1.Study on correlation between homocysteine and diabetes mellitus
Shaorong LIN ; Chunyi ZHEN ; Longfeng CHEN ; Manna CHEN ; Rong ZHOU
International Journal of Laboratory Medicine 2015;(13):1866-1867
Objective To explore the correlation between homocysteine(Hcy),lipids amd type 2 diabetes mellitus (T2DM). Methods The laboratory test results of 533 cases of patients with T2DM(T2DM group)and 362 cases of healthy individuals (healthy control group)were retrospectively analyzed.Results The serum levels of Hcy and rates of abnormal serum cholesterol (TC),triacylglycerol(TG),low density lipoprotein cholesterol(LDL-C),high density lipoprotein cholesterol(HDL-C)levels in the T2DM group were higher than those in the healthy control group,had statistically significant differences(P <0.05).Conclusion The high serum level of Hcy and abnormal lipid metabolism are correlated with T2DM,which might be risk factors of diabetes mel-litus and cardiovascular disease.
2.Effects of functional training on movement performance and balance in elite fencing athletes with patellar tendinopathy
Longfeng ZHOU ; Kun LIU ; Yuhan WANG ; Jun YIN ; Xiangjiang RONG ; Changgui CHEN ; Haikui JIANG
Chinese Journal of Physical Medicine and Rehabilitation 2016;38(9):682-687
Objective To investigate the effect of functional training on knee pain,functional movement screen (FMS) score and balance in Chinese elite fencing athletes with patellar tendinopathy.Methods Twenty-four fencing athletes with a diagnosed patellar tendinopathy were randomized into a treatment group (TG) and a control group (CG),each of 12.Both groups were given routine physical therapy,while TG received motor function training in addition for eight weeks.Both groups completed the numerical rating scale (NRS),FMS and balance test before and after the intervention.Results After the intervention,the average PRS and FMS of TG were 2.08± 1.24 and 16.25±0.97 respectively,which significantly outperformed those of TG before the intervention and those of CG after the intervention (P<0.05).Moreover,TG indicated superior results in parameters of static postural balance including center of pressure,total length of swinging pathway,maximal length of swinging pathway,and area of swinging pathway when compared to TG before the intervention and CG after the intervention(P<0.05).Conclusion The motor functiontraining is effective in improving functional movement and balance in elite fencing athletes with patellar tendinopathy.
3.Dynamic changes of peripheral blood lymphocyte subsets in fever with thrombocytopenia syndrome patients
Yaping HAN ; Donghui ZHOU ; Yali WENG ; Li DONG ; Nian CHEN ; Dongyue ZHANG ; Yuan LIU ; Longfeng JIANG ; Shuang LI ; Zuhu HUANG ; Jun LI
Chinese Journal of Laboratory Medicine 2012;35(9):826-831
Objective The aim of this study is to dynamically investigate peripheral blood lymphocyte subsets in fever with thrombocytopenia syndrome (SFTS) patients at different stages,to evaluate the influence of these changes in the infection process.Methods Case-control study was used in the research.Twelveconfirmedthrombocytopeniasyndromevirus ( SFTSV ) infectedpatientswere enrolled.According to SFTS prevention guide issued by Chinese Ministry of Health,these patients were divided into two groups,recovery group and death group.For each group,dynamic profiles of the CD3 + T cells,CD4 + helper T cells,CD8 + cytotoxic T cell and CD3 - CD16 + CD56 + natural killer cells were tested by flow cytometry.Meanwhile, the relationshipsbetween these dynamicchanges and liver function,leukocytes,and platelets were analyzed respectively.Two independent-samples t test was used to compare the difference of the peripheral blood lymphocyte subsets count between the SFTS patients and healthy control.Small sample was analyzed by Mann-Whitney U test.Results In the early stage of infection,Th cells in peripheral blood of recovery group were significantly reduced and Th/Tc ratio was reversed.On day 5,7,9 of post infection,Th cell counts in peripheral blood were (740.9 ± 6.4),(836.2 ± 272.3 ) and ( 1083.6 ± 319.7 ) cells/μl respectively,which were significantly lower than health control ( 1351.4 ± 295.1 ) cells/μl ( t value was -2.883,-4.235,-2.145 respectively,all P <0.05).Tc cell counts were significantly more than healthy controls (690.1 ± 194.8) cells/μl through the course,which were ( 1006.3 ±356.5),(1166.4±242.4),(1102.4±245.9),(991.3±205.1) and (886.5±154.5) cells/μl on day 7,9,11,13,15 of the course (t value was 3.312,5.661,4.574,3.874,2.382,all P<0.05).NK cells were decreased significantly from the ninth day of the course.Associated with abnormal changes of cell subsets,WBC and PLT decreased significantly,and serum ALT,AST,LDH and CK etc.were higher than normal level.With the disease recovery,the abnormality above was gradually improved.In contrast,death cases showed significant decrease in T and Th cells compared with health control (P < 0.05).On day 7,8,9 of the course,the counts of total T cell were (735.9 ± 359.9),(724.9 ± 125.9),(845.3 ± 389.3) cells/μl and the counts of Th cell were ( 533.2 ± 246.9 ),( 532.1 ± 105.7 ),( 551.7 ± 86.9 ) cells/μl,significantly lower than healthy control ( 1727.9 ± 230.2 ) cells/μl and ( 1351.4 ± 295.1 ) cells/μl,with statistically differences (z value was - 2.828, - 2.342,- 2.342 and - 2.828, - 2.342, - 2.342,all P < 0.05 ).On day 7,8,9 of the course,the numbers of NK cell in death group were ( 1141.8 ± 415.5),( 1047.2 ±68.4),( 1276.3 ±545.3) cells/μl,which were significantly more than health group (470.7 ± 242.2) cells/μl,with statistically differences (z value was - 2.180,- 2.335,- 2.258,all P <0.05).Conclusions SFTSV infection can induce cell immunity damage.The changes of lymphocyte subsets are associated with clinical classification and prognosis.Significant reduction of T cell and CD4 +cell in peripheral blood are accompanied with significant increase of NK cell,which may be a pivotal indicator of poor prognosis and play an important role in making appropriate strategy in clinical treatment.( Chin J Lab Med,2012,35:826-831 )
4.System construction of physical fitness index for pregnant women
Longfeng ZHOU ; Zhaoya SUN ; Ruimin ZHENG ; Mengyun SUN ; Li YANG
Chinese Journal of Perinatal Medicine 2021;24(9):677-681
Objective:Constructing a physical fitness test index system for pregnant women to fully understand their physical fitness level and provide a reference for exercise prescription for this population.Methods:The system was established by way of literature review and Delphi survey, which was further validated on 60 pregnant women undergoing prenatal examination at Maternal and Child Health Hospital of Beijing Haidian District from November 7, 2019, to January 7, 2020. A questionnaire was used to evaluate the satisfaction of pregnant women with the process and results of the physical fitness test. The test and survey data adopted the descriptive analysis. Paired sample t test was used for statistical analysis. Results:The index system of maternal physical fitness test during pregnancy was established through three rounds of expert discussion, and consists of three first-level indexes, 11 second-level indexes, and 23 third-level indexes. All 60 subjects completed the test successfully and no complaints or discomfort were reported. There was no significant difference in the fetal heart rate before and after the test [(142.1±3.8) vs (142.1±4.5) bpm; t=-0.025, P=0.980]. The average test duration was (32.6±3.4) min, and the average load consumption was (300.1±41.2) kcal (1 kcal=4.184 kJ). The questionnaire showed that all subjects were satisfied with the test process and results. Conclusions:The index system of physical fitness test for pregnant women established in this study is scientific, practical, and safe, which is a potential evaluation tool of the physical fitness level for pregnant women.
5.Evaluation of functional training specifically on physical and cognitive functions intervention among children aged 4-5
Chinese Journal of School Health 2021;42(6):883-886
Objective:
To investigate effects of functional training on physical and cognitive function in 4-5 years old children, so as to provide a reference for the research on development of children s physical and cognitive functions.
Methods:
The 173 participants aged 4-5 were enrolled from 6 kindergartens in Xicheng District, Beijing and were divided into experimental (n=94) and control groups (n=79) by randomized digital tables. The experimental group were asked to receive a 18 week special designed functional movement training, which were not performed to the control group. The two groups were tested with physical and cognitive assessments before and after the intervention, and the results were compared pre/post in individual group and between groups with t tests.
Results:
Compared with control group, the score of standing long jump among children in the experimental group was improved by 5.72%, and that of feet jump was improved by 23.79%, that of 10-meter-shuttle run was improved by 13.95%, that of simple reaction was by 20.34%, and that of attention was by 18.96%, and all the improvement was of statistical significance(t=-2.75, 6.68, 10.79, 5.07, 4.32, P<0.01).
Conclusion
Both physical and cognitive functions were enhanced by the functional physical training in 4-5 year-old children.
6.Research progress on medical image dataset expansion methods.
Ying CHEN ; Hongping LIN ; Wei ZHANG ; Longfeng FENG ; Cheng ZHENG ; Taohui ZHOU ; Zhen YI ; Lan LIU
Journal of Biomedical Engineering 2023;40(1):185-192
Computer-aided diagnosis (CAD) systems play a very important role in modern medical diagnosis and treatment systems, but their performance is limited by training samples. However, the training samples are affected by factors such as imaging cost, labeling cost and involving patient privacy, resulting in insufficient diversity of training images and difficulty in data obtaining. Therefore, how to efficiently and cost-effectively augment existing medical image datasets has become a research hotspot. In this paper, the research progress on medical image dataset expansion methods is reviewed based on relevant literatures at home and abroad. First, the expansion methods based on geometric transformation and generative adversarial networks are compared and analyzed, and then improvement of the augmentation methods based on generative adversarial networks are emphasized. Finally, some urgent problems in the field of medical image dataset expansion are discussed and the future development trend is prospected.
Humans
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Diagnosis, Computer-Assisted
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Diagnostic Imaging
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Datasets as Topic
7.A survey of loss function of medical image segmentation algorithms.
Ying CHEN ; Wei ZHANG ; Hongping LIN ; Cheng ZHENG ; Taohui ZHOU ; Longfeng FENG ; Zhen YI ; Lan LIU
Journal of Biomedical Engineering 2023;40(2):392-400
Medical image segmentation based on deep learning has become a powerful tool in the field of medical image processing. Due to the special nature of medical images, image segmentation algorithms based on deep learning face problems such as sample imbalance, edge blur, false positive, false negative, etc. In view of these problems, researchers mostly improve the network structure, but rarely improve from the unstructured aspect. The loss function is an important part of the segmentation method based on deep learning. The improvement of the loss function can improve the segmentation effect of the network from the root, and the loss function is independent of the network structure, which can be used in various network models and segmentation tasks in plug and play. Starting from the difficulties in medical image segmentation, this paper first introduces the loss function and improvement strategies to solve the problems of sample imbalance, edge blur, false positive and false negative. Then the difficulties encountered in the improvement of the current loss function are analyzed. Finally, the future research directions are prospected. This paper provides a reference for the reasonable selection, improvement or innovation of loss function, and guides the direction for the follow-up research of loss function.
Algorithms
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Image Processing, Computer-Assisted
8.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; 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 ; 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 ; 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
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
9.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; 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 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 2024;24(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
10.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.