Background: SARS-CoV-2 has caused a tremendous threat to global health. PCR and antigen testing have played a prominent role in the detection of SARS-CoV-2-infected individuals and disease control. An efficient, reliable detection tool is still urgently needed to halt the global COVID-19 pandemic. Recently, FDA emergency approved VOC as an alternative test for COVID-19 detection. Methods and materials: In this case-control study, we prospectively and consecutively recruited 95 confirmed COVID-19 patients and 106 healthy controls in the designated hospital for treatment of COVID-19 patients in Shenzhen, China. Exhaled breath samples were collected and stored in customized bags and then detected by HPPI-TOFMS for volatile organic components (VOCs). Machine learning (ML) algorithms were employed for COVID-19 detection model construction. Participants were randomly assigned in a 5:2:3 ratio to the training, validation, and blinded test sets. The sensitivity (SEN), specificity (SPE), and other general metrics were employed for the VOCs based COVID-19 detection model performance evaluation. Results: The VOCs based COVID-19 detection model achieved good performance, with a SEN of 92.2% (95% CI: 83.8%, 95.6%), a SPE of 86.1% (95% CI: 74.8%, 97.4%) on blinded test set. Five potential VOC ions related to COVID-19 infection were discovered, which are significantly different between COVID-19 infected patients and controls. Conclusions: This study evaluated a simple, fast, non-invasive VOCs-based COVID-19 detection method and demonstrated that it has good sensitivity and specificity in distinguishing COVID-19 infected patients from controls. It has great potential for fast and accurate COVID-19 detection.

Background: Diabetes mellitus (DM) is believed to affect tuberculosis (TB) at multiple levels in disease control and treatment efficacy, but clinical and radiological presentation resulting from interaction of the two diseases is not known. Methods: A cross-sectional study was conducted on data obtained from medical records of 438 patients confirmed with TB-DM comorbidity at the Third people's hospital of Shenzhen from May 01, 2014, to April 30, 2019. Their CT images were reviewed, and patients were divided into subgroups according to lung cavitation: with and without cavities, and number of segments showing pulmonary infiltration: <4 segment, 4-8 segment, >8 segment infiltrates. We then compared clinical parameters between these groups. Results: The median age of the patients was 50.0 years (IQR 43.3-56.0) and 86% (n=375) of them were male. Pulmonary cavities were found in 80.8% patients. About 42.7% and 27.2% patients were seen to have infiltration involving 4-8 and >8 lung segments, respectively. Patients presented with cavitation and infiltration involving a greater number of lung segments had significantly higher values of WBC, MONO%, GRA%, CRP, lower LYN% level and higher bacterial burden in sputum (P<0.001). Higher HbA1c and FBG were only observed in patients with lung cavities (P<0.001). There was no difference in positive ELISPOT.TB and PCT level between the groups regardless of presence or absence of lung cavity (P>0.9 and P=0.1 respectively). Lower HGB, ALB and higher PCT were observed in patients with infiltration involving more lung segments. Conclusion: Hyper-inflammation in peripheral blood was significantly associated with cavity and the number of lung lesions. Hyperglycemia was significantly associated with the development of lung cavity. Glycemic control and inflammation influenced radiographic manifestations in patients with TB-DM.

It is estimated that Mycobacterium tuberculosis (M.tb) infected a quarter of the world's population (1). Latent tuberculosis infection (LTBI) constitutes a broad spectrum of infection states that differ by the degree of pathogen replication, host immune response, and inflammation (2). Approximately 5-10% of those with LTBI will progress to active tuberculosis (ATB) (3). WHO recommends immunodiagnostic tests for LTBI detection, either a tuberculin skin test (TST) or interferon-gamma (IFN-γ) release assays (IGRAs) (4). However, these tests are not precise enough. In certain situations, TB exposure can be used as a surrogate for LTBI (5). Furthermore, TST and IGRAs can not differentiate LTBI from ATB (6). Thus, a more precise tool is urgently needed for the consecutive management of uninfected status, LTBI, and ATB.Recent studies indicate that breathomics may be a useful rule-in or rule-out tool for diagnosing ATB (7), which uncovers the host-pathogen interaction via comprehensive exhaled breath analysis. Breathomics may hold promise to distinguish healthy subjects, LTBI and ATB (8) if a breath test can find the trace and tell the difference of M.tb in consecutive states in the host (9). High-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) is designed and developed by our team, which can directly detect volatile organic compounds (VOCs) in exhaled breath (10). In our previous studies, this breath detection platform has been verified in lung cancer (11,12), esophagus cancer (13), and Corona Virus Disease 2019 . In this study, we explored the use of this novel, rapid, simple, and inexpensive breath test to detect LTBI.We conducted a cross-sectional study (Chinese Clinical Trials Registry number: ChiCTR2200058346) in which a breath sample was collected from 435 participants with informed consent signed at the Third

Purpose: Diabetes mellitus (DM) is believed to affect tuberculosis (TB) at multiple levels in disease control and treatment efficacy, but clinical and radiological presentation resulting from interaction of the two diseases is not known. We conducted a retrospective study to investigate how glycemic control impacts radiological and clinical manifestations in TB patients. Methods: A cross-sectional study was conducted on data obtained from medical records of 438 patients confirmed with TB-DM comorbidity at The Third people’s hospital of Shenzhen from April 1, 2014 to April 30, 2019. Their CT images were reviewed, and patients were divided into subgroups according to lung cavitation: with and without cavities, and number of segments showing pulmonary infiltration: <4 segment, 4-8 segment, >8 segment infiltrates. We then compared clinical parameters between these groups. Results: The median age of the patients was 50.0 years (IQR 43.3-56) and 86% (n=375) of them were male. Pulmonary cavities were found in 80.8% patients. 42.7% and 27.2% patients were seen to have infiltration involving 4-8 and >8 lung segments respectively. Patients presented with cavitation and infiltration involving a greater number of lung segments had significantly higher values of WBC, MONO%, GRA%, CRP, lower LYN% level and higher bacterial burden in sputum (P<0.001). Higher HbA1c and FBG were only observed in patients with lung cavities (P<0.001). There was no difference in positive ELISPOT.TB and PCT level between the groups regardless of presence or absence of lung cavity (P>0.9 and P=0.1 respectively). Lower HGB, ALB and higher PCT were observed in patients with infiltration involving more lung segments.Conclusion: Hyper-inflammation in peripheral blood was significantly associated with cavity and the number of lung lesions. Hyperglycemia was significantly associated with the development of lung cavity. Glycemic control and inflammation influenced radiographic manifestations in patients with TB-DM.