Objective To evaluate the characteristics of different antigen-specific T cell immune responses to severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)after inoculation with 2 doses of SARS-CoV-2 inactivated vaccine for 12 months.Methods Fifteen healthy adults were enrolled in this study and blood samples collected at 12 months after receiving two doses of SARS-CoV-2 inactivated vaccine.The level and phenotypic characteristics of SARS-CoV-2 antigen-specific T lymphocytes were detected by activation-induced markers(AIM)based on polychromatic flow cytometry.Results After 12 months of inoculation with 2 doses of SARS-CoV-2 inactivated vaccine,more than 90%of adults had detectable Spike and Non-spike antigen-specific CD4+ T cells immune responses(Spike:14/15,P=0.0001;Non-spike:15/15,P<0.0001).80%of adults had detectable Spike and Non-spike antigen-specific CD8+ T cells immune responses(Spike:12/15,P=0.0463;Non-spike:12/15,P=0.0806).Antigen-specific CD4+ T cells induced by SARS-CoV-2 inactivated vaccination after 12 months were composed of predominantly central memory(CM)and effector memory 1(EM1)cells.On the other hand,in terms of helper subsets,antigen-specific CD4+ T cells mainly showed T helper 1/17(Th1/17)and T helper 2(Th2)phenotypes.Conclusions SARS-CoV-2 inactivated vaccination generates durable and extensive antigen-specific CD4+ T cell memory responses,which may be the key factor for the low proportion of severe coronavirus disease 2019(COVID-19)infection in China.

Lipopolysaccharides (LPS) are major outer membrane components of Gram-negative bacteria. Unlike most Gram-negative bacteria, Acinetobacter baumannii can still survive and acquire polymyxin resistance after complete loss of LPS. Previous studies of LPS-deficient Acinetobacter baumannii mostly focused on LPS-deficient strains induced by polymyxin, whose background was complex and unstable. To investigate LPS loss-mediated polymyxin resistant-Acinetobacter baumannii, this study constructed a stable and clear background LPS-deficient strain by knocking out lpxC gene in Acinetobacter baumannii ATCC 19606 with CIRSPR/Cas9, and then studied the phenotypic changes of the lpxC-deficient strain including morphology, growth rate, antibiotic susceptibility, virulence, membrane permeability, and membrane potential. Animal experiments were approved by the Animal Care and Welfare Committee Institute of Medicinal Biotechnology, CAMS and PUMC (approval number: IMB-20240119D₉). The results indicated that the lpxC gene of Acinetobacter baumannii ATCC 19606 was successfully knocked out. After losing the lpxC, the strain underwent the morphological change from rod-shaped to spherical. Furthermore, it leads to reduced growth rate, enhanced membrane permeability, decreased membrane potential, lower virulence, and increased antibiotic susceptibility to β-lactams, quinolones, aminoglycosides, macrolides, glycopeptides. The lpxC deletion results in significant changes in membrane homeostasis and adaptability of Acinetobacter baumannii. Understanding the phenotypic changes of colistin-resistant Acinetobacter baumannii mediated by LPS loss is useful for exploring the resistance mechanism of Acinetobacter baumannii and developing new therapeutic strategies.

Objective:To explore the construction of a medical Artificial Intelligence(AI)technology assessment system suitable for the national conditions in China.Methods:Summarize the domestic and international traditional health technology assessment system,and analyze the distinctive characteristics and novel risk factors of medical AI technology.Results:The existing evaluation indexes of technical characteristics are most likely to assess AI technology based on the sub-evaluation indexes of reliability,but the evaluation focus of reliability cannot be assessed for algorithms,big data,arithmetic power and the existence of risk factors,and the existing system of health technology assessment needs to be further improved.Conclusion:Traditional health technology assessment system is challenging to apply to the evaluation of medical AI technology.It is recommended to use the traditional health technology assessment framework as a foundational structure,incorporate evaluation indicators related to the characteristics of medical AI technology,and refer to evaluation indicators and methods from relevant fields to adjust and refine the medical AI technology assessment system.

Objective:To explore the construction of a medical Artificial Intelligence(AI)technology assessment system suitable for the national conditions in China.Methods:Summarize the domestic and international traditional health technology assessment system,and analyze the distinctive characteristics and novel risk factors of medical AI technology.Results:The existing evaluation indexes of technical characteristics are most likely to assess AI technology based on the sub-evaluation indexes of reliability,but the evaluation focus of reliability cannot be assessed for algorithms,big data,arithmetic power and the existence of risk factors,and the existing system of health technology assessment needs to be further improved.Conclusion:Traditional health technology assessment system is challenging to apply to the evaluation of medical AI technology.It is recommended to use the traditional health technology assessment framework as a foundational structure,incorporate evaluation indicators related to the characteristics of medical AI technology,and refer to evaluation indicators and methods from relevant fields to adjust and refine the medical AI technology assessment system.

Objective:To explore the construction of a medical Artificial Intelligence(AI)technology assessment system suitable for the national conditions in China.Methods:Summarize the domestic and international traditional health technology assessment system,and analyze the distinctive characteristics and novel risk factors of medical AI technology.Results:The existing evaluation indexes of technical characteristics are most likely to assess AI technology based on the sub-evaluation indexes of reliability,but the evaluation focus of reliability cannot be assessed for algorithms,big data,arithmetic power and the existence of risk factors,and the existing system of health technology assessment needs to be further improved.Conclusion:Traditional health technology assessment system is challenging to apply to the evaluation of medical AI technology.It is recommended to use the traditional health technology assessment framework as a foundational structure,incorporate evaluation indicators related to the characteristics of medical AI technology,and refer to evaluation indicators and methods from relevant fields to adjust and refine the medical AI technology assessment system.

Objective:To explore the construction of a medical Artificial Intelligence(AI)technology assessment system suitable for the national conditions in China.Methods:Summarize the domestic and international traditional health technology assessment system,and analyze the distinctive characteristics and novel risk factors of medical AI technology.Results:The existing evaluation indexes of technical characteristics are most likely to assess AI technology based on the sub-evaluation indexes of reliability,but the evaluation focus of reliability cannot be assessed for algorithms,big data,arithmetic power and the existence of risk factors,and the existing system of health technology assessment needs to be further improved.Conclusion:Traditional health technology assessment system is challenging to apply to the evaluation of medical AI technology.It is recommended to use the traditional health technology assessment framework as a foundational structure,incorporate evaluation indicators related to the characteristics of medical AI technology,and refer to evaluation indicators and methods from relevant fields to adjust and refine the medical AI technology assessment system.

Objective:To explore the construction of a medical Artificial Intelligence(AI)technology assessment system suitable for the national conditions in China.Methods:Summarize the domestic and international traditional health technology assessment system,and analyze the distinctive characteristics and novel risk factors of medical AI technology.Results:The existing evaluation indexes of technical characteristics are most likely to assess AI technology based on the sub-evaluation indexes of reliability,but the evaluation focus of reliability cannot be assessed for algorithms,big data,arithmetic power and the existence of risk factors,and the existing system of health technology assessment needs to be further improved.Conclusion:Traditional health technology assessment system is challenging to apply to the evaluation of medical AI technology.It is recommended to use the traditional health technology assessment framework as a foundational structure,incorporate evaluation indicators related to the characteristics of medical AI technology,and refer to evaluation indicators and methods from relevant fields to adjust and refine the medical AI technology assessment system.

Objective:To explore the construction of a medical Artificial Intelligence(AI)technology assessment system suitable for the national conditions in China.Methods:Summarize the domestic and international traditional health technology assessment system,and analyze the distinctive characteristics and novel risk factors of medical AI technology.Results:The existing evaluation indexes of technical characteristics are most likely to assess AI technology based on the sub-evaluation indexes of reliability,but the evaluation focus of reliability cannot be assessed for algorithms,big data,arithmetic power and the existence of risk factors,and the existing system of health technology assessment needs to be further improved.Conclusion:Traditional health technology assessment system is challenging to apply to the evaluation of medical AI technology.It is recommended to use the traditional health technology assessment framework as a foundational structure,incorporate evaluation indicators related to the characteristics of medical AI technology,and refer to evaluation indicators and methods from relevant fields to adjust and refine the medical AI technology assessment system.

Objective:To explore the construction of a medical Artificial Intelligence(AI)technology assessment system suitable for the national conditions in China.Methods:Summarize the domestic and international traditional health technology assessment system,and analyze the distinctive characteristics and novel risk factors of medical AI technology.Results:The existing evaluation indexes of technical characteristics are most likely to assess AI technology based on the sub-evaluation indexes of reliability,but the evaluation focus of reliability cannot be assessed for algorithms,big data,arithmetic power and the existence of risk factors,and the existing system of health technology assessment needs to be further improved.Conclusion:Traditional health technology assessment system is challenging to apply to the evaluation of medical AI technology.It is recommended to use the traditional health technology assessment framework as a foundational structure,incorporate evaluation indicators related to the characteristics of medical AI technology,and refer to evaluation indicators and methods from relevant fields to adjust and refine the medical AI technology assessment system.

Objective:To explore the construction of a medical Artificial Intelligence(AI)technology assessment system suitable for the national conditions in China.Methods:Summarize the domestic and international traditional health technology assessment system,and analyze the distinctive characteristics and novel risk factors of medical AI technology.Results:The existing evaluation indexes of technical characteristics are most likely to assess AI technology based on the sub-evaluation indexes of reliability,but the evaluation focus of reliability cannot be assessed for algorithms,big data,arithmetic power and the existence of risk factors,and the existing system of health technology assessment needs to be further improved.Conclusion:Traditional health technology assessment system is challenging to apply to the evaluation of medical AI technology.It is recommended to use the traditional health technology assessment framework as a foundational structure,incorporate evaluation indicators related to the characteristics of medical AI technology,and refer to evaluation indicators and methods from relevant fields to adjust and refine the medical AI technology assessment system.