A comprehensive meta-analysis and systematic review of breath analysis in detection of COVID-19 through Volatile organic compounds.

BACKGROUND: The COVID-19 pandemic had profound global impacts on daily lives, economic stability, and healthcare systems. Diagnosis of COVID-19 infection via RT-PCR was crucial in reducing spread of disease and informing treatment management. While RT-PCR is a key diagnostic test, there is room for improvement in the development of diagnostic criteria. Identification of volatile organic compounds (VOCs) in exhaled breath provides a fast, reliable, and economically favorable alternative for disease detection. METHODS: This meta-analysis analyzed the diagnostic performance of VOC-based breath analysis in detection of COVID-19 infection. A systematic review of twenty-nine papers using the grading criteria from Newcastle-Ottawa Scale (NOS) and PRISMA guidelines was conducted. RESULTS: The cumulative results showed a sensitivity of 0.92 (95 % CI, 90 %-95 %) and a specificity of 0.90 (95 % CI 87 %-93 %). Subgroup analysis by variant demonstrated strong sensitivity to the original strain compared to the Omicron and Delta variant in detection of SARS-CoV-2 infection. An additional subgroup analysis of detection methods showed eNose technology had the highest sensitivity when compared to GC-MS, GC-IMS, and high sensitivity-MS. CONCLUSION: Overall, these results support the use of breath analysis as a new detection method of COVID-19 infection.

Predicting Helicobacter pylori infection from endoscopic features.

BACKGROUND: Helicobacter pylori infection, prevalent in more than half of the global population, is associated with various gastrointestinal diseases, including peptic ulcers and gastric cancer. The effectiveness of early diagnosis and treatment in preventing gastric cancer highlights the need for improved diagnostic methods. This study aimed to develop a simple scoring system based on endoscopic findings to predict H. pylori infection. METHODS: A retrospective analysis was conducted on 1,007 patients who underwent upper gastrointestinal endoscopy at Asan Medical Center from January 2019 to December 2021. Exclusion criteria included prior H. pylori treatment, gastric surgery, or gastric malignancies. Diagnostic techniques included rapid urease and 13C-urea breath tests, H. pylori culture, and assessment of endoscopic features following the Kyoto gastritis classification. A new scoring system based on endoscopic findings including regular arrangement of collecting venules (RAC), nodularity, and diffuse or spotty redness was developed for predicting H. pylori infection, utilizing logistic regression analysis in the development set. RESULTS: The scoring system demonstrated high predictive accuracy for H. pylori infection in the validation set. Scores of 2 and 3 were associated with 96% and 99% infection risk, respectively. Additionally, there was a higher prevalence of diffuse redness and sticky mucus in cases where the initial H. pylori eradication treatment failed. CONCLUSION: Our scoring system showed potential for improving diagnostic accuracy in H. pylori infection. H. pylori testing should be considered upon spotty redness, diffuse redness, nodularity, and RAC absence on endoscopic findings as determined by the predictive scoring system.

Cross-site validation of lung cancer diagnosis by electronic nose with deep learning: a multicenter prospective study.

BACKGROUND: Although electronic nose (eNose) has been intensively investigated for diagnosing lung cancer, cross-site validation remains a major obstacle to be overcome and no studies have yet been performed. METHODS: Patients with lung cancer, as well as healthy control and diseased control groups, were prospectively recruited from two referral centers between 2019 and 2022. Deep learning models for detecting lung cancer with eNose breathprint were developed using training cohort from one site and then tested on cohort from the other site. Semi-Supervised Domain-Generalized (Semi-DG) Augmentation (SDA) and Noise-Shift Augmentation (NSA) methods with or without fine-tuning was applied to improve performance. RESULTS: In this study, 231 participants were enrolled, comprising a training/validation cohort of 168 individuals (90 with lung cancer, 16 healthy controls, and 62 diseased controls) and a test cohort of 63 individuals (28 with lung cancer, 10 healthy controls, and 25 diseased controls). The model has satisfactory results in the validation cohort from the same hospital while directly applying the trained model to the test cohort yielded suboptimal results (AUC, 0.61, 95% CI: 0.47─0.76). The performance improved after applying data augmentation methods in the training cohort (SDA, AUC: 0.89 [0.81─0.97]; NSA, AUC:0.90 [0.89─1.00]). Additionally, after applying fine-tuning methods, the performance further improved (SDA plus fine-tuning, AUC:0.95 [0.89─1.00]; NSA plus fine-tuning, AUC:0.95 [0.90─1.00]). CONCLUSION: Our study revealed that deep learning models developed for eNose breathprint can achieve cross-site validation with data augmentation and fine-tuning. Accordingly, eNose breathprints emerge as a convenient, non-invasive, and potentially generalizable solution for lung cancer detection. CLINICAL TRIAL REGISTRATION: This study is not a clinical trial and was therefore not registered.

The Classification of VOCs Based on Sensor Images Using a Lightweight Neural Network for Lung Cancer Diagnosis.

The application of artificial intelligence to point-of-care testing (POCT) disease detection has become a hot research field, in which breath detection, which detects the patient's exhaled VOCs, combined with sensor arrays of convolutional neural network (CNN) algorithms as a new lung cancer detection is attracting more researchers' attention. However, the low accuracy, high-complexity computation and large number of parameters make the CNN algorithms difficult to transplant to the embedded system of POCT devices. A lightweight neural network (LTNet) in this work is proposed to deal with this problem, and meanwhile, achieve high-precision classification of acetone and ethanol gases, which are respiratory markers for lung cancer patients. Compared to currently popular lightweight CNN models, such as EfficientNet, LTNet has fewer parameters (32 K) and its training weight size is only 0.155 MB. LTNet achieved an overall classification accuracy of 99.06% and 99.14% in the own mixed gas dataset and the University of California (UCI) dataset, which are both higher than the scores of the six existing models, and it also offers the shortest training (844.38 s and 584.67 s) and inference times (23 s and 14 s) in the same validation sets. Compared to the existing CNN models, LTNet is more suitable for resource-limited POCT devices.

Periodic open and closed resonators as a biosensor using two computational methods.

The volatile particles and molecules in our dry exhaled breath can reveal enormous information about the health of any person, such as the person's respiratory and metabolic functioning. Beyond the carbon dioxide level is an indicator of life, it provides important health-related data like people's metabolic rate. This study considers periodic open and closed resonators for measuring carbon dioxide concentration in dry exhaled breath. Transfer matrix and green methods are used to simulate the interaction between acoustic waves and the proposed sensor. The band gaps using the green method coincide with the transmittance spectra by the transfer matrix. The suggested sensor recorded a sensitivity of 5.3 H z . m - 1 . s , a figure of merit of 10,254 m - 1 . s , a detection limit of 5 × 10 - 6 m . s - 1 , and a quality factor of 3 × 10 6 . Furthermore, the efficiency shows that the proposed design is appropriate as a diagnostic sensor for different diseases such as chronic obstructive pulmonary. Besides, cylindrical-adapted sensors are urgently needed in medicine, industry, and biology because they can simultaneously be used for fluid transport and detection.

Evaluation of the relationship between end-tidal carbon dioxide level and heart failure classification.

OBJECTIVE: Heart failure is a disease with cardiac dysfunction, and its morbidity and mortality are associated with the degree of dysfunction. The New York Heart Association classifies the heart failure stages based on the severity of symptoms and physical activity. End-tidal carbon dioxide refers to the level of carbon dioxide that a person exhales with each breath. End-tidal carbon dioxide levels can be used in many clinical conditions such as heart failure, asthma, and chronic obstructive pulmonary disease. The aim of the study was to reveal the relationship between end-tidal carbon dioxide levels and the New York Heart Association classification of heart failure stages. METHODS: This study was conducted at Kahramanmaras Sütçü Imam University Faculty of Medicine Adult Emergency Department between 01/03/2019 and 01/09/2019. A total of 80 patients who presented to the emergency department with a history of heart failure or were diagnosed with heart failure during admission were grouped according to the New York Heart Association classification of heart failure stages. The laboratory parameters, ejection fraction values, and end-tidal carbon dioxide levels of the patients were measured and recorded in the study forms. RESULTS: End-tidal carbon dioxide levels and ejection fraction values were found to be significantly lower in the stage 4 group compared to the other groups. Furthermore, pro-B-type natriuretic peptide (BNP) values were found to be significantly higher in stage 4 group compared to the other groups. CONCLUSION: It was concluded that end-tidal carbon dioxide levels could be used together with pro-BNP and ejection fraction values in determining the severity of heart failure.

Detection of Helicobacter pylori strain types and analysis of risk factors among subjects from Hainan Province, China.

OBJECTIVE: To explore the prevalence of type I and type II Helicobacter pylori infection and investigate risk factors in a population from Hainan Province in China. METHODS: Data came from a large, cross-sectional study conducted from August 2022 to April 2023 involving five cities of Hainan. Subjects with confirmed 14C-urea breath test (UBT) and positive serological assay were included. All subjects had a gastroscopy. According to presence or absence of CagA/VacA proteins, subjects were classified as either type I (present) or type II strains (absent). Gastroscopic findings and several socio-demographic factors were examined for correlation with antibody serotyping. RESULTS: In total, 410 subjects were investigated for H. pylori strain types. The overall prevalence of the highly virulent, type I H. pylori strain was 79% (324/410) and type II strain was 21% (86/410). There was a strong association between type I strain and peptic ulcer disease. Of several sociodemographic factors investigated, only smoking and data over baseline (DOB) values showed significant differences between type 1 and type II strains. Logistic regression analysis showed a lower risk of type I H. pylori infection in smokers compared with non-smokers, and a higher risk of H. pylori type I infection in subjects with medium and high data over baseline (DOB) values compared with subjects who had low DOB values. CONCLUSION: Highly virulent, type I H. pylori infections predominate in Hainan and the co-positivity of CagA and VacA antibodies are related to type I H. pylori infection. We found that Type I H. pylori was closely associated with peptic ulcer disease and the DOB values were generally high.

Efficient detection of nitric oxide a biomarker associated with COVID19 via N, P co-doped C60 fullerene: a computational study.

CONTEXT: Coronavirus (COVID-19) is a novel respiratory viral infection, causing a relatively large number of deaths especially in people who underly lung diseases such as chronic obstructive pulmonary and asthma, and humans are still suffering from the limited testing capacity. In this article, a solution is proposed for the detection of COVID-19 viral infections through the analysis of exhaled breath gasses, i.e., nitric oxide, a prominent biomarker released by respiratory epithelial, as a non-invasive and time-saving approach. Here, we designed a novel and low-cost N and P co-doped C60 fullerene-based breathalyzer for the detection of NO gas exhaled from the respiratory epithelial cells. This breathalyzer shows a quick response to the detection of NO gas by directly converting NO to NO2 without passing any energy barrier (0 kcal/mol activation energy). The recovery time of breathalyzer is very short (0.98 × 103 s), whereas it is highly selective for NO sensing in the mixture of CO2 and H2O gasses. The study provides an idea for the synthesis of low-cost (compared to previously reported Au atom decorated nanostructure and metal-based breathalyzer), efficient, and highly selective N and P co-doped C60 fullerene-based breathalyzer for COVID-19 detection. METHODS: The geometries of N and P-doped systems and gas molecules are simulated using spin-polarized density functional theory calculations.

Proteomic Analysis of Primary Graft Dysfunction in Porcine Lung Transplantation Reveals Alveolar-Capillary Barrier Changes Underlying the High Particle Flow Rate in Exhaled Breath.

Primary graft dysfunction (PGD) remains a challenge for lung transplantation (LTx) recipients as a leading cause of poor early outcomes. New methods are needed for more detailed monitoring and understanding of the pathophysiology of PGD. The measurement of particle flow rate (PFR) in exhaled breath is a novel tool to monitor and understand the disease at the proteomic level. In total, 22 recipient pigs underwent orthotopic left LTx and were evaluated for PGD on postoperative day 3. Exhaled breath particles (EBPs) were evaluated by mass spectrometry and the proteome was compared to tissue biopsies and bronchoalveolar lavage fluid (BALF). Findings were confirmed in EBPs from 11 human transplant recipients. Recipients with PGD had significantly higher PFR [686.4 (449.7-8,824.0) particles per minute (ppm)] compared to recipients without PGD [116.6 (79.7-307.4) ppm, p = 0.0005]. Porcine and human EBP proteins recapitulated proteins found in the BAL, demonstrating its utility instead of more invasive techniques. Furthermore, adherens and tight junction proteins were underexpressed in PGD tissue. Histological and proteomic analysis found significant changes to the alveolar-capillary barrier explaining the high PFR in PGD. Exhaled breath measurement is proposed as a rapid and non-invasive bedside measurement of PGD.

Impact of breath sample collection method and length of storage of breath samples in Tedlar bags on the level of selected volatiles assessed using gas chromatography-ion mobility spectrometry (GC-IMS).

The analysis of volatile organic compounds (VOCs) in exhaled air has attracted the interest of the scientific community because it provides the possibility of monitoring physiological and metabolic processes and non-invasive diagnostics of various diseases. However, this method remains underused in clinical practice as well as in research because of the lack of standardized procedures for the collection, storage and transport of breath samples, which would guarantee good reproducibility and comparability of results. The method of sampling, as well as the storage time of the breath samples in the polymer bags used for sample storage and transport, affect the composition and concentration of VOCs present in the breath samples. The aim of our study was to compare breath samples obtained using two methods with fully disposable equipment: a Haldane sampling tube intended for direct breath collection and breath samples exhaled into a transparent Tedlar bag. The second task was to monitor the stability of selected compounds of real breath samples stored in a Tedlar bag for 6 h. Gas chromatography coupled with ion mobility spectrometry (GC-IMS) implemented in the BreathSpec®device was used to analyse exhaled breath. Our results showed a significant difference in the signal intensity of some volatiles when taking a breath sample with a Haldane tube and a Tedlar bag. Due to its endogenous origin, acetone levels were significantly higher when the Haldane tube sampler was used while elevated levels of 2-propanol and unidentified VOC (designated as VOC 3) in the Tedlar bag samples likely originated from contamination of the Tedlar bags. The VOC stability study revealed compound-specific signal intensity changes of the selected VOCs with storage time in the Tedlar bags, with some volatiles showing increasing signal intensity during storage in Tedlar bags. This limits the use of Tedlar bags only for very limited time and carefully selected purpose. Our results highlight the importance of careful design and implementation of experiments and clinical protocols to obtain relevant and reliable results.

Exhaled breath analysis in patients with potentially curative lung cancer undergoing surgery: a longitudinal study.

Exhaled breath analysis has emerged as a non-invasive and promising method for early detection of lung cancer, offering a novel approach for diagnosis through the identification of specific biomarkers present in a patient's breath. For this longitudinal study, 29 treatment-naive patients with lung cancer were evaluated before and after surgery. Secondary electrospray ionization high-resolution mass spectrometry was used for exhaled breath analysis. Volatile organic compounds with absolute log2fold change ⩾1 andq-values ⩾ 0.71 were selected as potentially relevant. Exhaled breath analysis resulted in a total of 3482 features. 515 features showed a substantial difference before and after surgery. The small sample size generated a false positive rate of 0.71, therefore, around 154 of these 515 features were expected to be true changes. Biological identification of the features with the highest consistency (m/z-242.18428 andm/z-117.0539) revealed to potentially be 3-Oxotetradecanoic acid and Indole, respectively. Principal component analysis revealed a primary cluster of patients with a recurrent lung cancer, which remained undetected in the initial diagnostic and surgical procedures. The change of exhaled breath patterns after surgery in lung cancer emphasizes the potential for lung cancer screening and detection.

Halitosis in young patients with chronic kidney disease: findings from a randomized controlled trial.

BACKGROUND: Chronic kidney disease (CKD) directly affects oral health. Yet data about halitosis in young CKD patients and the impact of dental prophylaxis is limited. Therefore, as part of this randomized clinical trial, halitosis in young CKD patients undergoing intensive or standard oral preventive procedures was to be explored. METHODS: Three volatile sulfur compounds (hydrogen sulfide, methyl mercaptan and dimethyl sulfide) were measured in 30 young patients with CKD (mean age 14.2 years; 16 males, 14 females). Breath samples were taken after 3 and 6 months and analyzed with selective gas chromatography (OralChroma). Tongue coating (Winkel Index) and clinical indices to determine local inflammation or oral hygiene (Papillary Bleeding Index and Quigley-Hein Index) were assessed. Within an extended anamnesis, patients and their mothers and nurses were questioned about the perceived halitosis. Corresponding quotes were noted verbatim. Patients were randomized to either intensive need-related oral health care measures (oral preventative program, OPP) or a one-stage standard prevention (treatment as usual, TAU). RESULTS: While there were no differences in volatile sulfur compound levels between TAU and OPP at the three time points of measurements (p > 0.05), there was a tendency towards a reduction in dimethyl sulfide and hydrogen sulfide of affected patients within the OPP group over time. Looking at potential differences between both groups with regard to tongue coating, significant differences were observed between baseline and 3 months after study start in the OPP group, and between baseline and 6 months after study start in the TAU group (p < 0.05). The burden of halitosis was frequently reported by patients' mothers and nurses. CONCLUSIONS: Young CKD patients regularly suffered from halitosis and dimethyl sulfide was its main source. Preventive measures mainly resulted in a reduction of tongue coating. TRIAL REGISTRATION: The German Clinical Trial Register (# DRKS00010580).

Single and multiple breath nitrogen washout compared with the methacholine test in patients with suspected asthma and normal spirometry.

BACKGROUND: Methods used to assess ventilation heterogeneity through inert gas washout have been standardised and showed high sensitivity in diagnosing many respiratory diseases. We hypothesised that nitrogen single or multiple breath washout tests, respectively nitrogen single breath washout (N2SBW) and nitrogen multiple breath washout (N2MBW), may be pathological in patients with clinical suspicion of asthma but normal spirometry. Our aim was to assess whether N2SBW and N2MBW are associated with methacholine challenge test (MCT) results in this population. We also postulated that an alteration in SIII at N2SBW could be detected before the 20% fall of forced expiratory volume in the first second (FEV1) in MCT. STUDY DESIGN AND METHODS: This prospective, observational, single-centre study included patients with suspicion of asthma with normal spirometry. Patients completed questionnaires on symptoms and health-related quality-of-life and underwent the following lung function tests: N2SBW (SIII), N2MBW (Lung clearance index (LCI), Scond, Sacin), MCT (FEV1 and sGeff) as well as N2SBW between each methacholine dose. RESULTS: 182 patients were screened and 106 were included in the study, with mean age of 41.8±14 years. The majority were never-smokers (58%) and women (61%). MCT was abnormal in 48% of participants, N2SBW was pathological in 10.6% at baseline and N2MBW abnormality ranged widely (LCI 81%, Scond 18%, Sacin 43%). The dose response rate of the MCT showed weak to moderate correlation with the subsequent N2SBW measurements during the provocation phases (ρ 0.34-0.50) but no correlation with N2MBW. CONCLUSIONS: Both MCT and N2 washout tests are frequently pathological in patients with suspicion of asthma with normal spirometry. The weak association and lack of concordance across the tests highlight that they reflect different but not interchangeable pathological pathways of the disease.

Domiciliary monitoring of exhaled nitric oxide in the management of asthma: a pilot study.

BACKGROUND: Whether asthma patients could benefit from home monitoring for fractional exhaled nitric oxide (flow of 50 mL/s, FeNO50) is unknown. We explore the application value of home monitoring FeNO50 in daily asthma management. METHODS: Twenty-two untreated, uncontrolled asthma patients were selected. Medical history, blood and sputum samples, pulmonary function, Asthma Control Test (ACT), and other clinical data of the subjects were collected. All subjects underwent daily monitoring for four weeks using a FeNO50 monitor and mobile spirometry (mSpirometry). The diurnal differences and dynamic changes were described. Compare the effect-acting time and the relative plateau of treatment between FeNO50 and mSpirometry monitoring. RESULTS: In the first two weeks, the morning median (IQR) level of FeNO50 was 44 (35, 56) ppb, which was significantly higher than the evening median level [41 (32, 53) ppb, P = 0.028]. The median (IQR) effect-acting time assessed by FeNO50 was 4 (3, 5) days, which was significantly earlier than each measure of mSpirometry (P < 0.05). FeNO50 reached the relative plateau significantly earlier than FEV1 (15 ± 2 days vs. 21 ± 3 days, P < 0.001). After treatment, the daily and weekly variation rates of FeNO50 showed a gradually decreasing trend (P < 0.05). The ACT score, sputum eosinophils, and blood eosinophils also significantly improved (P ≤ 0.01). CONCLUSIONS: The daily home monitoring of FeNO50 in asthmatic patients showed significant circadian rhythm, and the sensitivity of FeNO50 in evaluating the response to treatment was higher than mSpirometry. The daily and weekly variation rates of FeNO50 change dynamically with time, which may be used to assess the condition of asthma.

Fecal Coprococcus, hidden behind abdominal symptoms in patients with small intestinal bacterial overgrowth.

BACKGROUND: Small intestinal bacterial overgrowth (SIBO) is the presence of an abnormally excessive amount of bacterial colonization in the small bowel. Hydrogen and methane breath test has been widely applied as a non-invasive method for SIBO. However, the positive breath test representative of bacterial overgrowth could also be detected in asymptomatic individuals. METHODS: To explore the relationship between clinical symptoms and gut dysbiosis, and find potential fecal biomarkers for SIBO, we compared the microbial profiles between SIBO subjects with positive breath test but without abdominal symptoms (PBT) and healthy controls (HC) using 16S rRNA amplicon sequencing. RESULTS: Fecal samples were collected from 63 SIBO who complained of diarrhea, distension, constipation, or abdominal pain, 36 PBT, and 55 HC. For alpha diversity, the Shannon index of community diversity on the genus level showed a tendency for a slight increase in SIBO, while the Shannon index on the predicted function was significantly decreased in SIBO. On the genus level, significantly decreased Bacteroides, increased Coprococcus_2, and unique Butyrivibrio were observed in SIBO. There was a significant positive correlation between saccharolytic Coprococcus_2 and the severity of abdominal symptoms. Differently, the unique Veillonella in the PBT group was related to amino acid fermentation. Interestingly, the co-occurrence network density of PBT was larger than SIBO, which indicates a complicated interaction of genera. Coprococcus_2 showed one of the largest betweenness centrality in both SIBO and PBT microbiota networks. Pathway analysis based on the Kyoto Encyclopedia of Genes and Genome (KEGG) database reflected that one carbon pool by folate and multiple amino acid metabolism were significantly down in SIBO. CONCLUSIONS: This study provides valuable insights into the fecal microbiota composition and predicted metabolic functional changes in patients with SIBO. Butyrivibrio and Coprococcus_2, both renowned for their role in carbohydrate fermenters and gas production, contributed significantly to the symptoms of the patients. Coprococcus's abundance hints at its use as a SIBO marker. Asymptomatic PBT individuals show a different microbiome, rich in Veillonella. PBT's complex microbial interactions might stabilize the intestinal ecosystem, but further study is needed due to the core microbiota similarities with SIBO. Predicted folate and amino acid metabolism reductions in SIBO merit additional validation.

Metabolic trajectories of diabetic ketoacidosis onset described by breath analysis.

Purpose: This feasibility study aimed to investigate the use of exhaled breath analysis to capture and quantify relative changes of metabolites during resolution of acute diabetic ketoacidosis under insulin and rehydration therapy. Methods: Breath analysis was conducted on 30 patients of which 5 with DKA. They inflated Nalophan bags, and their metabolic content was subsequently interrogated by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). Results: SESI-HRMS analysis showed that acetone, pyruvate, and acetoacetate, which are well known to be altered in DKA, were readily detectable in breath of participants with DKA. In addition, a total of 665 mass spectral features were found to significantly correlate with base excess and prompt metabolic trajectories toward an in-control state as they progress toward homeostasis. Conclusion: This study provides proof-of-principle for using exhaled breath analysis in a real ICU setting for DKA monitoring. This non-invasive new technology provides new insights and a more comprehensive overview of the effect of insulin and rehydration during DKA treatment.

Features of exocrine pancreatic insufficiency in patients with non-alcoholic fatty liver disease in combination with type 2 diabetes and COVID-19.

OBJECTIVE: Aim: The aim of the research was to study the features of pancreatic exocrine insufficiency (EPI) in patients with nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (DM) at COVID-19. PATIENTS AND METHODS: Materials and Methods: 72 patients with NAFLD and COVID-19 were examined. The patients have been divided into two groups: group 1 included 42 patients with NAFLD and insulin resistance (IR); group 2 consisted of 30 patients with NAFLD in the combination with type 2 DM. EPI was detected by 13С-mixed triglyceride breath test (13С-MTBT) in all the patients. RESULTS: Results: The result of 13С-MTBT indicates EPI in the examined subjects of the 2 group. A significant decrease in the maximum concentration of 13СО2 between 150 and 210 min was also diagnosed in group 1 patients. research (up to 8.2 ± 0.9% - p < 0.05), however, the total concentration of 13СО2 at the end of 360 min. the study reached only 27.7 ± 1.1% (p < 0.05). CONCLUSION: Conclusions: Based on the results of laboratory-instrumental methods of research, patients with NAFLD and type 2 diabetes with COVID-19 were diagnosed with severe EPI. The results of 13С-MTBT in NAFLD and IR with COVID-19 indicate a decrease in the functional reserves of the pancreas and the formation of its EPI.

Identifying potential breath biomarkers for early diagnosis of papillary thyroid cancer based on solid-phase microextraction gas chromatography-high resolution mass spectrometry with metabolomics.

INTRODUCTION: Thyroid cancer incidence rate has increased substantially worldwide in recent years. Fine needle aspiration biopsy (FNAB) is currently the golden standard of thyroid cancer diagnosis, which however, is invasive and costly. In contrast, breath analysis is a non-invasive, safe and simple sampling method combined with a promising metabolomics approach, which is suitable for early cancer diagnosis in high volume population. OBJECTIVES: This study aims to achieve a more comprehensive and definitive exhaled breath metabolism profile in papillary thyroid cancer patients (PTCs). METHODS: We studied both end-tidal and mixed expiratory breath, solid-phase microextraction gas chromatography coupled with high resolution mass spectrometry (SPME-GC-HRMS) was used to analyze the breath samples. Multivariate combined univariate analysis was applied to identify potential breath biomarkers. RESULTS: The biomarkers identified in end-tidal and mixed expiratory breath mainly included alkanes, olefins, enols, enones, esters, aromatic compounds, and fluorine and chlorine containing organic compounds. The area under the curve (AUC) values of combined biomarkers were 0.974 (sensitivity: 96.1%, specificity: 90.2%) and 0.909 (sensitivity: 98.0%, specificity: 74.5%), respectively, for the end-tidal and mixed expiratory breath, indicating of reliability of the sampling and analysis method CONCLUSION: This work not only successfully established a standard metabolomic approach for early diagnosis of PTC, but also revealed the necessity of using both the two breath types for comprehensive analysis of the biomarkers.

Evaluation of urea breath test as a diagnostic tool for Helicobacter pylori infection in adult dyspeptic patients.

In this editorial, we discuss the article in the World Journal of Gastroenterology. The article conducts a meta-analysis of the diagnostic accuracy of the urea breath test (UBT), a non-invasive method for detecting Helicobacter pylori (H. pylori) infection in humans. It is based on radionuclide-labeled urea. Various methods, both invasive and non-invasive, are available for diagnosing H. pylori infection, including endoscopy with biopsy, serology for immunoglobulin titers, stool antigen analysis, and UBT. Several guidelines recommend UBTs as the primary choice for diagnosing H. pylori infection and for reexamining after eradication therapy. It is used to be the first choice non-invasive test due to their high accuracy, specificity, rapid results, and simplicity. Moreover, its performance remains unaffected by the distribution of H. pylori in the stomach, allowing a high flow of patients to be tested. Despite its widespread use, the performance characteristics of UBT have been inconsistently described and remain incompletely defined. There are two UBTs available with Food and Drug Administration approval: The 13C and 14C tests. Both tests are affordable and can provide real-time results. Physicians may prefer the 13C test because it is non-radioactive, compared to 14C which uses a radioactive isotope, especially in young children and pregnant women. Although there was heterogeneity among the studies regarding the diagnostic accuracy of both UBTs, 13C-UBT consistently outperforms the 14C-UBT. This makes the 13C-UBT the preferred diagnostic approach. Furthermore, the provided findings of the meta-analysis emphasize the significance of precise considerations when choosing urea dosage, assessment timing, and measurement techniques for both the 13C-UBT and 14C-UBT, to enhance diagnostic precision.