1.Revisiting Intelligent Syndrome Differentiation in Traditional Chinese Medicine under the Disease-Syndrome Combination Model:Perspectives from Disease "Ambiguity and Precision"
Xinlong LI ; Sulin WANG ; Dongning YAN ; Xinran ZHAO ; Genming ZHANG
Journal of Traditional Chinese Medicine 2026;67(7):705-709
The ambiguity of symptom information in traditional Chinese medicine (TCM) syndrome differentiation can be amplified in the direct reasoning process from symptoms to syndromes in the absence of constraints, which affects the accuracy and stability of intelligent syndrome differentiation. TCM disease concepts, while historically rational, are structurally ambiguous in both their connotation and extension, making it difficult to serve as stable prior knowledge in intelligent modeling. In contrast, modern medical diseases, based on objective testing and quantifiable indicators, have relatively clear boundaries and reproducible standards. This study proposes a disease-syndrome combination model, adopting modern medical diseases as structural prior variables to reconstruct the hierarchical relationships among disease, symptoms, and syndromes. By applying disease constraints, effective screening of information from the four examinations and compressing the reasoning space are achieved. Furthermore, by integrating artificial intelligence technologies, such as multimodal fusion and knowledge graphs, an intelligent syndrome differentiation model driven by both prior knowledge and clinical data is constructed, providing a feasible path to enhance the accuracy of syndrome differentiation and realize the intelligentization of TCM diagnosis and treatment.
2.Dynamic Interactions Between Hemispheres Reveal a Compensatory Pathway for Motor Recovery in Moderate-to-Severe Subcortical Stroke
Huaxin FAN ; Hewei WANG ; Zhengxu LIAN ; Qiurong YU ; Xinran WU ; Nanyu KUANG ; Benjamin BECKER ; Jianfeng FENG ; Mingxia FAN ; Lili SONG ; Limin SUN ; Jie ZHANG ; Craig S. ANDERSON
Journal of Stroke 2026;28(1):97-114
Background:
and Purpose Therapeutic target selection in noninvasive brain stimulation for poststroke motor recovery typically relies on the interhemispheric inhibition model, which is effective for mildly affected patients but offers limited benefits for severely affected individuals. The mechanisms governing recovery from moderate-to-severe stroke remain poorly understood, which hinders the development of targeted interventions.
Methods:
We analyzed resting-state functional magnetic resonance imaging data from patients with unilateral subcortical stroke and moderate-to-severe upper limb deficits, both pre- and postintervention, along with data from healthy controls. We developed a novel dynamic lag analysis method for identifying recovery-related homotopic sensorimotor regions with altered interhemispheric interactions. To further uncover the global reorganization pathway, we developed dynamic lateralization approaches to detect large-scale functional connectivity (FC) alterations associated with the identified regions in transient lateralization states.
Results:
Dynamic time-lag analysis revealed significantly reduced synchronized states in the homotopic dorsal premotor cortex (PMd) post-intervention compared with pre-intervention, which correlated with motor recovery. Further dynamic lateralization analysis revealed a prolonged segregation state in patients, characterized by weakened interhemispheric and strengthened intrahemispheric interactions. In this state, patients showed decreased FC in the ipsilesional PMd and increased FC in the contralesional PMd with bilateral subcortical networks. These recoveryrelated alterations were absent in the traditional static analysis.
Conclusions
Dynamic analyses targeting interhemispheric interactions are valuable for understanding neural reorganization after stroke. The diminished interactions between the homotopic PMd indicate a compensatory mechanism. Importantly, a state-dependent compensatory pathway was identified, wherein the contralesional PMd assumes the functions of the ipsilesional PMd through enhanced interactions with subcortical structures, potentially guiding more effective interventions.
3.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.
4.A synthetic peptide, derived from neurotoxin GsMTx4, acts as a non-opioid analgesic to alleviate mechanical and neuropathic pain through the TRPV4 channel.
ShaoXi KE ; Ping DONG ; Yi MEI ; JiaQi WANG ; Mingxi TANG ; Wanxin SU ; JingJing WANG ; Chen CHEN ; Xiaohui WANG ; JunWei JI ; XinRan ZHUANG ; ShuangShuang YANG ; Yun ZHANG ; Linda M BOLAND ; Meng CUI ; Masahiro SOKABE ; Zhe ZHANG ; QiongYao TANG
Acta Pharmaceutica Sinica B 2025;15(3):1447-1462
Mechanical pain is one of the most common causes of clinical pain, but there remains a lack of effective treatment for debilitating mechanical and chronic forms of neuropathic pain. Recently, neurotoxin GsMTx4, a selective mechanosensitive (MS) channel inhibitor, has been found to be effective, while the underlying mechanism remains elusive. Here, with multiple rodent pain models, we demonstrated that a GsMTx4-based 17-residue peptide, which we call P10581, was able to reduce mechanical hyperalgesia and neuropathic pain. The analgesic effects of P10581 can be as strong as morphine but is not toxic in animal models. The anti-hyperalgesic effect of the peptide was resistant to naloxone (an μ-opioid receptor antagonist) and showed no side effects of morphine, including tolerance, motor impairment, and conditioned place preference. Pharmacological inhibition of TRPV4 by P10581 in a heterogeneous expression system, combined with the use of Trpv4 knockout mice indicates that TRPV4 channels may act as the potential target for the analgesic effect of P10581. Our study identified a potential drug for curing mechanical pain and exposed its mechanism.
5.Research progresses of artificial intelligence in imaging diagnosis of children developmental dysplasia of hip
Haoyue LUO ; Xin CHEN ; Jiajun SI ; Jun LI ; Yiran WANG ; Xinran LI ; Ling HE
Chinese Journal of Medical Imaging Technology 2025;41(1):160-163
Developmental dysplasia of hip(DDH)usually occurs in children,and delayed diagnosis of DDH might lead to serious complications and influence long-term prognosis.The application of artificial intelligence(AI)in medical images helps to quantitatively individualize image data,reduce bias generated by manual analysis and achieve early and accurate diagnosis of children DDH.The research progresses of AI in imaging diagnosis of children DDH were reviewed in this article.
6.Morphological and hemodynamic parameters of CT angiography for predicting recurrence of intracranial aneurysms after endovascular embolization
Xinran WANG ; Bin HU ; Zhao SHI ; Longjiang ZHANG
Chinese Journal of Medical Imaging Technology 2025;41(1):9-14
Objective To investigate the value of morphological and hemodynamic parameters of CT angiography(CTA)for predicting recurrence of intracranial aneurysms(IA)after endovascular embolization.Methods Totally 205 patients with ruptured IA who underwent endovascular embolization were retrospectively collected and divided into recurrence group(n=35)and non-recurrence group(n=170)according to follow-up results after embolization.The morphological and hemodynamic parameters of IA in CTA before treatment were compared between groups.Variance inflation factor(VIF)was used to explore whether there was collinearity between morphological and hemodynamic parameters,and those without collinearity were included in univariate and multivariate logistic regression analysis to screen predictors of recurrence of IA after endovascular embolization.Two prediction models were constructed based on morphological parameters(model 1)and combination with hemodynamic parameters(model 2).Receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC)was calculated to evaluate the predictive efficacy of models.Results The maximum diameter,aneurysm neck width,maximum height,maximum vertical height and size ratio(SR)of IA in recurrence group were all higher than those in non-recurrence group(all P<0.05),while gradient oscillatory number(GON)in recurrence group was lower than that in non-recurrence group(P<0.05).The neck width,SR,pressure at IA neck plane,intra-aneurysm time-averaged wall shear stress(TAWSS),oscillatory shear index(OSI)and GON had no significant collinearity(all VIF<10),among which the neck width,SR and TAWSS were all independent predictors(all P<0.05).AUC of model 1 and model 2 for predicting recurrence of IA after endovascular embolization was 0.668 and 0.723,respectively,which of model 2 was higher than which of model 1(integrated discrimination improvement index was 0.055,P=0.025).Conclusion CTA morphological parameters combined with hemodynamic parameters of IA could be used to predict its recurrence after endovascular embolization.
7.Dynamic contrast-enhanced MRI quantitative parameters for differentiating high-and low-grade breast cancer
Xinran LIU ; Zhaorong TIAN ; Na GAO ; Jiale MA ; Zhijun WANG
Chinese Journal of Medical Imaging Technology 2025;41(6):924-927
Objective To explore the value of dynamic contrast-enhanced(DCE)-MRI quantitative parameters based on differential sub-sampling with Cartesian ordering(DISCO)technology for differentiating high-and low-grade breast cancer.Methods A total of 80 patients with single breast cancer confirmed by biopsy pathology were retrospectively enrolled,including 40 cases of low-grade(L group)and 40 cases of high-grade breast cancer(H group).Then quantitative parameters obtained from DISCO-DCE-MRI before treatment were compared between groups,including extravascular extracellular volume fraction(Ve),rate constant(Kep),contrast enhancement ratio(CER),maximum slope(MaxSlope)and volume transfer constant(Ktrans),and their correlations with histological grade were analyzed.Receiver operating characteristic(ROC)curves of DISCO-DCE-MRI quantitative parameters being significantly different between groups were plotted,and the area under the curves(AUC)were calculated to evaluate their efficacy for differentiating high-and low-grade breast cancer.Results Ve(0.91[0.59,0.99]),CER(2.76±0.54)and MaxSlope(0.02[0.01,0.03])in L group were all higher than those in H group(0.52[0.34,0.73],[2.31±0.74],0.01[0.01,0.02],all P<0.05),and no significant difference of Kep nor Ktrans was found between groups(both P>0.05).Ve,CER and MaxSlope of breast cancer were all negatively correlated with histological grade(rs=-0.43,-0.39,-0.35,all P<0.05),while Kep andKtranshad no significant correlation with histological grade(both P>0.05).The AUC of Ve,CER and MaxSlope for differentiating high-and low-grade breast cancer was 0.749,0.725 and 0.700,respectively.Conclusion Among DISCO-DCE-MRI quantitative parameters,Ve,CER and MaxSlope could be used for differentiating high-and low-grade breast cancer.
8.Establishing a risk prediction model for the onset of female stress urinary incontinence based on machine learning
Xinran SHI ; Zhen PANG ; Ting QIAO ; Jingjing LI ; Qinzhang WANG
Journal of Modern Urology 2025;30(3):196-206
Objective: To construct prediction models of female stress urinary incontinence (SUI), and evaluate the efficacy of each model, so as to provide reference for the early diagnosis of SUI. Methods: Female SUI patients treated in our hospital during Oct. 2019 and Oct. 2023 and healthy women undergoing physical examination during the same period were involved. Women 42 days after delivery were included in the postpartum group (n=611), and perimenopausal and postmenopausal women were included in the non-postpartum group (n=409). The number of random seeds was set and the participants were divided into the training and verification sets in a ratio of 7∶3. Relevant clinical data were collected, and meaningful variables were screened using single factor and Lasso regression, which were then incorporated into the K-nearest neighbor method (KNN), support vector machine (SVM),decision tree (DT) and random forest (RF) algorithms. The sensitivity, specificity, accuracy and area under the receiver operating characteristic curve (AUC) of the models were calculated to screen out the optimal model. Results: There were 352 SUI patients (57.6%) in the postpartum group. According to single factor and Lasso regression, significant variables included age, body mass index (BMI), maximum rapid muscle stage, parity, bladder neck mobility (BND), urethral rotation angle (URA), lateral perineal incision, past incontinence, and constipation. In the verification set, the AUC of KNN,SVM,DT and RF models were 0.881,0.878,0.750 and 0.905,respectively; the AUC, accuracy, F1 index and Kappa value of RF model were the largest. In the non-postpartum group, there were 260 SUI patients, accounting for 63.6%. The significant variables were age,BMI, maximum value and recovery time of fast muscle stage, mean value of slow muscle stage, post-resting stage variability, vaginal delivery, past incontinence, and constipation. In the verification set, the AUC of KNN,SVM,DT and RF models were 0.819,0.805,0.603 and 0.830, respectively; the AUC, accuracy, Kappa value of the RF model were the largest. Conclusion: This study successfully established 4 prediction models for the incidence of SUI in women at 42 days postpartum, perimenopausal and postmenopausal women based on machine learning. Among them, the model adopting the RF algorithm had the best prediction efficiency.
9.Effect of electroacupuncture on learning and memory abilities in vascular dementia rats via the NCOA4/FTH1 signaling pathway-mediated ferritinophagy.
Wei SUN ; Yinghua CHEN ; Tong WU ; Hongxu ZHAO ; Haoyu WANG ; Ruiqi QIN ; Xiaoqing SU ; Junfeng LI ; Yuanyu SONG ; Yue MIAO ; Xinran LI ; Yusheng HAN
Chinese Acupuncture & Moxibustion 2025;45(9):1271-1280
OBJECTIVE:
To observe the effect of electroacupuncture at "Sishencong" (EX-HN1) and "Fengchi" (GB20) on hippocampal neuronal ferritinophagy mediated by the nuclear receptor coactivator 4 (NCOA4)/ferritin heavy chain 1 (FTH1) signaling pathway in vascular dementia (VD) rats, and to explore the potential mechanisms of electroacupuncture for VD.
METHODS:
A total of 60 male rats of SPF grade were randomly divided into a blank group (12 rats), a sham surgery group (12 rats) and a modeling group (36 rats). In the modeling group, the modified 4-vessel occlusion method was used to establish the VD model. The 24 successfully modeled rats were randomly divided into a model group and an electroacupuncture group, with 12 rats in each group. In the electroacupuncture group, electroacupuncture was applied at left and right "Sishencong" (EX-HN1), and bilateral "Fengchi" (GB20), with continuous wave, in frequency of 2 Hz and current intensity of 1 mA, 30 min a time, once daily for 21 consecutive days. The learning and memory abilities were assessed using the Morris water maze test before modeling, after modeling and after intervention, as well as the novel object recognition test after intervention. After intervention, the neuronal morphology in the hippocampus was observed by Nissl staining; the iron deposition was observed by Prussian blue staining; the reactive oxygen species (ROS) level was detected by dihydroethidium (DHE) fluorescence staining; the levels of iron, malondialdehyde (MDA) and superoxide dismutase (SOD) in the hippocampal tissue were measured by the colorimetric assay, TBA method, and WST-1 method, respectively; the positive expression of NCOA4, FTH1 and glutathione peroxidase 4 (GPX4) was detected by immunohistochemistry; the protein expression of NCOA4, FTH1, GPX4, and the ratio of microtubule-associated protein 1 light chain 3B (LC3B) Ⅱ/Ⅰ in the hippocampus were detected by Western blot.
RESULTS:
Compared with the sham surgery group, in the model group, the escape latency was prolonged, and the number of platform crossings reduced (P<0.01), the recognition index (RI) was decreased (P<0.01); the hippocampal neurons displayed a blurred laminar structure, disorganized cellular arrangement, and the number of Nissl bodies was decreased (P<0.01); the percentage of iron deposition area in the hippocampus was increased (P<0.01); in the hippocampus, the levels of ROS, iron, MDA, and the protein expression of NCOA4, as well as the LC3B Ⅱ/Ⅰ ratio were increased (P<0.01), the SOD level, and the protein expression of FTH1 and GPX4 were decreased (P<0.01). Compared with the model group, in the electroacupuncture group, the escape latency was shortened and the number of platform crossings was increased (P<0.01), the RI was increased (P<0.01); the hippocampal neurons exhibited more regular morphology, better-organized cellular structure, and the number of Nissl bodies was increased (P<0.05); the percentage of iron deposition area in the hippocampus reduced (P<0.01); in the hippocampus, the levels of ROS, iron, MDA, and the protein expression of NCOA4, as well as the LC3B Ⅱ/Ⅰ ratio were decreased (P<0.01, P<0.05), the SOD level, and the protein expression of FTH1 and GPX4 were increased (P<0.01).
CONCLUSION
Electroacupuncture at "Sishencong" (EX-HN1) and "Fengchi" (GB20) can improve learning and memory abilities in VD rats, and its mechanism may be associated with the regulation of the hippocampal NCOA4/FTH1 signaling pathway, inhibition of ferritinophagy, and alleviation of oxidative stress damage.
Animals
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Electroacupuncture
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Dementia, Vascular/genetics*
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Male
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Rats
;
Signal Transduction
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Humans
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Memory
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Rats, Sprague-Dawley
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Nuclear Receptor Coactivators/genetics*
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Ferritins/genetics*
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Learning
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Hippocampus/metabolism*
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Acupuncture Points
10.Diagnostic value of MS score in macrophage activation syndrome associated with systemic juvenile idiopathic arthritis
Lingling GENG ; Yue PENG ; Duomei SHI ; Li WANG ; Xianyan TANG ; Xinran WEN ; Wenhua ZHANG ; Xiaoqing LI
International Journal of Pediatrics 2025;52(7):476-480
Objective:To explore the diagnostic value of the macrophage activation syndrome/systemic juvenile idiopathic arthritis(MS)score in macrophage activation syndrome(MAS)associated with systemic juvenile idiopathic arthritis(sJIA),and to provide a reference for clinical work.Methods:This study was a retrospective case-control analysis,conducted on the patients initially diagnosed as sJIA-associated with MAS and admitted into the Department of Rheumatology and Immunology of Children's Hospital Affiliated to Xi 'an Jiaotong University from July 1st,2016 to June 30th,2023. All of the patients met the diagnostic criteria for patients with MAS associated with sJIA according to the 2016 European Alliance of Associations for Rheumatology(EULAR)/American College of Rheumatology(ACR)/Pediatric Rheumatology International Trials Organization(PRINTO)standards. The basic information at baseline,clinical manifestations,and auxiliary examination results were collected. The MS score was applied to re-evaluate the children diagnosed as sJIA-associated with MAS. When the MS score ≥-2.1,the possibility of sJIA with MAS was high. Thirty cases of sJIA without MAS were randomly selected as the control group.Results:There were 28 cases in the MAS group,including 13 males(46.43%)and 15 females(53.57%),with an average age of(7.51±4.01)years. Compared with the control group,the MAS group were significantly more likely to have high fever( χ2=8.539, P=0.003),hepatomegaly( χ2=11.621, P<0.001),splenomegaly( χ2=11.710, P<0.001)and neurological involvement( χ2=27.619, P<0.001),with the differences being statistically significant. Meanwhile,there were statistically significant differences between the two groups in terms of white blood cell count( Z=-4.001, P<0.001),neutrophil count( Z=-3.659, P<0.001),platelet count( Z=-4.687, P<0.001),albumin level( Z=-4.018, P<0.001),alanine aminotransferase( Z=-3.846, P<0.001),aspartate aminotransferase( Z=-5.932, P<0.001),lactate dehydrogenase( Z=-6.150, P<0.001),triglycerides( Z=-5.874, P<0.001),fibrinogen( Z=-5.808, P<0.001),ferritin( Z=-5.280, P<0.001),erythrocyte sedimentation rate( Z=-3.971, P<0.001),ferritin/erythrocyte sedimentation rate( Z=-5.433, P<0.001),reduction of two-line cells in blood( χ2=11.408, P<0.001)and the presence of hemophagocytosis in bone marrow smears( χ2=28.260, P<0.001). Moreover,there was a statistically significant difference in MS scores between the two groups( Z=-6.148, P<0.001),with higher MS scores in the MAS group. Nevertheless,this study showed the median MS scores of both groups ≥-2.1. Conclusion:The MS score was significant to a certain degree as reference for the diagnosis of MAS,and this study showed that the MS score in the MAS group was significantly higher than the control group. However,the median MS scores in both groups were no less than -2.1. This might be related to the influence of factors during the assessment,which made it necessary to optimize the cutoff values of the MS score. Therefore,prospective studies should be carried out on the role of MS score in early identification of MAS.

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