Objective: The clinical course of COVID-19, as well as the immunological reaction, is notable for its extreme variability. Identifying the main associated factors might help understand the disease progression and physiological status of COVID-19 patients. The dynamic changes of the antibody against Spike protein are crucial for understanding the immune response. This work explores a temporal attention (TA) mechanism of deep learning to predict COVID-19 disease severity, clinical outcomes, and Spike antibody levels by screening serological indicators over time. Methods: We use feature selection techniques to filter feature subsets that are highly correlated with the target. The specific deep Long Short-Term Memory (LSTM) models are employed to capture the dynamic changes of disease severity, clinical outcome, and Spike antibody level. We also propose deep LSTMs with a TA mechanism to emphasize the later blood test records because later records often attract more attention from doctors. Results: Risk factors highly correlated with COVID-19 are revealed. LSTM achieves the highest classification accuracy for disease severity prediction. Temporal Attention Long Short-Term Memory (TA-LSTM) achieves the best performance for clinical outcome prediction. For Spike antibody level prediction, LSTM achieves the best permanence. Conclusion: The experimental results demonstrate the effectiveness of the proposed models. The proposed models can provide a computer-aided medical diagnostics system by simply using time series of serological indicators.

Understanding the complexities of immune memory to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is key to gain insights into the durability of protective immunity against reinfection. We sought to evaluate the immune memory to SARS-CoV-2 in convalescent patients with longer follow-up time. SARS-CoV-2–specific humoral and cellular responses were assessed in convalescent patients with coronavirus disease 2019 (COVID-19) at 1 year postinfection. A total of 78 convalescent patients with COVID-19 (26 moderate, 43 severe, and 9 critical) were recruited after 1 year of recovery. The positive rates of both anti–receptor-binding domain and antinucleocapsid antibodies were 100%, whereas we did not observe a statistical difference in antibody levels among different severity groups. Accordingly, the prevalence of neutralizing antibodies (nAbs) reached 93.59% in convalescent patients. Although nAb titers displayed an increasing trend in convalescent patients with increased severity, the difference failed to achieve statistical significance. Notably, there was a significant correlation between nAb titers and anti–receptor-binding domain levels. Interestingly, SARS-CoV-2–specific T cells could be robustly maintained in convalescent patients, and their number was positively correlated with both nAb titers and anti–receptor-binding domain levels. Amplified SARS-CoV-2–specific CD4⁺ T cells mainly produced a single cytokine, accompanying with increased expression of exhaustion markers including PD-1, Tim-3, TIGIT, CTLA-4, and CD39, while the proportion of multifunctional cells was low. Robust SARS-CoV-2–specific humoral and cellular responses are maintained in convalescent patients with COVID-19 at 1 year postinfection. However, the dysfunction of SARS-CoV-2–specific CD4⁺ T cells supports the notion that vaccination is needed in convalescent patients for preventing reinfection.

Objective: The study aimed to comprehensively describe and evaluate the pathogenic and clinical characteristics of severe fever with thrombocytopenia syndrome (SFTS) patients with co-infections.Methods: We retrospectively collected clinical data and laboratory indicators of the SFTS patients at Tongji Hospital from October 2021 to July 2023.Results: A total of 157 patients with SFTS virus (SFTSV) infection were involved in the analysis, including 43 co-infection and 114 non-co-infection patients. The pathogens responsible for co-infection were primarily isolated from respiratory specimens. Fungal infections, primarily Aspergillus fumigatus, were observed in 22 cases. Bacterial infections, with Klebsiella pneumoniae and carbapenem-resistant Acinetobacter baumannii as the main pathogens, were identified in 20 cases. SFTS patients with co-infection exhibited higher mortality (P=0.011) compared to non-co-infection patients. Among SFTS patients co-infected with both bacteria and fungi (8 cases) or specific drug-resistant strains (11 cases), the mortality rate was as high as 70% (14/19). In comparison with the non-co-infection group, SFTS patients with co-infection displayed significant alteration in inflammatory markers, coagulation function, and liver function indicators.Conclusion: The mortality rate of SFTS patients with co-infection is relatively high, underscoring the need for enhanced monitoring and timely, appropriate treatment to minimize the mortality rate.

Background This study aimed to analyze the dynamic changes of lymphocyte subsets and specific antibodies in coronavirus disease 2019 (COVID‐19) patients with different illness severity. Methods The lymphocyte subsets and IgM and IgG antibody levels were retrospectively analyzed in 707 COVID‐19 cases. Results The amounts of lymphocyte subsets were significantly decreased with the increased severity of illness and the levels of IgM and IgG were lower in critical cases than severe and moderate cases. In deceased patients, the lymphocytes subsets were significantly lower than recovered patients. However, the relationship between the levels of IgM and IgG and the amounts of lymphocyte subsets were not significantly correlated. During different stages of COVID‐19, the total T cell, CD4⁺ T cell and CD8⁺ T cell counts were gradually recovered to the normal levels in severe and critical groups but the change trend was relatively stable in moderate group. The production of IgM and IgG antibodies were delayed in critical groups but also could reach the peak levels at one month after illness onset and decreased to background levels. Conclusion To detect the kinetics of lymphocytes and antibodies has important clinical value in predicting the illness severity and understanding the pathogenesis of COVID‐19.

Background: This study aimed to assess the host immune signatures associated with EBV infection and its clinical value in indicating the severity of children with acute infectious mononucleosis (IM).Methods: Twenty-eight pediatric patients with IM aged 3–8 years were enrolled. The immune phenotypes and cytokine secretion capability of T cells were detected.Results: The percentages and absolute numbers of CD3⁺and CD8⁺T cells were significantly increased in IM patients compared with HCs. The percentages of Naïve CD4⁺and CD8⁺T cells were decreased but with increased percentages of memory CD4⁺and CD8⁺T subsets. Our results showed the upregulation of active marker HLA-DR, TCR-αβ, and inhibitory receptors PD-1, TIGIT in CD8⁺T cells from IM patients, which suggested that effective cytotoxic T cells were highly against EBV infection. However, EBV exposure impaired the cytokine (IFN-γ, IL-2, and TNF-α) secretion capability of CD4⁺and CD8⁺T cells after stimulation with PMA/ionomycinin vitro. Multivariate analysis revealed that the percentage of HLA-DR⁺CD8⁺T cells was an independent prognostic marker for IM. The percentage of HLA-DR⁺CD8⁺T cells was significantly correlated with high viral load and abnormal liver function results.Conclusion: Robust expansion and upregulation of HLA-DR in CD8⁺T cells, accompanied with impaired cytokine secretion, were typical characteristics of children with acute IM. The percentage of HLA-DR⁺CD8⁺T cells might be used as a prominent marker not only for the early diagnosis but also for indicating the severity of IM.