BACKGROUND: The American Heart Association (AHA) introduced the concept of cardiovascular-kidney-metabolic (CKM) health and stage, reflecting the interaction among metabolism, chronic kidney disease (CKD), and the cardiovascular system. However, the association between CKM stage and the long-term risk of cardiovascular disease (CVD) has not been validated. This study aimed to evaluate the long-term CVD risk associated with CKM health metrics and CKM stage using data from a population-based cohort study. METHODS: In total, 5293 CVD-free participants were followed up to around 13 years in the Chinese Multi-provincial Cohort Study (CMCS). Considering the pathophysiologic progression of CKM health metrics abnormalities (comprising obesity, central adiposity, prediabetes, diabetes, hypertriglyceridemia, CKD, and metabolic syndrome), participants were divided into CKM stages 0, 1, and 2. The time-dependent Cox regression models were used to estimate the cardiovascular risk associated with CKM health metrics and stage. Additionally, broader CVD outcomes were examined, with a specific assessment of the impact of stage 3 in 2581 participants from the CMCS-Beijing subcohort. RESULTS: Among participants, 91.2% (4825/5293) had at least one abnormal CKM health metric, 8.8% (468/5293), 13.3% (704/5293), and 77.9% (4121/5293) were in CKM stages 0, 1, and 2, respectively; and 710 incident CVD cases occurred during a median follow-up time of 13.3 years (interquartile range: 12.1 to 13.6 years). Participants with each poor CKM health metric exhibited significantly higher CVD risk. Compared with stage 0, the hazard ratio (HR) (95% confidence interval [CI]) for CVD incidence was 1.31 (0.84-2.04) in stage 1 and 2.27 (1.57-3.28) in stage 2. Significant interactive impacts existed between CKM stage and age or sex, with higher CVD risk related to increased CKM stages in participants aged <60 years or females. CONCLUSION These findings highlight the contribution of CKM health metrics and CKM stage to the long-term risk of CVD, suggesting the importance of multi-component recognition and management of poor CKM health in CVD prevention.
Humans ; Female ; Male ; Cardiovascular Diseases/etiology* ; Middle Aged ; Adult ; Cohort Studies ; Renal Insufficiency, Chronic/metabolism* ; Aged ; Risk Factors ; Metabolic Syndrome/metabolism* ; China ; East Asian People

The study investigated the intrinsic changes in material basis of Angelicae Sinensis Radix during wine processing by headspace-gas chromatography-ion mobility spectrometry(HS-GC-IMS), headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS), and ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS) combined with chemometrics. HS-GC-IMS fingerprints of Angelicae Sinensis Radix before and after wine processing were established to analyze the variation trends of volatile components and characterize volatile small-molecule substances before and after processing. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed for differentiation and difference analysis. A total of 89 volatile components in Angelicae Sinensis Radix were identified by HS-GC-IMS, including 14 unsaturated hydrocarbons, 16 aldehydes, 13 ketones, 9 alcohols, 16 esters, 6 organic acids, and 15 other compounds. HS-SPME-GC-MS detected 118 volatile components, comprising 42 unsaturated hydrocarbons, 11 aromatic compounds, 30 alcohols, 8 alkanes, 6 organic acids, 4 ketones, 7 aldehydes, 5 esters, and 5 other volatile compounds. UPLC-Q-Orbitrap-MS identified 76 non-volatile compounds. PCA revealed distinct clusters of raw and wine-processed Angelicae Sinensis Radix samples across the three detection methods. Both PCA and OPLS-DA effectively discriminated between the two groups, and 145 compounds(VIP>1) were identified as critical markers for evaluating processing quality, including 4-methyl-3-penten-2-one, ethyl 2-methylpentanoate, and 2,4-dimethyl-1,3-dioxolane detected by HS-GC-IMS, angelic acid, β-pinene, and germacrene B detected by HS-SPME-GC-MS, and L-tryptophan, licoricone, and angenomalin detected by UPLC-Q-Orbitrap-MS. In conclusion, the integration of the three detection methods with chemometrics elucidates the differences in the chemical material basis between raw and wine-processed Angelicae Sinensis Radix, providing a scientific foundation for understanding the processing mechanisms and clinical applications of wine-processed Angelicae Sinensis Radix.
Wine/analysis* ; Gas Chromatography-Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Angelica sinensis/chemistry* ; Solid Phase Microextraction/methods* ; Drugs, Chinese Herbal/isolation & purification* ; Chemometrics ; Volatile Organic Compounds/chemistry* ; Principal Component Analysis ; Ion Mobility Spectrometry/methods*

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent inflammation and joint damage, accompanied by the accumulation of plasma cells, which contributes to its pathogenesis. Understanding the genetic alterations occurring during plasma cell differentiation in RA can deepen our comprehension of its pathogenesis and guide the development of targeted therapeutic interventions. Here, our study elucidates the intricate molecular mechanisms underlying plasma cell differentiation by demonstrating that PRDX1 interacts with DOK3 and modulates its degradation by the autophagy-lysosome pathway. This interaction results in the inhibition of plasma cell differentiation, thereby alleviating the progression of collagen-induced arthritis. Additionally, our investigation identifies Salvianolic acid B (SAB) as a potent small molecular glue-like compound that enhances the interaction between PRDX1 and DOK3, consequently impeding the progression of collagen-induced arthritis by inhibiting plasma cell differentiation. Collectively, these findings underscore the therapeutic potential of developing chemical stabilizers for the PRDX1-DOK3 complex in suppressing plasma cell differentiation for RA treatment and establish a theoretical basis for targeting PRDX1-protein interactions as specific therapeutic targets in various diseases.

Objective To specifically extract and analyze nascent proteins synthesized by bone marrow mesenchymal stem cells(BMSCs)after transplantation into ischemic hearts using a technique employing mutant methionyl-tRNA synthetase(MetRSL247G)for nascent protein labeling,in order to explore the potential mechanisms of action in BMSCs post-transplantation.Methods Point mutation at position 274 of the MetRS gene in BMSCs was induced via lentiviral infection to enable azidonorleucine(ANL)-mediated labeling of nascent proteins in BMSCs.The labeling efficiency was verified by means of fluorescent non-canonical amino-acid tagging(FUNCAT).Thirty healthy female C57BL/6J mice(8-10 weeks old)were divided into control and experimental groups,with 15 mice in each group.The acute myocardial infarction model was constructed by ligating the left anterior descending coronary artery in experimental group,while control mice underwent only thoracotomy without coronary ligation.After modeling,both groups received intramyocardial injections of MetRSL247G-modified BMSCs(MetRSL247G-BMSCs)at 3 different sites in the peri-infarct ischemic region.Mice were intraperitoneally injected with ANL every 6 hours for 4 times on postoperative days 0,2,and 6(n=5 for each time point)respectively,euthanized 24 h after the last injection,and cardiac tissues were isolated.The newly synthesized and labeled proteins produced by BMSCs after transplantation into the myocardium of experimental and control groups were collected,using an enrichment technique for ANL-tagged proteins and liquid chromatography-tandem mass spectrometry(LC-MS)analysis.Gene ontology(GO)analysis,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis,protein-protein interaction(PPI)analysis,and heatmap visualization analysis were performed to identify differentially expressed proteins at the 3 time points and screen key pathways and genes.Results Under fluorescence microscopy,the MetRSL247G lentivirus-infected BMSCs were observed to be labelled with mCherry signals,confirming the successful construction of the MetRSL247G-BMSCs cell line.Green fluorescent signals were detected only in nascent proteins in culture medium containing both MetRSL247G-BMSCs and ANL,validating the sensitivity and specificity of the labeling method.GO analysis revealed that differentially expressed proteins were primarily involved in basic cellular biological processes such as extracellular exosome formation,extracellular matrix organization,and focal adhesion.KEGG and PPI analyses indicated that the differential proteins were mainly involved in complement and coagulation cascade pathway,actin cytoskeleton regulation pathway,and apoptosis pathway.Heatmap analysis showed significantly upregulated expression of anti-apoptosis and cell adhesion-related factors in experimental group on day 1(P＜0.05),upregulated anti-apoptotic factors,pro-apoptotic factors,and cell adhesion-related factors on day 3(P＜0.05),and upregulated anti-apoptotic factors,cell differentiation-related factors,and cell adhesion-related factors on day 7(P＜0.05)compared with control group.Expression of apoptosis-inducing factor 1 was significantly downregulated on days 1 and 7(P＜0.05).On day 3,most differentially expressed proteins,including anti-apoptosis factors(Protein S100-A11,Clusterin,Gelsolin),pro-apoptosis factor(Cathepsin B),cell differentiation-related factor(Transgelin-2),and cell adhesion-related factors(Cofilin-1,Periostin,Fibronectin)were significantly upregulated(P＜0.05).Conclusions The MetRSL247G mutation enables BMSCs to incorporate ANL and synthesize labeled proteins,confirming the feasibility of this nascent protein labeling technique.Nascent proteins of BMSCs in ischemic myocardium primarily contribute to extracellular exosome secretion and extracellular matrix organization.BMSCs may adapt to and respond to ischemic and hypoxic environments by influencing complement and coagulation cascades,activating inflammatory factors,regulating actin cytoskeleton structure,and modulating apoptosis,thereby maintaining the survival of BMSCs.

Objective To explore how to organically integrate the human anatomy curriculum with medical imaging,thereby enhancing medical students' spatial understanding and 3D reconstruction skills,and strengthening their anatomical foundation and clinical competence.This approach aims to bridge the gap between basic science and clinical practice while cultivating clinical thinking abilities.Methods In this study,the medical imaging knowledge was introduced into the anatomy curriculum in Peking University,enabling students to better understand the human body structure and its relationship to the clinical practice with aid of the ultrasound and MRI method.After the course concluded,we evaluated the examination result and learning satisfaction data from the anatomy course.Results The result showed that students provided positive feedback,showing increased interest in learning,enhanced initiative,significant improvement in their anatomy grades(P＜0.01),and a notable enhancement in their ability to apply basic knowledge to solve clinical problems(P＜0.05).Conclusion The integrated teaching approach of medical imaging and human anatomy courses provides innovative ideas and practical method for medical students to learn the basic medical course and enhance their clinical skills in the future.

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

OBJECTIVE: Circadian rhythm disruption (CRD) is a risk factor that correlates with poor prognosis across multiple tumor types, including hepatocellular carcinoma (HCC). However, its mechanism remains unclear. This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity. METHODS: To quantify CRD, the HCC CRD score (HCCcrds) was developed. Using machine learning algorithms, we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort (n = 369), and the robustness of this method was validated. Furthermore, we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes. RESULTS: We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis. The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis, higher pathological grade, and advanced clinical stages, while the CRD-related subtype with low HCCcrds had better clinical outcomes. We also identified novel biomarkers for each subtype, such as nicotinamide n-methyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1. CONCLUSION We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers. Within these groups greater HCCcrds was associated with worse prognosis. This approach has the potential to improve prediction of an individual's prognosis, guide precision treatments, and assist clinical decision making for HCC patients. Please cite this article as: Li XJ, Chang L, Mi Y, Zhang G, Zhu SS, Zhang YX, et al. Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm. J Integr Med. 2025; 23(4): 445-456.
Humans ; Carcinoma, Hepatocellular/pathology* ; Liver Neoplasms/pathology* ; Circadian Rhythm/genetics* ; Prognosis ; Male ; Female ; Biomarkers, Tumor/genetics* ; Middle Aged ; Machine Learning ; Computational Biology

OBJECTIVE: To investigate chronic hepatitis C virus (HCV) infection's effect on gestational liver function, pregnancy and delivery complications, and neonatal development. METHODS: A total of 157 HCV antibody-positive (anti-HCV[+]) and HCV RNA(+) patients (Group C) and 121 anti-HCV(+) and HCV RNA(-) patients (Group B) were included as study participants, while 142 anti-HCV(-) and HCV RNA(-) patients (Group A) were the control group. Data on biochemical indices during pregnancy, pregnancy complications, delivery-related information, and neonatal complications were also collected. RESULTS: Elevated alanine aminotransferase (ALT) rates in Group C during early, middle, and late pregnancy were 59.87%, 43.95%, and 42.04%, respectively-significantly higher than Groups B (26.45%, 15.70%, 10.74%) and A (23.94%, 19.01%, 6.34%) ( P < 0.05). Median ALT levels in Group C were significantly higher than in Groups A and B at all pregnancy stages ( P < 0.05). No significant differences were found in neonatal malformation rates across groups ( P > 0.05). However, neonatal jaundice incidence was significantly greater in Group C (75.16%) compared to Groups A (42.25%) and B (57.02%) ( χ ² = 33.552, P < 0.001). HCV RNA positivity during pregnancy was an independent risk factor for neonatal jaundice ( OR = 2.111, 95% CI 1.242-3.588, P = 0.006). CONCLUSIONS Chronic HCV infection can affect the liver function of pregnant women, but does not increase the pregnancy or delivery complication risks. HCV RNA(+) is an independent risk factor for neonatal jaundice.
Humans ; Female ; Pregnancy ; Adult ; Pregnancy Complications, Infectious/epidemiology* ; Retrospective Studies ; Pregnancy Outcome ; Infant, Newborn ; Viremia/virology* ; Hepatitis C ; Hepacivirus/physiology* ; Hepatitis C, Chronic/virology* ; Young Adult ; Alanine Transaminase/blood*

Objective To explore the construction and visualization for knowledge graph of Ling Shu(Spiritual Pivot),with a view to providing ideas for the structured storage and display of the theoretical knowledge of the ancient Chinese medical books.Methods Using the professional idea of constructing knowledge graphs for reference,text mining technology was applied to construct the thesaurus,and then word division,entity recognition,and relationship extraction for the original text of Ling Shu were performed to get the elements of knowledge graph construction.The graph database Neo4j was used for the storage and query of the knowledge graph,and then the visual display of the knowledge graph was achieved.Results The 1 216 high-quality words consisting of the thesaurus of Ling Shu were obtained,and the construction of the knowledge graph of the theory of Ling Shu was realized.The constructed knowledge graph basically displayed the traditional Chinese medicine theories such as the correlation of visceral manifestations with essence qi,and the relationship between emotions and the five-zang organs described in Ling Shu,which made the retrieval and utilization of the related entities and relationships possible,and provided ideas for the structured storage and display of the theoretical knowledge of the ancient books of Chinese medicine.Conclusion The knowledge graph construction technology can be used to obtain the Chinese medicine theoretical knowledge graph of Ling Shu,and to display the knowledge connections of yin-yang and the five elements,and the internal organs and meridians expressed in the Ling Shu.The construction of the knowledge graph and its storage in the graph database enable the knowledge graph involved in the text of Ling Shu to be displayed in the form of visualized semantic network graph,and also make the embedding of other search systems such as the semantic search and semantic wiki possible,which will be helpful for the development of Chinese medicine intelligent medical services.

Objective:To investigate the prognostic factors for liver transplantation for hepatocellular carcinoma beyond UCSF criteria but without macrovascular invasion.Methods:A retrospective analysis was performed for the clinical data of the hepatocellular carcinoma patients without macrovascular invasion beyond UCSF criteria who underwent liver transplantation at our center from Jan 2018 to Jun 2023. The receiver operating characteristic curve analysis was performed to assess the predictive power of potential prognosis factors.Results:With this criteria, the 1-, 3-year overall survival rates were 94.1% and 75.0%, respectively, and the 1-, 3-year tumor free survival rates were 82.4% and 38.1%, respectively. The maximum tumor size, number of tumors, AFP, PIVKA-Ⅱ before transplantation, and whether undergo pretransplant down-stage therapy were significant prognostic factors ( P<0.05). Combining the above prognostic factors to construct the receiver operating characteristic curve yielded an area under the curve of 0.967, with a sensitivity and specificity of 0.932, 0.952, respectively. Further, the differentiation, MVI and Ki-67 were significant prognostic factors ( P<0.05). Combining pathological factors to construct the receiver operating characteristic curve yielded an area under the curve of 0.927, with a sensitivity and specificity of 0.769, 1, respectively. Conclusion:The maximum tumor diameter, number of tumors, AFP, PIVKA-Ⅱ before transplantation, and pretransplant down-stage therapy and tumor differentiation, MVI and Ki-67 are all prognostic factors of liver transplantation for hepatocellular carcinoma without macrovascular invasion beyond UCSF criteria.