In December 2019, an outbreak of COVID-19 occurred in Wuhan, China, and spread to the whole of China and to multiple countries worldwide. Unlike SARS and MERS, where secondary transmission mostly occurred in hospital settings, COVID-19 transmission occurs in large numbers within families. Herein we report three cases of a familial cluster with one family member being a kidney transplant recipient. The initial clinical symptoms of COVID-19 in these three patients were the same, but their progression was different. Based on the severity of clinical symptoms, chest computer tomography findings and SARS-Cov-2 RNA test results, we admitted the husband to the respiratory intensive care unit (RICU) and used a treatment consisting of immunosuppressant reduction/cessation and low dose methylprednisolone-based therapy, and his wife to the respiratory isolation ward. In contrast, the son received in-home isolation and home-based care. All three family members made a full recovery.

Hexokinase catalyzes the first rate-limiting step glycolysis. However, the roles of hexokinase 2 (HK2) in asthma remain incompletely understood. This study aimed to investigate metabolic alterations in asthma, focusing on the expression, function and regulation of HK2. In this study, non-targeted metabolomics analysis of 20 asthma patients and 15 healthy controls identified metabolic alterations in asthma, particularly in the glycolytic pathways. Consistently, HK2 expression was elevated in both asthma individuals and mice with allergic airway inflammation. Airway epithelium–specific HK2 knockdown and pharmacological inhibition with 2-deoxy-D-glucose (2-DG) significantly attenuated airway inflammation and hyperresponsiveness in mice induced by ovalbumin/ lipopolysaccharide. Mechanistic analyses demonstrated that HK2 regulates epithelial apoptosis and inflammation via interaction with peptidylprolyl isomerase F (PPIF), independent of voltage-dependent anion channel 1 (VDAC1). Asthma is associated with metabolic reprogramming, characterized by alterations in lipid and glucose metabolism. These findings establish HK2 plays a crucial role in asthma pathogenesis by promoting airway epithelial apoptosis and inflammation in asthma, suggesting its potential as a therapeutic target.

Introduction: The COVID-19 patients in the convalescent stage noticeably have pulmonary diffusing capacity impairment (PDCI). The pulmonary diffusing capacity is a frequently-used indicator of the COVID-19 survivors’ prognosis of pulmonary function, but the current studies focusing on prediction of the pulmonary diffusing capacity of these people are limited. The aim of this study was to develop and validate a machine learning (ML) model for predicting PDCI in the COVID-19 patients using routinely available clinical data, thus assisting the clinical diagnosis. Methods: Collected from a follow-up study from August to September 2021 of 221 hospitalized survivors of COVID-19 18 months after discharge from Wuhan, including the demographic characteristics and clinical examination, the data in this study were randomly separated into a training (80%) data set and a validation (20%) data set. Six popular machine learning models were developed to predict the pulmonary diffusing capacity of patients infected with COVID-19 in the recovery stage. The performance indicators of the model included area under the curve (AUC), Accuracy, Recall, Precision, Positive Predictive Value(PPV), Negative Predictive Value (NPV) and F1. The model with the optimum performance was defined as the optimal model, which was further employed in the interpretability analysis. The MAHAKIL method was utilized to balance the data and optimize the balance of sample distribution, while the RFECV method for feature selection was utilized to select combined features more favorable to machine learning. Results: A total of 221 COVID-19 survivors were recruited in this study after discharge from hospitals in Wuhan. Of these participants, 117 (52.94%) were female, with a median age of 58.2 years (standard deviation (SD) = 12). After feature selection, 31 of the 37 clinical factors were finally selected for use in constructing the model. Among the six tested ML models, the best performance was accomplished in the XGBoost model, with an AUC of 0.755 and an accuracy of 78.01% after experimental verification. The SHAPELY Additive explanations (SHAP) summary analysis exhibited that hemoglobin (Hb), maximal voluntary ventilation (MVV), severity of illness, platelet (PLT), Uric Acid (UA) and blood urea nitrogen (BUN) were the top six most important factors affecting the XGBoost model decision-making. Conclusion: The XGBoost model reported here showed a good prognostic prediction ability for PDCI of COVID-19 survivors during the recovery period. Among the interpretation methods based on the importance of SHAP values, Hb and MVV contributed the most to the prediction of PDCI outcomes of COVID-19 survivors in the recovery period.

Vaccines are the most effective and feasible way to control pathogen infection. Helminths have been reported to jeopardize the protective immunity mounted by several vaccines. However, there are no experimental data about the effect of helminth infection on the effectiveness of COVID-19 vaccines. Here, a mouse model of trichinosis, a common zoonotic disease worldwide, was used to investigate effects of Trichinella spiralis infection on the RBD protein vaccine of SARS-CoV-2 and the related immunological mechanism, as well as the impact of albendazole (ALB) deworming on the inhibitory effect of the parasite on the vaccination. The results indicated that both the enteric and muscular stages of T. spiralis infection inhibited the vaccine efficacy, evidenced by decreased levels of IgG, IgM, sIgA, and reduced serum neutralizing antibodies, along with suppressed splenic germinal center (GC) B cells in the vaccinated mice. Pre-exposure to trichinosis promoted Th2 and/or Treg immune responses in the immunized mice. Furthermore, ALB treatment could partially reverse the inhibitory effect of T. spiralis infection on the efficiency of the vaccination, accompanied by a restored proportion of splenic GC B cells. Therefore, given the widespread prevalence of helminth infections worldwide, deworming therapy needs to be considered when implementing COVID-19 vaccination strategies.

Objectives: Population screening for IgG and IgM against SARS-CoV-2 was initiated on March 25 and was open to all residents of Wuhan who were symptom-free. All ages with no fever, headache or other symptoms of COVID-19 among residents in Wuhan were included. Methods: This study adopted a cross-sectional study. Pearson Chi-square test, T-test, and Mann-Whitney test were used in comparison between different groups. To correct the effects of gender and age, the seroprevalence of IgM positivity, IgG positivity, and IgM and/or IgG positivity were standardized according to the gender and age-specific population of Wuhan in 2017. Results: The seroprevalence of IgG and IgM standardized for age and gender in Wuhan showed a downward trend. No significant correlation was observed between the seroprevalence of IgG and the different age groups. The seroprevalence was significantly higher for females than males (x ² =35.702, p < 0.001), with an odds ratio of 1.36 (95% CI: 1.24–1.48). A significant difference was seen in the seroprevalence of IgG among people from different geographic areas and different types of workplaces (respectively, x ² = 42.871, p < 0.001 and x ² = 202.43, p < 0.001). The IgG antibody-positive cases had a greater number of abnormalities in CT imaging than IgG-negative cases (30.7% vs 19.7%). Conclusions: Our work found the reported number of confirmed patients in Wuhan only represents a small proportion of the total number of infections. There was a significant aggregation of asymptomatic infections in individuals from some occupations, and based on CT and laboratory findings, some damage may have occurred in asymptomatic individuals positive for IgG antibody. Strengths and limitations of this study: This study has the important feature of having been designed as repeated five-day serosurveys, which allowed for the monitoring of seroprevalence progression. This study applied scientific statistical methods accounting for the demographic structure of the general population and imperfect diagnostic tests to estimate seroprevalence in the overall population. This study had selection bias since the analyzed medical records were based on examinees directed by their work units. People under the age of 19 and over age 65 were too few to be fully covered in analyses.