1.Predictive model for anxiety symptoms among junior high school students based on machine learning algorithms
YANG Yinmei, FENG Haiyang, LIU Mingxiu, YU Qiurui, MA Xin, YAN Hong, YU Bin, YU Chengcheng
Chinese Journal of School Health 2026;47(5):690-694
Objective:
To explore the influencing factors of anxiety symptoms and to construct a predictive model based on machine learning algorithms, so as to provide support for the prevention and management of anxiety symptoms among junior high school students.
Methods:
From April to May 2023, a stratified random cluster sampling method was adopted to select 8 176 junior high school students from Zhengzhou and Shangqiu citys. All participants completed the Adolescent Self rating Life Events Checklist, the 10item Connor-Davidson Resilience Scale, the School Connectedness Scale, the Parent-Child Cohesion Questionnaire, and the 7 item Generalized Anxiety Disorder Scale. Logistic regression analysis identified the associated factors of anxiety symptoms among junior high school students. Predictive models were constructed using Logistic regression, Random Forest, and eXtreme Gradient Boosting (XGBoost) algorithms, with SHapley Additive exPlanations analysis explaining the optimal model.
Results:
The detection rate of anxiety symptoms among junior high school students was 16.3%. Logistic regression analysis showed that junior high school students who were female ( OR =1.22), in the ninth grade ( OR =1.27), living in urban areas ( OR =1.37), having a father with a college education or above ( OR =1.26), having a mother with a senior high school education ( OR =1.26), and experiencing higher levels of negative life events ( OR =1.05) reported a higher risk of anxiety symptoms(all P <0.05). In contrast, those with moderate family economic status ( OR =0.71), moderate academic burden ( OR =0.59), low academic burden ( OR =0.54), moderate sleep quality ( OR =0.46), good sleep quality ( OR =0.26), excellent sleep quality ( OR =0.15), higher levels of psychological resilience ( OR =0.96), higher levels of school connectedness ( OR =0.96), and higher levels of parent-child cohesion ( OR =0.98) reported a lower risk of anxiety symptoms (all P <0.05). Three machine learning models demonstrated good predictive performance for anxiety symptoms among junior high school students (all AUC>0.8), with the XGBoost model achieving the best predictive performance. SHAP analysis revealed that negative life events, sleep quality, school connectedness, psychological resilience and parent-child cohesion were the top five relevant factors for predicting anxiety symptoms.
Conclusions
The detection rate of anxiety symptoms among junior high school students is relatively high. The XGBoost model is the optimal predictive model for anxiety symptoms in the population. Negative life events, sleep quality, school connectedness, psychological resilience, and parent-child cohesion are significant correlates of anxiety symptoms among junior high school students.
2.Pathological changes and macrophage polarization in the liver and spleen of mice infected with Angiostrongylus cantonensis
Xiaoyu QIN ; Yuchun CAI ; Yang HONG ; Fanna WEI ; Yahong HU ; Yumeng CAI ; Yuan HU ; Ting ZHANG ; Xiaojin MO ; Bin XU ; Yan LU ; Jiahui SUN ; Yan ZHOU ; Zelin ZHU ; Muxin CHEN
Chinese Journal of Schistosomiasis Control 2026;38(2):169-183
Objective To investigate the temporal changes in pathological damage and macrophage polarization in liver and spleen tissues of mice infected with Angiostrongylus cantonensis, and to preliminarily unravel the peripheral immune responses during the early stage of A. cantonensis infection. Methods Forty female BALB/c mice at ages of 6 to 8 weeks were randomly divided into four groups, including the control group and 7-, 14-, and 21-day infection groups, with 10 mice in each group. Each mouse in the infection groups was inoculated with 30 third-stage (L3) larvae of A. cantonensis by oral gavage, and five mice were randomly selected from each infection group on days 7, 14, and 21 post-infection, while mice in the control group were given the same volume of physiological saline and five mice were randomly selected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled. The histopathological changes of mouse liver and spleen tissues were observed using hematoxylin and eosin (HE) staining, and the percentage of positive staining area and the co-localization positive rates of the macrophage surface antigens F4/80, CD86, and CD206 were quantified in mouse liver and spleen tissues using immunohistochemical and immunofluorescence staining. In addition, five mice were collected from each infection group on days 7, 14, and 21 post-infection, and five mice were collected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled for detection of macrophage markers CD86 and CD206 and macrophage phenotyping using flow cytometry, and the expression of M1 macrophage markers, including inducible nitric oxide synthase (Nos2), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and M2 markers, including arginase 1 (Arg1), mannose receptor C-type 1 (Mrc1) and chitinase-like protein 3 (Chil3) was quantified in mouse liver and spleen tissues using real-time quantitative PCR (RT-qPCR) assay. Results Proliferative lesions of the hepatocyte were observed in mouse liver tissues and the follicular structures of the mouse spleen white pulp were disrupted 21 days post-infection with A. cantonensis. Immunohistochemical staining showed that there were significant differences in the percentages of F4/80, CD86 and CD206 positive staining areas in the liver and spleen tissues among the four groups of mice (F = 242.40, 197.14, 183.19, 157.65, 242.35 and 146.24; all P values < 0.001), and the percentages of positive staining in the liver and spleen tissues of mice in the 14-day infection group [(4.45 ± 0.51)%, (3.74 ± 0.67)%, (8.32 ± 0.72)%, (16.56 ± 1.14)%, (11.62 ± 0.52)%, and (8.29 ± 0.72)%, respectively] and the 21-day infection group [(3.70 ± 0.11)%, (3.22 ± 0.43)%, (11.53 ± 1.03)%, (12.59 ± 1.05)%, (9.02 ± 0.83)%, and (11.67 ± 1.10)%, respectively] were higher than in the control group [(0.35 ± 0.16)%, (0.40 ± 0.02)%, (0.93 ± 0.05)%, (2.78 ± 0.26)%, (2.33 ± 0.20)%, and (1.85 ± 0.20)%, respectively] (all P values < 0.05). Immunofluorescence staining showed significant differences in the positive rates of F4/80 co-localization with CD86 and CD206 in mouse liver and spleen tissues among the four groups (F = 24.42, 25.28, 54.51 and 130.55; all P values < 0.001). Flow cytometry detected significant differences in the proportions of CD86+ and CD206+ macrophages in mouse liver and spleen tissues among the four groups (F = 67.98, 18.41, 29.77, 172.80; all P values < 0.001), and the proportions of CD206+ macrophages in the liver and spleen of the 21-day infection group were significantly higher than those in the control group [(9.25 ± 2.55)% vs (3.83 ± 0.72)%, and (4.22 ± 0.56)% vs (0.47 ± 0.18)%, respectively] (both P values < 0.05). In addition, RT-qPCR assay quantified significant differences in the relative mRNA expression of M1 macrophage markers (IL-1β, TNF-α and Nos2) and M2 macrophage markers (Arg1, Chil3 and Mrc1) in mouse liver and spleen tissues among the four groups (F = 41.30, 31.82, 199.33, 19.96, 62.01, 119.76, 23.67, 95.90, 72.27, 82.59, 123.41 and 29.75; all P values < 0.05). Conclusions A. cantonensis infection may cause progressive pathological damage in mouse liver and spleen tissues, accompanied by dynamic temporal changes in macrophage polarization. M1 macrophage polarization predominates at the early stage of A. cantonensis infection and shifts towards M2 polarization at the later stages, suggesting that M2 polarization may participate in immune regulation at late stages of A. cantonensis infection by suppressing excessive inflammatory responses and promoting tissue repair.
3.Pre-operative risk assessment of hepatocellular carcinoma recurrence in liver transplant recipients by non-invasive detection of pre-existing genetic lesions
Suqin YANG ; Sunbin LING ; Jianhua LI ; Yan WANG ; Jiapei WANG ; Qiwei HUANG ; Fanming LIU ; Yiqi ZHUANG ; Yingyu ZHENG ; Rui WANG ; Zhe YANG ; Xiaoping ZHENG ; Kai WANG ; Zhikun LIU ; Jun CHEN ; Jianguo WANG ; Haiyang XIE ; Lin ZHOU ; Leiming CHEN ; Guoqiang CAO ; Dandan CHEN ; Junfang JI ; Bin ZHAO ; Chao JIANG ; Di LU ; Xuyong WEI ; Hangjin JIANG ; Qiaonan SHAN ; Hengbo SHI ; Yong-Zhen XU ; Shusen ZHENG ; Zhengxin WANG ; Shengda LIN ; Xiao XU
Clinical and Molecular Hepatology 2026;32(2):884-903
Background/Aims:
Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy.
Methods:
We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues.
Results:
We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts.
Conclusion
Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.
4.Optimization of Laser-Induced Breakdown Spectroscopy Parameters for Phosphorus Detection in Water Using Orthogonal Experiment
Xin-Yan YANG ; Xin WANG ; Wen-Wen ZHOU ; Yi-Heng LI ; Peng ZHU ; Bin WANG ; Xian-Feng ZHENG
Chinese Journal of Analytical Chemistry 2025;53(11):1921-1930
Aerosol-assisted plasma amplification laser-induced breakdown spectroscopy(LIBS)was employed for phosphorus detection in water.To address the multivariate coupling effects in LIBS and nebulization sampling system,an orthogonal experiment was employed to systematically optimize the key experimental parameters.Using the orthogonal experimental design,the parametric effects of laser energy(output voltage),signal acquisition delay,liquid velocity,and gas velocity on the signal to background ratio(SBR)of P I 213.618 nm were evaluated,and the optimal conditions were achieved,including laser energy of 86 mJ,delay time of 3 μs,gas velocity of 1.05 mL/min,and liquid velocity of 60 μL/min,which were in agreement with the control-variable optimization results.Moreover,the SBR response trends at P I 213.618 nm with all experimental parameters was strong in consistency with control-variable optimization results,which demonstrated the validity of the orthogonal array experimental design.This study established an efficient and accurate parameter optimization methodology for complex LIBS systems,significantly advancing the application of LIBS in environmental monitoring.
5.Relationship between serum miR-30a-5p,RUNX2 and severity and prognosis of patients with sepsis-induced acute lung injury
Yuan TANG ; Qingqing ZHANG ; Yan LI ; Jian YANG ; Bin LUO ; Boqing WANG
International Journal of Laboratory Medicine 2025;46(8):948-954
Objective To investigate the relationship between serum microRNA-30a-5p(miR-30a-5p),Runt-associated transcription factor 2(RUNX2)and the severity and prognosis of patients with sepsis-induced acute lung injury(ALI).Methods A total of 193 patients with sepsis-induced ALI(ALI group)and 54 pa-tients with simple sepsis(non-ALI group)admitted to the Fifth Affiliated Hospital of Xinjiang Medical Uni-versity from January 2021 to February 2024 were selected,and the patients with sepsis-induced ALI were di-vided into a mild ALI group(57 cases),a moderate ALI group(64 cases),and a severe ALI group(72 cases)according to the oxygenation index,and were divided into a death group(71 cases)and a survival group(122 cases)according to the 28 day prognosis situation.Serum miR-30a-5p level was detected by real time fluores-cent quantitative PCR,serum RUNX2 level was detected by enzyme-linked immunosorbent assay,and the binding sites of miR-30a-5p and RUNX2 were predicted by online database.Pearson's correlation coefficient was used to analyze the correlation between miR-30a-5p and RUNX2 in patients with sepsis-induced ALI,and Spearman's correlation coefficient was used to analyze the correlation between serum miR-30a-5p,RUNX2 levels and oxygenation index in patients with sepsis-induced ALI.With the prognosis of patients with sepsis-induced ALI as the dependent variable,multivariate unconditional Logistic regression was used to determine their influencing factors,and receiver operating characteristic curve was plotted to evaluate the prognostic val-ue of serum miR-30a-5p and RUNX2 levels in patients with sepsis-induced ALI.Results Compared with the non-ALI group,serum miR-30a-5p level was lower and RUNX2 level was higher in the ALI group(t=-11.749,11.691,P<0.001).There was a binding site between miR-30a-5p and RUNX2 at the 3'-untranslat-ed region 3 348-3 354.miR-30a-5p was negatively correlated with RUNX2 in patients with sepsis-induced ALI(r=-0.759,P<0.001).The level of serum miR-30a-5p increased in the severe ALI group,the moderate ALI group and the mild ALI group in turn(P<0.001),and the level of RUNX2 decreased in the severe ALI group,the moderate ALI group and the mild ALI group in turn(P<0.001).Oxygenation index was negative-ly correlated with serum miR-30a-5p level(r=-0.749,P<0.001),and positively correlated with RUNX2 level in patients with sepsis-induced ALI(r=0.723,P<0.001).Independent protective factors for death in patients with sepsis-induced ALI were increased oxygenation index(OR=0.988,95%CI:0.981-0.996,P<0.05),elevated miR-30a-5p(OR=0.814,95%CI:0.744-0.892,P<0.05),and independent risk factors were increased Sequential Organ Failure Assessment(SOFA)score(OR=1.391,95%CI:1.116-1.734,P<0.05),elevated blood lactate(OR=1.824,95%CI:1.211-2.748,P<0.05),and elevated RUNX2(OR=1.366,95%CI:1.170-1.595,P<0.05).The area under the curve of serum miR-30a-5p and RUNX2 levels combined to predict the death in patients with sepsis-induced ALI was 0.895(95%CI:0.842-0.934),which was greater than 0.788(95%CI:0.724-0.844)of serum miR-30a-5p and 0.786(95%CI:0.721-0.842)of RUNX2 levels alone(Z=4.015,3.746,P<0.001).Conclusion Increased miR-30a-5p level and decreased RUNX2 level are associated with the aggravation of the disease and the increased risk of death in patients with sepsis-induced ALI.The combination of serum miR-30a-5p and RUNX2 levels has relatively high value in pre-dicting the prognosis of patients with sepsis-induced ALI.
6.Consensus on informed consent for orthodontic treatment
Yang CAO ; Bing FANG ; Zuolin JIN ; Hong HE ; Yuxing BAI ; Lin WANG ; Haiping LU ; Zhihe ZHAO ; Tianmin XU ; Weiran LI ; Min HU ; Jinlin SONG ; Jun WANG ; Fang JIN ; Ding BAI ; Xianglong HAN ; Yuehua LIU ; Bin YAN ; Jie GUO ; Jiejun SHI ; Yongming LI ; Zhihua LI ; Xiuping WU ; Jiangtian HU ; Linyu XU ; Lin LIU ; Yi LIU ; Yanqin LU ; Wensheng MA ; Shuixue MO ; Liling REN ; Shuxia CUI ; Yongjie FAN ; Jianguang XU ; Lulu XU ; Zhijun ZHENG ; Peijun WANG ; Rui ZOU ; Chufeng LIU ; Lunguo XIA ; Li HU ; Weicai WANG ; Liping WU ; Xiaoxing KOU ; Jiali TAN ; Yuanbo LIU ; Bowen MENG ; Yuantao HAO ; Lili CHEN
Chinese Journal of Stomatology 2025;60(12):1327-1336
This consensus was developed by the Orthodontic Society of the Chinese Stomatological Association to provide a systematic, scientific, and practical guideline for informed consent in orthodontic care. Orthodontic treatment is typically lengthy, highly individualized, and involves multiple factors such as growth and development, occlusal function, and facial esthetics. Rapid technological advances and diverse risk profiles make the traditional reliance on orthodontist experience or institutional templates insufficient to ensure patients′ full understanding and autonomous decision-making. To address this, the expert panel conducted extensive reviews of domestic and international guidelines, analyzed representative dispute cases, and performed multicenter patient-clinician surveys. Using a multi-round Delphi method, the group established a standardized informed consent framework covering the initial consultation, treatment, and retention phases. The consensus emphasizes that informed consent is not only a fundamental legal and ethical requirement but also a key step in building trust, improving patient compliance, and enhancing treatment satisfaction. Orthodontists should clearly and comprehensively explain treatment plans, potential risks, uncertainties, and associated costs, while respecting the autonomy of patients or guardians, and maintain continuous communication and dynamic evaluation throughout the treatment process. The release of this consensus provides unified and authoritative guidance for clinical orthodontics, helping to standardize informed consent, enhance its transparency, safeguard patient rights, reduce medical risks, and promote high-quality, sustainable development of orthodontic practice.
7.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
8.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
9.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; 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 ; 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 ; 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 WEN ; 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(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
10.Clinical and Laboratory Characteristics of Acute Myeloid Leukemia, Myelodysplasia-Related.
Wei-Bin LI ; Lan YANG ; Shao-Jie CHENG ; Ya CHEN ; Yan JIANG
Journal of Experimental Hematology 2025;33(3):666-671
OBJECTIVE:
To understand clinical and laboratory characteristics of acute myeloid leukemia, myelodysplasia-related (AML-MR).
METHODS:
Blood sample of one patient with AML-MR admitted to our hospital in September 2021 was collected and synthetically analyzed by using techniques including complete blood cell count, peripheral blood and bone marrow cell morphology, bone marrow pathology and immunohistochemistry, hematology examination, flow cytometry (FCM), chromosome karyotype analysis and molecular pathology. The clinical and laboratory characteristics of AML-MR were analyzed and summarized according to the World Health Organization (WHO) standards.
RESULTS:
The patient showed pancytopenia and increased proportion of blasts in smear of peripheral blood cells. Bone marrow cytology and pathological examination showed significant proliferation of hematopoietic cells. Pathological immunohistochemistry showed increased expression of CD61, CD34, and CD117, while MPO, CD13, and CD33 were positive. FCM showed that abnormal myeloid progenitor cells accounted for approximately 18.61% of the total number of nuclear cells, with expression of CD34, CD13, CD117, HLA-DR, and CD33 (small amount). Additionally, 36.34% of the cells were primitive/immature red blood cells which expressed CD36, CD71, and CD117 (small amount). Chromosome karyotype analysis and molecular pathology detected three kinds of abnormalities including -5 and two kinds of TP53 related gene mutation, respectively.
CONCLUSION
AML-MR patient shows pancytopenia and increased proportion of blasts in smear of peripheral blood cells. Bone marrow cytology and pathological examination show significant proliferation of hematopoietic cells. FCM can detect myeloid progenitor cells and primitive/immature red blood cells, while chromosome karyotype analysis can detect three abnormal karyotypes.
Humans
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Leukemia, Myeloid, Acute/diagnosis*
;
Myelodysplastic Syndromes
;
Flow Cytometry
;
Karyotyping
;
Male
;
Middle Aged
;
Mutation


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