1.Prediction of Mismatch Repair Deficiency Status in Endometrial Cancer Using Multiparametric MRI Radiomics and Deep Learning: A Multimodal Model with Preliminary Validation
Liru WANG ; Shangying YANG ; Boyu CHEN ; Fuze CONG ; Xinran LI ; Xinyu LIU ; Huadan XUE ; Zhengyu JIN ; Yang XIANG ; Yonglan HE ; Yuan LI
Medical Journal of Peking Union Medical College Hospital 2026;17(4):976-984
To explore the clinical value of a multimodal predictive model based on multiparametric magnetic resonance imaging(MRI) radiomics combined with deep learning(DL) features for the preoperative noninvasive assessment of mismatch repair-deficient(MMRd) status in endometrial cancer(EC). Patients diagnosed with EC at Peking Union Medical College Hospital from January 2015 to December 2021 were retrospectively enrolled and randomly divided into a training set and a validation set at a ratio of 8∶2. Relevant clinical data were collected, and radiomics features and DL features were extracted from preoperative contrast-enhanced T1-weighted imaging(CE-T1WI), fat-suppressed T2-weighted imaging(fs-T2WI), and diffusion-weighted imaging(DWI) sequences. High-dimensional feature selection and dimensionality reduction were performed sequentially using the recursive feature elimination(RFE) algorithm to generate a radiomics score(Rad-score) and a deep learning score(DL-score), respectively. Multivariate logistic regression was utilized to construct a clinical model, a pure radiomics model, a clinical-radiomics model, and an integrated multimodal model incorporating clinical indicators, Rad-score, and DL-score. Model performance was assessed and compared using area under receiver operating characteristic curve(AUC) and DeLong test. A total of 509 patients were enrolled in this study, comprising 413 in the training cohort and 96 in the validation cohort. Independent predictors: Multivariate analysis indicated that preoperative fasting blood glucose level, histological grade, lymph node metastasis status, Rad-score, and DL-score were all independent significant predictors of MMRd status in EC patients. The integrated multimodal model demonstrated optimal predictive performance with an AUC of 0.699(95% CI: 0.635-0.763) in the training set, which was superior to the clinical model(AUC=0.629, 95% CI: 0.561-0.697) and the pure radiomics model(AUC=0.641, 95% CI: 0.575-0.706). In the validation set, the integrated model maintained good generalizability, achieving an AUC of 0.655(95% CI: 0.535-0.775), and its diagnostic efficacy was higher than that of the clinical model(AUC=0.578, 95% CI: 0.450-0.705) and the pure radiomics model(AUC=0.611, 95% CI: 0.488-0.734). According to the DeLong test, the incorporation of DL features resulted in the clinicalradiomicsdeep learning model performing better than both the clinicalonly model( The initially developed clinical-radiomics-deep learning model exhibits a certain predictive potential for the MMRd status in patients with EC. The inclusion of DL features may help complement the limitations of traditional evaluations, offering a preliminary radiological reference for preoperative non-invasive screening. However, given the current diagnostic performance, its overall accuracy and clinical generalizability warrant further validation in multi-center, large-sample external cohort studies.
2.Simultaneous content determination of eleven constituents in Bunao Soft Capsules by HPLC
Ting CHEN ; Xue-mei WANG ; Shuai-yin LI ; Xi-xiang LI ; Ya-li ZHOU ; Xiao-feng LI ; Shou-yuan YANG
Chinese Traditional Patent Medicine 2025;47(7):2144-2148
AIM To establish an HPLC method for the simultaneous content determination of 5-hydroxymethylfurfural,chlorogenic acid,caffeic acid,strychnine,paeoniflorin,ferulic acid,paeoniflorin Ⅰ,epimedium glycoside,psoralen,isopsoralen and glycyrrhetinic acid in Bunao Soft Capsules.METHODS The analysis was performed on a 35 ℃ thermostatic Waters Symmetry C18 column(250 mm×4.6 mm,5 μm),with the mobile phase comprising of acetonitrile-0.1%phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelengths were set at 230,280 nm.RESULTS Eleven constituents showed good linear relationships within their own ranges(r>0.999 0),whose average recoveries were 98.47%-103.30%with RSDs of 1.13%-2.80%.CONCLUSION This simple and reliable method can be used for the quality control of Bunao Soft Capsules.
3.Construction and application of AI course in Medical Immunology
Yuan LIU ; Ming CHU ; Na WANG ; Xintong ZHANG ; Yuedan WANG ; Yintong XUE ; Lijun WANG ; Yan LI ; Jie HAO ; Xiang GAO
Chinese Journal of Immunology 2025;41(6):1294-1300,中插2
Under the background of rapid development of artificial intelligence(AI),this paper systematically proposes AI-based education(AIBE).It empowers the teaching process,learning process,research process,and teaching management with AI,and constructs an AI-based educational paradigm,including AI-based teaching(AIBT),AI-based learning(AIBL),AI-based re-search(AIBR),and AI-based management(AIBM).Taking the AI course of immunology teaching as an example,this paper deeply analyzes the practices and explorations of implementing AIBT,AIBL,AIBR and AIBM based on the AI course,so as to accelerate the promotion of the transformation of the fourth generation of medical education.
4.Association between Fish Consumption and Stroke Incidence Across Different Predicted Risk Populations: A Prospective Cohort Study from China.
Hong Yue HU ; Fang Chao LIU ; Ke Yong HUANG ; Chong SHEN ; Jian LIAO ; Jian Xin LI ; Chen Xi YUAN ; Ying LI ; Xue Li YANG ; Ji Chun CHEN ; Jie CAO ; Shu Feng CHEN ; Dong Sheng HU ; Jian Feng HUANG ; Xiang Feng LU ; Dong Feng GU
Biomedical and Environmental Sciences 2025;38(1):15-26
OBJECTIVE:
The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks.
METHODS:
A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI).
RESULTS:
During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43).
CONCLUSION
Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans
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China/epidemiology*
;
Male
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Female
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Stroke/etiology*
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Middle Aged
;
Prospective Studies
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Incidence
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Aged
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Animals
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Fishes
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Risk Factors
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Diet
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Seafood
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Adult
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Cohort Studies
5.Value of the deep learning automated quantification of tumor-stroma ratio in predicting efficacy and prognosis of neoadjuvant therapy for breast cancer based on residual cancer burden grading
Ting XIE ; Aoling HUANG ; Lingyan XIANG ; Haochen XUE ; Zhengzhuo CHEN ; Aolong MA ; Honglin YAN ; Jingping YUAN
Chinese Journal of Pathology 2025;54(1):59-65
Objective:To investigate the prognostic value of deep learning-based automated quantification of tumor-stroma ratio (TSR) in patients undergoing neoadjuvant therapy (NAT) for breast cancer.Methods:Specimens were collected from 209 breast cancer patients who received NAT at Renmin Hospital of Wuhan University from October 2019 to June 2023. TSR levels in pre-NAT biopsy specimens were automatically computed using a deep learning algorithm and categorized into low stroma (TSR≤30%), intermediate stroma (TSR 30% to ≤60%), and high stroma (TSR>60%) groups. Residual cancer burden (RCB) grading of post-NAT surgical specimens was determined to compare the relationship between TSR expression levels and RCB grades. The correlation of TSR with NAT efficacy was analyzed, and the association between TSR expression and patient prognosis was further investigated.Results:There were 85 cases with low stroma (TSR≤30%), 93 cases with intermediate stroma (TSR 30% to ≤60%), and 31 cases with high stroma (TSR>60%). Different TSR expression levels showed significant differences between various RCB grades ( P<0.05). Logistic univariate and multivariate analyses showed that TSR was a risk factor for obtaining a complete pathological remission from neoadjuvant therapy for breast cancer when it was used as a continuous variable ( P<0.05); COX regression and survival analyses showed that the lower the percentage of tumorigenic mesenchyme was, the better the prognosis of the patient was ( P<0.05). Conclusions:The deep learning-based model enables automatic and accurate quantification of TSR. A lower pre-treatment tumoral stroma is associated with a lower RCB score and a higher rate of pathologic complete response, indicating that TSR can predict the efficacy of neoadjuvant therapy in breast cancer and thus holds prognostic significance. Therefore, TSR may serve as a biomarker for predicting therapeutic outcomes in breast cancer neoadjuvant therapy.
6.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
7.Cerebral syphilitic gumma misdiagnosed as multicentric glioma: a case report
Kun HU ; Xin XIANG ; Zhongqi QI ; Zhengyang LI ; Chenglian XUE ; Linyu HUO ; Ziyan ZHANG ; Yuan GAO ; Jidian SUN ; Fenghui SUN
Chinese Journal of Neurology 2025;58(4):419-425
Neurosyphilis is a group of clinical syndromes caused by treponema pallidum invading the central nervous system and causing varying degrees of damage to the brain parenchyma, brain (spinal) membrane or spinal cord. Cerebral syphilitic gumma is the rarest form of neurosyphilis, and its clinical manifestations lack specificity, which is easily confused with other intracranial space occupying lesions on imaging. In this article, a patient with cognitive dysfunction, intracranial hypertension, and imaging findings similar to multicentric glioma was diagnosed as cerebral syphilitic gumma by serology, cerebrospinal fluid test and brain histopathology. The symptoms basically disappeared after treatment with standard penicillin. This report aims to raise awareness of cerebral syphilitic gumma in order to reduce missed diagnosis and misdiagnosis.
8.Simultaneous content determination of eleven constituents in Bunao Soft Capsules by HPLC
Ting CHEN ; Xue-mei WANG ; Shuai-yin LI ; Xi-xiang LI ; Ya-li ZHOU ; Xiao-feng LI ; Shou-yuan YANG
Chinese Traditional Patent Medicine 2025;47(7):2144-2148
AIM To establish an HPLC method for the simultaneous content determination of 5-hydroxymethylfurfural,chlorogenic acid,caffeic acid,strychnine,paeoniflorin,ferulic acid,paeoniflorin Ⅰ,epimedium glycoside,psoralen,isopsoralen and glycyrrhetinic acid in Bunao Soft Capsules.METHODS The analysis was performed on a 35 ℃ thermostatic Waters Symmetry C18 column(250 mm×4.6 mm,5 μm),with the mobile phase comprising of acetonitrile-0.1%phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelengths were set at 230,280 nm.RESULTS Eleven constituents showed good linear relationships within their own ranges(r>0.999 0),whose average recoveries were 98.47%-103.30%with RSDs of 1.13%-2.80%.CONCLUSION This simple and reliable method can be used for the quality control of Bunao Soft Capsules.
9.Value of the deep learning automated quantification of tumor-stroma ratio in predicting efficacy and prognosis of neoadjuvant therapy for breast cancer based on residual cancer burden grading
Ting XIE ; Aoling HUANG ; Lingyan XIANG ; Haochen XUE ; Zhengzhuo CHEN ; Aolong MA ; Honglin YAN ; Jingping YUAN
Chinese Journal of Pathology 2025;54(1):59-65
Objective:To investigate the prognostic value of deep learning-based automated quantification of tumor-stroma ratio (TSR) in patients undergoing neoadjuvant therapy (NAT) for breast cancer.Methods:Specimens were collected from 209 breast cancer patients who received NAT at Renmin Hospital of Wuhan University from October 2019 to June 2023. TSR levels in pre-NAT biopsy specimens were automatically computed using a deep learning algorithm and categorized into low stroma (TSR≤30%), intermediate stroma (TSR 30% to ≤60%), and high stroma (TSR>60%) groups. Residual cancer burden (RCB) grading of post-NAT surgical specimens was determined to compare the relationship between TSR expression levels and RCB grades. The correlation of TSR with NAT efficacy was analyzed, and the association between TSR expression and patient prognosis was further investigated.Results:There were 85 cases with low stroma (TSR≤30%), 93 cases with intermediate stroma (TSR 30% to ≤60%), and 31 cases with high stroma (TSR>60%). Different TSR expression levels showed significant differences between various RCB grades ( P<0.05). Logistic univariate and multivariate analyses showed that TSR was a risk factor for obtaining a complete pathological remission from neoadjuvant therapy for breast cancer when it was used as a continuous variable ( P<0.05); COX regression and survival analyses showed that the lower the percentage of tumorigenic mesenchyme was, the better the prognosis of the patient was ( P<0.05). Conclusions:The deep learning-based model enables automatic and accurate quantification of TSR. A lower pre-treatment tumoral stroma is associated with a lower RCB score and a higher rate of pathologic complete response, indicating that TSR can predict the efficacy of neoadjuvant therapy in breast cancer and thus holds prognostic significance. Therefore, TSR may serve as a biomarker for predicting therapeutic outcomes in breast cancer neoadjuvant therapy.
10.Application and evaluation of carbon dioxide euthanasia system in experimental teaching of Medical Immunology
Xiang GAO ; Yuan LIU ; Jing LOU ; Yintong XUE ; Yan LI ; Jie HAO ; Lijun WANG ; Ziyuan WANG ; Yinchao MA ; Ming CHU ; Yuedan WANG
Chinese Journal of Immunology 2025;41(8):2003-2006,2011
Experimental teaching is an important component of the course Medical Immunology,which requires the use of experimental animals and the execution of experimental animals by medical students.By applying the carbon dioxide euthanasia system,it can effectively reduce the pain of experimental animals,ensure their welfare,and meet ethical requirements.It can also improve the efficiency of experimental teaching in Medical Immunology,reduce environmental pollution,and promote medical students to estab-lish scientific values and worldviews that pay attention to experimental animals and respect life,which is conducive to becoming future medical service talents.In the experimental teaching of Medical Immunology,the appropriate application of carbon dioxide euthanasia system combined with effective ideological and political construction of the curriculum can further implement the Party's educational policy of cultivating morality and talents,and lay a good foundation for cultivating medical talents with comprehensive knowledge,high skills and excellent quality.

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