1.Chest computed tomography-based artificial intelligence-aided latent class analysis for diagnosis of severe pneumonia.
Caiting CHU ; Yiran GUO ; Zhenghai LU ; Ting GUI ; Shuhui ZHAO ; Xuee CUI ; Siwei LU ; Meijiao JIANG ; Wenhua LI ; Chengjin GAO
Chinese Medical Journal 2025;138(18):2316-2323
BACKGROUND:
There is little literature describing the artificial intelligence (AI)-aided diagnosis of severe pneumonia (SP) subphenotypes and the association of the subphenotypes with the ventilatory treatment efficacy. The aim of our study is to illustrate whether clinical and biological heterogeneity, such as ventilation and gas-exchange, exists among patients with SP using chest computed tomography (CT)-based AI-aided latent class analysis (LCA).
METHODS:
This retrospective study included 413 patients hospitalized at Xinhua Hospital diagnosed with SP from June 1, 2015 to May 30, 2020. AI quantification results of chest CT and their combination with additional clinical variables were used to develop LCA models in an SP population. The optimal subphenotypes were determined though evaluating statistical indicators of all the LCA models, and clinical implications of them such as guiding ventilation strategies were further explored by statistical methods.
RESULTS:
The two-class LCA model based on AI quantification results of chest CT can describe the biological characteristics of the SP population well and hence yielded the two clinical subphenotypes. Patients with subphenotype-1 had milder infections ( P <0.001) than patients with subphenotype-2 and had lower 30-day ( P <0.001) and 90-day ( P <0.001) mortality, and lower in-hospital ( P = 0.001) and 2-year ( P <0.001) mortality. Patients with subphenotype-1 showed a better match between the percentage of non-infected lung volume (used to quantify ventilation) and oxygen saturation (used to reflect gas exchange), compared with patients with subphenotype-2. There were significant differences in the matching degree of lung ventilation and gas exchange between the two subphenotypes ( P <0.001). Compared with patients with subphenotype-2, those with subphenotype-1 showed a relatively better match between CT-based AI metrics of the non-infected region and oxygenation, and their clinical outcomes were effectively improved after receiving invasive ventilation treatment.
CONCLUSIONS
A two-class LCA model based on AI quantification results of chest CT in the SP population particularly revealed clinical heterogeneity of lung function. Identifying the degree of match between ventilation and gas-exchange may help guide decisions about assisted ventilation.
Humans
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Tomography, X-Ray Computed/methods*
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Male
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Female
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Retrospective Studies
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Middle Aged
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Artificial Intelligence
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Aged
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Pneumonia/diagnosis*
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Latent Class Analysis
;
Adult
2.Beyond cancer: The potential application of CD47-based therapy in non-cancer diseases.
Wei-Qing DENG ; Zi-Han YE ; Zhenghai TANG ; Xiao-Lei ZHANG ; Jin-Jian LU
Acta Pharmaceutica Sinica B 2025;15(2):757-791
CD47 is an immune checkpoint widely regarded as a 'don't eat me' signal. CD47-based anti-cancer therapy has received considerable attention, with a significant number of clinical trials conducted. While anti-cancer therapies based on CD47 remain a focal point of interest among researchers, it is noteworthy that an increasing number of studies have found that CD47-based therapy ameliorated the pathological status of non-cancer diseases. This review aims to provide an overview of the recent progress in comprehending the role of CD47-based therapy in non-cancer diseases, including diseases of the circulatory system, nervous system, digestive system, and so on. Furthermore, we sought to delineate the promising mechanisms of CD47-based therapy in treating non-cancer diseases. Our findings suggest that CD47-based agents may exert their effect by regulating phagocytosis, regulating T cells, dendritic cells, and neutrophils, and regulating the secretion of cytokines and chemokines. Additionally, we put forward the orientation of further research to bring to light the potential of CD47 and its binding partners as a target in non-cancer diseases.
3.BRICS report of 2018-2019: the distribution and antimicrobial resistance profile of clinical isolates from blood culture in China
Yunbo CHEN ; Jinru JI ; Chaoqun YING ; Peipei WANG ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Hui DING ; Yongyun LIU ; Haifeng MAO ; Ying HUANG ; Zhenghai YANG ; Yuanyuan DAI ; Guolin LIAO ; Lisha ZHU ; Liping ZHANG ; Yanhong LI ; Hongyun XU ; Junmin CAO ; Baohua ZHANG ; Liang GUO ; Haixin DONG ; Shuyan HU ; Sijin MAN ; Lu WANG ; Zhixiang LIAO ; Rong XU ; Dan LIU ; Yan JIN ; Yizheng ZHOU ; Yiqun LIAO ; Fenghong CHEN ; Beiqing GU ; Jiliang WANG ; Jinhua LIANG ; Lin ZHENG ; Aiyun LI ; Jilu SHEN ; Yinqiao DONG ; Lixia ZHANG ; Hongxia HU ; Bo QUAN ; Wencheng ZHU ; Kunpeng LIANG ; Qiang LIU ; Shifu WANG ; Xiaoping YAN ; Jiangbang KANG ; Xiusan XIA ; Lan MA ; Li SUN ; Liang LUAN ; Jianzhong WANG ; Zhuo LI ; Dengyan QIAO ; Lin ZHANG ; Lanjuan LI ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2021;14(1):32-45
Objective:To investigate the distribution and antimicrobial resistance profile of clinical bacteria isolated from blood culture in China.Methods:The clinical bacterial strains isolated from blood culture from member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS) were collected during January 2018 to December 2019. Antibiotic susceptibility tests were conducted with agar dilution or broth dilution methods recommended by US Clinical and Laboratory Standards Institute (CLSI). WHONET 5.6 was used to analyze data.Results:During the study period, 14 778 bacterial strains were collected from 50 hospitals, of which 4 117 (27.9%) were Gram-positive bacteria and 10 661(72.1%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (37.2%), Klebsiella pneumoniae (17.0%), Staphylococcus aureus (9.7%), coagulase-negative Staphylococci (8.7%), Pseudomonas aeruginosa (3.7%), Enterococcus faecium (3.4%), Acinetobacter baumannii(3.4%), Enterobacter cloacae (2.9%), Streptococci(2.8%) and Enterococcus faecalis (2.3%). The the prevalence of methicillin-resistant S. aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus were 27.4% (394/1 438) and 70.4% (905/1 285), respectively. No glycopeptide-resistant Staphylococcus was detected. More than 95% of S. aureus were sensitive to amikacin, rifampicin and SMZco. The resistance rate of E. faecium to vancomycin was 0.4% (2/504), and no vancomycin-resistant E. faecalis was detected. The ESBLs-producing rates in no carbapenem-resistance E. coli, carbapenem sensitive K. pneumoniae and Proteus were 50.4% (2 731/5 415), 24.6% (493/2001) and 35.2% (31/88), respectively. The prevalence of carbapenem-resistance in E. coli and K. pneumoniae were 1.5% (85/5 500), 20.6% (518/2 519), respectively. 8.3% (27/325) of carbapenem-resistance K. pneumoniae was resistant to ceftazidime/avibactam combination. The resistance rates of A. baumannii to polymyxin and tigecycline were 2.8% (14/501) and 3.4% (17/501) respectively, and that of P. aeruginosa to carbapenem were 18.9% (103/546). Conclusions:The surveillance results from 2018 to 2019 showed that the main pathogens of bloodstream infection in China were gram-negative bacteria, while E. coli was the most common pathogen, and ESBLs-producing strains were in majority; the MRSA incidence is getting lower in China; carbapenem-resistant E. coli keeps at a low level, while carbapenem-resistant K. pneumoniae is on the rise obviously.
4.BRICS report of 2020: The bacterial composition and antimicrobial resistance profile of clinical isolates from bloodstream infections in China
Yunbo CHEN ; Jinru JI ; Chaoqun YING ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Yuanyuan DAI ; Jiliang WANG ; Haifeng MAO ; Hui DING ; Yongyun LIU ; Yizheng ZHOU ; Hong LU ; Youdong YIN ; Yan JIN ; Hongyun XU ; Lixia ZHANG ; Lu WANG ; Haixin DONG ; Zhenghai YANG ; Fenghong CHEN ; Donghong HUANG ; Guolin LIAO ; Pengpeng TIAN ; Dan LIU ; Yan GENG ; Sijin MAN ; Baohua ZHANG ; Ying HUANG ; Liang GUO ; Junmin CAO ; Beiqing GU ; Yanhong LI ; Hongxia HU ; Liang LUAN ; Shuyan HU ; Lin ZHENG ; Aiyun LI ; Rong XU ; Kunpeng LIANG ; Zhuo LI ; Donghua LIU ; Bo QUAN ; Qiang LIU ; Jilu SHEN ; Yiqun LIAO ; Hai CHEN ; Qingqing BAI ; Xiusan XIA ; Shifu WANG ; Jinhua LIANG ; Liping ZHANG ; Yinqiao DONG ; Xiaoyan QI ; Jianzhong WANG ; Xuefei HU ; Xiaoping YAN ; Dengyan QIAO ; Ling MENG ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2021;14(6):413-426
Objective:To investigate the bacterial composition and antimicrobial resistance profile of clinical isolates from bloodstream infections in China.Methods:The clinical bacterial strains isolated from blood culture were collected during January 2020 to December 2020 in member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS). Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical Laboratory Standards Institute(CLSI, USA). WHONET 5.6 was used to analyze data.Results:During the study period, 10 043 bacterial strains were collected from 54 hospitals, of which 2 664 (26.5%) were Gram-positive bacteria and 7 379 (73.5%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (38.6%), Klebsiella pneumoniae (18.4%), Staphylococcus aureus (9.9%), coagulase-negative Staphylococci (7.5%), Pseudomonas aeruginosa (3.9%), Enterococcus faecium (3.3%), Enterobacter cloacae (2.8%), Enterococcus faecalis (2.6%), Acinetobacter baumannii (2.4%) and Klebsiella spp (1.8%). The prevalence of methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus aureus were 27.6% and 74.4%, respectively. No glycopeptide- and daptomycin-resistant Staphylococci were detected. More than 95% of Staphylococcus aureus were sensitive to rifampicin and SMZco. No vancomycin-resistant Enterococci strains were detected. Extended spectrum β-lactamase (ESBL) producing Escherichia coli, Klebsiella pneumoniae and Proteus mirabilis were 48.4%, 23.6% and 36.1%, respectively. The prevalence rates of carbapenem-resistance in Escherichia coli and Klebsiella pneumoniae were 2.3% and 16.1%, respectively; 9.6% of carbapenem-resistant Klebsiella pneumoniae strains were resistant to ceftazidime/avibactam combination. The prevalence rate of carbapenem-resistance in Acinetobacter baumannii was 60.0%, while polymyxin and tigecycline showed good activity against Acinetobacter baumannii. The prevalence rate of carbapenem-resistance of Pseudomonas aeruginosa was 23.2%. Conclusions:The surveillance results in 2020 showed that the main pathogens of bloodstream infection in China were gram-negative bacteria, while Escherichia coli was the most common pathogen, and ESBL-producing strains declined while carbapenem-resistant Klebsiella pneumoniae kept on high level. The proportion and the prevalence of carbapenem-resistant Pseudomonas aeruginosa were on the rise slowly. On the other side, the MRSA incidence got lower in China, while the overall prevalence of vancomycin-resistant Enterococci was low.
5.BRICS report of 2016-2017: the distribution and antimicrobial resistance profile of clinical isolates from blood culture in China
Yunbo CHEN ; Jinru JI ; Chaoqun YING ; Peipei WANG ; Qing YANG ; Haishen KONG ; Yongyun LIU ; Ying HUANG ; Yuanyuan DAI ; Liping ZHANG ; Hui DING ; Liang GUO ; Baohua ZHANG ; Lisha ZHU ; Haifeng MAO ; Zhixiang LIAO ; Yanhong LI ; Lu WANG ; Shuyan HU ; Zhenghai YANG ; Beiqing GU ; Haixin DONG ; Fei DU ; Lin ZHENG ; Bo QUAN ; Wencheng ZHU ; Jianzhong WANG ; Lan MA ; Rong XU ; Li SUN ; Aiyun LI ; Junmin CAO ; Jinhua LIANG ; Hongyun XU ; Kunpeng LIANG ; Dengyan QIAO ; Xiaoyan QI ; Xiusan XIA ; Lanjuan LI ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2020;13(1):42-54
Objective:To investigate the distribution and antimicrobial resistance profile of clinical bacteria isolated from blood culture in China.Methods:The clinical bacterial strains isolated from blood culture from member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS) were collected during January 2016 to December 2017. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by US Clinical and Laboratory Standards Institute (CLSI) 2019. WHONET 5.6 was used to analyze data.Results:During the study period, 8 154 bacterial strains were collected from 33 hospitals, of which 2 325 (28.5%) were Gram-positive bacteria and 5 829 (71.5%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (34.7%), Klebsiella pneumoniae (15.8%), Staphylococcus aureus (11.3%), coagulase-negative Staphylococci (7.4%), Acinetobacter baumannii (4.6%), Pseudomonas aeruginosa (3.9%), Enterococcus faecium (3.8%), Streptococci (2.9%), Enterobacter cloacae (2.7%) and Enterococcus faecalis (2.5%). Methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus (MRCNS) accounted for 34.2%(315/922) and 77.7%(470/605), respectively. No vancomycin-resistant Staphylococcus was detected. The resistance rate of Enterococcus faecium to vancomycin was 0.6%(2/312), and no vancomycin-resistant Enterococcus faecium was detected. The ESBLs-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus were 55.7%(1 576/2 831), 29.9%(386/1 289) and 38.5%(15/39), respectively. The incidences of carbapenem-resistance in Escherichia coli, Klebsiella pneumoniae were 1.2%(33/2 831), 17.5%(226/1 289), respectively. The resistance rates of Acinetobacter baumannii to polymyxin and tigecycline were 14.8%(55/372) and 5.9%(22/372) respectively, and those of Pseudomonas aeruginosa to polymyxin and carbapenem were 1.3%(4/315) and 18.7%(59/315), respectively. Conclusion:The surveillance results from 2016 to 2017 showed that the main pathogens of blood stream infection in China were gram-negative bacteria, while Escherichia coli was the most common pathogen; the MRSA incidence was lower than other surveillance data in the same period in China; carbapenem-resistant Escherichia coli was at a low level during this surveillance, while carbapenem-resistant Klebsiella pneumoniae is on the rise.
6.Survey of Current Work Situation of Clinical Pharmacy in Medical Institutions Above Class II in Wuhan City
Lu LIU ; Xiaoming WANG ; Feng LI ; Zhenghai XIE ; Yu CHEN ; Qiao ZHANG ; Chen WANG ; Yufeng DING
China Pharmacist 2016;19(6):1144-1146
Objective:To understand the current work situation of clinical pharmacy in medical institutions in Wuhan city .Meth-ods:A questionnaire survey was employed to investigate the stuffing situation of clinical pharmacists , quality of clinical pharmacists and clinical pharmacy development in medical institutions above class II in Wuhan city .The results were analyzed statistically .Re-sults:There was notable difference in the situation of clinical pharmacist among medical institutions above class Ⅱin Wuhan city , and so was in the development of clinical pharmacy .Conclusion:Clinical pharmacy work in medical institutions still demands much atten-tion and support from the relevant departments , and clinical pharmacists own need make great efforts constantly .
7.Study on correlation between nodule density of different organs and hypericin content in Hypericum perforatum
Chinese Traditional and Herbal Drugs 1994;0(11):-
Object In order to choose high hypericin content variety and its useful part, the study on the correlation between nodule density of different organs and hypericin content in Hypericum perforatum L was carried out Methods The nodule density of leaf, calyx and petal were observed under a Leica DMLB microscope; the hypericin contents of different organs were determined by HPLC Results Hypericin and its derivatives were not obtained from the root, fruit and leaf central part of H perforatum The hypericin contents of leaf margin, calyx, petal were 0 145 6%, 0 065 3%, 1 268 2%, respectively Conclusion The organs and parts with nodules contain hypericin and its derivatives There is positive correlation between the hypericin content and nodule density, but the other organs or parts without nodules don't contain such materials

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