Objective:To investigate the effects of down-regulation of p21 activated kinase 1(PAK1)on the proliferation,differentiation,and apoptosis of myeloproliferative neoplasm(MPN)cells(6133/MPL)with thrombopoietin receptor MPL mutation at codon 515(MPLW515L)and survival of 6133/MPL mice.Methods:Interference with the protein level of PAK1 in 6133/MPL cells was assessed using lentivirus-mediated shRNA transfection technology.CCK-8 assay was used to detect the effect of down-regulation of PAK1 on the proliferation viability of 6133/MPL cells,and colony-forming ability was measured by cell counting.Flow cytometry was used to detect the PAK1 kinase activity on the ability of polyploid DNA formation and cell apoptosis in 6133/MPL cells.The expression of cyclin D1,cyclin D3 and apoptosis-related protein Bax was detected by Western blot.The infiltration of tumor cells in spleen and bone marrow of 6133/MPL mice were detected by HE staining.Results:Down-regulation of PAK1 inhibited the proliferation and reduced the ability of cell colony formation of 6133/MPL cells.After knocking down PAK1,the content of polyploid DNA in 6133/MPL cells increased from 31.8 to 57.5％and 48.0％,and the proportion of apoptosis increased approximately to 10.8％.Down-regulation of PAK1 led to a reduction of infiltration of tumor cells in liver and bone marrow of 6133/MPL mice,thereby prolonging survival time.Conclusion:Down-regulation of PAK1 can significantly inhibit the growth of 6133/MPL cells,promote the formation of polyploid DNA,induce 6133/MPL cell apoptosis,and prolong the survival time of 6133/MPL mice.

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.