This article systematically reviews the current research status as well as diagnosis and treatment strategies of traditional Chinese medicine （TCM） for gastroesophageal reflux disease （GERD）. Studies demonstrate that TCM， based on the "disease-syndrome combination" approach， exhibits multi-target advantages in alleviating symptoms of various GERD subtypes， promoting mucosal repair， regulating emotions， and facilitating the reduction of western medication. To address clinical challenges such as symptom overlap and limited therapeutic efficacy， strategies have been proposed including "treating different diseases with the same method" and integrated regulation based on viscera correlation. Future efforts should focus on elucidating the mechanisms of compound prescriptions， promoting TCM drug development under the "three-combination" evaluation framework that integrates TCM theory， human experience and clinical trial evidence， and optimizing integrated traditional and western medicine models to enhance GERD management.

ObjectiveTo analyze the glycan receptor binding characteristics of capsid proteins of GⅡ.5 norovirus(NoV) in order to lay a foundation for the development of antiviral drugs and vaccines for NoV.MethodsThe P proteins of GⅡ.5 N490 and GⅡ.5 12X were expressed in prokaryotic system respectively, purified using glutathione affinity chromatography, and then the binding characteristics of P proteins with saliva and glycan were detected by ELISA. The structure of two GⅡ.5 strains was modeled and the binding amino acids between the P protein and glycan were analyzed based on the epidemic GⅡ.17 KW308.ResultsThe relative molecular mass of the both P proteins of GⅡ.5 N490 and GⅡ.5 12X was 61 000,which were expressed in soluble from in the supernatant, and the purified concentration was 0. 2 mg/mL. The P proteins of two GⅡ.5 strains could bind to most of A, B, O secretory and non-secretory saliva. The P protein of GⅡ.5 N490 exhibited binding to H disaccharide, while the P protein of GⅡ.5 12X showed specific binding to H disaccharide and B trisaccharide. In addition, the model of two GⅡ.5 strains displayed a conformation similar to that of GⅡ.17 KW308. Among the six amino acid sites interacting with glycan, Arg349, Asp378, Gly443 of GⅡ.5 N490 and GⅡ.5 12X were the same as those of G Ⅱ.17 KW308, while Asn375, Glu380 and Phe444 were different from those of G Ⅱ.17 KW308.ConclusionThe two strains of G Ⅱ. 5 exhibit similar binding characteristics in saliva binding patterns with P proteins and both have a wide susceptible population, while the glycan binding patterns are slightly different.

ObjectiveProtein-protein interactions (PPIs) are fundamental to the execution of biological functions within living cells. However, traditional biochemical methods, such as co-immunoprecipitation (Co-IP), often fail to capture transient, weak, or membrane-associated interactions due to the stringent detergent requirements for cell lysis. Proximity labeling (PL) has emerged in recent years as a transformative technology for mapping the proteomes of specific subcellular compartments and identifying dynamic interactomes in situ. Golgi protein 73 (GP73, also known as GOLPH2), a resident type II Golgi transmembrane protein, is a well-recognized clinical biomarker for liver diseases, including hepatocellular carcinoma (HCC). Despite its clinical significance, the comprehensive physiological and pathological functions of GP73 remain partially understood. This study aims to establish an APEX2-mediated proximity labeling system specifically targeting GP73 to map its interactome in a living cellular environment, thereby providing new insights into its molecular roles and regulatory mechanisms. MethodsTo achieve spatial specificity, we first constructed a stable cell line expressing a fusion protein consisting of GP73 and the engineered soybean peroxidase APEX2. The localization of the GP73-APEX2 fusion protein was validated to ensure it correctly targeted the Golgi apparatus. The proximity labeling reaction was initiated by incubating the cells with biotin-phenol (BP) for 30 min, followed by a brief (1 min) treatment with1 mmol/L hydrogen peroxide (H₂O₂). This catalytic reaction converts BP into highly reactive, short-lived biotin-phenoxyl radicals that covalently attach to endogenous proteins within a small labeling radius of the GP73-APEX2 enzyme. Subsequently, the cells were quenched, and biotinylated proteins were enriched using high-affinity streptavidin-coated magnetic beads. The captured “neighbor” proteins were subjected to on-bead digestion and analyzed via liquid chromatography-tandem mass spectrometry (LC-MS/MS) for high-throughput identification. Rigorous bioinformatics analysis, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction network mapping, was performed to interpret the biological significance of the identified candidates. ResultsOur results demonstrate the successful establishment of a robust and sensitive APEX2-based proximity labeling system for GP73. We identified a total of 95 high-confidence interacting proteins that were significantly enriched in the GP73 proximity proteome compared to control groups. Bioinformatics analysis revealed that these interactors were predominantly associated with biological processes such as vesicular transport, protein localization, and, most notably, molecular functions related to “ribosome binding” and “translation regulation”. This suggested an unexpected role for the Golgi-resident GP73 in the cellular translation machinery. To validate these findings, we performed targeted biochemical assays which confirmed a direct interaction between GP73 and the subunits of the eukaryotic translation initiation factor 3 (eIF3) complex, specifically EIF3G and EIF3I. Furthermore, functional validation using the surface sensing of translation (SUnSET) assay—a non-radioactive method to monitor protein synthesis—revealed that the overexpression of GP73 significantly promoted global protein translation levels in the cell, whereas its depletion or inhibition resulted in reduced translation efficiency. ConclusionThis study successfully utilized APEX2-mediated proximity labeling to provide the first systematic map of GP73 interactome in living cells. Our findings uncover a novel, unconventional function of GP73 as a regulator of cellular protein translation, likely mediated through its interaction with the eIF3 complex. This discovery significantly broadens our understanding of the biological roles of GP73 beyond its traditional function in the Golgi apparatus and suggests that it may act as a bridge between Golgi-related trafficking and the protein synthesis machinery. Furthermore, the technical framework established in this study provides a valuable template for investigating other complex organelle-associated protein networks and resolving transient macromolecular interactions in various physiological and pathological contexts.

Depression, a prevalent mental disorder with significant socioeconomic burdens, underscores the urgent need for safe and effective non-pharmacological interventions. Recent advances in microbiome research have revealed the pivotal role of gut microbiota dysbiosis in the pathogenesis of depression. Concurrently, exercise, as a cost-effective and accessible intervention, has demonstrated remarkable efficacy in alleviating depressive symptoms. This comprehensive review synthesizes current evidence on the interplay among exercise, gut microbiota modulation, and depression, elucidating the mechanistic pathways through which exercise ameliorates depressive symptoms via the microbiota-gut-brain (MGB) axis. Depression is characterized by gut microbiota alterations, including reduced alpha and beta diversity, depletion of beneficial taxa (e.g., Bifidobacterium, Lactobacillus, and Coprococcus), and overgrowth of pro-inflammatory and pathogenic bacteria (e.g., Morganella, Klebsiella, and Enterobacteriaceae). Metagenomic analyses reveal disrupted metabolic functions in depressive patients, such as diminished synthesis of short-chain fatty acids (SCFAs), impaired tryptophan metabolism, and dysregulated bile acid conversion. For instance, Bifidobacterium longum deficiency correlates with reduced synthesis of neuroactive metabolites like homovanillic acid, while decreased Coprococcus abundance limits butyrate production, exacerbating neuroinflammation. Furthermore, elevated levels of indole derivatives from Clostridium species inhibit serotonin (5-HT) synthesis, contributing to depressive phenotypes. These dysbiotic profiles disrupt the MGB axis, triggering systemic inflammation, neurotransmitter imbalances, and hypothalamic-pituitary-adrenal (HPA) axis hyperactivity. Exercise exerts profound effects on gut microbiota composition, diversity, and metabolic activity. Longitudinal studies demonstrate that sustained aerobic exercise increases alpha diversity, enriches SCFA-producing genera (e.g., Faecalibacterium prausnitzii, Roseburia, and Akkermansia), and suppresses pathobionts (e.g., Desulfovibrio and Streptococcus). For example, a meta-analysis of 25 trials involving 1 044 participants confirmed that exercise enhances microbial richness and restores the Firmicutes/Bacteroidetes ratio, a biomarker of metabolic health. Notably, endurance training promotes Veillonella proliferation, which converts lactate into propionate, enhancing energy metabolism and delaying fatigue. Exercise also strengthens intestinal barrier integrity by upregulating tight junction proteins (e.g., ZO-1, occludin), thereby reducing lipopolysaccharide (LPS) translocation and systemic inflammation. However, excessive exercise may paradoxically diminish microbial diversity and exacerbate intestinal permeability, highlighting the importance of moderate intensity and duration. Exercise ameliorates depressive symptoms through multifaceted interactions with the gut microbiota, primarily via 4 interconnected pathways. First, exercise mitigates neuroinflammation by elevating anti-inflammatory SCFAs such as butyrate, which suppresses NF-κB signaling to attenuate microglial activation and oxidative stress in the hippocampus. Animal studies demonstrate that voluntary wheel running reduces hippocampal TNF‑α and IL-17 levels in stress-induced depression models, while fecal microbiota transplantation (FMT) from exercised mice reverses depressive behaviors by modulating the TLR4/NF‑κB pathway. Second, exercise regulates neurotransmitter dynamics by enriching GABA-producing Lactobacillus and Bifidobacterium, thereby counteracting neuronal hyperexcitability. Aerobic exercise also enhances the abundance of Lactobacillus plantarum and Streptococcus thermophilus, which facilitate 5-HT and dopamine synthesis. Clinical trials reveal that 12 weeks of moderate exercise increases fecal Coprococcus and Blautia abundance, correlating with improved 5-HT bioavailability and reduced depression scores. Third, exercise normalizes HPA axis hyperactivity by reducing cortisol levels and restoring glucocorticoid receptor sensitivity. In rodent models, chronic stress-induced corticosterone elevation is reversed by probiotic supplementation (e.g., Lactobacillus), which enhances endocannabinoid signaling and hippocampal neurogenesis. Furthermore, exercise upregulates brain-derived neurotrophic factor (BDNF) via microbial metabolites like butyrate, promoting histone acetylation and synaptic plasticity. FMT experiments confirm that exercise-induced microbiota elevates prefrontal BDNF expression, reversing stress-induced neuronal atrophy. Fourth, exercise reshapes microbial metabolic crosstalk, diverting tryptophan metabolism toward 5-HT synthesis instead of neurotoxic kynurenine derivatives. Butyrate inhibits indoleamine 2,3-dioxygenase (IDO), a key enzyme in the kynurenine pathway linked to depression. Concurrently, exercise-induced Akkermansia enrichment enhances mucin production, fortifies the gut barrier, and reduces LPS-driven neuroinflammation. Collectively, these mechanisms underscore exercise as a potent modulator of the microbiota-gut-brain axis, offering a holistic approach to alleviating depression through microbial and neurophysiological synergy. Current evidence supports exercise as a potent adjunct therapy for depression, with personalized regimens (e.g., aerobic, resistance, or yoga) tailored to individual microbiota profiles. However, challenges remain in optimizing exercise prescriptions (intensity, duration, and type) and integrating them with probiotics, prebiotics, or FMT for synergistic effects. Future research should prioritize large-scale randomized controlled trials to validate causality, multi-omics approaches to decipher MGB axis dynamics, and mechanistic studies exploring microbial metabolites as therapeutic targets. The authors advocate for a paradigm shift toward microbiota-centric interventions, emphasizing the bidirectional relationship between physical activity and gut ecosystem resilience in mental health management. In conclusion, this review underscores exercise as a multifaceted modulator of the gut-brain axis, offering novel insights into non-pharmacological strategies for depression. By bridging microbial ecology, neuroimmunology, and exercise physiology, this work lays a foundation for precision medicine approaches targeting the gut microbiota to alleviate depressive disorders.

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.

ObjectiveThis study proposes a novel single-cell protein localization method based on a class perception graph convolutional network (CP-GCN) to overcome several critical challenges in protein microscopic image analysis, including the scarcity of cell-level annotations, inadequate feature extraction, and the difficulty in achieving precise protein localization within individual cells. The methodology involves multiple innovative components designed to enhance both feature extraction and localization accuracy. MethodsFirst, a class perception module (CPM) is developed to effectively capture and distinguish semantic features across different subcellular categories, enabling more discriminative feature representation. Building upon this, the CP-GCN network is designed to explore global features of subcellular proteins in multicellular environments. This network incorporates a category feature-aware module to extract protein semantic features aligned with label dimensions and establishes a subcellular relationship mining module to model correlations between different subcellular structures. By doing so, it generates co-occurrence embedding features that encode spatial and contextual relationships among subcellular locations, thereby improving feature representation. To further refine localization, a multi-scale feature analysis approach is employed using the K-means clustering algorithm, which classifies multi-scale features within each subcellular category and generates multi-cell class activation maps (CAMs). These CAMs highlight discriminative regions associated with specific subcellular locations, facilitating more accurate protein localization. Additionally, a pseudo-label generation strategy is introduced to address the lack of annotated single-cell data. This strategy segments multicellular images into single-cell images and assigns reliable pseudo-labels based on the CAM-predicted regions, ensuring high-quality training data for single-cell analysis. Under a transfer learning framework, the model is trained to achieve precise single-cell-level protein localization, leveraging both the extracted features and pseudo-labels for robust performance. ResultsExperimental validation on multiple single-cell test datasets demonstrates that the proposed method significantly outperforms existing approaches in terms of robustness and localization accuracy. Specifically, on the Kaggle 2021 dataset, the method achieves superior mean average precision (mAP) metrics across 18 subcellular categories, highlighting its effectiveness in diverse protein localization tasks. Visualization of the generated CAM results further confirms the model’s capability to accurately localize subcellular proteins within individual cells, even in complex multicellular environments. ConclusionThe integration of the CP-GCN network with a pseudo-labeling strategy enables the proposed method to effectively capture heterogeneous cellular features in protein images and achieve precise single-cell protein localization. This advancement not only addresses key limitations in current protein image analysis but also provides a scalable and accurate solution for subcellular protein studies, with potential applications in biomedical research and diagnostic imaging. The success of this method underscores the importance of combining advanced deep learning architectures with innovative training strategies to overcome data scarcity and improve localization performance in biological image analysis. Future work could explore the extension of this framework to other types of microscopic imaging and its application in large-scale protein interaction studies.

Objective:To explore the effects three of anesthetics(tribromoethanol,isoflurane,and pentobarbital so-dium)on the outcome of mice with post-stroke dysphagia(PSD)induced by photothrombosis(PT)method,and to e-valuate which anesthetic is more suitable for the preparation of this model.Methods:Sixty-six male C57BL/6J mice were divided into Tribromoethanol group,Isoflurane group,Pentobarbital sodium group and Sham group.The post-stroke dysphagia model was established by PT.Before and 5 min after modeling,a laser speckle imager was used to measure the regional cerebral blood flow(rCBF)decrease rate of mice and record the wake-up time of mice.Forty-eight hours after modeling,the mortality rate of PSD mice in three groups was recorded and the rCBF decrease rate was meas-ured again.The neurological function of mice was evaluated using the neurological deficit score,the water intake of mice was recorded using the 4-min drinking test,the infarct volume ratio was measured using the TTC staining method,and the swallowing counts induced by water administration was recorded using the multichannel physiological recorder MP160 and the myoelectric area of the swallowing muscle was calculated.Results:There was no statistical difference in the percentage of decrease in rCBF,infarct volume ratio,neurological deficit score,water intake,swallowing counts,and myoelectric area of swallowing muscle among the three groups of PSD mice 48 h after modeling(P＞0.05).Com-pared with the Tribromoethanol group and the Pentobarbital sodium group,the rCBF of the mice in the Isoflurane group decreased rapidly within 5 min(P＜0.05),and the mortality rate of the mice was lower and the awakening time was shorter.(P＜0.05).Conclusion:The use of different anesthesia will affect the mortality rate,wake-up time and the downward trend of rCBF within 48 h after modeling of PSD mice.Among the three anesthetics,isoflurane is more suit-able as an anesthetic for the PSD mouse model.

Objective:To analyze the clinical characteristics of frailty in elderly patients with chronic obstructive pulmonary disease (COPD).Methods:COPD patients aged ≥65 years registered in the RealDTC study from June 2023 to March 2024 were included. Demographic data, history of exacerbations in the past year, exposure to risk factors (smoking, biomass fuel exposure, occupational exposure), modified Medical Research Council (mMRC) dyspnea score, COPD Assessment Test (CAT) score, forced expiratory volume in the first second predicted of percentage (FEV 1%pred), forced expiratory volume in one second (FEV 1) to forced vital capacity (FVC), and comorbidities (bronchial asthma, bronchiectasis, pulmonary tuberculosis, cardiovascular disease, diabetes mellitus) were collected. According to Fried′s frailty phenotype, patients meeting any 3 of the 5 criteria were defined as frail and divided into a frailty group and a non-frailty group. Multivariate regression analysis was used to screen the related factors of frailty in elderly COPD patients, and the receiver operating characteristic (ROC) curve was used to calculate the area under the curve (AUC) of related factors for frailty assessment. Results:A total of 496 elderly COPD patients were included, of which 144(29.0%) had comorbid frailty. The frailty group had lower mass body index (BMI), FEV 1%pred, and FEV 1/FVC, higher mMRC and CAT scores, more exacerbations and hospitalizations in the past year (all P<0.001), and higher proportions of patients with junior high school education or below, Global Initiative for Chronic Obstructive Lung Disease (GOLD) group E, and GOLD grades 3 and 4 (all P<0.05). Multivariate regression analysis showed that low education level ( OR=2.117, 95% CI: 1.119-4.003), low BMI ( OR=0.927, 95% CI: 0.867-0.991), GOLD grade 4 ( OR=4.251, 95% CI: 1.477-12.235), high CAT score ( OR=1.174, 95% CI: 1.127-1.224), and high mMRC score ( OR=4.578, 95% CI: 3.364-6.231) were independent risk factors for frailty in elderly COPD patients (all P<0.05). The ROC curve showed that CAT score (AUC=0.78) and mMRC score (AUC=0.81) had the highest AUC for assessing frailty in elderly COPD patients. Conclusions:Elderly COPD patients with frailty have lower BMI, worse lung function, and more severe symptom burden. The results provide clinical reference for the management of frail elderly COPD patients.

Investigated the mechanisms by which baicalein regulates nuclear factor E2-related factor 2(Nrf2)/heme oxygenase-1(HO-1)to ameliorate lipopolysaccharide(LPS)-induced sepsis-asso-ciated acute kidney injury(AKI)in mice.Sixty male C57BL/6 mice were randomly divided into six groups:control,model,low-dose baicalein(50 mg/kg),medium-dose baicalein(100 mg/kg),high-dose baicalein(200 mg/kg),and high-dose baicalein+brusatol(4 mg/kg).Baicalein was adminis-tered orally for 7 days as a preventative measure.Sepsis was induced via intraperitoneal injection of LPS.Murine sepsis score(MSS)was assessed within 12 hours post-induction.Serum creatinine(Scr),blood urea nitrogen(BUN),tumor necrosis factor-α(TNF-α),interleukin-1β(IL-1β),and interleukin-6(IL-6)were measured using an automatic biochemical analyzer and enzyme-linked immunosorbent assays(ELISA),respectively.Histopathological changes in kidney tissues were ob-served via hematoxylin-eosin(HE)staining.Western blot analysis was employed to determine the protein expression levels of Nrf2,HO-1,caspase-8,TNF-α,IL-1β,and IL-6 in kidney tissues.Additionally,total superoxide dismutase(SOD)activity in kidney tissues was assessed using com-mercially available kits.Compared to the model group,baicalein treatment significantly improved renal histopathological changes,alleviated cellular damage,and reduced the levels of inflammatory cytokines(TNF-α,IL-1βand IL-6)(P＜0.01)and kidney injury markers(Scr and BUN)(P＜0.01).Moreover,baicalein treatment significantly increased the protein expression levels of Nrf2 and HO-1(P＜0.01)and enhanced antioxidant enzyme activity.In conclusion,baicalein may pro-tect against LPS-induced sepsis-associated AK1 in mice by modulating the Nrf2/HO-1 signaling pathway,thereby attenuating oxidative stress,reducing inflammation,and disrupting the vicious cycle between inflammation and oxidative stress.

Objective:To explore the effect of remote motor imagery therapy on rehabilitation of patients with severe coronary heart disease(CHD)after percutaneous coronary intervention(PCI).Methods:This randomized con-trolled study enrolled 164 patients with severe CHD undergoing PCI who admitted in the First Affiliated Hospital of Hebei North University between January 2022 and January 2024.Patients were divided into control group(n=82)and intervention group(n=82).Patients in the control group was given conventional home nursing intervention comparing to those in the intervention group receiving additional remote motor imagery therapy.Both groups were intervened for 8 weeks.Indexes of pain,psychological emotion,ability of daily living,motor function and fall were compared between two groups.Results:Compared to those in control group after intervention,patients in interven-tion group had significant lower scores of visual analogue scale(VAS)[(2.03±0.81)points vs.(5.14±0.84)points],the Hospital anxiety and depression scale(HADS)anxiety subscale(HADS-A)[(4.89±0.84)points vs.(9.05±0.78)points],HADS depression subscale(H ADS-D)[(5.31±1.10)points vs.(10.13±0.82)points],HADS total score[(10.20±1.39)points vs.(19.18±1.18)points](P＜0.001 all),and significant higher 6-min walking distance(6MWD)[(439.31±16.51)m vs.(364.94±12.76)m],peak oxygen uptake(VO2 peak)[(20.28±2.40)ml·kg-1·min-1 vs.(17.26±1.35)ml·kg-1·min-1],anaerobic threshold oxygen consumption(VO2AT)[(17.04±1.18)ml·kg-1·min-1 vs.(13.62±1.16)ml·kg-1·min-1],scores of Chinese modified Fall Efficacy Scale(MFES)[(107.28±4.84)points vs.(87.41±4.73)points],ability of daily living(ADL)scale[(78.95±3.92)points vs.(68.00±4.10)points]and Barthel index[(85.83±2.50)points vs.(69.79±3.42)points](P＜0.001 all).We detected significant lower incidence of falling(7.50％vs.21.25％)in the intervention group compared to control group(P=0.013).Conclusion:Remote motor imagery therapy may strengthen motor function and ability of daily living,and relieve pain and negative emotions in patients with severe CHD after PCI.