1.Multicenter study on the etiology characteristics of neonatal purulent meningitis
Yanli LIU ; Jiaojiao CAI ; Xiaoyi ZHANG ; Minli ZHU ; Zhenlang LIN ; Yicong PAN ; Junhu ZHENG ; Yiwei ZHAO ; Xiang WANG ; Hongping LU ; Meifang LIN ; Ji WANG ; Haihong GU ; Lizhen WANG ; Keping CHENG ; Yuxuan DAI ; Yuan GAO ; Junsheng LI ; Hongxia FANG ; Na SUN ; Lihua LI ; Xiaoquan LI ; Ying LIU ; Yingyu LI ; Wa GAO ; Minxia LI
Chinese Journal of Infectious Diseases 2023;41(6):393-400
Objective:To study the distribution and antibiotics resistance of the main pathogens of neonatal purulent meningitis in different regions of China.Methods:A retrospective descriptive clinical epidemiological study was conducted in children with neonatal purulent meningitis which admitted to 18 tertiary hospitals in different regions of China between January 2015 to December 2019. The test results of blood and cerebrospinal fluid, and drug sensitivity test results of the main pathogens were collected. The distributions of pathogenic bacteria in children with neonatal purulent meningitis in preterm and term infants, early and late onset infants, in Zhejiang Province and other regions outside Zhejiang Province, and in Wenzhou region and other regions of Zhejiang Province were analyzed. The chi-square test was used for statistical analysis.Results:A total of 210 neonatal purulent meningitis cases were collected. The common pathogens were Escherichia coli ( E. coli)(41.4%(87/210)) and Streptococcus agalactiae ( S. agalactiae)(27.1%(57/210)). The proportion of Gram-negative bacteria in preterm infants (77.6%(45/58)) with neonatal purulent meningitis was higher than that in term infants (47.4%(72/152)), and the difference was statistically significant ( χ2=15.54, P=0.001). There were no significant differences in the constituent ratios of E. coli (36.5%(31/85) vs 44.8%(56/125)) and S. agalactiae (24.7%(21/85) vs 28.8%(36/125)) between early onset and late onset cases (both P>0.05). The most common pathogen was E. coli in different regions, with 46.7%(64/137) in Zhejiang Province and 31.5%(23/73) in other regions outside Zhejiang Province. In Zhejiang Province, S. agalactiae was detected in 49 out of 137 cases (35.8%), which was significantly higher than other regions outside Zhejiang Province (11.0%(8/73)). The proportions of Klebsiella pneumoniae, and coagulase-negative Staphylococcus in other regions outside Zhejiang Province (17.8%(13/73) and 16.4%(12/73)) were both higher than those in Zhejiang Province (2.9%(4/137) and 5.1%(7/137)). The differences were all statistically significant ( χ2=14.82, 12.26 and 7.43, respectively, all P<0.05). The proportion of Gram-positive bacteria in Wenzhou City (60.8%(31/51)) was higher than that in other regions in Zhejiang Province (38.4%(33/86)), and the difference was statistically significant ( χ2=6.46, P=0.011). E. coli was sensitive to meropenem (0/45), and 74.4%(32/43) of them were resistant to ampicillin. E. coli had different degrees of resistance to other common cephalosporins, among which, cefotaxime had the highest resistance rate of 41.8%(23/55), followed by ceftriaxone (32.4%(23/71)). S. agalactiae was sensitive to penicillin, vancomycin and linezolid. Conclusions:The composition ratios of pathogenic bacteria of neonatal purulent meningitis are different in different regions of China. The most common pathogen is E. coli, which is sensitive to meropenem, while it has different degrees of resistance to other common cephalosporins, especially to cefotaxime.
2.Follow-up study of fetal cardiac birth defects after prenatal diagnosis and graded counseling
Junjun SHEN ; Chengcheng PANG ; Liuqing YANG ; Xieyi LIN ; Yingyu WANG ; Yuping HUANG ; Yufen LI ; Wei PAN
Chinese Journal of Obstetrics and Gynecology 2022;57(4):278-283
Objective:To explore accurate prenatal diagnosis, full-coverage graded counseling and follow-up for the fetus with cardiac birth defects (CBD).Methods:CBD fetus diagnosed prenatal by echocardiography from January 2018 to December 2020 in Guangdong Provincial People's Hospital were enrolled. Fetal CBD was graded (Ⅰ-Ⅵ) according to prognosis and possible operation time after birth, and the classification criteria and common diseases included were proposed. After the prenatal grading counseling, the outcome of the fetus was followed-up. The induced labor rate, live birth rate, prenatal and postnatal ultrasound diagnosis coincidence rate and other indicators were calculated. The disease composition ratio, prognosis of fetus with different grades and the outcome of integrated treatment were analyzed.Results:The detection rate of fetal CBD was up to 16.2% (1 971/12 188), 30 cases of which were excluded. A total of 1 941 cases were included in this study, including 196 cases (10.1%) of gradeⅠ, 433 cases (22.3%) of gradeⅡ, 615 cases (31.7%) of grade Ⅲ, 261 cases (13.4%) of grade Ⅳ, 388 cases (20.0%) of gradeⅤ, 48 cases (2.5%) of grade Ⅵ. Grade Ⅱ and gradeⅢ (the operation time was within 1 year after birth) accounted for 54.0% (1 048/1 941). The distribution of some diseases in different grades had obvious proportion advantage, which was representative. Among 1 747 CBD fetus, 736 cases (induced labor rate 42.1%) chose to terminate pregnancy due to CBD. Of the 1 010 live births, 975 cases (96.5%) had the same prenatal and postnatal diagnosis, 3 cases were missed diagnosis and 32 cases were misdiagnosed. The diagnostic accuracy of live births with severe and complex congenital heart disease was 383 out of 389 (98.5%). A total of 258 cases have received surgery or intervention. The age at the time of surgery or intervention was different among grades( χ2 =47.3, P<0.001). With the improvement of prognosis from gradeⅠ to Ⅴ, the live birth rate increased and the induced labor rate decreased accordingly; the difference between grades was significant( χ2 =623.6, P<0.001). Conclusions:Prenatal diagnosis and graded counseling is important in the integrated model. Fetal CBD grading could refine post-natal treatment strategies, guide delivery decisions and become an evaluation standard.
3.Fiber direction estimation using constrained spherical deconvolution based on multi-model response function.
Journal of Biomedical Engineering 2022;39(6):1117-1126
Constrained spherical deconvolution can quantify white matter fiber orientation distribution information from diffusion magnetic resonance imaging data. But this method is only applicable to single shell diffusion magnetic resonance imaging data and will provide wrong fiber orientation information in white matter tissue which contains isotropic diffusion signals. To solve these problems, this paper proposes a constrained spherical deconvolution method based on multi-model response function. Multi-shell data can improve the stability of fiber orientation, and multi-model response function can attenuate isotropic diffusion signals in white matter, providing more accurate fiber orientation information. Synthetic data and real brain data from public database were used to verify the effectiveness of this algorithm. The results demonstrate that the proposed algorithm can attenuate isotropic diffusion signals in white matter and overcome the influence of partial volume effect on fiber direction estimation, thus estimate fiber direction more accurately. The reconstructed fiber direction distribution is stable, the false peaks are less, and the recognition ability of cross fiber is stronger, which lays a foundation for the further research of fiber bundle tracking technology.
Brain
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White Matter/diagnostic imaging*
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Diffusion Magnetic Resonance Imaging/methods*
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Algorithms
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Databases, Factual
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Image Processing, Computer-Assisted/methods*
4.The effects of Zhiling capsule on the proliferation inhibition and apoptosis induction in K562 cell line via caspase-3 pathway
Zhihong ZHENG ; Yunling PAN ; Yingyu CHEN ; Mingji PAN ; Tingbo LIU ; Jianda HU
Chinese Pharmacological Bulletin 2003;0(09):-
Aim To investigate the effects of Zhiling capsule (ZLJN) on the proliferation inhibition and apoptosis induction in K562 cell line.Methods According to the different components of ZLJN,K562 cells were treated respectively with tradtional Chinese medicine,Western medicine and ZLJN compound groups.The cell viability and colony formation were observed by MTT assay and colony formation assay respectively.Apoptotic cells were detected by Annexin V-FITC/PI staining and DNA fragmentation assay.Caspase-3 activity was detected by flow cytometry,and pro-caspase-3 was detected by Western blot.Results Treated with drug,K562 cell growth and cell colony formation were significantly inhibited.Apoptosis occurring in the early stage was identified by Annexin V-FITC/PI staining.Typical DNA ladder was seen from gel electrophoresis and apparent apoptotic peaks were observed by flow cytometer.The level of caspase-3 activity increased after the treatment,while the level of pro-caspase-3 decreased.Conclusion ZLJN can efficiently inhibit proliferation and induce apoptosis in K562 cells,which may be related with the up-regulation of caspase-3 activity.
5.Effects of Zhiling capsule on apoptosis and expressions of hTERT,CD44 in small cell lung cancer cell line NCI-H446
Yingyu CHEN ; Yunling PAN ; Zhihong ZHENG ; Mingji PAN ; Jianda HU ; Tingbo LIU
Chinese Pharmacological Bulletin 2003;0(10):-
Aim To explore the mechanisms of the apoptosis induction and the effects of adhesion suppression of Zhiling capsule (ZLJN) in small cell lung cancer cell line NCI-H446.Methods According to the different components of ZLJN,NCI-H446 cells were treated with traditional Chinese medicine,western medicine and ZLJN composite groups.Apoptotic cells were tested by light microscopy,Hochest33258 staining method.The mRNA and protein expressions of bcl-2,bax and hTERT were analyzed by RT-PCR and Western blot respectively.The expressions of CD44 were detected by flow cytometry.Results After NCI-H446 cells were treated with different drug groups,The morphological changes of apoptotic cells were found by light microscopy and Hochest33258 staining method.The mRNA and protein expressions of bcl-2 were down-regulated while the expressions of bax were up-regulated compared to the control groups(P

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