Breast cancer (BC) is one of the most prevalent malignant tumors affecting women worldwide, with its incidence rate continuously increasing. As a result, treatment strategies for this disease have received considerable attention. Research has highlighted the crucial role of the Hedgehog (Hh) signaling pathway in the initiation and progression of BC, particularly in promoting tumor growth and metastasis. Therefore, molecular targets within this pathway represent promising opportunities for the development of novel BC therapies. This study aims to elucidate the therapeutic mechanisms by which natural compounds modulate the Hh signaling pathway in BC. By conducting a comprehensive review of various natural compounds, including polyphenols, terpenes, and alkaloids, we reveal both common and unique regulatory mechanisms that influence this pathway. This investigation represents the first comprehensive analysis of five distinct mechanisms through which natural compounds modulate key molecules within the Hh pathway and their impact on the aggressive behaviors of BC. Furthermore, by exploring the structure-activity relationships between these compounds and their molecular targets, we shed light on the specific structural features that enable natural compounds to interact with various components of the Hh pathway. These novel insights contribute to advancing the development and clinical application of natural compound-based therapeutics. Our thorough review not only lays the groundwork for exploring innovative BC treatments but also opens new avenues for leveraging natural compounds in cancer therapy.

Identifying drug-drug interactions (DDIs) is essential to prevent adverse effects from polypharmacy. Although deep learning has advanced DDI identification, the gap between powerful models and their lack of clinical application and evaluation has hindered clinical benefits. Here, we developed a Multi-Dimensional Feature Fusion model named MDFF, which integrates one-dimensional simplified molecular input line entry system sequence features, two-dimensional molecular graph features, and three-dimensional geometric features to enhance drug representations for predicting DDIs. MDFF was trained and validated on two DDI datasets, evaluated across three distinct scenarios, and compared with advanced DDI prediction models using accuracy, precision, recall, area under the curve, and F1 score metrics. MDFF achieved state-of-the-art performance across all metrics. Ablation experiments showed that integrating multi-dimensional drug features yielded the best results. More importantly, we obtained adverse drug reaction reports uploaded by Xiangya Hospital of Central South University from 2021 to 2023 and used MDFF to identify potential adverse DDIs. Among 12 real-world adverse drug reaction reports, the predictions of 9 reports were supported by relevant evidence. Additionally, MDFF demonstrated the ability to explain adverse DDI mechanisms, providing insights into the mechanisms behind one specific report and highlighting its potential to assist practitioners in improving medical practice.

Objective To explore the mechanism of Shengmai Decoction in improving heart failure by regulating mitochondrial apoptosis based on network pharmacology and experimental verification;To provide a basis for its clinical application.Methods The active components and targets of Shengmai Decoction were obtained through TCMSP and TCMID databases.Heart failure and mitochondrial apoptosis related targets were retrieved from GeneCards,OMIM,DrugBank,PharmGKB and TTD databases.A protein-protein interaction(PPI)network at the intersection of drugs and diseases was constructed using the STRING database,and a component-target network was constructed using Cytoscape 3.8.2 software.GO and KEGG pathway enrichment analysis was performed on intersecting targets using the DAVID database.Molecular docking was conducted to assess the binding affinity of key components to core target proteins.A rat model of heart failure was established,and the cardiac function of rats were detected by echocardiogram,ELISA was used to detect serum contents of BNP and NT-proBNP,mitochondrial ultrastructure was observed by transmission electron microscope,and Western blot was used to detect protein expressions of Bcl-2/Bax/Caspase-3 signaling pathway.Results A total of 66 active components and 146 targets of Shengmai Decoction were identified,and 22 intersecting targets with heart failure and mitochondrial apoptosis,including key proteins such as TNF,Bcl-2,Bax and Caspase-3.GO enrichment analysis revealed that the intersecting targets were closely associated with inflammation and cell signaling,while KEGG pathway analysis showed that the targets were primarily involved in the TNF signaling pathway,IL-17 signaling pathway,and mitochondrial function regulation.Molecular docking results indicated that Ginsenoside rh2,Beta-sitosterol and other components of Shengmai Decoction exhibited strong binding affinities with Bcl-2,Bax and Caspase-3.Animal experiments demonstrated that Shengmai Decoction significantly improved cardiac function(P<0.05,P<0.01),reduced serum BNP and NT-proBNP contents(P<0.01),alleviated mitochondrial damage,and inhibited mitochondrial apoptosis by upregulating Bcl-2 and downregulating Bax and Caspase-3 protein expression(P<0.01),thereby protecting cardiomyocytes.Conclusion Shengmai Decoction can target and regulate the Bcl-2/Bax/Caspase-3 signaling pathway,improving pathological processes associated with heart failure,which can provide a foundation for clinical optimization of Shengmai Decoction.

Breast cancer(BC)is one of the most prevalent malignant tumors affecting women worldwide,with its incidence rate continuously increasing.As a result,treatment strategies for this disease have received considerable attention.Research has highlighted the crucial role of the Hedgehog(Hh)signaling pathway in the initiation and progression of BC,particularly in promoting tumor growth and metastasis.There-fore,molecular targets within this pathway represent promising opportunities for the development of novel BC therapies.This study aims to elucidate the therapeutic mechanisms by which natural com-pounds modulate the Hh signaling pathway in BC.By conducting a comprehensive review of various natural compounds,including polyphenols,terpenes,and alkaloids,we reveal both common and unique regulatory mechanisms that influence this pathway.This investigation represents the first comprehen-sive analysis of five distinct mechanisms through which natural compounds modulate key molecules within the Hh pathway and their impact on the aggressive behaviors of BC.Furthermore,by exploring the structure-activity relationships between these compounds and their molecular targets,we shed light on the specific structural features that enable natural compounds to interact with various components of the Hh pathway.These novel insights contribute to advancing the development and clinical application of natural compound-based therapeutics.Our thorough review not only lays the groundwork for exploring innovative BC treatments but also opens new avenues for leveraging natural compounds in cancer therapy.

Identifying drug-drug interactions(DDIs)is essential to prevent adverse effects from polypharmacy.Although deep learning has advanced DDI identification,the gap between powerful models and their lack of clinical application and evaluation has hindered clinical benefits.Here,we developed a Multi-Dimensional Feature Fusion model named MDFF,which integrates one-dimensional simplified molec-ular input line entry system sequence features,two-dimensional molecular graph features,and three-dimensional geometric features to enhance drug representations for predicting DDIs.MDFF was trained and validated on two DDI datasets,evaluated across three distinct scenarios,and compared with advanced DDI prediction models using accuracy,precision,recall,area under the curve,and F1 score metrics.MDFF achieved state-of-the-art performance across all metrics.Ablation experiments showed that integrating multi-dimensional drug features yielded the best results.More importantly,we obtained adverse drug reaction reports uploaded by Xiangya Hospital of Central South University from 2021 to 2023 and used MDFF to identify potential adverse DDIs.Among 12 real-world adverse drug reaction reports,the predictions of 9 reports were supported by relevant evidence.Additionally,MDFF demon-strated the ability to explain adverse DDI mechanisms,providing insights into the mechanisms behind one specific report and highlighting its potential to assist practitioners in improving medical practice.

With the continuous development of China's aging society and the prevalence of unhealthy lifestyles, the incidence of cardiovascular disease in China has been increasing in recent years. Among them, atrial fibrillation (AF) is the most common arrhythmia disease. In recent years, pulsed field ablation (PFA) has been continuously applied to AF treatment as a novel treatment. This paper first introduces the principle of PFA applied to AF treatment, and introduces the research progress of PFA in different directions, such as the comparison of different ablation methods, the study of physical parameters, the study of ablation area, the study of tissue specificity and clinical research. Then, the clinical prior research of PFA is discussed, including the use of simulation software to obtain the simulation effect of different parameters, the evaluation of ablation effect during animal research, and finally the current AF treatment. Various prior studies and clinical studies are summarized, and suggestions are made for the shortcomings found in the study of AF treatment and the future research direction is prospected.

The development of classical anatomical liver resection has been a topic of considerable debate,particularly regarding its oncological efficacy in treating hepatocellular carcinoma.With continuous advancements in surgical techniques and iterative improvements in minimally invasive surgical equipment,laparoscopic portal territory anatomical resection(LPTAR)has gradually been adopted in clinical practice.Unlike classical anatomical liver resection,which approximates liver segmentectomy based on Couinaud's segmentation,LPTAR integrates technologies such as preoperative 3D visualization and intraoperative indocyanine green fluorescence navigation to target the true portal venous territory.Its core principle lies in achieving"precise liver segmentectomy"of the tumor-bearing portal venous territory.Currently,LPTAR is undergoing rapid development but faces several technical challenges,including the precise identification and control of hepatic pedicles,effective staining of difficult liver segments,and management of anatomical variations.Establishing standardized and streamlined technical protocols is crucial to addressing these issues,as it will improve surgical completeness and safety while enhancing oncological outcomes.Precision liver resection has long been a pursuit of surgeons,and laparoscopic liver resection,led by LPTAR,is poised to make a lasting impact in the field of precision hepatic surgery.

Objective::This study aimed to investigate the feasibility, efficacy, and safety of using a miniature mobile integrated cabin-theatre equipped with angiography and surgical operating room capabilities, and to explore its therapeutic scope, effectiveness, and operational mode.Methods::A miniature mobile integrated operating cabin-theatre was deployed across 15 hospitals in 15 cities or counties in China from April 2012 to November 2024. The interventions and outcomes of interventional and minimally invasive surgical procedures were prospectively observed and evaluated; perioperative complications were documented, and the stability, adaptability, and mobility of the integrated system were assessed.Results::A total of 133 procedures were successfully performed, 130 of which were interventional and 3 minimally invasive. The angiography machine showed good imaging performance without any equipment failures, loosening, or damage, with normal chamber unfolding. One patient experienced a fever the day after laparoscopy, while none of the other patients exhibited perioperative complications such as infection, surgical site bleeding/hematoma, or reperfusion arrhythmia. The instrument was easily manipulated, aligning with the needs of clinical intervention and surgery, and was perceived by patients as being a comfortable environment, with no psychological or other obvious discomfort.Conclusions::The miniature mobile integrated cabin-theatre, comprising an angiography machine and an operating room, allows interventional or minimally invasive surgical procedures to be performed smoothly and safely. It can also provide rapid and efficient on-site treatment of acute and critical illnesses across multiple body systems, including the cardiovascular, cerebrovascular, and gastrointestinal systems.

Pancreatic duct stents are essential devices for managing chronic pancreatitis,ductal strictures,and postoperative fistula.Conventional plastic and metal stents effectively facilitate pancreatic drainage but often cause infection,restenosis,or migration upon long-term implantation.An ideal stent should provide excellent biocompatibility,efficient drainage,and controllable biodegradation.With advances in material science and medical-engineering integration,stent technology has evolved from inert implantation to intelligent degradation.Biodegradable polymers and metals,particularly magnesium alloys(Mg-Zn-Mn),offer tunable mechanical strength,corrosion resistance,and in vivo degradability.Mg-2Zn-1.0Mn alloy achieves balanced strength and corrosion control through compositional optimization and surface modification.Polymeric stents such as polylactic acid and polydioxanone demonstrate favorable drainage and avoid secondary removal.Composite biodegradable stents,exemplified by the multi-rate ARCHIMEDES model,have received international approval.Supported by 3D printing and smart functionalization-such as drug-eluting or shape-memory designs-next-generation pancreatic stents may achieve integrated functions of support,repair,and tumor inhibition.Future research should emphasize interdisciplinary material design,degradation kinetics under physiological conditions,and long-term biocompatibility to accelerate clinical translation.

Objective:To explore the mediating effect of coping styles on the relationship between reinforce-ment sensitivity and non-suicidal self-injury(NSSI)behavior in adolescents.Methods:In total,4 462 middle school students were chosen by stratified cluster random sampling.All participants were asked with the question"In the past 1 year,have you intentionally harmed yourself(but not with the intention of ending your life)"to determine whether they had NSSI behavior in the past 12 months.All students were also assessed with the Trait Coping Style Questionnaire(TCSQ)and Reinforcement Sensitivity Scale(RSS).Results:The prevalence of NSSIbehavior in past year was 11.3％.Logistic regression analysis showed that the total scores of punishment sensitivity of RSS(OR=1.26,95％CI=1.10-1.46),negative coping style of TCSQ(OR=2.23,95％CI=1.92-2.60),and positive coping style of TCSQ(OR=0.70,95％CI=0.62-0.80)were associated with the screen-positive rate of NSSI behavior.Bootstrap test showed that the total scores of positive coping style of TCSQ(β=0.15,95％CI=0.10-0.20)and negative coping style of TCSQ(β=0.53,95％CI=0.43-0.64)partially mediated the relation-ship between the total scores of punishment sensitivity of RSS and the screen-positive rate of NSSI behavior in ado-lescents.Conclusion:The occurrence of NSSI behavior in adolescents is associated with the over-activation of pun-ishment sensitivity,partly through coping styles.