ObjectiveTo investigate the potential mechanism of Huatan Sanjie Formula （化痰散结方， HSF） in the treatment of triple negative breast cancer （TNBC） based on the integrinβ1/focal adhesion kinase/yes-associated protein （integrinβ1/FAK/YAP） mechanotransduction signaling pathway. MethodsFifty BALB/c mice were randomly assigned to a model group， doxorubicin group， low-， medium-， and high-dose HSF groups， with 10 mice per group. An orthotopic TNBC transplantation model was established in all mice using syngeneic implantation of 4T1 cells. After successful modeling， mice in the model group received intragastric administration of normal saline 0.2 ml each day. Mice in the low-， medium-， and high-dose HSF groups received HSF by gavage at doses of 5.99， 11.97， and 23.94 g/（kg·d）， respectively. The doxorubicin group received intraperitoneal injections of doxorubicin （1.5 mg/kg） once every two days. All treatments lasted for 30 days. After the final administration， mice were sacrificed， and tumor weight and volume were measured. Hematoxylin-eosin （HE）， Masson's trichrome， and Sirius Red staining were performed to evaluate histopathological changes and collagen fiber deposition in tumor tissues. TUNEL staining was used to assess apoptosis. The Young's modulus of tumor tissues was measured using atomic force microscopy （AFM）. The nuclear-cytoplasmic localization of YAP was determined by immunofluorescence staining. Protein expression levels of integrinβ1， focal adhesion kinase （FAK）， YAP， and phosphorylated focal adhesion kinase （p-FAK） were detected by Western Blotting. The mRNA expression levels of integrinβ1， FAK， and YAP were assessed by quantitative real-time polymerase chain reaction （qRT-PCR）. Pearson correlation analysis was performed to evaluate the relationships among tumor tissue Young's modulus， apoptosis rate， and the expression levels of proteins related to the integrinβ1/FAK/YAP signaling pathway. ResultsCompared to the model group， tumor weight was significantly reduced in the doxorubicin group and the medium- and high-dose HSF groups， while tumor volume significantly decreased in the doxorubicin group and the high-dose HSF group （P＜0.01）. Tumor weight in the high-dose HSF group was significantly lower than that in the low-dose group， and tumor volume was significantly smaller than that in both the low- and medium-dose groups （P＜0.05）. Marked improvements in histopathological morphology were observed in the medium- and high-dose HSF groups and the doxorubicin group， while the proportion of collagen fiber deposition and the nuclear-to-cytoplasmic ratio of YAP were significantly reduced （P＜0.01）. Compared to the model group， all three HSF groups and the doxorubicin group exhibited significantly increased apoptosis rates， decreased Young's modulus， and reduced mRNA expression levels of integrinβ1， and YAP （P＜0.05 or P＜0.01）. Furthermore， protein expression levels of integrinβ1， p-FAK， and YAP in the high-dose HSF group were significantly lower than those in the model group （P＜0.05 or P＜0.01）. Pearson correlation analysis demonstrated a significant negative correlation between tumor tissue Young's modulus and apoptosis rate （r =-0.93， P＜0.01）. In contrast， the protein expression levels of integrinβ1， p-FAK， and YAP were positively correlated with Young's modulus （r=0.88， 0.97， and 0.98， respectively； P＜0.05） and negatively correlated with apoptosis rate （r=-0.93，-0.97， and -0.93， respectively； P＜0.05）. ConclusionHSF can significantly inhibit tumor growth in TNBC model mice. Its antitumor effect may be associated with reducing tumor tissue stiffness through suppression of the integrinβ1/FAK/YAP mechanotransduction signaling pathway.

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.

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.

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.

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.

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.

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.

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.