1.Effect Analysis of Different Interventions to Improve Neuroinflammation in The Treatment of Alzheimer’s Disease
Jiang-Hui SHAN ; Chao-Yang CHU ; Shi-Yu CHEN ; Zhi-Cheng LIN ; Yu-Yu ZHOU ; Tian-Yuan FANG ; Chu-Xia ZHANG ; Biao XIAO ; Kai XIE ; Qing-Juan WANG ; Zhi-Tao LIU ; Li-Ping LI
Progress in Biochemistry and Biophysics 2025;52(2):310-333
Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.
2.Assessment of genetic associations between antidepressant drug targets and various stroke subtypes: A Mendelian randomization approach.
Luyang ZHANG ; Yunhui CHU ; Man CHEN ; Yue TANG ; Xiaowei PANG ; Luoqi ZHOU ; Sheng YANG ; Minghao DONG ; Jun XIAO ; Ke SHANG ; Gang DENG ; Wei WANG ; Chuan QIN ; Daishi TIAN
Chinese Medical Journal 2025;138(4):487-489
3.Analysis of clinical value of platelet antibody screening in 95 987 inpatients.
Ping CHEN ; Yang SUN ; Xiaoyue CHU ; Fenfang TIAN ; Yingqun YANG ; Wenhua WANG ; Jiameng NIU ; Boya ZHAO ; Jingyan CHANG ; Jiangcun YANG ; Chaofeng MA
Chinese Journal of Cellular and Molecular Immunology 2025;41(2):143-147
Objective To analyze the distribution of platelet antibodies in hospitalized patients and explore the clinical significance of platelet antibody detection. Methods A total of 95 987 hospitalized patient cases from a tertiary hospital in Xi'an from April 1, 2021 to December 31, 2023 were collected. Platelet antibodies were detected by solid-phase agglutination method. Statistical analysis was performed on variables including gender, age, blood type, department, history of blood transfusion, pregnancy history, and disease type. Results Among 95 987 hospitalized patients, the positive rate of platelet antibody detection reached 4.35%. The positive rate of platelet antibodies in female hospitalized patients (5.29%) was higher than that in male patients (3.31%), and the difference was statistically significant (x2=224.124). The positive rate of platelet antibodies in those with pregnancy history (7.92%) was higher than that in those without pregnancy history (4.19%), and the difference was significant (x2=292.773). Similarly, the positive rate of platelet antibodies in those with transfusion history (7.79%) was higher than that in those without transfusion history (3.97%), and the difference was significant (x2=300.209). There was a significant correlation between the positive rate of platelet antibodies and the number of pregnancies (x2=91.061). Conclusion The positive rate of platelet antibodies in 95 987 inpatient cases was 4.35%. The positive rate of platelet antibodies had a close relationship with a history of blood transfusions and pregnancies, and it increased with the number of pregnancies. For patients with multiple transfusion histories and pregnancy histories, screening for platelet antibodies holds significant diagnostic value.
Humans
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Female
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Male
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Adult
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Middle Aged
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Blood Platelets/immunology*
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Inpatients
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Aged
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Pregnancy
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Young Adult
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Adolescent
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Aged, 80 and over
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Autoantibodies/blood*
4.Application Study of Enzyme Inhibitors and Their Conformational Optimization in The Treatment of Alzheimer’s Disease
Chao-Yang CHU ; Biao XIAO ; Jiang-Hui SHAN ; Shi-Yu CHEN ; Chu-Xia ZHANG ; Yu-Yu ZHOU ; Tian-Yuan FANG ; Zhi-Cheng LIN ; Kai XIE ; Shu-Jun XU ; Li-Ping LI
Progress in Biochemistry and Biophysics 2024;51(7):1510-1529
Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive dysfunction and behavioral impairment, and there is a lack of effective drugs to treat AD clinically. Existing medications for the treatment of AD, such as Tacrine, Donepezil, Rivastigmine, and Aducanumab, only serve to delay symptoms and but not cure disease. To add insult to injury, these medications are associated with very serious adverse effects. Therefore, it is urgent to explore effective therapeutic drugs for AD. Recently, studies have shown that a variety of enzyme inhibitors, such as cholinesterase inhibitors, monoamine oxidase (MAO)inhibitors, secretase inhibitors, can ameliorate cholinergic system dysfunction, Aβ production and deposition, Tau protein hyperphosphorylation, oxidative stress damage, and the decline of synaptic plasticity, thereby improving AD symptoms and cognitive function. Some plant extracts from natural sources, such as Umbelliferone, Aaptamine, Medha Plus, have the ability to inhibit cholinesterase activity and act to improve learning and cognition. Isochromanone derivatives incorporating the donepezil pharmacophore bind to the catalytic active site (CAS) and peripheral anionic site (PAS) sites of acetylcholinesterase (AChE), which can inhibit AChE activity and ameliorate cholinergic system disorders. A compound called Rosmarinic acid which is found in the Lamiaceae can inhibit monoamine oxidase, increase monoamine levels in the brain, and reduce Aβ deposition. Compounds obtained by hybridization of coumarin derivatives and hydroxypyridinones can inhibit MAO-B activity and attenuate oxidative stress damage. Quinoline derivatives which inhibit the activation of AChE and MAO-B can reduce Aβ burden and promote learning and memory of mice. The compound derived from the combination of propargyl and tacrine retains the inhibitory capacity of tacrine towards cholinesterase, and also inhibits the activity of MAO by binding to the FAD cofactor of monoamine oxidase. A series of hybrids, obtained by an amide linker of chromone in combine with the benzylpiperidine moieties of donepezil, have a favorable safety profile of both cholinesterase and monoamine oxidase inhibitory activity. Single domain antibodies (such as AAV-VHH) targeted the inhibition of BACE1 can reduce Aβ production and deposition as well as the levels of inflammatory cells, which ultimately improve synaptic plasticity. 3-O-trans-p-coumaroyl maslinic acid from the extract of Ligustrum lucidum can specifically inhibit the activity of γ-secretase, thereby rescuing the long-term potentiation and enhancing synaptic plasticity in APP/PS1 mice. Inhibiting γ-secretase activity which leads to the decline of inflammatory factors (such as IFN-γ, IL-8) not only directly improves the pathology of AD, but also reduces Aβ production. Melatonin reduces the transcriptional expression of GSK-3β mRNA, thereby decreasing the levels of GSK-3β and reducing the phosphorylation induced by GSK-3β. Hydrogen sulfide can inhibitGSK-3β activity via sulfhydration of the Cys218 site of GSK-3β, resulting in the suppression of Tau protein hyperphosphorylation, which ameliorate the motor deficits and cognitive impairment in mice with AD. This article reviews enzyme inhibitors and conformational optimization of enzyme inhibitors targeting the regulation of cholinesterase, monoamine oxidase, secretase, and GSK-3β. We are hoping to provide a comprehensive overview of drug development in the enzyme inhibitors, which may be useful in treating AD.
5.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.
6.Application of IgG antibody combination of wild strain and epidemic strain of COVID-19 in identifying epidemic Omicron BA.5 strain infection
Jinjin CHU ; Hua TIAN ; Chuchu LI ; Zhifeng LI ; Chen DONG ; Xiaoxiao KONG ; Jiefu PENG ; Ke XU ; Jianli HU ; Changjun BAO ; Liguo ZHU
Chinese Journal of Preventive Medicine 2024;58(9):1354-1359
Objective:To explore the application of COVID-19-specific IgG antibody in identifying epidemic Omicron BA.5 strain infection.Method:Omicron BF.7/BA.5 naturally infected population, healthy population vaccinated with the COVID-19 vaccine, and Omicron BF.7/BA.5 breakthrough cases were enrolled into this study. The serum WT-S-IgG and BA.5-S-IgG were detected by indirect ELISA, and the serum-specific IgG antibody levels of different populations were compared. The application value of the two antibody titers and the ratio of the two antibodies in identifying Omicron BA.5 epidemic strain infection were explored by the ROC curve, aiming to provide technical support for pathogen diagnosis.Results:The antibody titers of WT-S-IgG and BA.5-S-IgG in the breakthrough cases were higher than those in the naturally infected population and the healthy population ( P<0.05). The area under the curve (AUC) of WT-S-IgG and BA.5-S-IgG in identifying epidemic Omicron BA.5 strain infection was 0.947 and 0.961, respectively. The AUC of BA.5-S-IgG and WT-S-IgG antibody titer ratio was 0.873. When the antibody titer ratio was 0.855, the sensitivity and specificity were 80.00% and 90.00%, respectively. According to the interval since the last infection, the AUC of the ratio of BA.5-S-IgG to WT-S-IgG antibody titer to identify the infection of epidemic strains less than 30 days and more than 30 days was 0.887 and 0.863, respectively, and the sensitivity and specificity were both above 80%. Conclusion:Both BA.5-S-IgG and WT-S-IgG, as well as the combination of these two antibodies, are of high value in the identification of epidemic strains.
7.Dawn of CAR-T cell therapy in autoimmune diseases
Yuxin LIU ; Minghao DONG ; Yunhui CHU ; Luoqi ZHOU ; Yunfan YOU ; Xiaowei PANG ; Sheng YANG ; Luyang ZHANG ; Lian CHEN ; Lifang ZHU ; Jun XIAO ; Wei WANG ; Chuan QIN ; Daishi TIAN
Chinese Medical Journal 2024;137(10):1140-1150
Chimeric antigen receptor (CAR)-T cell therapy has achieved remarkable success in the treatment of hematological malignancies. Based on the immunomodulatory capability of CAR-T cells, efforts have turned toward exploring their potential in treating autoimmune diseases. Bibliometric analysis of 210 records from 128 academic journals published by 372 institutions in 40 countries/regions indicates a growing number of publications on CAR-T therapy for autoimmune diseases, covering a range of subtypes such as systemic lupus erythematosus, multiple sclerosis, among others. CAR-T therapy holds promise in mitigating several shortcomings, including the indiscriminate suppression of the immune system by traditional immunosuppressants, and non-sustaining therapeutic levels of monoclonal antibodies due to inherent pharmacokinetic constraints. By persisting and proliferating in vivo, CAR-T cells can offer a tailored and precise therapeutics. This paper reviewed preclinical experiments and clinical trials involving CAR-T and CAR-related therapies in various autoimmune diseases, incorporating innovations well-studied in the field of hematological tumors, aiming to explore a safe and effective therapeutic option for relapsed/refractory autoimmune diseases.
8.Development of a risk prediction model for postoperative depression in patients with esophageal cancer
Yunxu ZHOU ; Jiaojiao SUN ; Jinyou LI ; Jiayu LIU ; Ying CHEN ; Jiajin DI ; Tian WANG ; Jianjun CHU ; Zhiqiang WANG
Chinese Journal of Digestion 2024;44(7):467-475
Objective:To explore the risk factors of postoperative depression in patients with esophageal cancer, and to develop a risk prediction model which providing a theoretical basis for the early detection of depression in high-risk groups by clinical staff.Methods:From September 2022 to March 2023, at the South Campus of Affiliated Hospital of Jiangnan University, 269 hospitalized patients with esophageal cancer (191 in depression group, 78 in non-depression group) were selected as the model construction set. From March to May 2023, at the South Campus of Affiliated Hospital of Jiangnan University, 78 hospitalized patients with esophageal cancer were selected as the external validation set. The patients with Beck depression inventory-Ⅱ score ≥5 and depression diagnosed by two experts (chief psychiatrists of the Department of Psychiatry of Affiliated Hospital of Jiangnan University) were considered as depression and included in the depression group, and the other patients were enrolled in the non-depression group. The general data, blood routine examination, high-sensitivity C-reactive protein (hs-CRP), blood electrolytes, blood lipids, clinical symptoms (gastroesophageal reflux, sleep disturbance, appetite, etc.) and depression score were compared between the depression group and the non-depression group. Independent sample t-test and Mann-Whitney U test were used for statistical analysis. Multiple logistic regression model was performed to analyze the independent risk factors of postoperative depression in patients with esophageal cancer, and a risk warning model was constructed. The Hosmer-Lemeshow test and receiver operating characteristic curve (ROC) were used to evaluate the fitting degree and predictive efficiency of the model, and the cross-validation method was used to verify the effectiveness of the model. Results:The incidence of postoperative depression in patients with esophageal cancer was 71.0% (191/269). The total white blood cell count, hs-CRP, blood phosphorus β 2 microglobulin and the proportion of sleep disorders of the depression group were higher than those of the non-depression group (1.3 (1.1, 5.4) ×10 9/L vs. 0.9 (0.3, 1.1) ×10 9/L, 75.8 (54.8, 102.1) mg/L vs. 60.8 (3.6, 61.5) mg/L, (1.33±0.32) mmol/L vs. (1.02±0.19) mmol/L, (2.17±0.72) mg/L vs.(2.12±0.49) mg/L, 84.3% (161/191) vs. 33.3% (26/78), and the differences were statistically significant ( Z=9.24, 7.88, t=9.24, χ2=67.87 t=1.98; all P<0.001); hemoglobin, total platelet count, high-density lipoprotein (HDL) and the proportion of poor appetite were lower than those of the non-depression group ((119.91±24.51) g/L vs. (122.09±22.97) g/L, (203.43±58.45)×10 9/L vs. (311.55±83.54)×10 9/L, (1.04±0.30) mmol/L vs. (1.43±0.23) mmol/L, 73.3% (140/191) vs. 84.6% (66/78)), and the differences were statistically significant ( t=-2.00, -8.42 and -8.48, χ2=3.96; P=0.047, <0.001, <0.001, =0.047). The results of multifactorial logistic regression model analysis showed that sleep disorder ( OR=3.976, 95% confidence interval (95% CI 1.601 to 9.872)), loss of appetite ( OR=0.271, 95% CI 0.092 to 0.791), white blood cell count ( OR=31.808, 95% CI 2.879 to 351.401), hs-CRP ( OR=1.031, 95% CI 1.017 to 1.044), platelet count ( OR=0.990, 95% CI 0.982 to 0.997), and HDL ( OR=0.017, 95% CI 0.001 to 0.242) were independent influencing factors of postoperative depression in patients with esophageal cancer. The formula of risk warning model was probability of depression=1-1/{1+ exp[1.544+ 1.380×sleep disturbance (yes=1, no=0)-1.307×loss of appetite (yes=1, no=0)-0.010×platelet count (×10 9/L)-4.063×HDL (mmol/L)+ 0.030×hs-CRP (mg/L)+ 3.460×white blood cell count (×10 9/L)]}. The results of Hosmer-Lemeshow test showed that the model has a good fit ( χ2=2.01, P=0.981), with an area under the ROC of 0.949, a sensitivity of 0.874, and a specificity of 0.872. The cross-validation of the external validation set showed that the accuracy of the risk warning model was 67.9%. Conclusion:This study is a preliminary study on the risk warning model of postoperative depression in patients with esophageal cancer, which provides a novel approach for screening depression in patients with esophageal cancer after surgery.
9.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; 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 ; Wei LI ; 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 ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
10.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.

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