Breast cancer has become the malignant tumor with the highest incidence rate among women， seriously threatening the life and health of women all over the world. The pathogenic factors and development mechanisms of breast cancer are complex and diverse. The development of breast cells from ordinary hyperplasia to atypical hyperplasia， and from pre-cancerous lesions to cancerous lesions， is a long-term progressive process. Therefore， early screening and prevention of breast cancer is particularly important. Western medicine has a relatively mature treatment program for breast cancer， which is mainly based on surgery and systemic treatment， whereas the ensuing complications and adverse reactions often bring a heavy burden to patients. For the precancerous lesions of breast cancer， surgery is also the mainstay of treatment. In recent years， traditional Chinese medicine （TCM） has increasingly highlighted its advantages in the prevention and treatment of breast cancer. Increasing studies have shown that in the prevention and treatment of breast cancer and pre-cancerous lesions， TCM compound prescriptions， single herbs or herb pairs， and active components are able to regulate a variety of intracellular signaling pathways through multi-targets to inhibit the proliferation and invasion， promote the apoptosis and autophagy of tumor cells， and regulate the cell cycle and the immune microenvironment， thus exerting anti-tumor effects. At the same time， they can significantly attenuate the toxic side effects of radiotherapy and drug resistance of patients. However， the specific mechanisms of TCM in the prevention and treatment of breast cancer and precancerous lesions have not been fully clarified. The available studies are tanglesome regarding the TCM inhibition of tumor development through the regulation of classical signaling pathways such as phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR）， Wnt/β-catenin， and Notch， which still need to be verified by a large number of clinical and experimental studies. Therefore， this paper reviews the research progress in the prevention and treatment of breast cancer and precancerous lesions by TCM through interfering with the relevant signaling pathways in recent years， aiming to summarize the possible mechanisms of TCM in the prevention and treatment of breast cancer and provide references for subsequent studies.

ObjectiveThis paper aims to investigate the material basis of the anti-inflammatory efficacy and mechanism of action of Bushen Tongdu prescription （BSTDP）. MethodsThe chemical components of BSTDP and its blood-absorbed components in vivo were systematically identified by using ultra-performance liquid chromatography-linear ion trap-electrostatic field orbitrap high-resolution mass spectrometry （UPLC-LIT-Orbitrap-MS）. Network pharmacology was employed to screen blood-absorbed bioactive components and potential targets of this formula. A protein-protein interaction （PPI） network of core targets was constructed to conduct enrichment analysis. Molecular docking was further utilized to verify the binding affinity between key components and targets. The inflammatory model was established and verified in vivo by using a transgenic zebrafish Tg （mpx： GFP）. At three days post-fertilization （3 dpf）， larvae of zebrafish were randomly assigned to blank group， model group， positive drug dexamethasone acetate group （75 μmol·L^-1）， and BSTDP groups with low， medium， and high doses （500， 1 000， and 2 000 mg·L^-1）. The distribution and quantity of neutrophils in the yolk sac region were observed under a fluorescence microscope. The mRNA expression levels of key genes in the toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor kappa-B （NF-κB） signaling pathway and inflammatory factors including interleukin （IL）-1β， IL-6， and tumor necrosis factor-α （TNF-α） were detected by Real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsA total of 120 chemical components were identified in BSTDP， among which 26 original components were confirmed by using serum pharmacochemical methods. A total of 227 common targets linking rheumatoid arthritis （RA） and the blood-absorbed components were screened by network pharmacology. It is suggested that pseudobrucine， vomicine， sinapine， rehmannioside， cinnamyl alcohol glycoside， and methylephedrine exert anti-inflammatory effects by acting on core targets including protein kinase B1 （Akt1）， signal transducer and activator of transcription 3 （STAT3）， tumor necrosis factor （TNF）， TLR4， mitogen-activated protein kinase 14 （MAPK14）， and phosphatidylinositol-4，5-bisphosphate 3-kinase catalytic subunit α （PIK3CA）， thereby modulating multiple signaling pathways such as TLR4 and NF-κB. In vivo verification in zebrafish demonstrates that the maximum tolerable concentration of Bushen Tongdu Formula is 2 000 mg·L^-1. Compared to those in the blank group， zebrafish in the model group showed a significantly higher number of neutrophils in the yolk sac region （P<0.01） and rising mRNA levels of TLR4， MyD88， NF-κB， TNF-α， IL-6， and IL-1β （P<0.01）. Compared to that in the model group， the number of neutrophils was significantly reduced in BSTDP groups with medium and high doses， as well as the dexamethasone acetate group （P<0.05， P<0.01）. There was no statistically significant difference in the low dose group. The mRNA expression levels of TLR4， MyD88， NF-κB， TNF-α， IL-6， and IL-1β were significantly down-regulated （P<0.05， P<0.01）. ConclusionThis paper identifies the material basis of the efficacy of BSTDP， demonstrating that the formula can exert an anti-inflammatory effect through the TLR4/MyD88/NF-κB signaling pathway. The results provide scientific experimental evidence for its further clinical application.

ObjectiveThis paper aims to investigate the material basis of the anti-inflammatory efficacy and mechanism of action of Bushen Tongdu prescription （BSTDP）. MethodsThe chemical components of BSTDP and its blood-absorbed components in vivo were systematically identified by using ultra-performance liquid chromatography-linear ion trap-electrostatic field orbitrap high-resolution mass spectrometry （UPLC-LIT-Orbitrap-MS）. Network pharmacology was employed to screen blood-absorbed bioactive components and potential targets of this formula. A protein-protein interaction （PPI） network of core targets was constructed to conduct enrichment analysis. Molecular docking was further utilized to verify the binding affinity between key components and targets. The inflammatory model was established and verified in vivo by using a transgenic zebrafish Tg （mpx： GFP）. At three days post-fertilization （3 dpf）， larvae of zebrafish were randomly assigned to blank group， model group， positive drug dexamethasone acetate group （75 μmol·L^-1）， and BSTDP groups with low， medium， and high doses （500， 1 000， and 2 000 mg·L^-1）. The distribution and quantity of neutrophils in the yolk sac region were observed under a fluorescence microscope. The mRNA expression levels of key genes in the toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor kappa-B （NF-κB） signaling pathway and inflammatory factors including interleukin （IL）-1β， IL-6， and tumor necrosis factor-α （TNF-α） were detected by Real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsA total of 120 chemical components were identified in BSTDP， among which 26 original components were confirmed by using serum pharmacochemical methods. A total of 227 common targets linking rheumatoid arthritis （RA） and the blood-absorbed components were screened by network pharmacology. It is suggested that pseudobrucine， vomicine， sinapine， rehmannioside， cinnamyl alcohol glycoside， and methylephedrine exert anti-inflammatory effects by acting on core targets including protein kinase B1 （Akt1）， signal transducer and activator of transcription 3 （STAT3）， tumor necrosis factor （TNF）， TLR4， mitogen-activated protein kinase 14 （MAPK14）， and phosphatidylinositol-4，5-bisphosphate 3-kinase catalytic subunit α （PIK3CA）， thereby modulating multiple signaling pathways such as TLR4 and NF-κB. In vivo verification in zebrafish demonstrates that the maximum tolerable concentration of Bushen Tongdu Formula is 2 000 mg·L^-1. Compared to those in the blank group， zebrafish in the model group showed a significantly higher number of neutrophils in the yolk sac region （P<0.01） and rising mRNA levels of TLR4， MyD88， NF-κB， TNF-α， IL-6， and IL-1β （P<0.01）. Compared to that in the model group， the number of neutrophils was significantly reduced in BSTDP groups with medium and high doses， as well as the dexamethasone acetate group （P<0.05， P<0.01）. There was no statistically significant difference in the low dose group. The mRNA expression levels of TLR4， MyD88， NF-κB， TNF-α， IL-6， and IL-1β were significantly down-regulated （P<0.05， P<0.01）. ConclusionThis paper identifies the material basis of the efficacy of BSTDP， demonstrating that the formula can exert an anti-inflammatory effect through the TLR4/MyD88/NF-κB signaling pathway. The results provide scientific experimental evidence for its further clinical application.

ObjectiveBased on ultra-high performance liquid chromatography-quadrupole-electrostatic field orbital trap-linear ion-trap mass spectrometry（UPLC-Orbitrap Fusion Lumos Tribrid-MS）， the plasma concentration of ziyuglycoside Ⅰ was determined at different time points after oral administration， and its pharmacokinetic characteristics in normal rats and rats with acute kidney injury were compared. MethodsRats were randomly divided into normal group and model group， the model group received intraperitoneal cisplatin（10 mg·kg^-1） to establish the acute kidney injury model， the normal group was given the same volume of saline. After successful modeling， rats in the normal and model groups were randomly divided into the normal low， medium and high dose groups（2.5， 5， 7.5 mg·kg^-1） and the model low， medium and high dose groups（2.5， 5， 7.5 mg·kg^-1）， 6 rats in each group， and the plasma was collected at different time points after receiving the corresponding dose of ziyuglycoside Ⅰ. Then， the concentration of ziyuglycoside Ⅰ in rat plasma was determined by UPLC-Orbitrap Fusion Lumos Tribrid-MS， and the drug-time curve was poltted. The pharmacokinetic parameters were calculated by Kinetica 5.1 software， and the differences in pharmacokinetic parameters between different administration groups were compared by independent sample t-test with SPSS 22.0. ResultsThe pharmacokinetic results showed that after receiving the different doses of ziyuglycoside Ⅰ， its concentration increased first and then decreased， and all of them reached the maximum plasma concentration at about 0.5 h. The area under the curve（AUC_0-t） and mean retention time（MRT_0-t） of normal and model rats increased with the increased dose， and the clearance（CL） decreased with the increasing dose. Compared with the normal group， the AUC_0-t was significantly increased（P<0.01）， peak concentration（C_max） and CL decreased in model rats at different doses， indicating that the physiological state of the rats could affect the absorption and elimination of ziyuglycoside Ⅰ in vivo. ConclusionThe pharmacokinetic characteristics of ziyuglycoside Ⅰ are quite different in normal rats and acute kidney injury model rats， which may be due to the change of the body environment in the pathological state， then lead to changes in absorption and metabolic processes.

OBJECTIVE To evaluate the cost-effectiveness of finerenone combined with standard treatment regimen in the treatment of diabetic nephropathy （DN）. METHODS From the perspective of healthcare service providers， a Markov model was established to simulate the dynamic changes of each stage in DN patients who received finerenone combined with the standard treatment regimen or the standard treatment regimen alone based on the phase Ⅲ clinical trial study of finerenone for DN. Markov model was used to perform the cost-effectiveness of long-term effects and the costs of the two therapies with a simulation cycle of 4 months， a simulation period of 15 years and an annual discount rate of 5%. At the same time， one-way sensitivity analysis and probability sensitivity analysis were performed， and the stability of the results was validated. RESULTS Accumulative cost of the standard treatment regimen was 579 329.54 yuan， and the accumulative utility was 8.052 4 quality-adjusted life year （QALYs）； the accumulative cost of finerenone combined with the standard treatment regimen was 332 520.61 yuan， and the accumulative utility was 8.187 4 QALYs. Finerenone combined with the standard treatment regimen was more cost-effective. The results of one-way sensitivity analysis showed that dialysis status utility value， DN stage 3 utility value and DN stage 4 utility value had a great influence on the incremental cost-effectiveness ratio， but did not affect the robustness of the model. The results of probability sensitivity analysis showed that finerenone combined with the standard treatment regimen was more cost-effective with 100% probability. CONCLUSIONS For DN patients， finerenone combined with the standard treatment regimen is more cost-effective as an absolute advantage option.

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.

This article systematically analyzes the historical evolution of the name， medicinal parts， origin， harvesting， processing and other aspects of Houttuyniae Herba（HH） by referring to the medical books， prescription books and other documents of the past dynasties， combined with the research materials related to modern and contemporary times， in order to provide a basis for the development of famous classical formulas containing this herb. In ancient literature， HH was often referred to as "Ji" and "Jicai"， the name of "Ji" was first recorded in Mingyi Bielu during the Han and Wei dynasties， and the name of Yuxingcao was first seen in Lyuchanyan Bencao during the southern Song dynasty and has continued to this day. The origin of HH used throughout history is consistent， all of which are the whole herb or aboveground parts of Houttuynia cordata in Saururaceae family. HH recorded throughout history has a wide range of production areas， mostly self-produced self-marketing. In ancient times， fresh HH was often used as medicine by pounding its juice without involving any processing steps. Both fresh and dried products can be used as medicine， the fresh products uses the whole plant， while the dried products uses the aboveground parts， which are cleaned， selected and processed before use. Fresh products are harvested regardless of season， while dried products are harvested in both summer and autumn， with summer as the best. In ancient times， there were no specific requirements for the quality of HH， while in modern times， "intact stems and leaves with a strong fishy smell" are preferred. In addition， the medicinal properties of HH have undergone significant changes from ancient to modern times. In the early period， it was believed that its medicinal property was slightly warm， until the 1977 edition of Chinese Pharmacopoeia officially changed it to slightly cold. Both ancient and modern literature states that HH can be used for the treatment of carbuncle and malignant sores， Lyuchanyan Bencao for the first time introduced HH fresh juice can relieve summer heat， since Diannan Bencao recorded that it can be used for lung carbuncle， and gradually developed into the first choice for the treatment of lung carbuncle. Based on the research results， it is suggested that fresh herb or dried aboveground parts of H. cordata are used as medicine when developing famous classical formulas.

AIM: To explore the factors influencing heart rate(HR)changes during small incision lenticule extraction(SMILE)surgery by monitoring HR trends at different time points of the procedure.METHODS: Prospective cohort study. A total of 69 patients who underwent SMILE surgery at the Laser Vision Correction Center of Xi'an No.1 Hospital from April to May 2024 were enrolled. Before the surgery, patients completed the State Anxiety Inventory(S-AI, questions 1-20)to assess their preoperative anxiety scores related to the next day's surgery. Baseline HR was recorded using medical pulse oximeter, and real-time HR was recorded during patient positioning, lenticule scanning, lenticule separation and extraction, and the application of postoperative eye drops.RESULTS: The HR during patient positioning was 83.61±13.87 bpm, which was significantly different from the baseline HR(77.52±10.88 bpm), HR during lenticule separation and extraction(75.54±12.52 bpm), and HR during postoperative eye drop application(76.65±10.54 bpm; all P<0.001). When stratified by median age, older patients(>26 years)had the HR during lenticule separation and extraction 76.27±9.93 bpm, which differed from the HR at positioning(84.82±14.10 bpm)and at lens scanning(82.76±13.72 bpm; all P<0.005). Stratified by gender, the HR of male patients at positioning was the highest(85.31±16.61 bpm), which differed significantly from the baseline HR(78.26±12.63 bpm), HR during lenticule separation and extraction(77.14±14.59 bpm), and HR during postoperative eye drop application(77.11±12.49 bpm; all P<0.005). There was no correlation between HR during positioning and preoperative anxiety scores(r=0.124, P=0.418).CONCLUSION: HR changes during SMILE surgery vary with different procedural stages, peaking during patient positioning and reaching the lowest point during lenticule separation and extraction. Older patients showed higher HR during positioning, and male patients exhibited higher HR during positioning.

This article systematically analyzes the historical evolution of the name， origin， quality evaluation， harvesting， processing and other aspects of Picrorhizae Rhizoma by referring to the medical books， prescription books， and other documents of the past dynasties， combined with relevant modern research materials， in order to provide a basis for the development and utilization of famous classical formulas containing this medicinal herb. The research results indicate that Picrorhizae Rhizoma was first recorded in New Revised Materia Medica from the Tang dynasty. Throughout history， Huhuanglian has been used as its official name， and there are also aliases such as Gehu Luze， Jiahuanglian and Hulian. The main source of past dynasties is the the rhizomes of Picrorhiza kurrooa and P. scrophulariiflora. In ancient times， Picrorhizae Rhizoma was mainly imported by foreign traders via Guangzhou and other regions， and also produced in China， mainly in Xizang. In ancient times， it was harvested and dried in early August of the lunar calendar， while in modern times， it is mostly harvested from July to September， with the best quality being those with thick and crispy rhizomes without impurities， and bitter taste. Throughout history， Picrorhizae Rhizoma was collected， washed， sliced， and dried before being used as a raw material for medicine， it has a bitter and cold taste， mainly used to treat bone steaming， hot flashes， infantile chancre fever， and dysentery. There is no significant difference in taste and efficacy between ancient and modern times. Based on the research results， it is recommended that the rhizomes of P. scrophulariiflora in the 2020 edition of Chinese Pharmacopoeia， or the rhizomes of P. kurrooa， can be used in famous classical formulas containing this medicinal herb， which can be processed according to the processing requirements marked by the original formula. For those without clear processing requirements， the dried raw products are used as medicine.

Stroke ranks as the third leading cause of death and the fourth leading cause of disability worldwide. Its high disability rate and prolonged recovery period not only severely impact patients' quality of life but also impose a significant burden on families and society. Primary prevention is the cornerstone of stroke control, as early intervention on risk factors can effectively reduce its incidence. Therefore, the development of predictive models for first-ever stroke risk holds substantial clinical value. In recent years, advancements in big data and artificial intelligence technologies have opened new avenues for stroke risk prediction. This article reviews the current research status of traditional methods and machine learning models in predicting first-ever stroke risk and outlines future development trends from three perspectives: First, emphasis should be placed on technological innovation by incorporating advanced algorithms such as deep learning and large models to further enhance the accuracy of predictive models. Second, there is a need to diversify data types and optimize model architectures to construct more comprehensive and precise predictive models. Lastly, particular attention should be given to the clinical validation of models in real-world settings. This not only enhances the robustness and generalizability of the models but also promotes physicians' understanding of predictive models, which is crucial for their application and dissemination.