Summary: Background: SARS-CoV-2 is a novel human coronavirus, there is no specific antiviral drugs. It has been proved that host-cell-expressed CD147 could bind spike protein of SARS-CoV-2 and involve in host cell invasion. Antibody against CD147 could block the infection of SARS-CoV-2. We aimed to assess the efficacy and safety of meplazumab, a humanized anti-CD147 antibody, as add-on therapy in patients with COVID-19 pneumonia. Methods: All patients received recommended strategy from Chinese Clinical Guidance for COVID-19 Pneumonia Diagnosis and Treatments released by National Health Commission of China. Eligible patients were add-on administered 10 mg meplazumab intravenously at days 1, 2, and 5. Patients hospitalized in the same period were observed as concurrent control. The endpoints include virological clearance rate, case severity, chest radiographic, and laboratory test. This trial was approved by the Ethics Committee of Institution at the Tangdu hospital, and registered with ClinicalTrials.gov, NCT 04275245. Findings: 17 patients were enrolled and assigned to meplazumab group between Feb 3, 2020 and Feb 10, 2020. 11 hospitalized patients served as concurrent control. Baseline characteristics were generally balanced across two groups. Compared to control group, meplazumab treatment significantly improved the discharged (p=0.005) and case severity (p=0.021) in patients. The time to virus negative in meplazumab group was reduced than that in control group (median 3, 95%CI[1.5-4.5] vs. 13, [6.5-19.5]; p=0.045, HR=0.374, 95%CI[0.143-0.978]). The percentages of patients recovered to the normal lymphocyte count and CRP concentration were also increased remarkably and rapidly in meplazumab group. No adverse effect was found in meplazumab-treated patients. Interpretation: Meplazumab efficiently improved the recovery of patients with SARS-CoV-2 pneumonia with a favorable safety profile. Our results support to carry out a large-scale investigation of meplazumab as a treatment for COVID-19 pneumonia. Funding: National Science and Technology Major Project.

Background: Latent tuberculosis infection (LTBI) is the primary source of active tuberculosis (ATB), but a preventive vaccine against LTBI is lacking. Methods: In this study, dominant helper T lymphocyte (HTL), cytotoxic T lymphocyte (CTL), and B-cell epitopes were identified from nine antigens related to LTBI and regions of difference (RDs). These epitopes were used to construct a novel multiepitope vaccine (MEV) based on their antigenicity, immunogenicity, sensitization, and toxicity. The immunological characteristics of the MEV were analyzed with immunoinformatics technology and verified by enzyme-linked immunospot assay and Th1/Th2/Th17 cytokine assay in vitro. Results: A novel MEV, designated PP19128R, containing 19 HTL epitopes, 12 CTL epitopes, 8 B-cell epitopes, toll-like receptor (TLR) agonists, and helper peptides, was successfully constructed. Bioinformatics analysis showed that the antigenicity, immunogenicity, and solubility of PP19128R were 0.8067, 9.29811, and 0.900675, respectively. The global population coverage of PP19128R in HLA class I and II alleles reached 82.24% and 93.71%, respectively. The binding energies of the PP19128R-TLR2 and PP19128R-TLR4 complexes were −1324.77 kcal/mol and −1278 kcal/mol, respectively. In vitro experiments showed that the PP19128R vaccine significantly increased the number of interferon gamma-positive (IFN-γ⁺) T lymphocytes and the levels of cytokines, such as IFN-γ, tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and IL-10. Furthermore, positive correlations were observed between PP19128R-specific cytokines in ATB patients and individuals with LTBI. Conclusions: The PP19128R vaccine is a promising MEV with excellent antigenicity and immunogenicity and no toxicity or sensitization that can induce robust immune responses in silico and in vitro. This study provides a vaccine candidate for the prevention of LTBI in the future.

Summary: Pegylated interferon and ribavirin combination therapy is known to be effective in suppressing viral replication in 50–60% of hepatitis C virus (HCV) ‐infected patients. However, HCV‐infected patients often exhibit varied responses to therapy. Therefore, the identification of immunological markers associated with the clinical outcomes of antiviral treatment is critical for improvement of therapeutic options. In this study, we aimed to investigate the ratio of CD4⁺ CD25⁺ FoxP3⁺ regulatory T (Treg) cells to interleukin‐17A (IL‐17A) ‐producing T helper type 17 (Th17) cells, and its association with clinical outcomes in response to anti‐HCV treatment. In all, 114 patients with HCV infection received pegylated interferon‐α2a and ribavirin therapy for 48 weeks, and the frequency of Treg cells and Th17 cells as well as the levels of secreted cytokines were longitudinally analysed by flow cytometry and ELISA. Treg cell proportions and IL‐10 production were significantly elevated in HCV‐infected patients, especially for HCV genotype 1b. However, the frequency of Th17 cells as well as the secretion of IL‐17, IL‐22 and IL‐23 did not reveal notable difference between HCV infections and healthy individuals. Inhibition of HCV replication was accompanied by a reduction in Treg cells, but little influence on Th17 cells, which led to a significant decrease in Treg : Th17 ratios. Skewed Treg : Th17 ratios existed in chronic hepatitis C. HCV RNA load is closely associated with Treg : Th17 ratios during pegylated interferon‐α2a and ribavirin treatment in HCV‐infected patients. The imbalance of Treg cells to Th17 cells might play an important role in persistent HCV infection.

As an emergent and fulminant infectious disease, Corona Virus Disease 2019 (COVID-19) has caused a worldwide pandemic. The early identification and timely treatment of severe patients are crucial to reducing the mortality of COVID-19. This study aimed to investigate the clinical characteristics and early predictors for severe COVID-19, and to establish a prediction model for the identification and triage of severe patients. All confirmed patients with COVID-19 admitted by the Second Affiliated Hospital of Air Force Medical University were enrolled in this retrospective non-interventional study. The patients were divided into a mild group and a severe group, and the clinical data were compared between the two groups. Univariate and multivariate analysis were used to identify the independent early predictors for severe COVID-19, and the prediction model was constructed by multivariate logistic regression analysis. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of the prediction model and each early predictor. A total of 40 patients were enrolled in this study, of whom 19 were mild and 21 were severe. The proportions of patients with venerable age (≥60 years old), comorbidities, and hypertension in severe patients were higher than that of the mild (P < 0.05). The duration of fever and respiratory symptoms, and the interval from illness onset to viral clearance were longer in severe patients (P < 0.05). Most patients received at least one form of oxygen treatments, while severe patients required more mechanical ventilation (P < 0.05). Univariate and multivariate analysis showed that venerable age, hypertension, lymphopenia, hypoalbuminemia and elevated neutrophil lymphocyte ratio (NLR) were the independent high-risk factors for severe COVID-19. ROC curves demonstrated significant predictive value of age, lymphocyte count, albumin and NLR for severe COVID-19. The sensitivity and specificity of the newly constructed prediction model for predicting severe COVID-19 was 90.5% and 84.2%, respectively, and whose positive predictive value, negative predictive value and crude agreement were all over 85%. The severe COVID-19 risk model might help clinicians quickly identify severe patients at an early stage and timely take optimal therapeutic schedule for them.