 4.1); 20 nonobese healthy controls BMI 24.9 ± 3.8)
Exhaled breath was collected and sampled by using an electronic nose (cyranose 320) and by gas chromatography-mass spectrometry (GC-MS) analysis
10 days
Analysis of collected breath samples enabled the identification of 49 volatile organic compounds that characterized the two investigated groups.
This review describes the current status on clinical validation and application of breath analysis by electronic noses in the diagnosis and monitoring of chronic airways diseases
Electronic noses (eNoses) is used to measuring the spectrum of VOCs
The past 20 years paved the way for application of advanced electronic noses in medical practice. Several proof of concept studies have shown promising results for diagnosing different (airway) diseases. Currently, the biggest limitation to progress in the field of exhaled breath diagnostics is the lack of sensors that can be produced identically in large quantities.
Observational investigation without any intervention.
The authors applied solid-phase microextraction onfiber-derivatization (SPME-OFD) to determine aldehyde concentrations in exhaled breath of cancer patients, smokers, and healthy volunteers; this study was intended to find out whether lung cancer could be recognized from aldehydes in the breath of cancer patients
36 subjects
Alveolar breath samples were collected under control of expired CO2; reactive aldehydes were transformed into stable oximes by means of on-fiber-derivatization (SPME-OFD); aldehyde concentrations in the ppt and ppb level were determined by means of gas chromatography-mass spectrometry (GC-MS)
Acetaldehyde, propanal, butanal, heptanal, and decanal concentrations showed no significant differences for cancer patients, smokers and healthy volunteers. Exhaled pentanal, hexanal, octanal, and nonanal concentrations were significantly higher in lung cancer patients than in smokers and healthy controls. Lung cancer patients could be identified by means of exhaled pentanal, hexanal, octanal, and nonanal concentrations. Exhaled aldehydes reflect aspects of oxidative stress and tumor-specific tissue composition and metabolism.
SPME was applied, in conjunction with gas chromatography-mass spectrometry to the analysis of volatile organic compounds (VOCs) in human breath samples without requiring exhaled breath condensate collection; an EBV collection with a is described
4 healthy, nonsmoking adults
After sample collection, compounds are desorbed from the SPME fiber at 250°C in the GC-MS injector; experiments were performed using EBV collected at −80 °C and at room temperature, and the results were compared to the traditional method
It is demonstrated that this active SPME breath-sampling device provides advantages in the forms of faster sample collection and data analysis, apparatus portability, and avoidance of power or cooling requirements, and performance for sample collection in a contaminated environment.
This work describes the first interfacing of a thermal desorption unit to an (ion mobility) IM-MS using an ESI (extractive electrospray ionization) source; The potential of (thermal desorption) TD-ESI-IM-MS for the rapid screening of breath volatiles as an alternative technique to TD-GC/MS is demonstrated
Breath samples were collected from a healthy volunteer using an adaptive sampling technique
Thermal desorption unit has been interfaced to an electrospray ionization-ion mobility-time-of-flight mass spectrometer
The combination of temperature-programmed thermal desorption and ion mobility improved the response of selected species against background ions. Analysis of breath samples resulted in the identification of breath metabolites, based on ion mobility and accurate mass measurement using siloxane peaks identified during the analysis as internal lock masses.
The present paper deals with the problems that occur with concentration determination of dimethylamine (DMA) and trimethylamine (TMA); these occur in the breath of people suffering from renal disease
The application of solid-phase microextraction (SPME) and thermal desorption (TD) with subsequent measurement by GC-MS for the determination of amines is discussed
For DMA, preconcentration by SPME did not give satisfactory results. TMA may be analyzed using SPME preconcentration with an LOD of 1.5 ppb. Thermal desorption with Tenax as the adsorbing material allows reliable concentration determination for TMA (LOD = 0.5 ppb) and DMA (LOD = 4.6 ppb). DMA cannot be stored reliably in Tedlar bags and longer storage on Tenax (with subsequent TD) does not give good repeatability of results. For TMA, storage can be done on Tenax or in bags, the best results for the latter being achieved with Flex Foil bags.
The first aim is to assess whether an eNose could discriminate the exhaled breath of patients with overlap syndrome (OVS) from that of subjects with obstructive sleep apnea (OSA) and chronic obstructive pulmonary disease (COPD) alone; the secondary aim is to verify whether these classification are replicated in a set of newly recruited patients as external validation
This study comprised a total of 59 patients; the first group is composed by 13 never-smoking patients with established diagnosis of OSA, without previous treatment with CPAP; the second group consisted of 15 subjects without a history of sleep disturbances and with a well-defined diagnosis of COPD; the third group included 13 individuals with a proven diagnosis of OVS.
Exhaled breath was collected by a formerly validated method and sampled by using an electronic nose (cyranose 320); raw data were analyzed by canonical discriminant analysis on principal component reduction; cross-validation accuracy (CVA) and ROC-curves were calculated. External validation in newly recruited patients (6 OSA, 6 OVS, and 6 COPD) was tested using the previous training set.
From December 2014 to August 2016
Breathprints of patients with OSA clustered distinctly from those with OVS (CVA = 96.2%) as well as those with COPD (CVA = 82.1%); breathprints from OVS were not significantly separated from those of COPD (CVA = 67.9%); external validation confirmed the above findings.
