1.Preoperative diagnostic efficacy of novel blood markers white blood cell ratio and fibrinogen levels in periprosthetic joint infection.
Geng-Yao ZHU ; Chao MA ; Guang-Wang LIU ; Jia-Zheng MAN
China Journal of Orthopaedics and Traumatology 2025;38(1):55-60
OBJECTIVE:
To investigate the clinical utility of novel of new hematological markers in the preoperative diagnosis of periprosthetic joint infection (PJI).
METHODS:
A retrospective analysis was conducted on a total of 149 patients who underwent revision of total hip arthroplasty (THA) or total knee arthroplasty (TKA) at a single center between January 2016 and June 2022, including 63 males and 86 females, aged from 47 to 93 years old with an average of (69.5±11.8) years old. Of them, 46 were diagnosed as PJI(PJI group), including 22 males and 24 females. The mean age was (71.3±12.5) years old. The body mass index (BMI) was (26.4±3.1) kg·m-2. And 103 patients were diagnosed as aseptic prosthesis loosening (aseptic group), including 41 males and 62 females. The mean age was (68.7±11.4) years old. The BMI was (25.8±3.5) kg·m-2. Preoperatively analyzed clinical parameters included C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), albumin, globulin, albumin-to-globulin ratio (AGR), plasma D-dimer, and plasma fibrinogen. The receiver operating characteristic curve (ROC), sensitivity, and specificity analysis were employed to compare the diagnostic value of each blood marker in preoperative PJI diagnosis.
RESULTS:
In the PJI group, the levels of CRP were 16.6 (7.6, 4.5) mg·L-1, ESR was 17.0 (12.8, 35.5) mm·h-1, plasma D-dimer was 1.0 (0.5, 3.1) μg·L-1, and plasma fibrinogen was 4.2 (3.2, 3.1) mg·L-1;all of which were higher compared to the aseptic group with CRP at 4.2 (2.6, 7.8) mg·L-1, ESR at 12.0(8.0, 20.0 )mm·h-l, D-dimer at 0.4(0.2, 0.7)μg·L-1, and fibrinogen at 2.8(2.4, 3.3 ) g·L-1(P<0.05). However, the albumin level of 35.3 (32.3, 37.5) g·L-1 and the WBC ratio of 1.0(0.9, 1.1) in the PJI group were significantly lower compared to the aseptic group with levels of 39.8 (36.1, 41.8) g·L-1 and 1.4 (1.3, 1.5), respectively (P<0.05). Only the area under the curve (AUC) of AGR and plasma fibrinogen were greater than 0.8. The optimal predictive cut-1off, AUC, sensitivity and specificity were 3.4 g·L-1, 0.820, 69.57% and 84.47% for plasma fibrinogen; 1.18, 0.813, 82.61% and 78.64% for AGR, respectively.
CONCLUSION
AGR and plasma fibrinogen are promising blood markers for improving the diagnosis of PJI.
Humans
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Female
;
Fibrinogen/metabolism*
;
Male
;
Middle Aged
;
Aged
;
Prosthesis-Related Infections/blood*
;
Retrospective Studies
;
Biomarkers/blood*
;
Aged, 80 and over
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Arthroplasty, Replacement, Knee/adverse effects*
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Arthroplasty, Replacement, Hip/adverse effects*
;
Leukocyte Count
2.Significance of precise classification of sacral meningeal cysts by multiple dimensions radiographic reconstruction MRI in guiding operative strategy and rehabilitation.
Jianjun SUN ; Qianquan MA ; Xiaoliang YIN ; Chenlong YANG ; Jia ZHANG ; Suhua CHEN ; Chao WU ; Jingcheng XIE ; Yunfeng HAN ; Guozhong LIN ; Yu SI ; Jun YANG ; Haibo WU ; Qiang ZHAO
Journal of Peking University(Health Sciences) 2025;57(2):303-308
OBJECTIVE:
To precise classify sacral meningeal cysts, effective guide minimally invasive neurosurgery and postoperative personalized rehabilitation by multiple dimensions radiographic reconstruction MRI.
METHODS:
From March to December 2021, based on the original 3D-fast imaging employing steadystate acquisition (FIESTA) scanning sequence, 92 patients with sacral meningeal cysts were pre-operatively evaluated by multiple dimensional reconstruction MRI. The shape of nerve root and the leakage of cyst were reconstructed according to the direction of nerve root or leakage track showed on original MRI scans. Sacral canal cysts were accurately classified as including nerve root and without nerve root, so as to accurately design the incision of skin and formulate corresponding open range of the posterior wall of the sacral canal. Under the microscope intraoperation, the shape of the nerve roots inside cysts or leakage track of the cysts without nerve roots were verified and explored. After the reinforcement and shaping operation, several reexaminations of multiple dimensional reconstruction MRI were performed to understand the deformation of the nerve root and hydrops in the operation cavity, so as to formulate a persona-lized rehabilitation plan for the patients.
RESULTS:
Among the 92 patients with sacral mengingeal cyst, 58 (63.0%) cysts with nerve root cyst, 29 (31.5%) cysts without nerve root cyst, and 5 (5.4%) cysts with mixed sacral canal cyst. In 58 patients with nerve root cysts, the accuracy of preoperative clinical classification on MRI image reached 96.6% (56/58) through confirmation by operating microscope. Only 2 cases of large single cyst with nerve root on the head of cyst were mistaken for without nerve root type. In 29 patients with sacral cyst without nerve root, the accuracy of preoperative image reached 100% through confirmation by operating microscope. The accuracy of judging the internal nerve root and leakage of 12 cases with recurrent sacral cyst was also 100%. Two cases of delayed postoperative hydrops were found one month after operation. After rehabilitation treatment by moxibustion and bathing, the hydrops disappeared 4-6 months after operation.
CONCLUSION
Multiple dimensional reconstruction MRI can precisely make clinical classification of sacral meningeal cysts before operation, guide minimally invasive neurosurgery effectively, and improve the rehabilitation effect.
Humans
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Magnetic Resonance Imaging/methods*
;
Male
;
Female
;
Sacrum/surgery*
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Adult
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Middle Aged
;
Imaging, Three-Dimensional/methods*
;
Cysts/rehabilitation*
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Aged
;
Adolescent
;
Young Adult
;
Spinal Nerve Roots/diagnostic imaging*
;
Minimally Invasive Surgical Procedures
;
Neurosurgical Procedures/methods*
3.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
4.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
5.Lung ultrasound for assessing lung aeration heterogeneity in neonatal respiratory distress syndrome: a retrospective cohort study
Yumo ZHU ; Lili FAN ; Jiancheng JIAO ; Chao JIA ; Weicong PU ; Li MA ; Yaofang XIA
Chinese Journal of Perinatal Medicine 2025;28(11):935-943
Objective:To evaluate lung ultrasound (LUS) for assessing lung aeration heterogeneity in neonatal respiratory distress syndrome (NRDS) across gestational ages and analyze its correlation with oxygenation.Methods:This retrospective cohort study enrolled 125 ventilated NRDS neonates from the neonatal intensive care unit of Hebei Children's Hospital (from March 2023 to May 2024), who were stratified as <32 gestational weeks ( n=47) and ≥32 gestational weeks ( n=78). All underwent LUS, chest X-ray, and blood gas analysis within 2 h of admission. The lung ultrasound score (LUSsc) quantified impaired lung volume percentage (graded: A=normal, B=coalescent B-lines, C=dense B-lines/focal consolidation, D=lobar consolidation). Aeration heterogeneity was measured by coefficient of variation (CV, within-patient) and Gini-Simpson index (between-patients), while oxygenation was assessed by arterial oxygen partial pressure/inhaled oxygen concentration (P/F). Group comparisons, including basic information, lung aeration, and lung aeration heterogeneity, used two independent sample t-tests, Mann-Whitney U tests, Chi square tests, or Wilcoxon tests; partial correlation analyzed aeration-oxygenation relationships. Results:(1) Analysis of impaired lung volume percentage revealed similar distribution patterns between groups, with the <32-week cohort ( n=47, 564 lung segments) showing proportions of 15.6% (88/564), 14.9% (84/564), 35.5% (200/564), and 34.0% (192/564) for graded patterns A through D, respectively, while the ≥32-week cohort ( n=78, 936 segments) demonstrated corresponding proportions of 15.7% (147/936), 16.3% (153/936), 31.7% (297/936), and 36.2% (339/936), with no statistically significant difference between groups ( Z=-0.24, P=0.812). (2) Within-patient heterogeneity analysis revealed no significant CV difference between <32-week group and ≥32-week group [0.33 (0.20-0.84) vs. 0.43 (0.21-0.73), Z=-0.99, P=0.321]. (3) Between-patient heterogeneity was significantly higher in the ≥32-week group, as reflected by the Gini-Simpson index [0.12 (0.09-0.14) vs. 0.09 (0.06-0.14), Z=-1.99, P=0.046], with heterogeneous aeration predominantly located in non-gravity-dependent regions—specifically the left upper lung in the <32-week group and anterior lungs in the ≥32-week group. (4) Correlation analyses demonstrated significantly inverse relationships between CV and LUSsc in <32-week and ≥32-week groups ( r=-0.912, P<0.001; r=-0.886, P<0.001), while the ≥32-week group additionally showed positive CV-P/F correlation ( r=0.373, P=0.001) and inverse LUSsc-P/F association ( r=-0.287, P=0.013). Conclusions:LUS effectively evaluates aeration and its heterogeneity in early NRDS. Infants ≥32 weeks exhibit greater between-patient heterogeneity, with ventilation parameters correlating significantly with oxygenation status.
6.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
7.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.
8.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
9.Conserved translational control in cardiac hypertrophy revealed by ribosome profiling.
Bao-Sen WANG ; Jian LYU ; Hong-Chao ZHAN ; Yu FANG ; Qiu-Xiao GUO ; Jun-Mei WANG ; Jia-Jie LI ; An-Qi XU ; Xiao MA ; Ning-Ning GUO ; Hong LI ; Zhi-Hua WANG
Acta Physiologica Sinica 2025;77(5):757-774
A primary hallmark of pathological cardiac hypertrophy is excess protein synthesis due to enhanced translational activity. However, regulatory mechanisms at the translational level under cardiac stress remain poorly understood. Here we examined the translational regulations in a mouse cardiac hypertrophy model induced by transaortic constriction (TAC) and explored the conservative networks versus the translatome pattern in human dilated cardiomyopathy (DCM). The results showed that the heart weight to body weight ratio was significantly elevated, and the ejection fraction and fractional shortening significantly decreased 8 weeks after TAC. Puromycin incorporation assay showed that TAC significantly increased protein synthesis rate in the left ventricle. RNA-seq revealed 1,632 differentially expressed genes showing functional enrichment in pathways including extracellular matrix remodeling, metabolic processes, and signaling cascades associated with pathological cardiomyocyte growth. When combined with ribosome profiling analysis, we revealed that translation efficiency (TE) of 1,495 genes was enhanced, while the TE of 933 genes was inhibited following TAC. In DCM patients, 1,354 genes were upregulated versus 1,213 genes were downregulated at the translation level. Although the majority of the genes were not shared between mouse and human, we identified 93 genes, including Nos3, Kcnj8, Adcy4, Itpr1, Fasn, Scd1, etc., with highly conserved translational regulations. These genes were remarkably associated with myocardial function, signal transduction, and energy metabolism, particularly related to cGMP-PKG signaling and fatty acid metabolism. Motif analysis revealed enriched regulatory elements in the 5' untranslated regions (5'UTRs) of transcripts with differential TE, which exhibited strong cross-species sequence conservation. Our study revealed novel regulatory mechanisms at the translational level in cardiac hypertrophy and identified conserved translation-sensitive targets with potential applications to treat cardiac hypertrophy and heart failure in the clinic.
Animals
;
Humans
;
Cardiomegaly/physiopathology*
;
Ribosomes/physiology*
;
Protein Biosynthesis/physiology*
;
Mice
;
Cardiomyopathy, Dilated/genetics*
;
Ribosome Profiling
10.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

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