1.Value of Repeat Renal Biopsy in the Treatment and Prognosis of Patients With Severe Lupus Nephritis.
Maheshati QIAOWAKE ; Wen-Ling YE ; Wei YE ; Yu-Bing WEN ; Gang CHEN ; Peng XIA ; Ke ZHENG ; Hang LI ; Li-Meng CHEN ; Xue-Mei LI
Acta Academiae Medicinae Sinicae 2025;47(5):801-810
Objective To investigate the value of repeat renal biopsy in the treatment and prognosis of nephrotic syndrome(NS)and acute kidney injury(AKI)following immunosuppressive therapy in patients with lupus nephritis(LN). Methods A retrospective analysis was conducted for the clinicopathological data and follow-up records of LN patients undergoing repeat renal biopsy at Peking Union Medical College Hospital from January 1,2009 to December 31,2021. Results A total of 76 patients(55 females,72.4%)were included in this study,with the mean age at the first biopsy being(29.0±10.4)years,the median inter-biopsy interval of 4.0(2.0,7.0) years,and the median total follow-up duration of 7.5(5.0,13.8)years.Pathological transformation occurred in 46(60.5%)patients,and 2 patients had comorbid diabetic nephropathy.At repeat renal biopsy,50(65.8%) patients presented NS.These patients demonstrated lower estimated glomerular filtration rate(eGFR)(P<0.001),higher chronicity index(CI)(P=0.029),and higher complement C3(P<0.001)and C4(P<0.001)levels than those with NS at the first renal biopsy(n=50).Among the 28(36.8%) patients with AKI at repeat renal biopsy,8(28.6%)experienced acute exacerbation of chronic renal insufficiency.These patients exhibited higher serum creatinine level(P=0.002),C4 level(P=0.033),CI(P=0.042),and prevalence of thrombotic microangiopathy(P=0.046)than the patients showing AKI at the first renal biopsy(n=16),while the activity index(AI)showed no significant difference(P=0.051).Over 50% of NS and AKI patients underwent treatment modifications post-repeat renal biopsy,with clinical remission rates comparable to those after the first renal biopsy(both P>0.05).Elevated CI(≥5,P=0.001)and serum creatinine(≥140 μmol/L,P<0.001)at repeat renal biopsy were identified as independent risk factors for poor prognosis.The patients with AKI at repeat renal biopsy had higher incidence of endpoint events than the non-AKI patients(P=0.015).Neither AKI at the first renal biopsy nor NS at both biopsies had significant associations with prognosis. Conclusions Repeat renal biopsy reveals not only sustained high disease activity but also accelerates chronic progression in LN patients,which underscore its critical role in guiding the therapy for severe LN post-immunosuppression.AKI,CI≥5,and serum creatinine ≥140 μmol/L at repeat renal biopsy are strongly associated with poor prognosis.
Humans
;
Lupus Nephritis/drug therapy*
;
Female
;
Retrospective Studies
;
Adult
;
Male
;
Prognosis
;
Biopsy
;
Kidney/pathology*
;
Acute Kidney Injury/pathology*
;
Nephrotic Syndrome/pathology*
;
Glomerular Filtration Rate
;
Young Adult
;
Immunosuppressive Agents/therapeutic use*
;
Middle Aged
2.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
3.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; 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 ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; 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 WEN ; 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(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
4.Research on left ventricle image segmentation approach incorporating a denoising module
Geyuan LI ; Wennan MENG ; Xinzhe XUE ; Yu WANG ; Zheng SUN
Journal of Capital Medical University 2025;46(5):853-859
Objective To address the issue of noise in medical images,this paper proposes a left ventricular image segmentation method integrated with a denoising module to improve segmentation accuracy.Methods The denoising module is based on a denoising diffusion probabilistic model,and the segmentation model includes two branches:motion estimation and segmentation.This paper modifies the prediction target of the denoising module to the original signal instead of noise,enabling the end-to-end cascade training process of the denoising module and the segmentation model.Results On the EchoNet-Dynamic dataset,the segmentation performance of traditional denoising methods was inferior to the benchmark model;the Noise2Noise model showed improvement in three metrics,while our proposed method achieved improvement in all four metrics.On the ACDC dataset,our method outperformed the benchmark model,while other methods either performed worse than the benchmark or showed no statistical difference.Conclusion Traditional denoising methods can impair segmentation performance,whereas our proposed method can stably and effectively improve segmentation performance.Experiments verify the feasibility and potential clinical application value of the proposed method.
5.Artificial intelligence in traditional Chinese medicine: from systems biological mechanism discovery, real-world clinical evidence inference to personalized clinical decision support.
Dengying YAN ; Qiguang ZHENG ; Kai CHANG ; Rui HUA ; Yiming LIU ; Jingyan XUE ; Zixin SHU ; Yunhui HU ; Pengcheng YANG ; Yu WEI ; Jidong LANG ; Haibin YU ; Xiaodong LI ; Runshun ZHANG ; Wenjia WANG ; Baoyan LIU ; Xuezhong ZHOU
Chinese Journal of Natural Medicines (English Ed.) 2025;23(11):1310-1328
Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods*
;
Artificial Intelligence
;
Humans
;
Precision Medicine
;
Decision Support Systems, Clinical
6.Extracellular vesicles as biomarkers and drug delivery systems for tumor.
Xue WANG ; Wenjing CHEN ; Wei ZENG ; Kuanhan FENG ; Yu ZHENG ; Ping WANG ; Fucai CHEN ; Wen ZHANG ; Liuqing DI ; Ruoning WANG
Acta Pharmaceutica Sinica B 2025;15(7):3460-3486
Extracellular vesicles (EVs) are crucial for facilitating intercellular communication, promoting cell migration, and orchestrating the immune response. Recently, EVs can diagnose and treat tumors. EVs can be measured as biomarkers to provide information about the type of disease and therapeutic efficacy. Furthermore, EVs with lower immunogenicity and better biocompatibility are natural carriers of chemicals and gene drugs. Herein, we review the molecular composition, biogenesis, and separation methods of EVs. We also highlight the important role of EVs from different origins as biomarkers and drug delivery systems in tumor therapy. Finally, we provide deep insights into how EVs play a role in reversing the immunosuppressive microenvironment.
7.The protein arginine methyltransferase PRMT1 ameliorates cerebral ischemia-reperfusion injury by suppressing RIPK1-mediated necroptosis and apoptosis.
Tengfei LIU ; Gan HUANG ; Xin GUO ; Qiuran JI ; Lu YU ; Runzhe ZONG ; Yiquan LI ; Xiaomeng SONG ; Qingyi FU ; Qidi XUE ; Yi ZHENG ; Fanshuo ZENG ; Ru SUN ; Lin CHEN ; Chengjiang GAO ; Huiqing LIU
Acta Pharmaceutica Sinica B 2025;15(8):4014-4029
Receptor-interacting protein kinase 1 (RIPK1) plays an essential role in regulating the necroptosis and apoptosis in cerebral ischemia-reperfusion (I/R) injury. However, the regulation of RIPK1 kinase activity after cerebral I/R injury remains largely unknown. In this study, we found the downregulation of protein arginine methyltransferase 1 (PRMT1) was induced by cerebral I/R injury, which negatively correlated with the activation of RIPK1. Mechanistically, we proved that PRMT1 directly interacted with RIPK1 and catalyzed its asymmetric dimethylarginine, which then blocked RIPK1 homodimerization and suppressed its kinase activity. Moreover, pharmacological inhibition or genetic ablation of PRMT1 aggravated I/R injury by promoting RIPK1-mediated necroptosis and apoptosis, while PRMT1 overexpression protected against I/R injury by suppressing RIPK1 activation. Our findings revealed the molecular regulation of RIPK1 activation and demonstrated PRMT1 would be a potential therapeutic target for the treatment of ischemic stroke.
8.Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm.
Xiao-Jie LI ; Le CHANG ; Yang MI ; Ge ZHANG ; Shan-Shan ZHU ; Yue-Xiao ZHANG ; Hao-Yu WANG ; Yi-Shuang LU ; Ye-Xuan PING ; Peng-Yuan ZHENG ; Xia XUE
Journal of Integrative Medicine 2025;23(4):445-456
OBJECTIVE:
Circadian rhythm disruption (CRD) is a risk factor that correlates with poor prognosis across multiple tumor types, including hepatocellular carcinoma (HCC). However, its mechanism remains unclear. This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity.
METHODS:
To quantify CRD, the HCC CRD score (HCCcrds) was developed. Using machine learning algorithms, we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort (n = 369), and the robustness of this method was validated. Furthermore, we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes.
RESULTS:
We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis. The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis, higher pathological grade, and advanced clinical stages, while the CRD-related subtype with low HCCcrds had better clinical outcomes. We also identified novel biomarkers for each subtype, such as nicotinamide n-methyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1.
CONCLUSION
We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers. Within these groups greater HCCcrds was associated with worse prognosis. This approach has the potential to improve prediction of an individual's prognosis, guide precision treatments, and assist clinical decision making for HCC patients. Please cite this article as: Li XJ, Chang L, Mi Y, Zhang G, Zhu SS, Zhang YX, et al. Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm. J Integr Med. 2025; 23(4): 445-456.
Humans
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Carcinoma, Hepatocellular/pathology*
;
Liver Neoplasms/pathology*
;
Circadian Rhythm/genetics*
;
Prognosis
;
Male
;
Female
;
Biomarkers, Tumor/genetics*
;
Middle Aged
;
Machine Learning
;
Computational Biology
9.Research Advances in the Construction and Application of Intestinal Organoids.
Qing Xue MENG ; Hong Yang YI ; Peng WANG ; Shan LIU ; Wei Quan LIANG ; Cui Shan CHI ; Chen Yu MAO ; Wei Zheng LIANG ; Jun XUE ; Hong Zhou LU
Biomedical and Environmental Sciences 2025;38(2):230-247
The structure of intestinal tissue is complex. In vitro simulation of intestinal structure and function is important for studying intestinal development and diseases. Recently, organoids have been successfully constructed and they have come to play an important role in biomedical research. Organoids are miniaturized three-dimensional (3D) organs, derived from stem cells, which mimic the structure, cell types, and physiological functions of an organ, making them robust models for biomedical research. Intestinal organoids are 3D micro-organs derived from intestinal stem cells or pluripotent stem cells that can successfully simulate the complex structure and function of the intestine, thereby providing a valuable platform for intestinal development and disease research. In this article, we review the latest progress in the construction and application of intestinal organoids.
Organoids/cytology*
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Intestines/physiology*
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Humans
;
Animals
;
Pluripotent Stem Cells
10.Association of Longitudinal Change in Fasting Blood Glucose with Risk of Cerebral Infarction in a Patients with Diabetes.
Tai Yang LUO ; Xuan DENG ; Xue Yu CHEN ; Yu He LIU ; Shuo Hua CHEN ; Hao Ran SUN ; Zi Wei YIN ; Shou Ling WU ; Yong ZHOU ; Xing Dong ZHENG
Biomedical and Environmental Sciences 2025;38(8):926-934
OBJECTIVE:
To investigate the association between long-term glycemic control and cerebral infarction risk in patients with diabetes through a large-scale cohort study.
METHODS:
This prospective, community-based cohort study included 12,054 patients with diabetes. From 2006 to 2012, 38,272 fasting blood glucose (FBG) measurements were obtained from these participants. FBG trajectory patterns were generated using latent mixture modelling. Cox proportional hazards models were applied to assess the subsequent risk of cerebral infarction associated with different FBG trajectory patterns.
RESULTS:
At baseline, the mean age of the participants was 55.2 years. Four distinct FBG trajectories were identified based on FBG concentrations and their changes over the 6-year follow-up period. After a median follow-up of 6.9 years, 786 cerebral infarction events were recorded. Different trajectory patterns were associated with significantly varied outcome risks (Log-Rank P < 0.001). Compared with the low-stability group, Hazard Ratio ( HR) adjusted for potential confounders were 1.37 for the moderate-increasing group, 1.23 for the elevated-decreasing group, and 2.08 for the elevated-stable group.
CONCLUSION
Sustained high FBG levels were found to play a critical role in the development of ischemic stroke among patients with diabetes. Controlling FBG levels may reduce the risk of cerebral infarction.
Humans
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Cerebral Infarction/blood*
;
Middle Aged
;
Male
;
Female
;
Blood Glucose/analysis*
;
Fasting/blood*
;
Aged
;
Prospective Studies
;
Risk Factors
;
Diabetes Mellitus/blood*
;
Adult
;
Proportional Hazards Models

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