1.Electrical stimulation based on triboelectric nanogenerator promotes osteogenesis of MC3T3-E1 cells on titanium surfaces.
Bo PANG ; Shu YANG ; Hongyang HAN ; Xingwei ZHANG ; Tao SONG
Journal of Biomedical Engineering 2025;42(2):366-373
This paper aims to explore the effect of electrical stimulation of triboelectric nanogenerators (TENGs) on the osteogenic and other biological behaviors of mouse embryonic osteoblast precursor cells (MC3T3-E1 cells) on titanium surfaces. First, an origami-type TENG was fabricated, and its electrical output performance was tested. The optimal current of the generator and the feasibility of the experiment were verified by the CCK-8 assay and scratch assay. At the optimal current, the osteogenic conditions of the cells in each group were determined by quantitative analysis of the total protein content, alkaline phosphatase (ALP) activity, and alizarin red staining (ARS) on the titanium surface. Finally, the adhesion and spreading of cells on the titanium surface after electrical stimulation were observed. The results showed that the TENG had good electrical output performance, with an open-circuit voltage of 65 V and a short-circuit current of 42 μA. Compared with the rest of the current, a current strength of 30 μA significantly improved cell proliferation and migration, osteogenesis, and adhesion and spreading capabilities. The above results confirm the safety and operability of TENG in biomedical applications, laying the foundation for future TENG applications in reducing the time of bone integration around titanium implants after surgery.
Titanium/chemistry*
;
Osteogenesis
;
Animals
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Mice
;
Osteoblasts/cytology*
;
Electric Stimulation/instrumentation*
;
Cell Adhesion
;
Cell Proliferation
;
Surface Properties
;
Cell Differentiation
;
Nanotechnology
2.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
3.EEG phase prediction method based on long short-term memory network
Zi-yan PANG ; Xin-yu ZHAO ; Wen-shu MAI ; Yue-zhuo ZHAO ; Zhi-peng LIU ; Tao YIN ; Jing-na JIN
Chinese Medical Equipment Journal 2025;46(3):1-8
Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P<0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89%)was higher than that by the traditional AR method(about 10%).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]
4.EEG phase prediction method based on long short-term memory network
Zi-yan PANG ; Xin-yu ZHAO ; Wen-shu MAI ; Yue-zhuo ZHAO ; Zhi-peng LIU ; Tao YIN ; Jing-na JIN
Chinese Medical Equipment Journal 2025;46(3):1-8
Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P<0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89%)was higher than that by the traditional AR method(about 10%).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]
5.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
6.A multi-center epidemiological study on pneumococcal meningitis in children from 2019 to 2020
Cai-Yun WANG ; Hong-Mei XU ; Gang LIU ; Jing LIU ; Hui YU ; Bi-Quan CHEN ; Guo ZHENG ; Min SHU ; Li-Jun DU ; Zhi-Wei XU ; Li-Su HUANG ; Hai-Bo LI ; Dong WANG ; Song-Ting BAI ; Qing-Wen SHAN ; Chun-Hui ZHU ; Jian-Mei TIAN ; Jian-Hua HAO ; Ai-Wei LIN ; Dao-Jiong LIN ; Jin-Zhun WU ; Xin-Hua ZHANG ; Qing CAO ; Zhong-Bin TAO ; Yuan CHEN ; Guo-Long ZHU ; Ping XUE ; Zheng-Zhen TANG ; Xue-Wen SU ; Zheng-Hai QU ; Shi-Yong ZHAO ; Lin PANG ; Hui-Ling DENG ; Sai-Nan SHU ; Ying-Hu CHEN
Chinese Journal of Contemporary Pediatrics 2024;26(2):131-138
Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]
7.Analysis on configuration of testing equipment in blood testing laboratories of blood stations in Shandong Province
Xiao-Tong SUN ; Zhong-Si YANG ; Hui-Xia ZHAO ; Shu-Tao PANG
Chinese Medical Equipment Journal 2024;45(3):81-85
Objective To analyze the configuration of testing equipment in blood testing laboratories of blood stations in Shandong Province to facilitate to optimize equipment configuration for blood testing laboratories.Methods Questionnaires were distributed to obtain information on the number,the proportions of domestic and imported equipment,the usage time and the number of annual sample detection for the testing equipment of 17 blood testing laboratories(one laboratory from blood center and 16 laboratories from central blood stations)in Shandong Province,including the equipment for blood group testing,alanine aminotransferase(ALT)testing,sample adding of enzyme-linked immunosorbent assay(ELISA),ELISA micro-plate processing and nucleic amplification test(NAT).The testing equipment in the laboratories with different sizes were analyzed in terms of substitutability,localization,number of annual sample detection and average usage time.Results The blood group and ALT testing equipment had low substitutability;the imported equipment for ALT testing and ELISA sample adding had high proportions;the numbers of yearly sample detection of the equipment for ELISA sample adding,ELISA microplate processing and NAT rose significantly with the increase of laboratory sizes(P<0.05);the equipment for ELISA sample adding and microplate processing had long usage time,and the differences between the usage time of the equipment for ELISA sample adding from the laboratories with different sizes were statistically significant(P<0.05).Conclusion The equipment configuration of blood testing laboratories of blood stations in Shandong Province varies greatly,and each laboratory has to take measures based on their own actual situations,such as increasing the number of equipment,purchasing domestic equipment or accelerating equipment updating.[Chinese Medical Equipment Journal,2024,45(3):81-85]
8.Changes in the Non-targeted Metabolomic Profile of Three-year-old Toddlers with Elevated Exposure to Polycyclic Aromatic Hydrocarbons
Yang LI ; Dan LIN ; Qin Xiu ZHANG ; Xiu Guang JU ; Ya SU ; Qian ZHANG ; Ping Hai DUAN ; Sen Wei YU ; Ling Bing WANG ; Tao Shu PANG
Biomedical and Environmental Sciences 2024;37(5):479-493
Objective To investigate changes in the urinary metabolite profiles of children exposed to polycyclic aromatic hydrocarbons(PAHs)during critical brain development and explore their potential link with the intestinal microbiota. Methods Liquid chromatography-tandem mass spectrometry was used to determine ten hydroxyl metabolites of PAHs(OH-PAHs)in 36-month-old children.Subsequently,37 children were categorized into low-and high-exposure groups based on the sum of the ten OH-PAHs.Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was used to identify non-targeted metabolites in the urine samples.Furthermore,fecal flora abundance was assessed by 16S rRNA gene sequencing using Illumina MiSeq. Results The concentrations of 21 metabolites were significantly higher in the high exposure group than in the low exposure group(variable importance for projection>1,P<0.05).Most of these metabolites were positively correlated with the hydroxyl metabolites of naphthalene,fluorine,and phenanthrene(r=0.336-0.531).The identified differential metabolites primarily belonged to pathways associated with inflammation or proinflammatory states,including amino acid,lipid,and nucleotide metabolism.Additionally,these distinct metabolites were significantly associated with specific intestinal flora abundances(r=0.34-0.55),which were mainly involved in neurodevelopment. Conclusion Higher PAH exposure in young children affected metabolic homeostasis,particularly that of certain gut microbiota-derived metabolites.Further investigation is needed to explore the potential influence of PAHs on the gut microbiota and their possible association with neurodevelopmental outcomes.
9.A multicenter epidemiological study of acute bacterial meningitis in children.
Cai Yun WANG ; Hong Mei XU ; Jiao TIAN ; Si Qi HONG ; Gang LIU ; Si Xuan WANG ; Feng GAO ; Jing LIU ; Fu Rong LIU ; Hui YU ; Xia WU ; Bi Quan CHEN ; Fang Fang SHEN ; Guo ZHENG ; Jie YU ; Min SHU ; Lu LIU ; Li Jun DU ; Pei LI ; Zhi Wei XU ; Meng Quan ZHU ; Li Su HUANG ; He Yu HUANG ; Hai Bo LI ; Yuan Yuan HUANG ; Dong WANG ; Fang WU ; Song Ting BAI ; Jing Jing TANG ; Qing Wen SHAN ; Lian Cheng LAN ; Chun Hui ZHU ; Yan XIONG ; Jian Mei TIAN ; Jia Hui WU ; Jian Hua HAO ; Hui Ya ZHAO ; Ai Wei LIN ; Shuang Shuang SONG ; Dao Jiong LIN ; Qiong Hua ZHOU ; Yu Ping GUO ; Jin Zhun WU ; Xiao Qing YANG ; Xin Hua ZHANG ; Ying GUO ; Qing CAO ; Li Juan LUO ; Zhong Bin TAO ; Wen Kai YANG ; Yong Kang ZHOU ; Yuan CHEN ; Li Jie FENG ; Guo Long ZHU ; Yan Hong ZHANG ; Ping XUE ; Xiao Qin LI ; Zheng Zhen TANG ; De Hui ZHANG ; Xue Wen SU ; Zheng Hai QU ; Ying ZHANG ; Shi Yong ZHAO ; Zheng Hong QI ; Lin PANG ; Cai Ying WANG ; Hui Ling DENG ; Xing Lou LIU ; Ying Hu CHEN ; Sainan SHU
Chinese Journal of Pediatrics 2022;60(10):1045-1053
Objective: To analyze the clinical epidemiological characteristics including composition of pathogens , clinical characteristics, and disease prognosis acute bacterial meningitis (ABM) in Chinese children. Methods: A retrospective analysis was performed on the clinical and laboratory data of 1 610 children <15 years of age with ABM in 33 tertiary hospitals in China from January 2019 to December 2020. Patients were divided into different groups according to age,<28 days group, 28 days to <3 months group, 3 months to <1 year group, 1-<5 years of age group, 5-<15 years of age group; etiology confirmed group and clinically diagnosed group according to etiology diagnosis. Non-numeric variables were analyzed with the Chi-square test or Fisher's exact test, while non-normal distrituction numeric variables were compared with nonparametric test. Results: Among 1 610 children with ABM, 955 were male and 650 were female (5 cases were not provided with gender information), and the age of onset was 1.5 (0.5, 5.5) months. There were 588 cases age from <28 days, 462 cases age from 28 days to <3 months, 302 cases age from 3 months to <1 year of age group, 156 cases in the 1-<5 years of age and 101 cases in the 5-<15 years of age. The detection rates were 38.8% (95/245) and 31.5% (70/222) of Escherichia coli and 27.8% (68/245) and 35.1% (78/222) of Streptococcus agalactiae in infants younger than 28 days of age and 28 days to 3 months of age; the detection rates of Streptococcus pneumonia, Escherichia coli, and Streptococcus agalactiae were 34.3% (61/178), 14.0% (25/178) and 13.5% (24/178) in the 3 months of age to <1 year of age group; the dominant pathogens were Streptococcus pneumoniae and the detection rate were 67.9% (74/109) and 44.4% (16/36) in the 1-<5 years of age and 5-<15 years of age . There were 9.7% (19/195) strains of Escherichia coli producing ultra-broad-spectrum β-lactamases. The positive rates of cerebrospinal fluid (CSF) culture and blood culture were 32.2% (515/1 598) and 25.0% (400/1 598), while 38.2% (126/330)and 25.3% (21/83) in CSF metagenomics next generation sequencing and Streptococcus pneumoniae antigen detection. There were 4.3% (32/790) cases of which CSF white blood cell counts were normal in etiology confirmed group. Among 1 610 children with ABM, main intracranial imaging complications were subdural effusion and (or) empyema in 349 cases (21.7%), hydrocephalus in 233 cases (14.5%), brain abscess in 178 cases (11.1%), and other cerebrovascular diseases, including encephalomalacia, cerebral infarction, and encephalatrophy, in 174 cases (10.8%). Among the 166 cases (10.3%) with unfavorable outcome, 32 cases (2.0%) died among whom 24 cases died before 1 year of age, and 37 cases (2.3%) had recurrence among whom 25 cases had recurrence within 3 weeks. The incidences of subdural effusion and (or) empyema, brain abscess and ependymitis in the etiology confirmed group were significantly higher than those in the clinically diagnosed group (26.2% (207/790) vs. 17.3% (142/820), 13.0% (103/790) vs. 9.1% (75/820), 4.6% (36/790) vs. 2.7% (22/820), χ2=18.71, 6.20, 4.07, all P<0.05), but there was no significant difference in the unfavorable outcomes, mortility, and recurrence between these 2 groups (all P>0.05). Conclusions: The onset age of ABM in children is usually within 1 year of age, especially <3 months. The common pathogens in infants <3 months of age are Escherichia coli and Streptococcus agalactiae, and the dominant pathogen in infant ≥3 months is Streptococcus pneumoniae. Subdural effusion and (or) empyema and hydrocephalus are common complications. ABM should not be excluded even if CSF white blood cell counts is within normal range. Standardized bacteriological examination should be paid more attention to increase the pathogenic detection rate. Non-culture CSF detection methods may facilitate the pathogenic diagnosis.
Adolescent
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Brain Abscess
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Child
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Child, Preschool
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Escherichia coli
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Female
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Humans
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Hydrocephalus
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Infant
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Infant, Newborn
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Male
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Meningitis, Bacterial/epidemiology*
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Retrospective Studies
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Streptococcus agalactiae
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Streptococcus pneumoniae
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Subdural Effusion
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beta-Lactamases
10.EPOSTER • DRUG DISCOVERY AND DEVELOPMENT
Marwan Ibrahim ; Olivier D LaFlamme ; Turgay Akay ; Julia Barczuk ; Wioletta Rozpedek-Kaminska ; Grzegorz Galita ; Natalia Siwecka ; Ireneusz Majsterek ; Sharmni Vishnu K. ; Thin Thin Wi ; Saint Nway Aye ; Arun Kumar ; Grace Devadason ; Fatin Aqilah Binti Ishak ; Goh Jia Shen ; Dhaniya A/P Subramaniam ; Hiew Ke Wei ; Hong Yan Ren ; Sivalingam Nalliah ; Nikitha Lalindri Mareena Senaratne ; Chong Chun Wie ; Divya Gopinath ; Pang Yi Xuan ; Mohamed Ismath Fathima Fahumida ; Muhammad Imran Bin Al Nazir Hussain ; Nethmi Thathsarani Jayathilake ; Sujata Khobragade ; Htoo Htoo Kyaw Soe ; Soe Moe ; Mila Nu Nu Htay ; Rosamund Koo ; Tan Wai Yee ; Wong Zi Qin ; Lau Kai Yee ; Ali Haider Mohammed ; Ali Blebil ; Juman Dujaili ; Alicia Yu Tian Tan ; Cheryl Yan Yen Ng ; Ching Xin Ni ; Michelle Ng Yeen Tan ; Kokila A/P Thiagarajah ; Justin Jing Cherg Chong ; Yong Khai Pang ; Pei Wern Hue ; Raksaini Sivasubramaniam ; Fathimath Hadhima ; Jun Jean Ong ; Matthew Joseph Manavalan ; Reyna Rehan ; Tularama Naidu ; Hansi Amarasinghe ; Minosh Kumar ; Sdney Jia Eer Tew ; Yee Sin Chong ; Yi Ting Sim ; Qi Xuan Ng ; Wei Jin Wong ; Shaun Wen Huey Lee ; Ronald Fook Seng Lee ; Wei Ni Tay ; Yi Tan ; Wai Yew Yang ; Shu Hwa Ong ; Yee Siew Lim ; Siddique Abu Nowajish ; Zobaidul Amin ; Umajeyam Anbarasan ; Lim Kean Ghee ; John Pinto ; Quek Jia Hui ; Ching Xiu Wei ; Dominic Lim Tao Ran ; Philip George ; Chandramani Thuraisingham ; Tan Kok Joon ; Wong Zhi Hang ; Freya Tang Sin Wei ; Ho Ket Li ; Shu Shuen Yee ; Goon Month Lim ; Wen Tien Tan ; Sin Wei Tang
International e-Journal of Science, Medicine and Education 2022;16(Suppl1):21-37


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