Chakaya J, Khan M, Ntoumi F, Aklillu E, Fatima R, Mwaba P, Kapata N, Mfinanga S, Hasnain SE, Katoto PDMC, et al. Global tuberculosis report 2020—reflections on the Global TB burden, treatment and prevention efforts. Int J Infect Dis. 2021;113:S7–12.
Keeler E, Perkins MD, Small P, Hanson C, Reed S, Cunningham J, Aledort JE, Hillborne L, Rafael ME, Girosi F, et al. Reducing the global burden of tuberculosis: the contribution of improved diagnostics. Nature. 2006;444(1):49–57.
World Health O. WHO consolidated guidelines on tuberculosis: module 3: diagnosis: rapid diagnostics for tuberculosis detection, 2021 update edn. Geneva: World Health Organization; 2021.
Parsons LM, Somoskövi A, Gutierrez C, Lee E, Paramasivan CN, Abimiku AL, Spector S, Roscigno G, Nkengasong J. Laboratory diagnosis of tuberculosis in resource-poor countries: challenges and opportunities. Clin Microbiol Rev. 2011;24(2):314–50.
Datta S, Evans CA. The uncertainty of tuberculosis diagnosis. Lancet Infect Dis. 2020;20:1002–4.
Gopi A, Madhavan SM, Sharma SK, Sahn SA. Diagnosis and treatment of tuberculous pleural effusion in 2006. Chest. 2007;131(3):880–9.
Jeon D. Tuberculous pleurisy: an update. Tubercul Respir Dis. 2014;76(4):153–9.
Theron G, Peter J, Meldau R, Khalfey H, Gina P, Matinyena B, Lenders L, Calligaro G, Allwood B, Symons G, et al. Accuracy and impact of Xpert MTB/RIF for the diagnosis of smear-negative or sputum-scarce tuberculosis using bronchoalveolar lavage fluid. Thorax. 2013;68(11):1043–51.
Yang J, Shen Y, Wang L, Ju L, Wu X, Wang P, Hao X, Sun Q, Yu F, Sha W. Efficacy of the Xpert Mycobacterium tuberculosis/rifampicin assay for diagnosing sputum-smear negative or sputum-scarce pulmonary tuberculosis in bronchoalveolar lavage fluid. Int J Infect Dis. 2021;107:121–6.
WHO. High priority target product profiles for new tuberculosis diagnostics. In: Report of a consensus meeting. Geneva, Switzerland; 2014.
Fowler SJ, Basanta-Sanchez M, Xu Y, Goodacre R, Dark PM. Surveillance for lower airway pathogens in mechanically ventilated patients by metabolomic analysis of exhaled breath: a case–control study. Thorax. 2015;70(4):320–5.
Rattray NJ, Hamrang Z, Trivedi DK, Goodacre R, Fowler SJ. Taking your breath away: metabolomics breathes life in to personalized medicine. Trends Biotechnol. 2014;32(10):538–48.
Saktiawati AMI, Putera DD, Setyawan A, Mahendradhata Y, van der Werf TS. Diagnosis of tuberculosis through breath test: a systematic review. EBioMedicine. 2019;46:202–14.
Beale DJ, Pinu FR, Kouremenos KA, Poojary MM, Narayana VK, Boughton BA, Kanojia K, Dayalan S, Jones OAH, Dias DA. Review of recent developments in GC–MS approaches to metabolomics-based research. Metabolomics. 2018;14(11):152.
Papadimitropoulos MP, Vasilopoulou CG, Maga-Nteve C, Klapa MI. Untargeted GC–MS metabolomics. Methods Mol Biol (Clifton, NJ). 2018;1738:133–47.
Mochalski P, Shuster G, Leja M, Unterkofler K, Jaeschke C, Skapars R, Gasenko E, Polaka I, Vasiljevs E, Shani G, et al. Non-contact breath sampling for sensor-based breath analysis. J Breath Res. 2019;13(3): 036001.
Phillips M, Cataneo RN, Condos R, Ring Erickson GA, Greenberg J, La Bombardi V, Munawar MI, Tietje O. Volatile biomarkers of pulmonary tuberculosis in the breath. Tuberculosis. 2007;87(1):44–52.
Phillips M, Basa-Dalay V, Bothamley G, Cataneo RN, Lam PK, Natividad MPR, Schmitt P, Wai J. Breath biomarkers of active pulmonary tuberculosis. Tuberculosis. 2010;90(2):145–51.
Beccaria M, Bobak C, Maitshotlo B, Mellors T, Purcaro G, Franchina F, Rees C, Nasir M, Black A, Hill J. Exhaled human breath analysis in active pulmonary tuberculosis diagnostics by comprehensive gas chromatography–mass spectrometry and chemometric techniques. J Breath Res. 2018;13:016005.
Beccaria M, Mellors TR, Petion JS, Rees CA, Nasir M, Systrom HK, Sairistil JW, Jean-Juste M-A, Rivera V, Lavoile K, et al. Preliminary investigation of human exhaled breath for tuberculosis diagnosis by multidimensional gas chromatography–time of flight mass spectrometry and machine learning. J Chromatogr B. 2018;1074–1075:46–50.
Bobak CA, Kang L, Workman L, Bateman L, Khan MS, Prins M, May L, Franchina FA, Baard C, Nicol MP, et al. Breath can discriminate tuberculosis from other lower respiratory illness in children. Sci Rep. 2021;11(1):2704.
Bruins M, Rahim Z, Bos A, van de Sande WWJ, Endtz HP, van Belkum A. Diagnosis of active tuberculosis by e-nose analysis of exhaled air. Tuberculosis. 2013;93(2):232–8.
Nakhleh MK, Jeries R, Gharra AL, Binder A, Broza YY, Pascoe M, Dheda K, Haick H. Detecting active pulmonary tuberculosis with a breath test using nanomaterial-based sensors. Eur Respir J. 2014;43(5):1522–5.
Mohamed EI, Mohamed MA, Moustafa MH, Abdel-Mageed SM, Moro AM, Baess AI, El-Kholy SM. Qualitative analysis of biological tuberculosis samples by an electronic nose-based artificial neural network. Int J Tuberculosis Lung Dis. 2017;21(7):810–7.
Trefz P, Schmidt M, Oertel P, Obermeier J, Brock B, Kamysek S, Dunkl J, Zimmermann R, Schubert JK, Miekisch W. Continuous real time breath gas monitoring in the clinical environment by proton-transfer-reaction-time-of-flight-mass spectrometry. Anal Chem. 2013;85(21):10321–9.
Gaugg MT, Bruderer T, Nowak N, Eiffert L, Martinez-Lozano Sinues P, Kohler M, Zenobi R. Mass-spectrometric detection of omega-oxidation products of aliphatic fatty acids in exhaled breath. Anal Chem. 2017;89(19):10329–34.
Singh KD, Del Miguel GV, Gaugg MT, Ibañez AJ, Zenobi R, Kohler M, Frey U, Sinues PM. Translating secondary electrospray ionization-high-resolution mass spectrometry to the clinical environment. J Breath Res. 2018;12(2): 027113.
Wang Y, Jiang J, Hua L, Hou K, Xie Y, Chen P, Liu W, Li Q, Wang S, Li H. High-pressure photon ionization source for TOFMS and its application for online breath analysis. Anal Chem. 2016;88(18):9047–55.
Huang Q, Wang S, Li Q, Wang P, Li J, Meng S, Li H, Wu H, Qi Y, Li X, et al. Assessment of breathomics testing using high-pressure photon ionization time-of-flight mass spectrometry to detect esophageal cancer. JAMA Netw Open. 2021;4(10): e2127042.
Meng S, Li Q, Zhou Z, Li H, Liu X, Pan S, Li M, Wang L, Guo Y, Qiu M, et al. Assessment of an exhaled breath test using high-pressure photon ionization time-of-flight mass spectrometry to detect lung cancer. JAMA Netw Open. 2021;4(3): e213486.
Wang P, Huang Q, Meng S, Mu T, Liu Z, He M, Li Q, Zhao S, Wang S, Qiu M. Identification of lung cancer breath biomarkers based on perioperative breathomics testing: a prospective observational study. EClinicalMedicine. 2022;47: 101384.
Zhao X, Liu X, Liu J, Chen J, Fu S, Zhong F. The effect of ionization energy and hydrogen weight fraction on the non-thermal plasma volatile organic compounds removal efficiency. J Phys D Appl Phys. 2019;52(14): 145201.
Lee G, Gommers R, Waselewski F, Wohlfahrt K, O’Leary A. PyWavelets: a Python package for wavelet analysis. J Open Source Softw. 2019;4:1237.
Breiman L. Random forests. Mach Learn. 2001;45(1):5–32.
Suthaharan S. Support vector machine. In: Suthaharan S, editor. Machine learning models and algorithms for big data classification: thinking with examples for effective learning. Boston: Springer; 2016. p. 207–35.
Bewick V, Cheek L, Ball J. Statistics review 14: logistic regression. Crit Care. 2005;9(1):112–8.
Deng L, Sui Y, Zhang J. XGBPRH: prediction of binding hot spots at protein–RNA interfaces utilizing extreme gradient boosting. LID. doi.org/10.3390/genes10030242.242: 2073–4425.
Jordan MI. A statistical approach to decision tree modeling. In: COLT '94: 1994; 1994.
Kuo TC, Tan CE, Wang SY, Lin OA, Su BH, Hsu MT, Lin J, Cheng YY, Chen CS, Yang YC, et al. Human breathomics database. Database (Oxford) 2020; 1758–0463 (Electronic)).
Kinoyama M, Nitta H, Watanabe A, Ueda H. Acetone and isoprene concentrations in exhaled breath in healthy subjects. J Health Sci. 2008;54:471–7.
Arashiro M, Lin Y-H, Zhang Z, Sexton KG, Gold A, Jaspers I, Fry RC, Surratt JD. Effect of secondary organic aerosol from isoprene-derived hydroxyhydroperoxides on the expression of oxidative stress response genes in human bronchial epithelial cells. Environ Sci Process Impacts. 2018;20(2):332–9.
Alkhouri N, Singh T, Alsabbagh E, Guirguis J, Chami T, Hanouneh I, Grove D, Lopez R, Dweik R. Isoprene in the exhaled breath is a novel biomarker for advanced fibrosis in patients with chronic liver disease: a pilot study. 2015; 6.
Wang Z, Wang C. Is breath acetone a biomarker of diabetes? A historical review on breath acetone measurements. J Breath Res. 2013;7(3): 037109.
Du Q, Wang L, Long Q, Zhao Y, Abdullah AS. Systematic review and meta-analysis: Prevalence of diabetes among patients with tuberculosis in China. Tropical Med Int Health. 2021;26(12):1553–9.
Vishinkin R, Busool R, Mansour E, Fish F, Haick H. Profiles of volatile biomarkers detect tuberculosis from skin. Adv Sci. 2021.
Denkinger C, Kik S, Cirillo D, Casenghi M, Shinnick T, Weyer K, Gilpin C, Boehme C, Schito M, Kimerling M, et al. Defining the needs for next generation assays for tuberculosis. J Infect Dis. 2015;211:S29–38.
Bhatter P, Raman K, Janakiraman V. Elucidating the biosynthetic pathways of volatile organic compounds in Mycobacterium tuberculosis through a computational approach. Mol BioSyst. 2017;13(4):750–5.
Küntzel A, Oertel P, Fischer S, Bergmann A, Trefz P, Schubert J, Miekisch W, Reinhold P, Köhler H. Comparative analysis of volatile organic compounds for the classification and identification of mycobacterial species. PLoS ONE. 2018;13(3): e0194348.
