ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

arcopenia is a systemic skeletal muscle disorder characterized by a decrease in skeletal muscle mass and progressive decline in function， with multiple signaling pathways involved in its occurrence and development. Among them， the AMP-activated protein kinase （AMPK） signaling pathway， as a key pathway regulating cellular energy homeostasis， plays an important role in the regulation of skeletal muscle metabolism and functional maintenance by improving abnormalities in glucose and lipid metabolism， balancing skeletal muscle protein synthesis and degradation， improving mitochondrial function， promoting autophagy， and inhibiting inflammatory responses and oxidative stress. This article reviews the research progress on how various traditional Chinese medicine （TCM） monomers， including polyphenols， flavonoids， and terpenoids； various traditional Chinese medicine extracts， such as those from Lycium barbarum ， Asini Corii Colla， and Panax quinquefolium ， and TCM compounds， such as Guiqi zhuangjin decoction， Jianpi qiangji granules， and Qigu capsules， intervene in sarcopenia by regulating the AMPK signaling pathway to promote muscle protein synthesis， inhibit protein degradation， improve mitochondrial function， and alleviate inflammation and oxidative stress. Additionally， their molecular mechanisms are explored. The aim is to deeply elucidate the basis of TCM in the prevention and treatment of sarcopenia and to provide theoretical support for the development of related innovative drugs.

Background: and Purpose Live cell-based assays (LCBA) are increasingly used for serological antibody detection due to their ability to preserve antigen conformation, offering moderately higher sensitivity than fixed cell-based assays. However, the clinical necessity of prioritizing LCBA for the detection of aquaporin-4 immunoglobulin G (AQP4-IgG) in neuromyelitis optica spectrum disorder (NMOSD) remains unclear, especially when compared to its established role in diagnosing myelin oligodendrocyte glycoprotein antibody-associated disease. Methods: We compared the performance of live cell-based assays using immunofluorescence (LCBA-IF) and fixed cell-based assays using immunofluorescence (FCBA-IF) in detecting AQP4-IgG in 90 cases of NMOSD meeting 2015 International Panel for Neuromyelitis Optica Diagnosis criteria, alongside 40 controls. Additionally, we further investigated the relationship between AQP4-IgG titers as measured by LCBA-IF and FCBA-IF and clinical parameters in NMOSD patients. Results: Results showed 96.9% agreement between LCBA-IF and FCBA-IF (Cohen’s κ=0.935), with a strong Spearman correlation (0.977, p<0.001). Both methods demonstrated 100% specificity, with LCBA-IF showing slightly higher sensitivity compared to FCBA-IF. Within LCBAIF-tested groups, statistically significant differences in annualized relapse rates were observed across all pairwise comparisons (low-titer vs. moderate-titer, low-titer vs. high-titer, and moderate-titer vs. high-titer; all p<0.050). However, this association reached statistical significance in some FCBA-IF-tested groups. Conclusions Overall, there is a strong concordance between LCBA-IF and FCBA-IF in detecting AQP4-IgG, where LCBA-IF shows slightly higher sensitivity. Furthermore, there is a potential link between elevated AQP4-IgG titers and an increased risk of relapse, and this correlation may appear more pronounced when using LCBA-IF.

Objective This study aims to explore the diagnostic value of medical indicators in identifying diuretic resistance(DR)among patients with heart failure(HF)using machine learning methods such as Least Absolute Shrinkage and Selection Operator(LASSO)regression.An early recognition model for diuretic resistance in heart failure patients is constructed to provide clinicians with timely intervention opportunities and reduce hospitalization duration.Methods 267 heart failure patients from Tianjin Chest Hospital were included in the study.Standard urine output and DR status were employed as dependent factors,whereas 64 clinical indicators were gathered as independent variables.Depending on the kind of dependent variable,two modeling strategies were used.The first method used LASSO regression to fit the model,and 10-fold cross-validation was used to find the ideal regularization parameter.Standard urine output was used to predict diuretic resistance in the test set.Root mean square error(RMSE),coefficient of determination(R2),and classification accuracy were employed to assess the model's performance.In the second method,the most pertinent subset of features in relation to DR status was selected utilizing the max-relevance and min-redundancy(mRMR)algorithm.After that,three machine learning classifiers were used for classification:support vector machines(SVM),random forests(RF),and logistic regression(LR).Accuracy,precision,recall,area under the receiver operating characteristic curve(AUC),and F1-score were used to evaluate the model's performance.Results The optimal LASSO parameter was 0.0161.On the test set,the RMSE was 0.3489,the R2 was 0.7200,and the classification accuracy was 91.36%.The AUCs for mRMR+LR,mRMR+RF,and mRMR+SVM were 0.94,0.89,and 0.95,respectively.Their accuracies were 0.86,0.77,and 0.90;precisions were 0.87,0.80,and 0.90;recalls were 0.86,0.75,and 0.90;and F1-scores were 0.86,0.75,and 0.90,respectively.In the validation set,the LASSO regression model outperformed the other machine learning methods in predictive performance.Conclusion Diuretic resistance in heart failure patients was successfully detected by both the LASSO regression model and mRMR-based machine learning classifiers.The LASSO regression model performed better than the mRMR-based classifiers,providing more accurate scientific evidence for early clinical intervention.

Aim To explore the mechanism of Yangxin decoction in the treatment of chronic heart failure(CHF)based on network pharmacology and animal ex-periments.Methods The database was used to screen Yangxin decoction,a network of"drug-compo-nent-disease-target"was established,and the obtained targets were enriched and analyzed.The CHF model of rats was replicated by abdominal aortic ligation.After the administration,the general condition,body weight and heart weight of the rats were observed,and the he-modynamic changes,echocardiography indicators and left ventricular mass index were measured.HE staining was used to observe the morphological changes of myo-cardial tissue.Serum IL-1 β,IL-18,TNF-α and BNP were detected by ELISA.The expressions of NLRP3,caspase-1,ASC and NF-κB p65 proteinswere detected by Western blot.Results Enrichment analysis showed that the potential regulatory pathways of Yangx-in decoction in the treatment of CHF involved NOD-like signaling pathway,NF-κB signaling pathway,etc.The results of animal experiments showed that the body weight,left ventricular diastolic diameter and left ven-tricular systolic diameter of the rats in the administra-tion group decreased(P＜0.05),the left ventricular mass index,ejection fraction and short axis narrowing rate increased(P＜0.05),the pathological morphology of myocardial tissue was reduced,and the levels of IL-1 β,IL-18,TNF-α,BNP,NLRP3,caspase-1,ASC and NF-κB p65 decreased(P＜0.05).Conclusions The mechanism of Yangxin decoction in the treatment of CHF rats may be related to inhibiting the activation of NLRP3 inflammasome signaling pathway and reduc-ing the inflammatory response.

Aim To explore the compatibility and po-tential mechanism of effective components of Biejia-Ezhu against triple negative breast cancer(TNBC)and verify it by experiments.Methods Effective compo-nents and targets of Biejia-Ezhu were obtained by TC-MSP and Swiss Target Prediction.Disease targets of TNBC were obtained from OMMI and GeneCards data-bases.The PPI network was constructed using STRING database.GO and KEGG path enrichment analysis was performed using DAVID database.Cytoscape3.9.1 software was used to construct the"drug-component-target-disease"network,screen key targets and compo-nents for molecular docking,and further verify the com-patibility of key components and targets in vitro.Re-sults ① A total of 71 effective components were iden-tified in the Biejia-Ezhu drug pair.There were 146 drug targets associated with the disease.A total of 113 signaling pathways were identified by KEGG analysis.The 71 potential active components of Biejia-Ezhu mainly acted on key targets such as mTORC1,ULK1,TNF,EGFR,ESR1,STAT3,HIF1A,and PTGS2.Mo-lecular docking results showed that glycine and curcu-min were the key active components of Biejia-Ezhu,and both had strong docking activity against key target proteins mTORC1 and ULK1.②The results of in vitro experiment showed that glycine combined with curcu-min significantly inhibited the proliferation and clonal formation ability of TNBC cells(P＜0.05),up-regula-ted the expression of autophagy marker LC3 Ⅱ/Ⅰ,down-regulated the expression of EGFR,down-regula-ted the expression of pathway protein mTORC1,p-mTOR,p-ULK1,and promoted the expression of path-way protein ULK1(P＜0.05).Conclusion The key component of Biejia-Ezhu against triple-negative breast cancer is glycine-curcumin,the mechanism of which may be related to the regulation of the mTORC1/ULK1 signaling pathway to promote autophagy.

In recent years,organs-on-chips(OOCs)technology has gradually matured and been recognized by regulatory agencies,playing a key role in the construction of pathophysiological models,pharmacodynamic screening,toxicological evaluation and other fields,providing guidance for the research and development of innovative drugs of Chinese materia medica and the clinical application of classic prescriptions.This article reviewed the application progress of OOCs technology in the research of Chinese materia medica from four dimensions:pharmacodynamic and toxicological evaluation,quality control,active component analysis and innovative drug research and development,in order to provide a reference for the precise application of this technology in the field of Chinese materia medica.

Objective To construct a nomogram prediction model based on anti-cyclic citrullinated peptide antibody(anti-CCP an-tibody)and rheumatoid factor(RF)to predict the probability of cardiovascular disease(CVD)in patients with rheumatoid arthritis(RA).Methods A total of 437 RA patients admitted to Zhengzhou Central Hospital Affiliated to Zhengzhou University from January 2018 to February 2024 were selected as the study objects,the clinical data of the patients were collected,and they were divided into RA+CVD group(n=88)and RA group(n=349)according to the follow-up results.The risk factors of CVD in RA patients were screened by univariate and multivariate Logistic regression analysis,and the prediction model of CVD in RA patients was constructed and internally validated.Results Multivariate Logistic regression analysis showed that age,course of disease,uric acid,C-reactive protein,hyperten-sion and diabetes,anti-CCP antibody and RF were independent risk factors for CVD in RA patients(P＜0.05).The constructed mod-el was internally validated.The area under the area(AUC)of the training set and the validation set were 0.891(95％CI:0.851-0.930)and 0.867(95％CI:0.790-0.944).Conclusion The prediction model constructed in this paper has good predictive and dis-crimination ability,and has a high predictive value for whether RA patients are complicated with CVD.

Aim To explore the mechanism of Yangxin decoction in the treatment of chronic heart failure(CHF)based on network pharmacology and animal ex-periments.Methods The database was used to screen Yangxin decoction,a network of"drug-compo-nent-disease-target"was established,and the obtained targets were enriched and analyzed.The CHF model of rats was replicated by abdominal aortic ligation.After the administration,the general condition,body weight and heart weight of the rats were observed,and the he-modynamic changes,echocardiography indicators and left ventricular mass index were measured.HE staining was used to observe the morphological changes of myo-cardial tissue.Serum IL-1 β,IL-18,TNF-α and BNP were detected by ELISA.The expressions of NLRP3,caspase-1,ASC and NF-κB p65 proteinswere detected by Western blot.Results Enrichment analysis showed that the potential regulatory pathways of Yangx-in decoction in the treatment of CHF involved NOD-like signaling pathway,NF-κB signaling pathway,etc.The results of animal experiments showed that the body weight,left ventricular diastolic diameter and left ven-tricular systolic diameter of the rats in the administra-tion group decreased(P＜0.05),the left ventricular mass index,ejection fraction and short axis narrowing rate increased(P＜0.05),the pathological morphology of myocardial tissue was reduced,and the levels of IL-1 β,IL-18,TNF-α,BNP,NLRP3,caspase-1,ASC and NF-κB p65 decreased(P＜0.05).Conclusions The mechanism of Yangxin decoction in the treatment of CHF rats may be related to inhibiting the activation of NLRP3 inflammasome signaling pathway and reduc-ing the inflammatory response.

Aim To explore the compatibility and po-tential mechanism of effective components of Biejia-Ezhu against triple negative breast cancer(TNBC)and verify it by experiments.Methods Effective compo-nents and targets of Biejia-Ezhu were obtained by TC-MSP and Swiss Target Prediction.Disease targets of TNBC were obtained from OMMI and GeneCards data-bases.The PPI network was constructed using STRING database.GO and KEGG path enrichment analysis was performed using DAVID database.Cytoscape3.9.1 software was used to construct the"drug-component-target-disease"network,screen key targets and compo-nents for molecular docking,and further verify the com-patibility of key components and targets in vitro.Re-sults ① A total of 71 effective components were iden-tified in the Biejia-Ezhu drug pair.There were 146 drug targets associated with the disease.A total of 113 signaling pathways were identified by KEGG analysis.The 71 potential active components of Biejia-Ezhu mainly acted on key targets such as mTORC1,ULK1,TNF,EGFR,ESR1,STAT3,HIF1A,and PTGS2.Mo-lecular docking results showed that glycine and curcu-min were the key active components of Biejia-Ezhu,and both had strong docking activity against key target proteins mTORC1 and ULK1.②The results of in vitro experiment showed that glycine combined with curcu-min significantly inhibited the proliferation and clonal formation ability of TNBC cells(P＜0.05),up-regula-ted the expression of autophagy marker LC3 Ⅱ/Ⅰ,down-regulated the expression of EGFR,down-regula-ted the expression of pathway protein mTORC1,p-mTOR,p-ULK1,and promoted the expression of path-way protein ULK1(P＜0.05).Conclusion The key component of Biejia-Ezhu against triple-negative breast cancer is glycine-curcumin,the mechanism of which may be related to the regulation of the mTORC1/ULK1 signaling pathway to promote autophagy.