ObjectiveThis study aims to develop a prediction model for the compatibility of Chinese medicinal pairs based on Graph Convolutional Networks （GCN）， named HC-GCN. The model integrates the properties of herbs with modern pharmacological mechanisms to predict pairs with specific therapeutic effects. It serves as a demonstration by applying the model to predict and validate the efficacy of blood-activating herb pairs. MethodsThe training dataset for herb pair prediction was constructed by systematically collecting commonly used herb pairs along with their characteristic data， including Qi， flavor， meridian tropism， and target genes. Integrating traditional characteristics of herb with modern bioinformatics， we developed an efficacy-oriented herb pair compatibility prediction model （HC-GCN） using graph convolutional networks （GCN）. This model leverages machine learning to capture the complex relationships in herb pair compatibility， weighted by efficacy features. The performance of the HC-GCN model was evaluated using accuracy （ACC）， recall， precision， F1 score （F1）， and area under the ROC curve （AUC）. Its predictive effectiveness was then compared to five other machine learning models： eXtreme Gradient Boosting （XGBoost）， logistic regression （LR）， Naive Bayes， K-nearest neighbor （KNN）， and support vector machine （SVM）. ResultsUsing herb pairs with blood-activating effects as a demonstration， a prediction model was constructed based on a foundational dataset of 46 blood-activating herb pairs， incorporating their Qi， flavor， meridian tropism， and target gene characteristics. The HC-GCN model outperforms other commonly used machine learning models in key performance metrics， including ACC， recall， precision， F1 score， and AUC. Through the predictive analysis of the HC-GCN model， 60 herb pairs with blood-activating effects were successfully identified. Among of these potential herb pairs， 44 include at least one herb with blood-activating effects. ConclusionIn this study， we established an efficacy-oriented compatibility prediction model for herb pairs based on GCN by integrating the unique characteristics of traditional herbs with modern pharmacological mechanisms. This model demonstrated high predictive performance， offering a novel approach for the intelligent screening and optimization of traditional Chinese medicine prescriptions， as well as their clinical applications.

Background::Genetic variants of dopaminergic transcription factor-encoding genes are suggested to be Parkinson’s disease (PD) risk factors; however, no comprehensive analyses of these genes in patients with PD have been undertaken. Therefore, we aimed to genetically analyze 16 dopaminergic transcription factor genes in Chinese patients with PD.Methods::Whole-exome sequencing (WES) was performed using a Chinese cohort comprising 1917 unrelated patients with familial or sporadic early-onset PD and 1652 controls. Additionally, whole-genome sequencing (WGS) was performed using another Chinese cohort comprising 1962 unrelated patients with sporadic late-onset PD and 1279 controls.Results::We detected 308 rare and 208 rare protein-altering variants in the WES and WGS cohorts, respectively. Gene-based association analyses of rare variants suggested that MSX1 is enriched in sporadic late-onset PD. However, the significance did not pass the Bonferroni correction. Meanwhile, 72 and 1730 common variants were found in the WES and WGS cohorts, respectively. Unfortunately, single-variant logistic association analyses did not identify significant associations between common variants and PD. Conclusions::Variants of 16 typical dopaminergic transcription factors might not be major genetic risk factors for PD in Chinese patients. However, we highlight the complexity of PD and the need for extensive research elucidating its etiology.

Abstract Fangjiomics is a promising paradigm that enhances research on multi-omics-based pharmacological mechanisms of Fangji from holistic and systematic perspective. We reviewed recent advances in Fangjiomics, focusing on database and analysis platform development, methodological innovations, and translational applications. Through the integration of Fangji and multi-omics data, multi-level system analysis approaches were developed, encompassing single-target analysis, signaling pathways, multi-targeted network and modules. Fangjiomics has emerged as a key strategy in various areas of Fangji research. To support the high quality development of Fangjiomics, we propose principles and perspectives from the integrated, macro-level, and practical viewpoints.

Objective To discuss the application of the"rotating guidewire and correcting the filter recovery hook direction technique"("rotation-correction loop technique"for short),a technique invented by the authors in clinical practice,in the retrieval of complex inferior vena cava filter(IVCF),and to discuss its technical skills and advantages.Methods The clinical data of 417 patients carrying an IVCF,who were admitted to the Department of Vascular Surgery of Second Hospital of Shanxi Medical University of China to retrieve IVCF between January 2022 and December 2022,were retrospectively analyzed.Taking the time spent on the retrieval of IVCF and the intraoperative radiation dose as the evaluation indicators,the advantages and disadvantages of the standard filter retrieval technique,the"rotation-correction loop technique"and the other loop-assisted techniques were compared.Results Both the intraoperative radiation dose and the time spent on the retrieval of IVCF using"rotation-correction loop technique"were remarkably lower than those of other loop-assisted techniques(P＜0.000 1).Conclusion For the retrieval of complex IVCF,especially for the IVCF which is heavily tilted and/or its recovered hook is attached to the vascular wall,the use of"rotation-correction loop technique"can shorten the time spent on the the retrieval of IVCF and reduce the intraoperative radiation dose.This technique carries high safety and practicability,the device is simple and it can be manipulated by single physician,which is conducive to clinical application and promotion.(J Intervent Radiol,2024,33:289-294)

The syndrome/pattern of defensive qi deficiency is a common basic syndrome of traditional Chinese medicine in clinical practice. However,there is a lack of standardized and operable diagnostic specifications in practical applications. Based on the previous literature,this study proposed the idea of starting from the elements of the syndrome,qualitative diagnostic criteria for the syndrome/pattern of defensive qi deficiency oriented to the entire region of the disease were constructed based on the two dimensions of " deficient defensive qi failing to consolidate the exterior" and " qi deficiency" and constructing a set of quantitative evaluation criteria as the supporting content for the diagnostic items. The core members of the research group attempted to formulate the draft standard,then reached a consensus through the Delphi method expert questionnaire consultation and the Nominal group technique,and finally evaluated the reliability and validity of the standard through clinical verification to provide ideas for the standardization and normalization of research on syndromes.

Objective To investigate the clinical significance of combined cerebrospinal fluid(CSF)and routine blood parameter analysis in differentiating between multiple cerebral glioma(MCG)and primary central nervous system lymphoma(PCNSL).Methods We Rretrospectively analyzed the clinical data,CSF and routine blood indicators levels of 62 MCG patients and 56 PCNSL patients admitted to Beijing Tiantan Hospital,Capital Medical University from November 2017 to March 2023.Additionally,we assessed the diagnostic value of individual meaningful indicators as well as their combinations in distinguishing between MCG and PCNSL.Results The levels of CSF total cell count,CSF white cell count,CSF:pro,lactate,routine bloodperipheral neutrophil count,and neu-trophil percentage were significantly higher in the MCG group than in the PCNSL group(P<0.05);while the levels of CSF:Glu,CSF:cl,routine blood lymphocyte count,eosinophil,lymphocyte percentage,and eosinophil percent-age were significantly higher in the PCNSL group than in the MCG group(P<0.05).The AUCs of CSF cell count,CSF white cell count,CSF:pro,lactate,routine blood neutrophil count,neutrophil percentage for differentiating MCG from PCNSL were 0.900,0.899,0.797,0.867,0.828 and 0.772 respectively;sensitivities were 72.4%,77.6%,63.8%,67.2%,72.4%,82.8%,77.6%and 81%,with sensitivities of 97.1%,100%,88.2%,91.2%,88.2%,64.7%,100%and 94.1%,respectively.In addition,the combined detection of CSF total cell count,CSF white cell count,CSF:pro,routine blood neutrophil count and neutrophil percentage in CSF had an AUC of 0.919 for differentiating MCG from PCNSL,with a sensitivity and specificity of 77.6%and 100%,respectively.Conclusions Combined detection of CSF indicators including CSF total cell count,CSF white cell count,CSF:pro,along with routine blood markers such as neutrophil count and neutrophil percentage,holds significant clinical utility for differ-entiating between MCG and PCNSL.

Objective:To retrospectively summarize the clinical characteristics and treatment of 49 patients with hyperthyroid cardiopath and to explore the diagnosis and treatment methods of hyperthyroid cardiopathy.Methods:A total of 49 patients with hyperthyroid cardiopath(HC group) who were successfully treated and followed up in the Department of Endocrinology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, from January 2016 to December 2021 were collected, and 85 cases of Graves′ disease without heart disease were collected as the control group(GD group). The medical history, laboratory tests, and echocardiographic parameters of the two groups were compared. Differences in thyroid and cardiac indicators before and after treatment in the HC group were summarized, along with the dosage of β-receptor blockers used in treating different types of conditions(atrial fibrillation and heart failure.Results:Patients in the HC group were older and had a longer duration of hyperthyroidism than those in the GD group( P<0.001, P=0.002). There were no significant differences in thyroid hormone levels between the two groups except for reverse triiodothyronine(rT 3). Age and rT 3 were independent risk factors of hyperthyroid cardiopathy. rT 3 level was linearly positively correlated with brain natriuretic peptide, systolic pulmonary artery pressure, left artrium diamete (LAD) and left ventricular end-systolic diameter(LVDs; r=0.352, P<0.001; r=0.392, P=0.019; r=0.202, P=0.029; r=0.242, P=0.028). In patients of HC group, free triiodothyronine(FT 3) level returned to normal range after 2.87(1.63, 5.53) months of treatment with radioiodine(41/49) or antithyroid drugs(8/49), while brain natriuretic peptide, LAD, LVDs, and systolic pulmonary artery pressure declined after 5.00(1.25, 8.00) months of treatment. Non-selective β-receptor blockers were used for both hyperthyroid heart failure and atrial fibrillation, and there was no statistically significant difference in dosage[(86.52±47.83)mg vs(88.67±47.19)mg, P>0.05]. Conclusions:rT 3 may be a biomarker of hyperthyroid cardiopath and indicate the severity of hyperthyroidism. β-receptor blockers are crucial in treating patients with hyperthyroidism who develop atrial fibrillation and heart failure.

The significant increase in clinical diagnosis research of Parkinson′s disease (PD) using artificial intelligence technology not only reflects its potential application in the field of medical engineering, but also highlights its important value in improving diagnostic efficiency and accuracy of PD. This review aims to systematically elaborate the current research status of artificial intelligence in the clinical diagnosis of PD through comprehensive analysis of existing literature, and deeply explore its latest research progress and existing problems in tremor detection, facial expression recognition, speech recognition, gait analysis, and radiomics analysis, providing reference and suggestions for the future clinical practice.

OBJECTIVE To design paclitaxel prodrug nanoparticles with dual reactive oxygen species/glutathione response (ProPTX-SS-NPs), providing new ideas and methods for the application of paclitaxel. METHODS The optimal preparation method and process of prodrug nanoparticles was investigated by using particle size and PDI as indicators; the morphology of prodrug nanoparticles was observed through electron microscopy and their particle size, potential, encapsulation efficiency, drug loading capacity, etc were investigated; the in vitro release characteristics of nanoparticles in reactive oxygen species and glutathione environments were investigated; the in vitro cytotoxicity and cellular uptake of prodrug nanoparticles were investigated through cell experiments. RESULTS The nano particle size prepared by the optimal process was (130.20±2.18)nm, with the PDI of 0.12±0.01, the Zeta potential of (-8.45±0.01)mV, the drug load of (10.27±1.36)%, and the encapsulation rate of (93.22±2.20)%. The prodrug nanoparticles showed reactive oxygen species and glutathione dual responsive release ability, and could significantly inhibit the proliferation of MCF-7, HepG2, and MDA-MB-231. Its inhibitory effect on MDA-MB-231 cells was the most significant. The IC50 of prodrug nanoparticles on MDA-MB-231 cells was (0.71±0.11)μmol·L, while the IC50of PTX was (22.38±3.27)μmol·L. CONCLUSION ProPTX-SS-NPs have excellent tumor microenvironment response performance and significant anti-tumor activity, which is a highly potential and promising anti-tumor nanosystem.

Tripterygium glycosides tablet(TGT),the classical commercial drug of Tripterygium wilfordii Hook.F.has been effectively used in the treatment of rheumatoid arthritis,nephrotic syndrome,leprosy,Behcet's syndrome,leprosy reaction and autoimmune hepatitis.However,due to its narrow and limited treatment window,TGT-induced organ toxicity(among which liver injury accounts for about 40％of clinical reports)has gained increasing attention.The present study aimed to clarify the cellular and molecular events underlying TGT-induced acute liver injury using single-cell RNA sequencing(scRNA-seq)technology.The TGT-induced acute liver injury mouse model was constructed through short-term TGT exposure and further verified by hematoxylin-eosin staining and liver function-related serum indicators,including alanine aminotransferase,aspartate aminotransferase,alkaline phosphatase and total bilirubin.Using the mouse model,we identified 15 specific subtypes of cells in the liver tissue,including endothelial cells,hepatocytes,cholangiocytes,and hepatic stellate cells.Further analysis indicated that TGT caused a significant inflammatory response in liver endothelial cells at different spatial locations;led to marked inflammatory response,apoptosis and fatty acid metabolism dysfunction in hepatocytes;activated he-patic stellate cells;brought about the activation,inflammation,and phagocytosis of liver capsular macrophages cells;resulted in immune dysfunction of liver lymphocytes;disturbed the intercellular crosstalk in liver microenvironment by regulating various signaling pathways.Thus,these findings elaborate the mechanism underlying TGT-induced acute liver injury,provide new insights into the safe and rational applications in the clinic,and complement the identification of new biomarkers and ther-apeutic targets for liver protection.