Purpose: Due to the preservation of the entire stomach after endoscopic resection, the occurrence of metachronous gastric cancer (MGC) remains a possibility. In this study, we investigated the incidence and risk factors for MGC in patients with early gastric cancer who underwent endoscopic submucosal dissection (ESD) and successfully eradicatedHelicobacter pylori. Materials and Methods: A retrospective analysis was conducted of 1,191 patients who underwent ESD and successfully eradicated H. pylori at the Affiliated Drum Tower Hospital of Nanjing University. Endoscopic surveillance was performed at 3, 6, and 12 months post-resection, and annually thereafter. MGC was defined as the development of a new cancer at a site other than the primary gastric cancer site, at least 1 year after the initial endoscopic resection. Results: A total of 77 patients were diagnosed with MGC during a median follow-up of 41.5 months. Kaplan-Meier analysis showed a 5-year cumulative incidence of MGC of 9.4% after successful H. pylori eradication. Multivariate analysis of the training set using Cox proportional hazards models identified male sex, severe atrophic gastritis, multiple gastric cancers before H. pylori eradication, and smoking history as independent risk factors for MGC.The nomogram exhibited favorable discrimination, with area under the curves of 0.767 and 0.822 in the training set and 0.724 and 0.745 in the testing set at 3 and 5 years, respectively. Conclusions Patients with gastric cancer who undergo endoscopic resection, even after successful H. pylori eradication, should undergo annual and continuous endoscopic surveillance for MGC.

Sarcopenia, an age-related degenerative skeletal muscle disorder characterized by progressive loss of muscle mass, diminished strength, and impaired physical function, poses substantial challenges to global healthy aging initiatives. The pathogenesis of this condition is fundamentally rooted in mitochondrial dysfunction, manifested through defective energy metabolism, disrupted redox equilibrium, imbalanced dynamics, and compromised organelle quality control. This comprehensive review elucidates the central role of exercise-induced mitochondrial hormesis as a critical adaptive mechanism counteracting sarcopenia. Mitohormesis represents an evolutionarily conserved stress response wherein sublethal mitochondrial perturbations, particularly transient low-dose reactive oxygen species (ROS) generated during muscle contraction, activate cytoprotective signaling cascades rather than inflicting macromolecular damage. The mechanistic foundation of this process involves ROS functioning as essential signaling molecules that activate the Keap1 nuclear factor erythroid 2 related factor 2 (Nrf2) antioxidant response element pathway. This activation drives transcriptional upregulation of phase II detoxifying enzymes including superoxide dismutase (SOD) and glutathione peroxidase (GPx), thereby enhancing cellular redox buffering capacity. Crucially, Nrf2 engages in bidirectional molecular crosstalk with peroxisome proliferator activated receptor gamma coactivator 1 alpha (PGC-1α), the principal regulator orchestrating mitochondrial biogenesis through coordinated induction of nuclear respiratory factors 1 and 2 (NRF1/2) along with mitochondrial transcription factor A (Tfam), collectively facilitating mitochondrial DNA replication and respiratory complex assembly. Concurrently, exercise-induced alterations in cellular energy status, specifically diminished ATP to AMP ratios, potently activate AMP activated protein kinase (AMPK). This energy-sensing kinase phosphorylates PGC-1α while concomitantly stimulating NAD dependent deacetylase sirtuin 1 (SIRT1) activity, which further potentiates PGC-1α function through post-translational deacetylation. The integrated AMPK/PGC-1α/SIRT1 axis coordinates mitochondrial biogenesis, optimizes network architecture through regulation of fusion proteins mitofusin 1 (Mfn1), mitofusin 2 (Mfn2) and optic atrophy protein 1 (OPA1), and enhances clearance of damaged organelles via selective activation of mitophagy receptors BCL2 interacting protein 3 (Bnip1) and FUN14 domain containing 1 (FNDC1). Exercise further stimulates the mitochondrial unfolded protein response (UPRmt), increasing molecular chaperones such as heat shock protein 60 (HSP60) and HSP10 to preserve proteostasis. Within the mitochondrial matrix, SIRT3 fine-tunes metabolic flux through deacetylation of electron transport chain components, improving phosphorylation efficiency while attenuating pathological ROS emission. Distinct exercise modalities differentially engage these pathways. Aerobic endurance training primarily activates AMPK/PGC-1α signaling and UPRmt to expand mitochondrial volume and oxidative capacity. Resistance training exploits mechanical tension to acutely stimulate mechanistic target of rapamycin complex 1 (mTORC1) mediated protein synthesis while modulating dynamin related protein 1 (Drp1) phosphorylation dynamics to support mitochondrial network reorganization. High intensity interval training generates potent metabolic oscillations that rapidly amplify AMPK/PGC-1α and Nrf2 activation, demonstrating particular efficacy in insulin-resistant phenotypes. Strategically designed concurrent training regimens synergistically integrate these adaptations. Mitochondrial-nuclear communication through tricarboxylic acid cycle metabolites and mitochondrially derived peptides such as mitochondrial open reading frame of 12s rRNA-c (MOTS-c) coordinates systemic metabolic reprogramming, with exercise-responsive myokines including fibroblast growth factor 21 (FGF-21) mediating inter-tissue signaling to reduce inflammation and enhance insulin sensitivity. This integrated framework provides the scientific foundation for precision exercise interventions targeting mitochondrial pathophysiology in sarcopenia, incorporating biomarker monitoring and exploring pharmacological potentiators including nicotinamide riboside and MOTS-c mimetics. Future investigations should delineate temporal dynamics of mitohormesis signaling and epigenetic regulation to optimize therapeutic approaches for age-related muscle decline.

Aim To investigate the antidepressant mechanism of hyperforin via the utilization of single-cell sequencing technology.Methods C57BL/6 mice were randomly divided into the control group,depres-sion model group,and hyperforin intervention group.The chronic unpredictable mild stress(CUMS)model was induced and drug interventions were administered for 28 d.Behavioral experiments were conducted to as-sess depressive symptoms,and hippocampal tissue was collected for single-cell RNA sequencing.Key cell populations and differentially expressed genes across groups were identified,followed by PPI network,GO,and KEGG enrichment analysis.Results Behavioral experiments indicated that CUMS successfully induced depressive symptoms in mice,while hyperforin im-proved depressive behavior.In the depression model group,the proportion of brain perivascular macrophages(PVM)increased,and this proportion decreased after hyperforin intervention,approaching the level seen in the control group.The top 20 common differentially ex-pressed genes in the PVM subpopulation were Saa3,Hbb-bs and Ccl24.PPI network analysis identified core targets,including Ccl2,Dhx9,C3,Msr1,Cxcl2 and Cx3cr1.KEGG enrichment analysis revealed pathways related to chemokines,phagosome formation,and inosi-tol phosphate metabolism.Conclusion The antide-pressant mechanism of hyperforin may be related to the regulation of Ccl24 and its related chemokine signaling pathway by PVM.

Esophageal cancer is one of the common malignant tumors,and its incidence in China is high.Effective prevention and control is a focus and challenge due to difficult prevention and late diagnosis.The development of liquid biopsy technology represented by circulating tumor DNA(ctDNA)provides new insights for early diagnosis,treatment evaluation and prognosis monitoring of esophageal cancer.ctDNA detection method has high specificity and sensitivity,which can be used in tumor screening and diagnosis,and has high application value in judging prognosis and guiding treatment.This article reviews the detection technology of ctDNA and the research progress in the diagnosis and treatment of esophageal cancer.

Aim To investigate the effect of KHSRP on the malignant biological behavior of gastric cardia ade-nocarcinoma by targeting JAK1/STAT3 signaling axis.Methods The expression levels of KHSRP in adeno-carcinoma tissues of gastric cardia adenocarcinoma and adjacent tissues were collected and compared.qRT-PCR experiment to detect transfection efficiency in gas-tric cardia adenocarcinoma cell lines(OE-19,TE-7,BIC-1,FLO-1,SK-GT-4,BE-3)and normal gastric mucosal epithelial cell line(GES-1).The knockdown and overexpression of KHSRP were treated by packa-ging lentiviral Vector,and the cells were divided into sh-NC group,sh-KHSRP group,vector group,and KH-SRP group.Cell counting kit-8(CCK-8)and Tran-swell assay were used to determine the effects of KH-SRP on the proliferation,migration and invasion of ade-nocarcinoma cells of gastric cardia adenocarcinoma.Xenograft tumor models were used to detect the effects of knockdown and overexpression of KHSRP in live an-imals.WB experiments confirmed that KHSRP targeted the JAK/STAT signaling pathway.Results KHSRP was overexpressed in GCA tissues and cell lines(P＜0.05).Cell function assay analysis showed that KH-SRP overexpression significantly promoted GCA cell proliferation,migration and invasion in vitro(P＜0.05).After KHSRP knockdown,the phosphorylation levels of JAK1 and STAT3 in JAK/STAT signaling pathway were significantly decreased,and the situation was opposite after KHSRP overexpression(P＜0.05).Conclusion KHSRP regulates the malignant progres-sion of metastasis of gastric cardia adenocarcinoma by activating JAK1/STAT3 signaling axis.

Aim To explore the mechanism of Con-grong Shujing granule(CSGs)in the treatment of Par-kinson's disease(PD)by network pharmacology,mo-lecular docking and parallel reaction monitoring(PRM)technology.Methods The active components of CSGs and the target genes of Parkinson's disease were obtained through the database.The intersection targets of drugs and diseases were selected to construct the"drug-active ingredient-target"and protein interac-tion network.The intersection target genes were impor-ted into David database for GO and KEGG enrichment analysis,and the main components were docked with key targets.27 SD rats were randomly divided into the normal group(n=9),model group(n=9)and treat-ment group(n=9).On day 1,7 and 14 of treatment,PRM analysis was used to detect the changes in the specific peptides of key target proteins in the substantia nigra of rats.Results The main components of CSGs wereTanshialdehyde,Baicalein,Quercetin and Kaempferol.The most important targets for the treat-ment of PD were TP53,AKT1,EGFR,HSP90 AA1 and STAT3.KEGG analysis mainly enriched MAPK,PI3K-Akt and neurotrophic factor signaling pathway.The molecular docking between core components and core targets showed that the binding of drugs and targets had good activity.PRM analysis of key proteins found that the target peptide expression levels of ASK1,JNK1 and JNK3 were different among groups(P＜0.05).Con-clusion CSGs can alleviate ERS,inhibit apoptosis and play a neural protective role through the ASK1-JNK pathway.

Objective To predict potential quality markers(Q-Markers)of Gastrodia elata using fingerprinting,chemical pattern recognition and network pharmacology methods.Methods A total of 46 batches of Gastrodia elata were analyzed using high-performance liquid chromatography(HPLC)to establish fingerprint profiles,and common peaks were identified.Systematic cluster analysis(HCA),principal component analysis(PCA),and orthogonal partial least squares discriminant analysis(OPLS-DA)were employed to evaluate the 46 batches of samples.Additionally,The network diagram of"components-targets-pathways"was constructed using network pharmacology.Q-Marker of Gastrodia elata was predicted and quantitative analysis was conducted simultaneously.Results Seven substances were identified among the 13 common peaks in the fingerprint profiles.Results from HCA,PCA,and OPLS-DA were consistent,while network pharmacology identified 17 core active ingredients,86 core targets,and 181 key pathways.Integrating fingerprinting and network pharmacology,Gastrodin,p-hydroxybenzyl alcohol,parishin A,parishin B,parishin C,and parishin E were selected as potential Q-Markers of Gastrodia elata.The total contents of GAS and HBA alcohol in 46 batches of Gastrodia gastrodia decoction pieces ranged from 0.17%to 2.08%.Conclusion Integration of fingerprinting and network pharmacology analyses predicted potential Q-Markers of Gastrodia elata,and providing a scientific basis for comprehensive quality control and evaluation.

Aim To investigate the antidepressant mechanism of hyperforin via the utilization of single-cell sequencing technology.Methods C57BL/6 mice were randomly divided into the control group,depres-sion model group,and hyperforin intervention group.The chronic unpredictable mild stress(CUMS)model was induced and drug interventions were administered for 28 d.Behavioral experiments were conducted to as-sess depressive symptoms,and hippocampal tissue was collected for single-cell RNA sequencing.Key cell populations and differentially expressed genes across groups were identified,followed by PPI network,GO,and KEGG enrichment analysis.Results Behavioral experiments indicated that CUMS successfully induced depressive symptoms in mice,while hyperforin im-proved depressive behavior.In the depression model group,the proportion of brain perivascular macrophages(PVM)increased,and this proportion decreased after hyperforin intervention,approaching the level seen in the control group.The top 20 common differentially ex-pressed genes in the PVM subpopulation were Saa3,Hbb-bs and Ccl24.PPI network analysis identified core targets,including Ccl2,Dhx9,C3,Msr1,Cxcl2 and Cx3cr1.KEGG enrichment analysis revealed pathways related to chemokines,phagosome formation,and inosi-tol phosphate metabolism.Conclusion The antide-pressant mechanism of hyperforin may be related to the regulation of Ccl24 and its related chemokine signaling pathway by PVM.

Objective To evaluate the effects of transcatheter aortic valve replacement(TAVR)on left ventricular reverse remodeling(LVRR)and outcomes in patients with mixed aortic valve disease(MAVD)and predominant aortic stenosis(AS).Methods Patients undergoing TAVR at our center between January 2020 and December 2022 were enrolled consecutively.Propensity score matching(PSM)(1∶1 ratio)was used to reduce selection bias.Transthoracic echocardiography(TTE)was used to monitor left ventricular ejection fraction(LVEF)and other structural parameters over time.The study outcome was a composite of cardiovascular death and rehospitalization due to cardiovascular causes.Linear mixed-effects models and logistic regression were utilized for comparing echocardiographic changes across groups and identifying independent risk factors for no-LVRR,respectively.Results After PSM,126 patients were included.MAVD group exhibited larger structural parameters(left ventricular end-systolic/end-diastolic diameter and volume,left ventricular mass index)and a lower left ventricular ejection fraction(LVEF)(all P＜0.05).However,more pronounced improvements in left ventricular structure and hemodynamics were observed during follow-up.Multivariate logistic regression analysis indicated that the left ventricular mass index(LVMI)was an independent predictor of left ventricular reverse remodeling(LVRR)after TAVR,whereas persistent moderate or greater mitral regurgitation(MR)and paravalvular leak(PVL)significantly reduced the incidence of LVRR.During a median follow-up period of 23 months,a total of 31 endpoint events occurred,and there was no statistically significant difference in long-term prognosis between the two groups(Log-rank P=0.330).Conclusions Compared to patients in the AS group,those in the MAVD group exhibited more severe left ventricular remodeling before TAVR.However,more significant LVRR was observed during postoperative follow-up.Additionally,the long-term prognosis was comparable between the two groups.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]