1.Hepatitis C virus infection:surveillance report from China Healthcare-as-sociated Infection Surveillance System in 2020
Xi-Mao WEN ; Nan REN ; Fu-Qin LI ; Rong ZHAN ; Xu FANG ; Qing-Lan MENG ; Huai YANG ; Wei-Guang LI ; Ding LIU ; Feng-Ling GUO ; Shu-Ming XIANYU ; Xiao-Quan LAI ; Chong-Jie PANG ; Xun HUANG ; An-Hua WU
Chinese Journal of Infection Control 2024;23(1):1-8
Objective To investigate the infection status and changing trend of hepatitis C virus(HCV)infection in hospitalized patients in medical institutions,and provide reference for formulating HCV infection prevention and control strategies.Methods HCV infection surveillance results from cross-sectional survey data reported to China Healthcare-associated Infection(HAI)Surveillance System in 2020 were summarized and analyzed,HCV positive was serum anti-HCV positive or HCV RNA positive,survey result was compared with the survey results from 2003.Results In 2020,1 071 368 inpatients in 1 573 hospitals were surveyed,738 535 of whom underwent HCV test,4 014 patients were infected with HCV,with a detection rate of 68.93%and a HCV positive rate of 0.54%.The positive rate of HCV in male and female patients were 0.60%and 0.48%,respectively,with a statistically sig-nificant difference(x2=47.18,P<0.001).The HCV positive rate in the 50-<60 age group was the highest(0.76%),followed by the 40-<50 age group(0.71%).Difference among all age groups was statistically signifi-cant(x2=696.74,P<0.001).In 2003,91 113 inpatients were surveyed.35 145 of whom underwent HCV test,resulting in a detection rate of 38.57%;775 patients were infected with HCV,with a positive rate of 2.21%.In 2020,HCV positive rates in hospitals of different scales were 0.46%-0.63%,with the highest in hospital with bed numbers ranging 600-899.Patients'HCV positive rates in hospitals of different scales was statistically signifi-cant(X2=35.34,P<0.001).In 2020,12 provinces/municipalities had over 10 000 patients underwent HCV-rela-ted test,and HCV positive rates ranged 0.19%-0.81%,with the highest rate from Hainan Province.HCV posi-tive rates in different departments were 0.06%-0.82%,with the lowest positive rate in the department of pedia-trics and the highest in the department of internal medicine.In 2003 and 2020,HCV positive rates in the depart-ment of infectious diseases were the highest,being 7.95%and 3.48%,respectively.Followed by departments of orthopedics(7.72%),gastroenterology(3.77%),nephrology(3.57%)and general intensive care unit(ICU,3.10%)in 2003,as well as departments of gastroenterology(1.35%),nephrology(1.18%),endocrinology(0.91%),and general intensive care unit(ICU,0.79%)in 2020.Conclusion Compared with 2003,HCV positive rate decreased significantly in 2020.HCV infected patients were mainly from the department of infectious diseases,followed by departments of gastroenterology,nephrology and general ICU.HCV infection positive rate varies with gender,age,and region.
2.Exploration on bioactive equivalent combinatorial components of Xiaoke formula and its mechanism based on insulin resistance mice
Jian ZHANG ; Wen-juan MA ; Lin-jie DONG ; Jiang-lan LONG ; Yu ZHANG ; Dan YAN
Acta Pharmaceutica Sinica 2024;59(6):1698-1705
Xiaoke formula (XKF) is a classic formula for the treatment of insulin resistance (IR), but there is still unclear on bioactive equivalent combinatorial components (BECC) of XKF. In this study, based on the previous research of our team, three components, berberine, astragaloside IV and chlorogenic acid, were selected as the BECC of XKF, and their efficacy and mechanism were investigated. A high-fat diet-induced IR mouse model was used to detect blood glucose, insulin sensitivity, lipid metabolism, immune & inflammatory factors, etc., and staining of pathology sections was used to detect histopathological changes. Network pharmacology was used to predict the potential targets and signaling pathways of XKF and its BECC, and the results of the network were verified by Western blot. The animal welfare and experimental procedures followed the regulations of the Laboratory Animal Ethics Committee of Beijing MDKN Biotech Company (MDKN-2023-019). The results showed that BECC, which was composed of berberine, astragaloside IV and chlorogenic acid in the ratio of the original formula of XKF, was comparable to XKF in improving the glycemia, insulin sensitivity, histopathological damage, dyslipidemia, and immuno-inflammation in IR mice. The results of network pharmacology and Western blot suggested that the BECC of XKF and XKF might alleviate IR by promoting the activation of hepatic phosphatidylinositol 3-kinase (PI3K), phosphorylation of protein kinase B (AKT), and inhibiting the expression of glucose-6-phosphate phosphatase (G6PC) and phosphoenolpyruvate carboxykinase 1 (PCK1), the key limiting enzymes of hepatic gluconeogenesis. The above results suggest that berberine, astragaloside IV and chlorogenic acid can be used as the potential BECC of XKF to improve IR, and can regulate lipid metabolism, immuno-inflammation, and promote hepatic PI3K/AKT signaling to inhibit hepatic gluconeogenesis, regulate glucose homeostasis, and improve IR in mice.
3.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
4.Advances and clinical transformation of microsphere drug delivery systems
Qi-long WU ; Wen-yue LAN ; Ming-jie CUI ; Jun-jue WANG ; Wen-hao CHENG ; Hai-jun YU
Acta Pharmaceutica Sinica 2024;59(12):3242-3250
The microsphere drug delivery systems have been extensively exploited for providing controllable drug release kinetics, enhancing drug stability and localized drug delivery. In past decade, dozens of microsphere drug delivery systems have been developed for clinical therapy of cancer, schizophrenia and neurodegenerative diseases (e.g., Alzheimer's disease and Parkinsonism). In this review article, we comprehensively summarized the fabrication methods of drug delivery systems and highlighted their advances for clinical application. Furthermore, we analyzed the potential and the challenges for clinical translation of the drug delivery systems.
5.Near Infrared Spectral Analysis Based on Data Augmentation Strategy and Convolutional Neural Network
Yun ZHENG ; Si-Yu YANG ; Tao WANG ; Zhuo-Wen DENG ; Wei-Jie LAN ; Yong-Huan YUN ; Lei-Qing PAN
Chinese Journal of Analytical Chemistry 2024;52(9):1266-1276
Near infrared spectroscopy(NIRS)technology combined with chemometrics algorithms has been widely used in quantitative and qualitative analysis of food and medicine.However,traditional chemometrics methods,especially linear classification methods,often yield unsatisfactory results when addressing multi-class classification problems.Convolutional neural network(CNN)is adept at extracting deep-level features from data and suitable for handling non-linear relationships.The modeling performance of CNN depends on the size and diversity of sample,while the collection and preprocessing of NIRS sample data is often time-consuming and labor-intensive.This study proposed a NIRS qualitative analysis method based on data augmentation strategies and CNN.The data augmentation strategy included two steps.Firstly,applying Bootstrap resampling and generative adversarial network(GAN)methods to augment three NIRS datasets(Medicine,coffee and grape).Secondly,combining the original samples(Y)with the Bootstrap augmented samples(B)and GAN augmented samples(G)to obtain three augmented datasets(Y-B,Y-G and Y-B-G).Based on this,a CNN model structure suitable for these datasets was designed,consisting of 2 one-dimensional convolutional layers,1 max-pooling layer,and 1 fully connected layer.The results showed that compared to the optimal models of partial least squares discriminant analysis(PLS-DA),support vector machine(SVM),and back propagation neural network(BP),the CNN model based on Y-B dataset achieved average accuracy improvements of 3.998%,9.364%,and 4.689%for medicine(Binary classification);the CNN model based on the Y-B-G dataset achieved average accuracy improvements of 6.001%,2.004%,and 7.523%for coffee(7-class classification);and the CNN model based on the Y-B dataset achieved average accuracy improvements of 33.408%,51.994%,and 34.378%for grapes(20-class classification).It was evident that the models established based on data augmentation strategies and CNN demonstrated better classification accuracy and generalization performance with different datasets and classification categories.
6.Effect of knockdown of ARHGAP30 on proliferation and apoptosis of Siha cells
Ya-Ting PENG ; Duan LIU ; Jie MENG ; Wen-Chao LI ; Hui-Qi LI ; Hua GUO ; Mei-Lan NIU ; Qiao-Hong QIN
Chinese Pharmacological Bulletin 2024;40(5):847-853
Aim To investigate the changes in the proliferation and apoptosis of Siha cells after knocking down Rho GTPase-activating protein 30(ARHGAP30).Methods After designing specific shARHGAP30 primers and connecting them to the pLKO.1 vector,we transformed them into Escherichia coli competent cells,then co-transfecting them with lentiviral helper plasmids into HEK-293T cells.We collected and filtered cell supernatant to obtain the vi-rus to infect Siha cells.RT-qPCR and Western blot were used to detect knockdown efficiency,as well as changes in the expression of Bax and Bcl-2 after trans-fection.The CCK-8 method was employed to measure the proliferation level of cells after knockdown.Results After successful construction of a lentiviral plasmid with knockdown of the ARHGAP30 gene and establish-ment of stably transfected Siha cells,ARHGAP30 tran-scription and translation(P<0.01)in Siha cells de-creased,Bax/Bcl-2 significantly decreased(P<0.01),indicating decreased apoptosis and increased cell proliferation(P<0.01).Conclusions This study suggests the involvement of ARHGAP30 in the proliferation and apoptosis of Siha cells,and regulating the ARHGAP30 gene may interfere with the occurrence and development of cervical cancer.
7.Effect of High-Concentration Uric Acid on Nitric Oxide.
Si-Yu QIN ; Rong-Yu LAN ; Jia ZENG ; Xue BAI ; Jing-Tao WANG ; Xiang-Lin YIN ; Rui-Jie QU ; Ming-Hai QU ; Hao JIANG ; Wen-Long LI ; Si-Ying PEI ; Zhi-Ling HOU ; Bao-Sheng GUAN ; Hong-Bin QIU
Acta Academiae Medicinae Sinicae 2023;45(4):666-671
Uric acid (UA) is the final product of purine metabolism in human body,and its metabolic disorder will induce hyperuricemia (HUA).The occurrence and development of HUA are associated with a variety of pathological mechanisms such as oxidative stress injury,activation of inflammatory cytokines,and activation of renin-angiotensin-aldosterone system.These mechanisms directly or indirectly affect the bioavailability of endogenous nitric oxide (NO).The decrease in NO bioavailability is common in the diseases with high concentration of UA as an independent risk factor.In this review,we summarize the mechanisms by which high concentrations of UA affect the endogenous NO bioavailability,with a focus on the mechanisms of high-concentration UA in decreasing the synthesis and/or increasing the consumption of NO.This review aims to provide references for alleviating the multisystem symptoms and improving the prognosis of HUA,and lay a theoretical foundation for in-depth study of the correlations between HUA and other metabolic diseases.
Humans
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Nitric Oxide
;
Uric Acid
;
Hyperuricemia
;
Biological Availability
;
Cytokines
8.Brain age prediction method based on deep convolutional generative adversarial network
Min XIONG ; Wen-Jie KANG ; Lan LIN
Chinese Medical Equipment Journal 2023;44(12):1-6
Objective To propose a brain age prediction method based on deep convolutional generative adversarial networks(DCGAN)for objective assessment of brain health status.Methods The DCGAN model was extended from 2D to 3D and improved by integrating the concept of residual block to enhance the ability for feature extraction.The classifiers were pre-trained with unsupervised adversarial learning and fine-tuned with migration learning to eliminate the overfitting of 3D convolutional neural network(CNN)due to small sample size.To verify the effectiveness of the improved model,comparison analyses based on UK Biobank(UKB)database were carried out between the improved model and least absolute shrinkage and selection operator(LASSO)model,machine learning model,3D CNN model and graph convolutional network model by using mean absolute error(MAE)as the evaluation metric.Results The model proposed gained advantages over LASSO model,machine learning model,3D CNN model and graph convolutional network model in predicting brain age with a MAE error of 2.896 years.Conclusion The method proposed behaves well for large-scale datasets,which can predict brain age accurately and assess brain health status objectively.
9.Establishment of contralateral arteriovenous fistula by using the waste vein on the side of central venous lesion: a case report.
Xue Dong BAO ; Ya Xue SHI ; Min YU ; Si Jie LIU ; Lan Hua MI ; Chang WU ; Wen Ping HU
Chinese Journal of Hepatology 2023;39(1):36-38
Central venous lesion is a difficult problem in the vascular access complications of hemodialysis, which can cause serious clinical symptoms and affect the quality of hemodialysis and life of patients. We established arteriovenous fistula of the contralateral graft blood vessel with the used vein on the diseased side of the central vein of the patient. The arteriovenous fistula of the graft blood vessel was successfully punctured and hemodialysis was performed 2 weeks later. In this way, we not only solved the problem of venous hypertension and subsequent vascular access in the patient, but also reserved more vascular resources.
Humans
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Arteriovenous Shunt, Surgical/adverse effects*
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Blood Vessel Prosthesis Implantation
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Treatment Outcome
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Renal Dialysis
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Arteriovenous Fistula
10.LOX-1 Regulation in Anti-atherosclerosis of Active Compounds of Herbal Medicine: Current Knowledge and the New Insight.
Si-Jie YAO ; Tao-Hua LAN ; Xin-Yu ZHANG ; Qiao-Huang ZENG ; Wen-Jing XU ; Xiao-Qing LI ; Gui-Bao HUANG ; Tong LIU ; Wei-Hui LYU ; Wei JIANG
Chinese journal of integrative medicine 2023;29(2):179-185
Lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1) have recently been identified to be closely related to the occurrence and development of atherosclerosis (AS). A growing body of evidence has suggested Chinese medicine takes unique advantages in preventing and treating AS. In this review, the related research progress of AS and LOX-1 has been summarized. And the anti-AS effects of 10 active components of herbal medicine through LOX-1 regulation have been further reviewed. As a potential biomarker and target for intervention in AS, LOX-1 targeted therapy might provide a promising and novel approach to atherosclerotic prevention and treatment.
Humans
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Atherosclerosis
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Scavenger Receptors, Class E/physiology*
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Biomarkers
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Plant Extracts
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Lipoproteins, LDL

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