1.Research on attention-enhanced networks for subtype classification of age-related macular degeneration in optical coherence tomography.
Minghui CHEN ; Wenyi YANG ; Shiyi XU ; Yanqi LU ; Zhengqi YANG ; Fugang LI ; Zhensheng GU
Journal of Biomedical Engineering 2025;42(5):901-909
Subtype classification of age-related macular degeneration (AMD) based on optical coherence tomography (OCT) images serves as an effective auxiliary tool for clinicians in diagnosing disease progression and formulating treatment plans. To improve the classification accuracy of AMD subtypes, this study proposes a keypoint-based, attention-enhanced residual network (KPA-ResNet). The proposed architecture adopts a 50-layer residual network (ResNet-50) as the backbone, preceded by a keypoint localization module based on heatmap regression to outline critical lesion regions. A two-dimensional relative self-attention mechanism is incorporated into convolutional layers to enhance the representation of key lesion areas. Furthermore, the network depth is appropriately increased and an improved residual module, ConvNeXt, is introduced to enable comprehensive extraction of high-dimensional features and enrich the detail of lesion boundary contours, ultimately achieving higher classification accuracy of AMD subtypes. Experimental results demonstrate that KPA-ResNet achieves significant improvements in overall classification accuracy compared with conventional convolutional neural networks. Specifically, for the wet AMD subtypes, the classification accuracies for inactive choroidal neovascularization (CNV) and active CNV reach 92.8% and 95.2%, respectively, representing substantial improvement over ResNet-50. These findings validate the superior performance of KPA-ResNet in AMD subtype classification tasks. This work provides a high-accuracy, generalizable network architecture for OCT-based AMD subtype classification and offers new insights into integrating attention mechanisms with convolutional neural networks in ophthalmic image analysis.
Tomography, Optical Coherence/methods*
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Humans
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Macular Degeneration/diagnostic imaging*
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Neural Networks, Computer
2.Efficacy and Safety of Decitabine-Based Myeloablative Preconditioning Regimen for allogeneic Hematopoietic Stem Cell Transplantation in Patients with Acute Myeloid Leukemia.
Xia-Wei ZHANG ; Jing-Jing YANG ; Ning LE ; Yu-Jun WEI ; Ya-Nan WEN ; Nan WANG ; Yi-Fan JIAO ; Song-Hua LUAN ; Li-Ping DOU ; Chun-Ji GAO
Journal of Experimental Hematology 2025;33(2):557-564
OBJECTIVE:
To analyze the efficacy and safety of decitabine-based myeloablative preconditioning regimen for allogeneic hematopoietic stem cell transplantation (allo-HSCT) in patients with acute myeloid leukemia (AML).
METHODS:
The clinical characteristics and efficacy of 115 AML patients who underwent allo-HSCT at the First Medical Center of Chinese PLA General Hospital from August 2018 to August 2022 were retrospectively analyzed, including 37 patients treated with decitabine conditioning regimen (decitabine group) and 78 patients without decitabine conditioning regimen (non-decitabine group). The cumulative incidence of relapse (CIR), overall survival (OS), leukemia-free survival (LFS), non-relapse mortality (NRM) and graft versus host disease (GVHD) were analyzed.
RESULTS:
For the patients in first complete remission (CR1) state before allo-HSCT, the 1-year relapse rates of decitabine group(22 cases) and non-decitabine group(69 cases) were 9.1% and 29.6%, respectively, the difference was statistically significant(P =0.042). The 1-year cumulative incidence of acute graft-versus-host disease (aGVHD) in decitabine group and non-decitabine group was 62.2% and 70.5%, respectively, and the 1-year cumulative incidence of chronic inhibitor-versus-host disease (cGVHD) was 18.9% and 14.1%, respectively, there were no significant differences in the incidence of aGVHD and cGVHD between the two groups (P >0.05). Of the 115 patients, there were no significantly differences in the 1-year CIR(21.7% vs 28.8%, P =0.866), NRM(10.9% vs 3.9%, P =0.203), OS(75.2% vs 83.8%, P =0.131) and LFS(74.6% vs 69.1%, P =0.912) between the decitabine group(37 cases) and the non-decitabine group(78 cases).
CONCLUSION
Decitabine-based conditioning regimen could reduce the relapse rate of AML CR1 patients with good safety.
Humans
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Leukemia, Myeloid, Acute/therapy*
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Hematopoietic Stem Cell Transplantation/methods*
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Decitabine/therapeutic use*
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Transplantation Conditioning/methods*
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Retrospective Studies
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Graft vs Host Disease
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Transplantation, Homologous
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Male
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Female
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Adult
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Middle Aged
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Adolescent
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Young Adult
3.Study on Differential DNA Methylation Profiles of Patients with High-Altitude Polycythemia.
Jun-Hua JI ; Min YANG ; Yan JIANG ; Ting-Xian YANG ; Xiao-Jing MA ; Qi-Chao YIN ; Hong-Wei YIN ; Lin-Hua JI
Journal of Experimental Hematology 2025;33(2):580-586
OBJECTIVE:
To investigate the whole-genome differential methylation profile of patients with high-altitude polycythemia (HAPC).
METHODS:
In this study, a total of 20 adult male patients with HAPC were included, including 10 Tibetan and 10 Han patients. The control group consisted of 20 healthy adult males, including 10 Tibetan and 10 Han patients. Peripheral blood was collected from each group for DNA extraction and quality inspection, and DNA libraries were constructed. The differential methylation regions (DMRs) between groups were detected using reduced representation bisulfite sequencing, with enriched regions compared to those of the control group. The differential enrichment regions were selected, and the intersection of the enriched regions was associated with genes. The methylation enrichment regions that differed significantly between groups were filtered based on the number of enriched samples in the enriched regions between the groups. GO, KEGG functional, and pathway analysis were performed on the differentially associated gene sets to reveal significant differences between the patients and control groups at the functional and pathway levels.
RESULTS:
In comparison with the control group, 17 152 sites with more than 25% difference and 15 558 sites with less than -25% difference were identified in Tibetan patients. The top 5 genes with the largest methylation differences between the two groups were MCCC2, RP3-399L15.3, ZNF621, RP11-394A14.2 and SLC39A10. The top significantly different pathways annotated in the differentially expressed genes pathway was serotonergic synapse. In comparison with the control group, 2 687 CpG sites with a greater than 25% difference and 2 602 CpG sites with a less than -25% difference were identified in Han patients. The top 5 genes with the largest methylation differences between the two groups were NAA25, CORO2B, PDC, ZNF853, and MLLT10. The top significantly different pathways annotated in the differentially expressed genes pathway were glutamatergic synapse, retrograde endocannabinoid signaling, Rap1 signaling pathway and cholinergic synapse. In comparison with the control group, 3 895 CpG sites with a greater than 25% difference and 3 969 CpG sites with a less than -25% difference were identified in HAPC patients. The maximum methylation difference between the two groups could reach 78.1%, while the minimum was -42.6%. The top 5 genes with the largest methylation differences between the two groups were MCCC2, ARSJ, CTNNA3, SLC39A10, and SWAP70. The top significantly different pathways annotated in the differentially expressed genes pathway was signaling pathways regulating pluripotency of stem cells.
CONCLUSION
The occurrence of HAPC may be related to abnormal changes in DNA methylation, and methylation sites may be helpful for the early diagnosis of HAPC.
Humans
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DNA Methylation
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Altitude
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Polycythemia/genetics*
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Male
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Adult
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CpG Islands
4.Design, synthesis and pharmacological evaluation of 1,2,3,4-tetrahydrobenzofuro2,3-cpyridine derivatives as p21-activated kinase 4 inhibitors for treatment of pancreatic cancer.
Yang LI ; Yan FANG ; Xiaoyu CHEN ; Linjiang TONG ; Fang FENG ; Qianqian ZHOU ; Shulun CHEN ; Jian DING ; Hua XIE ; Ao ZHANG
Acta Pharmaceutica Sinica B 2025;15(1):438-466
The p21-activated kinase 4 (PAK4), a key regulator of malignancy, is negatively correlated with immune infiltration and has become an emergent drug target of cancer therapy. Given the lack of high efficacy PAK4 inhibitors, we herein reported the identification of a novel inhibitor 13 bearing a tetrahydrobenzofuro[2,3-c]pyridine tricyclic core and possessing high potency against MIA PaCa-2 and Pan02 cell lines with IC50 values of 0.38 and 0.50 μmol/L, respectively. This compound directly binds to PAK4 in a non-ATP competitive manner. In the mouse Pan02 model, compound 13 exhibited significant tumor growth inhibition at a dose of 100 mg/kg, accompanied by reduced levels of PAK4 and its phosphorylation together with immune infiltration in mice tumor tissue. Overall, compound 13 is a novel allosteric PAK4 inhibitor with a unique tricyclic structural feature and high potency both in vitro and in vivo, thus making it worthy of further exploration.
5.VenusMutHub: A systematic evaluation of protein mutation effect predictors on small-scale experimental data.
Liang ZHANG ; Hua PANG ; Chenghao ZHANG ; Song LI ; Yang TAN ; Fan JIANG ; Mingchen LI ; Yuanxi YU ; Ziyi ZHOU ; Banghao WU ; Bingxin ZHOU ; Hao LIU ; Pan TAN ; Liang HONG
Acta Pharmaceutica Sinica B 2025;15(5):2454-2467
In protein engineering, while computational models are increasingly used to predict mutation effects, their evaluations primarily rely on high-throughput deep mutational scanning (DMS) experiments that use surrogate readouts, which may not adequately capture the complex biochemical properties of interest. Many proteins and their functions cannot be assessed through high-throughput methods due to technical limitations or the nature of the desired properties, and this is particularly true for the real industrial application scenario. Therefore, the desired testing datasets, will be small-size (∼10-100) experimental data for each protein, and involve as many proteins as possible and as many properties as possible, which is, however, lacking. Here, we present VenusMutHub, a comprehensive benchmark study using 905 small-scale experimental datasets curated from published literature and public databases, spanning 527 proteins across diverse functional properties including stability, activity, binding affinity, and selectivity. These datasets feature direct biochemical measurements rather than surrogate readouts, providing a more rigorous assessment of model performance in predicting mutations that affect specific molecular functions. We evaluate 23 computational models across various methodological paradigms, such as sequence-based, structure-informed and evolutionary approaches. This benchmark provides practical guidance for selecting appropriate prediction methods in protein engineering applications where accurate prediction of specific functional properties is crucial.
6.Expert consensus on the prevention and treatment of radiochemotherapy-induced oral mucositis.
Juan XIA ; Xiaoan TAO ; Qinchao HU ; Wei LUO ; Xiuzhen TONG ; Gang ZHOU ; Hongmei ZHOU ; Hong HUA ; Guoyao TANG ; Tong WU ; Qianming CHEN ; Yuan FAN ; Xiaobing GUAN ; Hongwei LIU ; Chaosu HU ; Yongmei ZHOU ; Xuemin SHEN ; Lan WU ; Xin ZENG ; Qing LIU ; Renchuan TAO ; Yuan HE ; Yang CAI ; Wenmei WANG ; Ying ZHANG ; Yingfang WU ; Minhai NIE ; Xin JIN ; Xiufeng WEI ; Yongzhan NIE ; Changqing YUAN ; Bin CHENG
International Journal of Oral Science 2025;17(1):54-54
Radiochemotherapy-induced oral mucositis (OM) is a common oral complication in patients with tumors following head and neck radiotherapy or chemotherapy. Erosion and ulcers are the main features of OM that seriously affect the quality of life of patients and even the progress of tumor treatment. To date, differences in clinical prevention and treatment plans for OM have been noted among doctors of various specialties, which has increased the uncertainty of treatment effects. On the basis of current research evidence, this expert consensus outlines risk factors, clinical manifestations, clinical grading, ancillary examinations, diagnostic basis, prevention and treatment strategies and efficacy indicators for OM. In addition to strategies such as basic oral care, anti-inflammatory and analgesic agents, anti-infective agents, pro-healing agents, and photobiotherapy recommended in previous guidelines, we also emphasize the role of traditional Chinese medicine in OM prevention and treatment. This expert consensus aims to provide references and guidance for dental physicians and oncologists in formulating strategies for OM prevention, diagnosis, and treatment, standardizing clinical practice, reducing OM occurrence, promoting healing, and improving the quality of life of patients.
Humans
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Chemoradiotherapy/adverse effects*
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Consensus
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Risk Factors
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Stomatitis/etiology*
7.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
8.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; 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 ; Wenhui HUANG ; 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 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
9.Effects of TREM2 on synaptic plasticity induced by cocaine addiction
Rui-ke XU ; Zhi-wen WANG ; Jiao-jiao OUYANG ; Qi DU ; Li-hua LI ; Shi-jun HONG ; Yan-xia PENG ; Gen-meng YANG
Chinese Pharmacological Bulletin 2025;41(12):2341-2347
Aim To investigate the role of triggering receptor expressed on myeloidcells 2(TREM2)in syn-aptic plasticity induced by cocaine addiction.Methods C57BL/6J mice and Trem2 knockout mice were uti-lized in this study to evaluate the alterations in postsyn-aptic density protein 95(PSD-95)and synapsin 1(SYN1)within the cortex and hippocampus of co-caine-addicted mice by using immunological tech-niques.Results HE staining and Nissl staining showed increased neuronal damage in the hippocampus and cortex of mice after cocaine addiction.The results of immunohistochemistry and fluorescence of PSD-95 and SYN1 were consistent with the expression trend of Western blot.In the wild type mouse model,the ex-pression level of PSD-95 in the hippocampus and cortex was lower than that in the saline group,and the ex-pression of SYN1 was higher than that in the saline group.In the knockout mouse model,the expression levels of PSD-95 and SYN1 in the hippocampus and cortex were significantly higher than those in the saline group after cocaine addiction.The expression levels of PSD-95 and SYN1 in the hippocampus and cortex of cocaine knockout mice were higher than those of co-caine wild type mice.Conclusion Cocaine addiction can change the synaptic plasticity,and TREM2 plays a regulatory role in the synaptic plasticity of hippocampus and cortex in mice with cocaine injury.TREM2 is ex-pected to be a new target for studying the mechanism of cocaine addiction.
10.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; 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 ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; 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 2025;25(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

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