1.Chinese experts' consensus on principles of preoperative hair removal
Yiping MAO ; Jun ZHENG ; Lei LI ; Deyan YANG ; Bing ZHANG ; Lei YANG ; Wang JIA ; Peng KANG ; Hui JIAO ; Yun YANG ; Qi QI ; Shiqing FENG ; Xiao LONG ; Yuewei ZHANG ; Xiaohui WANG ; Lize WANG ; Yuan WEI ; Jichao ZHOU ; Minghui MAO ; Pengju XIN ; Hongyu TAN ; Dahong ZHANG ; Lianxin LIU ; Lei TAO ; Xietong WANG ; Xiaoning YUAN ; Mang CAI ; Li MU ; Fang DU ; Rongzhu CHEN ; Fengmao ZHAO ; Jiuzuo HUANG ; Mingzi ZHANG ; Jie ZHANG ; Baoguo WANG ; Kun WANG ; Fang LUO ; Jinhua ZHANG ; Nong HE ; Ling LYU ; Zhiyong ZONG
Chinese Journal of Nosocomiology 2025;35(10):1441-1449
To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.
2.Analysis of VWF Gene c.7332G>A Nonsense Mutation Pedigree and Study of Molecular Pathogenesis
Duan-Yang WANG ; Lei WANG ; Dong-Yan FU ; Xiao-Mei LU ; Li-Dong ZHAO ; Jia-Wei ZHENG ; Ya-Lin YU ; Gang WANG ; Lin-Hua YANG
Journal of Experimental Hematology 2025;33(6):1701-1707
Objective:To analyze the genetic characteristics of the VWF gene c.7332G>A nonsense mutation and explore its molecular pathogenesis.Methods:Phenotypic diagnosis of the proband was performed using VWF:Ag,VWF:RCo,FⅧ:C and multimeric analysis.The probands were genotyped by NGS whole-exome sequencing,and the sequencing results were validated by sanger sequencing.The family members were genotyped by Sanger sequencing.The VWF gene c.7332G>A nonsense mutant plasmid was constructed.After transfection,the function of VWF gene c.7332G>A mutant plasmid was verified at cell level in vitro.The mRNA level was detected by qRT-PCR,and the expression level of protein was detected by Western blot,the function of multimerization was verified by the multimeric analysis.Results:VWF:Ag and VWF:RCo were all less than 3%in the proband,and the multimeric analysis showed multimer deficiency.The proband was diagnosed as type 3 VWD.The homozygous nonsense mutation of VWF gene c.7332G>A was detected by gene sequencing.The VWF mRNA level of the mutant plasmid was decreased,and the VWF protein expression in the cell supernatant was decreased,the mutant protein was truncated and the function of VWF multimerization was impaired.Conclusion:A homozygous mutation in exon 43 of VWF gene,c.7332G>A,was responsible for the probands type 3 VWD in the proband.The mutation caused a decrease in the relative level of VWF mRNA and protein,and impaired the function of VWF multimerization.
3.Construction and Optimization of Alzheimer's Disease Classification Model Based on Brain Mixed Function Network Topology Parameters and Machine Learning
Xiao-yu HAN ; Xiu-zhu JIA ; Yang LI ; Meng-ying LOU ; Yong-qi NIE ; Xin-ping GUO ; Lu YU ; Zhi-yuan LI ; Lian-zheng SU
Progress in Modern Biomedicine 2025;25(11):1770-1778
Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P<0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7%,and the AUC values were up to 100%,99.5%,99.1%and 99.5%,respectively.The accuracy(98.5%),precision(98.5%),recall(98.5%),and AUC(99.1%)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0%,while Bagging has the lowest AUC value(99.1%)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13%),AUC(99.42%),recall rate(99.46%)and specificity(99.42%)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.
4.Chinese experts' consensus on principles of preoperative hair removal
Yiping MAO ; Jun ZHENG ; Lei LI ; Deyan YANG ; Bing ZHANG ; Lei YANG ; Wang JIA ; Peng KANG ; Hui JIAO ; Yun YANG ; Qi QI ; Shiqing FENG ; Xiao LONG ; Yuewei ZHANG ; Xiaohui WANG ; Lize WANG ; Yuan WEI ; Jichao ZHOU ; Minghui MAO ; Pengju XIN ; Hongyu TAN ; Dahong ZHANG ; Lianxin LIU ; Lei TAO ; Xietong WANG ; Xiaoning YUAN ; Mang CAI ; Li MU ; Fang DU ; Rongzhu CHEN ; Fengmao ZHAO ; Jiuzuo HUANG ; Mingzi ZHANG ; Jie ZHANG ; Baoguo WANG ; Kun WANG ; Fang LUO ; Jinhua ZHANG ; Nong HE ; Ling LYU ; Zhiyong ZONG
Chinese Journal of Nosocomiology 2025;35(10):1441-1449
To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.
5.Antimicrobial resistance surveillance in the bacterial strains isolated from pediatric intensive care units in China:results from 2020 to 2022
Jing LIU ; Huiyuan YAN ; Gangfeng YAN ; Guoping LU ; Pan FU ; Chuanqing WANG ; Danqun JIN ; Wenjia TONG ; Chenyu ZHANG ; Jianli CHEN ; Yi LIN ; Jia LEI ; Yibing CHENG ; Qunqun ZHANG ; Kaijie GAO ; Yuanyuan CHEN ; Shufang XIAO ; Juan HE ; Li JIANG ; Huimin XU ; Yuxia LI ; Hanghai DING ; Hehe CHEN ; Yao ZHENG ; Qunying CHEN ; Ying WANG ; Hong REN ; Chenmei ZHANG ; Zhenjie CHEN ; Mingming ZHOU ; Yucai ZHANG ; Yiping ZHOU ; Zhenjiang BAI ; Saihu HUANG ; Lili HUANG ; Weiguo YANG ; Weike MA ; Qing MENG ; Pengwei ZHU ; Yong LI ; Yan XU ; Yi WANG ; Yanqiang DU ; Huijun CAI ; Bizhen ZHU ; Huixuan SHI ; Shaoxian HONG ; Yukun HUANG ; Meilian HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):303-311
Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2%)and gram-negative organisms(60.8%).The top three organisms were S.aureus(13.6%,1 453/10 688),A.baumannii(10.0%,1 067/10 688),and coagulase-negative Staphylococcus(9.9%,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1%,19.4%,8.8%,30.9%,67.4%,and 28.8%,respectively.Overall,more than 50%of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25%of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80%of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3%in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.
6.Construction and Optimization of Alzheimer's Disease Classification Model Based on Brain Mixed Function Network Topology Parameters and Machine Learning
Xiao-yu HAN ; Xiu-zhu JIA ; Yang LI ; Meng-ying LOU ; Yong-qi NIE ; Xin-ping GUO ; Lu YU ; Zhi-yuan LI ; Lian-zheng SU
Progress in Modern Biomedicine 2025;25(11):1770-1778
Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P<0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7%,and the AUC values were up to 100%,99.5%,99.1%and 99.5%,respectively.The accuracy(98.5%),precision(98.5%),recall(98.5%),and AUC(99.1%)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0%,while Bagging has the lowest AUC value(99.1%)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13%),AUC(99.42%),recall rate(99.46%)and specificity(99.42%)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.
7.Antimicrobial resistance surveillance in the bacterial strains isolated from pediatric intensive care units in China:results from 2020 to 2022
Jing LIU ; Huiyuan YAN ; Gangfeng YAN ; Guoping LU ; Pan FU ; Chuanqing WANG ; Danqun JIN ; Wenjia TONG ; Chenyu ZHANG ; Jianli CHEN ; Yi LIN ; Jia LEI ; Yibing CHENG ; Qunqun ZHANG ; Kaijie GAO ; Yuanyuan CHEN ; Shufang XIAO ; Juan HE ; Li JIANG ; Huimin XU ; Yuxia LI ; Hanghai DING ; Hehe CHEN ; Yao ZHENG ; Qunying CHEN ; Ying WANG ; Hong REN ; Chenmei ZHANG ; Zhenjie CHEN ; Mingming ZHOU ; Yucai ZHANG ; Yiping ZHOU ; Zhenjiang BAI ; Saihu HUANG ; Lili HUANG ; Weiguo YANG ; Weike MA ; Qing MENG ; Pengwei ZHU ; Yong LI ; Yan XU ; Yi WANG ; Yanqiang DU ; Huijun CAI ; Bizhen ZHU ; Huixuan SHI ; Shaoxian HONG ; Yukun HUANG ; Meilian HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):303-311
Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2%)and gram-negative organisms(60.8%).The top three organisms were S.aureus(13.6%,1 453/10 688),A.baumannii(10.0%,1 067/10 688),and coagulase-negative Staphylococcus(9.9%,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1%,19.4%,8.8%,30.9%,67.4%,and 28.8%,respectively.Overall,more than 50%of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25%of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80%of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3%in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.
8.Analysis of VWF Gene c.7332G>A Nonsense Mutation Pedigree and Study of Molecular Pathogenesis
Duan-Yang WANG ; Lei WANG ; Dong-Yan FU ; Xiao-Mei LU ; Li-Dong ZHAO ; Jia-Wei ZHENG ; Ya-Lin YU ; Gang WANG ; Lin-Hua YANG
Journal of Experimental Hematology 2025;33(6):1701-1707
Objective:To analyze the genetic characteristics of the VWF gene c.7332G>A nonsense mutation and explore its molecular pathogenesis.Methods:Phenotypic diagnosis of the proband was performed using VWF:Ag,VWF:RCo,FⅧ:C and multimeric analysis.The probands were genotyped by NGS whole-exome sequencing,and the sequencing results were validated by sanger sequencing.The family members were genotyped by Sanger sequencing.The VWF gene c.7332G>A nonsense mutant plasmid was constructed.After transfection,the function of VWF gene c.7332G>A mutant plasmid was verified at cell level in vitro.The mRNA level was detected by qRT-PCR,and the expression level of protein was detected by Western blot,the function of multimerization was verified by the multimeric analysis.Results:VWF:Ag and VWF:RCo were all less than 3%in the proband,and the multimeric analysis showed multimer deficiency.The proband was diagnosed as type 3 VWD.The homozygous nonsense mutation of VWF gene c.7332G>A was detected by gene sequencing.The VWF mRNA level of the mutant plasmid was decreased,and the VWF protein expression in the cell supernatant was decreased,the mutant protein was truncated and the function of VWF multimerization was impaired.Conclusion:A homozygous mutation in exon 43 of VWF gene,c.7332G>A,was responsible for the probands type 3 VWD in the proband.The mutation caused a decrease in the relative level of VWF mRNA and protein,and impaired the function of VWF multimerization.
9.The therapeutic effects of newly formulated Tadalafil tablets on rats with pulmonary fibrosis through promoting histone acetylation
Xiao-qing LIU ; Jie GAO ; Yu-heng LIAO ; Jia-xiu LEI ; Zheng-gang ZHAO ; Fang-hong LI ; Yun-ping MU ; Zi-jian ZHAO
Chinese Pharmacological Bulletin 2025;41(11):2143-2150
Aim To investigate the therapeutic effects of a newly developed Tadalafil tablet on pulmonary fi-brosis induced by paraquat(PQ)in rats,as well as its impact on histone acetylation levels in epithelial cells.Methods SD rats were randomly divided into four groups:the control group(control),the model group(PQ),the Tadalafil new tablet treatment group(N-Tad,1 mg·kg-1),and the positive control drug treatment group(Cialis,5 mg·kg-1).The model group and treatment group rats were intraperitoneally injected with PQ(30 mg·kg-1).Two hours after the initial treatment,the rats in the treatment group re-ceived N-Tad or Cialis via gavage,while the control and model groups were administered an equal volume of physiological saline by gavage once daily for 28 days.The weight gain rate and lung tissue index for each group of rats were calculated.Additionally,the effects of N-Tad treatment on lung tissue structural damage and collagen deposition in rats with PQ-in-duced pulmonary fibrosis were observed using HE stai-ning,Masson trichrome staining,and immunohisto-chemical techniques.By employing the Western blot technique,the effects of Tadalafil intervention on the expression of the epithelial marker E-cadherin(E-Cad),the stromal marker fibronectin(Fn),and the histone acetylation marker acetylated histones(Ac-his-tones)in A549 cells were observed.Results Com-pared to the control group,rats with PQ-induced pul-monary fibrosis exhibited a significant decrease in the rate of body weight growth,an increase in lung tissue index(P<0.05),and a notable increase in the expression and distribution of the fibrosis marker alpha-smooth muscle actin(α-SMA)in lung tissue.The structure of the lung tissue was disrupted,accompanied by the deposition of interstitial collagen fibers.Both N-Tad and Cialis treatments could significantly enhance the rate of weight gain,decrease the lung tissue index,inhibit the expression of α-SMA,and reduce the depo-sition of interstitial collagen in the lung tissue of rats with pulmonary fibrosis.Notably,low-dose N-Tad treatment was comparable to high-dose Cialis treat-ment.At the cellular level,Tadalafil significantly in-hibited the high expression of Fn induced by transfor-ming growth factor beta 1(TGF-β1)in A549 cells.It also upregulated the expression of E-cadherin and sig-nificantly increased the levels of acetylated histones(P<0.05).Conclusions N-Tad promotes histone acetylation in alveolar epithelial cells,significantly in-hibits epithelial-mesenchymal transition,increases E-cadherin expression,and improves lung tissue structur-al damage and collagen deposition caused by PQ.Ad-ditionally,it offers the advantage of a lower effective dose compared to Cialis,providing a new option for the treatment of pulmonary fibrosis.
10.Research status of lactate regulation of chronic liver disease
Lei WANG ; Jia-xin BAI ; Yu-ling ZHUANG ; Jia-hui WANG ; Tie-jian ZHAO ; Na HUANG ; Yang ZHENG ; Hua-ye XIAO
The Chinese Journal of Clinical Pharmacology 2025;41(1):111-115
Excessive fat accumulation,viral infections and sustained inflammatory responses caused by non-alcoholic and alcoholic factors can contribute to liver inflammation,fibrosis and carcinogenesis,promoting the development of chronic liver disease.Gaining an in-depth understanding of the etiologic factors and underlying mechanisms that lead to chronic liver disease can help identify potential therapeutic targets for targeted therapy.Lactate,as an important substance in hepatic metabolism,has been found to be involved in the process of chronic liver disease through various pathways,and this review will provide a useful reference for the prevention and treatment of chronic liver disease.

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