Peking University Yao Maosheng's team has developed a non-invasive rapid screening technology for new coronary pneumonia based on the fingerprint of exhaled breath volatile organic compounds

The novel coronavirus infection (COVID-19) epidemic is still ongoing in many parts of the world, and rapid screening for COVID-19 is essential to contain its pandemic and return to normal life

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However, the existing nucleic acid detection still has shortcomings in terms of detection time and sensitivity, especially the risk of missed detection by lifting the isolation under the condition of false negative nucleic acid

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At present, only epidemic prevention codes and temperature monitoring strategies are adopted in important public places, which poses a great challenge to the investigation of patients who are in the incubation period or asymptomatic

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Therefore, relying solely on nucleic acid testing still has public health and safety risks, and new testing methods and technologies are urgently needed

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Recently, Professor Yaosheng from the School of Environmental Science and Engineering of Peking University and Beijing Chaoyang District Center for Disease Control and Prevention and other cooperative teams have integrated exhaled breath sampling, gas chromatography-ion mobility spectrum detection and machine learning models to develop a non-invasive exhalation screen for new crown infections.

Check the system (TestBreathNow-TBN)

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The research team used the system to analyze the exhaled breath samples of 74 patients with COVID-19, 30 patients with non-COVID-19 respiratory infections, 87 medical staff and healthy subjects and their background ambient air, and identified 12 key types of exhaled breath.

VOCs marker species

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The study found that the level of propanol in the exhaled breath of patients with new crowns and other respiratory system patients was significantly higher than that of healthy subjects, while the level of acetone in the exhaled breath of patients with new crowns was significantly lower than that of patients with other respiratory infections and healthy subjects

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Using support vector (SVM), gradient acceleration (GBM) and random forests (Random Forests) three machine learning algorithms to model 12 key exhaled breath VOCs markers, which can accurately distinguish patients with COVID-19 from other respiratory infections other than COVID-19 For patients, based on the existing data model, the specificity and sensitivity are more than 95%, and the area under the acceptance curve (AUC)>0.95

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The sampling process of this test method is completely non-invasive.
The subject uses a disposable breathing bag and only needs to exhale 30 seconds to complete the sample collection; the test system program is simple to operate, does not require any test reagents, and combines the machine learning model with the fastest Rapid screening of new crown patients can be achieved within 5-10 minutes, and the cost of a single test is significantly reduced
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The system is currently planning to further optimize and test
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The system is expected to play an additional auxiliary role in addition to nucleic acid testing in the following situations in the rapid screening of new crowns to reduce the risk of new crown pneumonia: new crowns screening that requires rapid decision-making; screening for false negative nucleic acid tests; important high-level meetings; customs immigration; rapid screening special flight personnel; screening before discharge or when released from quarantine and isolation in the hotel, admitted to hospitals and other key sites, and so on
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The use of this technology to carry out rapid auxiliary screening for new coronary pneumonia in these special places and scenarios can contribute additional positive forces to the prevention and control of the new coronary pneumonia epidemic in China under the new normal
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Schematic diagram of the principle of the non-invasive rapid exhalation screening system for new crown infection (TestBreathNow-TBN)

 

Simulated display of the non-invasive rapid exhalation screening system for COVID-19 infection (TestBreathNow-TBN)

The research results were published as a pre-printed version on June 24 last year.
Recently, they were published online in the Journal of Breath Research under the title " COVID-19 Screening Using Breath-borne Volatile Organic Compounds " and applied for a national invention patent.
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Doctoral student Chen Haoxuan (currently engaged in postdoctoral research in the United States) of Peking University School of Environment, Qi Xiao of Chaoyang Center for Disease Control, Ph.D.
students Zhang Lu and Li Xinyue of Peking University School of Environmental Sciences are the co-first authors of the paper, and Maosheng is the corresponding author .
Also involved in this work are Ma Jianxin, Chief of the Epidemiology and Endemic Disease Control Department of Chaoyang Center for Disease Control and Prevention, and Professor Feng Huasong and Director Zhang Chunyang of the Respiratory Department of the Sixth Medical Center of the Chinese People's Liberation Army General Hospital .
This project is mainly funded by the National Science Fund for Distinguished Young Scholars of the National Natural Science Foundation of China (Fund No.21725701), the New Crown Special Project of the National Natural Science Foundation of China (Fund No.22040101) and Guangzhou Laboratory (EKPG21-02) .