Browsing by Subject "Exhaled breath"

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    A Concise Review of Exhaled Breath Testing for Respiratory Clinicians and Researchers
    (Mary Ann Liebert, 2024-04-22) Wang, Ran; Davis, Michael D.; Pediatrics, School of Medicine
    Exhaled breath contains an extensive reservoir of biomolecules. The collection of exhaled breath is noninvasive and low risk. Therefore, its testing is an appealing strategy for the discovery of biomarkers of respiratory diseases. In this concise review, we summarize the evidence of exhaled breath tests for airways diseases and respiratory infections. An overview of breath collection methods in both individuals who are spontaneously breathing and those receiving mechanical ventilation is outlined. We also highlight the challenges in exhaled breath testing and areas for future research.
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    Steps toward clinical validation of exhaled volatile organic compound biomarkers for hypoglycemia in persons with type 1 diabetes
    (Springer Nature, 2025-05-25) Woollam, Mark; Angarita-Rivera, Paula; Thakur, Sanskar; Daneshkhah, Ali; Siegel, Amanda P.; Hardin, Dana S.; Agarwal, Mangilal; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    Persons with type 1 diabetes (T1D) must track/control their blood glucose (BG) levels to avoid hypoglycemic events (BG < 70 mg/dL), which in the most severe cases can lead to seizures or even death. Canines may lead the way toward innovative testing solutions, as they can be trained to identify hypoglycemia simply and noninvasively by smelling exhaled volatile organic compounds (VOCs). To identify breath-based biomarkers of hypoglycemia, samples were collected during two consecutive summers at a diabetes camp (Cohort 1 and Cohort 2), and VOCs were analyzed by gas chromatography-mass spectrometry. Conserved VOCs between the two cohorts were identified, but individual VOCs alone had low accuracies for detection. Therefore, supervised multivariate statistical analysis was undertaken to identify a biosignature in the training data set (Cohort 1) that could detect hypoglycemia with higher accuracy (sensitivity = 94.8%/specificity = 95.0%). When this model was blindly tested on Cohort 2, hypoglycemia was classified with sensitivity = 90.0%/specificity = 89.9%. Ultimately, this study makes strides toward clinical validation through verifying biomarkers of hypoglycemia in hundreds of breath samples. These results may be translated to design a sensor array that could be integrated into a portable breathalyzer to increase glycemic control in persons with T1D.