ObjectiveBy exploring the influencing factors of readmission in patients with stable angina of coronary heart disease （CHD） based on real-world clinical data， to establish a risk prediction model of integrated traditional Chinese and western medicine， in order to provide a basis for early identification of high-risk populations and reducing readmission rates. MethodsA prospective clinical study was conducted involving patients with stable angina pectoris of CHD， who were divided into a training set and a validation set at a 7∶3 ratio. General information， traditional Chinese medicine （TCM）-related data， and laboratory test results were uniformly collected. After a one-year follow-up， patients were classified into a readmission group and a non-readmission group based on whether they were readmitted. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for readmission. A risk prediction model of integrated traditional Chinese and western medicine was constructed and visualized using a nomogram. The model was validated and evaluated in terms of discrimination， calibration， and clinical decision curve analysis. ResultsA total of 682 patients were included， with 477 in the training set and 205 in the validation set， among whom 89 patients were readmitted. Multivariate logistic regression analysis identified heart failure history ［OR = 6.93， 95% CI （1.58， 30.45）］， wiry pulse ［OR = 2.58， 95% CI （1.42， 4.72）］， weak pulse ［OR = 3.97， 95% CI （2.06， 7.67）］， teeth-marked tongue ［OR = 4.38， 95% CI （2.32， 8.27）］， blood stasis constitution ［OR = 2.17， 95% CI （1.06， 4.44）］， phlegm-stasis mutual syndrome ［OR = 3.64， 95% CI （1.87， 7.09）］， and elevated non-high-density lipoprotein cholesterol ［OR = 1.30， 95% CI （1.01， 1.69）］ as influencing factors of readmission. These factors were used as predictors to construct a nomogram-based risk prediction model for readmission in patients with stable angina. The model demonstrated moderate predictive capability， with an area under the receiver operating characteristic curve （AUC） of 0.818 ［95% CI （0.781， 0.852）］ in the training set and 0.816 ［95% CI （0.779， 0.850）］ in the validation set. The Hosmer-Lemeshow test showed good calibration （χ² = 4.55， P = 0.80）， and the model's predictive ability was stable. When the threshold probability exceeded 5%， the clinical net benefit of using the model to predict readmission risk was significantly higher than intervening in all patients. ConclusionHistory of heart failure， teeth-marked tongue， weak pulse， wiry pulse， phlegm-stasis mutual syndrome， blood stasis constitution， and non-high-density lipoprotein cholesterol are influencing factors for readmission in patients with stable angina of CHD. A clinical prediction model was developed based on these factors， which showed good discrimination， calibration， and clinical utility， providing a scientific basis for predicting readmission events in patients with stable angina.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

OBJECTIVE To construct three-class （insufficient， normal， excessive） and two-class （insufficient， normal） models for predicting plasma concentration of valproic acid （VPA）， and compare the performance of these two models， with the aim of providing a reference for formulating clinical medication strategies. METHODS The clinical data of 480 patients who received VPA treatment and underwent blood concentration test at the Xi’an International Medical Center Hospital were collected from November 2022 to September 2024 （a total of 695 sets of data）. In this study， predictive models were constructed for target variables of three-class and two-class models. Feature ranking and selection were carried out using XGBoost scores. Twelve different machine learning algorithms were used for training and validation， and the performance of the models was evaluated using three indexes: accuracy， F1 score， and the area under the working characteristic curve of the subject （AUC）. RESULTS XGBoost feature importance scores revealed that in the three-class model， the importance ranking of kidney disease and electrolyte disorders was higher. However， in the two-class model， the importance ranking of these features significantly decreased， suggesting a close association with the excessive blood concentration of VPA. In the three-class model， Random Forest method performed best， with F1 score of 0.704 0 and AUC of 0.519 3 on the test set； while in the two-class model， CatBoost method performed optimally， with F1 score of 0.785 7 and AUC of 0.819 5 on the test set. CONCLUSIONS The constructed three-class model has the ability to predict excessive VPA blood concentration， but its prediction and model generalization abilities are poor； the constructed two-class model can only perform classification prediction for insufficient and normal blood concentration cases， but its model performance is stronger.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.

BACKGROUND:Cadmium is a common environmental pollutant,which can damage multiple organs and tissues,such as the kidney and bone,but its effect on annulus fibrosus cells in the intervertebral disc has been less reported. OBJECTIVE:To investigate the effect of cadmium chloride on the senescence of annulus fibrosus cells and the role of PI3K/Akt signaling pathway. METHODS:Annulus fibrosus cells from Sprague-Dawley rat intervertebral discs were harvested and passage 3 cells were intervened with different concentrations of cadmium chloride(0,1,5,10,20 μmol/L).Cell viability and proliferation were detected by cell counting kit-8 assay.Transcriptome sequencing and Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis were performed on annulus fibrosus cells with or without cadmium chloride addition.Passage 3 annulus fibrosus cells were divided into control group,cadmium chloride group and LY294002 group.Cell proliferation rate was detected by EdU method,positive cell rate was detected by senescence-associated β-galactosidase staining,and expressions of senescence-associated proteins(p16,p21 and p53)and p-Akt at protein and mRNA levels were measured by western blot,RT-PCR and immunofluorescence. RESULTS AND CONCLUSION:5 μmol/L cadmium chloride could inhibit the proliferation of annulus fibrosus cells.Results from the Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis showed that the main signal transduction pathways included PI3K/Akt,cell cycle and p53 signaling pathways,which were related to cell senescence and proliferation.PI3K/Akt signaling pathways with significant differential expression were selected for validation.Compared with the control group,the EdU-positive rate was significantly decreased in the cadmium chloride group(P<0.05),while the β-galactosidase-positive rate,the expression of senescence-associated proteins(p16,p21 and p53)and p-Akt significantly increased(P<0.05).Compared with the cadmium chloride group,the EdU-positive rate and p-Akt expression were significantly decreased in the LY294002 group(P<0.05),while the β-galactosidase-positive rate and the expression of senescence-associated proteins(p16,p21 and p53)significantly increased(P<0.05).To conclude,cadmium chloride can regulate the senescence of annulus fibrosus cells by activating the PI3K/Akt signaling pathway,thereby inducing the occurrence and progression of intervertebral disc degeneration.

Objective: To investigate the clinical characteristics of induced labor in twin pregnancy and the related factors of induced labor failure. Methods: The clinical data of twin pregnant women who underwent induced labor in Peking University Third Hospital from January 2016 to December 2022 were retrospectively analyzed. According to whether they had labor or not after induction, pregnant women were divided into the success group (pregnant women who had labor after induction, 72 cases) and the failure group (pregnant women who did not have labor after induction, 30 cases). Logistic regression was used to analyze the related factors of induction failure in twin pregnant women. Results: The parity and cervical Bishop score in the failure group were significantly lower than those in the success group, while the proportion of dichorionic diamniotic twins, assisted reproductive technology pregnancy and cervical Bishop score <6, postpartum hospital stay and total hospital stay in the failure group were significantly higher than those in the success group (all P<0.05). The proportion of induced labor by artificial rupture of membranes ± oxytocin intravenous infusion in the success group was 72.2% (52/72), which was significantly higher than that in the failure group (46.7%, 14/30; P=0.030). There were no significant differences between the two groups in the gestational age at delivery, the incidence of severe postpartum hemorrhage and blood transfusion, the amount of postpartum hemorrhage, the neonatal weight of two fetuses, the incidence of neonatal asphyxia, and the proportion of neonates admitted to the neonatal intensive care unit (all P>0.05). There were no severe perineal laceration and hysterectomy in all pregnant women. Multivariate logistic regression analysis showed that primipara (OR=3.064, 95%CI: 1.112-8.443; P=0.030) and cervical Bishop score <6 (OR=5.208, 95%CI: 2.008-13.508; P=0.001) were the independent risk factors for induction failure in twin pregnancy. Conclusions: Elective induction of labor in twin pregnancy is safe and feasible. It is helpful to improve the success rate of induction of labor by strictly grasping the timing and indications of termination of pregnancy, choosing the appropriate method of induction according to the condition of the cervix, and actively promoting cervical ripening .
Infant, Newborn ; Pregnancy ; Female ; Humans ; Pregnancy Trimester, Third ; Pregnancy, Twin ; Postpartum Hemorrhage/etiology* ; Retrospective Studies ; Labor, Induced/methods* ; Cervical Ripening

A high-throughput three-dimensional (3D) hepatocyte culture model is constructed in this study. It is capable of replicating the 3D in vivo environment and offers the advantages of high throughput, enhanced reproducibility, low cost, and simplified operation, rendering a valuable tool for hepatotoxicity screening of traditional Chinese medicine (TCM). First, we constructed the 3D high throughput liver chip model using collagen hydrogel. The precision and its difference with traditional cell culture plates were assessed using acetaminophen, Tripterygium hypoglaucum, and Qili San as the references. The feasibility of this model was also investigated by comparing the hepatotoxicity among four batches of T. hypoglaucum and Qili San. The methodology verification shows that the 3D hepatocyte model is better than traditional two-dimensional (2D) cell culture model in precision and feasibility. Subsequently, we compared the hepatotoxicity of different samples over a period of three or seven days and found that the hepatotoxicity of TCM extracts increased over time. Finally, we compared the hepatotoxicity of T. hypoglaucum and its compound formula Kunxian capsule under equivalent concentration. The results showed that the compound Kunxian capsule could significantly reduce hepatotoxicity of T. hypoglaucum. Generally, we constructed a high-throughput, robust 3D liver-on-a-chip model with the potential of rapid assessing TCM-induced liver toxicity.

ObjectiveTo investigate the current status of secondary prevention of stable angina in patients with coronary heart disease in three regions of China， namely Henan Province， Xinjiang Uygur Autonomous Region， and Tianjin City， and analyze the the influencing factors. MethodsA cross-sectional study was conducted to include patients with stable angina with coronary heart disease in Henan， Tianjin and Xinjiang from August 10， 2020 to March 14， 2021. General information， traditional Chinese medicine （TCM） syndrome elements， prescriptions and other data of patients were collected， and clinical characteristics， blood pressure， blood lipid and blood glucose of patients were analyzed； the patients were divided into groups according to whether their blood pressure， blood lipid and blood glucose were up to standard. With the most common syndrome element as the main variable， region， age and gender as covariables， Logistic regression equation was incorporated to analyze the influencing factors for the patients' blood pressure， blood lipid and blood glucose being up to standard. ResultsA total of 1061 coronary heart disease patients with stable angina were included， including 658 in Henan， 210 in Xinjiang， and 193 in Tianjin. The clinical characteristics of patients in the three regions showed statistical different in age， sex， disease course， complication， blood pressure， blood lipid， blood glucose， smoking， drinking， living habits， and medication treatment （P＜0.05 or P＜0.01）. For the included patients， qi deficiency （79.55%， 844/1061） and blood stasis （39.96%， 424/1061） were the main syndrome elements. The overall compliance rate of blood pressure was 48.89% （506/1035）， blood lipids 12.68% （133/1049） and blood glucose 48.18% （504/1046）. Qi deficiency was the independent factor affecting the blood pressure of coronary heart disease patients with stable angina combined with hypertension （P = 0.029，95%CI ［1.048， 2.369］）， and the independent factors influencing the blood lipid standard of coronary heart disease patients with stable angina （P = 0.011， 95%CI ［1.133， 2.646］）， but not the independent factors affecting blood glucose standard in coronary heart disease patients with diabetes （P＞0.05）. ConclusionCoronary artery disease patients with stable angina have geographical variability in clinical characteristics and distribution of TCM syndrome elements， and the overall control of blood pressure， blood lipids， and blood glucose is poor， and qi deficiency syndrome is an independent risk factor affecting the control of blood pressure and blood lipids.

ObjectiveTo evaluate the efficacy of TCM health management based on tertiary management system for patients with myocardial infarction （MI）. MethodsA total of 277 patients with non-acute MI were enrolled and given comprehensive TCM health management strategies including health education， lifestyle adjustment， risk factors control， medication and TCM appropriate techniques management through a tertiary management system with "the patient as the core， village/community physicians as the main executive body， and tertiary TCM hospital specialists as the leading body"， for a period of 12 months by using a prospective single-arm cohort study. Through patient reporting and medical records surveys， various indicators before and after 12-month management were collected and compared. The primary efficacy indicators were readmission rate and recurrent exacerbation rate， and the secondary efficacy indicators included disease awareness-related indicators， lifestyle behavior-related indicators， cardiovascular risk factor-related indicators and Canadian cardiovascular society （CCS） cardiac function classification. ResultsA total of 255 patients completed the study and were included in the final analysis. The recurrent exacerbation and readmission rates of patients after management were 23.14% （59 cases） and 20.25% （49 cases）， respectively， significantly lower than 36.08% （92 cases） and 53.72% （130 cases） before management （P＜0.05）. Except for knowledge on diabetes diagnostic criteria with no significant difference before and after management （P＞0.05）， awareness of other knowledge with regard to the prevention and treatment of cardiovascular and cerebrovascular diseases were improved after management （P＜0.01）， as well as the total score （P＜0.01）. In terms of daily life behaviors， the rates of salty diet， sweet diet and greasy diet were significantly lower than baseline， while the rate of moderate exercise was significantly higher （P＜0.05 or P＜0.01）； the rates of ongoing smoking and vigorous exercise were not significantly changed （P＞0.05）. For cardiovascular risk factors， patients' total cholesterol， low-density lipoprotein （LDL） cholesterol， triglycerides， fasting glucose， total depression assessment scale score， and total anxiety assessment scale score were significantly reduced after management （P＜0.01）. Systolic blood pressure and body mass index （BMI） were both higher after management （P＜0.05 or P＜0.01）， and there was no statistically significant difference in diastolic blood pressure （P＞0.05）. In terms of the cardiovascular disease risk factors reaching the standard levels， the rate of LDL cholesterol ＜1.8 mmol/L significantly increased （P＜0.01）， while the rate of BMI ＜24 kg/m² and the rate of systolic blood pressure ＜140 mmHg both decreased significantly （P＜0.05 or P＜0.01） from baseline； the diastolic blood pressure and rate of fasting glucose ＜7.0 mmol/L were not significantly changed （P＞0.05）. The patients' CCS cardiac function classification was significantly reduced （P＜0.05）. ConclusionTCM health management based on the tertiary management system can enhance MI patients' awareness of the disease， change poor lifestyle habits， reduce risk factors such as blood lipids and blood glucose， improve anxiety and depression， increase activity tolerance， and reduce their recurrence exacerbation and readmission rates， which is worthy of clinical promotion.

Bacterial biofilms gave rise to persistent infections and multi-organ failure, thereby posing a serious threat to human health. Biofilms were formed by cross-linking of hydrophobic extracellular polymeric substances (EPS), such as proteins, polysaccharides, and eDNA, which were synthesized by bacteria themselves after adhesion and colonization on biological surfaces. They had the characteristics of dense structure, high adhesiveness and low drug permeability, and had been found in many human organs or tissues, such as the brain, heart, liver, spleen, lungs, kidneys, gastrointestinal tract, and skeleton. By releasing pro-inflammatory bacterial metabolites including endotoxins, exotoxins and interleukin, biofilms stimulated the body’s immune system to secrete inflammatory factors. These factors triggered local inflammation and chronic infections. Those were the key reason for the failure of traditional clinical drug therapy for infectious diseases.In order to cope with the increasingly severe drug-resistant infections, it was urgent to develop new therapeutic strategies for bacterial-biofilm eradication and anti-bacterial infections. Based on the nanoscale structure and biocompatible activity, nanobiomaterials had the advantages of specific targeting, intelligent delivery, high drug loading and low toxicity, which could realize efficient intervention and precise treatment of drug-resistant bacterial biofilms. This paper highlighted multiple strategies of biofilms eradication based on nanobiomaterials. For example, nanobiomaterials combined with EPS degrading enzymes could be used for targeted hydrolysis of bacterial biofilms, and effectively increased the drug enrichment within biofilms. By loading quorum sensing inhibitors, nanotechnology was also an effective strategy for eradicating bacterial biofilms and recovering the infectious symptoms. Nanobiomaterials could intervene the bacterial metabolism and break the bacterial survival homeostasis by blocking the uptake of nutrients. Moreover, energy-driven micro-nano robotics had shown excellent performance in active delivery and biofilm eradication. Micro-nano robots could penetrate physiological barriers by exogenous or endogenous driving modes such as by biological or chemical methods, ultrasound, and magnetic field, and deliver drugs to the infection sites accurately. Achieving this using conventional drugs was difficult. Overall, the paper described the biological properties and drug-resistant molecular mechanisms of bacterial biofilms, and highlighted therapeutic strategies from different perspectives by nanobiomaterials, such as dispersing bacterial mature biofilms, blocking quorum sensing, inhibiting bacterial metabolism, and energy driving penetration. In addition, we presented the key challenges still faced by nanobiomaterials in combating bacterial biofilm infections. Firstly, the dense structure of EPS caused biofilms spatial heterogeneity and metabolic heterogeneity, which created exacting requirements for the design, construction and preparation process of nanobiomaterials. Secondly, biofilm disruption carried the risk of spread and infection the pathogenic bacteria, which might lead to other infections. Finally, we emphasized the role of nanobiomaterials in the development trends and translational prospects in biofilm treatment.