Vascular endothelial growth factor (VEGF) inhibitors are drugs that target and inhibit tumor angiogenesis. By blocking the signaling pathway of VEGF and its receptor, they suppress tumor proliferation and play a crucial role in tumor treatment. However, their side effects, such as hypertension, proteinuria, hand-foot skin reactions, and myelosuppression, during treatment seriously affect patients' treatment compliance and quality of life. The development of intervention strategies for the side effects of VEGF inhibitors is of great importance for tumor treatment. This article reviews the clinical characteristics and toxic mechanisms of common side effects caused by VEGF inhibitors during tumor treatment and summarizes intervention strategies that combine traditional Chinese and Western medicines. Drug dosages were precisely monitored and adjusted to achieve antitumor treatment. Patients' discomfort symptoms are improved through prescriptions that act by tonifying qi and promoting blood circulation, strengthening the spleen, and tonifying the kidney. The combination of traditional Chinese and Western medicines is used to treat patients, thus providing a safe and effective treatment plan for patients with cancer.

This paper systematically reviews the current status of integrated traditional Chinese and western medicine in the treatment of Helicobacter pylori （Hp） infection， as well as recent progress in clinical and basic research both in China and internationally. It summarizes the advantages of traditional Chinese medicine （TCM） in Hp infection management， including improving Hp eradication rates， enhancing antibiotic sensitivity， reducing antimicrobial resistance， decreasing drug-related adverse effects， and ameliorating gastric mucosal lesions. These advantages are particularly evident in patients who are intolerant to bismuth-containing regimens， those with refractory Hp infection， and individuals with precancerous gastric lesions. An integrated， whole-process management approach and individualized， staged comprehensive treatment strategies combining TCM and western medicine are proposed for Hp infection. Future prevention and control of Hp infection should adopt an integrative Chinese-western medical strategy， emphasizing prevention， strengthening primary care， implementing proactive long-term monitoring， optimizing screening strategies， and advancing the development of novel technologies and mechanistic studies of Chinese herbal interventions. These efforts aim to provide a theoretical basis and practical pathways for the establishment and improvement of Hp infection prevention and control systems.

Objective To develop and validate a machine learning model based on preoperative clinical characteristics, laboratory indices, and radiological features for the non-invasive prediction of spread through air spaces (STAS) in patients with early-stage lung adenocarcinoma. Methods Preoperative data from patients with early-stage lung adenocarcinoma who underwent surgical resection at Northern Jiangsu People's Hospital between January 2020 and August 2025 were retrospectively collected. The data included clinical characteristics, laboratory indices, and radiological features. Patients were divided into a STAS-positive and a STAS-negative group based on postoperative pathological findings. The dataset was randomly split into a training set and a testing set at a 7 : 3 ratio. Feature variables were selected using the maximum relevance and minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression. Five machine learning models were constructed: logistic regression (LR), random forest (RF), support vector machine (SVM), light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). The shapley additive explanations (SHAP) method was employed to interpret the optimal prediction model. Results A total of 377 patients were included, comprising 177 (46.9%) males and 200 (53.1%) females, with a mean age of (63.31±9.73) years. There were 261 patients in the training set and 116 patients in the testing set. In the training set, statistically significant differences were observed between the STAS-positive group (n=130) and STAS-negative group (n=131) across multiple features, including age, sex, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), clinical T stage, and maximum solid component diameter (P<0.05). A final set of 10 feature variables was selected by combining mRMR and LASSO regression, and five machine learning models (LR, RF, SVM, LightGBM, XGBoost) were developed. The XGBoost model demonstrated optimal performance in both the training and testing sets, achieving AUCs of 0.947 [95%CI (0.920, 0.975)] and 0.943 [95%CI (0.894, 0.993)], respectively. DCA indicated that the XGBoost model provided a high net clinical benefit across a wide range of threshold probabilities. SHAP analysis revealed that the vessel convergence sign, clinical T stage, age, consolidation-to-tumor ratio (CTR), and MLR were the features with the highest contributions to STAS prediction. Conclusion The XGBoost model effectively predicts preoperative STAS status in early-stage lung adenocarcinoma, exhibiting excellent discriminative performance and good clinical interpretability. Key predictors such as the vessel convergence sign, clinical T stage, age and CTR provide a crucial reference for preoperative risk assessment and the individualized selection of surgical strategies, ultimately benefiting patients.

ObjectiveTo improve the quality of artificial cultivation of the source plant of Fritillariae Cirrhosae Bulbus （FCB）， an XGBoost regression model was constructed based on the Group-Lasso method to screen the characteristic variables. The key factors affecting the quality formation of the source plant were then analyzed. MethodsFirstly， with the total alkaloid content （TAC） of FCB as the dependent variable， explanatory characteristic variables were screened from the influencing factors of TAC in the literature studying FCB quality from 2010 to 2024 based on the Group-Lasso regression algorithm. The screening results were verified by ten-fold cross-validation. Secondly， the present study established an XGBoost regression model to analyze the influencing factors of the quality formation of the source plant， and calculated the importance score of the explanatory characteristic variables. ResultsGroup-Lasso regression removed 2 numerical independent variables and retained the remaining 5 categorical variables and 6 numerical variables； cross-validation also showed that the number of screening variables is 11， with the corresponding optimal λ parameter value of 0.000 515 225 1. The results of XGBoost regression model confirmed the geographical origin as the most critical factor affecting the quality formation of source plants， followed by growth status and soil type， and then by mean temperature of the warmest month， original plant type， mean annual temperature， and altitude. Climate type， precipitation， frost-free period and relative humidity of the geographical origin exerted little effect. ConclusionThe prediction tools of Group-Lasso and XGBoost regression analysis models were preliminarily established for the quality formation of FCB. These models overcame the multicollinearity among numerical independent variables， and explored the geographical distribution of TAC and its key driving factors. The suitable cultivation areas can be selected or wild-tending bases established based on these key factors， thereby effectively avoiding blind introduction and cultivation. Finally， the present study provided a reference for the development and utilization of FCB， a theoretical basis for the market expansion and quality regulation， and a direction for the sustainable development and protection of new and efficient FCB resources.

Objective:To establish fingerprints of Faeces Bombycis and simultaneously determine the content of four amino acids; To evaluate the quality of Faeces Bombycis from different regions. The fingerprint of Faeces Bombycis was established and the contents of 4 amino acids were determined.Methods:Kromasil 100-5 C18 (4.6 mm×250 mm, 5 μm) column was used for phenyl isothiocyanate (PITC) pre-column derivation-high performance liquid chromatography with acetonitrile-0.1 mol/L sodium acetate solution (pH adjusted to 6.5 with acetic acid) (7:93) mixed solution, and acetonitrile-water (4:1) mixed solution were mobile phase for gradient elution. The flow rate was 1.0 ml/min; the column temperature was 35 ℃; the detection wavelength was 254 nm; the injection amount was 5 μl. The fingerprints of 17 batches of Faeces Bombycis were established, the common peaks were identified by comparison of reference materials, and the similarity evaluation and principal component analysis (PCA) were carried out. The contents of glycine, alanine, proline and phenylalanine were determined simultaneously.Results:A total of 12 common peaks were identified from the fingerprints of Faeces Bombycis, and 12 amino acids were identified. The similarity of 17 batches of samples was greater than 0.95. PCA analysis showed that the regional difference of the quality of Faeces Bombycis was not significant. Faeces Bombycis produced in Qujing city in Yunnan Province had the highest total contents of 4 amino acids.Conclusion:The method has good repeatability and can provide reference for the quality evaluation and standard improvement of Faeces Bombycis.

Objective:To establish a quality control method for Aiye standard decoction.Methods:The ultra performance liquid chromatogrphy (UPLC) column Waters ACQUITY HSS T3 C18 (2.1 mm×150 mm,1.8 μm) was used to gradient elution by acetonitrile and 0.1% formic acid in water. 16 batches of Aiye standard decoction fingerprints were established by UPLC and the common peaks were determined in the fingerprints. The contents of 12 components were determined. The 16 batches of Aiye standard decoction were analyzed by similarity calculation, hierarchical cluster analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) for analysis of differential components of Artemisiae Argyi Folium from different origins.Results:A total of 13 common peaks were marked in the fingerprints of 16 batches of Aiye standard decoction, 12 of which were identified by comparison with reference substance, including chlorogenic acid, sochlorogenic acid A, neochlorogenic acid, cryptochlorogenic acid, caffeic acid,1,3-O-Dicaffeoylquinic acid, schaftoside, isochlorogenic acid B,1,5-O-Dicaffeoylquinic acid, isochlorogenic acid C, jaceosidin and eupatilin. Similarity evaluation, PCA and HCA all classified the 16 batches of Aiye standard decoction into 2 categories. Orthogonal partial least squares discriminant analysis screened 5 differential biomarkers from 13 common peaks. The content determination results showed that the phenolic compounds and flavonoids in samples from Hubei were significantly higher than that in samples from other areas.Conclusion:This method can effectively analyze the differences in the quality of Aiye standard decoction from different origins, and provide reference for the formulation of quality standards for Aiye standard decoction and related preparations.

Objective:To establish a method for the determination of triterpenes and nucleosides in Poria based on HPLC; To accurately determine the various bioactive components in Poria.Methods:Similarity evaluation, clustering analysis and principal component analysis were used to analyze the similarities and differences of different medicinal parts of Poria, and the key chromatographic peaks that could reflect the characteristics were found.Results:The Poricoic acid A and dehydroeburiconic acid could be used as the identification basis for Poriae Cutis and White Poria; at the same time, Polyporenic acid C, dehydropachymic acid and dehydrotrametenolic acid could be used to evaluate Rubra Poria and Poriae Cutis; uridine, guanosine and adenosine may be essential ingredients for evaluating the quality of White Poria, Poriae Cutis and Rubra Poria. In different medicinal parts of Poria, the triterpenes were showed significant differences; by contrary, there were little differences among the same medicinal parts.Conclusion:This study reveals the quality differences between different medicinal parts of Poria, which can provide a scientific basis for the rational application and pharmacodynamic standardization of Poria.

Objective Based on the clinical data and imaging manifestations of patients with ischemic stroke to establish a simple clinical prediction model that is used for identifying intracranial atherosclerotic stenosis-acute large vessel occlusion(ICAS-LVO in posterior circulation before surgery.Methods The clinical data of patients with acute large vessel occlusion(LVO in the posterior circulation,who received endovascular intervention at the First Affiliated Hospital of Nanjing Medical University of China from January 2019 to September 2022,were retrospectively analyzed.According to the intraoperative angiographic findings,the patients were divided into ICAS-LVO group and non-ICAS-LVO group.Univariate analysis and multivariate logistic regression analysis were used to analyze the patient's demographic characteristics,clinical history,imaging findings,and laboratory results,based on which a clinical prediction model for ICAS-LVO was established,and according to the relevant parameters a nomogram prediction model was plotted.Results A total of 110 patients with LVO in the posterior circulation who received endovascular treatment were included in the final analysis.In 51 patients(49.6％)the cause of vascular occlusion was the atherosclerotic stenosis of the intracranial arteries.Compared with non-ICAS-LVO group,in ICAS-LVO group the patients were younger,the incidence of atrial fibrillation was lower,and the level of plasma D-dimer was lower.Three factors,including atrial fibrillation,occlusion site and collateral circulation status,were finally screened out to establish the prediction model for ICAS-LVO.This model demonstrated acceptable calibration(Hosmer-Lemeshow test,P=0.562)and good discrimination ability(AUC=0.956;95％CI:0.906-0.986).Conclusion The clinical prediction model for ICAS-LVO,which is established on the three predictive factors(absence of atrial fibrillation,occlusion located at the V4 segment of the vertebral artery or at the proximal to mid segment of the basilar artery,and a favorable collateral circulation),carries high sensitivity and accuracy.This model can help neurointervention physicians to make early identification of ICAS-LVO and to promptly formulate vascular recanalization treatment strategies.

Objective To systematically evaluate the safety and efficacy of Kangfuxin liquid combined with adenosine monophosphate in the treatment of paediatric herpetic stomatitis.Methods Randomised controlled trials(RCTs)of Kangfuxin liquid combined with adenosine monophosphate for the treatment of paediatric herpetic stomatitis were searched in various databases,and Meta-analysis was performed using RevMan 5.4 software.Results A total of 12 RCTs with a sample size of 1,094 cases were included.Meta-analysis showed that the combination of Kangfuxin liquid with adenosine monophosphate significantly increased[RR=1.21,95%CI(1.16,1.28),P<0.000 01]the overall clinical efficacy rate of paediatric herpetic stomatitis.Compared with the conventional antiviral treatment group with adenosine monophosphate,the incidence of adverse events was lower in the Kangfuxin liquid group[RR=0.26,95%CI(0.14,0.51),P<0.000 01].In addition,the Kangfuxin liquid group could effectively shorten the time for herpes disappearance(skin lesion healing),pain disappearance,fever reduction,salivation disappearance and recovery of diet(P<0.05),and had advantages in promoting the recovery of lymphocytes(CD3+,CD4+,CD8+,and CD4+/CD8+),serological levels(CRP,TNF-α,WBC,IL-10,VEGF,EGF,and IL-6)(P<0.05).Conclusion Kangfuxin liquid combined with adenosine monophosphate has the better efficacy and safety in the treatment of paediatric herpetic stomatitis,and has advantages in shortening the symptomatic recovery time and improving the indicators of lymphocyte and serological levels in paediatric herpetic stomatitis.

ObjectiveTo evaluate the quality of Lygodium japonicum (Thunb.) Sw. (L. japonicum, Hai Jin Sha) by comparing its components without stewed (W) and stewed (S) using ultra-high-performance liquid chromatography (UHPLC) and chemometric analysis. Additionally, network pharmacology was employed to investigate the possible mechanisms of action of L. japonicum in the urinary calculi (UC) treatment.MethodsA fingerprinting method was established to identify components through UHPLC-tandem mass spectrometry. Chemometric techniques were used to compare the L. japonicum extraction methods. Furthermore, various network pharmacological approaches were used to identify and analyze the potential targets of the identified components in relation to UC.ResultsThe W and S extracts were distributed into two distinct clusters. Significant differences in the levels of protocatechuic aldehyde, caffeic acid, and p-coumaric acid were observed between S and W. Network pharmacology analysis revealed that the primary targets of L. japonicum in the UC treatment were serum albumin and epidermal growth factor receptors, with potential active components including protocatechuic acid and caffeic acid.ConclusionThis study comprehensively examined the therapeutic components of L. japonicum before and after boiling, shedding light on its potential mechanisms of action in UC treatment. These findings offer valuable insights into the development and utilization of L. japonicum resources.