A 71-year-old male presented with esophageal cancer and severe aortic valve regurgitation. Treatment strategies for such patients are controversial. Considering the risks of cardiopulmonary bypass and potential esophageal cancer metastasis, we successfully performed transcatheter aortic valve implantation and minimally invasive three-incision thoracolaparoscopy combined with radical resection of esophageal cancer (McKeown) simultaneously in the elderly patient who did not require neoadjuvant treatment. This dual minimally invasive procedure took 6 hours and the patient recovered smoothly without any surgical complications.

ObjectiveIn nature, objects cast shadows due to illumination, forming the basis for stereoscopic perception. Birds need to adapt to changes in lighting (meaning they can recognize stereoscopic shapes even when shadows look different) to accurately perceive different three-dimensional forms. However, how neurons in the key visual brain area in birds handle these lighting changes remains largely unreported. In this study, pigeons (Columba livia) were used as subjects to investigate how neurons in pigeon’s ventrolateral mesopallium (MVL) represent stereoscopic shapes consistently, regardless of changes in lighting. MethodsVisual cognitive training combined with neuronal recording was employed. Pigeons were first trained to discriminate different stereoscopic shapes (concave/convex). We then tested whether and how light luminance angle and surface appearance of the stereoscopic shapes affect their recognition accuracy, and further verify whether the results rely on specify luminance color. Simultaneously, neuronal firing activity of neurons was recorded with multiple electrode array implanted from the MVL during the presentation of difference shapes. The response was finally analyzed how selectively they responded to different stereoscopic shapes and whether their selectivity was affected by the changes of luminance condition (like lighting angle) or surface look. Support vector machine (SVM) models were trained on neuronal population responses recorded under one condition (light luminance angle of 45°) and used to decode responses under other conditions (light luminance angle of 135°, 225°, 315°) to verify the invariance of responses to different luminance conditions. ResultsBehavioral results from 6 pigeons consistently showed that the pigeons could reliably identify the core 3D shape (over 80% accuracy), and this ability wasn’t affected by changes in light angle or surface appearance. Statistical analysis of 88 recorded neurons from 6 pigeons revealed that 83% (73/88) showed strong selectivity for specific 3D shapes (selectivity index>0.3), and responses to convex shapes were consistently stronger than to concave shapes. These shape-selective responses remained stable across changes in light angle and surface appearance. Neural patterns were consistent under both blue and orange lighting. The decoding accuracy achieves above 70%, suggesting stable responses under different conditions (e.g., different lighting angles or surface appearance). ConclusionNeurons in the pigeon MVL maintain a consistent neural encoding pattern for different stereoscopic shapes, unaffected by illumination or surface appearance. This ensures stable object recognition by pigeons in changing visual environments. Our findings provide new physiological evidence for understanding how birds achieve stable perception (“invariant neural representations”) while coping with variations in the visual field.

ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Atherosclerosis (AS) is a prevalent clinical vascular condition and serves as a pivotal pathological foundation for cardiovascular diseases. Understanding the pathogenesis of AS has significant clinical and societal implications, aiding in the development of targeted drugs. Neutrophils, the most abundant leukocytes in circulation, assume a central role during inflammatory responses and closely interact with AS, which is a chronic inflammatory vascular disease. Neutrophil extracellular traps (NETs) are substantial reticular formations discharged by neutrophils that serve as an immune defense mechanism. These structures play a crucial role in inducing dysfunction of the vascular barrier following endothelial cell injury. Components released by NETs pose a threat to the integrity of vascular endothelium, which is essential as it acts as the primary barrier to maintain vascular wall integrity. Endothelial damage constitutes the initial stage in the onset of AS. Recent investigations have explored the intricate involvement of NETs in AS progression. The underlying structures of NETs and their active ingredients, including histone, myeloperoxidase (MPO), cathepsin G, neutrophil elastase (NE), matrix metalloproteinases (MMPs), antimicrobial peptide LL-37, alpha-defensin 1-3, and high mobility group protein B1 have diverse and complex effects on AS through various mechanisms. This review aims to comprehensively examine the interplay between NETs and AS while providing insights into their mechanistic underpinnings of NETs in this condition. By shedding light on this intricate relationship, this exploration paves the way for future investigations into NETs while guiding clinical translation efforts and charting new paths for therapeutic interventions.
Extracellular Traps/physiology* ; Humans ; Atherosclerosis/immunology* ; Neutrophils/physiology* ; Leukocyte Elastase/metabolism* ; Peroxidase/physiology* ; Matrix Metalloproteinases/physiology* ; Cathepsin G/metabolism* ; Cathelicidins ; HMGB1 Protein/physiology* ; Histones ; Animals ; Endothelium, Vascular

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

Based on the pharmacokinetics theory, this study investigated the pharmacokinetic characteristics of albiflorin, paeoniflorin, wogonoside, and wogonin in normal and febrile rats and summarized absorption and elimination rules of Dayuanyin in them to provide reference for further development and clinical application of Dayuanyin. Blood samples were taken from the fundus venous plexus of normal and model rats after intragastric administration of Dayuanyin at different time points. The concentration of each substance in blood was determined by ultra performance liquid chromatography-triple quadrupole mass spectrometry(UPLC-MS/MS) technique at different time points. DAS 2.0, a piece of pharmacokinetics software, was used to calculate the pharmacokinetic parameters of each component. The results show that the 4 components had good linear relationship in their respective ranges, and the results of methodological investigation met the requirements. The pharmacokinetic parameters of C_(max), T_(max), t_(1/2), AUC_(0-t), AUC_(0-∞), and MRT_(0-t) were calculated by the DAS 2.0 non-compartmental model. Compared with those in the normal group, C_(max) and AUC_(0-t) of the 4 components in the model group were significantly increased. There were significant differences in the pharmacokinetic characteristics between the normal and model groups, suggesting that the absorption and elimination of Dayuanyin may be affected by the changes of internal environment of the body in different physiological states.
Animals ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Rats, Sprague-Dawley ; Fever/metabolism* ; Tandem Mass Spectrometry ; Chromatography, High Pressure Liquid ; Glucosides/pharmacokinetics* ; Monoterpenes

This study aims to comprehensively analyze the material basis of toad visceral oil(hereafter referred to as toad oil), and explore the pharmacological effect of toad oil on atopic dermatitis(AD). Ultra-high performance liquid chromatography-linear ion trap/orbitrap high-resolution mass spectrometry(UHPLC-LTQ-Orbitrap-MS) and gas chromatography-mass spectrometry(GC-MS) were employed to comprehensively identify the chemical components in toad oil. The animal model of AD was prepared by the hapten stimulation method. The modeled animals were respectively administrated with positive drug(0.1% hydrocortisone butyrate cream) and low-and high-doses(1%, 10%) of toad oil by gavage. The effect of toad oil on AD was evaluated with the AD score, ear swelling rate, spleen index, and pathological section results as indicators. A total of 99 components were identified by UHPLC-LTQ-Orbitrap-MS, including 14 bufadienolides, 7 fatty acids, 6 alkaloids, 10 ketones, 18 amides, and other compounds. After methylation of toad oil samples, a total of 20 compounds were identified by GC-MS. Compared with the model group, the low-and high-dose toad oil groups showed declined AD score, ear swelling rate, and spleen index, alleviated skin lesions, and reduced infiltrating mast cells. This study comprehensively analyzes the chemical composition and clarifies the material basis of toad oil. Meanwhile, this study proves that toad oil has a good therapeutic effect on AD and is a reserve resource of traditional Chinese medicine for external use in the treatment of AD.
Animals ; Dermatitis, Atopic/immunology* ; Disease Models, Animal ; Mice ; Male ; Gas Chromatography-Mass Spectrometry ; Humans ; Bufonidae ; Oils/administration & dosage* ; Chromatography, High Pressure Liquid ; Female ; Mice, Inbred BALB C

This study aimed to investigate the underlying mechanisms of Duhuo Jisheng Decoction(DJD) in the prevention and treatment of knee osteoarthritis(KOA). Forty SPF New Zealand rabbits were randomly divided using SPSS 26.0 software into five groups: blank group, model group, low-dose DJD group, high-dose DJD group, and high-dose DJD+phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt)/mammalian target of rapamycin(mTOR) signaling pathway activator group(high-dose DJD+740Y-P group), with eight rabbits in each group. Except for the blank group, the KOA model was established in the other groups using papain injection into the knee joint cavity combined with forced flexion of the knee joint. The day after modeling, the blank group and model group were given normal saline at 10 mL·kg~(-1) by gavage, the low-dose DJD group received DJD at 8.8 g·kg~(-1) by gavage, the high-dose DJD group received DJD at 35.2 g·kg~(-1) by gavage, and the high-dose DJD+740Y-P group received DJD at 35.2 g·kg~(-1) by gavage along with 740Y-P at 0.15 μmoL·kg~(-1) injected via the auricular vein. All groups received treatment continuously for four weeks. After modeling and intervention, behavioral observations were performed for all groups, and after the intervention, imaging assessments of the knee joints were conducted. Cartilage from the knee joints was collected, and gross morphological changes were observed. Pathological changes in cartilage tissue were examined using hematoxylin-eosin(HE) staining. The results of these observations were quantitatively evaluated using the Lequesne MG score, Kellgren-Lawrence(K-L) grading, Pelletier score, and Mankin score. ELISA was used to measure the levels of interleukin-1β(IL-1β), interleukin-18(IL-18), and matrix metalloproteinase 13(MMP13) in cartilage tissue. Real-time RT-PCR was used to detect the mRNA expression levels of PI3K, Akt, mTOR, Nod-like receptor protein 3(NLRP3), cysteine protease 1(caspase-1), and gasdermin D(GSDMD) in cartilage tissue. Western blot was employed to measure the protein expression levels of PI3K, Akt, mTOR, NLRP3, caspase-1, and GSDMD. The results showed that compared with the blank group, the model group exhibited significant knee joint degeneration, increased Lequesne MG score, K-L grading, Pelletier score, and Mankin score, elevated levels of IL-1β, IL-18, and MMP13 in cartilage tissue, activation of PI3K, Akt, and mTOR phosphorylation along with increased mRNA expression levels, and elevated protein and mRNA expression levels of NLRP3, caspase-1, and GSDMD. Compared with the model group, these indicators were reversed in both the low-dose and high-dose DJD groups, with the high-dose group showing greater decline degree than the low-dose DJD group. However, compared with the high-dose DJD group, the improvements in knee joint degeneration were less pronounced in the high-dose DJD+740Y-P group, with increased Lequesne MG score, K-L grading, Pelletier score, Mankin score, elevated levels of IL-1β, IL-18, and MMP13, activation of PI3K, Akt, and mTOR phosphorylation along with increased mRNA expression, and increased protein and mRNA expression levels of NLRP3, caspase-1, and GSDMD. In conclusion, DJD is effective and safe in the treatment of KOA, and its mechanism may be related to the inhibition of PI3K/Akt/mTOR signaling pathway-mediated pyroptosis in cartilage tissue, thereby improving knee joint bone structure, reducing the inflammatory response, and preventing cartilage matrix degradation.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rabbits ; TOR Serine-Threonine Kinases/genetics* ; Osteoarthritis, Knee/genetics* ; Proto-Oncogene Proteins c-akt/genetics* ; Signal Transduction/drug effects* ; Male ; Disease Models, Animal ; Pyroptosis/drug effects* ; Phosphatidylinositol 3-Kinases/genetics* ; Humans ; Female

This study employed the "disease-medicine-dose" pattern to mine the medication rules of traditional Chinese medicine(TCM) prescriptions containing Astragali Radix in ancient Chinese medical books, aiming to provide a scientific basis for the clinical application of Astragali Radix and the development of new medicines. The TCM prescriptions containing Astragali Radix were retrieved from databases such as Chinese Medical Dictionary and imported into Excel 2020 to construct the prescription library. Statical analysis were performed for the prescriptions regarding the indications, syndromes, medicine use frequency, herb effects, nature and taste, meridian tropism, dosage forms, and dose. SPSS statistics 26.0 and IBM SPSS Modeler 18.0 were used for association rules analysis and cluster analysis. A total of 2 297 prescriptions containing Astragali Radix were collected, involving 233 indications, among which sore and ulcer, consumptive disease, sweating disorder, and apoplexy had high frequency(>25), and their syndromes were mainly Qi and blood deficiency, Qi and blood deficiency, Yin and Yang deficiency, and Qi deficiency and collateral obstruction, respectively. In the prescriptions, 98 medicines were used with the frequency >25 and they mainly included Qi-tonifying medicines and blood-tonifying medicines. Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Ginseng Radix et Rhizoma, Atractylodis Macrocephalae Rhizoma, and Citri Reticulatae Pericarpium were frequently used. The medicines with high frequency mainly have warm or cold nature, and sweet, pungent, or bitter taste, with tropism to spleen, lung, heart, liver, and kidney meridians. In the treatment of sore and ulcer, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to promote granulation and heal up sores. In the treatment of consumptive disease, Astragali Radix was mainly used with the dose of 37.30 g and combined with Ginseng Radix et Rhizoma to tonify deficiency and replenish Qi. In the treatment of sweating disorder, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to consolidate exterior and stop sweating. In the treatment of apoplexy, Astragali Radix was mainly used with the dose of 7.46 g and combined with Glycyrrhizae Radix et Rhizoma to dispell wind and stop convulsions. Astragali Radix can be used in the treatment of multiple system diseases, with the effects of tonifying Qi and ascending Yang, consolidating exterior and stopping sweating, and expressing toxin and promoting granulation. According to the manifestations of different diseases, when combined with other medicines, Astragali Radix was endowed with the effects of promoting granulation and healing up sores, tonifying deficiency and Qi, consolidating exterior and stopping sweating, and dispelling wind and replenishing Qi. The findings provide a theoretical reference and a scientific basis for the clinical application of Astragali Radix and the development of new medicines.
Drugs, Chinese Herbal/history* ; Humans ; Medicine, Chinese Traditional/history* ; History, Ancient ; Astragalus Plant/chemistry* ; China ; Astragalus propinquus