Objective:To understand the current research status, hot issues, and development trends of Taohong Siwu Decoction.Methods:Research literature about Taohong Siwu Decoction was retrieved from Wanfang Data, CBM, CNKI, and Chongqing VIP from January 1, 2014, to August 13, 2024. Excel 2024 software was used to analyze the annual number of publications, the source journals, literature types and the distribution of diseases and syndromes. CiteSpace 6.3.R3 software was used for visualization analysis on the authors, research institutions and key words.Results:A total of 2 519 articles were included, and the annual publication volume showed a fluctuating growth trend. There were 396 source journals, of which Medicine and Health published the most (80 articles); 208 authors were involved, and the core authors included Peng Daiyin of Anhui University of Chinese Medicine, Zhu Fuping of the First Affiliated Hospital of Hunan University of Chinese Medicine, Sun Shaoqiu of the Second Affiliated Hospital of Hunan University of Chinese Medicine and so on. The main research institutions in this field included Hunan University of Chinese Medicine and its affiliated hospitals. The high-frequency keywords included fracture, irregular menstruation, clinical efficacy, chloasma, Wuling Powder, experience of famous doctors, elderly, etc. Keywords could be clustered into 11 modules.Conclusions:The current research hotspots of Taohong Siwu Decoction mainly focus on the exploration of multi-system disease treatment, individualized syndrome differentiation and treatment, pharmacology and metabolic mechanism of Chinese materia medica, etc. Among them, the in-depth study of drug composition and metabolism, network pharmacology and mechanism is the research frontier in this field.

Objective To analyze the characteristics of acupoint selection in treatment for func-tional constipation.Methods Clinical literature on acupuncture and electroacupuncture therapy for functional constipation from January 1,2013,to December 31,2023,was retrieved from CNKI.The acupuncture prescriptions were collected and organized,and data mining techniques were employed to analyze the patterns of acupoint selection.Results A total of 182 articles were included,yielding 123 acupuncture prescriptions involving 92 acupoints with usage frequency of 967 times.The top 10 acu-points in frequency were Tianshu(158 times),Shangjuxu(138 times),Dachangshu(61 times),Zu-sanli(60 times),Zhigou(57 times),Fujie(57 times),Guanyuan(35 times),Zhongwan(34 times),Qihai(34 times),and Quchi(28 times).The meridians of the selected acupoints for acu-puncture treatment of functional constipation were mainly involved in stomach,bladder,Ren,and spleen meridians.Association rule analysis revealed that the combination of Tianshu-Shangjuxu had the highest occurrence probability(75.82％),followed by Tianshu-Dachangshu(33.52％)and Tianshu-Zusanli(32.97％).Cluster analysis of acupoints showed that the main acupoints selected for acu-puncture treatment of functional constipation could be divided into 10 clusters,including primary acu-points,acupoints for various syndrome types,acupoints for regulating spirit,and acupoints for regula-ting sympathetic nerves.Conclusion Acupuncture treatment for functional constipation should follow the principles of holistic treatment and syndrome differentiation,combined with the methods of selecting acupoints based on their upper-lower,proximal-distal,and anterior-posterior relationships.The acu-point selection patterns identified in this study can provide important references for clinical treatment of functional constipation,offer guidance for practitioners in acupoint selection,facilitate precise treatment,and promote early patient recovery.

Objective To explore the effects of behavior change intervention based on the multi-ple-theory model on patients with dyslipidemic ischemic stroke.Methods A total of 93 patients with dyslipidemic ischemic stroke who were hospitalized in the vascular neurology ward of Beijing Tiantan Hospital,Capital Medical University from January to August 2024 were selected as the study subjects using the convenience sampling method.They were randomly divided into control group(n=49)and intervention group(n=44)using the envelope-drawing method.Patients in the control group re-ceived routine stroke health education,while those in the intervention group underwent a 3-month be-havior change program guided by the multiple-theory model.The levels of healthy behaviors,body mass index(BMI),total cholesterol(TC),triglycerides(TG),high-density lipoprotein(HDL-C),and low-density lipoprotein(LDL-C)were compared between the two groups.Results There were no statistically significant differences in general information and disease-related data between the two groups(P＞0.05).At 1-,3-,and 6-month after the intervention,the level of healthy behaviors in the intervention group was higher than that in the control group,with statistically significant differ-ences(P＜0.05).There was a statistically significant difference in BMI between the two groups at 6 months after the intervention(P＜0.05).The TC levels in the intervention group at 3 and 6 months after the intervention were lower than those in the control group,with statistically significant differences(P＜0.05).The HDL-C level in the intervention group at 6 months after the intervention was high-er than that in the control group,with a statistically significant difference(P＜0.05).The LDL-C levels in the intervention group at 1-,3-,and 6-month after the intervention were lower than those in the control group,with statistically significant differences(P＜0.05).There were no statistically significant differences in TG levels between the intervention group and the control group at different time points after the intervention(P＞0.05).Conclusion The behavior change intervention pro-gram based on the multiple-theory model can effectively improve and maintain healthy behaviors and improve blood lipid levels in patients with dyslipidemic ischemic stroke.

Objective To explore the failure criterion that can accurately simulate the tensile and compressive fracture of hollow cortical bone structure.Methods Based on the previous compression and bending experimental data,the predicted results using different failure criteria were compared to determine the simulation accuracy.Results Under the compressive load,the differences in the fracture load between the simulations using the equivalent and invariant strain failure criteria and the experiment were less than 5％,indicating that these two failure criteria were suitable for predicting the cortical bone failure;under the bending load,the differences in the fracture load between the simulations using the equivalent and invariant strain failure criteria and the experiment were less than 5％,indicating that these two failure criteria could accurately predict the failure process.Conclusions The prediction accuracy using different failure criteria mainly depends on whether the strain growth rate conforms to the actual bone deformation.Too fast or too low strain growth rate will lead to premature or delayed structural fracture.The fracture simulation adopted in this study is suitable for most cortical bone structures,and can be used to determine the suitable failure criterion under different loads,so as to assist in obtaining the strength limit of cortical bone in various parts and provide data support for improving the simulation accuracy and grasping the condition of fracture occurrence in clinical practice.

Background and Aims:Biliary tract cancers(BTCs)are highly aggressive malignancies with dismal prognosis,for which radical resection remains the only potentially curative treatment.Laparoscopic surgery has demonstrated superiority over open surgery in perioperative safety and recovery,yet it is technically limited in complex operations.Robot-assisted laparoscopy,with its high-definition three-dimensional vision and enhanced instrument dexterity,may overcome these limitations.However,comparative evidence balancing baseline differences between laparoscopic and robot-assisted laparoscopic radical resections for BTCs is still lacking.This study aimed to evaluate and compare their short-term safety using propensity score matching(PSM).Methods:A total of 151 patients with biliary tract cancers who underwent radical resection were retrospectively enrolled from the Chinese Biliary Tract Tumor Collaborative Group database,including 128 in the laparoscopic group and 23 in the robotic-assisted laparoscopic group.To balance baseline differences,an initial 1∶1 PSM was performed,yielding 19 laparoscopic and 19 robotic cases.Subsequently,using the robotic group as the reference,a 1∶2 PSM was conducted,resulting in 36 laparoscopic and 18 robotic cases.Primary outcomes(conversion to open surgery,ICU admission,and postoperative complications)and secondary outcomes(operative time,intraoperative blood loss,transfusion,postoperative hospital stay,reoperation,readmission,and hospitalization costs)were compared between the two groups.Multivariate regression analyses were performed to explore factors associated with conversion to open surgery and postoperative hospital stay.Results:After matching,baseline characteristics were well balanced between groups.For primary outcomes,the conversion rate to open surgery was significantly higher in the laparoscopic group than in the robotic group(41.7％vs.0,P=0.001),while ICU admission,overall postoperative complications,and Clavien-Dindo graded complications showed no significant differences(all P＞0.05).For secondary outcomes,the postoperative hospital stay was significantly more extended in the laparoscopic group compared with the robotic group(18.5 d vs.8.0 d,P=0.005),whereas operative time,intraoperative blood loss,transfusion,reoperation,readmission,and hospitalization costs were comparable(all P＞0.05).Logistic regression for conversion did not identify statistically significant predictors,but moderately differentiated tumors,elevated preoperative CA19-9,and higher harvested lymph node counts showed trends toward increased risk.Multivariate linear regression revealed that robotic-assisted surgery was an independent factor for reduced postoperative hospital stay(P=0.024),while preoperative total bilirubin(P=0.020),longer operative time(P=0.000),postoperative complications(P=0.006),and reoperation(P=0.005)were found to be associated with a prolonged hospital stay.Conclusion:Robot-assisted laparoscopic radical resection for BTCs is not inferior to conventional laparoscopy in short-term safety and may further reduce conversion rates and hospital stay.Its technical advantages may be particularly valuable in anatomically complex or challenging cases.Nonetheless,cost-effectiveness and resource allocation should be considered for wider adoption.

Objective To investigate the weight loss efficacy and mechanisms of oligopeptide-herbal medicine composite,and to provide new approaches for obesity treatment.Methods Twenty-three SPF female SD rats were randomly divided into control group(n=3)and modeling group(n=20).The control group was fed an ordinary diet for 6 consecutive weeks,and the modeling group was fed a high-fat diet for 6 consecutive weeks to establish a simple obesity rat model.After successful modeling,the modeling group was randomly divided into model group(n=10)and treatment group(n=10).The treatment group started anoint-and-massage therapy with oligopeptide-herbal medicine composite(3 g per rat per time,once a day,20 min each time),which was recorded as day 1.The control group and model group were not treated with oligopeptide-herbal medicine composite but received the same massage,and continued to be fed ordinary feed and high-fat feed respectively.Ten rats in the model group and ten in the treatment group were each divided into 3 groups,with 3,3,and 4 rats in each group.On days 3,6,and 9 after treatment,the rats in the three groups were weighed and cardiac blood collection was performed after isoflurane respiratory anesthesia.After euthanasia by cardiac bloodletting,abdominal subcutaneous adipose tissue(aSAT)and perirenal white adipose tissue(pWAT)samples were collected and weighed.Serum triglycerides(TG)and high-density lipoprotein cholesterol(HDL-C)levels were measured.Image J software was used to measure aSAT thickness and the diameter and area of perirenal white adipocytes and abdominal subcutaneous adipocytes.Immunofluorescence technique was used to observe the number of telocytes(TCs),cell junctions and exosomes per unit area of aSAT.Transmission electron microscopy was used to measure the length of telopodes(Tps)of dermal and subcutaneous TCs in abdominal skin,and to observe the distribution of exosome vesicles,rough endoplasmic reticulum,mitochondria,and cell junctions.Results Compared with the control group,the body weight of rats in the modeling group increased significantly(P＜0.05).Compared with the control group,rats in the model group showed a significant increase in serum TG level,a significant decrease in HDL-C level,and a significant increase in pWAT mass(all P＜0.05).Compared with the model group,the treatment group showed a significantly increased rate of body weight reduction,significantly decreased pWAT mass,significantly decreased serum TG level,and significantly increased HDL-C level(all P＜0.05).Compared with the model group,the treatment group showed significant reductions in aSAT thickness,as well as cell diameter and area in both aSAT and pWAT(all P＜0.05).Compared with the model group,the treatment group showed significantly increased number of TCs per unit area of aSAT,number of exosomes from TCs in aSAT,and Tps length(all P＜0.05).The treatment group showed an increasing trend in the numbers of mitochondria,rough endoplasmic reticulum,and cell junctions in TCs.Conclusion Oligopeptide-herbal medicine composite applied via anoint-and-massage therapy effectively improves obesity-related symptoms such as dyslipidemia and fat accumulation in obese rats by regulating TCs and their intercellular communication.

Hypercholesterolemia is a significant risk factor for the development of atherosclerosis. 2',3',5'-Tri-O-acetyl-N ⁶-(3-hydroxyphenyl) adenosine (IMM-H007), a novel AMPK agonist, has shown protective effects in metabolic diseases. However, its impact on cholesterol and triglyceride metabolism in hypercholesterolemia remains unclear. In this study, we aimed to elucidate the effects and specific mechanisms by which IMM-H007 regulates cholesterol and triglyceride metabolism. To achieve this goal, we used Apoe ^-/- and Ldlr ^-/- mice to establish a hypercholesterolemia/atherosclerosis model. Additionally, hepatocyte-specific Ampka1/2 knockout mice were subjected to a 5-week high-cholesterol diet to establish hypercholesterolemia, while atherosclerosis was induced via AAV-PCSK9 injection combined with a 16-week high-cholesterol diet. Our results demonstrated that IMM-H007 improved cholesterol and triglyceride metabolism in mice with hypercholesterolemia. Mechanistically, IMM-H007 modulated the AMPKα1/2-LDLR signaling pathway, increasing cholesterol uptake in the liver. Furthermore, IMM-H007 activated the AMPKα1-FXR pathway, promoting the conversion of hepatic cholesterol to bile acids. Additionally, IMM-H007 prevented hepatic steatosis by activating the AMPKα1/2-ATGL pathway. In conclusion, our study suggests that IMM-H007 is a promising therapeutic agent for improving hypercholesterolemia and atherosclerosis through the activation of AMPKα.

Cancer is a serious global health problem and a major cause of human death. Conventional cancer treatments often run the risk of impairing vital organ functions. Anticancer peptides (ACPs) are considered to be one of the most promising therapeutic agents against common human cancers due to their small sizes, high specificity, and low toxicity. Since ACP recognition is highly limited to the laboratory, expensive, and time-consuming, we proposed pLM4ACP, a model for predicting ACPs based on machine learning and protein language models. In this model, the protein language model ProtT5 was used to extract the features of ACPs, and the extracted features were input into the support vector machine (SVM) classification algorithm for optimization and performance evaluation. The model showcased significantly higher accuracy than other methods, with the overall accuracy of 0.763, F1-score of 0.767, Matthews correlation coefficient of 0.527, and area under the curve of 0.827 on the independent test set. This study constructs an efficient anticancer peptide prediction model based on protein language models, further advancing the application of artificial intelligence in the biomedical field and promoting the development of precision medicine and computational biology.
Machine Learning ; Antineoplastic Agents/chemistry* ; Humans ; Peptides/chemistry* ; Support Vector Machine ; Algorithms ; Computational Biology/methods* ; Neoplasms/drug therapy*

Gastric cancer is a highly lethal malignant tumor, with early diagnosis being difficult and treatment outcomes influenced by multiple factors. In recent years, comprehensive treatment approach, incorporating surgery, chemotherapy, radiotherapy, targeted therapy, and immuno-therapy, has significantly improved efficacy. The advantages of comprehensive treatment are most important in patients with locally advanced and metastatic gastric cancer. For locally advanced cases, surgery serves as the core treatment, with various therapeutic modalities applied during the peri-operative period to enhance surgical outcomes. For metastatic patients, drug therapy is the primary method, supplemented by local treatments to achieve the best benefit. With the understanding of the molecular mechanisms underlying gastric cancer development, the use of molecular biomarkers for prognostic stratification and guidance for targeted therapy or immuno-therapy has become a crucial aspect of comprehensive treatment. Based on the latest research advancements, the authors discuss comprehensive treatment strategies for gastric cancer at different stages, offering insights into impro-ving efficacy and prognosis.

The profound integration of novel qualitative productive forces throughout the entire process of diagnosing and treating gastrointestinal cancer has catalyzed innovative advance-ments in surgical techniques and postoperative rehabilitation. In the field of minimally invasive resection, technological innovations, from laparoscopic surgery to robot-assisted surgical systems that transcend traditional visual and operational limitations, and further to the integration of artificial intelligence and 5G technologies that overcome spatiotemporal barriers for real-time decision-making and telemedicine, have significantly enhanced the precision and safety of gastrointestinal tumor surgery. Concurrently, the development of innovative medical devices plays a pivotal role in improving perioperative and postoperative rehabilitation efficiency. Functional device design focuses on addressing the holistic needs of patients throughout their clinical journey, systematically resolving efficiency and safety bottlenecks inherent in conventional diagnostic and therapeutic approaches. Technological progress has further enabled non-invasive, convenient remote health management for patients. Novel qualitative productive forces not only redefine surgical paradigms but also deliver efficient, safe, and patient-centered diagnostic and therapeutic experiences through comprehensive innovation across all treatment phases. This evolution marks a critical breakthrough in modern medicine's transition toward intelligence and systematization, heralding a new era of intelligent healthcare delivery.