Silicosis is a prevalent chronic occupational disease, causing incurable damage to the lungs. The conventional methods for diagnosing silicosis are costly and complex. Noninvasive biomarker studies based on exhalation metabolomics have potential in the early diagnosis of silicosis, but existing studies remain scarce and especially lack the biomarkers for staging diagnosis. Exhaled breath from 74 healthy controls and 112 patients, including 28 stage Ⅰ silicosis patients (SILs), 22 stage Ⅱ SILs, 52 stage Ⅲ SILs and 10 coal workers' pneumoconiosis (CWP) patients, were detected using solid-phase microextraction incorporating gas chromatography-mass spectrometry (SPME-GC-MS) for the identification of the volatile metabolites. The univariate statistical analysis and orthogonal partial least squares-discriminant analysis (OPLS-DA) were employed to screen potential biomarkers of SILs, with diagnostic performance assessed with the receiver-operating characteristic (ROC) curve and decision tree model. Fourteen volatile metabolites were found to distinguish different stages of SILs from healthy controls, and 8 metabolites differentiating stage Ⅰ and Ⅲ as well as 3 metabolites distinguishing stage Ⅱ and Ⅲ. The ROC analysis of silicosis based on the biomarkers exhibited an area under curve (AUC) of more than 0.9, with the largest AUC of 0.986 in stage Ⅰ SILs and healthy controls. Mechanistic exploration showed that these biomarkers were associated with inflammatory response, oxidative stress, and fibrosis in silicosis, respectively. This study preliminarily screened out the biomarkers of exhaled breath for different stages of SILs, and explored the metabolic pathways of biomarkers, which can provide basic data for the early, staging and specific diagnosis of SILs.

Irritable Bowel Syndrome (IBS), a disorder of gut-brain interaction, is diagnosed using symptom-based Rome criteria. These criteria classify IBS patients into four subtypes in accordance to their stool patterns. However, whether this subtyping approach is based on true differences in the underlying biology of IBS patients, is unclear. Volatile organic compounds (VOCs) in the faecal headspace reflect both the gut microbial and host intestinal intraluminal processes and thereby may be used to study pathophysiological differences between IBS and its subtypes. We profiled faecal headspace VOCs in a cohort of 164 patients with IBS and 143 healthy controls using gas chromatography-mass spectrometry (GC-MS). Random forest models were employed to impute missing values and identify discriminatory VOCs to differentiate IBS patients from healthy controls. We corrected for faecal water content using Partial Least Squares Regression. Multivariate associations between the obtained volatile profiles and Rome III IBS subtypes were evaluated using regularized MANOVA. A total of 39 VOCs, including short-chain fatty acid esters, neurotransmitter-related metabolites, alcohols, and sulphides, were selected as significantly altered in patients with IBS. Our classification model achieved an area under the curve (AUC) of 0.82 on both training and independent test sets, demonstrating robust separation between IBS patients and healthy individuals. However, VOC profiles did not associate to Rome III -based IBS subtypes. This study highlights the potential of faecal VOC profiling as a non-invasive tool for studying and characterising IBS, yet they also reveal a disconnect between metabolic signatures and current stool-based subtypes. While the Rome criteria remain the clinical standard for diagnosis and subtyping of IBS, they offer limited insight into underlying disease mechanisms. Future research should focus on integrating VOC analysis with other omics approaches to refine IBS sub-classification into biologically relevant clusters, which may aid to improve personalised therapeutic strategies.

Increased exhaled breath acetone (EBA) concentrations might reflect impaired myocardial energetics and haemodynamic stress. We investigated the relation of EBA and cardiac structure, function, and exercise capacity in patients with or at risk of heart failure (HF).We enrolled outpatients with HF and reduced (<50%, HFrEF) or preserved (>50%, HFpEF) left ventricular ejection fraction (LVEF) and subjects with cardiovascular risk factors and/or structural heart disease without established HF. All participants underwent clinical and laboratory evaluation, resting transthoracic echocardiography, and a combined cardiopulmonary-echocardiographic stress test with EBA monitoring at rest (EBA) and during exercise (EBA).Patients with HFpEF (= 62) were older and more often female than those at risk of HF (= 50) or with HFrEF (= 41). EBA(1.5, interquartile range (IQR) 1.0-3.1 vs 0.9, IQR 0.7-1.2 mcg l) and EBA(2.4, IQR 1.5-4.4 vs 1.1, IQR 0.9-2.1 mcg l; all< 0.0001) were significantly higher in patients with HF compared to others. Among HF patients, those in the highest EBAtertile had lower LVEF, greater echocardiographic signs of congestion, higher NT-proBNP levels, and lower peak oxygen consumption, indicating impaired exercise capacity. In multivariate regression, NT-proBNP (= 0.0004) and the slope of minute ventilation to carbon dioxide production (= 0.0013) were independent predictors of EBA(adjusted= 0.458).EBA concentrations are higher in patients with HF compared to those without, regardless of LVEF, and are associated with markers of disease severity. Further studies are needed to determine whether EBA measurement can aid in HF diagnosis and management.

Atmospheric microplastics and nanoplastics (MPs/NPs) have become an increasing concern, with health impacts that remain insufficiently characterised and measured. Indoor airborne MP/NPs have raised greater alarm due to their origins in routine domestic activities and sources such as synthetic textiles, bed linen, face masks, electric dryers, and household laundry, posing a high inhalation risk that can lead to serious health consequences. These particles can enter the human body through various routes, with inhalation being the main pathway for both short- and long-term health effects. Additionally, they are engulfed by epithelial and immune cells, causing multiple pathological effects on the lungs, which can subsequently lead to or contribute to various disease entities. This narrative review thoroughly explores potential cellular, genetic, and immunological mechanisms by which MP/NPs impact the respiratory system, emphasising immune mediators and cytosolic pathways involved, and linking these mechanisms to various pulmonary diseases.

Several investigations have identified volatile organic compounds (VOCs) as potential biomarkers for the detection and identification of microbial contamination of metabolically active mammalian cell cultures. In this study, we showed that emitted VOCs discriminate between uncontaminated mesenchymal stromal cells (MSCs) and those contaminated with the bacteriumor fungusseparately,, using a methodology based on an adapted cell culture and thermal desorption-gas chromatography-mass spectrometry. In addition, we elucidated a set of discriminatory volatile compounds from the MSC cultures and media alone across a time series experiment. Partial least squares-discriminant analysis-variable importance in projection confirmed putative identifications of 18, 16, and 26 VOCs that showed relevant changes in a bacterial, fungal, and universal pathogen model, respectively, with an accuracy of 100% in the fungal model. Among these metabolites, octane, 2,5,6-trimethyl- overlapped between the three groups. Furthermore, a total of 15 VOCs were found most relevant to cell culture expansion over three days based on cluster analysis. This novel study goes a step further in identifying distinct VOC signatures of MSCs contaminated withor, and in monitoring MSCs proliferation over time. This pilot study shows preliminary results that indicate that VOC headspace analysis could serve as a suitable, rapid, non-invasive, and non-destructive tool for the metabolic and growth monitoring of MSCs in a dynamic cell culture bioreactor system.

To evaluate the therapeutic efficacy of probiotics in managing halitosis and to determine the optimal intervention strategies. Methods: An extensive search was conducted in PubMed, Web of Science, Cochrane Library, and Embase up to December 2024, focusing on studies evaluating probiotic interventions for halitosis. Sensitivity and subgroup analyses were undertaken to assess the robustness of the results and to explore potential sources of heterogeneity. All analyses were performed through Review Manger 5.4 and STATA 15.0. Results: Of the 194 records initially identified, 10 studies met the predefined criteria. The pooled results demonstrated a significant reduction in volatile sulfur compounds (VSCs) levels in the probiotic group compared to controls (SMD = -1.01, 95% CI [-1.93, -0.09], P = 0.03). Likewise, the organoleptic test (OLT) scores showed a marked improvement in the probiotic group (RR = 1.31, 95% CI [1.22, 1.41], P < 0.00001). Nevertheless, no substantial differences were observed between groups in oral health-related quality of life (SMD = 0.21, 95% CI [-0.06, 0.49], P = 0.12), subjective oral health status (SMD = -0.04, 95% CI [-0.35, 0.28], I² = 0%, p = 0.74), depression (SMD = 0.03, 95% CI [-0.29, 0.35], I² = 0%, p = 0.85), self-esteem (SMD = -0.07, 95% CI [-0.39, 0.25], I² = 0%, p = 0.67), OLT scores (SMD = -0.24, 95% CI [-0.64, 0.16], I² = 0%, p = 0.24), or plaque index (SMD = -0.06, 95% CI [-0.57, 0.46], I² = 0%, p = 0.82). Conclusions: The findings suggest that probiotic therapy, when combined with conventional treatments, may be more effective in enhancing OLT scores and reducing VSC levels in individuals with halitosis than using probiotic alone. Nonetheless, potential publication bias, limited sample sizes, and heterogeneity among the included clinical trials may affect the reliability of these conclusions.

Millions of people worldwide are exposed to environmental arsenic in drinking water, resulting in both malignant and nonmalignant diseases. Interestingly, early life exposure by itself is sufficient to produce higher incidences of these diseases later in life. Based on the delayed onset of disease, we hypothesized that early life arsenic exposure would also induce long-term alterations in the metabolic profile. The objective of this study was to examine metabolomic biomarkers in exhaled breath condensate (EBC) of individuals exposed to arsenic in drinking water early in life, but not later. One hundred and fifty subjects (75 males and 75 females) were initially recruited from Antofagasta, Chile, some of whom were exposed to high water arsenic levels (⩾870g l; HighAE group), and others, low water arsenic levels (⩽110g l; LowAE group) early in life (1958-1970). EBC samples were collected for targeted and untargeted metabolomic biomarker analysis. The results showed significantly shorter individuals and reduced pulmonary functions (forced vital capacity, FVC and forced expiratory volume in 1 s, FEV) in both males and females in the high-arsenic groups. Males exposed to high arsenic levels also had reduced red blood cell concentrations, as well as higher concentrations of the oxidative stress metabolites 8-OH-2dG and 8-iso-PGF2. Females in the high-arsenic group showed reductions in 8-OH-2dG. Untargeted analysis revealed metabolomic markers that differentiated the HighAE group from the LowAE group, with a subgroup of markers whose concentrations were proportional to the level of arsenic exposure. Targeted and untargeted analyses of EBC using liquid chromatography-mass spectrometry indicated that adults exposed to high arsenic levels in drinking water in utero and during early childhood retained a modified metabolic profile 47 years after the end of exposure.

Some cases of halitosis associated with small intestinal bacterial overgrowth (SIBO) are refractory to antibiotic therapy. The low fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAPs) diet (LFD) has emerged as an alternative therapeutic option for SIBO. This retrospective study is the first to investigate the efficacy of LFD in refractory SIBO-associated halitosis. We consecutively reviewed data from 141 patients with refractory SIBO-associated halitosis who underwent a four-week LFD intervention. Halitosis was diagnosed using organoleptic test. Volatile sulfur compounds-including hydrogen sulfide, methyl mercaptan (MM) and dimethyl sulfide (DMS)-were quantified in nasal breath using the OralChroma device. SIBO was confirmed via hydrogen/methane breath test. Serum nutritional parameters were measured to assess nutritional status. Dietary adherence was evaluated using the FODMAP Adherence Report Scale. All patients demonstrated good adherence to the LFD, with no significant changes in nutritional parameters post-treatment. Overall, 80.85% and 78.72% of the patients exhibited SIBO resolution and halitosis improvement, respectively. DMS levels significantly decreased after treatment [41.84 ± 10.73 parts per billion (ppb)19.22 ± 7.91 ppb,< 0.001]. In contrast, baseline hydrogen sulfide (17.08 ± 12.30 ppb) and MM (13.50 ± 5.65 ppb) levels were low and remained unchanged post-treatment (> 0.05). Moreover, post-treatment comparison between SIBO-negative and SIBO-positive groups revealed a higher rate of halitosis improvement in the SIBO-negative group (90.35%29.63%< 0.001), accompanied by significantly lower DMS levels (17.15 ± 5.81 ppb23.63 ± 9.99 ppb,= 0.006). Therefore, we conclude that a four-week LFD intervention appears effective for refractory SIBO-associated halitosis, with great adherence and no risk of malnutrition. Its mechanism likely involves SIBO alleviation, thereby reducing intestinal production and breath excretion of volatile malodorous compounds, particularly DMS.

Adenoid hypertrophy (AH) is a common condition among pediatric and adolescent populations. The clinical diagnosis primarily relies on rhinoscopy, with a notable absence of noninvasive early diagnostic methods. This study sought to identify potential biomarkers to facilitate the early diagnosis of AH. Ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS) was employed to analyze and compare urine samples from 40 patients with AH and 30 healthy controls. To validate and enhance the findings from untargeted metabolomics, targeted metabolomics was conducted using UHPLC-QqQ-MS/MS, aiming to elucidate the relationship between AH and metabolic pathways. The untargeted metabolomics analysis, utilizing multivariate techniques, identified significant differences in the levels of 20 endogenous metabolites in urine samples between the AH and healthy groups. Further investigation of metabolic pathways indicated that sphingolipid and riboflavin metabolism are implicated in the pathogenesis of AH. Riboflavin and phytosphingosine were identified as potential biomarkers using targeted metabolomics. In this study, a comprehensive approach involving both untargeted and targeted metabolomics was employed to investigate diagnostic biomarkers of AH. The abnormal expression levels of riboflavin and phytosphingosine may be related to inflammation, oxidative damage, and immunomodulatory dysfunction in the pathogenesis of AH. The results showed that the identified biomarkers may serve as a novel tool for early diagnosis and tracking of disease progression.

Currently, there are no standardized procedures for sampling exhaled volatile organic compounds (VOCs) from dairy cows. Therefore, this study aimed to compare exhaled VOCs captured on solid-phase extraction (SPE) cartridges using five variants of three breath collection devices (face mask and GreenFeed system [C-Lock, South Dakota, US] collecting unfiltered [GreenFeed] and filtered [GreenFeed] air). The variants were: a tight-fitting face mask (Mask), the Maskwith the openings sealed using activated carbon filters (Mask), the Maskcovered with an over-mask ventilated with synthetic air for cow breathing (Mask), the GreenFeed, and the GreenFeed. The variants were compared in two experiments (trial registration number (2023-30-FR) regarding possible VOC carryover over the samples (experiment 1) and their suitability for sampling exhaled VOC from cows (experiment 2). In both experiments, the SPE cartridges were connected to capture VOCs from collected air before GC-MS-based analysis. In experiment 1, our data showed evidence for VOC deposits and potential VOC carryover, particularly for GreenFeed(16.3%). In exhaled breath samples from experiment 2, we detected 1217 ± 197 peaks. After subtracting the background air peaks, the exhaled VOCs consisted mostly of esters (20.9%), ketones (13.2%), and alkanes (13.0%). Maskdetected the highest number of aldehydes, ketones, alcohols, alkanes, and alkenes, and GreenFeedthe highest number of esters. The highest relative concentrations of most individual exhaled VOC were detected using Mask. The tested variants, except Maskdue to low acceptance of the animals, seemed suitable for exhaled VOC sampling, with Maskseemed to be most suitable due to the detection of the highest VOC number and the lowest VOC carryover.

Bacterial volatile organic compounds (VOCs) have been investigated as a non-invasive approach to diagnosis of infectious diseases. Here, we aimed to explore potential diagnostic markers by profiling VOCs in cultures of unique clinicalisolates and stool samples from pediatric patients withinfection (CDI) using headspace solid-phase microextraction coupled with gas chromatography combined with mass spectrometry (HS-SPME-GC-MS). A total of 106 individual compounds were detected in 39isolate cultures, of which 1-hexanol, ethanol and 4-methylvaleric acid were detected in all bacterial cultures, and 2-methyl-butanoic acid, 1-pentanol, 2-methyl-1-propanol,-xylene and 6-methyl-2-heptanone were found in 38 (97.4%), 37 (94.9%), 34 (87.2%), 34 (87.2%) and 32 (82.1%) isolate cultures, respectively. The most abundant compound was 4-methylvaleric acid (relative abundance 14.71%, interquartile range 11.73%, 16.38%). A direct comparison of six paired isolates and stools revealed the transfer ofisolate VOCs to feces: ethanol was detected in all six pairs, 4-methylvaleric acid was in five pairs and 1-hexanol in four pairs. Fecal VOC patterns between the CDI children and healthy children were significantly different. Receiver operating characteristic analysis showed that 1-propanol, 6-methyl-2-heptanone, phenylethyl alcohol and ethanol presented the highest discrimination value for differentiating feces of CDI children from healthy children. Our data indicate that fecal 1-propanol, 6-methyl-2-heptanone, phenylethyl alcohol and ethanol may be used as potential screening biomarkers for diagnosing CDI.

Hyperglycemia can shorten red blood cell (RBC) lifespan, leading to incorrectly measured glycated hemoglobin (HbA1c) values. Correcting for the impact of the RBC lifespan on HbA1c is a critical issue in clinical practice. Before establishing a generally accepted correction formula to account for the impact of RBC lifespan on HbA1c, it is necessary to investigate the duration necessary to emake the hyperglycemia-induced RBC lifespan shortening reverse to normal. This longitudinal clinical trial examined the RBC lifespan in 31 hospitalized patients with type 2 diabetes mellitus by measuring the concentration of exhaled endogenous carbon monoxide. The 31 non-smoking patients with type 2 diabetes were all admitted due to blood glucose (BG) imbalance, and their RBC lifespan was tested at admission, discharge (after ∼2 weeks of intensive glycemic control), and 3 months after discharge. During the period from admission to three months after discharge, RBC lifespan significantly increased in the patients as they underwent drug treatment to control BG (< 0.05) effectively. HbA1c, fasting plasma glucose, and 2 h postprandial glucose decreased significantly. This study found that (i) a shortened RBC lifespan caused by hyperglycemia is reversible, and (ii) the time required for this reversal is three months of effective drug treatment to control BG.

There is an unmet need for breath-based markers for pulmonary vascular disease (PVD). We developed a fully-automatic algorithm to analyze expiratory COflow from resting ventilation and evaluated the clinical associations of our readouts. We enrolled patients with chronic obstructive pulmonary disease (COPD), interstitial lung disease (ILD), pulmonary arterial hypertension (PAH) and healthy controls and evaluated fractionated volumes for dead space, mixed space (MSV) and alveolar space, their respective COvolumes and ventilatory equivalents for CO(EqCO) and the maximum slope of the first derivative of the cumulative expiratory COvolume over expired volume (MSV-slope) as primary readouts. Differences between groups were analyzed using non-parametric tests. Associations were analyzed by Spearman correlation. The discriminatory power was determined with receiver operating characteristic analysis. Eleven COPD (median (IQR) age 64 (63-69) years), 10 ILD (61 (54-77) years), 10 PAH (64 (61-73) years) and 21 healthy controls (56 (52-61) years) were investigated. Patients vs healthy controls showed increased MSV and mixed space CO(221 (164-270) ml vs 144 (131-167) ml, and 3.9 (3.2-4.9) ml vs 3.0 (2.7-3.4) ml,< 0.001 and= 0.002) and EqCO(38 (34-42) vs 30 (29-35),< 0.001), and decreased MSV-slopes (0.16 (0.12-0.21) vs 0.27 (0.23-0.32) l COl,< 0.001). Area under the curve (AUC) for MSV and MSV-slope for disease prediction was 0.81 (95% CI 0.69-0.93) and 0.84 (0.73-0.95), respectively. MSV and mixed space COwere only strongly increased in COPD and ILD but not PAH, resulting in a significant difference between PAH and COPD&ILD (AUC 0.74 (95% CI: 0.56-0.92). MSV and MSV-slope were significantly correlated with DLCO (=-0.69 and= 0.72, respectively; both< 0.001). Fully-automatic high-fidelity expiratory COflow analysis is technically feasible, easy and safe to perform, and may represent a novel approach to detect PVD with or without structural changes of the airways and lung parenchyma. Prospective studies with larger sample size are needed to validate these findings.

Obtaining multiple sample types from the same exhaled breath condensate (EBC) sample can reduce the number of samples needed for diagnostics purposes, allowing for sampling to be completed quicker and making it even easier to collect breath from patients. In this study, we performed analysis for volatile organic compounds (VOCs) and proteins from the same EBC sample. Pooled EBC samples were split into two groups: three samples that utilized immersion thin film-solid phase microextraction (TF-SPME) sampling for VOC analysis and three samples that did not undergo TF-SPME sampling (non-TF-SPME). All six EBC samples were analyzed using liquid chromatography with tandem mass spectrometry (LC-MS/MS) for proteomics analysis. VOCs were analyzed via two-dimensional gas chromatography-mass spectrometry (GC x GC-MS). One hundred and eighty-four VOCs were found to be more abundant in EBC samples compared to blank or controls. There was no significant difference in the number of proteins detected in the TF-SPME samples compared to the non-TF-SPME samples and 144 of the 206 total unique proteins detected were found in both sample groups. These results indicate that TF-SPME sampling does not negatively affect the number of proteins that can be detected in EBC. This work is a step towards linking VOC and protein data together to obtain multi-omics breath data from a single breath sample. EBC samples were collected as part of a vaccination clinical trial (NCT05346302).

The rapid transfer of volatiles from alveolar blood into the lungs and then out of the body in exhaled breath leads to the common and natural conclusion that these volatiles provide information on health and metabolic processes, with considerable potential as biomarkers for use in the screening, diagnosis and monitoring of diseases. Whilst these exhaled volatiles could well serve as biomarkers for human metabolic processes, thereby providing insights into the clinical and nutritional status of individuals, there exist various confounding factors that limit their easy application. A major confounding factor is the introduction of microbially produced oral volatiles into the exhaled breath, yet these volatiles are often ignored in discovery volatile research studies. Here, we provide a comparative cross-sectional study of selected volatiles commonly found in exhaled breath. Using gas chromatography-ion mobility spectrometry, we monitored these selected volatiles in nasal and oral end-tidal exhaled breath samples from twenty-one volunteers. The signal intensities from untargeted volatile detection were analysed for variances using principal component analysis (PCA), revealing a clear separation correlated with the sampling method. Four compounds representing sampling method-independent (acetone, isoprene, methanol, and 2-pentanone) and four corresponding to sampling method-dependent (1-propanol, 2-propanol, ethanol, and acetoin) were identified and selected based on their high PCA loadings. These compounds are further analysed and discussed to illustrate the extent to which the oral microbiome can influence volatile concentrations in exhaled breath. An additional noteworthy finding of this study is that the nasally sampled selected exhaled volatiles are little influenced by the inhalation route (oral or nasal). The outcome from this study is clear, namely that in order to reduce the influence of the oral microbiome on untargeted discovery breath research studies, end-tidal exhaled nasal breath samples should be taken for endogenous volatile analysis, otherwise oral microbial volatiles could be falsely identified as biomarkers. This is particularly important given the continuous rise in the use of machine learning algorithms and artificial intelligence to identify variations in volatilomes. The development and commercialisation of simple, user-friendly and comfortable end-tidal exhaled nasal sample collection devices are required for nasal sampling to become widely adopted.

Breath contains numerous classes of compounds and biomolecules that could potentially be used as biomarkers for infectious disease as well as a range of other respiratory conditions or states. The goal of this work was to develop a testbed for simultaneous, multi-modal breath measurements. To validate the capabilities of this testbed, a pilot human-subjects research study was conducted to gather a wide range of correlated breath measurements. Seventeen healthy subjects provided breath samples at baseline respiratory rate for particle size, lipid composition and bacterial nucleic acid composition analysis. The majority of the particles the participants exhaled at baseline were smaller than 5m, consistent with previous literature. A deviation from baseline was detected in one participant immediately prior to COVID-19 symptom onset. This feature persisted for weeks after infection. The exhaled breath particulate contained lipids found in lung surfactant, indicating origin in the lung. Although bacterial DNA was not significantly higher in the exhaled breath particulate than in the environmental background, the metagenome of the breath was distinct from the environment, oral cavity and nasal passages of the participants. The low abundance of the breath microbiome limited analysis. No assertions of statistical significance are offered due to the limited nature of the study scope, the multi-modal breath testbed has promise for discovery of breath biomarkers and as a reference for biomarkers of different classes that are currently being used.

The non-invasive biological marker exhaled nitric oxide (FE) is increasingly used in asthma, but its clinical role in COPD is less established. FEhas been reported to be both high and low outside the COPD exacerbation period. The study aimed to follow FEvalues over two years during stable conditions in a cohort of COPD subjects participating in the TIE-study (Tools Identifying Exacerbation). The follow-up study included 353 subjects who attended three visits one year apart. The subjects that were ex-smokers (= 265) had higher FEvalues (median and IQR) compared with current smokers (= 88), at inclusion 15 (10, 24) versus 9 (7, 15) ppb, after one year 15 (10, 24) versus 10 (7, 18) ppb, and after two years 14 (9, 22) versus 10 (7, 17) ppb, all< 0.001. All subjects were further divided into two FEgroups: <20 ppb (72%) and ⩾20 ppb (28%). After one year, 81% of the participants remained in the low group and 65% in the high FEgroup. After two years, 71% remained in the low group and 52% in the high FEgroup. The persistent low FEgroup had statistically significantly lower FEV%pred and FVC%pred compared to the high FEgroup for all three visits. Among the ex-smokers, the proportion of subjects reporting dyspnoea (mMRC ⩾ 2) was higher in the persistent low FEgroup than in the persistent high FEgroup at all three visits. In conclusion, good consistency in FEover two years is promising for monitoring FEduring stable disease. COPD subjects with persistent low FEhad poorer lung function and reported more dyspnoea than subjects with persistent high FE.

Chios mastic gum, derived from Pistacia lentiscus variation chia, has emerged as a significant natural remedy to improve oral health and mitigate halitosis. This study aimed to examine the effect of mastic toothpaste on halitosis, plaque, and gingival indices in adolescents undergoing orthodontic treatment with fixed appliances. This study was a double-blind, placebo-controlled, parallel-group, randomized clinical trial. Thirty-two patients were randomly divided into two groups: A) mastic-toothpaste group and B) placebo-toothpaste group. Participants in both groups used the assigned toothpaste three times daily for 14 d. The primary outcome was objective hydrogen sulfide (HS) levels in breath, measured using a gas chromatograph. The secondary outcomes were dimethyl sulfide and methyl-mercaptan levels, as well as the Silness and Löe Gingival Index (GI) and the Modified Silness and Löe Plaque Index (PI-M). Assessments were conducted at baseline and after two weeks. Data were analyzed using the Mann-Whitneytest and Student's-test. A statistically significant difference was found between interventions, in favor of the mastic group's HS (= 0.001). The HS median levels decreased from 158 parts per billion (ppb) to 26 ppb. Neither treatment group experienced a different decline in the levels of the other two components. Statistically significant differences were observed in the periodontal parameters, favoring the mastic group. The GI index decreased from 1.8 to 1 [< 0.001, 95% CI: -0.7, -0.4], whereas the PI-M index decreased from 1.2 to 0.8 [< 0.001, (95% CI: -0.5, -0.2)]. Mastic toothpaste may be an alternative option to reduce halitosis in adolescents undergoing orthodontic treatment with fixed appliances. Regular use of this toothpaste may lead to a clinically meaningful reduction in plaque and gingival indices (ClinicalTrials.gov, NCT06766097).

Chronic kidney disease (CKD) is a long-term progressive disease. The key to treatment lies in early diagnosis and timely intervention. How to achieve early diagnosis of CKD has always been an important challenge. Exhaled breath sample analysis, as an emerging method, has attracted much attention due to its non-invasiveness and the convenience of sample collection. Compared with the complex traditional detection methods, it is more suitable for large-scale screening. The main purpose of this review is to extensively collect relevant literature on the research of exhaled breath biomarkers for CKD, summarize the potential biomarkers discovered in these studies, and compare the similarities and differences. Through in-depth analysis of the causes of these differences and commonalities, this review aims to explore whether these potential exhaled breath biomarkers could serve as reliable indicators for the early diagnosis of CKD.

Volatile organic compounds (VOCs) offer potential for non-invasive diagnosis as biomarkers of disease and metabolism. In complex biological matrices, such as breath however, identifying useful biomarkers from hundreds, or even thousands of VOCs can be challenging. Models of disease, such as cellular or animal models, offer a means to elucidate VOC metabolisms, for accurate targeted studies in patient samples. Neurodegenerative conditions, such as Parkinson's have been associated with changed VOCs, offering a potential for early diagnostics and interventions improving treatments and outcomes for patients. Here, three separate models including; human HEK-293t cells, isolated primary rat glial cells, andfruit flies (wild type and a mutant of the Parkinson's associated gene,) were grown for an extended period and levels of the VOC chloroform investigated using custom static headspace sampling chambers. Samples were analysed using targeted gas chromatography mass spectroscopy with selected ion monitoring mode, measuring chloroform at masses 83/85. Chloroform levels were shown to dramatically increase in all models over time. HEK-293t cells revealed a 60-fold increase after 10 weeks, glial cells revealed a 10-fold increase after 3-4 weeks andmutant flies revealed significant increases compared to control flies at 4 weeks. These results, taken together, suggest that chloroform release is related to ageing in these models and may provide a target for neurodegenerative studies. We present here the first evidence of chloroform being actively produced by human and rat cells and the first observation of volatile metabolisms in. Recent clinical studies have also identified increased chloroform flux in the breath of patients, supporting the translational potential of our findings.

Nonalcoholic fatty liver disease (NAFLD) is now the leading cause of global chronic liver disease, affecting approximately 32.4% of the population in various regions and imposing healthcare and economic burdens. The gold standard for the diagnosis of NAFLD, such as liver biopsy, has numerous limitations in large-scale screening. Recent studies have explored the use of machine learning to diagnose NAFLD. In this study, we investigated the effect of the lactulose breath test (LBT) on a machine-learning model for predicting NAFLD. The input variables for machine learning included three combination sets to assess the effect of the LBT results: anthropometric characteristics and blood test results; anthropometric characteristics and LBT results; and anthropometric characteristics, blood test results, and LBT results. The machine learning models developed in this study included linear regression, support vector machine, K-nearest neighbour, Random forest, and extreme gradient boosting (XGBoost) with 536 participants. The model performance was evaluated using six metrics: Accuracy, Area Under the Receiver Operating Characteristic curve (AUROC), specificity, sensitivity, precision, and F1 score. Among the six models, XGBoost had the highest AUROC at 0.88. The AUROC results from the three combination variable sets indicate that the LBT results significantly improve the model performance. LBT results improve the NAFLD prediction model and provide an opportunity for additional NAFLD screening in patients receiving LBT.